  We consider a strongly nonlinear PDE system describing solid-solid phase
transitions in shape memory alloys. The system accounts for the evolution of an
order parameter (related to different symmetries of the crystal lattice in the
phase configurations), of the stress (and the displacement), and of the
absolute temperature. The resulting equations present several technical
difficulties to be tackled: in particular, we emphasize the presence of
nonlinear coupling terms, higher order dissipative contributions, possibly
multivalued operators. As for the evolution of temperature, a highly nonlinear
parabolic equation has to be solved for a right hand side that is controlled
only in L^1. We prove the existence of a solution for a regularized version, by
use of a time discretization technique. Then, we perform suitable a priori
estimates which allow us pass to the limit and find a weak global-in-time
solution to the system.


  Accretion flow in a contracting magnetized isothermal cloud was studied using
magnetohydrodynamical simulations and a nested grid technique. First, the
interstellar magnetized cloud experiences a ``runaway collapse'' phase, in
which the central density increases drastically within a finite time scale.
Finally, it enters an accretion phase, in which inflowing matter accretes onto
a central high-density disk or a new-born star. We found that the accretion
rate reaches (4 -- 40) $\times c_s^3/G$, where $c_s$ and $G$ represent the
isothermal sound speed and the gravitational constant, respectively. This is
much larger than the standard accretion rate of $0.975c_s^3/G$ for a
hydrostatic isothermal spherical cloud (Shu 1977, AAA19.065.044). Due to the
effect of an extra infall velocity achieved in the runaway phase ($\sim 2
c_s$), the accretion rate is boosted. This rate declines with time in contrast
to Shu's solution, but keeps $\gtsim 2.5 c_s^3/G$. The observed gas infall rate
around proto-stars such as L1551 IRS 5 and HL Tau is also discussed.


  We propose a decomposition framework for the parallel optimization of the sum
of a differentiable (possibly nonconvex) function and a (block) separable
nonsmooth, convex one. The latter term is usually employed to enforce structure
in the solution, typically sparsity. Our framework is very flexible and
includes both fully parallel Jacobi schemes and Gauss- Seidel (i.e.,
sequential) ones, as well as virtually all possibilities "in between" with only
a subset of variables updated at each iteration. Our theoretical convergence
results improve on existing ones, and numerical results on LASSO, logistic
regression, and some nonconvex quadratic problems show that the new method
consistently outperforms existing algorithms.


  We review the mathematical speed limits on quantum information processing in
many-body systems. After the proof of the Lieb-Robinson Theorem in 1972, the
past two decades have seen substantial developments in its application to other
questions, such as the simulatability of quantum systems on classical or
quantum computers, the generation of entanglement, and even the properties of
ground states of gapped systems. Moreover, Lieb-Robinson bounds have been
extended in non-trivial ways, to demonstrate speed limits in systems with
power-law interactions or interacting bosons, and even to prove notions of
locality that arise in cartoon models for quantum gravity with all-to-all
interactions. We overview the progress which has occurred, highlight the most
promising results and techniques, and discuss some central outstanding
questions which remain open. To help bring newcomers to the field up to speed,
we provide self-contained proofs of the field's most essential results.


  We propose deterministic and stochastic models for studying the
pharmacokinetics of chronic myeloid leukemia (CML), upon administration of
IFN-$\alpha$ (the traditional treatment for CML), TKI (the current frontline
medication for CML) and Wnt/$\beta$-catenin signaling (the state-of-the art
therapeutic breakthrough for CML). To the best of our knowledge, no
mathematical model incorporating all these three therapeutic protocols are
available in literature. Further, this work introduces a stochastic approach in
the study of CML dynamics. The key contributions of this work are: (1)
Determination of the patient condition, contingent upon the patient specific
model parameters, which leads to prediction of the appropriate patient specific
therapeutic dosage. (2) Addressing the question of how the dual therapy of TKI
and Wnt/$\beta$-catenin signaling or triple combination of all three, offers
potentially improved therapeutic responses, particularly in terms of reduced
side effects of TKI or IFN-$\alpha$. (3) Prediction of the likelihood of CML
extinction/remission based on the level of CML stem cells at detection.


  Low Earth Orbit Satellite Networks such as Starlink promise to provide
world-wide Internet access. While traditionally designed for stationary use, a
new dish, released in April 2023 in Europe, provides mobile Internet access
including in-motion usage, e.g., while mounted on a car. In this paper, we
design and build a mobile measurement setup. Our goal is to fully autonomously
conduct continuous Starlink measurements while the car is in motion. We share
our practical experiences, including challenges regarding the permanent power
supply. We measure the Starlink performance over the span of two months from
mid-January to mid-March 2024 when the car is in motion. The measurements
consist of all relevant network parameters, such as the download and upload
throughput, the RTT, and packet loss, as well as detailed power consumption
data. We analyze our dataset to assess Starlink's mobile performance in Central
Europe, Germany, and compare it to stationary measurements in proximity. We
find that the mobile performance is significantly worse than stationary
performance. The power consumption of the new dish is higher, but seems to be
more correlated to the heating function of the dish than to the speed of the
vehicle.


  We present a high-resolution view of bubbles within The Phantom Galaxy (NGC
628); a nearby (~10Mpc), star-forming (~2Msun/yr), face-on (i~9deg)
grand-design spiral galaxy. With new data obtained as part of the PHANGS-JWST
treasury program, we perform a detailed case-study of two regions of interest,
one of which contains the largest and most prominent bubble in the galaxy (The
Phantom Void; over 1kpc in diameter), and the other being a smaller region that
may be the precursor to such a large bubble (The Precursor Phantom Void). When
comparing to matched resolution Halpha observations from the Hubble Space
Telescope (HST), we see that the ionized gas is brightest in the shells of both
bubbles, and is coincident with the youngest (~1Myr) and most massive
(~100,000Msun) stellar associations. We also find an older generation (~20Myr)
of stellar associations is present within the bubble of The Phantom Void. From
our kinematic analysis of the HI, H2 (CO) and HII gas across The Phantom Void,
we infer a high expansion speed of around 15 to 50km/s. The large size and high
expansion speed of The Phantom Void suggest that the driving mechanism is
sustained stellar feedback due to multiple mechanisms, where early feedback
first cleared a bubble (as we observe now in The Precursor Phantom Void), and
since then SNe have been exploding within the cavity, and have accelerated the
shell. Finally, comparison to simulations shows a striking resemblance to our
JWST observations, and suggests that such large-scale stellar feedback-driven
bubbles should be common within other galaxies.


  Drinfeld associator is a key tool in computing the Kontsevich integral of
knots. A Drinfeld associator is a series in two non-commuting variables,
satisfying highly complicated algebraic equations - hexagon and pentagon. The
logarithm of a Drinfeld associator lives in the Lie algbera L generated by the
symbols a,b,c modulo [a,b]=[b,c]=[c,a]. The main result is a description of
compressed associators that satisfy the compressed pentagon and hexagon in the
quotient L/[[L,L],[L,L]]. The key ingredient is an explicit form of
Campbell-Baker-Hausdorff formula in the case when all commutators commute.


  We perform a likelihood analysis of the minimal Anomaly-Mediated
Supersymmetry Breaking (mAMSB) model using constraints from cosmology and
accelerator experiments. We find that a wino-like or a Higgsino-like neutralino
LSP, $m_{\tilde \chi^0_{1}}$, may provide the cold dark matter (DM) with
similar likelihood. The upper limit on the DM density from Planck and other
experiments enforces $m_{\tilde \chi^0_{1}} \lesssim 3~TeV$ after the inclusion
of Sommerfeld enhancement in its annihilations. If most of the cold DM density
is provided by the $\tilde \chi_0^1$, the measured value of the Higgs mass
favours a limited range of $\tan \beta \sim 5$ (or for $\mu > 0$, $\tan \beta
\sim 45$) but the scalar mass $m_0$ is poorly constrained. In the wino-LSP
case, $m_{3/2}$ is constrained to about $900~TeV$ and ${m_{\tilde \chi^0_{1}}}$
to $2.9\pm0.1~TeV$, whereas in the Higgsino-LSP case $m_{3/2}$ has just a lower
limit $\gtrsim 650TeV$ ($\gtrsim 480TeV$) and $m_{\tilde \chi^0_{1}}$ is
constrained to $1.12 ~(1.13) \pm0.02~TeV$ in the $\mu>0$ ($\mu<0$) scenario. In
neither case can the anomalous magnetic moment of the muon, ${(g-2)_\mu}$, be
improved significantly relative to its Standard Model (SM) value, nor do
flavour measurements constrain the model significantly, and there are poor
prospects for discovering supersymmetric particles at the LHC, {though there}
are some prospects for direct DM detection. On the other hand, if the
${m_{\tilde \chi^0_{1}}}$ contributes only a fraction of the cold DM density,
{future LHC $E_T$-based searches for gluinos, squarks and heavier chargino and
neutralino states as well as disappearing track searches in the wino-like LSP
region will be relevant}, and interference effects enable ${\rm BR}(B_{s, d}
\to \mu^+\mu^-)$ to agree with the data better than in the SM in the case of
wino-like DM with $\mu > 0$.


  An example of Floquet operator with purely point spectrum and energy
instability is presented. In the unperturbed energy eigenbasis its
eigenfunctions are exponentially localized.


  Entangled states with a positive partial transpose (so-called PPT states) are
central to many interesting problems in quantum theory. On one hand, they are
considered to be weakly entangled, since no pure state entanglement can be
distilled from them. On the other hand, it has been shown recently that some of
these PPT states exhibit genuinely high-dimensional entanglement, i.e. they
have a high Schmidt number. Here we investigate $d\times d$ dimensional PPT
states for $d\ge 4$ discussed recently by Sindici and Piani, and by
generalizing their methods to the calculation of Schmidt numbers we show that a
linear $d/2$ scaling of its Schmidt number in the local dimension $d$ can be
attained.


  Given a domain of characteristic zero $R$, we functorially construct a rigid
symmetric monoidal stable $\infty$-category whose $K_0$ is $R$, solving a
problem of Khovanov. We also functorially construct for any reduced commutative
ring $R$ a rigid braided monoidal stable $\infty$-category whose $K_0$ is $R$.


  We propose an improved methodology to constrain spatial variations of the
fine structure constant using clusters of galaxies. We use the {\it Planck}
2013 data to measure the thermal Sunyaev-Zeldovich effect at the location of
618 X-ray selected clusters. We then use a Monte Carlo Markov Chain algorithm
to obtain the temperature of the Cosmic Microwave Background at the location of
each galaxy cluster. When fitting three different phenomenological
parameterizations allowing for monopole and dipole amplitudes in the value of
the fine structure constant we improve the results of earlier analysis
involving clusters and the CMB power spectrum, and we also found that the
best-fit direction of a hypothetical dipole is compatible with the direction of
other known anomalies. Although the constraining power of our current datasets
do not allow us to test the indications of a fine-structure constant dipole
obtained though high-resolution optical/UV spectroscopy, our results do
highlight that clusters of galaxies will be a very powerful tool to probe
fundamental physics at low redshift.


  Following Semmes and Zinsmeister, we continue the study of Carleson measures
and their invariance under pull-back and push-forward operators. We also study
the analogous statements for vanishing Carleson measures. As an application, we
show that some quotient space of the space of chord-arc curves has a natural
complex structure.


  This work presents a comparative study to numerically compute impulse
approximate controls for parabolic equations with various boundary conditions.
Theoretical controllability results have been recently investigated using a
logarithmic convexity estimate at a single time based on a Carleman commutator
approach. We propose a numerical algorithm for computing the impulse controls
with minimal $L^2$-norms by adapting a penalized Hilbert Uniqueness Method
(HUM) combined with a Conjugate Gradient (CG) method. We consider static
boundary conditions (Dirichlet and Neumann) and dynamic boundary conditions.
Some numerical experiments based on our developed algorithm are given to
validate and compare the theoretical impulse controllability results.


  In recent years, deep learning has presented a great advance in hyperspectral
image (HSI) classification. Particularly, long short-term memory (LSTM), as a
special deep learning structure, has shown great ability in modeling long-term
dependencies in the time dimension of video or the spectral dimension of HSIs.
However, the loss of spatial information makes it quite difficult to obtain the
better performance. In order to address this problem, two novel deep models are
proposed to extract more discriminative spatial-spectral features by exploiting
the Convolutional LSTM (ConvLSTM). By taking the data patch in a local sliding
window as the input of each memory cell band by band, the 2-D extended
architecture of LSTM is considered for building the spatial-spectral ConvLSTM
2-D Neural Network (SSCL2DNN) to model long-range dependencies in the spectral
domain. To better preserve the intrinsic structure information of the
hyperspectral data, the spatial-spectral ConvLSTM 3-D Neural Network (SSCL3DNN)
is proposed by extending LSTM to 3-D version for further improving the
classification performance. The experiments, conducted on three commonly used
HSI data sets, demonstrate that the proposed deep models have certain
competitive advantages and can provide better classification performance than
other state-of-the-art approaches.


  The spin Hall magnetoresistance (SMR) allows to investigate the magnetic
textures of magnetically ordered insulators in heterostructures with normal
metals by magnetotransport experiments. We here report the observation of the
SMR in in-situ prepared ferromagnetic EuO/W thin film bilayers with
magnetically and chemically well-defined interfaces. We characterize the
magnetoresistance effects utilizing angle-dependent and field-dependent
magnetotransport measurements as a function of temperature. Applying the
established SMR model, we derive and quantify the real and imaginary parts of
the complex spin mixing interface conductance. We find that the imaginary part
is by one order of magnitude larger than the real part. Both decrease with
increasing temperature. This reduction is in agreement with thermal
fluctuations in the ferromagnet.


  We present the results of microlens ray-tracing simulations showing the
effect of absorbing material between a source quasar and a lensing galaxy in a
gravitational lens system. We find that, in addition to brightness fluctuations
due to microlensing, the strength of the absorption line relative to the
continuum varies with time, with the properties of the variations depending on
the structure of the absorbing material. We conclude that such variations will
be measurable via UV spectroscopy of image A of the gravitationally lensed
quasar Q2237+0305 if the Lyman Alpha clouds between the quasar and the lensing
galaxy possess structure on scales smaller than $\sim 0.1$ pc. The time scale
for the variations is on the order of order years to decades, although very
short term variability can occur. While the Lyman alpha lines may not be
accessible at all wavelengths, this approach is applicable to any absorption
system, including metal lines.


  In this paper, we have studied the effect of strain relaxation on
magneto-transport properties of La_0.7Ca_0.3MnO_3 epitaxial films (200 nm
thick), which were deposited by pulsed laser deposition technique under
identical conditions. All the films are epitaxial and have cubic unit cell. The
amount of strain relaxation has been varied by taking three different single
crystal substrates of SrTiO_3, LaAlO_3 and MgO. It has been found that for
thicker films the strain gets relaxed and produces variable amount of disorder
depending on the strength of strain relaxation. The magnitude of lattice
relaxation has been found to be 0.384, 3.057 and 6.411 percent for film
deposited on SrTiO_3, LaAlO_3 and MgO respectively. The films on LaAlO_3 and
SrTiO_3 show higher T_{IM} of 243 K and 217 K respectively as compared to
T_{IM} of 191 K for the film on MgO. Similarly T_C of the films on SrTiO_3 and
LaAlO_3 is sharper and has value of 245 K and 220 K respectively whereas the TC
of the film on MgO is 175 K. Higher degree of relaxation creates more defects
and hence TIM (T_C) of the film on MgO is significantly lower than of SrTiO_3
and LaAlO_3. We have adopted a different approach to correlate the effect of
strain relaxation on magneto-transport properties of LCMO films by evaluating
the resistivity variation through Mott's VRH model. The variable presence of
disorder in these thick films due to lattice relaxation which have been
analyzed through Mott's VRH model provides a strong additional evidence that
the strength of lattice relaxation produces disorder dominantly by increase in
density of defects such as stacking faults, dislocations, etc. which affect the
magneto-transport properties of thick epitaxial La_0.7Ca_0.3MnO_3 films.


  Intensity mapping experiments are beginning to measure the spatial
distribution of neutral atomic hydrogen (HI) to constrain cosmological
parameters and the large-scale distribution of matter. However, models of the
behaviour of HI as a tracer of matter are complicated by galaxy evolution. In
this work, we examine the clustering of HI in relation to galaxy colour,
stellar mass, and HI mass in IllustrisTNG at $z$ = 0, 0.5, and 1. We compare
the HI-red and HI-blue galaxy cross-power spectra, finding that HI-red has an
amplitude 1.5 times higher than HI-blue at large scales. The cross-power
spectra intersect at $\approx 3$ Mpc in real space and $\approx 10$ Mpc in
redshift space, consistent with $z \approx 0$ observations. We show that HI
clustering increases with galaxy HI mass and depends weakly on detection limits
in the range $M_{\mathrm{HI}} \leq 10^8 M_\odot$. In terms of $M_\star$, we
find blue galaxies in the greatest stellar mass bin cluster more than blue
galaxies in other stellar mass bins. Red galaxies in the greatest stellar mass
bin, however, cluster the weakest amongst red galaxies. These trends arise due
to central-satellite compositions. Centrals correlate less with HI for
increasing stellar mass, whereas satellites correlate more, irrespective of
colour. Despite the clustering relationships with stellar mass, we find that
the cross-power spectra are largely insensitive to detection limits in HI and
galaxy surveys. Counter-intuitively, all auto and cross-power spectra for red
and blue galaxies and HI decrease with time at all scales in IllustrisTNG. We
demonstrate that processes associated with quenching contribute to this trend.
The complex interplay between HI and galaxies underscores the importance of
understanding baryonic effects when interpreting the large-scale clustering of
HI, blue, and red galaxies at $z \leq 1$.


  We prove that a version of the Thurston-Bennequin inequality holds for
Legendrian and transverse links in a rational homology contact 3-sphere
$(M,\xi)$, whenever $\xi$ is tight. More specifically, we show that the
self-linking number of a transverse link $T$ in $(M,\xi)$, such that the
boundary of its tubular neighbourhood consists of incompressible tori, is
bounded by the Thurston norm $||T||_T$ of $T$. A similar inequality is given
for Legendrian links by using the notions of positive and negative transverse
push-off. We apply this bound to compute the tau-invariant for every strongly
quasi-positive link in $S^3$. This is done by proving that our inequality is
sharp for this family of smooth links. Moreover, we use a stronger Bennequin
inequality, for links in the tight 3-sphere, to generalize this result to
quasi-positive links and determine their maximal self-linking number.


  We consider a polynomial version of the Cayley numbers. Namely, we define the
ring of Cayley polynomials in terms of generators and relations in the category
of alternative algebras. The ring turns out to be an octonion algebra over an
ordinary polynomial ring. Also, a localization (a ring of quotients) of the
ring of Cayley polynomials gives another description of an octonion torus.
Finally, we find a subalgebra of a prime nondegenerate alternative algebra so
that the subalgebra is an octonion algebra over the center.


  Adapting End-to-End ASR models to out-of-domain datasets with text data is
challenging. Factorized neural Transducer (FNT) aims to address this issue by
introducing a separate vocabulary decoder to predict the vocabulary.
Nonetheless, this approach has limitations in fusing acoustic and language
information seamlessly. Moreover, a degradation in word error rate (WER) on the
general test sets was also observed, leading to doubts about its overall
performance. In response to this challenge, we present the improved factorized
neural Transducer (IFNT) model structure designed to comprehensively integrate
acoustic and language information while enabling effective text adaptation. We
assess the performance of our proposed method on English and Mandarin datasets.
The results indicate that IFNT not only surpasses the neural Transducer and FNT
in baseline performance in both scenarios but also exhibits superior adaptation
ability compared to FNT. On source domains, IFNT demonstrated statistically
significant accuracy improvements, achieving a relative enhancement of 1.2% to
2.8% in baseline accuracy compared to the neural Transducer. On out-of-domain
datasets, IFNT shows relative WER(CER) improvements of up to 30.2% over the
standard neural Transducer with shallow fusion, and relative WER(CER)
reductions ranging from 1.1% to 2.8% on test sets compared to the FNT model.


  Visual topological navigation has been revitalized recently thanks to the
advancement of deep learning that substantially improves robot perception.
However, the scalability and reliability issue remain challenging due to the
complexity and ambiguity of real world images and mechanical constraints of
real robots. We present an intuitive solution to show that by accurately
measuring the capability of a local controller, large-scale visual topological
navigation can be achieved while being scalable and robust. Our approach
achieves state-of-the-art results in trajectory following and planning in
large-scale environments. It also generalizes well to real robots and new
environments without retraining or finetuning.


  Studies of the inner few parsecs at the Galactic Centre provide evidence of a
supermassive black hole, associated with the unusual, variable radio and
infrared source Sgr A*.
  Our major aim is the study and analysis of the physical processes responsible
for the variable emission from the compact radio source Sgr A*. In order to
understand the physics behind the observed variability, we model the time
evolution of the flare emitting region by studying light curves and spectra of
emission originating at the surface of the accretion disk, close to the event
horizon, near the marginally stable orbit of a rotating black hole.
  Here we discuss the methods used in the analysis of the time-variable
spectral features and subsequently present preliminary modeling results.


  It is generally accepted today that our solar system has undergone a phase
during which the orbits of the giant planets became very unstable. In recent
years, many studies have identified traces of this event and have provided
reasonable justification for this occurrence. The magnitude (in terms of
orbital variation) and the timing of the instability though (early or late with
respect to the dispersal of the gas disk) still remains an open debate. The
terrestrial planets seem to set a strict constraint: either the giant planet
instability happened early, while the terrestrial planets were still forming,
or the orbits of Jupiter and Saturn had to separate from each other
impulsively, with a large enough `jump' in semimajor axis (Brasser et al. 2009;
Kaib and Chambers 2016) for the terrestrial planets to remain stable. Because a
large orbital jump is a low probability event, the early instability hypothesis
seems to be favored. However, the asteroid belt would also evolve in a
different way, assuming different instability amplitudes. These two constraints
need to match each other in order to favor one scenario over the other.
Considering an initially dynamically cold disk of asteroids, Morbidelli et al.
(2010) concluded that a comparably large jump is needed to reconstruct the
current asteroid belt. Here we confirm the same conclusion, but considering an
asteroid population already strongly excited in eccentricity, such as that
produced in the Grand Tack scenario (Walsh et al. 2011). Because the asteroids
existed since the time of removal of the gas disk, unlike the terrestrial
planets, this constraint on the width of the giant planet jump is valid
regardless of whether the instability happened early or late. Hence, at this
stage, assuming an early instability does not appear to provide any advantage
in terms of the probabilistic reconstruction of the solar system structure.


  To first approximation, a binary system conserves its angular momentum while
it evolves to its state of minimum kinetic energy: circular orbit, all spins
aligned, and components rotating in synchronism with the orbital motion. The
pace at which this final state is achieved depends on the physical processes
that are responsible for the dissipation of the tidal kinetic energy. For stars
(or planets) with an outer convection zone, the dominant mechanism identified
so far is the viscous dissipation acting on the equilibrium tide. For stars
with an outer radiation zone, it is the radiative damping operating on the
dynamical tide. After a brief presentation of the tides, I shall review these
physical processes; I shall discuss the uncertainties of their present
treatment, describe the latest developments, and compare the theoretical
predictions with the observed properties concerning the orbital circularization
of close binaries.


  We highlight phenomenological aspects of Verlinde's recent proposal to
account for the mass anomalies in galactic systems without dark matter -- in
particular in their relation to MOND. Welcome addition to the MOND lore as it
is, this approach have reproduced, so far, only a small fraction of MOND
phenomenology, and is still rather tentative, both in its theoretical
foundations and in its phenomenology. What Verlinde has extracted from this
approach, so far, is a formula -- of rather limited applicability, and with no
road to generalization in sight -- for the effective gravitational field of a
spherical, isolated, static baryonic system. This formula cannot be used to
calculate the gravitational field of disk galaxies, with their rich MOND
phenomenology. Notably, it cannot predict their rotation curves, except
asymptotically. It does not apply to the few-, or many-body problem; so, it
cannot give, e.g., the two-body force between two galaxies, or be used to
conduct N-body calculations of galaxy formation, evolution, and interactions.
The formula cannot be applied to the internal dynamics of a system embedded in
an external field, where MOND predicts important consequences. etc. MOND is
backed by full-fledged, Lagrangian theories that can be, and are, routinely
applied to all the above phenomena, and more. Verlinde's formula, as it now
stands, strongly conflicts with solar-system and possibly earth-surface
constraints, and cannot fully account for the mass anomalies in the cores of
galaxy clusters (a standing conundrum in MOND). The recent weak-lensing test of
the formula is, in fact, testing a cornerstone prediction of MOND, one that the
formula does reproduce, and which has been tested before in the very same way.


  Chord diagrams, under the name of Gauss diagrams, are used in low-dimensional
topology as an important tool for studying curves or knots. Those Gauss
diagrams that correspond to curves or knots are called realizable. The theme of
our paper is the fact that realizability of a Gauss diagram can be expressed
via its circle graph. Accordingly, one can define and study realizable circle
graphs (with realizability of a circle graph understood as realizability of any
one of chord diagrams corresponding to the graph). Several studies contain
theorems purporting to prove the fact. We check several of these descriptions
experimentally and find counterexamples to the descriptions of realizable Gauss
diagrams in some of these publications. We formulate new descriptions of
realizable circle graphs and present an elegant algorithm for checking if a
circle graph is realizable. We enumerate realizable circle graphs for small
sizes and comment on these numbers. Then we concentrate on one type of curves,
called meanders, and study the circle graphs of their Gauss diagrams.


  A subset of ultraluminous X-ray sources (those with luminosities < 10^40
erg/s) are thought to be powered by the accretion of gas onto black holes with
masses of ~5-20 M_solar, probably via an accretion disc. The X-ray and radio
emission are coupled in such Galactic sources, with the radio emission
originating in a relativistic jet thought to be launched from the innermost
regions near the black hole, with the most powerful emission occurring when the
rate of infalling matter approaches a theoretical maximum (the Eddington
limit). Only four such maximal sources are known in the Milky Way, and the
absorption of soft X-rays in the interstellar medium precludes determining the
causal sequence of events that leads to the ejection of the jet. Here we report
radio and X-ray observations of a bright new X-ray source whose peak luminosity
can exceed 10^39 erg/s in the nearby galaxy, M31. The radio luminosity is
extremely high and shows variability on a timescale of tens of minutes, arguing
that the source is highly compact and powered by accretion close to the
Eddington limit onto a stellar mass black hole. Continued radio and X-ray
monitoring of such sources should reveal the causal relationship between the
accretion flow and the powerful jet emission.


  In this work we construct 36 tetraquark configurations for the $1S$-, $1P$-,
and $2S$-wave states, and make a prediction of the mass spectrum for the
tetraquark $ss\bar{s}\bar{s}$ system in the framework of a nonrelativistic
potential quark model without the diquark-antidiquark approximation. The model
parameters are well determined by our previous study of the strangeonium
spectrum. We find that the resonances $f_0(2200)$ and $f_2(2340)$ may favor the
assignments of ground states $T_{(ss\bar{s}\bar{s})0^{++}}(2218)$ and
$T_{(ss\bar{s}\bar{s})2^{++}}(2378)$, respectively, and the newly observed
$X(2500)$ at BESIII may be a candidate of the lowest mass $1P$-wave $0^{-+}$
state $T_{(ss\bar{s}\bar{s})0^{-+}}(2481)$. Signals for the other $0^{++}$
ground state $T_{(ss\bar{s}\bar{s})0^{++}}(2440)$ may also have been observed
in the $\phi\phi$ invariant mass spectrum in $J/\psi\to\gamma\phi\phi$ at
BESIII. The masses of the $J^{PC}=1^{--}$ $T_{ss\bar{s}\bar{s}}$ states are
predicted to be in the range of $\sim 2.44-2.99$ GeV, which indicates that the
$\phi(2170)$ resonance may not be a good candidate of the
$T_{ss\bar{s}\bar{s}}$ state. This study may provide a useful guidance for
searching for the $T_{ss\bar{s}\bar{s}}$ states in experiments.


  We study the fine-structure constant dependence of the rates of some selected
radiative capture reactions within the framework of so-called Halo Effective
Field Theory in order to assess the adequacy of some assumptions made on the
Coulomb penetrability. We find that this dependence deviates from that implied
by a parameterization of the cross sections of this effect via a simple
penetration factor. Some features of this fine-structure dependence are
discussed, in particular its potential impact on the abundances of the light
elements in primordial nucleosynthesis.


  PROSPECT, the Precision Reactor Oscillation and SPECTrum experiment, is a
short-baseline reactor antineutrino experiment designed to provide precision
measurements of the $^{235}$U product $\overline{\nu}_e$ spectrum of utilizing
an optically segmented 4-ton liquid scintillator detector. PROSPECT's
segmentation system, the optical grid, plays a central role in reconstructing
the position and energy of $\overline{\nu}_e$ interactions in the detector.
This paper is the technical reference for this PROSPECT subsystem, describing
its design, fabrication, quality assurance, transportation and assembly in
detail. In addition, the dimensional, optical and mechanical characterizations
of optical grid components and the assembled PROSPECT target are also
presented. The technical information and characterizations detailed here will
inform geometry-related inputs for PROSPECT physics analysis, and can guide a
variety of future particle detection development efforts, such as those using
optically reflecting materials or filament-based 3D printing.


  Stated succinctly, the original version of the Campbell-Magaard theorem says
that it is always possible to locally embed any solution of 4-dimensional
general relativity in a 5-dimensional Ricci-flat manifold. We discuss the proof
of this theorem (and its variants) in n dimensions, and its application to
current theories that postulate that our universe is a 4-dimensional
hypersurface Sigma_0 within a 5-dimensional manifold, such as Space-Time-Matter
(STM) theory and the Randall & Sundrum (RS) braneworld scenario. In particular,
we determine whether or not arbitrary spacetimes may be embedded in such
theories, and demonstrate how these seemingly disparate models are
interconnected. Special attention is given to the motion of test observers in 5
dimensions, and the circumstances under which they are confined to Sigma_0. For
each 5-dimensional scenario considered, the requirement that observers be
confined to the embedded spacetime places restrictions on the 4-geometry. For
example, we find that observers in the thin braneworld scenario can be
localized around the brane if its total stress-energy tensor obeys the
5-dimensional strong energy condition. As a concrete example of some of our
technical results, we discuss a Z_2 symmetric embedding of the standard
radiation-dominated cosmology in a 5-dimensional vacuum.


  Graph Auto-Encoders (GAEs) are powerful tools for graph representation
learning. In this paper, we develop a novel Hierarchical Cluster-based GAE
(HC-GAE), that can learn effective structural characteristics for graph data
analysis. To this end, during the encoding process, we commence by utilizing
the hard node assignment to decompose a sample graph into a family of separated
subgraphs. We compress each subgraph into a coarsened node, transforming the
original graph into a coarsened graph. On the other hand, during the decoding
process, we adopt the soft node assignment to reconstruct the original graph
structure by expanding the coarsened nodes. By hierarchically performing the
above compressing procedure during the decoding process as well as the
expanding procedure during the decoding process, the proposed HC-GAE can
effectively extract bidirectionally hierarchical structural features of the
original sample graph. Furthermore, we re-design the loss function that can
integrate the information from either the encoder or the decoder. Since the
associated graph convolution operation of the proposed HC-GAE is restricted in
each individual separated subgraph and cannot propagate the node information
between different subgraphs, the proposed HC-GAE can significantly reduce the
over-smoothing problem arising in the classical convolution-based GAEs. The
proposed HC-GAE can generate effective representations for either node
classification or graph classification, and the experiments demonstrate the
effectiveness on real-world datasets.


  In this paper convexity constraints are derived for a background model of
electron energy loss spectra (EELS) that is linear in the fitting parameters.
The model outperforms a power-law both on experimental and simulated
backgrounds, especially for wide energy ranges, and thus improves elemental
quantification results. Owing to the model's linearity, the constraints can be
imposed through fitting by quadratic programming. This has important advantages
over conventional nonlinear power-law fitting such as high speed and a
guaranteed unique solution without need for initial parameters. As such, the
need for user input is significantly reduced, which is essential for
unsupervised treatment of large data sets. This is demonstrated on a demanding
spectrum image of a semiconductor device sample with a high number of elements
over a wide energy range.


  One leading question with respect to Bi-intuitionistic logic (BINT) is, what
does BINT look like across the three arcs -- logic, typed $\lambda$-calculi,
and category theory -- of the Curry-Howard-Lambek correspondence?
Categorically, BINT can be seen as a mixing of two worlds: the first being
intuitionistic logic (IL), which is modeled by a cartesian closed category, and
the second being the dual to intuitionistic logic called cointuitionistic logic
(coIL), which is modeled by a cocartesian coclosed category. Crolard showed
that combining these two categories into the same category results in it
degenerating to a poset. However, this degeneration does not occur when both
logics are linear. We propose that IL and coIL need to be separated, and then
mixed in a controlled way using the modalities from linear logic. This
separation can be ultimately achieved by an adjoint formalization of
bi-intuitionistic logic. This formalization consists of three worlds instead of
two: the first is intuitionistic logic, the second is linear bi-intuitionistic
(Bi-ILL), and the third is cointuitionistic logic. They are then related via
two adjunctions. The adjunction between IL and ILL is known as a
Linear/Non-linear model (LNL model) of ILL, and is due to Benton. However, the
dual to LNL models which would amount to the adjunction between coILL and coIL
has yet to appear in the literature. In this paper we fill this gap by studying
the dual to LNL models which we call dual LNL models. We show that dual LNL
models correspond to dual linear categories, the dual to Bierman's linear
categories proposed by Bellin. Then we give the definition of bi-LNL models by
combining our model with LNL models to obtain a new model of bi-intuitionistic
logic. Finally, we give a corresponding sequent calculus, natural deduction,
and term assignment for dual LNL models.


  In this work, we analyze the applicability of Inverse Dynamic Game (IDG)
methods based on the Minimum Principle (MP). The IDG method determines unknown
cost functions in a single- or multi-agent setting from observed system
trajectories by minimizing the so-called residual error, i.e. the extent to
which the optimality conditions of the MP are violated with a current guess of
cost functions. The main assumption of the IDG method to recover cost functions
such that the resulting trajectories match the observed ones is that the given
trajectories are the result of a Dynamic Game (DG) problem with known
parameterized cost function structures. However, in practice, when the IDG
method is used to identify the behavior of unknown agents, e.g. humans, this
assumption cannot be guaranteed. Hence, we introduce the notion of the
trustworthiness of the residual error and provide necessary conditions for it
to define when the IDG method based on the MP is applicable to such problems.
From the necessary conditions, we conclude that the MP-based IDG method cannot
be used to validate DG models for unknown agents but can yield under certain
conditions robust parameter identifications, e.g. to measurement noise.
Finally, we illustrate these conclusions by validating a DG model for the
collision avoidance behavior between two mobile robots with human operators.


  We study random walks on the semi-direct product of F_p^d and SL_d(F_p). We
estimate the spectral gap in terms of the spectral gap of the projection to the
linear part SL_d(F_p). This problem is motivated by an analogue in the isometry
group of Euclidean space, which have application to smoothness of self-similar
measures.


  We discuss integral field spectroscopy of proplyds in M42 using the FLAMES
Argus unit and report the first detection of recombination lines of C II and O
II from the archetypical Laques-Vidal-2 object. These lines can provide
important new diagnostics of the physical conditions in proplyds. We also draw
attention to the future capabilities of the MUSE spectrograph in relation to
similar studies.


  Similar to the diode in electronics, a thermal diode is a two-terminal device
that allows heat to transfer easier in one direction (forward bias) than in the
opposite direction (reverse bias). Unlike conductive and convective thermal
diodes, a photonic thermal diode operates in a contactless mode and may afford
a large operating temperature range. In this work, a novel near-field photonic
thermal diode with hexagonal boron nitride (hBN) and indium antimonide (InSb)
is proposed and theoretically demonstrated. The temperature dependence of the
interband absorption of InSb is used to couple (or decouple) with the
hyperbolic phonon polaritons in hBN. The numerical analysis predicts a
rectification ratio greater than 17 for a 10 nm vacuum gap when operating at an
average temperature of 300 K and a temperature difference of 200 K. The
calculated rectification ratio exceeds 35 with higher average temperatures and
larger temperature differences. The mechanism proposed here for achieving
photonic thermal rectification provides a new way of controlling radiative heat
transfer.


  We present the application of the Schur-Weyl duality in the one-dimensional
Hubbard model in the case of half-filled system of any numer of atoms. We
replace the actions of the dual symmetric and unitary groups in the whole
Hilbert space by the actions of the dual groups in the spin and pseudo-spin
spaces. The calculations significantly reduce the dimension of the eigenproblem
of the one-dimensional Hubbard model.


  We discuss the role of quantum coherence in the energy fluctuations of open
quantum systems. To this aim, we introduce a protocol, to which we refer to as
the end-point-measurement scheme, allowing to define the statistics of energy
changes as a function of energy measurements performed only after the evolution
of the initial state. At the price of an additional uncertainty on the initial
energies, this approach prevents the loss of initial quantum coherences and
enables the estimation of their effects on energy fluctuations. We demonstrate
our findings by running an experiment on the IBM Quantum Experience
superconducting qubit platform.


  We present spectral and timing analyses of the X-ray emission from the pulsar
wind nebula DA 495 and its central object, J1952.2+2925, suggested to be the
pulsar, using archival Chandra and XMM-Newton data. J1952.2+2925 has a pure
thermal spectrum which is equally well fitted either by the blackbody model
with a temperature of $\approx 215$ eV and an emitting area radius of $\approx
0.6$ km or by magnetized neutron star atmosphere models with temperatures of
80-90 eV. In the latter case the thermal emission can come from the entire
neutron star surface which temperature is consistent with standard neutron star
cooling scenarios. We place also an upper limit on the J1952.2+2925 nonthermal
flux. The derived spectral parameters are generally compatible with published
ones based only on the Chandra data, but they are much more accurate due to the
inclusion of XMM-Newton data. No pulsations were found and we placed an upper
limit for the J1952.2+2925 pulsed emission fraction of 40 per cent. Utilizing
the interstellar absorption-distance relation, we estimated the distance to DA
495, which can be as large as 5 kpc if J1952.2+2925 emission is described by
the atmosphere models. We compiled possible multi-wavelength spectra of the
nebula including radio data; they depend on the spectral model of the central
object. Comparing the results with other pulsar plus wind nebula systems we set
reasonable constraints on the J1952.2+2925 spin-down luminosity and age. We
suggest that the Fermi source 3FGL J1951.6+2926 is the likely $\gamma$-ray
counterpart of J1952.2+2925.


  The Chandra image of the merging, hot galaxy cluster 1E0657-56 reveals a bow
shock propagating in front of a bullet-like gas cloud just exiting the
disrupted cluster core. This is the first clear example of a shock front in a
cluster. From the jumps in the gas density and temperature at the shock, the
Mach number of the bullet-like cloud is 2-3. This corresponds to a velocity of
3000-4000 km/s relative to the main cluster, which means that the cloud
traversed the core just 0.1-0.2 Gyr ago. The 6-7 keV "bullet" appears to be a
remnant of a dense cooling flow region once located at the center of a merging
subcluster whose outer gas has been stripped by ram pressure. The bullet's
shape indicates that it is near the final stage of being destroyed by ram
pressure and gas dynamic instabilities, as the subcluster galaxies move well
ahead of the cool gas. The unique simplicity of the shock front and bullet
geometry in 1E0657-56 may allow a number of interesting future measurements.
The cluster's average temperature is 14-15 keV but shows large spatial
variations. The hottest gas (T>20 keV) lies in the region of the radio halo
enhancement and extensive merging activity involving subclusters other than the
bullet.


  We prove that for every integer $k$, every finite set of points in the plane
can be $k$-colored so that every half-plane that contains at least $2k-1$
points, also contains at least one point from every color class. We also show
that the bound $2k-1$ is best possible. This improves the best previously known
lower and upper bounds of $\frac{4}{3}k$ and $4k-1$ respectively. We also show
that every finite set of half-planes can be $k$ colored so that if a point $p$
belongs to a subset $H_p$ of at least $3k-2$ of the half-planes then $H_p$
contains a half-plane from every color class. This improves the best previously
known upper bound of $8k-3$. Another corollary of our first result is a new
proof of the existence of small size $\eps$-nets for points in the plane with
respect to half-planes.


  When an X-ray area detector based on a single crystalline material, for
instance, a state of the art hybrid pixel detector, is illuminated from a point
source by monochromatic radiation, a pattern of lines appears which overlays
the detected image. These lines can be easily found by scattering experiments
with smooth patterns, such as small-angle X-ray scattering. The origin of this
effect is the Bragg reflection in the sensor layer of the detector.
Experimental images are presented over a photon energy range from 3.4 keV to 10
keV, together with a theoretical analysis. The intensity of this pattern is up
to 20%, which can disturb the evaluation of scattering and diffraction
experiments. The patterns can be exploited to check the alignment of the
detector surface with the direct beam, and the alignment of individual detector
modules with each other in the case of modular detectors, as well as for the
energy calibration of the radiation.


  It is well known that the set of possible degree sequences for a graph on $n$
vertices is the intersection of a lattice and a convex polytope. We show that
the set of possible degree sequences for a $k$-uniform hypergraph on $n$
vertices is not the intersection of a lattice and a convex polytope for $k \geq
3$ and $n \geq k+13$. We also show an analogous nonconvexity result for the set
of degree sequences of $k$-partite $k$-uniform hypergraphs and the generalized
notion of $\lambda$-balanced $k$-uniform hypergraphs.


  Short-depth algorithms are crucial for reducing computational error on
near-term quantum computers, for which decoherence and gate infidelity remain
important issues. Here we present a machine-learning approach for discovering
such algorithms. We apply our method to a ubiquitous primitive: computing the
overlap ${\rm Tr}(\rho\sigma)$ between two quantum states $\rho$ and $\sigma$.
The standard algorithm for this task, known as the Swap Test, is used in many
applications such as quantum support vector machines, and, when specialized to
$\rho = \sigma$, quantifies the Renyi entanglement. Here, we find algorithms
that have shorter depths than the Swap Test, including one that has a constant
depth (independent of problem size). Furthermore, we apply our approach to the
hardware-specific connectivity and gate sets used by Rigetti's and IBM's
quantum computers and demonstrate that the shorter algorithms that we derive
significantly reduce the error - compared to the Swap Test - on these
computers.


  We consider a system of the form x'=P_n(x,y)+xR_m(x,y),
y'=Q_n(x,y)+yR_m(x,y), where P_n(x,y), Q_n(x,y) and R_m(x,y) are homogeneous
polynomials of degrees n, n and m, respectively, with n<=m. We prove that this
system has at most one limit cycle and that when it exists it can be explicitly
found. Then we study a particular case, with n=3 and m=4. We prove that this
quintic polynomial system has an explicit limit cycle which is not algebraic.
To our knowledge, there are no such type of examples in the literature.
  The method that we introduce to prove that this limit cycle is not algebraic
can be also used to detect algebraic solutions for other families of polynomial
vector fields or for probing the absence of such type of solutions.


  Recent studies have attempted to refine the Transformer architecture to
demonstrate its effectiveness in Long-Term Time Series Forecasting (LTSF)
tasks. Despite surpassing many linear forecasting models with ever-improving
performance, we remain skeptical of Transformers as a solution for LTSF. We
attribute the effectiveness of these models largely to the adopted Patch
mechanism, which enhances sequence locality to an extent yet fails to fully
address the loss of temporal information inherent to the permutation-invariant
self-attention mechanism. Further investigation suggests that simple linear
layers augmented with the Patch mechanism may outperform complex
Transformer-based LTSF models. Moreover, diverging from models that use channel
independence, our research underscores the importance of cross-variable
interactions in enhancing the performance of multivariate time series
forecasting. The interaction information between variables is highly valuable
but has been misapplied in past studies, leading to suboptimal cross-variable
models. Based on these insights, we propose a novel and simple Patch-based
Decomposed MLP (PDMLP) for LTSF tasks. Specifically, we employ simple moving
averages to extract smooth components and noise-containing residuals from time
series data, engaging in semantic information interchange through channel
mixing and specializing in random noise with channel independence processing.
The PDMLP model consistently achieves state-of-the-art results on several
real-world datasets. We hope this surprising finding will spur new research
directions in the LTSF field and pave the way for more efficient and concise
solutions.


  We analyse the effects of galaxy interactions on star formation in groups and
clusters of galaxies with virial masses in the range $10^{13} - 10 ^{15}
M_{\odot}$. We find a trend for galaxy-galaxy interactions to be less efficient
in triggering star formation in high density regions in comparison with
galaxies with no close companion.
  However, we obtain the same relative projected distance and relative radial
velocity thresholds for the triggering of significant star formation activity
($r_p \sim 25 h^{-1} $ kpc and $\Delta V \sim 100 {\rm km s^{-1}}$) as found in
the field. Thus, the nature of star formation driven by galaxy interactions is
nearly independent of environment, although there is a general lower level of
star formation activity in massive systems. The above results reflect, on one
hand, the local nature of star formation induced by tidal interactions and, on
the other, the role played by the internal properties of galaxies. By using a
2dFGRS mock catalog we estimate the contamination by spurious pairs finding
that the statistics are cleary dominated by real pairs. We also found the
behaviour of the trends to be robust against the use of more restrictive
relative velocity thresholds.(Abridged)


  Statistical properties of a local fluctuational fluxes measured at the plasma
edge are investigated in the work. It's shown that the amplitudes increments of
the local fluctuational fluxes decrease by power law. For approximation of
experimental PDFs the fractional stable distributions are used. The new
algorithm of statistical estimation of the FSD parameters based on maximum
likelihood method is described. By using of the algorithm the parameters of FSD
are estimated by using experimental samples. It is shown good agreement between
experimental and theoretical distributions. On the basis of this results the
conclusion is made about applicability of the CTRW model for description of a
processes underlying of the plasma turbulence.


  In this paper we combine the Early Science radio continuum data from the
MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE) Survey,
with optical and near-infrared data and release the cross-matched catalogues.
The radio data used in this work covers $0.86$ deg$^2$ of the COSMOS field,
reaches a thermal noise of $1.7$ $\mu$Jy/beam and contains $6102$ radio
components. We visually inspect and cross-match the radio sample with optical
and near-infrared data from the Hyper Suprime-Cam (HSC) and UltraVISTA surveys.
This allows the properties of active galactic nuclei and star-forming
populations of galaxies to be probed out to $z \approx 5$. Additionally, we use
the likelihood ratio method to automatically cross-match the radio and optical
catalogues and compare this to the visually cross-matched catalogue. We find
that 94 per cent of our radio source catalogue can be matched with this method,
with a reliability of $95$ per cent. We proceed to show that visual
classification will still remain an essential process for the cross-matching of
complex and extended radio sources. In the near future, the MIGHTEE survey will
be expanded in area to cover a total of $\sim$20~deg$^2$; thus the combination
of automated and visual identification will be critical. We compare redshift
distribution of SFG and AGN to the SKADS and T-RECS simulations and find more
AGN than predicted at $z \sim 1$.


  Industry 4.0 brings up new types of use cases, whereby mobile use cases play
a significant role. These use cases have stringent requirements on both
automation and communication systems that cannot be achieved with recent shop
floor technologies. Therefore, novel technologies such as IEEE time-sensitive
networking (TSN) and Open Platform Communications Unified Architecture (OPC UA)
are being introduced. In addition, for the realization of mobile use cases,
wireline technologies cannot be used and have to be replaced by wireless
connections, which have to meet the high demands of the industrial landscape.
Here, 5th generation wireless communication system (5G) is seen as a promising
candidate. Especially encouraging and similarly challenging is the cooperative
work of mobile robots, where particularly high demands on time synchronization
arise. Therefore, this paper introduces a concept for the integration of TSN
time synchronization (IEEE 802.1AS) conform with 5G to fulfill the requirements
of these use cases. Furthermore, the paper describes a testbed for discrete
manufacturing, consisting pre-dominantly of industrial equipment, in order to
evaluate the presented approach.


  It is well known that the conjugate gradient method and a quasi-Newton
method, using any well-defined update matrix from the one-parameter Broyden
family of updates, produce identical iterates on a quadratic problem with
positive-definite Hessian. This equivalence does not hold for any quasi-Newton
method. We define precisely the conditions on the update matrix in the
quasi-Newton method that give rise to this behavior. We show that the crucial
facts are, that the range of each update matrix lies in the last two dimensions
of the Krylov subspaces defined by the conjugate gradient method and that the
quasi-Newton condition is satisfied. In the framework based on a sufficient
condition to obtain mutually conjugate search directions, we show that the
one-parameter Broyden family is complete.
  A one-to-one correspondence between the Broyden parameter and the non-zero
scaling of the search direction obtained from the corresponding quasi-Newton
method compared to the one obtained in the conjugate gradient method is
derived. In addition, we show that the update matrices from the one-parameter
Broyden family are almost always well-defined on a quadratic problem with
positive-definite Hessian. The only exception is when the symmetric rank-one
update is used and the unit steplength is taken in the same iteration. In this
case it is the Broyden parameter that becomes undefined.


  Integral formulae for form factors of a large family of charged local
operators in SU(2) invariant Thirring model are given extending Smirnov's
construction of form factors of chargeless local operators in the sine-Gordon
model. New abelian symmetry acting on this family of local operators is found.
It creates Lukyanov's operators which are not in the above family of local
operators in general.


  We consider compressible pressureless fluid flows in Lagrangian coordinates
in one space dimension. We assume that the fluid self-interacts through a force
field generated by the fluid itself. We explain how this flow can be described
by a differential inclusion on the space of transport maps, in particular when
a sticky particle dynamics is assumed. We study a discrete particle
approximation and we prove global existence and stability results for solutions
of this system. In the particular case of the Euler-Poisson system in the
attractive regime our approach yields an explicit representation formula for
the solutions.


  The existence of a projective plane of order $p\equiv3\pmod{4}$, where $p$ is
a prime power, is shown to be equivalent to the existence of a balancedly
multi-splittable embeddable $p^2\times p(p+1)$ partial Hadamard matrix.


  The tensor flattenings appear naturally in quantum information when one
produces a density matrix by partially tracing the degrees of freedom of a pure
quantum state. In this paper, we study the joint $^*$-distribution of the
flattenings of large random tensors under mild assumptions, in the sense of
free probability theory. We show the convergence toward an operator-valued
circular system with amalgamation on permutation group algebras for which we
describe the covariance structure. As an application we describe the law of
large random density matrix of bosonic quantum states.


  The ARGO-YBJ experiment has been in stable data taking for 5 years at the
YangBaJing Cosmic Ray Observatory (Tibet, P.R. China, 4300 m a.s.l., 606
g/cm$^2$). With a duty-cycle greater than 86\% the detector collected about
5$\times $10$^{11}$ events in a wide energy range, from few hundreds GeV up to
about 10 PeV. A number of open problems in cosmic ray physics has been faced
exploiting different analyses. In this paper we summarize the latest results in
cosmic ray physics and in gamma-ray astronomy.


  We report a simultaneous measurement of a longitudinal spin Seebeck effect
(LSSE) and thermal conductivity in a Pt/${\rm Y_{3}Fe_{5}O_{12}}$ (YIG)/Pt
system in a temperature range from 10 to 300 K. By directly monitoring the
temperature difference in the system, we excluded thermal artifacts in the LSSE
measurements. It is found that both the LSSE signal and the thermal
conductivity of YIG exhibit sharp peaks at the same temperature, differently
from previous reports. The maximum LSSE coefficient is found to be
$S{\rm_{LSSE}}>10\ \mu{\rm V/K}$, one-order-of magnitude greater than the
previously reported values. The concomitant enhancement of the LSSE and thermal
conductivity of YIG suggests the strong correlation between magnon and phonon
transport in the LSSE.


  What is the observer's role in quantum measurement? Obviously, observers
prepare the apparatus, observe and interpret the measured results. Although the
observer will have a certain influence on the measurement results by setting up
the measuring apparatus, we don't believe human consciousness cause reducing of
wave packet; also observers are certainly required to interpret the measured
results with physical meanings. We believe observers build up their experience
of the external world by playing games with nature, and then "decode" the
nature based on their experiences. We propose a quantum decision theory
approach to explain the role of the observer in quantum measurements, and
pointed out that a set of quantum decision trees (strategies to answer natural
questions with yes/no logic) can be optimized to deal with the challenges of
nature through quantum genetic programming based on maximization of the
expected value of the observers; Quantum decision trees can discover the
dynamics rules of quantum entities and Just as classical mechanics uses the
principle of least action to obtain the trajectories of particles, we use the
principle of maximum expected value to approximately obtain the kinematic
"trajectories" of quantum entities by learning from natural historical "events"
(measured results); even we can "reconstruct" the past of quantum entity,
because we don't know the prior information of quantum entity, it is very
difficult to predict the future of the nature.


  In this paper, we determine bundles which compute the higher Clifford indices
for trigonal curves.


  We investigate equilibrium configurations of uniformly rotating neutron stars
in $R^2$ gravity with axion scalar field for GM1 equation of state (EoS) for
nuclear matter. The mass-radius diagram, mass-central energy density are
presented for some frequencies in comparison with static stars. We also compute
equatorial and polar radii and moment of inertia for stars. For axion field
$\phi$ the coupling in the form $\sim R^2\phi$ is assumed. Several interesting
results follow from our consideration. Maximal possible star mass with given
EoS increases due to the contribution of coupling term. We discovered the
possibility to increase maximal frequency of the rotation in comparison with
General Relativity. As a consequence the lower bound on mass of the fast
rotating stars decreases. For frequency $f=700$ Hz neutron stars with masses
$\sim M_\odot$ can exist for some choice of parameters (in General Relativity
for same EoS this limit is around $1.2 M_{\odot}$). Another feature of our
solutions is relatively small increase of stars radii for high frequencies in
comparison with static case. Thus, eventually the new class of neutron stars in
$R^2$ gravity with axions is discovered namely fast rotating compact stars with
intermediate masses.


  The Kepler map was derived by Petrosky (1986) and Chirikov and Vecheslavov
(1986) as a tool for description of the long-term chaotic orbital behaviour of
the comets in nearly parabolic motion. It is a two-dimensional area-preserving
map, describing the motion of a comet in terms of energy and time. Its second
equation is based on Kepler's third law, hence the title of the map. Since
1980s the Kepler map has become paradigmatic in a number of applications in
celestial mechanics and atomic physics. It represents an important kind of
general separatrix maps. Petrosky and Broucke (1988) used refined methods of
mathematical physics to derive analytical expressions for its single parameter.
These methods became available only in the second half of the 20th century, and
it may seem that the map is inherently a very modern mathematical tool. With
the help of the Jacobi integral I show that the Kepler map, including
analytical formulae for its parameter, can be derived by quite elementary
methods. The prehistory and applications of the Kepler map are considered and
discussed.


  Tree tensor networks, or tree-based tensor formats, are prominent model
classes for the approximation of high-dimensional functions in computational
and data science. They correspond to sum-product neural networks with a sparse
connectivity associated with a dimension tree and widths given by a tuple of
tensor ranks. The approximation power of these models has been proved to be
(near to) optimal for classical smoothness classes. However, in an empirical
risk minimization framework with a limited number of observations, the
dimension tree and ranks should be selected carefully to balance estimation and
approximation errors. We propose and analyze a complexity-based model selection
method for tree tensor networks in an empirical risk minimization framework and
we analyze its performance over a wide range of smoothness classes. Given a
family of model classes associated with different trees, ranks, tensor product
feature spaces and sparsity patterns for sparse tensor networks, a model is
selected (\`a la Barron, Birg\'e, Massart) by minimizing a penalized empirical
risk, with a penalty depending on the complexity of the model class and derived
from estimates of the metric entropy of tree tensor networks. This choice of
penalty yields a risk bound for the selected predictor. In a least-squares
setting, after deriving fast rates of convergence of the risk, we show that our
strategy is (near to) minimax adaptive to a wide range of smoothness classes
including Sobolev or Besov spaces (with isotropic, anisotropic or mixed
dominating smoothness) and analytic functions. We discuss the role of sparsity
of the tensor network for obtaining optimal performance in several regimes. In
practice, the amplitude of the penalty is calibrated with a slope heuristics
method. Numerical experiments in a least-squares regression setting illustrate
the performance of the strategy.


  To reduce the time-to-market of future aircraft, it is crucial to predict the
flight envelope accurately before building prototypes for flight tests. The
High-Lift Prediction Workshop (HLPW) series aims to assess the numerical
prediction capability of current CFD technology considering NASA's high-lift
version of the Common Research Model (CRM-HL). The present work contributes to
these collaborative efforts, quantifying sensitivities for RANS-based steady,
unsteady, and hybrid RANS/LES scale-resolving approaches. Uncertainties
associated with the choice of turbulence model, initialization strategies, grid
resolution, and iterative convergence at free-air conditions are covered. Near
stall, a large spread of RANS results was observed for different turbulence
models and initialization strategies, while iterative convergence appeared less
crucial for the present simulations. Steady and unsteady RANS simulations were
unable to predict the correct flow physics near CLmax, even for large grids.
Delayed Detached Eddy Simulations (DDES), however, showed good accuracy
compared with wind-tunnel experiments and predicted CLmax with an error of
around 5%. Compared to steady RANS, the computational cost of DDES was a factor
of ten higher. Lessons learned and potential best-practice strategies are
shared to aid future studies. While warm-started RANS simulations using SA
models are recommended at lower angles of attack, scale-resolving methods are
required near stall.


  We analyze confining mechanisms for L\'evy flights evolving under an
influence of external potentials. Given a stationary probability density
function (pdf), we address the reverse engineering problem: design a jump-type
stochastic process whose target pdf (eventually asymptotic) equals the
preselected one. To this end, dynamically distinct jump-type processes can be
employed. We demonstrate that one "targeted stochasticity" scenario involves
Langevin systems with a symmetric stable noise. Another derives from the
L\'evy-Schr\"odinger semigroup dynamics (closely linked with topologically
induced super-diffusions), which has no standard Langevin representation. For
computational and visualization purposes, the Cauchy driver is employed to
exemplify our considerations.


  We apply the relativistic chiral SU(3) Lagrangian density to kaon-nucleon
scattering imposing constraints from the pion-nucleon s- and p-wave threshold
parameters at chiral order $Q^2$. The s and u channel decouplet baryon exchange
is included explicitly and is found to play a crucial role in understanding the
empirical s- and p-wave nuclear kaon dynamics quantitatively.


  Can Visual Question Answering (VQA) systems perform just as well when
deployed in the real world? Or are they susceptible to realistic corruption
effects e.g. image blur, which can be detrimental in sensitive applications,
such as medical VQA? While linguistic or textual robustness has been thoroughly
explored in the VQA literature, there has yet to be any significant work on the
visual robustness of VQA models. We propose the first large-scale benchmark
comprising 213,000 augmented images, challenging the visual robustness of
multiple VQA models and assessing the strength of realistic visual corruptions.
Additionally, we have designed several robustness evaluation metrics that can
be aggregated into a unified metric and tailored to fit a variety of use cases.
Our experiments reveal several insights into the relationships between model
size, performance, and robustness with the visual corruptions. Our benchmark
highlights the need for a balanced approach in model development that considers
model performance without compromising the robustness.


  In this note we prove a Birkhoff type transitivity theorem for continuous
maps acting on non-separable completely metrizable spaces and we give some
applications for dynamics of bounded linear operators acting on complex
Fr\'{e}chet spaces. Among them we show that any positive power and any
unimodular multiple of a topologically transitive linear operator is
topologically transitive, generalizing similar results of S.I. Ansari and F.
Le\'{o}n-Saavedra V. M\"{u}ller for hypercyclic operators.


  The optical conductance of a multiple scattering medium is the total
transmitted light of a diffuse incoming beam. This quantity, very analogous to
the electronic conductance, exhibits universal conductance fluctuations. We
perform a detailed diagrammatic analysis of these fluctuations. With a
Kadanoff-Baym technique all the leading diagrams are systematically generated.
A cancellation of the short distance divergencies occurs, that yields a well
behaved theory. The analytical form of the fluctuations is calculated and
applied to optical systems. Absorption and internal reflections reduce the
fluctuations significantly.


  The production of a $W$ boson in association with a single charm quark is
studied using 140 $\mathrm{fb}^{-1}$ of $\sqrt{s} = 13\,\mathrm{TeV}$
proton-proton collision data collected with the ATLAS detector at the Large
Hadron Collider. The charm quark is tagged by a charmed hadron, reconstructed
with a secondary-vertex fit. The $W$ boson is reconstructed from an
electron/muon decay and the missing transverse momentum. The mesons
reconstructed are $D^{\pm} \to K^\mp \pi^\pm \pi^\pm$ and $D^{*\pm} \to D^{0}
\pi^\pm \to (K^\mp \pi^\pm) \pi^\pm$, where $p_{\text{T}}(e, \mu) >
30\,\mathrm{GeV}$, $|\eta(e, \mu)| < 2.5$, $p_{\text{T}}(D) > 8\,\mathrm{GeV}$,
and $|\eta(D)| < 2.2$. The integrated and normalized differential
cross-sections as a function of the pseudorapidity of the lepton from the $W$
boson decay, and of the transverse momentum of the meson, are extracted from
the data using a profile likelihood fit. The measured fiducial cross-sections
are $\sigma^{\mathrm{OS-SS}}_{\mathrm{fid}}(W^{-}{+}D^{+}) =
50.2\pm0.2\,\mathrm{(stat.)}\,^{+2.4}_{-2.3}\,\mathrm{(syst.)}\,\mathrm{pb}$,
$\sigma^{\mathrm{OS-SS}}_{\mathrm{fid}}(W^{+}{+}D^{-}) =
48.5\pm0.2\,\mathrm{(stat.)}\,^{+2.3}_{-2.2}\,\mathrm{(syst.)}\,\mathrm{pb}$,
$\sigma^{\mathrm{OS-SS}}_{\mathrm{fid}}(W^{-}{+}D^{*+}) =
51.1\pm0.4\,\mathrm{(stat.)}\,^{+1.9}_{-1.8}\,\mathrm{(syst.)}\,\mathrm{pb}$,
and $\sigma^{\mathrm{OS-SS}}_{\mathrm{fid}}(W^{+}{+}D^{*-}) =
50.0\pm0.4\,\mathrm{(stat.)}\,^{+1.9}_{-1.8}\,\mathrm{(syst.)}\,\mathrm{pb}$.
Results are compared with the predictions of next-to-leading-order quantum
chromodynamics calculations performed using state-of-the-art parton
distribution functions. The ratio of charm to anti-charm production
cross-sections is studied to probe the $s$-$\bar{s}$ quark asymmetry and is
found to be $R_c^\pm =
0.971\pm0.006\,\mathrm{(stat.)}\pm0.011\,\mathrm{(syst.)}$.


  It has been shown that fragmentation within self-gravitating, turbulent
molecular clouds ("turbulent fragmentation") can naturally explain the observed
properties of protostellar cores, including the core mass function (CMF). Here,
we extend recently-developed analytic models for turbulent fragmentation to
follow the time-dependent hierarchical fragmentation of self-gravitating cores,
until they reach effectively infinite density (and form stars). We show that
turbulent fragmentation robustly predicts two key features of the IMF. First, a
high-mass power-law scaling very close to the Salpeter slope, which is a
generic consequence of the scale-free nature of turbulence and self-gravity. We
predict the IMF slope (-2.3) is slightly steeper then the CMF slope (-2.1),
owing to the slower collapse and easier fragmentation of large cores. Second, a
turnover mass, which is set by a combination of the CMF turnover mass (a couple
solar masses, determined by the `sonic scale' of galactic turbulence, and so
weakly dependent on galaxy properties), and the equation of state (EOS). A
"soft" EOS with polytropic index $\gamma<1.0$ predicts that the IMF slope
becomes "shallow" below the sonic scale, but fails to produce the full turnover
observed. An EOS which becomes "stiff" at sufficiently low surface densities
$\Sigma_{\rm gas} \sim 5000\,M_{\odot}\,{\rm pc^{-2}}$, and/or models where
each collapsing core is able to heat and effectively stiffen the EOS of a
modest mass ($\sim 0.02\,M_{\odot}$) of surrounding gas, are able to reproduce
the observed turnover. Such features are likely a consequence of more detailed
chemistry and radiative feedback.


  We propose a one-dimensional electron model with parameters modulated
adiabatically in closed cycles, which can continuously pump spin to leads. By
defining the spin-polarized Wannier functions, we show that the spin pump is
protected by the spin Chern numbers, so that it is stable to perturbations
violating the time-reversal symmetry and spin conservation. Our work
demonstrates the possibility and principle to realize topological spin pumps
independent of any symmetries, and also suggests a possible way to
experimentally observe the bulk topological invariants.


  The important role played by magnetic reconnection in the early acceleration
of coronal mass ejections (CMEs) has been widely discussed. However, as CMEs
may have expansion speeds comparable to their propagation speeds in the corona,
it is not clear whether and how reconnection contributes to the true
acceleration and expansion separately. To address this question, we analyze the
dynamics of a moderately fast CME on 2013 February 27, associated with a
continuous acceleration of its front into the high corona, even though its
speed had reached $\sim$700~km~s$^{-1}$ and larger than the solar wind speed.
The apparent CME acceleration is found to be due to the CME expansion in the
radial direction. The CME true acceleration, i.e., the acceleration of its
center, is then estimated by taking into account the expected deceleration
caused by the solar wind drag force acting on a fast CME. It is found that the
true acceleration and the radial expansion have similar magnitudes. We find
that magnetic reconnection occurs after the CME eruption and continues during
the CME propagation in the high corona, which contributes to the CME dynamic
evolution. Comparison between the apparent acceleration related to the
expansion and the true acceleration that compensates the drag shows that, for
this case, magnetic reconnection contributes almost equally to the CME
expansion and to the CME acceleration. The consequences of these measurements
for the evolution of CMEs as they transit from the corona to the heliosphere
are discussed.


  Low frequency resistance variations due to mobility fluctuations is one of
the key factors of $1/f$ noise in metallic conductors. According to theory,
such noise in a two-dimensional (2D) device can be suppressed to zero at small
magnetic fields, implying important technological benefits for low noise 2D
devices. In this work, we provide direct evidence of anisotropic mobility
fluctuations by demonstrating a strong field-induced suppression of noise in a
high-mobility graphene Corbino disk, even though the device displays only a
tiny amount of $1/f$ noise inherently. The suppression of the $1/f$ noise
depends on charge density, showing less non-uniform mobility fluctuations away
from the Dirac point with charge puddles. We model our results using a new
approach based on impurity clustering dynamics and find our results consistent
with the $1/f$ noise induced by scattering of carriers on mobile impurities
forming clusters.


  Recovering the skeletal shape of an animal from a monocular video is a
longstanding challenge. Prevailing animal reconstruction methods often adopt a
control-point driven animation model and optimize bone transforms individually
without considering skeletal topology, yielding unsatisfactory shape and
articulation. In contrast, humans can easily infer the articulation structure
of an unknown animal by associating it with a seen articulated character in
their memory. Inspired by this fact, we present CASA, a novel Category-Agnostic
Skeletal Animal reconstruction method consisting of two major components: a
video-to-shape retrieval process and a neural inverse graphics framework.
During inference, CASA first retrieves an articulated shape from a 3D character
assets bank so that the input video scores highly with the rendered image,
according to a pretrained language-vision model. CASA then integrates the
retrieved character into an inverse graphics framework and jointly infers the
shape deformation, skeleton structure, and skinning weights through
optimization. Experiments validate the efficacy of CASA regarding shape
reconstruction and articulation. We further demonstrate that the resulting
skeletal-animated characters can be used for re-animation.


  There are several theories or processes which may underlie quantum mechanics
and make it deterministic. Some references are given in the main text. Any such
theory, plus a number of reasonable assumptions, implies the existence of what
I have called ``special" states. The assumptions are conservation laws,
obedience (up to a point) of Schrodinger's equation, and a single world, in the
sense of the many worlds interpretation (the last one a consequence of any
deterministic theory). This article also, for clarity, gives an example of a
``special" state. There is an experimental test of the ``special" state theory.


  We investigate the $\eta'$ photoproduction off the nucleon with a particular
interest in the effect of the final-state interaction (FSI) of the $\eta'$
meson and nucleon $(\eta'N)$ based on three-flavor linear sigma model. We find
an enhancement in the cross section of the $\eta'$ photoproduction near the
$\eta'N$-threshold energy owing to the $\eta'N$ FSI. With the $\eta'$ meson at
forward angles, the energy dependence near the $\eta'N$ threshold is well
reproduced with the $\eta'N$ FSI. The cross section at backward angles can also
be a good probe to investigate the strength of the $\eta'N$ interaction.


  Symmetry relationships for optical observations of matter generally fall into
several common scattering geometries. The 'planetary' configuration is
preferred among a group of observers of extraterrestrial planets, 'laboratory'
observations are performed in the biomedical research field and the LIDAR
configuration is preferred among those using lasers to probe optical properties
of horizontal surfaces with mirror or axial symmetry. This paper starts with
the Stokes matrix formalism and uses symmetries of Mueller matrix scattering to
establishes links between the mathematical symmetries of each geometric
configuration.


  We consider the following \emph{model repair problem}: given a finite Kripke
structure $M$ and a specification formula $\eta$ in some modal or temporal
logic, determine if $M$ contains a substructure $M'$ (with the same initial
state) that satisfies $\eta$. Thus, $M$ can be ``repaired'' to satisfy the
specification $\eta$ by deleting some transitions.
  We map an instance $(M, \eta)$ of model repair to a boolean formula
$\repfor(M,\eta)$ such that $(M, \eta)$ has a solution iff $\repfor(M,\eta)$ is
satisfiable. Furthermore, a satisfying assignment determines which transitions
must be removed from $M$ to generate a model $M'$ of $\eta$. Thus, we can use
any SAT solver to repair Kripke structures. Furthermore, using a complete SAT
solver yields a complete algorithm: it always finds a repair if one exists.
  We extend our method to repair finite-state shared memory concurrent
programs, to solve the discrete event supervisory control problem
\cite{RW87,RW89}, to check for the existence of symmettric solutions
\cite{ES93}, and to accomodate any boolean constraint on the existence of
states and transitions in the repaired model.
  Finally, we show that model repair is NP-complete for CTL, and logics with
polynomial model checking algorithms to which CTL can be reduced in polynomial
time. A notable example of such a logic is Alternating-Time Temporal Logic
(ATL).


  This article surveys quantum computational complexity, with a focus on three
fundamental notions: polynomial-time quantum computations, the efficient
verification of quantum proofs, and quantum interactive proof systems.
Properties of quantum complexity classes based on these notions, such as BQP,
QMA, and QIP, are presented. Other topics in quantum complexity, including
quantum advice, space-bounded quantum computation, and bounded-depth quantum
circuits, are also discussed.


  The skin forms an efficient barrier against the environment, and rapid
cutaneous wound healing after injury is therefore essential. Healing of the
uppermost layer of the skin, the epidermis, involves collective migration of
keratinocytes, which requires coordinated polarization of the cells. To study
this process, we developed a model that allows analysis of live-cell images of
migrating keratinocytes in culture based on a small number of parameters,
including the radius of the cells, their mass and their polarization. This
computational approach allowed the analysis of cell migration at the front of
the wound and a reliable identification and quantification of the impaired
polarization and migration of keratinocytes from mice lacking fibroblast growth
factors 1 and 2 an established model of impaired healing. Therefore, our
modeling approach is suitable for large-scale analysis of migration phenotypes
of cells with specific genetic defects or upon treatment with different
pharmacological agents.


  A review is given of quantum network models in class C which, on a suitable
2d lattice, describe the spin quantum Hall plateau transition. On a general
class of graphs, however, many observables of such models can be mapped to
those of a classical walk in a random environment, thus relating questions of
quantum and classical localization. In many cases it is possible to make
rigorous statements about the latter through the relation to associated
percolation problems, in both two and three dimensions.


  We formulate the hadronic tensor $W_{\mu\nu}$ of deep inelastic scattering in
the path-integral formalism. It is shown that there are 3 gauge invariant and
topologically distinct contributions. Besides the valence contribution, there
are two sources for the sea -- one in the connected insertion and the other in
the disconnected insertion. The operator product expansion is carried out in
this formalism. The operator rescaling and mixing reveal that the connected sea
partons evolve the same way as the valence, i.e. their evolution is decoupled
from the disconnected sea and the gluon distribution functions. We explore the
phenomenological consequences of this classification in terms of the small x
behavior, Gottfried sum rule violation, and the flavor dependence. In
particular, we point out that in the nucleon $\bar{u}$ and $\bar{d}$ partons
have both the connected and disconnected sea contributions; whereas, $\bar{s}$
parton has only the disconnected sea contribution. This difference between
$\bar{u} + \bar{d}$ and $\bar{s}$, as far as we know, has not been taken into
account in the fitting of parton distribution functions to experiments.


  The holographic Witten-Sakai-Sugimoto model is often employed to describe
strongly-coupled baryonic and isospin-asymmetric matter, for example in the
context of neutron stars. Here we consider the case of vanishing baryon
chemical potential, where detailed comparisons to data from lattice QCD are
possible. To this end, we extend previous works by including a realistic pion
mass and pion condensation into the decompactified limit of the model and
evaluate the system for arbitrary isospin chemical potentials and temperatures.
After suitably fixing the 3 parameters of the model, we find that the overall
phase structure is in excellent agreement with lattice results. This also holds
for observables at low temperatures in the strongly coupled regime, while we
discover and discuss some discrepancies at large temperatures. Our findings
give reassurance for the validity of previous and future applications of this
model and highlight the aspects where improvements are needed.


  EX Lupi-type objects (EXors) form a sub-class of T Tauri stars, defined by
sudden sporadic flare-ups of 1-5 magnitudes at optical wavelengths. These
eruptions are attributed to enhanced mass accretion from the circumstellar disk
to the star, and may constitute important events in shaping the structure of
the inner disk and the forming planetary system. Although disk properties must
play a fundamental role in driving the outbursts, they are surprisingly poorly
known. In order to characterize the dust and gas components of EXor disks, here
we report on observations of the $^{12}$CO J=3-2 and 4-3 lines, and the
$^{13}$CO 3-2 line in EX Lup, the prototype of the EXor class. We reproduce the
observed line fluxes and profiles with a line radiative transfer model, and
compare the obtained parameters with corresponding ones of other T Tauri disks.


  This paper is devoted to establish semiclassical Weyl formulae for the Robin
Laplacian on smooth domains in any dimension. Theirs proofs are reminiscent of
the Born-Oppenheimer method.


  Given copies of a quantum state $\rho$, a shadow tomography protocol aims to
learn all expectation values from a fixed set of observables, to within a given
precision $\epsilon$. We say that a shadow tomography protocol is triply
efficient if it is sample- and time-efficient, and only employs measurements
that entangle a constant number of copies of $\rho$ at a time. The classical
shadows protocol based on random single-copy measurements is triply efficient
for the set of local Pauli observables. This and other protocols based on
random single-copy Clifford measurements can be understood as arising from
fractional colorings of a graph $G$ that encodes the commutation structure of
the set of observables. Here we describe a framework for two-copy shadow
tomography that uses an initial round of Bell measurements to reduce to a
fractional coloring problem in an induced subgraph of $G$ with bounded clique
number. This coloring problem can be addressed using techniques from graph
theory known as chi-boundedness. Using this framework we give the first triply
efficient shadow tomography scheme for the set of local fermionic observables,
which arise in a broad class of interacting fermionic systems in physics and
chemistry. We also give a triply efficient scheme for the set of all $n$-qubit
Pauli observables. Our protocols for these tasks use two-copy measurements,
which is necessary: sample-efficient schemes are provably impossible using only
single-copy measurements. Finally, we give a shadow tomography protocol that
compresses an $n$-qubit quantum state into a $\text{poly}(n)$-sized classical
representation, from which one can extract the expected value of any of the
$4^n$ Pauli observables in $\text{poly}(n)$ time, up to a small constant error.


  Generative models have had a profound impact on vision and language, paving
the way for a new era of multimodal generative applications. While these
successes have inspired researchers to explore using generative models in
science and engineering to accelerate the design process and reduce the
reliance on iterative optimization, challenges remain. Specifically,
engineering optimization methods based on physics still outperform generative
models when dealing with constrained environments where data is scarce and
precision is paramount. To address these challenges, we introduce Diffusion
Optimization Models (DOM) and Trajectory Alignment (TA), a learning framework
that demonstrates the efficacy of aligning the sampling trajectory of diffusion
models with the optimization trajectory derived from traditional physics-based
methods. This alignment ensures that the sampling process remains grounded in
the underlying physical principles. Our method allows for generating feasible
and high-performance designs in as few as two steps without the need for
expensive preprocessing, external surrogate models, or additional labeled data.
We apply our framework to structural topology optimization, a fundamental
problem in mechanical design, evaluating its performance on in- and
out-of-distribution configurations. Our results demonstrate that TA outperforms
state-of-the-art deep generative models on in-distribution configurations and
halves the inference computational cost. When coupled with a few steps of
optimization, it also improves manufacturability for out-of-distribution
conditions. By significantly improving performance and inference efficiency,
DOM enables us to generate high-quality designs in just a few steps and guide
them toward regions of high performance and manufacturability, paving the way
for the widespread application of generative models in large-scale data-driven
design.


  Whisper, the recently developed multilingual weakly supervised model, is
reported to perform well on multiple speech recognition benchmarks in both
monolingual and multilingual settings. However, it is not clear how Whisper
would fare under diverse conditions even on languages it was evaluated on such
as Arabic. In this work, we address this gap by comprehensively evaluating
Whisper on several varieties of Arabic speech for the ASR task. Our evaluation
covers most publicly available Arabic speech data and is performed under n-shot
(zero-, few-, and full) finetuning. We also investigate the robustness of
Whisper under completely novel conditions, such as in dialect-accented standard
Arabic and in unseen dialects for which we develop evaluation data. Our
experiments show that although Whisper zero-shot outperforms fully finetuned
XLS-R models on all datasets, its performance deteriorates significantly in the
zero-shot setting for five unseen dialects (i.e., Algeria, Jordan, Palestine,
UAE, and Yemen).


  This paper provides a detailed description of the data collection and machine
learning model used in our recent PNAS paper "Flat Teams Drive Scientific
Innovation" Xu et al. [2022a]. Here, we discuss how the features of scientific
publication can be used to estimate the implicit hierarchy in the corresponding
author teams. Besides, we also describe the method of evaluating the impact of
team hierarchy on scientific outputs. More details will be updated in this
article continuously. Raw data and Readme document can be accessed in this
GitHub repository Xu et al. [2022b].


  The recursive least-squares (RLS) algorithm is one of the most well-known
algorithms used in adaptive filtering, system identification and adaptive
control. Its popularity is mainly due to its fast convergence speed, which is
considered to be optimal in practice. In this paper, RLS methods are used to
solve reinforcement learning problems, where two new reinforcement learning
algorithms using linear value function approximators are proposed and analyzed.
The two algorithms are called RLS-TD(lambda) and Fast-AHC (Fast Adaptive
Heuristic Critic), respectively. RLS-TD(lambda) can be viewed as the extension
of RLS-TD(0) from lambda=0 to general lambda within interval [0,1], so it is a
multi-step temporal-difference (TD) learning algorithm using RLS methods. The
convergence with probability one and the limit of convergence of RLS-TD(lambda)
are proved for ergodic Markov chains. Compared to the existing LS-TD(lambda)
algorithm, RLS-TD(lambda) has advantages in computation and is more suitable
for online learning. The effectiveness of RLS-TD(lambda) is analyzed and
verified by learning prediction experiments of Markov chains with a wide range
of parameter settings. The Fast-AHC algorithm is derived by applying the
proposed RLS-TD(lambda) algorithm in the critic network of the adaptive
heuristic critic method. Unlike conventional AHC algorithm, Fast-AHC makes use
of RLS methods to improve the learning-prediction efficiency in the critic.
Learning control experiments of the cart-pole balancing and the acrobot
swing-up problems are conducted to compare the data efficiency of Fast-AHC with
conventional AHC. From the experimental results, it is shown that the data
efficiency of learning control can also be improved by using RLS methods in the
learning-prediction process of the critic. The performance of Fast-AHC is also
compared with that of the AHC method using LS-TD(lambda). Furthermore, it is
demonstrated in the experiments that different initial values of the variance
matrix in RLS-TD(lambda) are required to get better performance not only in
learning prediction but also in learning control. The experimental results are
analyzed based on the existing theoretical work on the transient phase of
forgetting factor RLS methods.


  We consider sudden quenches across quantum phase transitions in the $S=1$ XXZ
model starting from the Haldane phase. We demonstrate that dynamical phase
transitions may occur during these quenches that are identified by
nonanalyticities in the rate function for the return probability. In addition,
we show that the temporal behavior of the string order parameter is intimately
related to the subsequent dynamical phase transitions. We furthermore find that
the dynamical quantum phase transitions can be accompanied by enhanced two-site
entanglement.


  We report on a population of X-ray weak quasars with similar UV emission-line
properties to those of the remarkable quasar PHL 1811. All radio-quiet PHL 1811
analogs are notably X-ray weak by a mean factor of ~13, with hints of heavy
X-ray absorption. Correlations between the X-ray weakness and UV emission-line
properties suggest that PHL 1811 analogs may have extreme wind-dominated broad
emission-line regions (BELRs). We propose an AGN geometry that can potentially
unify the PHL 1811 analogs and the general population of weak-line quasars.


  Current transformer language models (LM) are large-scale models with billions
of parameters. They have been shown to provide high performances on a variety
of tasks but are also prone to shortcut learning and bias. Addressing such
incorrect model behavior via parameter adjustments is very costly. This is
particularly problematic for updating dynamic concepts, such as moral values,
which vary culturally or interpersonally. In this work, we question the current
common practice of storing all information in the model parameters and propose
the Revision Transformer (RiT) to facilitate easy model updating. The specific
combination of a large-scale pre-trained LM that inherently but also diffusely
encodes world knowledge with a clear-structured revision engine makes it
possible to update the model's knowledge with little effort and the help of
user interaction. We exemplify RiT on a moral dataset and simulate user
feedback demonstrating strong performance in model revision even with small
data. This way, users can easily design a model regarding their preferences,
paving the way for more transparent AI models.


  In this Comment it is argued that Stishov et al. [Phys. Rev. B 86, 064433
(2012)] incorrectly estimated concentrations of (supposed) paramagnetic centers
with \mu_eff = 4.8\mu_B in the investigated CoSi crystals. Correct estimation
gives concentrations of such centers from 25 to 50 times smaller than reported
(appr. 0.04 to 0.16% instead of appr. 2 to 4%). Also the reported data on
temperature dependence of resistivity \rho(T) of four CoSi crystals prepared in
different Labs are so close to each other at T = 250 to 300K that it is
extremely unlikely to be reproducible for any reasonable accuracy of
resistivity measurements. These and some other problems of the paper are
related to the key points of the authors argumentation. As a result their main
conclusions become unjustified.


  We compute the reduced version of Khovanov and Rozansky's sl(N) homology for
two-bridge knots and links. The answer is expressed in terms of the HOMFLY
polynomial and signature.