title: Black Bounces with multiple throats and anti-throats

abstract:
  In this work we verify the possibility of building new solutions of
black-bounces with modifications in the area in the context of the general
relativity in four dimensions. These new solutions can present extra structures
such as anti-throats. We see that there are two regions where the area goes to
infinity and depending on the model one of these regions presents curvature
singularities. Regular solutions can be extended to negative values of the
radial coordinate and have a symmetrical structure whereas some singular
solutions cannot be extended and have no symmetrical structure. The energy
conditions are analyzed and, for some solutions, at lest one of the
inequalities in the null energy condition is not respected, in such a way that
the remains energy conditions are violated in some given region. We also
presented solutions that satisfied the null energy condition at lest outside
the event horizon.


title: Graph Auto-Encoders for Network Completion

abstract:
  Completing a graph means inferring the missing nodes and edges from a
partially observed network. Different methods have been proposed to solve this
problem, but none of them employed the pattern similarity of parts of the
graph. In this paper, we propose a model to use the learned pattern of
connections from the observed part of the network based on the Graph
Auto-Encoder technique and generalize these patterns to complete the whole
graph. Our proposed model achieved competitive performance with less
information needed. Empirical analysis of synthetic datasets and real-world
datasets from different domains show that our model can complete the network
with higher accuracy compared with baseline prediction models in most cases.
Furthermore, we also studied the character of the model and found it is
particularly suitable to complete a network that has more complex local
connection patterns.


title:
Real or Virtual: A Video Conferencing Background Manipulation-Detection
  System

abstract:
  Recently, the popularity and wide use of the last-generation video
conferencing technologies created an exponential growth in its market size.
Such technology allows participants in different geographic regions to have a
virtual face-to-face meeting. Additionally, it enables users to employ a
virtual background to conceal their own environment due to privacy concerns or
to reduce distractions, particularly in professional settings. Nevertheless, in
scenarios where the users should not hide their actual locations, they may
mislead other participants by claiming their virtual background as a real one.
Therefore, it is crucial to develop tools and strategies to detect the
authenticity of the considered virtual background. In this paper, we present a
detection strategy to distinguish between real and virtual video conferencing
user backgrounds. We demonstrate that our detector is robust against two attack
scenarios. The first scenario considers the case where the detector is unaware
about the attacks and inn the second scenario, we make the detector aware of
the adversarial attacks, which we refer to Adversarial Multimedia Forensics
(i.e, the forensically-edited frames are included in the training set). Given
the lack of publicly available dataset of virtual and real backgrounds for
video conferencing, we created our own dataset and made them publicly available
[1]. Then, we demonstrate the robustness of our detector against different
adversarial attacks that the adversary considers. Ultimately, our detector's
performance is significant against the CRSPAM1372 [2] features, and
post-processing operations such as geometric transformations with different
quality factors that the attacker may choose. Moreover, our performance results
shows that we can perfectly identify a real from a virtual background with an
accuracy of 99.80%.


title:
A non-singular closed bouncing universe without violation of null energy
  condition

abstract:
  A matter bouncing entropy-corrected cosmological model has been suggested.
The model allows only positive curvature with negative pressure and no
violation of the null energy condition. The result obtained in this paper is
supported by some recent theoretical works where the combination of positive
spatial curvature and vacuum energy leads to non-singular bounces with no
violation of the null energy condition. An important feature of the current
model is that evolutions of the cosmic pressure, energy density and equation of
state parameter are independent of the values of the prefactors $\alpha$ and
$\beta$ in the corrected entropy-area relation. The validity of the classical
and the new nonlinear energy conditions has been discussed. The cosmographic
parameters have been analyzed


title:
Discovering Gateway Ports in Maritime Using Temporal Graph Neural
  Network Port Classification

abstract:
  Vessel navigation is influenced by various factors, such as dynamic
environmental factors that change over time or static features such as vessel
type or depth of the ocean. These dynamic and static navigational factors
impose limitations on vessels, such as long waiting times in regions outside
the actual ports, and we call these waiting regions gateway ports. Identifying
gateway ports and their associated features such as congestion and available
utilities can enhance vessel navigation by planning on fuel optimization or
saving time in cargo operation. In this paper, we propose a novel temporal
graph neural network (TGNN) based port classification method to enable vessels
to discover gateway ports efficiently, thus optimizing their operations. The
proposed method processes vessel trajectory data to build dynamic graphs
capturing spatio-temporal dependencies between a set of static and dynamic
navigational features in the data, and it is evaluated in terms of port
classification accuracy on a real-world data set collected from ten vessels
operating in Halifax, NS, Canada. The experimental results indicate that our
TGNN-based port classification method provides an f-score of 95% in classifying
ports.


title: Ross's second conjecture and supermodular stochastic ordering

abstract:
  This short note discusses open problems and partial solutions related to
Sheldon M Ross's second conjecture about the classical single server queue
subject to a randomly time-varying rate arrival rate.


title:
GDGRU-DTA: Predicting Drug-Target Binding Affinity Based on GNN and
  Double GRU

abstract:
  The work for predicting drug and target affinity(DTA) is crucial for drug
development and repurposing. In this work, we propose a novel method called
GDGRU-DTA to predict the binding affinity between drugs and targets, which is
based on GraphDTA, but we consider that protein sequences are long sequences,
so simple CNN cannot capture the context dependencies in protein sequences
well. Therefore, we improve it by interpreting the protein sequences as time
series and extracting their features using Gate Recurrent Unit(GRU) and
Bidirectional Gate Recurrent Unit(BiGRU). For the drug, our processing method
is similar to that of GraphDTA, but uses two different graph convolution
methods. Subsequently, the representation of drugs and proteins are
concatenated for final prediction. We evaluate the proposed model on two
benchmark datasets. Our model outperforms some state-of-the-art deep learning
methods, and the results demonstrate the feasibility and excellent feature
capture ability of our model.


title: Data Uncertainty without Prediction Models

abstract:
  Data acquisition processes for machine learning are often costly. To
construct a high-performance prediction model with fewer data, a degree of
difficulty in prediction is often deployed as the acquisition function in
adding a new data point. The degree of difficulty is referred to as uncertainty
in prediction models. We propose an uncertainty estimation method named a
Distance-weighted Class Impurity without explicit use of prediction models. We
estimated uncertainty using distances and class impurities around the location,
and compared it with several methods based on prediction models for uncertainty
estimation by active learning tasks. We verified that the Distance-weighted
Class Impurity works effectively regardless of prediction models.


title: Mapping Research Trajectories

abstract:
  Steadily growing amounts of information, such as annually published
scientific papers, have become so large that they elude an extensive manual
analysis. Hence, to maintain an overview, automated methods for the mapping and
visualization of knowledge domains are necessary and important, e.g., for
scientific decision makers. Of particular interest in this field is the
development of research topics of different entities (e.g., scientific authors
and venues) over time. However, existing approaches for their analysis are only
suitable for single entity types, such as venues, and they often do not capture
the research topics or the time dimension in an easily interpretable manner.
  Hence, we propose a principled approach for \emph{mapping research
trajectories}, which is applicable to all kinds of scientific entities that can
be represented by sets of published papers. For this, we transfer ideas and
principles from the geographic visualization domain, specifically trajectory
maps and interactive geographic maps. Our visualizations depict the research
topics of entities over time in a straightforward interpr. manner. They can be
navigated by the user intuitively and restricted to specific elements of
interest. The maps are derived from a corpus of research publications (i.e.,
titles and abstracts) through a combination of unsupervised machine learning
methods.
  In a practical demonstrator application, we exemplify the proposed approach
on a publication corpus from machine learning. We observe that our trajectory
visualizations of 30 top machine learning venues and 1000 major authors in this
field are well interpretable and are consistent with background knowledge drawn
from the entities' publications. Next to producing interactive, interpr.
visualizations supporting different kinds of analyses, our computed
trajectories are suitable for trajectory mining applications in the future.


title: Multi-objective Pointer Network for Combinatorial Optimization

abstract:
  Multi-objective combinatorial optimization problems (MOCOPs), one type of
complex optimization problems, widely exist in various real applications.
Although meta-heuristics have been successfully applied to address MOCOPs, the
calculation time is often much longer. Recently, a number of deep reinforcement
learning (DRL) methods have been proposed to generate approximate optimal
solutions to the combinatorial optimization problems. However, the existing
studies on DRL have seldom focused on MOCOPs. This study proposes a
single-model deep reinforcement learning framework, called multi-objective
Pointer Network (MOPN), where the input structure of PN is effectively improved
so that the single PN is capable of solving MOCOPs. In addition, two training
strategies, based on representative model and transfer learning, respectively,
are proposed to further enhance the performance of MOPN in different
application scenarios. Moreover, compared to classical meta-heuristics, MOPN
only consumes much less time on forward propagation to obtain the Pareto front.
Meanwhile, MOPN is insensitive to problem scale, meaning that a trained MOPN is
able to address MOCOPs with different scales. To verify the performance of
MOPN, extensive experiments are conducted on three multi-objective traveling
salesman problems, in comparison with one state-of-the-art model DRL-MOA and
three classical multi-objective meta-heuristics. Experimental results
demonstrate that the proposed model outperforms all the comparative methods
with only 20\% to 40\% training time of DRL-MOA.


title: Constraining the shape of dark matter haloes with globular clusters

abstract:
  We explore how diffuse stellar light and globular clusters (GCs) can be used
to trace the matter distribution of their host halo using an observational
methodology. For this, we use 117 simulated dark matter (DM) haloes from the
$(34.4~\rm cMpc)^3$ periodic volume of the E-MOSAICS project. For each halo, we
compare the stellar surface brightness and GC projected number density maps to
the surface densities of DM and total mass. We find that the dominant
structures identified in the stellar light and in the GCs correspond closely
with those from the DM and total mass. Our method is unaffected by the presence
of satellites and its precision improves with fainter GC samples. We recover
tight relations between the profiles of stellar surface brightness and GC
number density to those of the DM, suggesting that the profile of DM can be
accurately recovered from the stars and GCs ($\sigma\leq0.5~$dex). We quantify
the projected morphology of DM, stars and GCs, and find that the stars and GCs
are more flattened than the DM. Additionally, the semi-major axes of the
distribution of stars and GCs are typically misaligned by $\sim 10~$degrees
from that of DM. We demonstrate that deep imaging of diffuse stellar light and
GCs can place constraints on the shape, profile and orientation of their host
halo. These results extend down to haloes with central galaxies
$M_{\star}\geq10^{10}~M_{\odot}$, and the analysis will be applicable to future
data from the Euclid, Roman and the Rubin observatories.


title: Radiative transfer in stars by feebly interacting bosons

abstract:
  Starting from first principles, we study radiative transfer by new
feebly-interacting bosons (FIBs) such as axions, axion-like particles (ALPs),
dark photons, and others. Our key simplification is to include only boson
emission or absorption (including decay), but not scattering between different
modes of the radiation field. Based on a given distribution of temperature and
FIB absorption rate in a star, we derive explicit volume-integral expressions
for the boson luminosity, reaching from the free-streaming to the
strong-trapping limit. The latter is seen explicitly to correspond to
quasi-thermal emission from a "FIB sphere" according to the Stefan-Boltzmann
law. Our results supersede expressions and approximations found in the recent
literature on FIB emission from a supernova core and, for radiatively unstable
FIBs, provide explicit expressions for the nonlocal ("ballistic") transfer of
energy recently discussed in horizontal-branch stars.


title:
Transverse charge and current densities in the nucleon from dispersively
  improved chiral effective field theory

abstract:
  Background: The transverse densities $\rho_{1, 2}(b)$ describe the
distributions of electric charge and magnetic moment at fixed light-front time
and connect the nucleon's elastic form factors with its partonic structure. The
dispersive representation of the form factors $F_{1, 2}(t)$ expresses the
densities in terms of exchanges of hadronic states in the $t$-channel and
permits their analysis using hadronic physics methods.
  Purpose: Compute the densities at peripheral distances $b =
\mathcal{O}(M_\pi^{-1})$, where they are generated predominantly by the
two-pion states in the dispersive representation. Quantify the uncertainties.
  Methods: Dispersively improved chiral effective field theory (DI$\chi$EFT) is
used to calculate the isovector spectral functions $\textrm{Im}\, F_{1, 2}(t)$
on the two-pion cut. The method includes $\pi\pi$ interactions ($\rho$
resonance) through elastic unitarity and provides realistic spectral functions
up to $t \approx$ 1 GeV$^2$. Higher-mass states are parametrized by effective
poles and constrained by sum rules (charges, radii, superconvergence
relations). The densities $\rho_{1, 2}(b)$ are obtained from their dispersive
representation. Uncertainties are quantified by varying the spectral functions.
The method respects analyticity and ensures the correct $b \rightarrow \infty$
asymptotic behavior of the densities.
  Results: Accurate densities are obtained at all distances $b \gtrsim 0.5$ fm,
with correct behavior down to $b \rightarrow 0$. The region of distances is
quantified where transverse nucleon structure is governed by the two-pion
state. The light-front current distributions in the polarized nucleon are
computed and discussed.
  Conclusions: Peripheral nucleon structure can be computed from first
principles using DI$\chi$EFT. The method can be extended to generalized parton
distributions and other nucleon form factors.


title:
Constraining high-redshift stellar-mass primordial black holes with
  next-generation ground-based gravitational-wave detectors

abstract:
  The possible existence of primordial black holes in the stellar mass window
has received considerable attention because their mergers may contribute to
current and future gravitational-wave detections. Primordial black hole
mergers, together with mergers of black holes originating from Population~III
stars, are expected to dominate at high redshifts ($z\gtrsim 10$). However the
primordial black hole merger rate density is expected to rise monotonically
with redshift, while Population~III mergers can only occur after the birth of
the first stars. Next-generation gravitational-wave detectors such as Cosmic
Explorer~(CE) and Einstein Telescope~(ET) can access this distinctive feature
in the merger rates as functions of redshift, allowing for a direct measurement
of the abundance of the two populations, and hence for robust constraints on
the abundance of primordial black holes. We simulate four-months worth of data
observed by a CE-ET detector network and perform hierarchical Bayesian analysis
to recover the merger rate densities. We find that if the Universe has no
primordial black holes with masses of $\mathcal{O}(10M_{\odot})$, the projected
upper limit on their abundance $f_{\rm PBH}$ as a fraction of dark matter
energy density may be as low as $f_{\rm PBH}\sim \mathcal{O}({10^{-5}})$, about
two orders of magnitude lower than current upper limits in this mass range. If
instead $f_{\rm PBH}\gtrsim 10^{-4}$, future gravitational wave observations
would exclude $f_{\rm PBH}=0$ at the 95\% credible interval.


title: The Upper Edge of the Neptune Desert Is Stable Against Photoevaporation

abstract:
  Transit surveys indicate that there is a deficit of Neptune-sized planets on
close-in orbits. If this ``Neptune desert' is entirely cleared out by
atmospheric mass loss, then planets at its upper edge should only be marginally
stable against photoevaporation, exhibiting strong outflow signatures in
tracers like the metastable helium triplet. We test this hypothesis by carrying
out a 12-night photometric survey of the metastable helium feature with
Palomar/WIRC, targeting seven gas-giant planets orbiting K-type host stars.
Eight nights of data are analyzed here for the first time along with reanalyses
of four previously-published datasets. We strongly detect helium absorption
signals for WASP-69b, HAT-P-18b, and HAT-P-26b; tentatively detect signals for
WASP-52b and NGTS-5b; and do not detect signals for WASP-177b and WASP-80b. We
interpret these measured excess absorption signals using grids of Parker wind
models to derive mass-loss rates, which are in good agreement with predictions
from the hydrodynamical outflow code ATES for all planets except WASP-52b and
WASP-80b, where our data suggest that the outflows are much smaller than
predicted. Excluding these two planets, the outflows for the rest of the sample
are consistent with a mean energy-limited outflow efficiency of $\varepsilon =
0.41^{+0.16}_{-0.13}$. Even when we make the relatively conservative assumption
that gas-giant planets experience energy-limited outflows at this efficiency
for their entire lives, photoevaporation would still be too inefficient to
carve the upper boundary of the Neptune desert. We conclude that this feature
of the exoplanet population is a pristine tracer of giant planet formation and
migration mechanisms.


title:
Red supergiant stars in binary systems. I. Identification and
  characterisation in the Small Magellanic Cloud from the UVIT ultraviolet
  imaging survey

abstract:
  We aim to identify and characterise binary systems containing red supergiant
(RSG) stars in the Small Magellanic Cloud (SMC) using a newly available
ultraviolet (UV) point source catalogue obtained using the Ultraviolet Imaging
Telescope (UVIT) on board AstroSat. We select a sample of 560 SMC RSGs based on
photometric and spectroscopic observations at optical wavelengths and
cross-match this with the far-UV point source catalogue using the UVIT F172M
filter, finding 88 matches down to m$_{F172M}$=20.3 ABmag, which we interpret
as hot companions to the RSGs. Stellar parameters (luminosities, effective
temperatures and masses) for both components in all 88 binary systems are
determined and we find mass distributions in the ranges 6.1 to 22.3 Solar
masses for RSGs and 3.7 to 15.6 Solar masses for their companions. The most
massive RSG binary system in the SMC has a combined mass of 32 $\pm$4
M$_\odot$, with a mass ratio (q) of 0.92. By simulating observing biases, we
find an intrinsic multipliciy fraction of 18.8 $\pm$ 1.5% for mass ratios in
the range 0.3 < q < 1.0 and orbital periods approximately in the range 3 < log
P [days] < 8. By comparing our results with those of a similar mass on the
main-sequence, we determine the fraction of single stars to be ~20% and argue
that the orbital period distribution declines rapidly beyond log P ~ 3.5. We
study the mass-ratio distribution of RSG binary systems and find that a uniform
distribution best describes the data below 14 M$_\odot$. Above 15 M$_\odot$, we
find a lack of high mass-ratio systems.


title: Mass Renormalization in Lattice Simulations of False Vacuum Decay

abstract:
  False vacuum decay, a quantum mechanical first-order phase transition in
scalar field theories, is an important phenomenon in early universe cosmology.
Recently, a new real-time semi-classical technique based on ensembles of
lattice simulations was introduced to describe false vacuum decay. In this
context, or any other lattice simulation, the effective potential experienced
by long-wavelength modes is not the same as the bare potential. To make
quantitative predictions using the real-time semi-classical techniques, it is
therefore necessary to understand the redefinition of model parameters and the
corresponding deformation of the vacuum state, as well as stochastic
contributions that require modeling of unresolved subgrid modes. In this work,
we focus on the former corrections and compute the expected modification of the
true and false vacuum effective mass, which manifests as a modified dispersion
relationship for linear fluctuations about the vacuum. We compare these
theoretical predictions to numerical simulations and find excellent agreement.
Motivated by this, we use the effective masses to fix the shape of a
parameterized effective potential, and explore the modeling uncertainty
associated with non-linear corrections. We compute the decay rates in both the
Euclidean and real-time formalisms, finding qualitative agreement in the
dependence on the UV cutoff. These calculations further demonstrate that a
quantitative understanding of the rates requires additional corrections.


title:
Model-agnostic interpretation of 10 billion years of cosmic evolution
  traced by BOSS and eBOSS data

abstract:
  We present the first model-agnostic analysis of the complete set of Sloan
Digital Sky Survey III (BOSS) and -IV (eBOSS) catalogues of luminous red galaxy
and quasar clustering in the redshift range $0.2\leq z \leq 2.2$ (10 billion
years of cosmic evolution), which consistently includes the baryon acoustic
oscillations (BAO), redshift space distortions (RSD) and the shape of the
transfer function signatures, from pre- and post-reconstructed catalogues in
Fourier space. This approach complements the standard analyses techniques which
only focus on the BAO and RSD signatures, and the full-modeling approaches
which assume a specific underlying cosmology model to perform the analysis.
These model-independent results can then easily be interpreted in the context
of the cosmological model of choice. In particular, when combined with $z>2.1$
Ly-$\alpha$ BAO measurements, the clustering BAO, RSD and {\it Shape}
parameters can be interpreted within a flat-$\Lambda$CDM model yielding
$h=0.6816\pm0.0067$, $\Omega_{\rm m}=0.3001\pm0.0057$ and $10^{9}\times A_s=
2.43\pm0.20$ (or $\sigma_8=0.858\pm0.036$) with a Big Bang Nucleosynthesis
prior on the baryon density. Without any external dataset, the BOSS and eBOSS
data alone imply $\Omega_{\rm m}=0.2971\pm 0.0061$ and $10^{9}\times
A_s=2.39^{+0.24}_{-0.43}$ (or $\sigma_8=0.857\pm0.040$). For models beyond
$\Lambda$CDM, eBOSS data alone (in combination with Planck) constrain the sum
of neutrino mass to be $\Sigma m_\nu< 0.40$ eV with a BBN prior ($\Sigma m_\nu
<0.082$ eV) at 95\% CL, the curvature energy density to $\Omega_\mathrm{k} =
-0.022_{-0.038}^{+0.032}$ ($\Omega_\mathrm{k} = 0.0015\pm 0.0016$) and the dark
energy equation of state parameter to $w=-0.998_{-0.073}^{+0.085}$
($w=-1.093_{-0.044}^{+0.048}$) at 68\% CL without a BBN prior.


title: Large-Field Inflation and the Cosmological Collider

abstract:
  Large-field inflation is a major class of inflation models featuring a near-
or super-Planckian excursion of the inflaton field. We point out that the large
excursion generically introduces significant scale dependence to spectator
fields through inflaton couplings, which in turn induces characteristic
distortions to the oscillatory shape dependence in the primordial bispectrum
mediated by a spectator field. This so-called cosmological collider signal can
thus be a useful indicator of large field excursions. We show an explicit
example with signals from the "tower states" motivated by the swampland
distance conjecture.


title:
Diagnostics for PopIII galaxies and Direct Collapse Black Holes in the
  early universe

abstract:
  Forthcoming observational facilities will make the exploration of the early
universe routine, likely probing large populations of galaxies at very low
metallicities. It will therefore be important to have diagnostics that can
solidly identify and distinguish different classes of objects in such low
metallicity regimes. We use new photoionisation models to develop diagnostic
diagrams involving various nebular lines. We show that combinations of these
diagrams allow the identification and discrimination of the following classes
of objects in the early universe: PopIII and Direct Collapse Black Holes (DCBH)
in pristine environments, PopIII and DCBH embedded in slightly enriched ISM
(Z~10^{-5}-10^{-4}), (metal poor) PopII and AGN in enriched ISM. Diagnostics
involving rest-frame optical lines (that will be accessible by JWST) have a
better discriminatory power, but also rest-frame UV diagnostics can provide
very useful information. Interestingly, we find that metal lines such as [OIII]
5007A and CIV 1549A can remain relatively strong (about a factor of 0.1-1
relative H-beta and HeII 1640A, respectively), even in extremely metal poor
environments (Z~10^{-5}-10^{-4}), which could be embedding PopIII galaxies and
DCBH.


title:
The physics case for a neutrino lepton collider in light of the CDF W
  mass measurement

abstract:
  We propose a neutrino lepton collider where the neutrino beam is generated
from TeV scale muon decays. Such a device would allow for a precise measurement
of the W mass based on single W production: nu l to W. Although it is
challenging to achieve high instantaneous luminosity with such a collider, we
find that a total luminosity of 0.1/fb can already yield competitive physics
results. In addition to a W mass measurement, a rich variety of physics goals
could be achieved with such a collider, including W boson precision
measurements, heavy leptophilic gauge boson searches, and anomalous Znunu
coupling searches. A neutrino lepton collider is both a novel idea in itself,
and may also be a useful intermediate step, with less muon cooling required,
towards the muon-muon collider already being pursued by the energy frontier
community. A neutrino neutrino or neutrino proton collider may also be
interesting future options for the high energy frontier.


title: Angular Quantization in CFT

abstract:
  The most common quantization scheme in which to study a conformal field
theory is radial quantization, wherein a Hilbert space of states is defined on
a sphere, whose Hamiltonian when mapped to the plane is the dilatation
generator and which boasts a state/operator correspondence. In this paper, we
consider an alternative quantization scheme for 2d CFTs in which the plane is
foliated by constant-angle slices, as opposed to concentric circles, whose
Hamiltonian is the rotation generator. In this angular quantization, there is
no state/operator correspondence but instead an "asymptotics/operator
correspondence". A central feature is that the quantization slice ends on two
operators, and a regulator must be chosen by excising holes around each
operator and imposing suitable boundary conditions such that the holes shrink
to the desired local operators. This angular quantization may be viewed as
constructing CFTs in Minkowski space, or separately as studying non-conformal
(but local) boundary conditions in CFTs. We provide explicit Fock space
constructions for various free 2d CFTs. In addition to the motivation of
applying angular quantization in string theory situations where traditional
radial quantization is insufficient, we comment on its relation to modular
Hamiltonian approaches to entanglement entropy.


title:
Collisional dilemma: Enhancement or damping of fast flavor conversion of
  neutrinos

abstract:
  Fast neutrino flavor conversion can occur in core-collapse supernovae or
compact binary merger remnants when non-forward collisions are also at play,
and neutrinos are not fully decoupled from matter. This work aims to shed light
on the conditions under which fast flavor conversion is enhanced or suppressed
by collisions. By relying on a neutrino toy model with three angular bins in
the absence of spatial inhomogeneities, we consider two angular configurations:
one with the distributions of $\nu_e$ and $\bar\nu_e$ being almost isotropic
(as expected before neutrino decoupling) and the other one with the
distributions of $\nu_e$ and $\bar\nu_e$ being strongly forward peaked (as
expected in the free-streaming regime). By including angle-independent,
direction-changing collisions, we find that collisions are responsible for an
overall enhancement (damping) of flavor conversion in the former (latter)
angular configuration. These opposite outcomes are due to the non-trivial
interplay between collisions, flavor conversion, and the initial angular
distributions of the electron flavors.


title:
On the Viability of Determining Galaxy Properties from Observations I:
  Star Formation Rates and Kinematics

abstract:
  We explore how observations relate to the physical properties of the emitting
galaxies by post-processing a pair of merging $z\sim2$ galaxies from the
cosmological, hydrodynamical simulation NewHorizon using LCARS (Light from
Cloudy Added to RAMSES) to encode the physical properties of the simulated
galaxy into H$\alpha$ emission line. By carrying out mock observations and
analysis on these data cubes we ascertain which physical properties of the
galaxy will be recoverable with the HARMONI spectrograph on the European
Extremely Large Telescope (ELT). We are able to estimate the galaxy's star
formation rate and dynamical mass to a reasonable degree of accuracy, with
values within a factor of $1.81$ and $1.38$ of the true value. The kinematic
structure of the galaxy is also recovered in mock observations. Furthermore, we
are able to recover radial profiles of the velocity dispersion and are
therefore able to calculate how the dynamical ratio varies as a function of
distance from the galaxy centre. Finally, we show that when calculated on
galaxy scales the dynamical ratio does not always provide a reliable measure of
a galaxy's stability against gravity or act as an indicator of a minor merger.


title: Experimental limit on non-linear state-dependent terms in quantum theory

abstract:
  We report the results of an experiment that searches for causal non-linear
state-dependent terms in quantum field theory. Our approach correlates a binary
macroscopic classical voltage with the outcome of a projective measurement of a
quantum bit, prepared in a coherent superposition state. Measurement results
are recorded in a bit string, which is used to control a voltage switch.
Presence of a non-zero voltage reading in cases of no applied voltage is the
experimental signature of a non-linear state-dependent shift of the
electromagnetic field operator. We implement blinded measurement and data
analysis with three control bit strings. Control of systematic effects is
realized by producing one of the control bit strings with a classical
random-bit generator. The other two bit strings are generated by measurements
performed on a superconduting qubit in an IBM Quantum processor, and on a
$^{15}$N nuclear spin in an NV center in diamond. Our measurements find no
evidence for electromagnetic quantum state-dependent non-linearity. We set a
bound on the parameter that quantifies this non-linearity
$|\epsilon_{\gamma}|<4.7\times 10^{-11}$, at 90% confidence level. Within the
Everett many-worlds interpretation of quantum theory, our measurements place
limits on the electromagnetic interaction between different branches of the
universe, created by preparing the qubit in a superposition state.


title: Probing the $\nu_{R}$-philic $Z'$ at DUNE near detectors

abstract:
  We consider a hidden $U(1)$ gauge symmetry under which only the right-handed
neutrinos ($\nu_{R}$) are charged. The corresponding gauge boson is referred to
as the $\nu_{R}$-philic $Z'$. Despite the absence of direct gauge couplings to
ordinary matter at tree level, loop-induced couplings of the $\nu_{R}$-philic
$Z'$ via left-right neutrino mixing can be responsible for its experimental
accessibility. An important feature of the $\nu_{R}$-philic $Z'$ is that its
couplings to neutrinos are generally much larger than its couplings to charged
leptons and quarks, thus providing a particularly interesting scenario for
future neutrino experiments such as DUNE to probe. We consider two approaches
to probe the $\nu_{R}$-philic $Z'$ at DUNE near detectors via (i) searching for
$Z'$ decay signals, and (ii) precision measurement of elastic neutrino-electron
scattering mediated by the $Z'$ boson. We show that the former will have
sensitivity comparable to or better than previous beam dump experiments, while
the latter will improve current limits substantially for large neutrino
couplings.


title:
Ab-initio QCD calculations impact the inference of the
  neutron-star-matter equation of state

abstract:
  We demonstrate that ab-initio calculations in QCD at high densities offer
significant and nontrivial information about the equation of state of matter in
the cores of neutron stars, going beyond that which is obtainable from current
astrophysical observations. We do so by extrapolating the equation of state to
neutron-star densities using a Gaussian process and conditioning it
sequentially with astrophysical observations and QCD input. Using our recent
work, imposing the latter does not require an extrapolation to asymptotically
high density. We find the QCD input to be complementary to the astrophysical
observations, offering strong additional constraints at the highest densities
reached in the cores of neutron stars; with the QCD input, the equation of
state is no longer prior dominated at any density. The QCD input reduces the
pressure and speed of sound at high densities, and it predicts that binary
collisions of equal-mass neutron stars will produce a black hole with greater
than $95\%$ ($68\%$) credence for masses $M \geq 1.38 M_\odot$ ($M \geq 1.25
M_\odot$). We provide a Python implementation of the QCD likelihood function so
that it can be conveniently used within other inference setups.


title:
Comeback Kid: Resilience for Mixed-Critical Wireless Network Resource
  Management

abstract:
  The future sixth generation (6G) of communication systems is envisioned to
provide numerous applications in safety-critical contexts, e.g., driverless
traffic, modular industry, and smart cities, which require outstanding
performance, high reliability and fault tolerance, as well as autonomy.
Ensuring criticality awareness for diverse functional safety applications and
providing fault tolerance in an autonomous manner are essential for future 6G
systems. Therefore, this paper proposes jointly employing the concepts of
resilience and mixed criticality. In this contribution, we conduct physical
layer resource management in cloud-based networks under the rate-splitting
paradigm, which is a promising factor towards achieving high resilience. We
recapitulate the concepts individually, outline a joint metric to measure the
criticality-aware resilience, and verify its merits in a case study. We,
thereby, formulate a non-convex optimization problem, derive an efficient
iterative algorithm, propose four resilience mechanisms differing in quality
and time of adaption, and conduct numerical simulations. Towards this end, a
highly autonomous rate-splitting-enabled physical layer resource management
algorithm for future 6G networks respecting mixed-critical QoS levels and
providing high levels of resilience is proposed. Results emphasize the
appreciable improvements of implementing mixed criticality-aware resilience
under channel outages and strict quality of service (QoS) demands. The
rate-splitting paradigm is particularly shown to overcome state-of-the-art
interference management techniques, and the resilience and throughput adaption
over consecutive outage events reveals the proposed schemes suitability for
future 6G networks.


title: The Decoupled Kinematics of high-z QSO Host Galaxies and their Lya halos

abstract:
  We present a comparison of the interstellar medium traced by [CII] (ALMA),
and ionised halo gas traced by Lya (MUSE), in and around QSO host galaxies at
z~6. To date, 18 QSOs at this redshift have been studied with both MUSE and
high-resolution ALMA imaging; of these, 8 objects display a Lya halo. Using
datacubes matched in velocity resolution, we compare and contrast the spatial
and kinematic information of the Lya halos and the host galaxies' [CII] (and
dust-continuum) emission. We find that the Lya halos extend typically 3-30
times beyond the interstellar medium of the host galaxies. The majority of the
Lya halos do not show ordered motion in their velocity fields, whereas most of
the [CII] velocity fields do. In those cases where a velocity gradient can be
measured in Lya, the kinematics do not align with those derived from the [CII]
emission. This implies that the Lya emission is not tracing the outskirts of a
large rotating disk that is a simple extension of the central galaxy seen in
[CII] emission. It rather suggests that the kinematics of the halo gas are
decoupled from those of the central galaxy. Given the scattering nature of Lya,
these results need to be confirmed with JWST IFU observations that can
constrain the halo kinematics further using the non-resonant Ha line.


title:
Quasiparticle interference as a direct experimental probe of bulk
  odd-frequency superconducting pairing

abstract:
  We show that the quasiparticle interference (QPI) probed by Fourier transform
scanning tunneling microscopy and spectroscopy acts as a direct experimental
probe of bulk odd-frequency superconducting pairing. Taking the example of a
conventional $s$-wave superconductor under applied magnetic field, we show that
the nature of the QPI peaks can only be characterized by including the
odd-frequency pairing correlations generated in this system. In particular, we
identify that the defining feature of odd-frequency pairing gives rise to a
bias asymmetry in the QPI, thus present generically in materials with
odd-frequency pairing.


title: Some post-starburst E+A galaxies are not truly post starburst

abstract:
  Post-starburst E+A galaxies are believed to be systems in a rapid transition
between major merger starbursts and quiescent ellipticals. Their optical
spectrum is dominated by A-type stars, suggesting a significant starburst that
was quenched recently. While optical observations of post-starburst galaxies
suggest little ongoing star formation, they have been shown to host significant
molecular gas reservoirs. This led to the suggestion that gas consumption or
expulsion are not required to end the starburst, and that star formation is
suppressed by turbulent heating of the molecular gas. We present NOEMA
continuum and CO(1-0) observations of 15 post-starburst galaxies, and collect
CO measurements in post-starburst galaxies from the literature. Using archival
far-infrared observations, we show that the majority of these systems host
obscured star formation, with some showing far-infrared emission that is
comparable to those of luminous and ultraluminous infrared galaxies. Once
far-infrared star formation rates are used, these systems show similar
SFR-$M_{\mathrm{H_2}}$ and Kennicutt-Schmidt relations to those observed in
star-forming and starburst galaxies. In particular, there is no need to
hypothesize star formation quenching by processes other than the consumption of
molecular gas by star formation. The combination of optical, far-infrared, and
CO observations indicates that some regions within these galaxies have been
recently quenched, while others are still forming stars at a high rate. We find
little connection between the post-burst age of the optically-thin quenched
regions and the star formation rate in the obscured regions. All this calls
into question the traditional classification of E+A galaxies.


title: Page Curves of Reissner-Nordstr\"om Black Hole in HD Gravity

abstract:
  We obtain the Page curves of an eternal Reissner-Nordstr\"om black hole in
the presence of higher derivative terms in four dimensions. We consider the two
cases: gravitational action with general ${\cal O}(R^2)$ terms plus Maxwell
term and Einstein-Gauss-Bonnet gravity plus Maxwell term. In both the cases
entanglement entropy of the Hawking radiation in the absence of island surface
increases linearly with time. After including contribution from the island
surface, we find that after the Page time entanglement entropy of the Hawking
radiation in both the cases reaches a constant value which is the twice of the
Bekenstein-Hawking entropy of the black hole and we obtain the Page curves.
Further we find that Page curves appear at later or earlier time when the
Gauss-Bonnet coupling increases or decreases. As a consistency check, in the
limit of vanishing GB coupling we obtain the Page curve of the
Reissner-Nordstr\"om black hole obtained in arXiv:2101.06867.


title:
The Nature of Low Surface Brightness Galaxies in the Hyper Suprime-Cam
  Survey

abstract:
  We present the statistical redshift distribution of a large sample of low
surface brightness (LSB) galaxies identified in the first 200 deg$^2$ of the
Hyper Suprime-Cam Strategic Survey Program. Through cross-correlation with the
NASA-SDSS Atlas, we find that the majority of objects lie within z<0.15 or ~
500 Mpc, yielding a mass range of $M_*$ ~ $10^7-10^9$ M_sun and size range of
$r_{\rm{eff,g}}$ ~ 1-8 kpc. We find a peak in the distance distribution within
100 Mpc, corresponding mostly to ~ $10^7$ M_sun galaxies that fall on the known
mass-size relation. There is also a tail in the redshift distribution out to
z~0.15, comprising more massive ($M_*=10^8-10^9$ M_sun) galaxies at the larger
end of our size range. We see tentative evidence that at the higher-mass end
($M_* > 10^8$ M_sun) the LSB galaxies do not form a smooth extension of the
mass-size relation of higher surface brightness galaxies, perhaps suggesting
that the LSB galaxy population is distinct in its formation path.


title: Dust evolution in cosmological simulations

abstract:
  We study the evolution of dust in a cosmological volume using a
hydrodynamical simulation in which the dust production is coupled with the
MUPPI (MUlti Phase Particle Integrator) sub-resolution model of star formation
and feedback. As for the latter, we keep as reference the model setup
calibrated previously to match the general properties of Milky Way like
galaxies in zoom-in simulations. However, we suggest that an increase of the
star formation efficiency with the local dust to gas ratio would better
reproduce the observed evolution of the cosmic star formation density.
Moreover, the paucity of quenched galaxies at low redshift demands a stronger
role of AGN feedback. We tune the parameters ruling direct dust production from
evolved stars and accretion in the inter stellar medium to get scaling
relations involving dust, stellar mass and metallicity in good agreement with
observations. In low mass galaxies the accretion process is inefficient. As a
consequence, they remain poorer in silicate and small grains than higher mass
ones. We reproduce reasonably well the few available data on the radial
distribution of dust outside the galactic region, supporting the assumption
that the dust and gas dynamics are well coupled at galactic scales.


title:
Neutrino secret self-interactions: a booster shot for the cosmic
  neutrino background

abstract:
  Neutrinos might interact among themselves through forces that have so far
remained hidden. Throughout the history of the Universe, such secret
interactions could lead to scatterings between the neutrinos from supernova
explosions and the non-relativistic relic neutrinos left over from the Big
Bang. Such scatterings can boost the cosmic neutrino background (C$\nu$B) to
energies of ${\cal O}$(MeV), making it, in principle, observable in experiments
searching for the diffuse supernova neutrino background. Assuming a
model-independent four-Fermi interaction, we determine the upscattered cosmic
neutrino flux, and derive constraints on such secret interactions from the
latest results from Super-Kamiokande. Furthermore, we also study prospects for
detection of the boosted flux in future lead-based coherent elastic
neutrino-nucleus scattering experiments.


title: Mutually Unbiased Measurements, Hadamard Matrices, and Superdense Coding

abstract:
  Mutually unbiased bases (MUBs) are highly symmetric bases on complex Hilbert
spaces, and the corresponding rank-1 projective measurements are ubiquitous in
quantum information theory. In this work, we study a recently introduced
generalization of MUBs called mutually unbiased measurements (MUMs). These
measurements inherit the essential property of complementarity from MUBs, but
the Hilbert space dimension is no longer required to match the number of
outcomes. This operational complementarity property renders MUMs highly useful
for device-independent quantum information processing. It has been shown that
MUMs are strictly more general than MUBs. In this work we provide a complete
proof of the characterization of MUMs that are direct sums of MUBs. We then
proceed to construct new examples of MUMs that are not direct sums of MUBs. A
crucial technical tool for these construction is a correspondence with
quaternionic Hadamard matrices, which allows us to map known examples of such
matrices to MUMs that are not direct sums of MUBs. Furthermore, we show that --
in stark contrast with MUBs -- the number of MUMs for a fixed outcome number is
unbounded. Next, we focus on the use of MUMs in quantum communication. We
demonstrate how any pair of MUMs with d outcomes defines a d-dimensional
superdense coding protocol. Using MUMs that are not direct sums of MUBs, we
disprove a recent conjecture due to Nayak and Yuen on the rigidity of
superdense coding for infinitely many dimensions.


title: Evolutionary latent space search for driving human portrait generation

abstract:
  This article presents an evolutionary approach for synthetic human portraits
generation based on the latent space exploration of a generative adversarial
network. The idea is to produce different human face images very similar to a
given target portrait. The approach applies StyleGAN2 for portrait generation
and FaceNet for face similarity evaluation. The evolutionary search is based on
exploring the real-coded latent space of StyleGAN2. The main results over both
synthetic and real images indicate that the proposed approach generates
accurate and diverse solutions, which represent realistic human portraits. The
proposed research can contribute to improving the security of face recognition
systems.


title: Monopole Josephson Effects in a Dirac Spin Liquid

abstract:
  Dirac Spin liquids (DSLs) are gapless featureless states, yet interesting by
virtue of the effective field theory describing them -- (2+1)-dimensional
quantum electrodynamics (QED$_3$). Further, a DSL is known to be a "parent
state" of various seemingly unrelated ordered states, such as antiferromagnets
and valence bond solids in the sense that one can obtain ordered states by
condensing magnetic monopoles of the emergent gauge field. Can operators in the
effective field theory, such as the emergent electric field, be externally
induced and measured? In this work, we exploit the parent state picture to
argue that the answer is yes. We propose a range of "monopole Josephson
effects" that arise when two ordered states are separated by a region of the
parent DSL. In particular, we show that one can induce an AC monopole Josephson
effect, which manifests itself as an AC emergent electric field in the spin
liquid, accompanied by a measurable spin current. Further, we show that this AC
emergent electric field can be measured as a sharp tunable peak in Raman
scattering. This work provides a theoretical proof of principle that emergent
gauge fields in spin liquids can be externally induced, manipulated, and probed
using more conventional states, which offers a generic platform for studying
the exotic spin phases.

categories: cond-mat.str-el cond-mat.mes-hall hep-lat hep-th quant-ph


title: Boosting mono-jet searches with model-agnostic machine learning

abstract:
  We show how weakly supervised machine learning can improve the sensitivity of
LHC mono-jet searches to new physics models with anomalous jet dynamics. The
Classification Without Labels (CWoLa) method is used to extract all the
information available from low-level detector information without any reference
to specific new physics models. For the example of a strongly interacting dark
matter model, we employ simulated data to show that the discovery potential of
an existing generic search can be boosted considerably.


title:
How to simulate key properties of lithium-ion batteries with a
  fault-tolerant quantum computer

abstract:
  There is a pressing need to develop new rechargeable battery technologies
that can offer higher energy storage, faster charging, and lower costs. Despite
the success of existing methods for the simulation of battery materials, they
can sometimes fall short of delivering accurate and reliable results. Quantum
computing has been discussed as an avenue to overcome these issues, but only
limited work has been done to outline how they may impact battery simulations.
In this work, we provide a detailed answer to the following question: how can a
quantum computer be used to simulate key properties of a lithium-ion battery?
Based on recently-introduced first-quantization techniques, we lay out an
end-to-end quantum algorithm for calculating equilibrium cell voltages, ionic
mobility, and thermal stability. These can be obtained from ground-state
energies of materials, which is the core calculation executed by the quantum
computer using qubitization-based quantum phase estimation. The algorithm
includes explicit methods for preparing approximate ground states of periodic
materials in first quantization. We bring these insights together to perform
the first estimation of the resources required to implement a quantum algorithm
for simulating a realistic cathode material, dilithium iron silicate.


title:
ProCST: Boosting Semantic Segmentation using Progressive Cyclic
  Style-Transfer

abstract:
  Using synthetic data for training neural networks that achieve good
performance on real-world data is an important task as it has the potential to
reduce the need for costly data annotation. Yet, a network that is trained on
synthetic data alone does not perform well on real data due to the domain gap
between the two. Reducing this gap, also known as domain adaptation, has been
widely studied in recent years. In the unsupervised domain adaptation (UDA)
framework, unlabeled real data is used during training with labeled synthetic
data to obtain a neural network that performs well on real data. In this work,
we focus on image data. For the semantic segmentation task, it has been shown
that performing image-to-image translation from source to target, and then
training a network for segmentation on source annotations - leads to poor
results. Therefore a joint training of both is essential, which has been a
common practice in many techniques. Yet, closing the large domain gap between
the source and the target by directly performing the adaptation between the two
is challenging. In this work, we propose a novel two-stage framework for
improving domain adaptation techniques. In the first step, we progressively
train a multi-scale neural network to perform an initial transfer between the
source data to the target data. We denote the new transformed data as "Source
in Target" (SiT). Then, we use the generated SiT data as the input to any
standard UDA approach. This new data has a reduced domain gap from the desired
target domain, and the applied UDA approach further closes the gap. We
demonstrate the improvement achieved by our framework with two state-of-the-art
methods for semantic segmentation, DAFormer and ProDA, on two UDA tasks, GTA5
to Cityscapes and Synthia to Cityscapes. Code and state-of-the-art checkpoints
of ProCST+DAFormer are provided.


title: Membranes in AdS4 orientifold vacua and their Weak Gravity Conjecture

abstract:
  We study type IIA orientifold compactifications with fluxes that give rise to
perturbatively stable, non-supersymmetric AdS$_4$ vacua with D6-brane gauge
sectors. Non-perturbative instabilities can be mediated by D8-branes wrapped on
the six internal dimensions $X_6$, if they reduce to 4d membranes with a charge
$Q$ larger than its tension $T$. The mismatch $Q \neq T$ arises due to i)
curvature corrections and ii) the BIon backreaction of D6-branes wrapping
3-cycles of $X_6$. We give a simple expression for the second effect in
toroidal orientifolds, and find that only pairs of 3-cycles at SU(2) angles
contribute to it. They either contribute towards $Q>T$ or $Q<T$ depending on
the 3-cycles separation, allowing to engineer 4d $\mathcal{N}=0$ vacua in
tension with the Weak Gravity Conjecture for membranes.


title: Degenerate fermionic matter at N$^3$LO: Quantum Electrodynamics

abstract:
  We determine the pressure of a cold and dense electron gas to a nearly
complete next-to-next-to-next-to-leading order (N$^3$LO) in the fine-structure
constant $\alpha_e$, utilizing a new result for the two-loop photon self-energy
from a companion paper. Our result contains all infrared-sensitive
contributions to the pressure at this order, including the coefficient of the
$O(\alpha_e^3 \ln \alpha_e^{ })$ term, and leaves only a single coefficient
associated with the contributions of unresummed hard momenta undetermined.
Moreover, we explicitly demonstrate the complete cancellation of infrared
divergences according to the effective field theory paradigm by determining
part of the hard contributions at this order. Our calculation provides the
first improvement to a 45-year-old milestone result and demonstrates the
feasibility of the corresponding N$^3$LO calculation for cold and dense quark
matter.


title: Properly learning monotone functions via local reconstruction

abstract:
  We give a $2^{\tilde{O}(\sqrt{n}/\varepsilon)}$-time algorithm for properly
learning monotone Boolean functions under the uniform distribution over
$\{0,1\}^n$. Our algorithm is robust to adversarial label noise and has a
running time nearly matching that of the state-of-the-art improper learning
algorithm of Bshouty and Tamon [BT96] and an information-theoretic lower bound
of [BCO+15]. Prior to this work, no proper learning algorithm with running time
smaller than $2^{\Omega(n)}$ was known to exist.
  The core of our proper learner is a local computation algorithm for sorting
binary labels on a poset. Our algorithm is built on a body of work on
distributed greedy graph algorithms; specifically we rely on a recent work of
Ghaffari and Uitto [GU19], which gives an efficient algorithm for computing
maximal matchings in a graph in the LCA model of [RTVX11, ARVX11]. The
applications of our local sorting algorithm extend beyond learning on the
Boolean cube: we also give a tolerant tester for Boolean functions over general
posets that distinguishes functions that are $\varepsilon/3$-close to monotone
from those that are $\varepsilon$-far. Previous tolerant testers for the
Boolean cube only distinguished between $\varepsilon/\Omega(\sqrt{n})$-close
and $\varepsilon$-far.


title:
The TESS-Keck Survey. XI. Mass Measurements for Four Transiting
  sub-Neptunes orbiting K dwarf TOI-1246

abstract:
  Multi-planet systems are valuable arenas for investigating exoplanet
architectures and comparing planetary siblings. TOI-1246 is one such system,
with a moderately bright K dwarf ($\rm{V=11.6,~K=9.9}$) and four transiting
sub-Neptunes identified by TESS with orbital periods of
$4.31~\rm{d},~5.90~\rm{d},~18.66~\rm{d}$, and $~37.92~\rm{d}$. We collected 130
radial velocity observations with Keck/HIRES and TNG/HARPS-N to measure planet
masses. We refit the 14 sectors of TESS photometry to refine planet radii
($\rm{2.97 \pm 0.06~R_\oplus},\rm{2.47 \pm 0.08~R_\oplus}, \rm{3.46 \pm
0.09~R_\oplus}$, $\rm{3.72 \pm 0.16~R_\oplus}$), and confirm the four planets.
We find that TOI-1246 e is substantially more massive than the three inner
planets ($\rm{8.1 \pm 1.1 M_\oplus}$, $\rm{8.8 \pm 1.2 M_\oplus}$, $\rm{5.3 \pm
1.7 M_\oplus}$, $\rm{14.8 \pm 2.3 M_\oplus}$). The two outer planets, TOI-1246
d and TOI-1246 e, lie near to the 2:1 resonance ($\rm{P_{e}/P_{d}=2.03}$) and
exhibit transit timing variations. TOI-1246 is one of the brightest four-planet
systems, making it amenable for continued observations. It is one of only six
systems with measured masses and radii for all four transiting planets. The
planet densities range from $\rm{0.70 \pm 0.24}$ to $3.21 \pm 0.44
\rm{g/cm^3}$, implying a range of bulk and atmospheric compositions. We also
report a fifth planet candidate found in the RV data with a minimum mass of
25.6 $\pm$ 3.6 $\rm{M_\oplus}$. This planet candidate is exterior to TOI-1246 e
with a candidate period of 93.8 d, and we discuss the implications if it is
confirmed to be planetary in nature.


title:
Gravitational production of dark photon dark matter with mass generated
  by the Higgs mechanism

abstract:
  We study the gravitational production of dark photon dark matter during
inflation, when dark photons acquire mass by the Higgs mechanism. In the
previous study, it was assumed that the dark photon has a St\"uckelberg mass,
or a mass generated by the Higgs mechanism with a sufficiently heavy Higgs
boson. In this paper we consider a case in which the Higgs boson is not fully
decoupled; the Higgs field changes its vacuum expectation value after
inflation. Then, the dark photon mass also changes with time after inflation,
and the time evolution of the longitudinal mode is different from the case with
a St\"{u}ckelberg mass. Consequently, the spectrum of the dark photon energy
density can have two peaks at an intermediate scale and a small scale. We show
that the dark photon can explain the dark matter if its current mass is larger
than $6 \, \mu {\rm eV} \times (H_I / 10^{14} \, {\rm GeV})^{-4}$ and smaller
than $0.8 \, {\rm GeV} \times (H_I / 10^{14} \, {\rm GeV})^{-3/2}$, with $H_I$
being the Hubble parameter during inflation. A higher mass is required if one
considers a larger gauge coupling constant. The result for the St\"uckelberg
mass can be reproduced in the limit of a small gauge coupling constant. We also
comment on the constraints set by various conjectures in quantum gravity
theory.


title: Reinforcement Teaching

abstract:
  We propose Reinforcement Teaching: a framework for meta-learning in which a
teaching policy is learned, through reinforcement, to control a student's
learning process. The student's learning process is modelled as a Markov reward
process and the teacher, with its action-space, interacts with the induced
Markov decision process. We show that, for many learning processes, the
student's learnable parameters form a Markov state. To avoid having the teacher
learn directly from parameters, we propose the Parameter Embedder that learns a
representation of a student's state from its input/output behaviour. Next, we
use learning progress to shape the teacher's reward towards maximizing the
student's performance. To demonstrate the generality of Reinforcement Teaching,
we conducted experiments in which a teacher learns to significantly improve
supervised and reinforcement learners by using a combination of learning
progress reward and a Parameter Embedded state. These results show that
Reinforcement Teaching is not only an expressive framework capable of unifying
different approaches, but also provides meta-learning with the plethora of
tools from reinforcement learning.


title: Quark and Gluon Helicity Evolution at Small $x$: Revised and Updated

abstract:
  We revisit the problem of small Bjorken-$x$ evolution of the gluon and
flavor-singlet quark helicity distributions in the shock wave ($s$-channel)
formalism. Earlier works on the subject in the same framework resulted in an
evolution equation for the gluon field-strength $F^{12}$ and quark "axial
current" ${\bar\psi}\gamma^+\gamma^5\psi$ operators (sandwiched between the
appropriate light-cone Wilson lines) in the double-logarithmic approximation
(DLA: summing powers of $\alpha_s\,\ln^2(1/x)$ with $\alpha_s$ the strong
coupling constant). In this work, we observe that an important mixing of the
above operators with another gluon operator, $\overleftarrow{D}^i\,{D}^i$, also
sandwiched between the light-cone Wilson lines (with the repeated index $i=1,2$
summed over), was missing in the previous works. This operator has the physical
meaning of the sub-eikonal (covariant) phase: its contribution to helicity
evolution is shown to be proportional to another sub-eikonal operator,
$D^i-\overleftarrow{D}^i$, which is related to the Jaffe-Manohar polarized
gluon distribution. In this work we include this operator into small-$x$
helicity evolution, and construct a novel evolution mixing all three operators
($D^i-\overleftarrow{D}^i$, $F^{12}$, and ${\bar\psi}\gamma^+\gamma^5\psi$),
generalizing the previous results. We also construct closed DLA evolution
equations in the large-$N_c$ and large-$N_c\& N_f$ limits, with $N_c$ and $N_f$
the numbers of quark colors and flavors, respectively. Solving the large-$N_c$
equations numerically we obtain the following small-$x$ asymptotics of the
quark and gluon helicity distributions $\Delta \Sigma$ and $\Delta G$, along
with the $g_1$ structure function, \[\Delta\Sigma(x,Q^2)\sim\Delta G(x,Q^2)\sim
g_1(x,Q^2)\sim\left(\frac{1}{x}\right)^{3.66\,\sqrt{\frac{\alpha_s\,N_c}{2\pi}}},\]
in complete agreement with the earlier work by Bartels, Ermolaev and Ryskin.


title:
Influence of invasion on natural selection in dispersal-structured
  populations

abstract:
  We investigate how initial and boundary conditions influence the competition
dynamics and outcome in dispersal-structured populations. The study is carried
out through numerical modeling of the heterogeneous Brownian bugs model, in
which individuals are characterized by diversified diffusion coefficients and
compete for resources within a finite interaction range. We observed that if
instead of being distributed randomly across the domain the population is
initially localized within a small region, the dynamics and the stationary
state of the system differ significantly. The outcome of the natural selection
is determined by different competition processes, fluctuations, and spreading
of the organisms.


title: Towards a Geometry and Analysis for Bayesian Mechanics

abstract:
  In this paper, a simple case of Bayesian mechanics under the free energy
principle is formulated in axiomatic terms. We argue that any dynamical system
with constraints on its dynamics necessarily looks as though it is performing
inference against these constraints, and that in a non-isolated system, such
constraints imply external environmental variables embedding the system. Using
aspects of classical dynamical systems theory in statistical mechanics, we show
that this inference is equivalent to a gradient ascent on the Shannon entropy
functional, recovering an approximate Bayesian inference under a locally
ergodic probability measure on the state space. We also use some geometric
notions from dynamical systems theory$\unicode{x2014}$namely, that the
constraints constitute a gauge degree of freedom$\unicode{x2014}$to elaborate
on how the desire to stay self-organised can be read as a gauge force acting on
the system. In doing so, a number of results of independent interest are given.
Overall, we provide a related, but alternative, formalism to those driven
purely by descriptions of random dynamical systems, and take a further step
towards a comprehensive statement of the physics of self-organisation in formal
mathematical language.

categories: math-ph cond-mat.stat-mech math.DS math.MP nlin.AO physics.bio-ph


title: Bootstrapping a Stress-Tensor Form Factor through Eight Loops

abstract:
  We bootstrap the three-point form factor of the chiral stress-tensor
multiplet in planar $\mathcal{N}=4$ supersymmetric Yang-Mills theory at six,
seven, and eight loops, using boundary data from the form factor operator
product expansion. This may represent the highest perturbative order to which
multi-variate quantities in a unitary four-dimensional quantum field theory
have been computed. In computing this form factor, we observe and employ new
restrictions on pairs and triples of adjacent letters in the symbol. We provide
details about the function space required to describe the form factor through
eight loops. Plotting the results on various lines provides striking numerical
evidence for a finite radius of convergence of perturbation theory. By the
principle of maximal transcendentality, our results are expected to give the
highest weight part of the $g g \rightarrow H g$ and $H \rightarrow ggg$
amplitudes in the heavy-top limit of QCD through eight loops. These results
were also recently used to discover a new antipodal duality between this form
factor and a six-point amplitude in the same theory.


title: Learning First-Order Symbolic Planning Representations That Are Grounded

abstract:
  Two main approaches have been developed for learning first-order planning
(action) models from unstructured data: combinatorial approaches that yield
crisp action schemas from the structure of the state space, and deep learning
approaches that produce action schemas from states represented by images. A
benefit of the former approach is that the learned action schemas are similar
to those that can be written by hand; a benefit of the latter is that the
learned representations (predicates) are grounded on the images, and as a
result, new instances can be given in terms of images. In this work, we develop
a new formulation for learning crisp first-order planning models that are
grounded on parsed images, a step to combine the benefits of the two
approaches. Parsed images are assumed to be given in a simple O2D language
(objects in 2D) that involves a small number of unary and binary predicates
like "left", "above", "shape", etc. After learning, new planning instances can
be given in terms of pairs of parsed images, one for the initial situation and
the other for the goal. Learning and planning experiments are reported for
several domains including Blocks, Sokoban, IPC Grid, and Hanoi.


title: Supersymmetric $dS_n$ solutions for $n \geq 5$ in $D=11$ supergravity

abstract:
  We determine the necessary and sufficient conditions for warped product
$dS_n$ solutions, $5 \leq n \leq 10$, to preserve supersymmetry in $D=11$
supergravity, without assuming factorization of the Killing spinors. We prove
that for $7 \leq n \leq 10$, all such solutions are flat, with vanishing
4-form. We also show that the only warped product $dS_6$ solutions are either
the maximally supersymmetric $AdS_7 \times S^4$ solution, or $\mathbb{R}^{1,6}
\times N_4$ where $N_4$ is hyperKahler, with vanishing 4-form. Supersymmetric
warped product $dS_5$ solutions are then classified; it is shown that all such
solutions are generalized M5-brane configurations, for which the transverse
space is $\mathbb{R} \times N_4$, and $N_4$ is a hyperKahler manifold. If the
4-form is covariantly constant, then $N_4$ admits a hyperKahler potential.


title:
Neural network representation for minimally entangled typical thermal
  states

abstract:
  Minimally entangled typical thermal states (METTS) are a construction that
allows one to to solve for the imaginary time evolution of quantum many body
systems. By using wave functions that are weakly entangled, one can take
advantage of efficient representations in the form of matrix product states. We
generalize these ideas to arbitrary variational wave functions and we focus, as
illustration, on the particular case of restricted Boltzmann machines. The
imaginary time evolution is carried out using stochastic reconfiguration
(natural gradient descent), combined with Monte Carlo sampling. Since the time
evolution takes place on the tangent space, deviations between the actual path
in the Hilbert space and the trajectory on the variational manifold can be
important, depending on the internal structure and expressivity of the
variational states. We show how these differences translate into a rescaled
temperature and demonstrate the application of the method to quantum spin
systems in one and two spatial dimensions.


title: An open-source linear program for testing nonclassicality

abstract:
  The gold standard for demonstrating that an experiment resists any classical
explanation is to show that its statistics violate generalized
noncontextuality. We here provide an open-source linear program for testing
whether or not any given prepare-measure experiment is classically-explainable
in this sense. The input to the program is simply an arbitrary set of quantum
states and an arbitrary set of quantum effects; the program then determines if
the Born rule statistics generated by all pairs of these can be explained by a
classical (noncontextual) model. If a classical model exists, it provides an
explicit model. If it does not, then it computes the minimal amount of noise
that must be added such that a model does exist, and then provides this model.
We generalize all these results to arbitrary generalized probabilistic theories
(and accessible fragments thereof) as well; indeed, our linear program is a
test of simplex-embeddability.


title: Clogging, Diode and Collective Effects of Skyrmions in Funnel Geometries

abstract:
  Using a particle-based model, we examine the collective dynamics of skyrmions
interacting with a funnel potential under dc driving as the skyrmion density
and relative strength of the Magnus and damping terms are varied. For driving
in the easy direction, we find that increasing the skyrmion density reduces the
average skyrmion velocity due to jamming of skyrmions near the funnel opening,
while the Magnus force causes skyrmions to accumulate on one side of the funnel
array. For driving in the hard direction, there is a critical skyrmion density
below which the skyrmions become trapped. Above this critical value, a clogging
effect appears with multiple depinning and repinning states where the skyrmions
can rearrange into different clogged configurations, while at higher drives,
the velocity-force curves become continuous. When skyrmions pile up near the
funnel opening, the effective size of the opening is reduced and the passage of
other skyrmions is blocked by the repulsive skyrmion-skyrmion interactions. We
observe a strong diode effect in which the critical depinning force is higher
and the velocity response is smaller for hard direction driving. As the ratio
of Magnus force to dissipative term is varied, the skyrmion velocity varies in
a non-linear and non-monotonic way due to the pile up of skyrmions on one side
of the funnels. At high Magnus forces, the clogging effect for hard direction
driving is diminished.


title:
Addendum to: Towards next-to-next-to-leading-log accuracy for the width
  difference in the $\mathbf{B_s-\bar{B}_s}$ system: fermionic contributions to
  order $\mathbf{(m_c/m_b)^0}$ and $\mathbf{(m_c/m_b)^1}$

abstract:
  We calculate the three-loop master integrals of Ref. [1] [arXiv:1709.02160]
in analytic form. This allows us to present the fermionic contributions to the
$\Delta B=2$ Wilson coefficients of the $B$-$\bar B$ decay matrix in
next-to-next-to-leading order of QCD with full analytic dependence on the mass
of the charm quark in the fermionic loops.


title:
Comparison study of the combination of the SPSA algorithm and the PSO
  algorithm

abstract:
  Particle swarm optimization (PSO) is attracting an ever-growing attention and
more than ever it has found many application areas for many challenging
optimization problems. It is, however, a known fact that PSO has a severe
drawback in the update of its global best (gbest) particle, which has a crucial
role of guiding the rest of the swarm. In this paper, we propose three
efficient solutions to remedy this problem using the SPSA Algorithm. In the
first approach, gbest is updated with respect to a global estimation of the
gradient and can avoid getting trapped into a local optimum. The second
approach is based on the formation of an alternative or artificial global best
particle, the so-called aGB, which can replace the native gbest particle for a
better guidance, the decision of which is held by a fair competition between
the two. The third approach is based on the update of the swarm particle. For
this purpose we use simultaneous perturbation stochastic approximation (SPSA)
for its low cost. Since SPSA is applied only to the gbest (not to the entire
swarm) or to the entire swarm, both approaches result thus in a negligible
overhead cost for the entire PSO process. Both approaches are shown to
significantly improve the performance of PSO over a wide range of non-linear
functions, especially if SPSA and PSO parameters are well selected to fit the
problem at hand. As in the basic PSO application, experimental results show
that the proposed approaches significantly improved the quality of the
Optimization process as measured by a statistic analysis.


title:
How can NLP Help Revitalize Endangered Languages? A Case Study and
  Roadmap for the Cherokee Language

abstract:
  More than 43% of the languages spoken in the world are endangered, and
language loss currently occurs at an accelerated rate because of globalization
and neocolonialism. Saving and revitalizing endangered languages has become
very important for maintaining the cultural diversity on our planet. In this
work, we focus on discussing how NLP can help revitalize endangered languages.
We first suggest three principles that may help NLP practitioners to foster
mutual understanding and collaboration with language communities, and we
discuss three ways in which NLP can potentially assist in language education.
We then take Cherokee, a severely-endangered Native American language, as a
case study. After reviewing the language's history, linguistic features, and
existing resources, we (in collaboration with Cherokee community members)
arrive at a few meaningful ways NLP practitioners can collaborate with
community partners. We suggest two approaches to enrich the Cherokee language's
resources with machine-in-the-loop processing, and discuss several NLP tools
that people from the Cherokee community have shown interest in. We hope that
our work serves not only to inform the NLP community about Cherokee, but also
to provide inspiration for future work on endangered languages in general. Our
code and data will be open-sourced at
https://github.com/ZhangShiyue/RevitalizeCherokee


title:
Integrating Reward Maximization and Population Estimation: Sequential
  Decision-Making for Internal Revenue Service Audit Selection

abstract:
  We introduce a new setting, optimize-and-estimate structured bandits. Here, a
policy must select a batch of arms, each characterized by its own context, that
would allow it to both maximize reward and maintain an accurate (ideally
unbiased) population estimate of the reward. This setting is inherent to many
public and private sector applications and often requires handling delayed
feedback, small data, and distribution shifts. We demonstrate its importance on
real data from the United States Internal Revenue Service (IRS). The IRS
performs yearly audits of the tax base. Two of its most important objectives
are to identify suspected misreporting and to estimate the "tax gap" - the
global difference between the amount paid and true amount owed. We cast these
two processes as a unified optimize-and-estimate structured bandit. We provide
a novel mechanism for unbiased population estimation that achieves rewards
comparable to baseline approaches. This approach has the potential to improve
audit efficacy, while maintaining policy-relevant estimates of the tax gap.
This has important social consequences given that the current tax gap is
estimated at nearly half a trillion dollars. We suggest that this problem
setting is fertile ground for further research and we highlight its interesting
challenges.


title: DArch: Dental Arch Prior-assisted 3D Tooth Instance Segmentation

abstract:
  Automatic tooth instance segmentation on 3D dental models is a fundamental
task for computer-aided orthodontic treatments. Existing learning-based methods
rely heavily on expensive point-wise annotations. To alleviate this problem, we
are the first to explore a low-cost annotation way for 3D tooth instance
segmentation, i.e., labeling all tooth centroids and only a few teeth for each
dental model. Regarding the challenge when only weak annotation is provided, we
present a dental arch prior-assisted 3D tooth segmentation method, namely
DArch. Our DArch consists of two stages, including tooth centroid detection and
tooth instance segmentation. Accurately detecting the tooth centroids can help
locate the individual tooth, thus benefiting the segmentation. Thus, our DArch
proposes to leverage the dental arch prior to assist the detection.
Specifically, we firstly propose a coarse-to-fine method to estimate the dental
arch, in which the dental arch is initially generated by Bezier curve
regression, and then a graph-based convolutional network (GCN) is trained to
refine it. With the estimated dental arch, we then propose a novel Arch-aware
Point Sampling (APS) method to assist the tooth centroid proposal generation.
Meantime, a segmentor is independently trained using a patch-based training
strategy, aiming to segment a tooth instance from a 3D patch centered at the
tooth centroid. Experimental results on $4,773$ dental models have shown our
DArch can accurately segment each tooth of a dental model, and its performance
is superior to the state-of-the-art methods.


title: A density-constrained model for Chemotaxis

abstract:
  We consider a model of congestion dynamics with chemotaxis: The density of
cells follows a chemical signal it generates, while subject to an
incompressibility constraint. The incompressibility constraint results in the
formation of patches, describing regions where the maximal density has been
reached. The dynamics of these patches can be described by either Hele-Shaw or
Richards equation type flow (depending on whether we consider the model with
diffusion or the model with pure advection). Our focus in this paper is on the
construction of weak solutions for this problem via a variational discrete time
scheme of JKO type. We also establish the uniqueness of these solutions. In
addition, we make more rigorous the connection between this incompressible
chemotaxis model and the free boundary problems describing the motion of the
patches in terms of the density and associated pressure variable. In
particular, we obtain new results characterizing the pressure variable as the
solution of an obstacle problem and prove that in the pure advection case the
dynamic preserves patches.


title:
And then they were two: detection of non-thermal radio emission from the
  bow shocks of two runaway stars

abstract:
  Winds from massive stars have recently been deemed promising sites for
investigating relativistic particle acceleration. Particularly, the resulting
bow shock from the interaction of the winds of runaway stars with interstellar
matter has been observed at multiple wavelengths. Here we investigate the O4If
star, BD+433654, the bow shock of which is, so far, the only one proven to
radiate both thermally and non-thermally at radio frequencies. We also consider
NGC7635 as a bow shock candidate and examine its apex for indications of
thermal and non-thermal radio emission. We observed both sources with the VLA
at 4-8 GHz and 8-12 GHz, and with the Effelsberg telescope at 4-8 GHz. We
analysed data from both telescopes individually and combined, obtained their
spectral index maps and calculated their Spectral Energy Distributions. We
present the first high-resolution maps of radio emission from NGC7635. We find
that both emit non-thermal emission in the radio regime, with the clearest
evidence for NGC7635. Our results are less conclusive for BD+433654, as the
emission from its bow shock becomes weaker and fainter at higher radio
frequencies. Our results extend the previous radio results for the BD+433654
bow shock to higher frequencies. Modelling of our data for both sources shows
that accelerated electrons at the wind termination shock are a plausible source
for the non-thermal radio emission, but energetics arguments suggest that any
non-thermal X-ray and $\gamma$-ray emission could be significantly below
existing upper limits. Enhanced synchrotron emission from compressed Galactic
cosmic rays in the radiative bow shock could also explain the radio emission
from the BD+433654 bow shock but not NGC7635. Non-detection of point-like radio
emission from BD+433654 puts an upper limit on the mass-loss rate of the star
that is lower than values quoted in the literature. [abridged]


title: Generating and Visualizing Trace Link Explanations

abstract:
  Recent breakthroughs in deep-learning (DL) approaches have resulted in the
dynamic generation of trace links that are far more accurate than was
previously possible. However, DL-generated links lack clear explanations, and
therefore non-experts in the domain can find it difficult to understand the
underlying semantics of the link, making it hard for them to evaluate the
link's correctness or suitability for a specific software engineering task. In
this paper we present a novel NLP pipeline for generating and visualizing trace
link explanations. Our approach identifies domain-specific concepts, retrieves
a corpus of concept-related sentences, mines concept definitions and usage
examples, and identifies relations between cross-artifact concepts in order to
explain the links. It applies a post-processing step to prioritize the most
likely acronyms and definitions and to eliminate non-relevant ones. We evaluate
our approach using project artifacts from three different domains of
interstellar telescopes, positive train control, and electronic health-care
systems, and then report coverage, correctness, and potential utility of the
generated definitions. We design and utilize an explanation interface which
leverages concept definitions and relations to visualize and explain trace link
rationales, and we report results from a user study that was conducted to
evaluate the effectiveness of the explanation interface. Results show that the
explanations presented in the interface helped non-experts to understand the
underlying semantics of a trace link and improved their ability to vet the
correctness of the link.


title: K-matrix Analysis of $e^+e^-$ Annihilation in the Bottomonium Region

abstract:
  We perform the first global and unitary analysis of $e^+e^-\to b\bar{b}$
cross sections. We analyze exclusive cross sections in the $B\bar{B}$, $B^*
\bar{B}(+c.c.)$, $B^*\bar{B}^*$, $B_s^*\bar{B}_s^*$, $\Upsilon(nS)\pi^+\pi^-$
and $h_b(nP)\pi^+\pi^-$ channels as well as the total inclusive cross section
for $b\bar{b}$ production. Pole positions and residues are determined for four
vector states, which we associate with the $\Upsilon(4S)$, $\Upsilon(10750)$,
$\Upsilon(5S)$ (or $\Upsilon(10860)$), and $\Upsilon(6S)$ (or
$\Upsilon(11020)$). We find strong evidence for the new $\Upsilon(10750)$
recently claimed by Belle, although with parameters not well constrained by the
data. Results presented here cast doubt on the validity of branching ratios
reported earlier using Breit-Wigner parameterizations or ratios of cross
sections. We also compare our results with a selection of theoretical
calculations for the vector bottomonium spectrum.


title: Non-exactness of toric Poisson structures

abstract:
  We prove that a Poisson structure on a projective toric variety which is
invariant by the torus action and whose symplectic leaves are the torus orbits
is not exact. This is deduced from a geometric criterion for non-exactness of
Poisson structures with a finite number of symplectic leaves.


title: Density-constrained Chemotaxis and Hele-Shaw flow

abstract:
  We consider a model of congestion dynamics with chemotaxis, where the density
of cells follows the chemical signal it generates, while observing an
incompressibility constraint. We show that when the chemical diffuses slowly
and attracts the cells strongly, then the dynamics of the congested cells is
well approximated by a surface-tension driven free boundary problem. More
precisely, we show that in this limit the density of cell converges to the
characteristic function of a set whose evolution is described by a Hele-Shaw
free boundary problem with surface tension. Our problem is set in a bounded
domain, which leads to an interesting analysis on the limiting boundary
conditions for the density function. Namely, we prove that the assumption of
Robin boundary conditions for the chemical potential leads to a contact angle
condition for the free interface.


title:
Google Scanned Objects: A High-Quality Dataset of 3D Scanned Household
  Items

abstract:
  Interactive 3D simulations have enabled breakthroughs in robotics and
computer vision, but simulating the broad diversity of environments needed for
deep learning requires large corpora of photo-realistic 3D object models. To
address this need, we present Google Scanned Objects, an open-source collection
of over one thousand 3D-scanned household items released under a Creative
Commons license; these models are preprocessed for use in Ignition Gazebo and
the Bullet simulation platforms, but are easily adaptable to other simulators.
We describe our object scanning and curation pipeline, then provide statistics
about the contents of the dataset and its usage. We hope that the diversity,
quality, and flexibility of Google Scanned Objects will lead to advances in
interactive simulation, synthetic perception, and robotic learning.


title:
Applications of ferroelectric materials for dark matter axions detection
  haloscopes

abstract:
  Tuning is an essential requirement for the search of dark matter axions
employing haloscopes, since its mass is not known yet to the scientific
community. At the present day, most haloscope tuning systems are based on
mechanical devices, which can lead to failures due to the complexity of the
environment in which they are used. However, the electronic tuning making use
of ferroelectric materials can provide a path that is less vulnerable to
mechanical failures and thus complements and expands current tuning systems. In
this work, we present and design several ideas for using the ferroelectric
$KTaO_3$ material as a tuning element in haloscopes based on coupled cavities.
On the other hand, the structures used in the Relic Axion Detector Exploratory
Setup (RADES) group are based on several cavities that are connected by
metallic irises, which act as interresonator coupling elements. In this
article, we also show how to use these $KTaO_3$ films as interresonator
couplings between cavities, instead of inductive or capacitive metallic
windows. These two concepts represent a crucial upgrade over the current
systems employed in the axion community. The theoretical results demonstrate
the interest of the novel concepts proposed for the use of this kind of
ferroelectric media in the search for dark matter axions.


title:
Quo Vadis, Optical Network Architecture? Towards an
  Optical-processing-enabled Paradigm

abstract:
  Among various aspects in optical network architectures, handling transit
traffic at intermediate nodes represents a defining characteristic for
classification. In this context, the transition from the first generation of
optical-electrical-optical (O-E-O) mode to the second generation of
optical-bypass marked a paradigm shift in redesigning optical transport
networks towards greater network efficiency. Optical-bypass operation has then
become the \textit{de facto} approach adopted by the majority of carriers in
both metro and backbone networks in the last two decades and has remained
basically unchanged. However, in optical-bypass network, the fact that
in-transit lightpaths crossing a common intermediate node must be separated in
either time, frequency or spatial domain to avoid adversarial interference
appears to be a critical shortcoming as the interaction of such lightpaths in
optical domain may result in efficient computing and/or signal processing
operations for saving spectral resources. Inspired by the accelerated
progresses in optical signal processing technologies and the integration of
computing and communications, we introduce in this paper a new architectural
paradigm for future optical networks and highlight how this new architecture
has the potential to shatter the \textit{status quo}. Indeed, our proposal is
centered on exploiting the superposition of in-transit lightpaths at
intermediate nodes to generate more spectrally efficient lightpaths and how to
harness this opportunity from network design perspectives. We present two case
studies featuring optical aggregation and optical XOR encoding to demonstrate
the merit of optical-processing-enabled operation compared to its counterpart,
optical-bypass. Numerical results on realistic network typologies are provided,
revealing that a spectral saving up to $30\%$ could be achieved thanks to
adopting optical-processing network.


title:
Logarithmic improvements in the Weyl law and exponential bounds on the
  number of closed geodesics are predominant

abstract:
  Let $M$ be a smooth compact manifold of dimension $d$ without boundary. We
introduce the concept of predominance for Riemannian metrics on $M$, a notion
analogous to full Lebesgue measure which, in particular, implies density. We
show that for a predominant metric, the number of closed geodesics of length
smaller than $T$ has a stretched exponential upper bound in $T$.
  In addition, we study remainders in the Weyl law for predominant metrics. The
Weyl law states that the number of Laplace-Beltrami eigenvalues smaller than
$\lambda^2$ is asymptotic to $C\lambda^d$ with an $O(\lambda^{d-1})$ error. We
show that, for a predominant metric, the estimate on the error can by improved
by a power of $\log \lambda$. After an application of recent results of the
authors in the case of the Weyl law, these estimates follow from a study of the
non-degeneracy properties of nearly closed orbits for predominant sets of
metrics.

categories: math.DS math-ph math.AP math.DG math.MP math.SP


title:
Super-Prompting: Utilizing Model-Independent Contextual Data to Reduce
  Data Annotation Required in Visual Commonsense Tasks

abstract:
  Pre-trained language models have shown excellent results in few-shot learning
scenarios using in-context learning. Although it is impressive, the size of
language models can be prohibitive to make them usable in on-device
applications, such as sensors or smartphones. With smaller language models,
task-specific data annotation is needed to fine-tune the language model for a
specific purpose. However, data annotation can have a substantial financial and
time burden for small research groups, startups, and even companies. In this
paper, we analyze different prompt-based fine-tuning techniques to improve
results on both language and multimodal causal transformer models. To evaluate
our results, we use a dataset focusing on visual commonsense reasoning in time.
Our results show that by simple model-agnostic prompt-based fine-tuning,
comparable results can be reached by only using 35%-40% of the fine-tuning
training dataset. The proposed approaches result in significant time and
financial savings. As the proposed methods make minimal architectural
assumptions, other researchers can use the results in their transformer models
with minimal adaptations. We plan to release the source code freely to make it
easier for the community to use and contribute to our work.


title:
Sparse-Dense Motion Modelling and Tracking for Manipulation without
  Prior Object Models

abstract:
  This work presents an approach for modelling and tracking previously unseen
objects for robotic grasping tasks. Using the motion of objects in a scene, our
approach segments rigid entities from the scene and continuously tracks them to
create a dense and sparse model of the object and the environment. While the
dense tracking enables interaction with these models, the sparse tracking makes
this robust against fast movements and allows to redetect already modelled
objects.
  The evaluation on a dual-arm grasping task demonstrates that our approach 1)
enables a robot to detect new objects online without a prior model and to grasp
these objects using only a simple parameterisable geometric representation, and
2) is much more robust compared to the state of the art methods.


title:
Learning High-Dimensional McKean-Vlasov Forward-Backward Stochastic
  Differential Equations with General Distribution Dependence

abstract:
  One of the core problems in mean-field control and mean-field games is to
solve the corresponding McKean-Vlasov forward-backward stochastic differential
equations (MV-FBSDEs). Most existing methods are tailored to special cases in
which the mean-field interaction only depends on expectation or other moments
and thus inadequate to solve problems when the mean-field interaction has full
distribution dependence. In this paper, we propose a novel deep learning method
for computing MV-FBSDEs with a general form of mean-field interactions.
Specifically, built on fictitious play, we recast the problem into repeatedly
solving standard FBSDEs with explicit coefficient functions. These coefficient
functions are used to approximate the MV-FBSDEs' model coefficients with full
distribution dependence, and are updated by solving another supervising
learning problem using training data simulated from the last iteration's FBSDE
solutions. We use deep neural networks to solve standard BSDEs and approximate
coefficient functions in order to solve high-dimensional MV-FBSDEs. Under
proper assumptions on the learned functions, we prove that the convergence of
the proposed method is free of the curse of dimensionality (CoD) by using the
generalized maximum mean discrepancy metric previously developed in [Han, Hu
and Long, arXiv:2104.12036]. The proved theorem shows the advantage of the
method in high dimensions. We present the numerical performance in
high-dimensional MV-FBSDE problems, including a mean-field game example of the
well-known Cucker-Smale model whose cost depends on the full distribution of
the forward process.


title:
Structural and electronic properties of rare earth chromites: A
  computational and experimental study

abstract:
  In this work, the structural, optical, and electronic properties of
rare-earth perovskites of the general formula RCrO3, where R represents the
rare-earth Gd, Tb, Dy, Ho, Er, and Tm, have been studied in detail. These
compounds were synthesized through a facile citrate route. X-ray diffraction,
Raman spectroscopy, and UV-Vis spectroscopy were used to reveal the structural
evolutions in RCrO3. The lattice parameter, Cr3+-O2--Cr3+ bond angle, and CrO6
octahedral distortions were found to strongly depend on the ionic radii of the
rare-earth element. First-principles calculations based on density-functional
theory within the generalized gradient approximation (GGA) of Perdew- Burke-
Ernzerhof (PBE) and strongly constrained-and-appropriately normed (SCAN)
meta-GGA were also employed to calculate the structural and electronic
properties of RCrO3. The ground-state energy, lattice constants, electronic
structure, and density of states (DOS) of RCrO3 were calculated. These provide
some insights into the electronic characteristics of the series of RCrO3
compounds. The calculated values of lattice parameters and band gaps with
Hubbard U correction (SCAN+U) agree well with values measured experimentally
and show more accuracy in predicting the ground-state crystal structure and
band structure compared to PBE+U approximation. The band gap of RCrO3 is found
to be independent of the ionic radii of the element R from both experiments and
calculations