# ULTRASAT: A wide-field time-domain UV space telescope

Y. Shvartzvald  Department of Particle Physics and Astrophysics, Weizmann
Institute of Science, Rehovot 7610001, Israel  E. Waxman  Department of
Particle Physics and Astrophysics, Weizmann Institute of Science, Rehovot
7610001, Israel  A. Gal-Yam  Department of Particle Physics and Astrophysics,
Weizmann Institute of Science, Rehovot 7610001, Israel  E. O. Ofek  Department
of Particle Physics and Astrophysics, Weizmann Institute of Science, Rehovot
7610001, Israel  S. Ben-Ami  Department of Particle Physics and Astrophysics,
Weizmann Institute of Science, Rehovot 7610001, Israel  D. Berge  Deutsches
Elektronen Synchrotron DESY, Platanenallee 6, 15738 Zeuthen, Germany  Institut
fur Physik, Humboldt-Universität zu Berlin, D-12489 Berlin, Germany  M.
Kowalski  Deutsches Elektronen Synchrotron DESY, Platanenallee 6, 15738
Zeuthen, Germany  Institut fur Physik, Humboldt-Universität zu Berlin, D-12489
Berlin, Germany  R. Bühler  Deutsches Elektronen Synchrotron DESY,
Platanenallee 6, 15738 Zeuthen, Germany  S. Worm  Deutsches Elektronen
Synchrotron DESY, Platanenallee 6, 15738 Zeuthen, Germany  J. E. Rhoads  NASA
Goddard Space Flight Center, Greenbelt, MD 20771, USA  I. Arcavi School of
Physics and Astronomy, Tel-Aviv University, Tel-Aviv 69978, Israel  CIFAR
Azrieli Global Scholars program, CIFAR, Toronto, Canada  D. Maoz  School of
Physics and Astronomy, Tel-Aviv University, Tel-Aviv 69978, Israel  D.
Polishook  Faculty of Physics, Weizmann Institute of Science, Rehovot 7610001,
Israel  N. Stone  Racah Institute of Physics, The Hebrew University of
Jerusalem, Jerusalem 91904, Israel  B. Trakhtenbrot School of Physics and
Astronomy, Tel-Aviv University, Tel-Aviv 69978, Israel  M. Ackermann
Deutsches Elektronen Synchrotron DESY, Platanenallee 6, 15738 Zeuthen, Germany
O. Aharonson  Helen Kimmel Center for Planetary Science, Weizmann Institute of
Science, Rehovot, Israel  Planetary Science Institute, Tucson, Arizona, USA
O. Birnholtz  Department of Physics, Bar-Ilan University Ramat-Gan 52900,
Israel  D. Chelouche  Department of Physics, Faculty of Natural Sciences,
University of Haifa, Haifa 3498838, Israel  Haifa Research Center for
Theoretical Physics and Astrophysics, University of Haifa, Haifa 3498838,
Israel  D. Guetta  Department of Physics, Ariel University, Ariel, IL-40700,
Israel  N. Hallakoun  Department of Particle Physics and Astrophysics,
Weizmann Institute of Science, Rehovot 7610001, Israel  A. Horesh  Racah
Institute of Physics, The Hebrew University of Jerusalem, Jerusalem 91904,
Israel  D. Kushnir  Department of Particle Physics and Astrophysics, Weizmann
Institute of Science, Rehovot 7610001, Israel  T. Mazeh  School of Physics and
Astronomy, Tel-Aviv University, Tel-Aviv 69978, Israel  J. Nordin  Institut
fur Physik, Humboldt-Universität zu Berlin, D-12489 Berlin, Germany  A. Ofir
Helen Kimmel Center for Planetary Science, Weizmann Institute of Science,
Rehovot, Israel  S. Ohm  Deutsches Elektronen Synchrotron DESY, Platanenallee
6, 15738 Zeuthen, Germany  D. Parsons  Deutsches Elektronen Synchrotron DESY,
Platanenallee 6, 15738 Zeuthen, Germany  A. Pe’er  Department of Physics, Bar-
Ilan University Ramat-Gan 52900, Israel  H. B. Perets  Physics Department,
Technion—Israel Institute of Technology, Technion City, Haifa 3200002, Israel
Department of Natural Sciences, The Open University of Israel, 1 University
Road, PO Box 808, Raanana 4353701, Israel  V. Perdelwitz  Helen Kimmel Center
for Planetary Science, Weizmann Institute of Science, Rehovot, Israel  D.
Poznanski  School of Physics and Astronomy, Tel-Aviv University, Tel-Aviv
69978, Israel  I. Sadeh  Deutsches Elektronen Synchrotron DESY, Platanenallee
6, 15738 Zeuthen, Germany  I. Sagiv  ElOp - Elbit Systems Ltd., Rehovot,
Israel  S. Shahaf  Department of Particle Physics and Astrophysics, Weizmann
Institute of Science, Rehovot 7610001, Israel  M. Soumagnac  Department of
Physics, Bar-Ilan University Ramat-Gan 52900, Israel  L. Tal-Or  Department of
Physics, Ariel University, Ariel, IL-40700, Israel  Astrophysics Geophysics
And Space Science Research Center, Ariel University, Ariel 40700, Israel  J.
Van Santen  Deutsches Elektronen Synchrotron DESY, Platanenallee 6, 15738
Zeuthen, Germany  B. Zackay  Department of Particle Physics and Astrophysics,
Weizmann Institute of Science, Rehovot 7610001, Israel  O. Guttman  Department
of Particle Physics and Astrophysics, Weizmann Institute of Science, Rehovot
7610001, Israel  P. Rekhi  Department of Particle Physics and Astrophysics,
Weizmann Institute of Science, Rehovot 7610001, Israel  A. Townsend  Institut
fur Physik, Humboldt-Universität zu Berlin, D-12489 Berlin, Germany  A.
Weinstein  Tufts University, Medford, MA 02155, USA  I. Wold  NASA Goddard
Space Flight Center, Greenbelt, MD 20771, USA Yossi Shvartzvald
<EMAIL_ADDRESS>
###### Abstract

The Ultraviolet Transient Astronomy Satellite (ULTRASAT) is scheduled to be
launched to geostationary orbit in 2026. It will carry a telescope with an
unprecedentedly large field of view (204 deg2) and NUV (230-290nm) sensitivity
(22.5 mag, 5$\sigma$, at 900s). ULTRASAT will conduct the first wide-field
survey of transient and variable NUV sources and will revolutionize our
ability to study the hot transient universe: It will explore a new parameter
space in energy and time-scale (months long light-curves with minutes
cadence), with an extra-Galactic volume accessible for the discovery of
transient sources that is $>$300 times larger than that of GALEX and
comparable to that of LSST. ULTRASAT data will be transmitted to the ground in
real-time, and transient alerts will be distributed to the community in $<$15
min, enabling a vigorous ground-based follow-up of ULTRASAT sources. ULTRASAT
will also provide an all-sky NUV image to $>$23.5 AB mag, over 10 times deeper
than the GALEX map.

Two key science goals of ULTRASAT are the study of mergers of binaries
involving neutron stars, and supernovae: With a large fraction ($>$50%) of the
sky instantaneously accessible, fast (minutes) slewing capability and a field-
of-view that covers the error ellipses expected from GW detectors beyond 2025,
ULTRASAT will rapidly detect the electromagnetic emission following BNS/NS-BH
mergers identified by GW detectors, and will provide continuous NUV light-
curves of the events; ULTRASAT will provide early (hour) detection and
continuous high (minutes) cadence NUV light curves for hundreds of core-
collapse supernovae, including for rarer supernova progenitor types.

##  1 Introduction

Time domain surveys are a developing focus of astronomy with an unusual
discovery potential. There are three main reasons for this. First, the static
sky has already been well imaged in most electromagnetic bands. Second, new
technology enables efficient monitoring of large swaths of sky. Finally, some
of the most exciting frontiers, particularly those related to cosmic
cataclysms, require wide-field synoptic surveys. It is therefore not
surprising that large powerful surveys across the electromagnetic spectrum
(e.g., SKA, VRO, ZTF, eROSITA, Euclid, Roman), are at the focus of attention
by the global community. However, a key piece, the UV, is missing from this
synoptic suite.

The UV band is unique in its ability to probe the physics of hot sources
(Sagiv et al., 2014; Kulkarni et al., 2021). Many of the interesting and
exotic astrophysical sources shine brightly in the UV, and explosive
transients are initially hot, so UV can provide the earliest notification.
Thus, even a modest UV time-domain explorer has a vast discovery potential,
and can uncover evidence to solve many open questions.

Figure 1: The volume of the universe per unit time (grasp; Ofek & Ben-Ami
2020a) accessible to several past, current and future sky surveys (VRO/LSST,
Ivezić et al. 2019; LAST, Ofek et al. in prep.; ZTF, Bellm et al. 2019; ATLAS,
Heinze et al. 2018; Pan-STARRS, Chambers et al. 2016; KMTNet, Kim et al. 2016;
TESS, Ricker et al. 2015; Black-GEM, Bloemen et al. 2015; MASTER, Gorbovskoy
et al. 2013; GOTO, Steeghs et al. 2022; GALEX, Martin et al. 2005), as a
function of wavelength (normalized such that ULTRASAT’s grasp is 1). The grasp
is given for a 20,000 K black-body source spectrum (e.g., a hot transient).
ULTRASAT’s grasp is an order of magnitude larger than that of current surveys,
two orders of magnitudes larger than that of GALEX, the largest grasp UV
mission to date, and comparable to that of LSST, the largest grasp optical
survey under construction.

ULTRASAT is a UV space telescope that will undertake the first wide-field UV
time-domain survey, and is planned to be launched to its geostationary (GEO)
orbit in 2026. Its main properties are given in Table 1. The celestial volume
accessible for transient detection by a survey, and hence the number of extra-
galactic objects detected per unit time, are proportional to the survey’s
grasp $G\propto\Omega S_{m}^{-3/2}$, where $\Omega$ is the field of view (FoV)
and $S_{m}$ is the minimum detectable flux (Ofek & Ben-Ami, 2020a). Fig. 1
shows a comparison of the grasp for hot transients of ULTRASAT with that of
other surveys. ULTRASAT’s grasp is much larger than that of existing optical
surveys, comparable to that of the Vera Rubin Observatory (VRO), which is
planned to begin operation in 2024, and over 300 times that of GALEX, which
had a similar sensitivity but a much smaller FoV. The large grasp, continuous
cadence and fast slew rate enable early detection of transients by ULTRASAT at
a rate that is much larger than that of existing and planned surveys, as
demonstrated in fig. 2. In addition to its large grasp, ULTRASAT is unique in
its energy and time windows. It will provide continuous months-long UV light
curves with minutes cadence, as well as early alerts that will enable rapid
ground- and space- based followup of transients. Historically, such great
leaps in capability have led to marvelous discoveries – a major incentive for
ULTRASAT.

Table 1:  ULTRASAT Key Properties  Property | Value | Comments
---|---|---
Spacecraft parameters
| Orbit | GEO |
| Real-time download of data | Continuous |
| Slew rate |  $>30^{\circ}/$min |
| Transient alert after observation end |  $<15$ min | For both survey and ToO modes
| Sky accessibility at any given moment | $>50\%$ | See Figure 3
| Observation start after ToO trigger |  $<15$ min | At any visible position
Payload parameters
| Aperture | 33 cm |
| Total FoV | 204 deg2 | Covered by four 7.14 deg x 7.14 deg sensors
| Pixel scale | 5.4 ″/pix | Total of 89.9M pixels
| Operation waveband | 230-290 nm | See Figure 4
| Mean throughput in operation waveband | 0.25 | See Figure 4
| Out of Band Rejection ($>300$ nm) | $2.9\times 10^{-5}$ | See Figure 4
| Mean effective FWHMa | 8.3″ | See Figure 5
| Mean limiting magnitudea (in 900 s, 5$\sigma$) | 22.5 AB mag | See Figure 6
a In central 170 deg2 of FoV, for a $T=20,000$ K blackbody source. |
Assuming the conservative background values as in Table 3. |

Figure 2: The number per year of supernova (SN) transients and EM transients
following binary neutron star (BNS) mergers, expected to be detected at early
time (as indicated in the plot) by ULTRASAT (assuming the limiting magnitude
for $3\times 300$ s exposures), the Vera Rubin Observatory (LSST), ZTF (Law et
al., 2009) and LAST (Ofek & Ben-Ami, 2020b). The blue/green/orange parts of
the SN bars correspond to RSG/BSG/WR progenitors respectively. The SN rates
are taken from Ganot et al. (2016), based on simulations calibrated to
GALEX/PTF observations. The BNS rates were obtained assuming 12 GW detections
per year out to 300Mpc, with UV flux similar to that observed following GW
170817.

While ULTRASAT is expected to revolutionize the study of a wide range of
transients (see § 5 and Table 2), the mission design is set by two key science
goals of fundamental importance – the study of the mergers of binaries
involving neutron stars (binary neutron stars, BNS, or neutron star-black
hole, NS-BH, binaries; see § 5.1) and the study of supernovae (SNe; see §
5.2). Measuring the electromagnetic (EM) emission following BNS/NS-BH mergers
will (i) provide direct constraints on the structure and composition of the
ejected material, thus providing unique diagnostics of the properties of
matter at nuclear density and of the merger dynamics; (ii) enable to determine
whether mergers are the sources of r-process elements and gamma-ray bursts;
and (iii) allow to determine the location in, and properties of, the host
galaxy, thus revealing the stellar antecedents of the binary systems.
Measuring the early shock breakout/cooling part of SN light curves will
provide unique information on the progenitor star and its pre-explosion
evolution, in particular mapping the different types of SNe to the different
stellar progenitors, and hence also providing constraints on the explosion
mechanisms, which are not fully understood.

Table 2:  ULTRASAT Science Highlights  Source Type | # Events per | Science Impact
---|---|---
| 3 yr mission |
Supernovae
| Shock break-out and | $>40$ | Understand the explosive death
| Early (shock cooling) of core collapse SNe | $>500$ | of massive stars
| Superluminous SNe | $>250$ | Early evolution, shock cooling emission
| Type Ia SNe | $>1000$ | Discriminate between SD and DD progenitors, dust reddening
Compact Object Transients
| Emission from Gravitational Wave events: | $\sim 25$ | Constrain the physics of the sources of
| NS-NS and NS-BH |  | gravitational waves
| Tidal disruption events |  $>300$ (high-cadence) | Accretion physics, black hole demographics
|  |  $>4500$ (low-cadence) |
Quasars and Active Galactic Nuclei
| Continuous UV lightcurves | $>7500$ | Accretion physics, BLR reverberation mapping, lensed quasars
| AGN-related flares & transients | $>100$ | Accretion physics
Stars & Exoplanets
| Active & Flaring stars | $>4\times 10^{5}$ | Planet habitability, high-energy flare frequency,
|  |  | stellar magnetic structure, gyrochronology, magnetospheres
| White dwarfs | $>3\times 10^{4}$ | Planetary systems, debris accretion, rotation-related variability
| RR Lyrae | $>1000$ | Pulsation physics
| Nonradial hot pulsators, e.g., $\alpha$ Cyg, | $>250$ | Asteroseismology
|  $\delta$ Scuti, SX Phe, $\beta$ Cep types |  |
| Eclipsing binaries | $>400$ | Chromosphere and eclipse mapping
Galaxies and Clusters
| All Sky Survey – galaxies | $>10^{8}$ | Galaxy Evolution, star formation rate
Gamma Ray Bursts
| GRBs occurring in-field | $\sim 30$ | Prompt emission & afterglow physics, dust reddening
| Orphan Afterglows | $>30$ | Fireball $\Gamma$ and opening angle distributions
Solar System
| Asteroids and other small bodies | $>10^{4}$ | Asteroid classification, origin

Rapid detection and continuous UV measurements of the EM emission following
BNS/NS-BH mergers identified by GW detectors set requirements for rapid
spacecraft slew capability, instantaneous access to a large fraction of the
sky, real-time communication, and a wide FoV. The early (hour) detection and
continuous measurements of UV light curves for hundreds of core-collapse
supernovae requires a high cadence and a large grasp. A wide FoV, with a
correspondingly lower sensitivity for a given grasp, is required in order to
obtain a lower characteristic distance, that will enable spectroscopic
followup of a large fraction of detected SNe.

In addition to the study of BNS/NS-BH mergers and SNe, ULTRASAT will provide
continuous NUV light curves for hundreds of tidal disruptions of stars by
super-massive black holes, thousands of active galactic nuclei, and $>10^{5}$
flaring and variable stars (See Table 2).

This paper is organized as follows. An overview of ULTRASAT’s system design
and expected performance is given in §2, a description of the currently
planned modes of operations of ULTRASAT is given in §3, and the Science
Operation Center (SOC) is described in §4. An overview of the mission science
objectives is given in §5. A short summary of the expected contributions of
ULTRASAT to the key science goals is given in §6.

##  2 Design and performance

Here we briefly describe the spacecraft, its payload, and performance.
ULTRASAT’s key performance characteristics are given in Table 1. The ULTRASAT
spacecraft will be constructed by the Israeli Aerospace Industry (IAI). It
will carry a single instrument - a wide field of view ($\cong 204$ deg2)
telescope constructed by Elbit/Elop, with a focal-plane array (hereafter
camera) constructed by Deutsches Elektronen-Synchrotron (DESY), including a
UV-optimized detector produced by TowerJazz and designed by AnalogValue.

ULTRASAT will be launched to a geostationary transfer orbit (GTO) and then
self-perform a GTO-GEO transfer to acquire its final Geosynchronous Earth
Orbit (GEO) position. It is planned for a minimum 3-year mission operation,
with sufficient propellant for a 6-year science mission. The mission lifetime
is limited by propellant availability for station keeping, and final
evacuation from its GEO position to the geostationary graveyard belt.

###  2.1 Spacecraft

The ULTRASAT spacecraft bus is constructed around two main components: the
ULTRASAT wide-field telescope, and the bi-propellant propulsion system. The
propellant mass contributes about half of ULTRASAT’s total launch mass of
$\sim$1,100 kg, and is required to enable the GTO-GEO maneuvers. The bus uses
high TRL components and is based on the successful IAI heritage series of
small satellites, benefiting from that company’s long-term experience in
fabricating and operating missions in both LEO and GEO. The spacecraft is
designed so that it can be attached as a hosted payload inside the launcher.

The spacecraft gimbaled high-gain antennas are designed to support ULTRASAT’s
data rate ($\sim$5Mbps), and together with the GEO orbit allow for continuous
real-time data download for all allowed pointings (see pointing restrictions
below). In case of a communication failure, images will be stored on the
ULTRASAT On-Board Recorder (OBR) and will be downloaded once the communication
is restored. The OBR can store images of nearly 8 days of continuous
observations with the nominal exposure time (300 s).

In order to enable a quick response to targets of opportunity (ToOs), ULTRASAT
is designed with full-hemispheric telecommand antennas and pointing slew
agility ($>0.5$ deg s-1), which enable starting observations at any visible
position in less than 15 min from an incoming alert trigger (e.g., of a GW
event) at the SOC. ULTRASAT’s power system (solar panels, battery) supports at
least 3 hours of ToO observations with negative power balance (in survey mode
the power balance is always positive, see Section 3.1). Assuming randomly
distributed ToO’s, negative power balance will occur for $\lesssim 33\%$ of
ToO observations.

The (angular sky) directions allowed for ToO observations are limited by
stray-light constraints. ULTRASAT is restricted to observe fields for which
the optical axis is $>70$ deg away from the Sun (this restriction also apply
during slewing), $>48$ deg from the Earth limb, and $>35$ deg from the Moon,
in order to limit the stray-light contribution to the background (see § 2.2
for a discussion of stray-light suppression). Under these restrictions,
ULTRASAT can access instantaneously (i.e. at any given moment) $>50\%$ of the
sky and observe $>42\%$ of the sky continuously for at least 3 hours (see
Figure 3). The fraction of the sky accessible to ULTRASAT within 3 (6) hours
is $>58\%$ ($>66\%$).

Figure 3: Sky availability for ToO observations under ULTRASAT pointing
restrictions. At any given time ULTRASAT can access $>50\%$ of the sky, and
$>58\%$ within 3 hrs. The minimal sky fraction for a 3-hr continuous
observation (the nominal ToO duration) is 42%, and the median is 51%.

Figure 4: Left: ULTRASAT’s total throughput, accounting for all optical
elements, the detector QE, and obscuration. The minor variation of the
throughput across the field of view (gray curves) is due to the variation of
the obscuration and of the angle-of-incidence distribution. Right: Color-color
relation between ULTRASAT and $Gaia$-bands, for a range of main-sequence
dwarfs (blue dots) and blackbody sources (red dots).

ULTRASAT’s pointing stability (”jitter”) of $<3\arcsec$ ($3\sigma$) over 300 s
(the nominal exposure time) is achieved using its attitude and orbit control
system (specifically, the star-trackers, reaction wheels, and inertial
measurement units). For blue sources at radial distance of $\sim 5$ deg off
the FOV center, the jitter contributes significantly to the image PSF, while
for blue sources at other locations in the FoV, and for red sources at any
location within the FoV, the jitter contribution is negligible (see § 2.2 and
Figure 5 for more details).

###  2.2 Payload

The ULTRASAT payload has three main components - a baffle, the optical tube
assembly (OTA; i.e. telescope) and the focal-plane array (FPA; aka camera).
Below we give a brief overview of each of them. Detailed description of the
baffle and the OTA is given in Ben-Ami et al. (2022), and in-depth description
of the camera design and characterization is given in Asif et al. (2021) and
Bastian-Querner et al. (2021), respectively.

ULTRASAT achieves its wide-field capabilities via a wide-field Schmidt
telescope design. A 33 cm diameter double corrector plate, made of a single
fused silica lens and a single CaF2 lens, is mounted at the entrance of the
telescope. The 50 cm diameter Zerodur mirror has a clear aperture of 48 cm. A
field-flattener assembly, made of a fused silica lens, a CaF2 lens and a
Sapphire filter, is mounted $\approx$0.55 mm in front of the focal-plane
array.

Achieving strong out-of-band attenuation, while maintaining high throughput
within the operation band, is crucial for meeting the signal-to-noise (S/N)
requirements. The payload design addresses the out-of-band attenuation by
minimizing the red leak through a combination of coatings on the sapphire
filter, the lenses, the mirror, and the detector. This leads to transmission
of only $2.9\times 10^{-5}$ (band average) of visible light while maintaining
$>25\%$ overall in-band throughput. The variation of obscuration and Angle-of-
Incidence (AOI) distribution across the FOV results in a minor radial
variation of the overall throughput (see Figure 4).

ULTRASAT’s optical design maximizes the system grasp via a chromatic radial-
dependent PSF optimized to the ULTRASAT band. Figure 5 gives the PSF full-
width at half maximum (FWHM; including spacecraft jitter, thermal variations
and assembly errors) for various sources at different radial positions. The
system area-averaged PSF FWHM for a $T=20,000$K blackbody source in the
central 170 deg2 of FoV is 8.3”.

Figure 5: ULTRASAT’s radial-dependent effective PSF FWHM for three
representative sources – $G$ and $M$ dwarfs, and a $T=20,000$K blackbody
source.

A 20∘ slanted baffle is mounted in front of the telescope to prevent stray
light from entering the telescope and to reduce Cerenkov radiation. The
slanted geometry enables the telescope to point $>70$ deg from the Sun without
allowing any Sunlight into the optical system. The baffle includes vanes to
suppress the stray light from the Earth and the Moon, achieving, together with
the OTA elements (in particular the Sapphire filter and the mirror), better
than $2\times 10^{-11}$ stray light suppression111Stray light suppression is
defined as the ratio between the scattered photon flux produced by a source
(e.g., Earth) on the detector and the source photon flux at geostationary
orbit.. The second main task of the baffle is to suppress the flux of high
energy electrons penetrating the outer corrector lens, reducing by a factor of
$\approx 10$ the Cerenkov radiation produced as these electrons propagate
through the lens, which is one of the two main noise sources (see § 2.3).

The FPA consists of four $45\times 45$ mm2 back-side illuminated (BSI) CMOS
detectors, with 9.5 $\mu$m pixels. The camera is shutter-less and is read in a
rolling-shutter mode, that allows continuous exposures with minimal overhead
time ($\sim 2$ milliseconds). The entire pixel array is read in less than 20
s. High Dynamic Range (HDR) capability is achieved by dual gain 5T pixels. The
high quantum efficiency (QE) in the ULTRASAT waveband is achieved via a high-K
dielectric layer and a UV-optimized anti-reflection coating (ARC). See Liran
et al. (2022) for more details on the development and characteristics of the
ULTRASAT customized sensor.

The FPA is mounted on a spider arm assembly within the telescope tube,
thermally isolating the FPA, that operates at 200 K to minimize dark current,
from the telescope structure, that is kept at 293 K. The instrumental camera
noise (e.g., dark current, read noise) contributes less than 30% to the total
background noise variance (see table 3).

###  2.3 Sensitivity

ULTRASAT’s sensitivity (e.g., limiting magnitude and other S/N calculations)
is affected by three types of noise sources – instrumental, external and
source related. ULTRASAT’s design addresses and minimizes each of these, and
specifically ensures that for the nominal observations the contribution of the
instrumental noises is sub-dominant. In this section we first describe the
contribution of each of the noise sources and then derive the limiting
magnitude and S/N for various astrophysical sources. These are used later, in
§ 5, to derive their estimated detection rates. The S/N is calculated using
publicly available tools (Ofek 2014; MAAT222https://github.com/EranOfek).

For the sensitivity calculations we assume conservative observing conditions
(see details below for each noise source) and a minimal observing visit per
pointing of $3\times 300$ s (the three exposures are required to reliably
identify and eliminate cosmic-ray signatures). The resulting contributions to
the background variance of the various noise sources for a single $300$ s
exposure are summarized in Table 3. The three external noise sources –
Zodiacal light, Cerenkov radiation, and stray light – dominate ULTRASAT’s
background noise. The variation across the FoV of these external noise sources
(due to the varying throughput) is negligible ($<0.1\%$).

Zodiacal light. ULTRASAT’s out-of-band ($\gtrsim 300$ nm) rejection suppresses
most of the Zodiacal light, mainly by the Sapphire filter. The Zodiacal light
varies with Ecliptic latitude and longitude, increasing for observations
closer to the Sun with a relatively sharp increase at angles $<90$ deg from
the Sun. ULTRASAT’s survey fields and the all-sky map observations (see § 3.1
and § 3.3) are planned to always be at $\geq 90$ deg away from the Sun. In our
conservative reference sensitivity we calculate the Zodiacal light for our
survey fields close to the Ecliptic poles, when they are in a direction
perpendicular to the Sun’s direction. We use the Zodiac spectrum from the HST
STIS instrument handbook333STIS instrument handbook, chapter 6.6, table 6.4. ,
and adjust for the Ecliptic coordinates using the table from the HST WFC3
instrument handbook444WFC3 instrument handbook, chapter 9.7.1, table 9.4. .
The resulting noise of 27 $e^{-}$ pix-1 per 300 s exposure is the highest
background noise.

Figure 6: Left: Limiting point source AB magnitude achieved in $3\times 300$ s ULTRASAT exposures, plotted as a function of radial distance from the field center. Right: ULTRASAT’s Signal-to-Noise Ratio (SNR) as a function of AB magnitude for $3\times 300$ s exposures, for $G$ and $M$ dwarfs at the FoV center and at $R=5^{\circ}$. The dots at the end of each curve mark the saturation limit.  Table 3: ULTRASAT estimated background noise in a single $300$ s exposure Source | Variance
---|---
| [$e^{-}$/pix]
Zodiac (perpendicular to Sun’s direction) | 27
Cerenkov (75 percentile high flux) | 15
Stray light (max) | 12
Dark current | 12
Readout noise [squared] | 6
Electronic cross-talk | 2
Gain | 1
Quantum yield | $<1$
Total | 75

Cerenkov emission. Trapped energetic electrons hitting the external fused-
silica corrector lens are the main source for the Cerenkov radiation
illuminating the detector. ULTRASAT’s baffle significantly reduces the flux of
electrons reaching the outer lens (dominated by the flux entering through the
baffle opening angle), and hence the resulting Cerenkov background. The
Cerenkov noise contribution was calculated using a detailed Monte-Carlo ray-
shooting simulation to estimate the energy dependent electron intensity
incident at various depths and radial positions across the outer lens. The
electron intensity distribution was then used to derive the resulting Cerenkov
emission at relevant angles (for which propagation through the optical system
leads to illumination of the detector). The numeric results are consistent
with those we obtained using a simplified analytic calculation (confirming in
particular that the contribution to the Cerenkov light from optical elements
other than the outer lens is negligible). The trapped electron flux at GEO
orbit is highly variable on timescales of days, with variations of 3-4 orders
of magnitude. For our conservative noise estimations we used the 75 percentile
of electron flux based on the AE9 model (Ginet et al., 2013). The resulting
Cerenkov noise contribution is about half of the Zodiacal. For the 95
percentile electron flux, the Cerenkov noise will be 2.8 times larger, while
for the median electron flux it will be 2.5 times smaller (thus already below
the instrumental noise). Our estimates of the Cerenkov contribution are
consistent with the results of Kruk et al. (2016), who studied the radiation-
induced background at GEO orbit and found that for exterior glasses (e.g., un-
shielded external lens) Zodiacal light dominates at $\gtrsim 300$ nm, while
Cerenkov radiation dominates at shorter wavelengths (see their Fig. 8).

Scattered light. Under our pointing restrictions (described above), scattered
light from Earth is the dominant stray light source. The baffle design (e.g.,
vanes and Acktar vacuum black coating) was optimized to suppress this
contribution. The Earth’s flux at GEO orbit was estimated based both on the
observations of the Sentinel 5P satellite (Veefkind et al., 2012), and on
calculations using the Solar irradiance and Earth’s albedo, with consistent
results between the two methods. The stray-light flux reaching the detector
was calculated by detailed Monte-Carlo simulations of light propagation
through the optical system. For our conservative noise estimations we assumed
full Earth at the closest allowed angle from the lowest side of the baffle.
The resulting stray light noise contribution is similar to (but slightly
smaller than) the Cerenkov noise.

Instrumental noise. ULTRASAT’s sensor was designed to minimize the
instrumental noise (Liran et al., 2022). The nominal sensor design performance
was already measured and verified. The sensors are kept at 200 K, yielding a
low dark current of $<0.05e^{-}$ s-1 pix-1. Long-term radiation effects (TID)
will lead to some increase in dark current, but the sensors are sufficiently
shielded so that the worst-case dark-current increase at the end of the
mission is expected to be less than a factor of 2. The read noise was measured
to be $<2.5e^{-}$ pix-1 (averaged over the PSF, taking into account also the
tail of high read noise pixels). The remaining instrumental noise sources –
electronic cross-talk, gain, and quantum yield – do not contribute
significantly to the overall noise.

Resulting sensitivity. ULTRASAT’s chromatic and radial-dependent PSF yields a
radial and source-dependent sensitivity. Figure 6 shows ULTRASAT’s radial-
dependent limiting AB magnitude (5$\sigma$ detection in 3 co-added $300$ s
images) for various point sources, and the S/N achieved with 3 co-added $300$
s images as a function of AB magnitude. For these calculations, we use either
the Pickles (1998) spectral flux library for stellar sources or a black-body
spectrum. The measured source flux is derived using ULTRASAT’s throughput
curve and by conservatively assuming 80$\%$ PSF photometry efficiency (i.e.,
20$\%$ source flux losses due to imperfect PSF representation and fitting).
The noise is calculated within an effective PSF, which is calculated by
applying the ULTRASAT chromatic and radial-dependent PSF to the source
spectrum propagated through ULTRASAT’s throughput. A faint 24 AB mag host
galaxy is assumed for the calculations, thus not dominating the background
noise in these estimates.

Confusing limit. ULTRASAT will observe some regions of the sky repeatedly for
a total of more than 100–$10^{4}$ hours (e.g., the high- and low-cadence
survey fields. See § 3.1). Crowding may become a major issue in deep co-added
images of these regions. In § 5.9 below, we carry a detailed analysis of the
confusion limits as a function of ULTRASAT PSF FWHM, as part of the estimates
for expected galaxy counts. The radial-dependent confusion limit in the
central 170 deg2 of FoV is in the range 24.0-25.5 AB mag (achieved by co-
addition of 200-400 images of $300$ s exposures) . See Figure 14 and § 5.9 for
more details.

##  3 Modes of Operation

ULTRASAT will have two main modes of operation: (i) Survey observations during
which the telescope stares at the same field (or cycle through a few adjacent
fields) for a long period of time, and (ii) Target of Opportunity (ToO)
observations, a triggered mode where ULTRASAT stops its survey observations
and slews to a new position. In addition, at the beginning of the mission an
all-sky UV map will be constructed.

During the survey mode, the extra-galactic survey volume will be maximized by
pointing ULTRASAT at fields near the ecliptic poles, minimizing Galactic
extinction, and switching between North and South in summer/winter, minimizing
Zodiacal background. Below we describe in some detail our current observing
plan, which is used in § 5 for the calculations related to observations
designed for meeting the science goals. This plan will be re-evaluated, and
potentially revised, before the beginning of the mission and annually during
the mission.

###  3.1 Survey modes

ULTRASAT will devote $\approx 90\%$ of its time during the first year to a
high cadence survey, and $\approx 10\%$ to a low cadence survey. In both
survey modes, the images will be transmitted to the ground in real-time.
ULTRASAT’s SOC will issue alerts of new transients detected by ULTRASAT within
15 min from image capture. Every 6 months, as the Sun switches hemispheres,
ULTRASAT will slew to the region in the opposite hemisphere. During each
semester ULTRASAT rotates about the center of the FoV by $\approx$1 deg every
$\approx$1 day to keep the Sun within $\approx$10 deg of the solar panels’
normal.

High cadence survey (21.25 hours/day): ULTRASAT will be pointed towards one
predetermined field near the ecliptic poles. The fields selection is based on
minimizing both the Zodiacal background and Galactic extinction, such that the
extra-galactic survey volume is maximized. Each field will be observed for six
months, with continuous 300 s exposures.

Low cadence survey (2.75 hours/day): During each seasonal (north/south) dwell
ULTRASAT will cycle through 40 fields covering $\sim$8000 deg2, observing 10
fields each day (i.e., a 4-day cadence per field). In this mode, ULTRASAT will
stare at a given field for 15min (3 consecutive 300 $s$ exposures), and then
move to observe a nearby field. The angular distance between adjacent fields
will be $<40$ deg and the slew time between adjacent fields will be $<1.5$
min. The survey fields will meet the Sun and Moon minimum angle limits during
the entire 6-month observing window.

###  3.2 Target of Opportunity (ToO)

Upon reception of a ToO trigger command, ULTRASAT will interrupt observations
and slew to the designated pointing. At any given moment, $>$50% of the sky
will be available for ToO observations (limited by the pointing restrictions
with respect to the Sun, Earth and Moon). ULTRASAT will slew to any observable
point on the sky within $<15$ min from the time a trigger was received at
ULTRASAT’s SOC. The interruption time per ToO is nominally capped at $<3$ hr.
ULTRASAT will observe the ToO field continuously with a nominal exposure time
of 300 s.

###  3.3 All-sky UV map

During the first six months of the mission, ULTRASAT will undertake an all-sky
survey of total integration of $6\times 300$ s (1800 s) at low Galactic
latitudes ($|b|<30$ deg) and $50\times 300$ s (15,000 s) at high Galactic
latitude ($|b|>30\deg$). The high latitude survey with an AB limiting
magnitude of 23.5 to 24 mag will be $>$10 times deeper than the GALEX all-sky
survey. Furthermore, it will provide an all-sky UV variability survey.

The All-sky UV map is required as a deep reference image for transient
detection using image subtraction. Specifically, following triggers of
gravitational wave events (see more details in § 5.1). The scheduling of the
all-sky map observations will be optimized with respect to the LIGO/VIRGO O5
run.

##  4 Science Operation Center

The ULTRASAT Science Operations Center (SOC) will be located at the Weizmann
Institute of Science (WIS) in Israel, and will support all scientific aspects
of the ULTRASAT mission, including observation planning, data reduction and
alerts distribution. The SOC interfaces with the Ground Control Segment (GCS)
at IAI, which is responsible for all direct communications with the ULTRASAT
spacecraft. The GCS will acquire the spacecraft after separation from the host
vehicle and maintain continuous communication through a ground antenna.

The SOC will plan and schedule in advance the survey and all-sky UV imaging
observations (see § 3). In addition, the SOC will receive real-time alerts
from several sources (mainly GW events; GRB, TDE, and neutrino triggers are
also under consideration). The SOC will send a new immediate ToO observing
plan to the GCS in cases where a ToO observation is both relevant (meeting
predefined criteria) and feasible (considering, e.g., target visibility and
spacecraft power condition). Observations will start within no more than 15
minutes from the time the incoming alert was received at the SOC.

The GCS will distribute the science and telemetry data to the SOC for real
time processing, calibration, and archiving. The ULTRASAT pipeline will
generate a large number of data products, the goal of which is to minimize the
time required to perform scientific research using the data. Focus is
therefore given to quality, diversity, and ease of use. The pipeline is based
on the software package described in Ofek (2014) and Ofek et al. (in prep).

The SOC will issue public alerts of new transients, for both survey and ToO
observations, within less than 15 minutes of image capture. All other ULTRASAT
data products will be made available via periodic data releases (DRs)
following full calibration and verification. The proprietary period will be 12
months. Members of the ULTRASAT collaboration and the science working groups
will have immediate access to all ULTRASAT data products.

##  5 Science Objectives

ULTRASAT will detect transient events in an unprecedented large volume of the
universe, and will explore a new parameter space in energy (NUV) and time-
scale (minutes to months). It is thus expected to have a major impact on a
wide range of astrophysics topics, with a vast space for serendipitous
discoveries. In this section we discuss ULTRASAT’s broad scientific impact
across the fields of GW sources (§ 5.1), deaths of massive stars (§ 5.2),
cosmology (§ 5.3), gamma-ray bursts (§ 5.4), stars and stellar remnants (§
5.5), exoplanets and star-planet connection (§ 5.6), tidal disruption events
(§ 5.7), active galactic nuclei (§ 5.8), galaxies (§ 5.9), and the Solar
system (§ 5.10). Table 2 summarizes ULTRASAT’s science highlights.

###  5.1 Search for UV Emission from Gravitational Wave (GW) Sources

The era of GW astrophysics has begun with the detection of GW from black-hole
(BH) and Neutron Star (NS) mergers by the laser interferometer observatories
LIGO and Virgo (Abbott et al., 2016a, 2017a). The possibilities are many and
exciting (Barack et al., 2019; Margutti & Chornock, 2021): New tests of
general relativity, a new probe of stellar death in binary evolution, and
determination of the demographics of stellar remnants. Coalescences involving
NS provide unique insights into the physics of our Universe: They are the most
likely sites of production of r-process elements (e.g., Pt, Au) (Fernández &
Metzger, 2016; Cowan et al., 2021) and provide unique diagnostics of the
physics of the densest matter in the Universe (Phinney, 2009).

The detection of the associated electro-magnetic (EM) emission will be the key
to using these events for addressing fundamental physics and astrophysics
questions: It will provide direct constraints on the structure of the ejected
material, which will in turn provide unique diagnostics of the properties of
matter at nuclear density and of the merger dynamics; It will enable us to
determine whether and which r-process elements are produced and whether highly
relativistic gamma-ray burst jets are produced; It will allow us to precisely
localize the mergers. Determining the location in, and properties of, the host
galaxy will reveal the stellar antecedents of NS binaries, and the host
redshift distribution can be used to measure cosmological parameters, in
particular H0.

By 2026, GW interferometer networks are expected to provide a few to a few
tens of detections of mergers involving NS per year within $\approx 300$ Mpc,
with angular localization of about $\sim 100$ deg2 (Abbott et al., 2016b,
2018, 2020). In this era, issues of GW alerts with rough parameter estimates
(NS-NS, NS-BH or BH-BH; rough sky position and distance) are expected within
minutes and with refined parameters within hours.

With a large fraction ($>50\%$) of the sky instantaneously accessible, fast
(minutes) slewing capability and a field-of-view that covers the error
ellipses expected from GW detectors beyond 2025, ULTRASAT will rapidly detect,
and provide continuous UV light-curves of, the EM emission following BNS
mergers identified by GW detectors. The alerts provided by ULTRASAT will
further enable early ground/space-based follow-up spectroscopy and monitoring
at other wavelengths.

In § 5.1.1 we show that the distance out to which the EM emission will be
detectable by ULTRASAT is expected to exceed the $\approx 300$ Mpc horizon of
the GW detectors. In § 5.1.2 we discuss ULTRASAT’s advantages, compared to the
capabilities of other surveys, in detecting EM emission following GW events.
In § 5.1.3 we discuss the unique constraints that will be provided by early
(hour time scale) light curves, in particular in the UV, on the structure and
composition of the merger ejecta.

####  5.1.1 Detecting UV emission following BNS mergers

Direct calculations of the structure and composition of the ejecta produced in
NS-NS/BH mergers are highly complicated and computationally demanding since
they involve a density range of over 30 decades, the entire periodic table,
sub-relativistic to relativistic flows, and require consideration of neutrino
transport, GR and magnetic field effects (Shibata & Hotokezaka, 2019; Radice
et al., 2020; Rosswog & Korobkin, 2022). Modeling the EM output is thus a
challenging but vibrant field (Fernández & Metzger, 2016; Nakar, 2020;
Margutti & Chornock, 2021).

Many models predict an UV signal, with a $10^{41}-10^{42}$ erg s-1 luminosity
lasting for hours to a day, that may be produced by different ejecta
components (see Fernández & Metzger (2016); Nakar (2020); Margutti & Chornock
(2021) for reviews, and recent analyses by Banerjee et al. (2020); Dean et al.
(2021); Hamidani & Ioka (2022); Banerjee et al. (2022); Combi & Siegel
(2022)): free neutron beta decay in high-velocity matter, high $Y_{e}$ ejecta
with lower r-process element content and opacity, hot low $Y_{e}$ ejecta, and
boosted relativistic material and/or shock cooling. These predicted signals
will be detectable by ULTRASAT out to $\approx 300$ Mpc.

The detection of EM emission following the nearby (40 Mpc) NS merger event GW
170817 lends strong support to the estimates of the expected UV signal, and
highlights the advantages of ULTRASAT as an EM counterpart detection machine.
The EM counterpart of GW 170817 (AT 2017gfo) was detected 10 hours following
the merger, with a luminosity of $10^{42}$ erg s-1 and a temperature exceeding
10,000 K. The absolute NUV magnitude of AT 2017gfo was about $-14.5$ at about
0.6 days after the merger. Furthermore, the NUV light curve was possibly
decaying between the two first epochs, indicating that the NUV peak luminosity
was earlier and brighter. Given these parameters, ULTRASAT can detect AT
2017gfo-like events to a distance of about 240 (400) Mpc, in 15 min (2 hr)
integrations. However, it is likely that the AT 2017gfo was brighter in NUV in
earlier times. In this case, ULTRASAT may detect these events to larger
distances.

####  5.1.2 ULTRASAT’s advantages in detecting EM emission following GW events

Major ground-based optical/IR (OIR) facilities will also react to GW events.
These facilities have the sensitivity to detect the optical emission, but have
much lower real-time sky accessibility ($\sim 6\%$ per location, given
day/night, horizon, moon, and weather effects).

The ground-based detection of EM emission 10 hours following GW 170817, by
targeting known galaxies in the GW source error volume, is an impressive
result. However, earlier detection would be crucial for obtaining spectra and
early light curves, which are essential for determining the properties of the
ejecta (see more below). Furthermore, although the GW angular localization is
expected to improve to 10-100 deg2 by 2026, EM transient identification will
remain challenging as the GW detection horizon is increased to $\approx 300$
Mpc, implying a larger error volume containing hundreds to thousands of
galaxies and fainter signals with a larger number of background transients
that would need to be classified.

Before the launch of ULTRASAT, several more GW events with exceptional
properties (dense ISM, a rare on-axis orientation) might have been localized
to their host galaxies. If so, the EM/GW frontier will be in early
localization and in constructing larger, unbiased samples and detailed study
of BNS mergers, for which ULTRASAT is ideally suited.

Finally, let us comment about EM searches in other bands. It is generally
accepted that GW events involving NS can produce short hard gamma-ray bursts.
So X-ray and $\gamma$-ray searches are clearly useful. However, there is sound
empirical evidence that the prompt high energy emission is strongly “beamed”
(conical emission). Only $\sim$1 in 100 events will be aimed towards us and
detectable at high energies, to distances larger than tens of Mpc. This is
well supported by the very weak X/$\gamma$-ray counterpart of GW 170817, that
would not have been detectable beyond 60 Mpc. The explosive energy of the
coalescence will also drive a strong shock in the ambient medium, from which
radio emission is expected to be detectable after months to years. The radio
channel is attractive because it is isotropic. However, the long delay
precludes key observational diagnostics for r-process elements – specifically
OIR spectroscopy on timescales of days to a week. This conclusion is also well
supported by the radio emission from GW 170817, that was detected with a two-
week time delay despite its proximity.

####  5.1.3 The importance of early UV measurements

Despite the extensive observations and study of the EM emission following the
nearby BNS merger GW 170817, large uncertainties remain regarding both the
structure and the composition of the ejecta.

[1] The observed UV-IR emission is consistent with the emission of radiation
from a mildly relativistic expanding ejecta, which is being continuously
heated by radioactive energy release at a rate corresponding to radioactive
elements heavier than the Iron group (e.g. Kasen et al. (2017); Drout et al.
(2017); Rosswog et al. (2018); Cowperthwaite et al. (2017); Tanaka et al.
(2017); Perego et al. (2017); Waxman et al. (2018)). This is remarkably
consistent with the ”kilonova” emission predicted to follow NS mergers
Fernández & Metzger (2016). However, the detailed properties of the ejecta,
which are inferred from observations, are inconsistent with those obtained in
merger simulations (see Nedora et al. (2021) for a recent detailed
discussion). In particular, the mass of the ejecta is larger than obtained in
simulations, and it is difficult to explain (e.g. Waxman et al. (2018);
Metzger et al. (2018); Fujibayashi et al. (2018)) the existence of a fairly
massive, $\simeq 0.05M_{\odot}$, fast, $v\sim 0.3c$, component with low
opacity corresponding to a large initial electron fraction $Y_{e}$ and a low
Lanthanide mass fraction $X_{\rm Ln}$, that is inferred from the early UV/blue
emission (Waxman et al., 2018). Alternative models have thus been proposed, in
which the blue emission is produced by boosted relativistic material and/or
shock cooling of an expanding mildly relativistic shell (e.g. Kasliwal et al.
(2017); Piro & Kollmeier (2018); Gottlieb et al. (2018)).

[2] The abundances of elements produced in GW 170817 is not yet clear. The
blue to red evolution of the emission may be explained by the existence of
several ejecta components characterized by largely differing compositions,
with higher opacity components corresponding to $X_{\rm Ln}\approx 10^{-1.5}$
dominating at later times (Kasen et al., 2017; Drout et al., 2017; Rosswog et
al., 2018; Cowperthwaite et al., 2017; Tanaka et al., 2017; Perego et al.,
2017). We have shown (Waxman et al., 2018) (see also Smartt et al. (2017))
that an alternative explanation is possible, in which the entire ejecta is
composed of low opacity material corresponding to $X_{\rm Ln}\approx 10^{-3}$,
spanning a wider velocity distribution than previously assumed. Inferences of
composition based on spectral analyses (e.g. Pognan et al. (2022); Hotokezaka
et al. (2021, 2022); Watson et al. (2019); Perego et al. (2022); Gillanders et
al. (2022); Domoto et al. (2022)) are challenged by the partial atomic data
(opacities, excitation/ionization cross sections) available for heavy
elements, and by the large density of lines of such elements combined with
relativistic expansion velocity. Watson et al. (2019); Perego et al. (2022);
Gillanders et al. (2022) find that features in the early ($\sim 1$ d) spectra
may be explained as due to first peak $r$-process elements (Sr & Zr) with low
$X_{\rm Ln}$ ($<5\times 10^{-3}$ Gillanders et al. (2022)), while $X_{\rm Ln}$
values inferred from (the large IR opacity implied by) later spectra differ
widely between different analyses (Waxman et al., 2018; Gillanders et al.,
2022; Domoto et al., 2022).

Different models for the structure and composition of the ejecta differ in
their predictions for the early, hour time scale emission, in particular in
the UV. Earlier detection of the EM transients and early UV light curves will
therefore be highly useful for discriminating between these models (e.g.
Arcavi (2018); Banerjee et al. (2020); Dean et al. (2021); Hamidani & Ioka
(2022); Banerjee et al. (2022); Combi & Siegel (2022); Dorsman et al. (2022);
Werner et al. (2022)).

###  5.2 Characterizing the Death of Massive Stars

Most stars of $>8M_{\odot}$ end their lives in supernova (SN) explosions,
which create and distribute the majority of the heavy elements (e.g., Woosley
et al., 2002). The explosion mechanisms are a subject of vigorous research.
Theoretical models begin with initial conditions – the assumed structure of a
model star – and attempt to predict the properties of the resulting explosion.
Progress thus requires assembly of a data set connecting observations of pre-
explosion stars with measured explosion properties. Such observational
constraints are critical, but exceedingly scarce – few SNe have an identified
progenitor visible in pre-explosion imaging (e.g., Smartt, 2015), and few more
are likely to be found in the foreseeable future, due to the low rate of such
events in very nearby galaxies where individual stars can be observed.
Charting the fate of the diverse populations of massive stars to specific
explosive outcomes is important in order to elucidate the feedback of massive
stars on their gaseous environments, and their role in galaxy evolution.

Detection of SNe shortly after explosion and observations following the early
emission from such events will enable dramatic advances in our understanding
of the way massive stars evolve shortly prior to explosion, the connection
between the properties of the progenitor stars and the resulting explosions,
and the physics of the explosive process.

The earliest emission of radiation from a SN explosion is associated with
“shock breakout” (e.g., Waxman & Katz, 2017; Levinson & Nakar, 2020). As the
radiation mediated shock (RMS) that drives the ejection of the SN envelope
expands outwards, the optical depth of the material lying ahead of it
decreases. When the optical depth drops to $\sim c/v_{shock}$ where
$v_{shock}$ is the shock velocity, radiation escapes and the shock dissolves.
Such breakout may take place once the shock reaches the edge of the star,
producing a bright, $10^{44}-10^{45}$ erg s-1, X-ray/UV flash lasting
typically over the progenitor light crossing time $R_{*}/c$ (seconds to a
fraction of an hour, depending on the radius of the exploding star $R_{*}$),
forming the first electromagnetic signal that can reach an external observer.

Alternatively, the breakout may take place at larger radii, within the circum-
stellar material (CSM) ejected from the progenitor star prior to the SN
explosion, e.g. by a steady stellar “wind” or by an episodic ejection of an
outer envelope shell, provided that the CSM optical depth is larger than
$c/v_{shock}$ (e.g., Ofek et al., 2010). In this case, the breakout time scale
may be extended from $\sim{\rm hour}$ to many days (e.g., Ofek et al., 2010).

Following the shock breakout flare, the hot ejecta cool and expand, emitting
UV/optical emission from the expanding envelope (the “shock cooling” phase),
with L$\sim 10^{43}$ erg s-1 on a day time scale.

####  5.2.1 Simple shock breakout observations

Due to the short duration of the breakout pulse, only a handful of cases have
been observed with an indication for a breakout signal (e.g., Campana et al.,
2006a; Soderberg et al., 2008; Gezari et al., 2008a, 2015; Schawinski et al.,
2008). ULTRASAT will change that.

For spherical stars with standard density profiles, and lacking dense CSM, the
duration of the shock breakout flare provides a direct measurement of the
stellar radius at explosion ($R_{*}/c$). This duration ranges from minutes to
about an hour for supergiant stars, making the ULTRASAT cadence uniquely
powerful to obtain such measurements.

However, the observed duration may be dominated by the intrinsic pulse
duration rather than by light travel time, $R_{*}/c$, as well as by
differences in the arrival time of the shock to the stellar surface at
different (angular) positions in strongly a-spherical explosions or
progenitors (Katz et al., 2012; Afsariardchi & Matzner, 2018). In such cases,
the breakout flare temporal structure provides instead a unique probe of the
pre-explosion inner structure of the progenitor star, that is mostly
inaccessible to other probes 555We note though that the $>R_{*}/c$ breakout
duration, obtained in the 3D calculation of a breakout from a convective red
supergiant envelope in (Goldberg et al., 2022), is dominated by the intrinsic
duration of the pulse (which is significantly longer than $R_{*}/c$ for the
chosen progenitor parameters), rather than by the convective density
inhomogeneities (Morag et al., 2022).

Though theoretical details of the shock breakout flares at very early times
($<1$ h) are still debated (see. e.g., Figure 1 of Ganot et al. 2016), the UV
shock-breakout emission must match smoothly to the well-understood, and
observed subsequent shock-cooling phase. The high temperature of the breakout
and shock-cooling implies that the UV and optical bands are in the Rayleigh-
Jeans regime. The decrease in flux due to falling temperature is nearly offset
by radius expansion. Thus, for large (supergiant) progenitors the ratio of
breakout to shock cooling flux is close to unity at a few hours. Using these
robust flux estimate and observationally-calibrated event rates we can
determine that ULTRASAT is expected to detect about 15 flares per year (Ganot
et al. 2016; see Figure 2).

####  5.2.2 CSM shock breakout observations

Consideration of CSM breakouts is motivated e.g., by the indication that pre-
SN “precursors” are common for SNe IIn (e.g., Ofek et al., 2014a; Strotjohann
et al., 2021) and occur also in other SN types (Foley et al., 2007; Jacobson-
Galán et al., 2022). These month-long precursor events occurring within the
final years prior to explosion provide direct evidence for intense mass loss
episodes in many SN progenitors shortly before the explosion. This challenges
the canonical picture (e.g., Langer, 2012) of a rapidly evolving (through
nuclear burning) core surrounded by a nearly time independent envelope.
Various mechanisms have been proposed to generate rapid mass loss, including
pair instability pulsations (Woosley et al., 2007), convection and radiation
driven instabilities (Suárez-Madrigal et al., 2013; Smith & Arnett, 2014),
waves excited by core convection (Quataert & Shiode, 2012; Fuller & Ro, 2018),
and common envelope interaction (Chevalier, 2012; Soker & Kashi, 2013).

Observations of CSM breakout flares provide information about the properties
of the surrounding CSM, and, most interestingly, on the rate and duration of
the mass loss episode (e.g., Ofek et al., 2010), which map the violent pre-
explosion evolution of massive SN progenitors, which is observationally hard
to observe and theoretically poorly understood.

Furthermore, non-relativistic CSM breakouts are interesting because they may
be the sources of several classes of powerful transients. Non-relativistic CSM
breakouts are considered as possible explanations of (at least part of) the
super-luminous SN (SLSN) class (Ofek et al., 2010; Chevalier & Irwin, 2011;
Balberg & Loeb, 2011; Ginzburg & Balberg, 2012; Moriya et al., 2013), of
“double peak” SNe, of some rapidly evolving transients (e.g., Margalit, 2022)
and of the early part of the emission of SNe of type IIn (Ofek et al., 2014b).
Specifically, early UV observations were found to be essential to accurately
estimate the temperature, radius, and bolometric luminosity of interacting
SNe, because they provide a better handle on the blackbody spectrum shape
compared to visible light alone. Such observations have recently shown that
SNe IIn are hotter and brighter than previously thought, with their radius
growing faster (Soumagnac et al., 2020a). Additionally, early UV observations
can help determine the geometrical distribution of the CSM surrounding these
events, shedding light on the mass-loss processes which occur before the
explosion and on the nature of the progenitors. Recent studies using early UV
observations have found that at least a third of SNe IIn have non-spherical
CSM (Soumagnac et al., 2019, 2020a), challenging the usual assumption of
spherically symmetric models. ULTRASAT will provide UV light curves for about
a thousand of SNe IIn and enable to perform such studies on a much larger
scale. This could open a new chapter in the study of SNe IIn, allowing for a
stronger constraint on the number of aspherical CSM cocoons and bringing us
closer to understand their progenitors and explosion physics.

Relativistic breakouts are also very interesting, especially for high-energy
signals (e.g., GRBs and XRFs Waxman et al., 2007; Campana et al., 2006b;
Calzavara & Matzner, 2004; Tan et al., 2001; Budnik et al., 2010; Katz et al.,
2010; Nakar & Sari, 2012). ULTRASAT detection and prompt alerts of such rare
phenomena could provide highly interesting information.

####  5.2.3 Shock cooling observations

Following the breakout flare, the shock cooling emission phase provides
additional unique signatures of the structure of the progenitor star
(including radius, envelope mass and surface composition) and of its mass-loss
history close to the explosion (and possibly also of CSM density
inhomogeneities, e.g. Fryer et al. 2020; Goldberg et al. 2022).

For non-relativistic ($v/c<0.1$) breakouts from stellar surfaces, existing
theoretical analyses (e.g., Rabinak & Waxman, 2011; Sapir & Waxman, 2017; Katz
et al., 2012; Sapir et al., 2013; Nakar & Sari, 2010; Kozyreva et al., 2020;
Piro et al., 2021; Morag et al., 2022), provide a good understanding, and
tools for accurate description of the radiation emitted during and following
breakout (see Waxman & Katz, 2017; Levinson & Nakar, 2020, for reviews).

Early SN observations were used to set, utilizing these theoretical analyses,
important constraints on the progenitors of SNe of Types Ia, Ib/c and II (Maoz
et al., 2014; Waxman & Katz, 2017; Levinson & Nakar, 2020; Soumagnac et al.,
2020b; Irani et al., 2022). A major challenge facing utilizing the early
emission for a systematic study of SN progenitors and explosion parameters is
obtaining the required early, $<1$ d, high cadence, $\sim 1$ hr, multi-band
observations: for most shock cooling observations, early multi-band
observations, including in particular at short, UV, wavelengths, are not
available at the high cadence and accuracy required for an accurate
determination of model parameters (see, e.g., Rubin et al., 2016; Soumagnac et
al., 2020b; Ganot et al., 2022, for examples and discussion). UV measurements
are essential for an accurate determination of the high color temperature
(Rabinak & Waxman, 2011; Sapir & Waxman, 2017; Rubin et al., 2016); high
cadence multi-band observations are required for a determination of the
relative extinction (Rabinak & Waxman, 2011), which strongly affects the
inferred luminosity and color temperature. ULTRASAT will revolutionize this
field, with both the quantity and quality of data expected to improve
significantly. This will enable a systematic accurate determination of
progenitor and explosion parameters based on shock cooling, and possibly shock
breakout, observations.

In summary, studying the early SN emission provides unique information on the
SN progenitor and its pre-explosion evolution, which cannot be directly
inferred from later time observations. This information is highly instructive
for the study of the supernova explosion mechanisms, which are not fully
understood despite many years of research (e.g., Janka et al., 2016; Burrows &
Vartanyan, 2021; Maoz et al., 2014).

###  5.3 Cosmology & Type Ia SNe

Standard candles such as Type Ia supernovae (SNe Ia), plateau core-collapse
supernovae (SNe IIP) and kilonovae (KNe) can be used to derive distances in
the Universe. Together with redshifts these constrain the physical properties
of the Universe at large scales. Distant SNe Ia were fundamental in the
discovery of the accelerated expansion of the Universe and the existence of
dark energy (Perlmutter et al., 1999; Riess et al., 1998). More recently,
standard candles in our local neighborhood indicate that the local expansion
velocity (Hubble constant) is in tension with values predicted based on CMB
observations (Riess et al., 2019; Wong et al., 2020) (however, see Rigault et
al. (2015); Mortsell et al. (2022)). Looking towards the future, large field-
of-view surveys such as ZTF and LSST will provide tens of thousands of
supernovae at intermediate distances (Feindt et al., 2019; The LSST Dark
Energy Science Collaboration et al., 2018). These samples can be used to
construct peculiar velocity maps of the full distribution of matter, i.e. also
including the otherwise ”invisible” dark matter (Kim et al., 2019a). Standard
candles, observed at different redshifts, thus uniquely allow us to probe all
aspects of cosmology, from the nature of dark energy and dark matter through
tests of the early Universe to tests of general relativity. Today, the
discovery and classification of large numbers of transients have been largely
streamlined (Nordin et al., 2019; Fremling et al., 2020) and the fundamental
limitation has instead shifted to the possible impact of systematic effects
(Brout et al., 2019). Even rare objects, such as Kilonovae and strongly lensed
SNe, where any discovery provides immediately new insights (Goobar et al.,
2017; Abbott et al., 2017b), are facing systematic uncertainties. In the
following, we discuss how ULTRASAT observations can have significant impact on
these cosmology related questions.

####  5.3.1 SN Ia: progenitors, dust and cosmology

Thousands of SNe Ia have been observed with high precision during the last
decade, but these observations, typically occuring around peak light, have
still not answered the fundamental question of what triggers the explosion. A
SN Ia is driven by the thermonuclear explosion of a white dwarf, but the exact
nature of the precursor system and how the explosion is ignited is still not
known. Two main progenitor scenarios have been identified, either involving
the merger of two double degenerate white dwarfs (DD) or mass transfer from a
companion onto a Single Degenerate (SD) white dwarf (Maeda & Terada, 2016;
Livio & Mazzali, 2018). For each of these, further unknowns create additional
uncertainty: Is the companion a main sequence, giant or helium star and what
is the role of circumstellar medium (SD)? How violent and clumpy is the
merger, and is the detonation caused by an initial explosion in an outer layer
of material (DD)? It is likely that several of these explosion scenarios are
realized in nature, which could map to the intrinsic diversity among SNe Ia
(Pakmor et al., 2013; Soker, 2019). The question about the progenitors,
besides being of fundamental interest, also implies a systematic uncertainty
for cosmology as the potential progenitor scenarios can be expected to evolve
differently with time or occur more frequently in some galactic environments.
As an example, DD scenarios involving two degenerate objects can be expected
to be found also long after star formation occurred while SD models typically
require a younger companion stars (Maoz & Mannucci, 2012). Observational
evidence does suggest cosmological differences between SNe Ia in different
environments exist (Rigault et al., 2013). Any unaccounted difference in
luminosity between these progenitor classes could quickly bias cosmological
constraints.

Lightcurves of SNe Ia are famously standard close to peak light, as the
strength of the detonation erases the signatures of the progenitor setup.
Distinguishing these instead requires to observe at very early phases (or very
late). Comparisons between theoretical predictions yield significant
differences during the first hours/days (Noebauer et al., 2017; Piro &
Morozova, 2016; Magee & Maguire, 2020). This is particularly true for the SD
scenario, where the expanding ejecta is expected to strongly interact with the
companion star for certain viewing angles (Kasen, 2010; Boehner et al., 2017).

Extensive searches during the last decade have yielded claims of individual
SNe both with and without an early flux excess (e.g. Nugent et al., 2011; Cao
et al., 2015; Kromer et al., 2016; Hosseinzadeh et al., 2017; Jiang et al.,
2017; Miller et al., 2018, 2020; Siebert et al., 2020; Dimitriadis et al.,
2023; Lim et al., 2023), but consistent studies of larger samples are limited
and hard to interpret (Bianco et al., 2011; Milne et al., 2013; Olling et al.,
2015; Nordin et al., 2018; Fausnaugh et al., 2021; Burke et al., 2022). In
particular, it has been seen that both SD and DD scenarios are expected to
produce early variability through effects such as Ni mixing or heating from
outer Ni shells / clumps (Magee et al., 2021).

UV observations have the power to finally solve the progenitor puzzle, as the
additional information allows to disentangle the currently discussed models:
Companion interaction is expected to produce a shock-like signature at early
times where the flux increase is even larger at short wavelengths while
radioactive material distributed to the outer ejecta will at least partially
absorb UV emission (Maeda et al., 2018). As it is now likely that multiple
explosion channels exist, and that each could be associated with stochastic
variations (e.g. due to viewing angle), a significant statistical sample of
O($100$) SNe Ia with early ($<3$ days) UV observations will be needed.
ULTRASAT is uniquely positioned for obtaining this sample, and thus for
solving the long-lasting progenitor debate.

An ULTRASAT SNIa sample could also be used to directly improve SNIa distances
and thus cosmological parameter estimates. The standardized SN peak magnitude
for large samples currently displays an intrinsic scatter around $0.13$ mag
(Betoule et al., 2014), but several extended standardization methods shows
that the underlying true intrinsic dispersion is likely at least $30\%$ lower
(Fakhouri et al., 2015). U-band features have been shown to be one possible
way to achieve this reduction (Nordin et al., 2018). An improved intrinsic
dispersion directly translates into improved cosmological constraints, in a
way which for example an increased sample does not. Interestingly, a low
redshift SNeIa sample observed in the ULTRASAT band (in addition to the
optical bands accessible with many surveys) maps well to the $g$-band of the
LSST survey for SNeIa detected at redshifts $z\sim 0.9\pm 0.1$, allowing for a
sensitive test for SNeIa evolution over more than half the Universe’s age. So
far, only a handful of SNIa have good UV coverage, but already this small
sample shows interesting signs of variation not easily captured in the
standard lightcurve analysis (Brown et al., 2018). It is plausible but
untested that the standardization potential extends, or even increases, into
the UV. If this would be the case, ULTRASAT observations could be used to
immediately improve cosmological constraints.

Photon absorption and/or scatter by dust along the line of sight constitutes a
fundamental uncertainty for luminosity distances to both SNe Ia and SNe IIp
(Goobar & Leibundgut, 2011). This effect causes a systematic bias whereby
objects appear fainter, and thus more distant, than they really are.
Extinction is routinely corrected for as dust absorption is stronger at bluer
wavelength, assuming color measurements are obtained (Cardelli et al., 1989;
Schlegel et al., 1998). However, for cosmology this corrections needs to be
accurate at the 1% level, far below what standard methods provide (Berger et
al., 2003). Reaching this level requires knowing both the intrinsic transient
color as well as the wavelength dependence of the dust absorption. The
distribution and property variations of dust is only well studied in the most
nearby galaxies, while supernovae are more likely to explode in particular
(star forming) galactic environments. An extreme example of this is the
potential existence of dust in the immediate supernova environment, possibly
previously ejected, which might evolve in time through the interaction with
the explosion itself.

In fact, attempts to model reddening of SNe Ia empirically during the recent
decades have yielded models that vary significantly from the expected
properties of any kind of dust (Schulze et al., 2014; Amanullah et al., 2015).
The potential cause of this difference was at the core of the different
approaches taken by the two teams who detected the expansion acceleration, and
it has not yet been resolved. The underlying problem is that supernovae are
typically observed at optical wavelengths where it has turned out to be
difficult to separate variations due to dust absorption with intrinsic
variations in the SN SED. Both can reasonably be expected to vary e.g. with
the surrounding environment.

The ULTRASAT observations have the opportunity to fully reform our
understanding of dust absorption of SNe through directly probing the kind of
dust individual SNe have encountered, as well as look for any variation in
time. This is because different dust models show significant variations in the
UV, even for similar amounts of extinction in the optical. In addition,
extinction in the UV is very pronounced, making this an easy observation. So
far, such studies are confined to only a small set of SNe Ia observed in the
UV by HST Amanullah et al. (2015).

####  5.3.2 SN Ia: rates

Estimating the expected rate of Type-Ia SNe (SNeIa) observable by ULTRASAT is
difficult, since the established emission parameterizations do not extend into
the UV (e.g. Guy et al. (2007); Kenworthy et al. (2021)), and theoretical
models show a large variation. In order to nevertheless obtain a robust
estimate of the expected rate, we have used the fact that the rest frame UV
band of high-redshift SNeIa falls into the well observed optical bands. We
focused on data from the SNLS survey (Betoule et al., 2014). The redshifted
$g$-band light curves from SNLS can be approximated as rest-frame ULTRASAT UV
light curves for a redshift $z=\lambda_{g}/\lambda_{\rm UV}-1\approx 0.92$,
where $\lambda_{g}\approx 5000$ Å and $\lambda_{\rm UV}=2600$ Å. The
difference in limiting magnitudes between the SNLS $g$-band and ULTRASAT
translates to a redshift of $\sim 0.2$, up to which ULTRASAT would still have
similar sensitivity. The SNeIa of the SNLS/JLA sample within the range
$z=0.92\pm 0.1$ were analysed for emission in the SNLS $g$-band. The light
curves of the 46 objects in the high redshift bin were evaluated both by eye,
and by using statistical information. Seventeen objects where selected that
have at least one UV detection, i.e. 37% of the initial sample. Given the
high-redshift of the SNeIa sample, we must expect a significant Malmquist
bias. Indeed, in comparison to a large sample of local SNeIa from ZTF, it
became evident that the SNLS SNeIa are missing redder objects ($c<0.1$). The
redder objects make up about 50% of the ZTF sample, and accordingly, and it is
unknown if these would show UV emission, if probed with a more sensitive
instrument (if the reddening is due to dust one would expect to observe a
large fraction of the nearby objects). Accordingly, a conservative assumption
is that the 50% missing red objects are not detectable in the UV.

Combined, we can make a robust prediction that $\geq 18\%$ of SNeIa below 0.2
are detectable in the UV by ULTRASAT. For a volumetric rate of SNe Ia of
$3\times 10^{-5}\,{\rm Mpc}^{-3}\,{\rm yr}^{-1}$ (Dilday et al., 2010) and a
survey area of 8000 deg2, the rate will be $\geq 300\,\,(2400)$ SNeIa per year
up to a redshift of 0.1 (0.2). This is sufficient statistics to make the above
mentioned studies promising.

####  5.3.3 Hubble constant from Kilonovae, time delay of lensed SNe and other
exotic transients

Gravitational waves can function as cosmological sirens and in principle allow
sub-percent measurements of the Hubble parameter, $H_{0}$ (Schutz, 1986;
Abbott et al., 2017). The major uncertainties are caused by the distance
measurement and inclination of the GW source, both almost fully degenerate
with $H_{0}$. The redshift can most easily be determined from the detection of
the optical counterpart (kilonova) caused by a neutron star merger. The most
promising methods for estimating inclination focus either on measuring the GRB
afterglow time-delay, the color evolution of the early kilonova lightcurve or
through polarimitry (Bulla et al., 2022). Both the afterglow as well as the
early kilonova evolution are prime targets for high-cadence ULTRASAT
observations. Current radiative transfer kilonova studies do not focus on the
UV region, but it is clear that the dominant inclination effect is in the
u-band (the bluest band included), where inclination cause a four magnitude
variability during the first day after explosion (Bulla, 2023). The opacity
difference between ”blue” and ”red” kilonova components are likely even
stronger at UV wavelengths, making colors based on ULTRASAT observations an
excellent inclination indicator.

An alternative path to measure the Hubble constant is the time-delay between
multiply (strongly) lensed transient sources. This technique has now reached
maturity for lensed quasars (Wong et al., 2020) and is expected to become of
use for supernovae within the next years (Goldstein et al., 2018). As
gravitational lensing is achromatic, ULTRASAT will not in itself increase the
sensitivity for strongly lensed sources. However, as the cosmological
constraint directly depends on the precision with which the time-delay can be
measured, blue and short-lived events such as the shock-breakout of core
collapse SNe could allow ULTRASAT to measure the time-delay between strongly
lensed events even when these cannot be spatially resolved. Such events are
rare, but the shorter signature will allow to probe less massive lenses, which
can increase the rate compared to that of current surveys. A sample
characteristic signature would be a shock breakout with multiple peaks which
evolves into an over-luminous SN (during which the time-difference cannot be
seen).

###  5.4 Gamma Ray Bursts (GRBs)

ULTRASAT will enable GRB studies both through target-of-opportunity followup
and through direct detection of their ultraviolet counterparts in time domain
fields.

While GRB afterglows are effectively panchromatic, and near-UV observations
probe roughly the same phenomena as optical observations, ULTRASAT has
significant strengths for GRB astrophysics. First, its combination of
sensitivity, field of view, duty cycle, and response time stands out among
present and near-future facilities. Second, the near-UV sky has a lower
density of confounding sources (both steady and transient) than the optical
sky. Third, because near-UV observations are more sensitive to dust extinction
than optical or near-IR observations, ULTRASAT data may effectively probe dust
columns along GRB sight lines.

Approximately 10 cosmological GRBs per year are expected to occur within
ULTRASAT’s field of view. UV afterglow emission from these GRBs can be
detected to cosmological distances, given ULTRASAT’s sensitivity. Moreover,
prompt emission may also be detected, provided the fluence within a 300s
ULTRASAT exposure exceeds the detection limit. A typical prompt UV luminosity
of $>10^{45}\,\hbox{erg}\,\hbox{s}^{-1}$ and a prompt emission duration $\sim
10\,\hbox{s}$ is sufficient up to a luminosity distance $d_{L}\approx
5\,\hbox{Gpc}$, corresponding to redshift $z\sim 0.8$.

ULTRASAT may be particularly valuable in constraining the existence of orphan
GRB afterglows and of dirty fireballs.

GRBs may be part of a larger class of cosmological fireballs. Such fireballs
are generically expected when a sufficiently large amount of energy is
released into a sufficiently small volume along with a (relatively small)
quantity of ordinary baryonic matter. This results in optically thick
conditions, so that a large part of the energy is converted into kinetic
energy of ejecta. The smaller the baryon loading is, the more relativistic the
ejecta become. For bulk Lorentz factors $\Gamma\gtrsim 100$, internal shocks
within the ejecta and/or external shocks between ejecta and ambient medium can
produce gamma rays. However, there is no a priori reason that “dirty
fireballs,” which are physically similar apart from larger baryon loading and
lower peak Lorentz factors, could not exist. Such explosions would not produce
much gamma ray emission, but could resemble GRBs in most other ways. In
particular, they could still produce bright transients with properties similar
to GRB afterglows at longer wavelengths, including the near-UV.

Afterglows without accompanying gamma rays may also be expected as a
consequence of GRB collimation. Relativistic beaming of photons has a
characteristic half-angle $\sim 1/\Gamma$. When ejecta from a fireball that is
collimated into angle $\theta_{jet}$ decelerate to $\Gamma<1/\theta_{jet}$,
the fireball becomes visible at viewing angles $\theta_{obs}\sim
1/\Gamma>\theta_{jet}$ (Rhoads, 1997, 1999; Sari & Piran, 1999). Photon
energies from the expanding remnant decrease as $\Gamma$ decreases, with the
net effect that some off-axis events should be seen as “orphan afterglows”
without accompanying gamma rays.

In principle, event rates of both dirty fireballs and off-axis orphans could
greatly exceed the rate of observable GRBs. In practice, preliminary
indications from ZTF do not show large numbers of orphans (Ho et al., 2022).

Ultimately, we would like to study the overall population of relativistic
fireballs. Suppose we describe each fireball with its total energy $E$,
collimation angle $\theta_{jet}$, and peak Lorentz factor $\Gamma$. We would
like to measure the event rate in this multidimensional parameter space
$R(E,\theta_{jet},\Gamma,z)$.

GRB experiments constrain this distribution for the $\Gamma\gtrsim 100$,
subject to thresholds in fluence or flux. Multiwavelength monitoring of GRB
afterglows yields constraints on the distribution of $\theta_{jet}$. ULTRASAT
offers the wavelength coverage to probe down to $\Gamma$ of a few, and the
survey efficiency (grasp) to measure values of $R$ that are appreciably
smaller than the intrinsic GRB rate.

Full interpretation of the fireball population observed by ULTRASAT will
doubtless require more sophisticated physical models than the arguments
presented above. Relativistic hydrodynamical simulations (Granot et al., 2018)
can be used to examine the light curves expected as a function of wavelength,
jet angle, and viewing angle.

###  5.5 Stars and stellar remnants

In the UV range, as in the optical and in the IR, the majority of sources
brighter than $\sim 20$ mag in an astronomical image, particularly at low
Galactic latitudes, are stars and their white-dwarf (WD) remnants. ULTRASAT’s
unique combination of a large field of view, a long, continuous, dwell time
with a high cadence, and all this in the UV, will open up largely uncharted
territories in the study of stars and WDs.

####  5.5.1 Stellar rotation and chromospheric activity

The link between rotation and magnetic activity in stars can appear in all
layers of the stellar atmosphere, be it in the photosphere (e.g. Suárez
Mascareño et al. 2016), the chromosphere (e.g. Olmedo et al. 2013; Astudillo-
Defru et al. 2017) or the corona (e.g. Wright et al. 2011; Pizzocaro et al.
2019). The manifestations of stellar spots and flares and their connections to
magnetic field, stellar age, and rotation, have been probed only scantily in
the UV, let alone have they been well characterized. Apart from the poorly
understood physics underlying these phenomena, observing stellar activity has
gained also practical importance for the discovery and characterization of
exoplanets. The radial velocity (RV) accuracy achievable using advanced
methods and stabilized spectrographs (e.g. Anglada-Escudé et al. 2016) is
ultimately limited by the magnetic activity of the host stars, which can cause
RV jitter with amplitudes of $\gtrsim 10$ m s-1 (Tal-Or et al., 2018), and can
mask or mimic the signal caused by substellar companions.

Figure 7: Relative chromospheric flux excess over the model photospheric flux,
versus effective temperature, for 8859 stellar sources observed in the UV with
the XMM-Newton Optical Monitor, in the Gaia DR2 source catalog, and in the
LAMOST DR5 catalog. The color coding of the points reflects the reddening. The
red line denotes the the flux excess of the bottom 5th percentile of stars
having reddening coefficient $E(BP-RP)\leq 0.05$.

To assess quantitatively the amount of magnetic-activity-related emission from
normal stars that ULTRASAT will see, we have analyzed archival data from the
XMM-Newton Optical Monitor (OM; Mason et al. 2001), whose UVM2 filter is
similar in width and central wavelength to the ULTRASAT bandpass. Point
sources from the XMM-SUSS 4.1 catalog (Page et al., 2012) with a signal-to-
noise ratio $\geq 5$ in the UVM2 filter were cross-matched with the GAIA DR2
source catalog (Gaia Collaboration et al., 2018) to obtain parallaxes, and
with the LAMOST DR5 catalog (Luo et al., 2019) to obtain stellar parameters
(log g, [Fe/H], $T_{\rm eff}$) for a total of 8859 stars. The UV flux measured
by the XMM OM consists of photospheric and chromospheric contributions. To
estimate the photospheric contribution, we folded each spectrum from the
latest PHOENIX stellar atmosphere grid (Husser et al., 2013) through the UVM2
filter transmission function, yielding a grid of theoretical UV fluxes for the
full range of surface gravities, effective temperatures and metallicities. For
each star in the XMM OM catalog we then interpolated, on this grid, its
theoretical photospheric UV flux. In analogy to the stellar activity indicator
$R^{{}^{\prime}}_{HK}$, we define a UV excess index,

$R^{{}^{\prime}}_{\rm NUV}=\frac{f_{\rm UVM2}-f_{\rm phot}}{f_{\rm bol}}$ (1)

where $f_{\rm UVM2}$ is the flux measured by the XMM OM, $f_{\rm phot}$ is the
theoretical photospheric flux in the UVM2 band from PHOENIX, and $f_{\rm bol}$
is the bolometric flux based on Gaia.

Figure 7 shows the UV non-photospheric flux excess as a function of stellar
effective temperature, where the color coding of the points denotes the
Gaia/Apsis reddening coefficient $E(BP-RP)$. The red curve shows the
$R^{{}^{\prime}}_{\rm UVM2}$ of the bottom 5th percentile of all sources with
a reddening coefficient $E(BP-RP)\leq 0.05$. We see that, in a large majority
of all stars, chromospheric emission in the UVM2 band constitutes a non-
negligible fraction, 0.1% to 5%, of the bolometric luminosity of the star,
with typical values of $\sim 1-3$%, and a clear rising trend with effective
temperature. Note that this excess UV flux is accumulated over generally long
XMM integrations, and likely consists of both variable and steady-state
components. ULTRASAT will thus be ideally positioned to measure and
characterize this important component of stars, and its behavior (particularly
in the temporal regime).

The magnetic activity of stars manifests itself observationally as variability
in two forms: stochastic variability from stellar flares that arise from
magnetic instabilities in the chromosphere and the corona; and periodic
variations resulting from photospheric stellar spots, combined with stellar
rotation. The mission-long UV light curves of all stars observed with ULTRASAT
will be an unparalleled resource for characterizing both of these types of
stellar variability in the UV.

Recent studies have revealed, in growing detail, large scale trends with
stellar properties of the optical variability periods that trace the rotation
periods (e.g. McQuillan et al. 2014; Davenport & Covey 2018; Canto Martins et
al. 2020; Gordon et al. 2021; Briegal et al. 2022). Apart from an empirical
trend between stellar color and rotation period, which permits deducing a
star’s age (”gyrochronology”–stars lose angular momentum and magnetic-field
strength as they age), several of these studies and others have shown an
intriguing bi-modal structure in the parameter space of rotation periods of
main-sequence stars with respect to color, with a dearth of stars in a period
gap between $\sim 15$ and 25 days. These results have emerged largely from
Kepler and TESS data with their continuous, high-cadence, temporal sampling,
similar to that planned for ULTRASAT. The ULTRASAT data will permit extending
such studies, for the first time, into the UV, with this band’s sensitive,
independent, indicators of magnetic activity. Systematic large surveys of
stellar activity are in progress also in X-rays (e-ROSITA; Merloni et al.
2012). In radio, stellar activity studies require observations based on
pointing and dwelling on individual stars, but a large body of data has
already been collected (e.g. Crosley & Osten 2018; Villadsen & Hallinan 2019;
Vedantham et al. 2020; and references therein). ULTRASAT data will thus be
instrumental for the inter-comparison of these phenomena across the
electromagnetic spectrum. Active short-period binaries and planet hosts are
another promising category for ULTRASAT studies. The topology of the stellar
magnetic field may be modified by the presence of a close companion. The UV
emission from the corona, which is in interaction with the magnetic field,
should be modulated with the stellar binary period, and with the rotation
period, assuming the system has reached synchronization via tidal dissipation.
If synchronization has not been achieved, the stellar magnetic topology can be
complex, with possible induced instabilities that will be reflected in the UV
variability observed by ULTRASAT.

In summary, the still-poorly understood question of how magnetic activity
operates in normal stars will receive a major resource from the
characterization by ULTRASAT of UV variability, potentially for a large
fraction of all the stars that it will observe. Planned ULTRASAT studies of
the stochastic flaring activity (rather than periodic variability) of normal
stars are further discussed in Section 5.6, below.

####  5.5.2 White dwarf accretion and rotation

Distinct from pulsating WDs (which are on the WD instability regions in the HR
diagram, with periods of minutes), photometrically variable WDs with
amplitudes of order $\sim 10\%$ and periods of hours to months are known, but
rare. Except in a few individual cases that may be explained by effects
connected to an orbit with a companion mass (beaming, reflection, ellipsoidal
tidal distortion), the variability has been generally associated with WD
rotation (which has the same typical range of periods), combined with non-
uniform surface emissivity. Except for very cool WDs, most WDs have fully
radiative atmospheres, devoid of the convective cells that can produce star
spots. The photospheric inhomogeneity implied in variable WDs has therefore
been ascribed, instead, to extreme magnetic field strengths that produce
magnetic dichroism (Angel et al., 1981).

However, Maoz et al. (2015), analyzing the Kepler time series of 14 normal
WDs, found periodic photometric modulations in seven of them. The variation
periods were of order hours to 10 days, with amplitudes of order $10^{-4}$ to
$10^{-3}$, much lower than could have been detected with pre-Kepler
technology. This discovery raised the possibility that most or all WDs have
low-level variability associated with rotation, but also exacerbated the
problem of how to produce, as a rule in WDs, an inhomogenous WD photosphere.
Maoz et al. (2015) and Hallakoun et al. (2018) hypothesized that the optical-
band low-level photometric modulation seen in many WDs could be associated
with photospheric metal pollution, which is likewise seen in a large fraction
of WDs (Koester et al., 2014).

Over the past couple of decades it has become widely accepted that the optical
and UV metal absorption lines seen in WD atmospheres are the result of ongoing
accretion of planetary debris onto the WD (Jura, 2003; Zuckerman et al., 2003,
2010; Gänsicke et al., 2012; Koester et al., 2014). Slightly inhomogeneous
surface coverage of the accreted material (e.g. due to moderate magnetic
fields) could lead to inhomogeneous UV absorption. Optical fluorescence of the
absorbed UV photons (Pinto & Eastman, 2000), combined with the WD rotation,
could then potentially produce the observed levels and periods of optical
modulation.

We estimate that $\sim 400$ WDs will be detected above the limiting magnitude
in every ULTRASAT field. Although the $10^{-4}-10^{-3}$ variation amplitudes
seen with Kepler will be near the limit detectable with ULTRASAT (depending on
the level of hard-to-foresee systematics), many WDs show modulations with
larger amplitudes, mostly in optical-band photometric surveys (such as
Kepler’s K2 continuation mission). One example of a high-amplitude UV-variable
WD is GD 394. This hot, metal-polluted, WD was observed in the past by the
Extreme Ultraviolet Explorer (EUVE) and displayed 25% variations in the
extreme UV (70-380 Å) with a period of 1.15 d (Christian et al., 1999; Dupuis
et al., 2000). Follow-up far UV spectroscopy (1144-1710 Å) taken in 2015 with
$HST$ failed to detect any variability, down to the 1% level (Wilson et al.,
2019). However, recent TESS data have revealed 12%-amplitude optical
variations, with a similar period (Wilson et al., 2020). GD 394 has some
striking similarities to WD J1855+4207 (Maoz et al., 2015; Hallakoun et al.,
2018). Both are hot ($\gtrsim 30,000$ K) WDs with indications of highly
ionized circumstellar metals, in addition to the detected photospheric metals,
and both have relatively large periodic optical modulations. The monitoring of
the numerous WDs in the ULTRASAT-monitored fields can potentially detect
additional such large-amplitude or changing-amplitude WDs.

Furthermore, in the case of a WD with significant metal pollution in its
photosphere, UV variability over short (minutes to days) or long (months to
years) timescales, could indicate a change in the debris accretion rate, or in
the structure of the circumstellar debris around the WD. Combined with
simultaneous photometric monitoring in multiple bands (from the UV to the near
infrared) using ground-based facilities (e.g. Hallakoun et al. 2017; Xu et al.
2019), ULTRASAT may thus finally provide answers to the question of how
periodic variability is produced in a large fraction of WDs.

###  5.6 Exoplanets & Star-Planet Connection

The discovery of thousands of extrasolar planets ranks among the most exciting
scientific developments of the past decades. ULTRASAT capabilities allow us to
explore unique regions of exoplanet and star-planet connection parameter
space. In this section we focus on two research topics that ULTRASAT will
significantly advance - host activity (Section 5.6.1) and the search for
planets around WDs (Section 5.6.2). We also discuss ULTRASAT potential to
study exoplanet atmospheres (Section 5.6.3), albeit this will require
modifying the survey modes.

####  5.6.1 Planet’s host activity

The UV radiation emitted from a host star on an orbiting planet can dictate
whether a planet retains its atmosphere, and govern the photochemistry in it.
In addition, the UV flux will have both positive and negative contribution to
the likelihood of life developing on it (Buccino et al., 2006; Ranjan &
Sasselov, 2016). As a stressor, high fluxes of UV radiation, in either steady
state emission or through flares, can destroy nascent biomolecules through
photolysis. As a eustressor, recent studies indicate UV radiation can play a
key role in prebiotic chemistry, and might have been the most abundant energy
source on the young earth. In the context of the search for biologic activity,
UV emission can result in abiotic generation of bona-fide biosignatures, such
as the disassociation of water molecules in exoplanets orbiting M-dwarf (dM)
stars that will in turn result in high concentration of molecular oxygen
(Meadows et al., 2017). Therefore, one must know the UV radiation field around
a planet to understand its atmosphere evolution. Defining a UV habitable zone
(UV HZ) – the range of orbits in which the UV radiation from the host star
will allow (and contribute) to the evolution of life as we know it, is
critical for putting the evolution of life on our own planet on a galactic
scale, and for the search of bioactivity on other worlds.

Despite the impact of UV radiation on exoplanet atmospheres evolution and the
likelihood of bioactivity, our understanding of the UV emission from stellar
objects is limited, and the commonly used photospheric models routinely
underestimate it, as the UV emisison for e.g., dM stars, originates in the
chromosphere and transition region (France et al., 2013). Our current
capability to characterize it for various stellar types is hindered by the
small number of UV observatories to date, the lack of large UV datasets, and
the large variance in the UV radiation in both short and long time scales,
i.e., flares for the former and variability for the latter.

Initial studies performed with the limited data available are portraying a
complicated picture, specifically for dM stars, the most common stars in the
solar neighborhood and preferred targets for many exoplanet transit searches
due to favorable planet-to-host radius ratio, and the potential for atmosphere
studies. Some suggest that the HZ and the UV HZ do not necessarily coincide
for various stellar types (Buccino et al., 2006). Another study using HST data
indicates that some dM stars that seem to be in a quiescent state when
observed in the visible band are active in the UV band (France et al., 2016).
These results demonstrate clearly the need for a detailed study of UV
radiation from a large sample of stars of various stellar types. Additional
data, albeit for a limited sample, is expected from two CubeSats missions that
have recently been launched: The Colorado UV Transit Explorer (CUTE; Fleming
et al., 2018), and The Star-Planet Activity Research CubeSat (SPARCS;
Ramiaramanantsoa et al., 2022).

The total number of stars within ULTRASAT $200\,$deg2 FoV and up to $\sim 800$
pc is estimated to be $\approx 200,000$ stars, with roughly half of them being
dM stars, see Figure 8. For the latter in quiescence, we expect to detect only
$O(1-10)$ stars for co-adds of three images, and $O(10^{3})$ stars for co-adds
reaching an estimated confusion limit of 24 magnitude in the ULTRASAT
waveband. Assuming the NUV flare frequency distribution (FFD) derived by Rekhi
et al. (submitted) using archival $GALEX$ data, each 300 s ULTRASAT image will
capture $\sim 150$ flaring dM stars, with equivalent duration distribution
shown in Figure 9, for which $\approx 50\%$ of the flares are in the poorly
constrained high energy regime. The distributions shown in Figures 8 and 9
demonstrate how the long baseline observations of ULTRASAT will allow us to
monitor the high energy tail of the FFD (i.e., equivalent duration $\geq
10^{4}\,$s), which is poorly constrained to date. Flares in this energy range
are expected to have a significant effect on an exoplanet atmosphere. The data
will provide us a more complete picture of the high energy radiation
environment around stellar hosts, and will allow us to determine the best
candidates for expensive spectroscopic studies of exoplanet atmospheres by
e.g., JWST and the upcoming ELTs.

Figure 8: Magnitude distribution of dM stars in quiescence up to 800 pc in an
exemplar ULTRASAT FoV of $200\,$deg2. While flaring they can get up to $\sim$5
mag brighter (Rekhi et al. 2023, submitted). Input catalogues used include the
TESS Input Catalogue (Stassun, 2019). Limiting magnitude for a 3 image co-add
for dM stars is $\approx 21.4$.

Figure 9: The expected distribution of flares detected in each 300 s ULTRASAT
image, for the the dM population shown in Figure 8. The high energy tail of
the distribution, with equivalent duration $\geq 10^{4}\,$s, is poorly
constrained. A Monte-Carlo simulation in which the $NUV$ FFD was empirically
derived from $GALEX$ observations suggests each ULTRASAT image will capture
$\sim 150$ flares from dM stars (Rekhi et al. 2023, submitted).

####  5.6.2 Planets around white dwarfs

Occurrence rate studies show that most main sequence stars host exoplanets
(Winn & Fabrycky, 2015; Cassan et al., 2012). The vast majority of these hosts
will evolve into WDs. Planets in close orbits are unlikely to survive this
transition, as the host star climbs the red giant branch, and its envelope
expands. Despite the expected fate of close-in planets, both direct and
indirect evidence have been accumulated for the presence of sub-stellar
objects and minor bodies in close orbit around WDs (Veras, 2021). Several
explanations for the presence of these objects have been suggested. Planets
can be captured and/or migrate from wide orbits into close orbits after the
host transition into a WD is completed (Debes & Sigurdsson, 2002). Planets can
also form out of gas near the WD, e.g., via the interaction or merger of
binary stars (i.e., second-generation planets; Livio et al. 2005). Studying
the occurrence rates of planets around WDs can shed light on the evolution of
these systems. Moreover, given the slow change in the flux emitted by a WD as
it ages, the continuous habitable zone (CHZ) around a WD can have a lifetime
of $\gtrsim 3$ Gyr for orbital periods $\approx 4-32$hr (Agol, 2011). Planets
detected in the CHZ, will be optimal for atmosphere studies and search for
biomarker in their transmission spectra (Loeb & Maoz, 2013).

The search for planets around WDs is a rapidly growing field, with a few
detections of both disintegrating planets or planetesimals, and a transiting
giant planet candidate (e.g., Vanderburg et al., 2020, ; See review by Veras
2021). Due to the small radii of WDs, the transit depth induced by a planet is
large and can be detected with standards photometric precision telescopes
(e.g., ground-based, ULTRASAT), making transit detection possible despite WDs
being faint compared to typical targets of exoplanet surveys. Currently, all
occurrence rate constraints are based on null detections (thus giving only
upper limits). Fulton et al. (2014) used a sample of $\sim$1700 WDs observed
by the PanSTARRS survey to constrain planets occurrence rates in the HZ of
WDs. They find an occurrence upper limit of 3.5% for $R_{\rm
pl}=2-5R_{\oplus}$, but cannot constrain the occupancy rate for planets with
smaller radii. van Sluijs & Van Eylen (2018) investigated the light curves of
1148 WDs from Kepler’s K2 campaign, and conclude that the occurrence of
habitable Earth-sized planets ($R_{\rm pl}=1-2R_{\oplus}$) around WDs is
$<28\%$, approximately equal or less than their main-sequence occurrence. A
key to move forward is to significantly increase the number of monitored WDs.
ULTRASAT, with a large FoV that can image hundreds of WDs in a single
exposure, is ideal for this task.

The number of WD transiting planets is given by

$N_{\rm WD,pl}=N_{\rm WD}f_{\rm WD,pl}P_{\rm transit}P_{\rm detection},$ (2)

where $N_{\rm WD}$ is the total number of monitored WDs, $f_{\rm WD,pl}$ is
the fraction of WDs hosting planets with orbital period $<P$, $P_{\rm
transit}$ is the transit probability, $(R_{\rm pl}+R_{\rm WD})/a$, and $P_{\rm
detection}$ is the probability to detect at least $N_{\rm tr}$ transits.
ULTRASAT low-cadence survey will monitor $N_{\rm WD}\approx 32,000$ WDs (40
fields in each hemisphere, 400 WDs per field), an order of magnitude larger
than previous studies (see Ben-Ami et al. 2023 for a future planned survey).
In addition, $\sim 800$ WDs will be monitored by ULTRASAT high-cadence survey
each year.666We assume that the high-cadence fields will be different each
year, though this is still to be decided. The detection probability, assuming
the transit can be detected in a single visit, is:

$P_{\rm tr,det}=1-\sum^{N_{\rm tr}-1}_{k=0}\binom{n_{\rm
vis}}{k}\left(\frac{t_{\rm vis}}{P}\right)^{k}\left(1-\frac{t_{\rm
vis}}{P}\right)^{n-k},$ (3)

where $n_{\rm vis}$ is the number of visits and $t_{\rm vis}$ is the duration
of each visit. The 40 fields of the low-cadence survey (8000 deg2) cover
almost all of the low-extinction ($A_{\rm ULTRASAT}<1$) sky in each
hemisphere. Thus, for our current calculations we assume these will be the
same fields for the entire 3-year mission. Under this assumption, the low-
cadence survey will have $\sim$135 visits per field, each of $t_{\rm vis}=15$
min. The high-cadence survey fields will have over 45,000 images each year.

Figure 10:  Maximum number of WD transiting planets detected by ULTRASAT, by
both the low cadence survey and high cadence survey. Based on the current
occurrence rate upper limits from van Sluijs & Van Eylen (2018).

We use the 68% upper limits on $f_{\rm WD,pl}$ from van Sluijs & Van Eylen
(2018), to estimate the maximal number of WD-transiting planets with at least
$N_{\rm tr}=3$ detected transits by ULTRASAT, for a range of planet’s radii
and orbital period (Figure 10). We find that ULTRASAT is highly sensitive to
planets in the entire CHZ, with maximal number of detected planets well over
100 (assuming occupancy rates identical to the upper limits derived by van
Sluijs & Van Eylen 2018). The high number of detections is a result of the
large sample of WDs monitored by the low-cadence survey. ULTRASAT will thus be
able to deliver significantly tighter upper limits to those available by any
other existing survey, or better yet, will deliver a unique sample of planets
and minor bodies in short orbits around WDs. Planets at wider orbits than the
CHZ can also be detected (mainly via the high-cadence survey), but with a
smaller statistical impact.

####  5.6.3 Exoplanet atmospheres

The near UV bandpass holds unique prospects for the study of exoplanet
atmospheres (e.g., Christian et al., 1999). Several studies show the potential
of $NUV$ observations to differentiate between atmosphere models, as this
wavelength range contains telltales for the presence of clouds and haze (Goyal
et al., 2018). In addition, an escaping atmosphere will result in deeper
transits in the $NUV$, as the optical depth of the escaping atmosphere is
higher at shorter wavelengths (e.g., Vidal-Madjar et al., 2013; Salz et al.,
2019). While the cases above are typically targeted by FUV measurements, as
the signature is expected to be intrinsically stronger at this band, the $NUV$
bandpass hold several unique advantages (e.g., Christian et al., 1999), mainly
the uniform distribution of $NUV$ emission across the stellar disk when
compared to the FUV – which makes the scientific derivation more secure, and
the reduced stellar attenuation in the $NUV$ bandpass relative to the FUV. It
is not clear whether ULTRASAT will deliver the precision needed for such
studies. As a starting point and capability demonstration, ULTRASAT will
attempt to detect the signature of escaping atmosphere from several bona-fide
examples, such as WASP-12b. The signature of the escaping atmosphere in these
cases is several milimag (Fossati et al., 2010), well within the instrument
capabilities, see Figure 6. These cases will allow us to establish the
precision limits of the instrument and will allow us to plan a dedicated
survey for e.g., the search for escaping atmospheres from exoplanets in short
orbits. We emphasize that the science case described in this section is not a
part of the standard survey, and will require several changes to the standard
observing strategy, such as changes in the exposure time.

###  5.7 TDEs

Tidal disruption events (TDEs) offer a novel probe of massive black hole (MBH)
demographics, super-Eddington accretion physics, and stellar dynamics in
galactic nuclei. Theoretical dynamics calculations indicate that the
volumetric TDE rate should be dominated by the smallest galaxies with a high
MBH occupation fraction (Wang & Merritt, 2004; Stone & Metzger, 2016),
indicating that statistical samples of TDEs can resolve open questions about
the poorly-understood low end of the MBH mass function (Greene et al., 2020).
As probes of MBH demographics, TDEs have the unique ability to sample
quiescent galactic nuclei to cosmological distances (Bloom et al., 2011;
Chornock et al., 2014), and perhaps to measure MBH spins (Stone & Loeb, 2012;
Guillochon & Ramirez-Ruiz, 2015; Wen et al., 2020) as well as masses (Rees,
1988; Mockler et al., 2019; Ryu et al., 2020). There are indications that TDEs
may be multimessenger sources, as two different high-energy IceCube neutrinos
have been temporally and spatially coincident with TDE flares (Stein et al.,
2021; Reusch et al., 2022). More speculatively, TDEs may be linked to LISA-
band gravitational wave sources, either preceding (Seto & Muto, 2011) or
following (Stone & Loeb, 2011) the GW signal from a merging MBH binary, and
may even lead to novel tests of fundamental physics (Lu et al., 2017; Wen et
al., 2021).

A TDE is set in motion when a star is scattered onto a highly radial orbit
(Frank & Rees, 1976) around a MBH of mass $M_{\bullet}$. Once its pericenter
$R_{\rm p}$ passes within the tidal radius $R_{\rm t}\approx
R_{\star}(M_{\bullet}/M_{\star})^{1/3}$, the star is disrupted (Hills, 1975;
Rees, 1988). Half of the stellar debris eventually returns on highly eccentric
($e\gtrsim 0.99$) but bound orbits, powering a highly luminous flare. While
the hydrodynamic evolution and radiative emission processes in TDEs remain
highly uncertain and hotly debated (see Roth et al. 2020; Bonnerot & Stone
2021 for recent reviews), the last decade of detections has shown that typical
TDEs are blue, quasi-thermal transients of high luminosity (Gezari et al.,
2008b; van Velzen et al., 2011; Gezari et al., 2012; Arcavi et al., 2014).
Typical peak bolometric luminosities range from $L_{\rm BB}\sim
10^{43-44.5}\,{\rm erg\,s}^{-1}$; typical blackbody temperatures range from
$T_{\rm BB}\approx 2-4\times 10^{4}$ K; there is little color evolution over
timescales of weeks-months (Hung et al., 2017; van Velzen et al., 2021).
Despite their high luminosities, TDEs are challenging to discover because of
their low event rate, which is likely $\dot{N}_{\rm TDE}\sim 10^{-4}\,{\rm
galaxy}^{-1}\,{\rm yr}^{-1}$ (Stone & Metzger, 2016; van Velzen, 2018), about
$1\%$ of the core-collapse supernova (CCSN) rate.

The high effective temperatures and low volumetric rates of TDEs make them
ideal targets for ULTRASAT, given the mission’s large grasp and UV
sensitivity. In contrast to other transients of interest for ULTRASAT (e.g.
shock breakout), TDEs evolve slowly, over timescales of days to weeks (Gezari
et al., 2012; Arcavi et al., 2014; Hung et al., 2017), and therefore will
benefit from the low-cadence survey mode.

We now quantify the number of TDEs that ULTRASAT will detect and identify
every year. We emphasize in advance that these estimates are quite approximate
and incorporate significant assumptions on TDE flare populations as well as
unavoidable ambiguities in what counts as a secure identification.

Figure 11: The cumulative number of TDEs detected per year within a given
redshift, $N(<z)$. Colors show the effective blackbody temperatures $T$ of TDE
spectra at peak; we consider the idealized cases of $T=2\times 10^{4}~{}{\rm
K}$ (red), $T=3\times 10^{4}~{}{\rm K}$ (blue), $T=4\times 10^{4}~{}{\rm K}$
(purple). Detection rates are shown assuming a volumetric rate that declines
steeply with $z$ (top panel, dark colors) or one that is constant with $z$
(bottom panel, light colors). In this rate calculation, we consider both the
high-cadence (solid lines) and low-cadence (dashed lines) survey modes. In the
low-cadence calculations, we count as a “detection” every TDE with a peak
magnitude $m\leq 22.5$, while in the high-cadence calculations, we assume
faint exposures over the course of one day are co-added up to a confusion
limit of $m=23.5$.

Figure 12: The differential number of TDEs suitable for spectroscopic followup
detected per year around a certain redshift, ${\rm d}N/{\rm d}z$. Line styles
and colors are the same as in Fig. 11, except that we now only count TDEs with
peak UV magnitude $m\leq 19$ (top panel) or $m\leq 20$ (bottom panel). This
restriction greatly reduces the maximum redshift out to which ULTRASAT will
find TDEs of interest, and represents a factor of $\sim 50-150$ reduction from
the total number of detected TDEs (for the $m\leq 19$ case).

We crudely estimate the limiting luminosity distance for detecting a TDE:

$D_{\rm L}^{\rm max}=\sqrt{\frac{L_{\nu,\rm peak}}{4\pi F_{\nu,\rm lim}}},$
(4)

where $L_{\nu,\rm peak}$ is the peak UV luminosity density of a TDE and
$F_{\nu,\rm lim}$ is the limiting flux density of ULTRASAT. If we consider a
fiducial TDE with a single-temperature blackbody spectrum, an effective
temperature (at peak) $T=2\times 10^{4}~{}{\rm K}$ and peak (bolometric)
luminosity $L_{\rm peak}=10^{44}~{}{\rm erg}~{}{\rm s}^{-1}$, then the peak
luminosity density at the center of the ULTRASAT band (250 nm) is $L_{\nu,\rm
peak}=5.2\times 10^{28}~{}{\rm erg}~{}{\rm s}^{-1}~{}{\rm Hz}^{-1}$.
Considering the low-cadence survey mode with a typical limiting AB magnitude
of $m=22.5$, the UV detection horizon will be cosmological in distance, so we
include K-corrections, and find that $D_{\rm L}^{\rm max}\approx 3$ Gpc, or
$z^{\rm max}\approx 0.6$.

Since TDEs show minimal UV brightness evolution over the course of a few days
(see van Velzen et al. 2020 and Gezari 2021, and references therein), neither
survey mode will be cadence-limited, and the number of TDEs found in a single
survey of duration $\Delta T$ and sky coverage $\Delta\Omega$ will be

$\displaystyle N\approx$ $\displaystyle\frac{\Delta\Omega}{4\pi}\Delta
T\int_{L_{\rm min}}^{L_{\rm max}}{\rm d}L_{\rm peak}\int_{0}^{D_{\rm L}^{\rm
max}(L_{\rm peak})}{\rm d}D_{\rm L}$ $\displaystyle\times 4\pi D_{\rm
L}^{2}(1+z)^{-3}\frac{{\rm d}\dot{n}}{{\rm d}L_{\rm peak}}.$ (5)

Here the extra factor of $(1+z)^{-3}$ converts to an integral over comoving
distance. In the following rate calculations, we will estimate the total
number of TDEs $N$ found during a survey of $\Delta T=1$ yr, considering both
the low-cadence ($\Delta\Omega=6800~{}{\rm deg}^{2}$) and high-cadence
($\Delta\Omega=170~{}{\rm deg}^{2}$) modes of operation. For the low-cadence
survey, we take a limiting AB magnitude of $m_{\rm low}=22.5$ for detection.
For the high-cadence survey, we assume that individual exposures can be co-
added over the course of a single day to increase detection sensitivity. As
$m=22.5$ was the limiting magnitude for a set of exposures with total duration
900 s, we estimate the limiting magnitude for a detection using 21 hours of
stacked observations as $m_{\rm high}=m_{\rm
low}+(5/4)\log_{10}(75600/900)\approx 24.9$. However, ULTRASAT fields will
typically be confusion-limited at magnitudes $m>m_{\rm conf}\approx 23.5$, so
we conservatively assume any TDEs dimmer than $m_{\rm conf}$ will not be
found.

We will approximate the volumetric (and bolometric) TDE luminosity function as

$\frac{{\rm d}\dot{n}}{{\rm d}L_{\rm peak}}=\dot{n}\times\frac{{\rm d}N}{{\rm
d}L_{\rm peak}},$ (6)

where $\dot{n}$ is the volumetric TDE rate, and

$\frac{{\rm d}N}{{\rm d}L_{\rm peak}}=1.5\frac{L_{\rm peak}^{-2.5}}{L_{\rm
min}^{-1.5}-L_{\rm max}^{-1.5}}.$ (7)

This is the empirical bolometric optical/NUV luminosity function fitted by van
Velzen (2018), where $L_{\rm min}$ is the unknown bottom end of the luminosity
function and $L_{\rm max}\approx 10^{45}~{}{\rm erg}~{}{\rm s}^{-1}$ (Leloudas
et al., 2016; van Velzen et al., 2021; Reusch et al., 2022). Based on our
current flux-limited sample, $L_{\rm min}\lesssim 10^{42.5}~{}{\rm
erg\,s}^{-1}$; as these faint TDEs will dominate the total volumetric event
rate, we set $L_{\rm min}=10^{42.5}~{}{\rm erg\,s}^{-1}$ as a conservative
choice. For simplicity, we will convert bolometric luminosities into UV
magnitudes by assuming that every TDE is a blackbody of constant temperature
$T_{\rm BB}$, although we consider three different cases: $T_{\rm
BB}=\\{2,3,4\\}\times 10^{4}~{}{\rm K}$.

A final assumption that enters our calculation concerns the volumetric TDE
rate $\dot{n}(z)$. At low redshift, we take $\dot{n}(0)=3\times 10^{-6}~{}{\rm
Mpc}^{-3}~{}{\rm yr}^{-1}$ (the most conservative choice from the rate
calculations of Stone & Metzger 2016, and a result in reasonable agreement
with the volume-corrected empirical analysis of van Velzen 2018). However, the
redshift evolution of this rate is almost completely unknown. Theoretical
calculations (Kochanek, 2016) suggest that if $\dot{n}$ tracks the volume
density of SMBHs, it will decline steeply with redshift. We consider as an
optimistic case $\dot{n}(z)=\dot{n}(0)$, and as a pessimistic case,
$\dot{n}(z)=\dot{n}(0)/(1+10z)$, which crudely approximates the results of
Kochanek (2016).

The results of our approximate rate calculations are presented in Figure 11,
which shows the cumulative number of TDEs found below a certain redshift. For
the most pessimistic combination of assumptions ($T_{\rm BB}=2\times
10^{4}~{}{\rm K}$; $\dot{n}(z)$ declines with $z$), the high-cadence survey
will detect $N\approx 100$ TDEs per year and the low-cadence survey $N\approx
1500$. For the most optimistic combination of assumptions ($T_{\rm BB}\approx
4\times 10^{4}~{}{\rm K}$; $\dot{n}(z)$ independent of $z$), the high-cadence
survey will detect $N\approx 1400$ TDEs per year and the low-cadence survey
$N\approx 14000$.

These detection rates are enormous, and dwarf the current sample of a few tens
of TDEs (van Velzen et al., 2020). Of course, the number of events that can be
classified as TDEs via photometric and spectroscopic followup will be smaller,
perhaps drastically so. This number depends on the limiting magnitude of
available followup facilities. With commonly available followup resources, we
will be able to spectroscopically follow dozens of TDEs at or brighter than
19th magnitude. A smaller number of spectroscopic instruments will be able to
follow targets peaking at $m\leq 20$. We repeat our calculations using these
two limiting magnitudes (19 and 20) for both the low- and high-cadence fields.
The results are shown in Figure 12. When $m\leq 19$ is used as the relevant
threshold, the low-cadence survey will find $N\approx 32-88$ suitable TDEs per
year across our range of temperature and redshift assumptions, while the high-
cadence survey will struggle to find a single one ($N\approx 0.8-2.2$). When
$m\leq 20$ is used, the low-cadence survey will find $N\approx 103-383$
suitable TDEs per year, and the low-cadence survey will find $N\approx
2.6-9.6$.

ULTRASAT will not be the only active wide-field survey searching for TDEs. At
present, the leader in TDE discovery is the ZTF optical survey, which detects
$\approx 20$ new flares per year (van Velzen et al., 2021), although the
eROSITA X-ray instrument, which has so far found a comparable number (Sazonov
et al., 2021), may ultimately be more productive once a longer temporal
baseline is established for this low-cadence survey (Khabibullin & Sazonov,
2014; Jonker et al., 2020). In the near future, the LSST optical survey will
detect thousands of new TDEs every year (van Velzen et al., 2011), but only a
small minority of these will actually be identified as TDEs from LSST
photometry alone, perhaps as few as $5-10\%$ (Bricman & Gomboc, 2020). Both
the cadence limitations of eROSITA and the wavelength limitations of LSST can
potentially be ameliorated by contemporaneous ULTRASAT coverage of the same
fields. Likewise, the multiwavelength photometry from these other surveys may
help to secure a TDE identification for the more marginal ULTRASAT detections
($m\approx 22.5$) which are inaccessible to spectroscopic confirmation yet
nevertheless dominate the raw detection rate. Joint ULTRASAT-optical
detections will also be highly valuable for identifying nuclear transients, a
task that will be challenging for ULTRASAT-only detections given resolution
limitations.

###  5.8 AGN

The radiation emitted from the central engines of active galactic Nuclei
(AGN), powered by accretion onto supermassive black holes (SMBHs), is known to
vary on all timescales probed, and to peak in the UV regime. Assuming the
canonical geometrically-thin, optically-thick accretion disk framework,
ULTRASAT will be probing the inner parts of AGN accretion disks (10s-100s
gravitational radii) down to dynamical timescales ($\sim$10 hours or less; see
Stern et al. 2018; Trakhtenbrot et al. 2019a, and references therein for
scaling relations). It will also allow to better understand phenomena that
arises from the reprocessing of this “seed” UV radiation in the circumnuclear
gas regions gravitationallly bound to the accreting SMBH.

ULTRASAT is expected to probe significantly large samples of AGNs, thanks to
its wide FoV and high sensitivity, combined with the steep redshift evolution
of the AGN luminosity function. Specifically, at the typical ULTRASAT depth of
$NUV{\simeq}21.5$ AB mag in a single $3\times 300\,{\rm s}$ visit (for
$S/N=10$; see Fig. 6), the sky density of unobscured (broad-line) AGNs is
expected to reach ${\gtrsim}70\,{\rm deg}^{-2}$. This (somewhat conservative)
estimate is based on the $g$-band number counts of confirmed broad-line AGNs
out to $z\approx 2$ (e.g., Richards et al., 2005) and assuming a canonical SED
shape of $f_{\nu}\propto\nu^{-1/2}$ (Vanden Berk et al., 2001), which yields
$NUV\simeq g+0.32$ (neglecting additional foreground extinction). Thus, every
ULTRASAT pointing/FoV is expected to include several thousands of UV-
detectable AGNs. Many of these, and particularly the brighter ones, will be
previously known spectroscopically confirmed quasars (i.e., from the various
SDSS projects, including SDSS-V in the southern hemisphere; Kollmeier et al.
2017).

Below we briefly describe some of the main AGN-related science cases for
ULTRASAT.

To enable some of these research efforts we plan to pursue follow-up
observations in the optical regime, using several facilities. This includes
(robotic) spectroscopy, using the Las Cumbres Observatory 2m telescopes (Sand
et al., 2011), and narrow/medium-band imaging, using a new telescope under
construction at Wise Observatory ($>$15 filters with widths ${\sim}100-400$ Å)
as well as the Pan chromatic Array for Survey Telescopes (PAST; Ofek et al. in
prep).

####  5.8.1 Stochastic variability of persistent AGNs

Multi-epoch imaging surveys of large AGN samples provide a phenomenological
description of their variability, most commonly expressed through the
Structure Function (SF) or the complementary Power Spectrum Distribution
(PSD). Persistent AGN generally vary by ${\sim}$10% over a year, and show
greater (lesser) variability on longer (shorter) timescales. Moreover, the
variability amplitude is anti-correlated with luminosity (at a given
timescale), and there is ambiguous evidence for trends with other properties
(e.g., Vanden Berk et al., 2004; Wilhite et al., 2008; Caplar et al., 2017).

UV variability is known to be higher compared to the optical regime (e.g.,
Meusinger et al., 2011; Hung et al., 2016; Caplar et al., 2017), and it is key
to probing the inner parts of the accretion disks that power AGNs
(particularly on short timescales). Our current understanding of short-
timescales UV variability in AGN is, however rather limited. ULTRASAT will
provide almost continuous observations, with time scales of minutes to months
(4.5 orders of magnitude in time scale) of a large sample of quasars with high
$S/N$ (see above). This will allow us to pursue the following studies, among
others:

##### Quantifying AGN UV variability on short timescales

ULTRASAT will survey the (nearly) uncharted territory of short timescale
variability of “normal”, persistent AGNs (minutes to days). This would allow
to quantify the full distribution of AGN variability in this crucial regime,
and to search for links with basic SMBH properties, such as BH mass, accretion
rate ($L_{\rm AGN}$ or $L/L_{\rm Edd}$), radio jet activity, etc., to yield
insights for accretion flow models.

Specifically, we will be able to construct the ensemble SF (and PSD) of
various groups of AGNs, on all accessible timescales and drawing from all
ULTRASAT surveys. The shortest timescales (minutes-to-hours) are of particular
interest, as explained below. We will be able to compare the resulting SF to
what is known from the optical regime, and specifically test whether the
phenomenological (damped) random walk model, which was suggested to describe
AGN variability in the optical regime, is applicable to the UV regime. The
ensemble SF and PSD can be also constructed in bins of $L_{\rm AGN}$, $M_{\rm
BH}$, and $L/L_{\rm Edd}$, to search for correlations with any of these
properties. This, in turn, can be directly used to test various models for
accretion disk instabilities (see, e.g., Arévalo & Uttley, 2006; Ruan et al.,
2014; Caplar et al., 2017). Understanding the full distribution of variability
is also important for our ability to identify and quantify “extreme”
variability and/or AGN-related transients (see Section 5.8.3 below).

##### Black hole mass from break in power spectrum

Observations suggests that AGN variability is well described by a PSD with a
steep power-law index (e.g., Smith et al., 2018; Caplar et al., 2017, and
references therein). In principle, this power-law should have both high
frequency (“inner”) and low frequency (“outer”) break. Since timescales in the
disk scale with the distance from the central BH, the inner break in the PSD
may reflect the innermost radius of the accretion disk, which in turn scales
linearly with BH mass. Thus, if a high-frequency break in the PSD of AGNs, and
its correlation with $M_{\rm BH}$ are established, this may provide a new tool
to estimate BH masses in distant systems (and perhaps even probe BH spin).

Measuring this inner break likely requires high precision continuous UV
observations, as the UV radiation is emitted from inner-most parts of the disk
(see Springer & Ofek, 2021a). Even in the event that an inner break is found,
but it is not correlated with BH mass, it may provide a new information on
accretion physics in AGNs. Unlike previous studies that focused on the PSD of
the corona-reprocessed X-ray emission (Kelly et al., 2013), ULTRASAT would
focus directly on inner disk itself, exploring a much broader range of
frequencies and possibilities.

####  5.8.2 Agile Reverberation Mapping

The basic premise of reverberation mapping (RM) in AGN is to map the physical
structure of and around the central engine by measuring time lags between
variations in the “seed” (UV-dominated) radiation coming from the inner
accretion disk, and the reprocessed radiation arising from various
circumnuclear gaseous regions. These mainly include the (outer) disk itself
and the broad line region (BLR), but also the dusty “torus” (via NIR RM; e.g.,
Koshida et al. 2014), or the X-ray emitting corona (e.g., Kara et al., 2016).

All RM efforts face the same two key practical challenges. First, most
campaigns focus on the optical regime, while the seed disk radiation is UV-
dominated. This practical choice complicates the measurement with (persistent)
host emission, and perhaps other reprocessing components (e.g., Chelouche et
al., 2019). Second, monitoring a sizable AGN sample for a long period and a
sufficiently high cadence is extremely challenging, although it is clearly
required to ensure that significant variability in both the seed (disk) and
responsive emission components is properly recorded. Photometric RM alleviates
some of these practical challenges, as it allows to robustly measure AGN time
lags through photometric monitoring with various band widths instead of
spectroscopy, as demonstrated by a growing number of studies (see, e.g.,
Chelouche & Zucker, 2013; Chelouche et al., 2014; Ramolla et al., 2018; Kim et
al., 2019b, and additional references below).

ULTRASAT will allow to make great progress in AGN RM studies. It will
continuously monitor the NUV emission of hundreds-to-thousands of luminous