  The IceCube Neutrino Observatory deployed 5160 digital optical modules (DOMs)
on 86 cables, called strings, in a cubic kilometer of deep glacial ice below
the geographic South Pole. These record the Cherenkov light of passing charged
particles. Knowledge of the DOM positions is vital for event reconstruction.
While vertical positions have been calibrated, previous in-situ geometry
calibration methods have been unable to measure horizontal deviations from the
surface positions, largely due to degeneracies with ice model uncertainties.
Thus the lateral position of the surface position of each hole is to date in
almost all cases used as the lateral position of all DOMs on a given string.
With the recent advances in ice modeling, two new in-situ measurements have now
been undertaken. Using a large sample of muon tracks, the individual positions
of all DOMs on a small number of strings around the center of the detector have
been fitted.
  Verifying the results against LED calibration data shows that the
string-average corrections improve detector modeling. Directly fitting
string-average geometry corrections for the full array using LED data agrees
with the average corrections as derived from muons where available. Analyses
are now ongoing to obtain per-DOM positions using both methods and in addition,
methods are being developed to correct the recorded arrival times for the
expected scattering delay, allowing for multilateration of the positions using
nanosecond-precision propagation delays.


  Spin systems such as silicon or nitrogen vacancy centers in diamond, quantum
dots and quantum dot molecules coupled to optical cavities appear as key
elements for creating quantum networks as not only constituting the nodes of
the network, but also assisting the creation of photonic networks. Here we
study deterministic preparation of arbitrary size $W$ states with spin systems.
We present an efficient operation on three qubits, two being the logical qubits
and one being the ancillary qubit, where no interaction between the logical
qubits are required. The proposed operation can create a $W$-type
Einstein-Podolsky-Rosen (EPR) pair from two separable qubits, and expand that
EPR pair or an arbitrary size $W$ state by one, creating a $W$-like state.
Taking this operation as the fundamental building block, we show how to create
a large scale $W$ state out of separable qubits, or double the size of a $W$
state. Based on this operation and focusing on nitrogen vacancy (NV) centers in
diamond as an exemplary spin system, we propose a setup for preparing $W$
states of circularly polarized photons, assisted by a single spin qubit, where
no photon-photon interactions are required. Next, we propose a setup for
preparing $W$ states of spin qubits of spatially separated systems, assisted by
a single photon. We also analyze the effects of possible imperfections in
implementing the gates on the fidelity of the generated $W$ states. In our
setups, neither post-measurement, nor post-processing on the states of spin or
photonic qubit is required. Our setups can be implemented with current
technology, and we anticipate that they contribute to quantum science and
technologies.


  M82 is one of the best studied starburst galaxies in the local universe, and
is consequently a benchmark for studying star formation feedback at both low
and high redshift. We present new VLA HI observations that reveal the cold gas
kinematics along the minor axis in unprecedented detail. This includes the
detection of HI up to 10 kpc along the minor axis toward the South and beyond 5
kpc to the North. A surprising aspect of these observations is that the
line-of-sight HI velocity decreases substantially from about 120 km/s to 50
km/s from 1.5 to 10 kpc off the midplane. The velocity profile is not
consistent with the HI gas cooling from the hot wind. We demonstrate that the
velocity decrease is substantially greater than the deceleration expected from
gravitational forces alone. If the HI consists of a continuous population of
cold clouds, some additional drag force must be present, and the magnitude of
the drag force places a joint constraint on the ratio of the ambient medium to
the typical cloud size and density. We also show that the HI kinematics are
inconsistent with a simple conical outflow centered on the nucleus, but instead
require the more widespread launch of the HI over the ~1 kpc extent of the
starburst region. Regardless of the launch mechanism for the HI gas, the
observed velocity decrease along the minor axis is sufficiently great that the
HI may not escape the halo of M82. We estimate the HI outflow rate is much less
than 1 M$_{\odot}$ per year at 10 kpc off the midplane.


  We study capillary condensation in a bath consisting of active Brownian
particles (ABPs) and the forces acting on the capillary close to the
motility-induced phase separation (MIPS). The capillary is modelled as two
parallel rods of high aspect ratio which are fixed in space. We consider a bath
of ABPs having a self-propulsion speed much larger than the critical speed
necessary for MIPS to occur. For a given particle speed, we gradually increase
the packing fraction of ABPs, starting from a homogeneous dilute phase of ABPs
and going towards the binodal of MIPS. Depending on the packing fraction of
ABPs and capillary width, we find that the effective force between the
capillary rods can be either attractive or repulsive. In fact, with increasing
width it shows damped oscillations as long as capillary condensation occurs. We
analyze them in detail by studying the distribution of particle distances from
the inner and outer wall of the capillary, respectively. In addition, we
examine the capillary in the active bath prepared under conditions close to the
critical point. We do not observe signs of the presence of long-range Casimir
interactions.


  Recent results from the LHC's first run have revealed intriguing departures
from lepton flavour universality in the semi-leptonic decays of $B$-mesons. We
discuss the complementary role that rare kaon decays can provide in testing new
physics explanations of these flavour anomalies. In the framework of minimal
flavour violation, we relate the chiral low-energy constants involved in
$K\to\pi\ell\ell'$ and $K\to\ell\ell'$ ($\ell = \mu \mbox{ or } e$) with the
new physics Wilson coefficients of the $b\to s$ effective Hamiltonian. We
comment on the determination of these low-energy constants at NA62 and future
kaon experiments, as well as the required improvements in sensitivity necessary
to test the $B$-physics anomalies in the kaon sector.


  The licas (lightweight Internet-based communication for autonomic services)
system is a Java-based open source framework for building service-based
networks, similar to what you would use a Cloud or SOA platform for. The
framework comes with a server for running the services on, mechanisms for
adding services to the server, mechanisms for linking services with each other,
and mechanisms for allowing the services to communicate with each other. The
general architecture of the system is now fairly well set, where this paper
describes recent developments that have focused on making the framework more
robust and additional features for easier programming.


  Convolutional Neural Network (CNN) recognition rates drop in the presence of
noise. We demonstrate a novel method of counteracting this drop in recognition
rate by adjusting the biases of the neurons in the convolutional layers
according to the noise conditions encountered at runtime. We compare our
technique to training one network for all possible noise levels, dehazing via
preprocessing a signal with a denoising autoencoder, and training a network
specifically for each noise level. Our system compares favorably in terms of
robustness, computational complexity and recognition rate.


  By means of density functional theory (DFT) calculations we have
quantitatively estimated the impact of the spontaneous polarization (SP) of the
SiC(0001) substrate on the electronic properties of quasi-freestanding graphene
(QFG) decoupled from the SiC by H intercalation. To correctly include within
standard DFT slab calculations the influence of the SP, which is a bulk
property, on a surface confined property such as the graphene's doping, we
attach a double gold layer at the C-terminated bottom of the slab which
introduces a metal induced gap state that pins the chemical potential within
the gap. Furthermore, expanding the interlayer distances at the bottom of the
slab creates a local dipole moment which counters that arising from the slab's
polar character and allows to align the location of the graphene's Dirac point
(DP) for cubic SiC(111) with the chemical potential. Thus, the DP shifts
obtained for other polytypes under the same slab model become an almost direct
measurement of the SP-induced doping. Our results confirm the recent proposal
that the SP induces the experimentally observed p-type doping in the graphene
layer which can achieve DP shifts of up to several hundreds of meV (or
equivalently, $\sim 10^{13} e$/cm$^2$) for specific polytypes. The doping is
found to increase with the hexagonality of the polytype and its thickness. For
the slab thickensses considered (6-12 SiC bilayers) an ample, almost
continuous, range of doping values can be achieved by tuning the number of
stacking defects and their location with respect to the surface. The slab model
is next generalized by performing large scale DFT calculations where
self-doping is included in the QFG via point defects (vacancy plus a H atom)
thus allowing to estimate the interplay between both sources of p-doping (SP-
versus defect-induced) which turns out to be essentially additive.


  Human activity recognition has wide applications in medical research and
human survey system. In this project, we design a robust activity recognition
system based on a smartphone. The system uses a 3-dimentional smartphone
accelerometer as the only sensor to collect time series signals, from which 31
features are generated in both time and frequency domain. Activities are
classified using 4 different passive learning methods, i.e., quadratic
classifier, k-nearest neighbor algorithm, support vector machine, and
artificial neural networks. Dimensionality reduction is performed through both
feature extraction and subset selection. Besides passive learning, we also
apply active learning algorithms to reduce data labeling expense. Experiment
results show that the classification rate of passive learning reaches 84.4% and
it is robust to common positions and poses of cellphone. The results of active
learning on real data demonstrate a reduction of labeling labor to achieve
comparable performance with passive learning.


  Recent studies point towards nontriviality of the ergodic phase in systems
exhibiting many-body localization (MBL), which shows subexponential relaxation
of local observables, subdiffusive transport and sublinear spreading of the
entanglement entropy. Here we review the dynamical properties of this phase and
the available numerically exact and approximate methods for its study. We
discuss in which sense this phase could be considered ergodic and present
possible phenomenological explanations of its dynamical properties. We close by
analyzing to which extent the proposed explanations were verified by numerical
studies and present the open questions in this field.


  The quark behaviour in the background of intensive stochastic gluon field is
studied. An approximate procedure for calculating the effective Hamiltonian is
developed and the corresponding ground state within the Hartree-Fock-Bogolyubov
approach is found. The comparative analysis of various model Hamiltonian is
given and transition to the chiral limit in the Keldysh model is discused in
detail.


  We have simulated the formation of an X-ray cluster in a cold dark matter
universe using 12 different codes. The codes span the range of numerical
techniques and implementations currently in use, including SPH and grid methods
with fixed, deformable or multilevel meshes. The goal of this comparison is to
assess the reliability of cosmological gas dynamical simulations of clusters in
the simplest astrophysically relevant case, that in which the gas is assumed to
be non-radiative. We compare images of the cluster at different epochs, global
properties such as mass, temperature and X-ray luminosity, and radial profiles
of various dynamical and thermodynamical quantities. On the whole, the
agreement among the various simulations is gratifying although a number of
discrepancies exist. Agreement is best for properties of the dark matter and
worst for the total X-ray luminosity. Even in this case, simulations that
adequately resolve the core radius of the gas distribution predict total X-ray
luminosities that agree to within a factor of two. Other quantities are
reproduced to much higher accuracy. For example, the temperature and gas mass
fraction within the virial radius agree to about 10%, and the ratio of specific
kinetic to thermal energies of the gas agree to about 5%. Various factors
contribute to the spread in calculated cluster properties, including
differences in the internal timing of the simulations. Based on the overall
consistency of results, we discuss a number of general properties of the
cluster we have modelled.


  Oscillation can be observed in candle flames under certain circumstances.
This research theoretically proposed an hydrodynamic-instability-based approach
towards the oscillation and coupling of candle flames, claiming that the
visible flame is part of a jet flow undergoing three stages: laminar, wave, and
turbulence. In the ordinary stable combustion the visible flame is in the
laminar stage, while under these oscillating circumstances it is in the surface
wave stage. In-phase coupling was explained as two jet flows merging into one,
and anti-phase coupling occur when mergence becomes unavailable. The Schlieren
image experiments, frequency measuring experiments and some "disturbance"
experiments were conducted to support this view. Mathematical models were also
proposed for description.


  User-defined keyword spotting is a task to detect new spoken terms defined by
users. This can be viewed as a few-shot learning problem since it is
unreasonable for users to define their desired keywords by providing many
examples. To solve this problem, previous works try to incorporate
self-supervised learning models or apply meta-learning algorithms. But it is
unclear whether self-supervised learning and meta-learning are complementary
and which combination of the two types of approaches is most effective for
few-shot keyword discovery. In this work, we systematically study these
questions by utilizing various self-supervised learning models and combining
them with a wide variety of meta-learning algorithms. Our result shows that
HuBERT combined with Matching network achieves the best result and is robust to
the changes of few-shot examples.


  This report reviews the recent experimental results from the CLAS
collaboration (Hall B of Jefferson Lab, or JLab) on Deeply Virtual Compton
Scattering (DVCS) and Deeply Virtual Meson Production (DVMP) and discusses
their interpretation in the framework of Generalized Parton Distributions
(GPDs). The impact of the experimental data on the applicability of the GPD
mechanism to these exclusive reactions is discussed. Initial results obtained
from JLab 6 GeV data indicate that DVCS might already be interpretable in this
framework while GPD models fail to describe the exclusive meson production
(DVMP) data with the GPD parameterizations presently used. An exception is the
$\phi$ meson production for which the GPD mechanism appears to apply. The
recent global analyses aiming to extract GPDs from fitting DVCS CLAS and world
data are discussed. The GPD experimental program at CLAS12, planned with the
upcoming 12 GeV upgrade of JLab, is briefly presented.


  The ultraviolet (UV) emission from the most numerous stars in the universe, M
dwarfs, impacts the formation, chemistry, atmospheric stability, and surface
habitability of their planets. We have analyzed the spectral evolution of UV
emission from M0-M2.5 (0.3-0.6 Msun) stars as a function of age, rotation, and
Rossby number, using Hubble Space Telescope observations of Tucana Horologium
(40 Myr), Hyades (650 Myr), and field (2-9 Gyr) objects. The quiescent surface
flux of their C II, C III, C IV, He II, N V, Si III, and Si IV emission lines,
formed in the stellar transition region, remains elevated at a constant level
for 240 $\pm$ 30 Myr before declining by 2.1 orders of magnitude to an age of
10 Gyr. Mg II and far-UV pseudocontinuum emission, formed in the stellar
chromosphere, exhibit more gradual evolution with age, declining by 1.3 and 1.7
orders of magnitude, respectively. The youngest stars exhibit a scatter of 0.1
dex in far-UV line and pseudocontinuum flux attributable only to rotational
modulation, long-term activity cycles, or an unknown source of variability.
Saturation-decay fits to these data can predict an M0-M2.5 star's quiescent
emission in UV lines and the far-UV pseudocontinuum with an accuracy of roughly
0.2-0.3 dex, the most accurate means presently available. Predictions of UV
emission will be useful for studying exoplanetary atmospheric evolution, the
destruction and abiotic production of biologically relevant molecules, and
interpreting infrared and optical planetary spectra measured with observatories
like the James Webb Space Telescope.


  BaFe2(PO4)2 is an unusual Ising insulating ferromagnet based on the Fe$^{2+}$
spin $S$ = 2 ion, the susceptibility of which suggests a large orbital
component to the Fe local moment. We apply density functional theory based
methods to obtain a microscopic picture of the competing interactions and the
critical role of spin-orbit coupling (SOC) in this honeycomb lattice system.
The low-temperature ferromagnetic phase displays a half-semimetallic Dirac
point pinning the Fermi level and preventing gap opening before consideration
of SOC, presenting a case in which correlation effects modeled by a repulsive
Hubbard $U$ fail to open a gap. Simultaneous inclusion of both correlation and
SOC drives a large orbital moment in excess of 0.7 $\mu_B$ (essentially $L$ =
1) for spin aligned along the $\hat{c}$ axis, with a gap comparable with the
inferred experimental value. The large orbital moment accounts for the large
Ising anisotropy, in spite of the small magnitude of the SOC strength on the
3$d$ (Fe) ion. Ultimately, the Mott-Hubbard gap is enabled by degeneracy
lifting by SOC and the large Fe moments, rather than by standard Hubbard
interactions alone. We suggest that competing orbital occupations are
responsible for the structural transitions involved in the observed re-entrant
rhombohedral-triclinic-rhombohedral sequence.


  We propose an optomechanics experiment that can search for signatures of a
fundamentally classical theory of gravity and in particular of the many-body
Schroedinger-Newton (SN) equation, which governs the evolution of a crystal
under a self-gravitational field. The SN equation predicts that the dynamics of
a macroscopic mechanical oscillator's center of mass wavefunction differ from
the predictions of standard quantum mechanics. This difference is largest for
low-frequency oscillators, and for materials, such as Tungsten or Osmium, with
small quantum fluctuations of the constituent atoms around their lattice
equilibrium sites. Light probes the motion of these oscillators and is
eventually measured in order to extract valuable information on the pendulum's
dynamics. Due to the non-linearity contained in the SN equation, we analyze the
fluctuations of measurement results differently than standard quantum
mechanics. We revisit how to model a thermal bath, and the wavefunction
collapse postulate, resulting in two prescriptions for analyzing the quantum
measurement of the light. We demonstrate that both predict features, in the
outgoing light's phase fluctuations' spectrum, which are separate from
classical thermal fluctuations and quantum shot noise, and which can be clearly
resolved with state of the art technology.


  This paper introduces the Circular Restricted n-Body Problem (CRNBP), an
extension of the bicircular restricted four-body problem (BCR4BP) designed to
describe the dynamics of an n-body system. In the CRNBP, each massive body in
the system is constrained to follow a Keplerian motion, similar to the BCR4BP's
artificial constraint. The CRNBP is an efficient alternative for trajectory
design in multiple-body systems, particularly for outer planetary systems, as
it requires integrating only six first-order ordinary differential equations
compared to the 6N equations in an ephemerides model. By reproducing complex
dynamical behaviors observed in ephemerides n-body problems, we demonstrate the
structural stability of the CRNBP. Additionally, we propose a straightforward
approach to relate the CRNBP with ephemerides, enabling the exploration of
trajectory design possibilities before committing to a dedicated ephemerides
analysis. This allows for the identification of general dynamical behaviors and
provides valuable insights into the dynamics of multiple body systems. Finally,
illustrative examples highlight the richness of trajectories and potential
advantages of using the CRNBP for designing complex trajectories in outer
planetary systems. The CRNBP proves to be a valuable tool for preliminary
trajectory design, facilitating the identification of low-energy trajectories
and providing a foundation for further exploration in future dedicated studies.


  It is shown that in charge unbalanced double layer quantum Hall system with
zero tunneling pseudospin Goldstone mode excitations form moving kink-soliton
in weakly nonlinear limit. This charge-density localization moves with a
velocity of gapless linear spin-wave mode and could be easily observed
experimentally. We claim that mentioned Goldstone mode kink-solitons define
diffusionless charge transport properties in double layer quantum Hall systems.


  This letter introduces the concept of antifragile electronic warfare (EW),
which we define as the ability to allow a communications link to improve
performance due to the presence of a jammer. This concept should not be
confused with jamming countermeasures (a.k.a. anti-jamming or electronic
protection). Rather, antifragile EW can be thought of as the next step beyond
simply avoiding or mitigating jamming. After introducing the concept we narrow
down the subset of jammers this concept can be applied to, and provide a brief
example of an antifragile EW strategy.


  This paper introduces the method of composite quantile factor model for
factor analysis in high-dimensional panel data. We propose to estimate the
factors and factor loadings across different quantiles of the data, allowing
the estimates to better adapt to features of the data at different quantiles
while still modeling the mean of the data. We develop the limiting distribution
of the estimated factors and factor loadings, and an information criterion for
consistent factor number selection is also discussed. Simulations show that the
proposed estimator and the information criterion have good finite sample
properties for several non-normal distributions under consideration. We also
consider an empirical study on the factor analysis for 246 quarterly
macroeconomic variables. A companion R package cqrfactor is developed.


  We show that the Higgs boson exchange contribution can be large in three-body
decays of neutralinos even in the case of small tan(beta). This enlarges the
branching ratios for the decays neutralino_2 -> neutralino_1 b \bar{b} and
neutralino_2 -> neutralino_1 tau- tau+. This is the case in the region of the
parameter space where the two lightest neutralinos are gaugino-like, the
sfermions are heavier than 300 GeV, and m_A0 = 200 GeV or smaller.


  X-ray substructures in clusters of galaxies provide indirect clues about the
microphysical properties of the intracluster medium (ICM), which are still not
very well known. In order to investigate X-ray substructures in detail, we
studied archival $\sim$1~Msec Chandra data of the core of the Perseus cluster,
focusing on the substructures associated with the sloshing cold front. In the
east half of the cold front, we found a Kelvin-Helmholtz instability (KHI)
layer candidate. The measured width-to-azimuthal extension ratio and the
thermodynamic properties are all consistent with it being a KHI layer currently
developing along the sloshing cold front. We found a thermal pressure deficit
of the order of 10$^{-2}~\mathrm{keV~cm^{-3}}$ at the KHI layer. Assuming that
turbulent pressure fully supports the pressure deficit, we estimated the
turbulent strength at several hundred km~s$^{-1}$, which translates into the
turbulent heating rate of $Q_\mathrm{turb}\sim
10^{-26}~\mathrm{erg~cm^{-3}~s^{-1}}$. This value agrees within an order of
magnitude with the previous estimation derived from the surface brightness
fluctuations, and can balance the radiative cooling at this radius. In the west
half of the cold front, we found feather-like structures which are similar to
the structures observed in recent numerical simulations of the gas sloshing of
magnetized plasma. Their thermodynamic properties are consistent with one of
the feathers being a projected gas depletion layer induced by the amplified
magnetic field whose strength is $B\sim$30$~\mathrm{\mu G}$.


  Brans-Dicke theory contains an additional propagating mode which causes
homogeneous expansion and contraction of test bodies in transverse directions.
This "breathing" mode is associated with novel memory effects in addition to
those of general relativity. Standard tensor mode memories are related to a
symmetry principle: they are determined by the balance equations corresponding
to the BMS symmetries. In this paper, we show that the leading and subleading
breathing memory effects are determined by the balance equations associated
with the leading and "overleading" asymptotic symmetries of a dual formulation
of the scalar field in terms of a two-form gauge field. The memory effect
causes a transition in the vacuum of the dual gauge theory. These results
highlight the significance of dual charges and the physical role of overleading
asymptotic symmetries.


  We study the $W_\infty$ algebra in the Calegero-Sutherland model using the
exchange operators. The presence of all the sub-algebras of $W_\infty$ is shown
in this model. A simplified proof for this algebra, in the symmetric ordered
basics, is given. It is pointed out that the algebra contains in general,
nonlinear terms. Possible connection to the nonlinear $W_\infty$ is discussed.


  Angle-action coordinates are used to study the relic of an N-body simulation
of a self-gravitating satellite galaxy that was released on a short-period
orbit within the disc of the Galaxy. Satellite stars that lie within 1.5 kpc of
the Sun are confined to a grid of patches in action space. As the relic
phase-mixes for longer, the patches become smaller and more numerous. These
patches can be seen even when the angle-action coordinates of an erroneous
Galactic potential are used, but using the wrong potential displaces them.
Diagnostic quantities constructed from the angle coordinates both allow the
true potential to be identified, and the relic to be dated. Hence when the full
phase space coordinates of large numbers of solar-neighbourhood stars are
known, it should be possible to identify members of particular relics from the
distribution of stars in an approximate action space. This would then open up
the possibility of determining the time since the relic was disrupted and
gaining better knowledge of the Galactic potential.
  The availability of angle-action coordinates for arbitrary potentials is the
key to these developments. The paper includes a brief introduction to the torus
technique used to generate them.


  A model of bound state formation from the delocalized edge states of 2D
topological insulator is derived by considering the effects of magnetic
barriers attached to the edge of the HgTe/CdTe quantum well. The resulting
structure has a spatial form of 1D quantum dot with variable number of bound
states depending on barrier parameters. The spatial profile of exchange
interaction between the edge states and barriers is derived from the
interaction with single impurity magnetic moment and is generalized for the
barrier bulk structure formed by ensemble of impurities. The resulting
Hamiltonian is studied as a function of barrier parameters including their
strength and orientation of the magnetic moments. It is shown that for parallel
magnetization of two barriers at least two discrete levels are formed
regardless of the barrier strength. For antiparallel magnetization at least a
single bound state is formed for any strength of the barriers. Our results may
help in design of novel types of quantum dots based on topological insulators.


  Stimulated by the newly observed $a_0(1817)$ by the BESIII Collaboration, we
find a perfect Regge trajectory composed of the $a_0(980)$, $a_0(1450)$, and
$a_0(1817)$, which leads us to categorize the $a_0(980)$, $a_0(1450)$, and
$a_0(1817)$ into the isovector scalar meson family. This scenario is supported
by their two-body Okubo-Zweig-Iizuka allowed strong decay behaviors. In this
scheme, we also predict the third radial excitation of the $a_0(980)$, which is
denoted as the $a_0(2115)$, accessible at future experiment as a direct test of
this assignment. We find another Regge trajectory which contains three
isoscalar scalar states $f_0(980)$, $X(1812)$, and $f_0(2100)$. We investigate
their two-body Okubo-Zweig-Iizuka allowed strong decay patterns, which are
roughly consistent with the experimental data. The $f_0(980)$, $X(1812)$, and
$f_0(2100)$ can be well grouped into the isoscalar scalar meson family. We want
to emphasize that these two Regge trajectories have a similar slope. In
summary, the present work provides a scheme of constructing the scalar meson
family based on these reported scalar states. The possibility of the
$f_0(1710)$ as the candidate of the scalar glueball cannot be excluded by the
observation of the $a_0(1817)$ since the $a_0(1817)$ is more suitable as the
isovector partner of the $X(1812)$.


  The propagation of detonation waves in reactive media bounded by an inert,
compressible layer is examined via computational simulations in two different
geometries, axisymmetric cylinders and two dimensional, planar slabs. For
simplicity, an ideal gas equation of state is used with a pressure-dependent
reaction rate that results in a stable detonation wave structure. The
detonation is initiated as an ideal Chapman-Jouguet (CJ) detonation with a
one-dimensional structure, and then allowed to propagate into a finite diameter
or thickness layer of explosive surrounded by an inert layer. The yielding
confinement of the inert layer results in the detonation wave decaying to a
sub-CJ steady state velocity or failing entirely. Simulations are performed
with different values of the reaction rate pressure exponent (n = 2 and 3) and
different impedance confinement (greater than, less than, and equal to the
confinement of the explosive). The velocity decrement and critical dimension
(critical diameter or thickness) are determined, and a 2:1 scaling between the
cylinder diameter and slab thickness results is confirmed, in good agreement
with curvature-based models of detonation propagation. The measured shock front
curvature and detonation velocity relation agrees with the classic model of
Wood and Kirkwood. The computational simulations are compared to a simple,
analytic model that treats the interaction of the confinement with the
detonation products via Newtonian theory and a model that assumes a continuous
variation in shock front curvature with the shock angle at the interface with
the confinement matching the angle determined by shock polar analysis. The
Newtonian model works very well for the case of high impedance confinement,
while the shock front curvature model agrees with the simulations for the case
of low impedance confinement.


  A statistical study of global galaxy parameters can help to improve our
understanding of galaxy formation processes. In this paper we present the
analysis of global galaxy parameters based on optical and near-infrared
observations of a large sample of edge-on disc galaxies. We found a correlation
between the ratio of the radial to vertical scale parameter and galaxy type:
galaxies become systematically thinner when going from S0's to Sc's, whereas
the distribution seems to level off for later types.
  The observed scale length ratios (and thus the radial colour gradients)
largely represent the galaxies' dust content. On average the colour gradients
indicated by the scale length ratios increase from type Sa to at least type Sc.
For galaxy types later than Sc, the average colour gradient seems to decrease
again.
  The distribution of K-band (edge-on) disc central surface brightnesses is
rather flat, although with a large scatter. However, the latest-type sample
galaxies (T > 6) show an indication that their average disc central surface
brightnesses may be fainter than those of the earlier types. This effect is
probably not the result of dust extinction.


  A two-body problem on the square lattice is analyzed. The interaction
potential consists of strong on-site repulsion and nearest-neighbor attraction.
Exact pairing conditions are derived for s-, p-, and d-symmetric bound states.
The pairing conditions are strong functions of the total pair momentum K. It is
found that the stability of pairs increases with K. At weak attraction, the
pairs do not form at the $\Gamma$-point but stabilize at lattice momenta close
to the Brillouin zone boundary. The phase boundaries in the momentum space,
which separate stable and unstable pairs are calculated. It is found that the
pairs are formed easier along the $(\pi,0)$ direction than along the
$(\pi,\pi)$ direction. This might lead to the appearance of ``hot pairing
spots" on the Kx and Ky axes.


  In this paper we prove several weighted estimates for bilinear fractional
integral operators and their commutators with BMO functions. We also prove
maximal function control theorem for these operators, that is, we prove the
weighted $L^p$ norm is bounded by the weighted $L^p$ norm of a natural maximal
operator when the weight belongs to $A_\infty$. As a corollary we are able to
obtain new weighted estimates for the bilinear maximal function associated to
the bilinear Hilbert transform.


  Machine learning models with high accuracy on test data can still produce
systematic failures, such as harmful biases and safety issues, when deployed in
the real world. To detect and mitigate such failures, practitioners run
behavioral evaluation of their models, checking model outputs for specific
types of inputs. Behavioral evaluation is important but challenging, requiring
that practitioners discover real-world patterns and validate systematic
failures. We conducted 18 semi-structured interviews with ML practitioners to
better understand the challenges of behavioral evaluation and found that it is
a collaborative, use-case-first process that is not adequately supported by
existing task- and domain-specific tools. Using these findings, we designed
Zeno, a general-purpose framework for visualizing and testing AI systems across
diverse use cases. In four case studies with participants using Zeno on
real-world models, we found that practitioners were able to reproduce previous
manual analyses and discover new systematic failures.


  Optimal Transport (OT) is a fundamental tool for comparing probability
distributions, but its exact computation remains prohibitive for large
datasets. In this work, we introduce novel families of upper and lower bounds
for the OT problem constructed by aggregating solutions of mini-batch OT
problems. The upper bound family contains traditional mini-batch averaging at
one extreme and a tight bound found by optimal coupling of mini-batches at the
other. In between these extremes, we propose various methods to construct
bounds based on a fixed computational budget. Through various experiments, we
explore the trade-off between computational budget and bound tightness and show
the usefulness of these bounds in computer vision applications.


  The presence of a strong magnetic background can modify the nature and the
dynamics of the chiral phase transition at finite temperature: for high enough
magnetic fields, comparable to the ones expected to be created in noncentral
high-energy heavy ion collisions at RHIC and the LHC, the original crossover is
turned into a first-order transition. We illustrate this effect within the
linear sigma model with quarks to one loop in the ${\rm MS}$ scheme for
$N_{f}=2$.


  We investigate the asymptotic behavior of the free path of a variable density
random flight model in an external field as the initial velocity of the
particle goes to infinity. The random flight models we study arise naturally as
the Boltzmann-Grad limit of a random Lorentz gas in the presence of an external
field. By analyzing the time duration of the free path, we obtain exact forms
for the asymptotic mean and variance of the free path in terms of the external
field and the density of scatterers. As a consequence, we obtain a diffusion
approximation for the joint process of the particle observed at reflection
times and the amount of time spent in free flight.


  The fidelity of Generative Adversarial Networks (GAN) inversion is impeded by
Out-Of-Domain (OOD) areas (e.g., background, accessories) in the image.
Detecting the OOD areas beyond the generation ability of the pre-trained model
and blending these regions with the input image can enhance fidelity. The
"invertibility mask" figures out these OOD areas, and existing methods predict
the mask with the reconstruction error. However, the estimated mask is usually
inaccurate due to the influence of the reconstruction error in the In-Domain
(ID) area. In this paper, we propose a novel framework that enhances the
fidelity of human face inversion by designing a new module to decompose the
input images to ID and OOD partitions with invertibility masks. Unlike previous
works, our invertibility detector is simultaneously learned with a spatial
alignment module. We iteratively align the generated features to the input
geometry and reduce the reconstruction error in the ID regions. Thus, the OOD
areas are more distinguishable and can be precisely predicted. Then, we improve
the fidelity of our results by blending the OOD areas from the input image with
the ID GAN inversion results. Our method produces photo-realistic results for
real-world human face image inversion and manipulation. Extensive experiments
demonstrate our method's superiority over existing methods in the quality of
GAN inversion and attribute manipulation.


  Interpretations of the Beurling-Lax-Halmos Theorem on invariant subspaces of
the unilateral shift are explored using the language of Hilbert modules.
Extensions and consequences are considered in both the one and multivariate
cases with an emphasis on the classical Hardy, Bergman and Drury-Arveson
spaces.


  Detection of gravitational waves(GW) involves using the network of GW
telescopes to observe a large sky region. However, owing to the arrangement of
the GW telescopes, even with aLIGO- aVirgo-KAGRA network,parameter estimation
accuracy deteriorates depending on the sky region of the GW source due to the
ill-posed nature of the inverse operator. A regularization-based method is
proposed herein to improve parameter estimation accuracy. Although conventional
regularization methods cannot optimize all regulator parameters completely, the
proposed method archives full optimization by applying an a-posteriori
parameter choice rule to determine regulator parameters. We demonstrate that
the proposed method can shrink the credible regions of inclination vs lumi-
nosity distance and polarization vs initial phase significantly in the sky
wherein the accuracy of the amplitude parameters of a GW has been deteriorated.
The proposed method suppresses the systematic error of a GW depending on the
sky region and allows us investigating the cosmological information more
precisely.


  The temporal smearing of impulsive radio events at cosmological redshifts
probes the properties of the ionized Inter-Galactic Medium (IGM). We relate the
degree of temporal smearing and the profile of a scattered source to the
evolution of turbulent structure in the IGM as a function of redshift. We
estimate the degree of scattering expected by analysing the contributions to
the Scattering Measure (SM) of the various components of baryonic matter
embedded in the IGM, including the diffuse IGM, intervening galaxies and
intracluster gas. These estimates predict that the amount of temporal smearing
expected at 300\,MHz is typically as low as ~1 ms and suggests that these
bursts may be detectable with low frequency widefield arrays. A generalization
of the DM-SM relation observed for Galactic scattering to the densities and
turbulent conditions relevant to the IGM suggests that scattering measures of
order 10^{-6} kpc m {-20/3} would be expected at z ~ 1. This scattering is
sufficiently low that its effects would, for most lines of sight, not be
manifest in existing observations of the scattering broadening in images of
extragalactic compact sources. The redshift dependence of the temporal smearing
discriminates between scattering that occurs in the host galaxy of the burst
and the IGM, with tau_host \propto (1+z)^{-3} if the scattering probes length
scales below the inner scale of the turbulence or tau_host \propto
(1+z)^{-17/5} if the turbulence follows a Kolmogorov spectrum. This differs
strongly from the expected IGM scaling tau_{IGM} ~ z^2 for z < 1 and
(1+z)^{0.2-0.5} for z >> 1.


  Kinetics of systems specified by anharmonic, nonconservative and nonlocally
coupled model Hamiltonians is reproduced in the Fokker-Planck and imaginary
time Schrodinger equation techniques with subsequent symplectic integration.
Test solutions focused on dielectric response in ferroelectrics demonstrates
potential of this technique even for nonlocal and hardly nonlinear problems of
polarization switching, and reassure the H-theorem of global stability [M.
Shiino, Phys. Rev. A, Vol 36, pp. 2393-2411 (1987)] in the global coupling and
zero driving limit.
  PACS: 64.60.Cn; 77.80.Dj; 77.80 Fm. Keywords: ferroelectric hysteresis,
nonequilibrium thermodynamics, nonadiabatic behaviour.


  State-of-the-art techniques like dual-frequency Time-Domain Thermoreflectance
(TDTR) and Frequency-Domain Thermoreflectance (FDTR) offer superb capability
for simultaneous measurements of thermal conductivity and heat capacity with a
spatial resolution on the order of 10 {\mu}m. However, their applicability is
limited to highly conductive materials with an in-plane thermal conductivity
exceeding 10 W/(m*K). In this paper, we introduce the Square-Pulsed Source
(SPS) technique, offering a novel approach to concurrently measure thermal
conductivity and heat capacity with a 10 {\mu}m spatial resolution, while
significantly extending the measurable thermal conductivity range to an
unprecedented low of 0.1 W/(m*K), offering enhanced versatility. To demonstrate
and validate its efficacy, we conducted measurements on various standard
materials--PMMA, silica, sapphire, silicon, and diamond--spanning a wide
thermal conductivity range from 0.1 to 2000 W/(m*K). The obtained results
exhibit remarkable agreement with literature values, with a typical measurement
uncertainty of less than 10% across the entire thermal conductivity range. By
providing a unique capability to characterize both highly and lowly conductive
materials with micron-scale spatial resolution, the SPS method opens new
avenues for understanding and engineering thermal properties across diverse
applications.


  This paper presents a model-based planner called the Probabilistic Sulu
Planner or the p-Sulu Planner, which controls stochastic systems in a goal
directed manner within user-specified risk bounds. The objective of the p-Sulu
Planner is to allow users to command continuous, stochastic systems, such as
unmanned aerial and space vehicles, in a manner that is both intuitive and
safe. To this end, we first develop a new plan representation called a
chance-constrained qualitative state plan (CCQSP), through which users can
specify the desired evolution of the plant state as well as the acceptable
level of risk. An example of a CCQSP statement is go to A through B within 30
minutes, with less than 0.001% probability of failure." We then develop the
p-Sulu Planner, which can tractably solve a CCQSP planning problem. In order to
enable CCQSP planning, we develop the following two capabilities in this paper:
1) risk-sensitive planning with risk bounds, and 2) goal-directed planning in a
continuous domain with temporal constraints. The first capability is to ensures
that the probability of failure is bounded. The second capability is essential
for the planner to solve problems with a continuous state space such as vehicle
path planning. We demonstrate the capabilities of the p-Sulu Planner by
simulations on two real-world scenarios: the path planning and scheduling of a
personal aerial vehicle as well as the space rendezvous of an autonomous cargo
spacecraft.


  The universality class, even the order of the transition, of the
two-dimensional Ising model depends on the range and the symmetry of the
interactions (Onsager model, Baxter-Wu model, Turban model, etc.), but the
critical temperature is generally the same due to self-duality. Here we
consider a sudden change in the form of the interaction and study the
nonequilibrium critical dynamical properties of the nearest-neighbor model. The
relaxation of the magnetization and the decay of the autocorrelation function
are found to display a power law behavior with characteristic exponents that
depend on the universality class of the initial state.


  We consider a system of nonlinear spinor and scalar fields with minimal
coupling in general relativity. The nonlinearity in the spinor field Lagrangian
is given by an arbitrary function of the invariants generated from the bilinear
spinor forms $S= {\bar \psi} \psi$ and $P=i {\bar \psi} \gamma^5 \psi$; the
scalar Lagrangian is chosen as an arbitrary function of the scalar invariant
${\Upsilon} = {\phi}_{,\alpha}{\phi}^{,\alpha}$, that becomes linear at
${\Upsilon} \to 0$. The spinor and the scalar fields in question interact with
each other by means of a gravitational field which is given by a
plane-symmetric metric. Exact plane-symmetric solutions to the gravitational,
spinor and scalar field equations have been obtained. Role of gravitational
field in the formation of the field configurations with limited total energy,
spin and charge has been investigated. Influence of the change of the sign of
energy density of the spinor and scalar fields on the properties of the
configurations obtained has been examined. It has been established that under
the change of the sign of the scalar field energy density the system in
question can be realized physically iff the scalar charge does not exceed some
critical value. In case of spinor field no such restriction on its parameter
occurs. In general it has been shown that the choice of spinor field
nonlinearity can lead to the elimination of scalar field contribution to the
metric functions, but leaving its contribution to the total energy unaltered.
  Key words: Nonlinear spinor field (NLSF), nonlinear scalar field,
plane-symmetric metric PACS: 03.65.P, 04.20.H


  We propose a method of encoding a topologically-protected qubit using
Majorana fermions in a trapped-ion chain. This qubit is protected against major
sources of decoherence, while local operations and measurements can be
realized. Furthermore, we show that an efficient quantum interface and memory
for arbitrary multiqubit photonic states can be built, encoding them into a set
of entangled Majorana-fermion qubits inside cavities.


  We calculate the typical bipartite entanglement entropy $\langle
S_A\rangle_N$ in systems containing indistinguishable particles of any kind as
a function of the total particle number $N$, the volume $V$, and the subsystem
fraction $f=V_A/V$, where $V_A$ is the volume of the subsystem. We expand our
result as a power series $\langle S_A\rangle_N=a f V+b\sqrt{V}+c+o(1)$, and
find that $c$ is universal (i.e., independent of the system type), while $a$
and $b$ can be obtained from a generating function characterizing the local
Hilbert space dimension. We illustrate the generality of our findings by
studying a wide range of different systems, e.g., bosons, fermions, spins, and
mixtures thereof. We provide evidence that our analytical results describe the
entanglement entropy of highly excited eigenstates of quantum-chaotic spin and
boson systems, which is distinct from that of integrable counterparts.


  Azo-dye-doped liquid crystal elastomers (LCEs) are known to show a strong
photomechanical response. We report on experiments that suggest that
photothermal heating is the underlying mechanism in surface-constrained
geometry. In particular, we use optical interferometry to probe the length
change of the material and direct temperature measurements to determine
heating. LCEs with various dopants and optical density were used to study the
individual mechanisms. In the high dye-doped limit, most of the light is
absorbed near the entry surface, which causes a local strain from photothermal
heating and a nonlocal strain from thermal diffusion. The results of our
research on the microscopic mechanisms of the photomechanical response can be
applied to designing photomechanical materials for actuating/sensing devices,
the potential basis of smart structures.


  We discuss a hierarchy of broken symmetries with special emphasis on partial
dynamical symmetries (PDS). The latter correspond to a situation in which a
non-invariant Hamiltonian accommodates a subset of solvable eigenstates with
good symmetry, while other eigenstates are mixed. We present an algorithm for
constructing Hamiltonians with this property and demonstrate the relevance of
the PDS notion to nuclear spectroscopy, to quantum phase transitions and to
mixed systems with coexisting regularity and chaos.


  Warfield proved that every injective module has the exchange property. This
was generalized by Fuchs who showed that quasi-injective modules satisfy the
exchange property. We extend this further and prove that a module invariant
under automorphisms of its injective hull satisfies the exchange property. We
also show that automorphism-invariant modules are clean and that
directly-finite automorphism-invariant modules satisfy the internal
cancellation and hence the cancellation property.


  We shall present and analyze two examples of extended theories of gravitation
in Palatini formalism with matter that couples to the connection. This will
show that the class of Further Extended Theories of Gravitation introduced in
ref. [1] does not trivially reduce to f(R) models. It will also produce an
example of theory that on-shell endowes spacetime with a non-trivial Weyl
geometry where the connection is not induced by the metric structure (though it
is compatible with it in the sense of Ehlers-Pirani-Schild; see ref. [2]).


  The detailed observations of the diffuse ionized gas through the emission
lines H$\alpha$, [NII], and [SII] in the Perseus Arm of our Galaxy by the
Wisconsin H$\alpha$ Mapper (WHAM)--survey challenge photoionization models.
They have to explain the observed rise in the line ratios [NII]/H$\alpha$ and
[SII]/H$\alpha$. The models described here consider for the first time the
detailed observational geometry toward the Perseus Arm. The models address the
vertical variation of the line ratios up to height of 2 kpc above the midplane.
The rising trends of the line ratios are matched. The increase in the line
ratios is reflected in a rise of the temperature of the gas layer. This is due
to the progressive hardening of the radiation going through the gas. However an
extra heating above photoionization is needed to explain the absolute values.
Two different extra heating rates are investigated which are proportional to
$n^0$ and $n^1$. The models show that a combination of both are best to explain
the data, where the extra heating independent of density is dominant for z $>$
0.8 kpc.


  Quantum correlations exhibit behaviour that cannot be resolved with a local
hidden variable picture of the world. In quantum information, they are also
used as resources for information processing tasks, such as Measurement-based
Quantum Computation (MQC). In MQC, universal quantum computation can be
achieved via adaptive measurements on a suitable entangled resource state. In
this paper, we look at a version of MQC in which we remove the adaptivity of
measurements and aim to understand what computational abilities still remain in
the resource. We show that there are explicit connections between this model of
computation and the question of non-classicality in quantum correlations. We
demonstrate this by focussing on deterministic computation of Boolean
functions, in which natural generalisations of the Greenberger-Horne-Zeilinger
(GHZ) paradox emerge; we then explore probabilistic computation, via which
multipartite Bell Inequalities can be defined. We use this correspondence to
define families of multi-party Bell inequalities, which we show to have a
number of interesting contrasting properties.


  Recently, Di\'osi et al. (Int. J. Quant. Inf. 4, 99 (2006)) introduced a
simple, yet very interesting model for reservoirs, in order to study the
relationship between thermodynamic entropy production of a system and the
corresponding von Neumann entropy (or informatic entropy, as it was called by
the authors). They came up with a conjecture about the asymptotic behaviour of
the state introduced in the model. The conjecture was proven later by Csisz\'ar
et al. (J. Math. Phys. 48, 092102 (2007)). In this paper we give a different
interpretation of the original question and extend the result to a collection
of more general states.


  This paper continues a study on Choptuik scaling in gravitational collapse of
a complex scalar field at the threshold for black hole formation. We perform a
linear perturbation analysis of the previously derived complex critical
solution, and calculate the critical exponent for black hole mass, $\gamma
\approx 0.387106$. We also show that this critical solution is unstable via a
growing oscillatory mode.


  Nitrogen-doped ultrananocrystalline diamond (N-UNCD) is a promising material
for a variety of neural interfacing applications, due to its unique combination
of high conductivity, bioinertness, and durability. One emerging application
for N-UNCD is as a photoelectrode material for high-precision optical neural
stimulation. This may be used for the treatment of neurological disorders and
for implantable bionic devices such as cochlear ear implants and retinal
prostheses. N-UNCD is a well-suited material for stimulation photoelectrodes,
exhibiting a photocurrent response to light at visible wavelengths with a high
charge injection density [A. Ahnood, A. N. Simonov, J. S. Laird, M. I.
Maturana, K. Ganesan, A. Stacey, M. R. Ibbotson, L. Spiccia, and S. Prawer,
Appl. Phys. Lett. 108, 104103 (2016)]. In this study, the photoresponse of
N-UNCD to near-infrared (NIR) irradiation is measured. NIR light has greater
optical penetration through tissue than visible wavelengths, opening the
possibility to stimulate previously inaccessible target cells. It is found that
N-UNCD exhibits a photoresponsivity which diminishes rapidly with increasing
wavelength and is attributed to transitions between mid-gap states and the
conduction band tail associated with the graphitic phase present at the grain
boundaries. Oxygen surface termination on the diamond films provides further
enhancement of the injected charge per photon, compared to as-grown or hydrogen
terminated surfaces. Based on the measured injected charge density, we estimate
that the generated photocurrent of oxygen terminated N-UNCD is sufficient to
achieve extracellular stimulation of brain tissue within the safe optical
exposure limit.


  Generating animation of physics-based characters with intuitive control has
long been a desirable task with numerous applications. However, generating
physically simulated animations that reflect high-level human instructions
remains a difficult problem due to the complexity of physical environments and
the richness of human language. In this paper, we present InsActor, a
principled generative framework that leverages recent advancements in
diffusion-based human motion models to produce instruction-driven animations of
physics-based characters. Our framework empowers InsActor to capture complex
relationships between high-level human instructions and character motions by
employing diffusion policies for flexibly conditioned motion planning. To
overcome invalid states and infeasible state transitions in planned motions,
InsActor discovers low-level skills and maps plans to latent skill sequences in
a compact latent space. Extensive experiments demonstrate that InsActor
achieves state-of-the-art results on various tasks, including
instruction-driven motion generation and instruction-driven waypoint heading.
Notably, the ability of InsActor to generate physically simulated animations
using high-level human instructions makes it a valuable tool, particularly in
executing long-horizon tasks with a rich set of instructions.


  This paper deals with the investigation of the solution of an unified
fractional reaction-diffusion equation associated with the Caputo derivative as
the time-derivative and Riesz-Feller fractional derivative as the
space-derivative. The solution is derived by the application of the Laplace and
Fourier transforms in closed form in terms of the H-function. The results
derived are of general nature and include the results investigated earlier by
many authors, notably by Mainardi et al. (2001, 2005) for the fundamental
solution of the space-time fractional diffusion equation, and Saxena et al.
(2006a, b) for fractional reaction- diffusion equations. The advantage of using
Riesz-Feller derivative lies in the fact that the solution of the fractional
reaction-diffusion equation containing this derivative includes the fundamental
solution for space-time fractional diffusion, which itself is a generalization
of neutral fractional diffusion, space-fractional diffusion, and
time-fractional diffusion. These specialized types of diffusion can be
interpreted as spatial probability density functions evolving in time and are
expressible in terms of the H-functions in compact form.


  Scale functions play a central role in the fluctuation theory of spectrally
negative L\'evy processes. For spectrally negative compound Poisson processes
with positive drift, a new representation of the $q$-scale functions in terms
of the characteristics of the process is derived. Moreover, similar
representations of the derivatives and the primitives of the $q$-scale
functions are presented. The obtained formulae for the derivatives allow for a
complete exposure of the smoothness properties of the considered $q$-scale
functions. Some explicit examples of $q$-scale functions are given for
illustration.


  In this paper we investigate a high dimensional version of Selberg's minorant
problem for the indicator function of an interval. In particular, we study the
corresponding problem of minorizing the indicator function of the box
$Q_{N}=[-1,1]^N$ by a function whose Fourier transform is supported in the same
box $Q_N$. We show that when the dimension is sufficiently large there are no
minorants with positive mass and we give an explicit lower bound for such
dimension. On the other hand, we explicitly construct minorants for dimensions
$1,2,3,4$ and $5$ and, as an application, we use them to produce an improved
diophantine inequality for exponential sums.


  The experimental search for new thermoelectric materials remains largely
confined to a limited set of successful chemical and structural families, such
as chalcogenides, skutterudites, and Zintl phases. In principle, computational
tools such as density functional theory (DFT) offer the possibility of
rationally guiding experimental synthesis efforts toward very different
chemistries. However, in practice, predicting thermoelectric properties from
first principles remains a challenging endeavor, and experimental researchers
generally do not directly use computation to drive their own synthesis efforts.
To bridge this practical gap between experimental needs and computational
tools, we report an open machine learning-based recommendation engine
(http://thermoelectrics.citrination.com) for materials researchers that
suggests promising new thermoelectric compositions, and evaluates the
feasibility of user-designed compounds. We show that this engine can identify
interesting chemistries very different from known thermoelectrics.
Specifically, we describe the experimental characterization of one example set
of compounds derived from our engine, RE12Co5Bi (RE = Gd, Er), which exhibits
surprising thermoelectric performance given its unprecedentedly high loading
with metallic d and f block elements, and warrants further investigation as a
new thermoelectric material platform.


  Generating photon pairs via spontaneous parametric down-conversion (SPDC) in
nonlinear crystals is important for a wide range of quantum optics experiments
with spectral properties such as their bandwidths often being a crucial
concern. Here, we show the generic existence of particular phase-matching
conditions in quasi-phase matched KTP, MgO:LN and SLT crystals that lead to
ultra-broadband, widely non-degenerate photon pairs. It is based on the
existence of group-velocity matched, far apart wavelength pairs and for 2 mm
long crystals results in SPDC bandwidths between 15 and 25 THz (FWHM) for
photon pairs with the idler photon in the technologically relevant mid-IR range
3-5 {\mu}m and the signal photon in the NIR below 1100 nm. We experimentally
demonstrate this type of broadband phase-matching in ppKTP crystals for photon
pairs centered at 800 nm and 3800 nm and measure a bandwidth of 15 THz. This
novel method of generating broadband photon-pairs will be highly beneficial for
SPDC-based imaging, spectroscopy, refractometry and OCT with undetected mid-IR
photons.


  Full characterization of imaging detectors involves subjecting them to
spatially and temporally varying illumination patterns over a large dynamic
range. Here we present a scene generator that fulfills many of these functions.
Based on a modern smartphone, it has a number of good features, including the
ability to generate nearly arbitrary optical scenes, high spatial resolution
(13 um), high dynamic range (~10^4), near-Poisson limited illumination
stability over time periods from 100 ms to many days, and no background noise.
The system does not require any moving parts and may be constructed at modest
cost. We present the optical, mechanical, and software design, test data
validating the performance, and application examples.


  The previously proposed ansatz for density cumulant theory that combines
orbital-optimization and a parameterization of the 2-electron reduced density
matrix cumulant in terms of unitary coupled cluster amplitudes (OUDCT) is
carefully examined. Formally, we elucidate the relationship between OUDCT and
orbital-optimized unitary coupled cluster theory and show the existence of
near-zero denominators in the stationarity conditions for both the exact and
some approximate OUDCT methods. We implement methods of the OUDCT ansatz
restricted to double excitations for numerical study, up to the fifth
commutator in the Baker-Campbell-Hausdorff expansion. We find that methods
derived from the ansatz beyond the previously known ODC-12 method tend to be
less accurate for equilibrium properties and less reliable when attempting to
describe $H2$ dissociation. New developments are needed to formulate more
accurate DCT variants.


  Kiva is an online non-profit crowdsouring microfinance platform that raises
funds for the poor in the third world. The borrowers on Kiva are small business
owners and individuals in urgent need of money. To raise funds as fast as
possible, they have the option to form groups and post loan requests in the
name of their groups. While it is generally believed that group loans pose less
risk for investors than individual loans do, we study whether this is the case
in a philanthropic online marketplace. In particular, we measure the effect of
group loans on funding time while controlling for the loan sizes and other
factors. Because loan descriptions (in the form of texts) play an important
role in lenders' decision process on Kiva, we make use of this information
through deep learning in natural language processing. In this aspect, this is
the first paper that uses one of the most advanced deep learning techniques to
deal with unstructured data in a way that can take advantage of its superior
prediction power to answer causal questions. We find that on average, forming
group loans speeds up the funding time by about 3.3 days.


  We calculate the secular changes of the orbital parameters of a point
particle orbiting a Kerr black hole, due to the gravitational radiation
reaction. For this purpose, we use the post-Newtonian (PN) approximation in the
first order black hole perturbation theory, with the expansion with respect to
the orbital eccentricity. In this work, the calculation is done up to the
fourth post-Newtonian (4PN) order and to the sixth order of the eccentricity,
including the effect of the absorption of gravitational waves by the black
hole. We confirm that, in the Kerr case, the effect of the absorption appears
at the 2.5PN order beyond the leading order in the secular change of the
particle's energy and may induce a superradiance, as known previously for
circular orbits. In addition, we find that the superradiance may be suppressed
when the orbital plane inclines with respect to the equatorial plane of the
central black hole. We also investigate the accuracy of the 4PN formulae by
comparing to numerical results. If we require that the relative errors in the
4PN formulae are less than $10^{-5}$, the parameter region to satisfy the
condition will be $p\gtrsim 50$ for $e=0.1$, $p\gtrsim 80$ for $e=0.4$, and
$p\gtrsim 120$ for $e=0.7$ almost irrespective of the inclination angle nor the
spin of the black hole, where $p$ and $e$ are the semi-latus rectum and the
eccentricity of the orbit. The region can further be extended using an
exponential resummation method to $p\gtrsim 40$ for $e=0.1$, $p\gtrsim 60$ for
$e=0.4$, and $p\gtrsim 100$ for $e=0.7$. Although we still need the higher
order calculations of the PN approximation and the expansion with respect to
the orbital eccentricity to apply for data analysis of gravitational waves, the
results in this paper would be an important improvement from the previous work
at the 2.5PN order, especially for large $p$ region.


  Linear-array based photoacoustic images are reconstructed using the
conventional delay-and-sum (DAS) beamforming method. Although the DAS
beamformer is well suited for PA image formation, reconstructed images are
often afflicted by noises, sidelobes, and other intense artifacts due to
inaccurate assumptions of PA signal correlation. The work aims to develop an
inversion method that reduces the occurrence of sidelobes and artifacts and
improves image quality performance. We present a novel beamformer based on
higher-order signal correlation, where more number of delayed PA signals are
combined and summed up than the conventional delay-multiply-and-sum (DMAS). The
proposed technique provides efficient improvements in resolution, contrast, and
SNR compared to the traditional beamformers. Computational complexity in this
method is shrunk to the same order of DAS $O(N)$. Therefore, this beamformer
can be implemented in real-time PA image reconstruction. A GPU based study was
performed on computation time. Proposed method almost executes in the same time
frame of DAS and real-time DMAS. A validation study of the algorithm was
accomplished both numerically and experimentally. Higher-order DMAS beamformers
demonstrate superior reconstruction in all cases. The quantitative evaluation
of the ex-vivo phantom shows that the proposed method leads to 51% and 6%
improvement in FWHM, 81% and 39% improvement in SNR compared to DAS and DMAS,
respectively. Conclusively, the proposed algorithm is very much potential and
promising in real-time photoacoustic imaging and its applications.


  We use deep panchromatic datasets in the GOODS-N field, from GALEX to the
deepest Herschel far-infrared and VLA radio continuum imaging, to explore,
using mass-complete samples, the evolution of the star formation activity and
dust attenuation of star-forming galaxies to z~4. Our main results can be
summarized as follows: i) the slope of the SFR-M correlation is consistent with
being constant, and equal to ~0.8 at least up to z~1.5, while its normalization
keeps increasing with redshift; ii) for the first time here we are able to
explore the FIR-radio correlation for a mass-selected sample of star-forming
galaxies: the correlation does not evolve up to z~4; iii) we confirm that
galaxy stellar mass is a robust proxy for UV dust attenuation in star-forming
galaxies, with more massive galaxies being more dust attenuated, strikingly we
find that this attenuation relation evolves very weakly with redshift, the
amount of dust attenuation increasing by less than 0.3 magnitudes over the
redshift range [0.5-4] for a fixed stellar mass, as opposed to a tenfold
increase of star formation rate; iv) the correlation between dust attenuation
and the UV spectral slope evolves in redshift, with the median UV spectral
slope of star-forming galaxies becoming bluer with redshift. By z~3, typical UV
slopes are inconsistent, given the measured dust attenuation, with the
predictions of commonly used empirical laws. Finally, building on existing
results, we show that gas reddening is marginally larger (by a factor of around
1.3) than stellar reddening at all redshifts probed, and also that the amount
of dust attenuation at a fixed ISM metallicity increases with redshift. We
speculate that our results support evolving ISM conditions of typical
star-forming galaxies such that at z~1.5 Main Sequence galaxies have ISM
conditions getting closer to those of local starbursts.


  Gibbs random fields (GRF) are polymorphous statistical models that can be
used to analyse different types of dependence, in particular for spatially
correlated data. However, when those models are faced with the challenge of
selecting a dependence structure from many, the use of standard model choice
methods is hampered by the unavailability of the normalising constant in the
Gibbs likelihood. In particular, from a Bayesian perspective, the computation
of the posterior probabilities of the models under competition requires special
likelihood-free simulation techniques like the Approximate Bayesian Computation
(ABC) algorithm that is intensively used in population genetics. We show in
this paper how to implement an ABC algorithm geared towards model choice in the
general setting of Gibbs random fields, demonstrating in particular that there
exists a sufficient statistic across models. The accuracy of the approximation
to the posterior probabilities can be further improved by importance sampling
on the distribution of the models. The practical aspects of the method are
detailed through two applications, the test of an iid Bernoulli model versus a
first-order Markov chain, and the choice of a folding structure for two
proteins.


  This exposition reviews what exactly Gauss asserted and what did he prove in
the last chapter of {\sl Disquisitiones Arithmeticae} about dividing the circle
into a given number of equal parts. In other words, what did Gauss claim and
actually prove concerning the roots of unity and the construction of a regular
polygon with a given number of sides. Some history of Gauss's solution is
briefly recalled, and in particular many relevant classical references are
provided which we believe deserve to be better known.


  Following a nonperturbative formulation of strong-field QED developed in our
earlier works, and using the Dirac model of the graphene, we construct a
reduced QED_{3,2} to describe one species of the Dirac fermions in the graphene
interacting with an external electric field and photons. On this base, we
consider the photon emission in this model and construct closed formulas for
the total probabilities. Using the derived formulas, we study probabilities for
the photon emission by an electron and for the photon emission accompanying the
vacuum instability in the quasiconstant electric field that acts in the
graphene plane during the time interval T. We study angular and polarization
distribution of the emission as well as emission characteristics in a high
frequency and low frequency approximations. We analyze the applicability of the
presented calculations to the graphene physics in laboratory conditions. In
fact, we are talking about a possible observation of the Schwinger effect in
these conditions.


  We have made a preliminary analysis of the results about the eVects on
tumoral cell line (lymphoid T cell line Jurkat) induced by UVB radiation (dose
of 310 mJ/cm^2) with and without a vegetable mixture. In the present study, we
have used two techniques: Fourier transform infrared spectroscopy (FTIR) and
flow cytometry. FTIR spectroscopy has the potential to provide the
identiWcation of the vibrational modes of some of the major compounds (lipid,
proteins and nucleic acids) without being invasive in the biomaterials. The
second technique has allowed us to perform measurements of cytotoxicity and to
assess the percentage of apoptosis. We already studied the induction of
apoptotic process in the same cell line by UVB radiation; in particular, we
looked for correspondences and correlations between FTIR spetroscopy and flow
cytometry data finding three highly probable spectroscopic markers of apoptosis
(Pozzi et al. in Radiat Res 168:698-705, 2007). In the present work, the
results have shown significant changes in the absorbance and spectral pattern
in the wavenumber protein and nucleic acids regions after the treatments.


  The metal-poor damped Lyman alpha (DLA) system at z = 3.04984 in the QSO
SDSSJ1419+0829 has near-ideal properties for an accurate determination of the
primordial abundance of deuterium, (D/H)_p. We have analysed a high-quality
spectrum of this object with software specifically designed to deduce the best
fitting value of D/H and to assess comprehensively the random and systematic
errors affecting this determination. We find (D/H)_DLA = (2.535 +/-0.05) x
10^(-5), which in turn implies Omega_b h^2 = 0.0223 +/- 0.0009, in very good
agreement with Omega_b h^2 (CMB) = 0.0222 +/- 0.0004 deduced from the angular
power spectrum of the cosmic microwave background. If the value in this DLA is
indeed the true (D/H)_p produced by Big-Bang nucleosynthesis (BBN), there may
be no need to invoke non-standard physics nor early astration of D to bring
together Omega_b h^2 (BBN) and Omega_b h^2 (CMB). The scatter between most of
the reported values of (D/H)_p in the literature may be due largely to
unaccounted systematic errors and biases. Further progress in this area will
require a homogeneous set of data comparable to those reported here and
analysed in a self-consistent manner. Such an endeavour, while observationally
demanding, has the potential of improving our understanding of BBN physics,
including the relevant nuclear reactions, and the subsequent processing of 4He
and 7Li through stars.


  In this work, we address the problem of tuning communication libraries by
using a deep reinforcement learning approach. Reinforcement learning is a
machine learning technique incredibly effective in solving game-like
situations. In fact, tuning a set of parameters in a communication library in
order to get better performance in a parallel application can be expressed as a
game: Find the right combination/path that provides the best reward. Even
though AITuning has been designed to be utilized with different run-time
libraries, we focused this work on applying it to the OpenCoarrays run-time
communication library, built on top of MPI-3. This work not only shows the
potential of using a reinforcement learning algorithm for tuning communication
libraries, but also demonstrates how the MPI Tool Information Interface,
introduced by the MPI-3 standard, can be used effectively by run-time libraries
to improve the performance without human intervention.


  We discuss the polynomial bi-Hamiltonian structures for the Kowalevski top in
special case of zero square integral. An explicit procedure to find variables
of separation and separation relations is considered in detail.


  We present a brief description of the recently developed Fortran code TERAD91
for semi-analytical calculations of the double differential cross sections of
NC and CC deep inelastic electron-proton scattering and of some related
observables. The code is mainly intended for the calculations at HERA or other
ep-colliders but may be also used for similar processes like muon-proton
scattering in fixed-target experiments.


  This article summarises the outstanding scientific career of Giorgio Parisi,
who was awarded the 2021 Nobel Prize in Physics, with special emphasis on his
contributions to the description of the equilibrium properties of disordered
systems.


  We discuss a synchronization property for subshifts, that we call
$\lambda$-synchronization. Under an irreducibility assumption we associate to a
$\lambda$-synchronizing subshift a simple and purely infinite $C^*$-algebra.


  Video super-resolution (VSR) aiming to reconstruct a high-resolution (HR)
video from its low-resolution (LR) counterpart has made tremendous progress in
recent years. However, it remains challenging to deploy existing VSR methods to
real-world data with complex degradations. On the one hand, there are few
well-aligned real-world VSR datasets, especially with large super-resolution
scale factors, which limits the development of real-world VSR tasks. On the
other hand, alignment algorithms in existing VSR methods perform poorly for
real-world videos, leading to unsatisfactory results. As an attempt to address
the aforementioned issues, we build a real-world 4 VSR dataset, namely
MVSR4$\times$, where low- and high-resolution videos are captured with
different focal length lenses of a smartphone, respectively. Moreover, we
propose an effective alignment method for real-world VSR, namely EAVSR. EAVSR
takes the proposed multi-layer adaptive spatial transform network (MultiAdaSTN)
to refine the offsets provided by the pre-trained optical flow estimation
network. Experimental results on RealVSR and MVSR4$\times$ datasets show the
effectiveness and practicality of our method, and we achieve state-of-the-art
performance in real-world VSR task. The dataset and code will be publicly
available.


  The spherical collapse model is often used to follow the evolution of
overdensities into the nonlinear regime. We describe the correct approach to be
used in coupled dark energy cosmologies, where a fifth force, different from
gravity and mediated by the dark energy scalar field, influences the collapse.
We reformulate the spherical collapse description by deriving it directly from
the set of nonlinear hydrodynamical Navier Stokes equations. By comparing with
the corresponding relativistic equations, we show how the fifth force should be
taken into account within the spherical collapse picture and clarify the
problems arising when an inhomogeneous scalar field is considered within a
spherical collapse picture. We then apply our method to the case of coupled
quintessence, where the fifth force acts among cold dark matter particles, and
to growing neutrino quintessence, where the fifth force acts between neutrinos.
Furthermore, we review this method when applied to standard cosmologies and
apply our analysis to minimally coupled quintessence and check past results for
early dark energy parametrizations.


  Despite advances in the programmable logic capabilities of modern trigger
systems, a significant bottleneck remains in the amount of data to be
transported from the detector to off-detector logic where trigger decisions are
made. We demonstrate that a neural network autoencoder model can be implemented
in a radiation tolerant ASIC to perform lossy data compression alleviating the
data transmission problem while preserving critical information of the detector
energy profile. For our application, we consider the high-granularity
calorimeter from the CMS experiment at the CERN Large Hadron Collider. The
advantage of the machine learning approach is in the flexibility and
configurability of the algorithm. By changing the neural network weights, a
unique data compression algorithm can be deployed for each sensor in different
detector regions, and changing detector or collider conditions. To meet area,
performance, and power constraints, we perform a quantization-aware training to
create an optimized neural network hardware implementation. The design is
achieved through the use of high-level synthesis tools and the hls4ml
framework, and was processed through synthesis and physical layout flows based
on a LP CMOS 65 nm technology node. The flow anticipates 200 Mrad of ionizing
radiation to select gates, and reports a total area of 3.6 mm^2 and consumes 95
mW of power. The simulated energy consumption per inference is 2.4 nJ. This is
the first radiation tolerant on-detector ASIC implementation of a neural
network that has been designed for particle physics applications.


  Dark deposits visible from orbit appear in the Martian south polar region
during the springtime. These are thought to form from explosive jets of carbon
dioxide gas breaking through the thawing seasonal ice cap, carrying dust and
dirt which is then deposited onto the ice as dark 'blotches', or blown by the
surface winds into streaks or 'fans'. We investigate machine learning (ML)
methods for automatically identifying these seasonal features in High
Resolution Imaging Science Experiment (HiRISE) satellite imagery. We designed
deep Convolutional Neural Networks (CNNs) that were trained and tested using
the catalog generated by Planet Four, an online citizen science project mapping
the south polar seasonal deposits. We validated the CNNs by comparing their
results with those of ISODATA (Iterative Self-Organizing Data Analysis
Technique) clustering and as expected, the CNNs were significantly better at
predicting the results found by Planet Four, in both the area of predicted
seasonal deposits and in delineating their boundaries. We found neither the
CNNs or ISODATA were suited to predicting the source point and directions of
seasonal fans, which is a strength of the citizen science approach. The CNNs
showed good agreement with Planet Four in cross-validation metrics and detected
some seasonal deposits in the HiRISE images missed in the Planet Four catalog;
the total area of seasonal deposits predicted by the CNNs was 27% larger than
that of the Planet Four catalog, but this aspect varied considerably on a
per-image basis.


  The study of the relation between Lie algebras and groups, and especially the
derivation of new algebras from them, is a problem of great interest in
mathematics and physics, because finding a new Lie group from an already known
one also means that a new physical theory can be obtained from a known one. One
of the procedures that allow to do so is called expansion of Lie algebras, and
has been recently used in different physical applications - particularly in
gauge theories of gravity. Here we report on further developments of this
method, required to understand in a deeper way their consequences in physical
theories. We have found theorems related to the preservation of some properties
of the algebras under expansions that can be used as criteria and, more
specifically, as necessary conditions to know if two arbitrary Lie algebras can
be related by the some expansion mechanism. Formal aspects, such as the Cartan
decomposition of the expanded algebras, are also discussed. Finally, an
instructive example that allows to check explicitly all our theoretical results
is also provided.


  Following our recent study (S. Kundu and M. Acharyya, International Journal
of Modern Physics C, 35 (2024) 2450094), we have introduced stochasticity
(random noise) in the Fairen-Velarde deterministic differential equations. The
role of such noise on time scales is studied. The probability of reaching the
domain of fixed points in a given interval is also calculated. The probability
is studied as a function of the width of the noise, and a hyperbolic tangent
fitting is proposed. The noise reduces the time scale for bringing the bacteria
into an inactive state. The area of the fixed-point domain was found to be
asympotically linear with noise. The time to reach the fixed-point domain is
fitted to a Gaussian function with noise intensity.


  In this paper, we study deformations of coisotropic submanifolds in a
symplectic manifold. First we derive the equation that governs $C^\infty$
deformations of coisotropic submanifolds and define the corresponding
$C^\infty$-moduli space of coisotropic submanifolds modulo the Hamiltonian
isotopies. This is a non-commutative and non-linear generalization of the
well-known description of the local deformation space of Lagrangian
submanifolds as the set of graphs of {\it closed} one forms in the
Darboux-Weinstein chart of a given Lagrangian submanifold. We then introduce
the notion of {\it strong homotopy Lie algebroid} (or {\it
$L_\infty$-algebroid}) and associate a canonical isomorphism class of strong
homotopy Lie algebroids to each pre-symplectic manifold $(Y,\omega)$ and
identify the formal deformation space of coisotropic embeddings into a
symplectic manifold in terms of this strong homotopy Lie algebroid. The formal
moduli space then is provided by the gauge equivalence classes of solutions of
a version of the {\it Maurer-Cartan equation} (or the {\it master equation}) of
the strong homotopy Lie algebroid, and plays the role of the classical part of
the moduli space of quantum deformation space of coisotropic $A$-branes. We
provide a criterion for the unobstructedness of the deformation problem and
analyze a family of examples that illustrates that this deformation problem is
obstructed in general and heavily depends on the geometry and dynamics of the
null foliation.


  We define and study the secondary Chern-Euler class for a general submanifold
of a Riemannian manifold. Using this class, we define and study index for a
vector field with non-isolated singularities on a submanifold. As an
application, our studies give conceptual proofs of a classical result of Chern.


  Let $f\colon X\to Y$ be a perfect $n$-dimensional surjection of paracompact
spaces with $Y$ being a $C$-space. We prove that, for any $m\geq n+1$, almost
all (in the sense of Baire category) maps $g$ from $X$ into the $m$-dimensional
cube have the following property: $g(f^{-1}(y))$ is at most $n$-dimensional for
every $y\in Y$.


  Systematic studies on metastability exchange optical pumping of $^3$He nuclei
have been performed at Jefferson Lab using a 1-torr sealed cell at magnetic
fields from 2 to 4 T. The effects of the discharge intensity, pump laser power,
and pumping transition schemes on achievable nuclear polarization and pumping
rate have been investigated. A maximum steady-state nuclear polarization of
about 75% has been obtained. This work provides a baseline for the development
of the novel polarized $^3$He target for CLAS12 at Jefferson Lab.


  We give an analytic construction of a class of two-qubit gate pulse sequences
that act on five of the six spin-$\frac12$ particles used to encode a pair of
exchange-only three-spin qubits. Within this class, the problem of gate
construction reduces to that of finding a smaller sequence that acts on four
spins and is subject to a simple constraint. The optimal sequence satisfying
this constraint yields a two-qubit gate sequence equivalent to that found
numerically by Fong and Wandzura. Our construction is sufficiently simple that
it can be carried out entirely with pen, paper, and knowledge of a few basic
facts about quantum spin. We thereby analytically derive the Fong-Wandzura
sequence that has so far escaped intuitive explanation.


  The study of relativistic particle acceleration is a major topic of
high-energy astrophysics. It is well known that massive black holes in active
galaxies can release a substantial fraction of their accretion power into
energetic particles, producing gamma-rays and relativistic jets. Galactic
microquasars (hosting a compact star of 1-10 solar masses which accretes matter
from a binary companion) also produce relativistic jets. However, no direct
evidence of particle acceleration above GeV energies has ever been obtained in
microquasar ejections, leaving open the issue of the occurrence and timing of
extreme matter energization during jet formation. Here we report the detection
of transient gamma-ray emission above 100 MeV from the microquasar Cygnus X-3,
an exceptional X-ray binary which sporadically produces powerful radio jets.
Four gamma-ray flares (each lasting 1-2 days) were detected by the AGILE
satellite simultaneously with special spectral states of Cygnus X-3 during the
period mid-2007/mid-2009. Our observations show that very efficient particle
acceleration and gamma-ray propagation out of the inner disk of a microquasar
usually occur a few days before major relativistic jet ejections. Flaring
particle energies can be thousands of times larger than previously detected
maximum values (with Lorentz factors of 105 and 102 for electrons and protons,
respectively). We show that the transitional nature of gamma-ray flares and
particle acceleration above GeV energies in Cygnus X-3 is clearly linked to
special radio/X-ray states preceding strong radio flares. Thus gamma-rays
provide unique insight into the nature of physical processes in microquasars.


  We study the positivity of an Ulrich vector bundle defined with respect to a
globally generated ample line bundle. First we prove a generalization of a
Lopez theorem on the first Chern class and the bigness of an Ulrich bundle.
Then, under some additional assumptions on the polarization, we give a
description of its augmented base locus, which consequently leads to a
characterization of the V-bigness and of the ampleness of an Ulrich bundle in
this setting.


  In this paper we classify all surfaces in the 3-dimensional Lie group $Sol_3$
whose normals make constant angle with a left invariant vector field.


  We provide a set of rules to define several spinful quantum Hall model
states. The method extends the one known for spin polarized states. It is
achieved by specifying an undressed root partition, a squeezing procedure and
rules to dress the configurations with spin. It applies to both the
excitation-less state and the quasihole states. In particular, we show that the
naive generalization where one preserves the spin information during the
squeezing sequence, may fail. We give numerous examples such as the Halperin
states, the non-abelian spin-singlet states or the spin-charge separated
states. The squeezing procedure for the series (k=2,r) of spinless quantum Hall
states, which vanish as r powers when k+1 particles coincide, is generalized to
the spinful case. As an application of our method, we show that the counting
observed in the particle entanglement spectrum of several spinful states
matches the one obtained through the root partitions and our rules. This
counting also matches the counting of quasihole states of the corresponding
model Hamiltonians, when the latter is available.


  Wildfires have emerged as one of the most destructive natural disasters
worldwide, causing catastrophic losses in both human lives and forest wildlife.
Recently, the use of Artificial Intelligence (AI) in wildfires, propelled by
the integration of Unmanned Aerial Vehicles (UAVs) and deep learning models,
has created an unprecedented momentum to implement and develop more effective
wildfire management. Although some of the existing survey papers have explored
various learning-based approaches, a comprehensive review emphasizing the
application of AI-enabled UAV systems and their subsequent impact on
multi-stage wildfire management is notably lacking. This survey aims to bridge
these gaps by offering a systematic review of the recent state-of-the-art
technologies, highlighting the advancements of UAV systems and AI models from
pre-fire, through the active-fire stage, to post-fire management. To this aim,
we provide an extensive analysis of the existing remote sensing systems with a
particular focus on the UAV advancements, device specifications, and sensor
technologies relevant to wildfire management. We also examine the pre-fire and
post-fire management approaches, including fuel monitoring, prevention
strategies, as well as evacuation planning, damage assessment, and operation
strategies. Additionally, we review and summarize a wide range of computer
vision techniques in active-fire management, with an emphasis on Machine
Learning (ML), Reinforcement Learning (RL), and Deep Learning (DL) algorithms
for wildfire classification, segmentation, detection, and monitoring tasks.
Ultimately, we underscore the substantial advancement in wildfire modeling
through the integration of cutting-edge AI techniques and UAV-based data,
providing novel insights and enhanced predictive capabilities to understand
dynamic wildfire behavior.


  Turbulence is still one of the main challenges for accurately predicting
reactive flows. Therefore, the development of new turbulence closures which can
be applied to combustion problems is essential. Data-driven modeling has become
very popular in many fields over the last years as large, often extensively
labeled, datasets became available and training of large neural networks became
possible on GPUs speeding up the learning process tremendously. However, the
successful application of deep neural networks in fluid dynamics, for example
for subgrid modeling in the context of large-eddy simulations (LESs), is still
challenging. Reasons for this are the large amount of degrees of freedom in
realistic flows, the high requirements with respect to accuracy and error
robustness, as well as open questions, such as the generalization capability of
trained neural networks in such high-dimensional, physics-constrained
scenarios. This work presents a novel subgrid modeling approach based on a
generative adversarial network (GAN), which is trained with unsupervised deep
learning (DL) using adversarial and physics-informed losses. A two-step
training method is used to improve the generalization capability, especially
extrapolation, of the network. The novel approach gives good results in a
priori as well as a posteriori tests with decaying turbulence including
turbulent mixing. The applicability of the network in complex combustion
scenarios is furthermore discussed by employing it to a reactive LES of the
Spray A case defined by the Engine Combustion Network (ECN).


  We are currently developing Cadmium Zinc Telluride (CZT) detectors for a
next-generation space-borne hard X-ray telescope which can follow up on the
highly successful NuSTAR (Nuclear Spectroscopic Telescope Array) mission. Since
the launch of NuSTAR in 2012, there have been major advances in the area of
X-ray mirrors, and state-of-the-art X-ray mirrors can improve on NuSTAR's
angular resolution of ~1 arcmin Half Power Diameter (HPD) to 15" or even 5"
HPD. Consequently, the size of the detector pixels must be reduced to match
this resolution. This paper presents detailed simulations of relatively thin (1
mm thick) CZT detectors with hexagonal pixels at a next-neighbor distance of
150 $\mu$m. The simulations account for the non-negligible spatial extent of
the deposition of the energy of the incident photon, and include detailed
modeling of the spreading of the free charge carriers as they move toward the
detector electrodes. We discuss methods to reconstruct the energies of the
incident photons, and the locations where the photons hit the detector. We show
that the charge recorded in the brightest pixel and six adjacent pixels
suffices to obtain excellent energy and spatial resolutions. The simulation
results are being used to guide the design of a hybrid application-specific
integrated circuit (ASIC)-CZT detector package.


  Accurate animal pose estimation is an essential step towards understanding
animal behavior, and can potentially benefit many downstream applications, such
as wildlife conservation. Previous works only focus on specific animals while
ignoring the diversity of animal species, limiting the generalization ability.
In this paper, we propose AP-10K, the first large-scale benchmark for mammal
animal pose estimation, to facilitate the research in animal pose estimation.
AP-10K consists of 10,015 images collected and filtered from 23 animal families
and 54 species following the taxonomic rank and high-quality keypoint
annotations labeled and checked manually. Based on AP-10K, we benchmark
representative pose estimation models on the following three tracks: (1)
supervised learning for animal pose estimation, (2) cross-domain transfer
learning from human pose estimation to animal pose estimation, and (3) intra-
and inter-family domain generalization for unseen animals. The experimental
results provide sound empirical evidence on the superiority of learning from
diverse animals species in terms of both accuracy and generalization ability.
It opens new directions for facilitating future research in animal pose
estimation. AP-10k is publicly available at
https://github.com/AlexTheBad/AP10K.