  The nucleon radiative capture reactions are important in pure and applied
nuclear physics, especially in nuclear astrophysics. The keV-nucleon radiative
capture reactions are studied with $^{12}$C and $^{16}$O targets using the
bound-to-continuum potential model in which both scattering and bound states
are treated simultaneously and based on the Skyrme Hartree-Fock approximation.
The obtained results are shown to be in good agreement with the available
experimental data. Alongside astrophysical aspects, the nuclear structure
features were revisited for enlarging the prospect of adopting the nucleon
radiative capture processes as a spectroscopic tool.


  Optimisation of fleets of commercial vehicles with regards scheduling tasks
from various locations to vehicles can result in considerably lower fleet
traversal times. This has significant benefits including reduced expenses for
the company and more importantly, a reduction in the degree of road use and
hence vehicular emissions. Exact optimisation methods fail to scale to real
commercial problem instances, thus meta-heuristics are more suitable. Ant
Colony Optimisation (ACO) generally provides good solutions on small to medium
problem sizes. However, commercial fleet optimisation problems are typically
large and complex, in which ACO fails to scale well. Partial-ACO is a new ACO
variant designed to scale to larger problem instances. Therefore this paper
investigates the application of Partial-ACO on the problem of fleet
optimisation, demonstrating the capacity of Partial-ACO to successfully scale
to larger problems. Indeed, for real-world fleet optimisation problems supplied
by a Birmingham based company with up to 298 jobs and 32 vehicles, Partial-ACO
can improve upon their fleet traversal times by over 44%. Moreover, Partial-ACO
demonstrates its ability to scale with considerably improved results over
standard ACO and competitive results against a Genetic Algorithm.


  The dwarf galaxy Segue 1 is one of the most promising targets for the
indirect detection of dark matter. Here we examine what constraints 9 months of
Fermi-LAT gamma-ray observations of Segue 1 place upon the Constrained Minimal
Supersymmetric Standard Model (CMSSM), with the lightest neutralino as the dark
matter particle. We use nested sampling to explore the CMSSM parameter space,
simultaneously fitting other relevant constraints from accelerator bounds, the
relic density, electroweak precision observables, the anomalous magnetic moment
of the muon and B-physics. We include spectral and spatial fits to the Fermi
observations, a full treatment of the instrumental response and its related
uncertainty, and detailed background models. We also perform an extrapolation
to 5 years of observations, assuming no signal is observed from Segue 1 in that
time. Results marginally disfavour models with low neutralino masses and high
annihilation cross-sections. Virtually all of these models are however already
disfavoured by existing experimental or relic density constraints.


  The Fermi bubbles, two giant gamma-ray bubbles above and below the Galactic
center (GC), are among the most important findings of the Fermi Gamma-ray Space
Telescope. Because of the proximity, spatially resolved, multi-wavelength
observations offer excellent opportunities to learn about the physical origin
of the bubbles. One of the unique features of the observed bubbles is that
their gamma-ray spectrum, including a high-energy cutoff at ~110 GeV and the
overall shape of the spectrum, is nearly spatially uniform. The high-energy
spectral cutoff is suggestive of a leptonic origin as it could be a signature
of synchrotron and inverse-Compton (IC) cooling of cosmic-ray (CR) electrons;
however, even for a leptonic model, it is not obvious why the spectrum should
be spatially uniform. In this work, we investigate the formation of the Fermi
bubble in the leptonic jet scenario using a newly implemented CRSPEC module in
FLASH that allows us to track the evolution of CR spectrum on-the-fly during
the simulations. We show that the high-energy cutoff is caused by fast
synchrotron and IC cooling near the GC when the jets were first launched. After
the jets propagate away from the GC, the dynamical timescale of the jets become
the shortest among all relevant timescales, and therefore the spectrum is
essentially advected with only mild cooling losses. This could explain why the
bubble spectrum is nearly spatially uniform: the CRs from different parts of
the bubbles as seen today all share the same origin near the GC at early stage
of the bubble expansion. We find that the CR spatial and spectral distribution
predicted by the leptonic jet model can simultaneously match the normalization,
spectral shape, and high-energy cutoff of the observed gamma-ray spectrum and
their spatial uniformity, suggesting that past AGN jet activity is a likely
mechanism for the formation of the Fermi bubbles.


  We describe the properties of the host galaxy of the gamma-ray burst
GRB060510B based on a spectrum of the burst afterglow obtained with the Gemini
North 8m telescope. The galaxy lies at a redshift of z = 4.941 making it the
fourth highest spectroscopically identified burst host. However, it is the
second highest redshift galaxy for which the quality of the spectrum permits a
detailed metallicity analysis. The neutral hydrogen column density has a
logarithmic value of 21.0--21.2 cm^-2 and the weak metal lines of Ni, S and Fe
show that the metallicity is in excess of a tenth of solar which is far above
the metallicities in damped Lyman alpha absorbers at high redshift. The
tightest constraint is from the Fe lines which place [Fe/H] in excess of -0.8.
We argue that the results suggest that metallicity bias could be a serious
problem with inferring star formation from the GRB population and consider how
future higher quality measurements could be used to resolve this question.


  We analyze the properties of optical cavities contained in spacers with
approximate octahedral symmetry and made of different materials,following the
design of Webster and Gill (S. Webster, P. Gill, Optics Letters 36(18), 3572
(2011)). We show that for isotropic materials with Young's modulus less than
200 GPa, the Poisson's ratio $\nu$ must lie in a "magic" range 0.13<$\nu$<0.23
in order to null the influence of the forces supporting the spacer. This
restriction can be overcome with the use of anisotropic materials such as
silicon. A detailed study aiming at identification of all suitable crystal
orientations of silicon with respect to the resonator body is performed and the
relation to the Poisson's ratio and the Young's modulus along these
orientations is discussed. We also perform an analysis of the sensitivity of
the cavity performance to errors in spacer manufacturing. We find that the
orientation of the [110] or [100] crystallographic directions oriented along
one of the three optical axes of the resonator provides low sensitivities to
imprecise manufacturing and interesting options for fundamental physics
experiments.


  We present an extensive theoretical investigation of the proximity effects
that occur in Ferromagnet/Superconductor ($F/S$) systems. We use a numerical
method to solve self consistently the Bogoliubov-de Gennes equations in the
continuum. We obtain the pair amplitude and the local density of states (DOS),
and use these results to extract the relevant lengths characterizing the
leakage of superconductivity into the magnet and to study spin splitting into
the superconductor. These phenomena are investigated as a function of
parameters such as temperature, magnet polarization, interfacial scattering,
sample size and Fermi wavevector mismatch, all of which turn out to have
important influence on the results. These comprehensive results should help
characterize and analyze future data and are shown to be in agreement with
existing experiments.


  Given a convex disk $K$ and a positive integer $k$, let $\delta_T^k(K)$ and
$\delta_L^k(K)$ denote the $k$-fold translative packing density and the
$k$-fold lattice packing density of $K$, respectively. Let $T$ be a triangle.
In a very recent paper, K. Sriamorn proved that
$\delta_L^k(T)=\frac{2k^2}{2k+1}$. In this paper, I will show that
$\delta_T^k(T)=\delta_L^k(T)$.


  We present an analysis of the predictions made by the Galform semi-analytic
galaxy formation model for the evolution of the relationship between stellar
mass and halo mass. We show that for the standard implementations of supernova
feedback and gas reincorporation used in semi-analytic models, this
relationship is predicted to evolve weakly over the redshift range 0<z<4.
Modest evolution in the median stellar mass versus halo mass (SHM) relationship
implicitly requires that, at fixed halo mass, the efficiency of stellar mass
assembly must be almost constant with cosmic time. We show that in our model,
this behaviour can be understood in simple terms as a result of a constant
efficiency of gas reincorporation, and an efficiency of SNe feedback that is,
on average, constant at fixed halo mass. We present a simple explanation of how
feedback from active galactic nuclei (AGN) acts in our model to introduce a
break in the SHM relation whose location is predicted to evolve only modestly.
Finally, we show that if modifications are introduced into the model such that,
for example, the gas reincorporation efficiency is no longer constant, the
median SHM relation is predicted to evolve significantly over 0<z<4.
Specifically, we consider modifications that allow the model to better
reproduce either the evolution of the stellar mass function or the evolution of
average star formation rates inferred from observations.


  In this Note we show that Einstein's equations for gravity are generically
invariant under 'disformations'. We also show that the particular subclass when
this is not true yields the equations of motion of 'Mimetic Gravity'. Finally
we give the 'mimetic' generalization of the Schwarzschild solution.


  Quantum dynamical simulations of statistical ensembles pose a significant
computational challenge due to the fact that mixed states need to be
represented. If the underlying dynamics is fully unitary, for example in
ultrafast coherent control at finite temperatures, one approach to approximate
time-dependent observables is to sample the density operator by solving the
Schr\"{o}dinger equation for a set of wave functions with randomized phases. We
show that, on average, random-phase wave functions perform well for ensembles
with high mixedness, whereas at higher purities a deterministic sampling of the
energetically lowest-lying eigenstates becomes superior. We prove that
minimization of the worst-case error for computing arbitrary observables is
uniquely attained by eigenstate-based sampling. We show that this error can be
used to form a qualitative estimate of the set of ensemble purities for which
the sampling performance of the eigenstate-based approach is superior to
random-phase wave functions. Furthermore we present refinements to both schemes
which remove redundant information from the sampling procedure to accelerate
their convergence. Finally, we point out how the structure of low-rank
observables can be exploited to further improve eigenstate-based sampling
schemes.


  Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer in which
the tumor-vascular involvement greatly affects the resectability and, thus,
overall survival of patients. However, current prognostic prediction methods
fail to explicitly and accurately investigate relationships between the tumor
and nearby important vessels. This paper proposes a novel learnable neural
distance that describes the precise relationship between the tumor and vessels
in CT images of different patients, adopting it as a major feature for
prognosis prediction. Besides, different from existing models that used CNNs or
LSTMs to exploit tumor enhancement patterns on dynamic contrast-enhanced CT
imaging, we improved the extraction of dynamic tumor-related texture features
in multi-phase contrast-enhanced CT by fusing local and global features using
CNN and transformer modules, further enhancing the features extracted across
multi-phase CT images. We extensively evaluated and compared the proposed
method with existing methods in the multi-center (n=4) dataset with 1,070
patients with PDAC, and statistical analysis confirmed its clinical
effectiveness in the external test set consisting of three centers. The
developed risk marker was the strongest predictor of overall survival among
preoperative factors and it has the potential to be combined with established
clinical factors to select patients at higher risk who might benefit from
neoadjuvant therapy.


  Aiming for a better integration of data-driven and linguistically-inspired
approaches, we explore whether RST Nuclearity, assigning a binary assessment of
importance between text segments, can be replaced by automatically generated,
real-valued scores, in what we call a Weighted-RST framework. In particular, we
find that weighted discourse trees from auxiliary tasks can benefit key NLP
downstream applications, compared to nuclearity-centered approaches. We further
show that real-valued importance distributions partially and interestingly
align with the assessment and uncertainty of human annotators.


  The determination of cluster centers generally depends on the scale that we
use to analyze the data to be clustered. Inappropriate scale usually leads to
unreasonable cluster centers and thus unreasonable results. In this study, we
first consider the similarity of elements in the data as the connectivity of
nodes in an undirected graph, then present the concept of a connection center
and regard it as the cluster center of the data. Based on this definition, the
determination of cluster centers and the assignment of class are very simple,
natural and effective. One more crucial finding is that the cluster centers of
different scales can be obtained easily by the different powers of a similarity
matrix and the change of power from small to large leads to the dynamic
evolution of cluster centers from local (microscopic) to global (microscopic).
Further, in this process of evolution, the number of categories changes
discontinuously, which means that the presented method can automatically skip
the unreasonable number of clusters, suggest appropriate observation scales and
provide corresponding cluster results.


  Dissolving armored bubbles stabilize with nonspherical shapes by jamming the
initially Brownian particles adsorbed on their interfaces. In a gas-saturated
solution, these shapes are characterized by planar facets or folds for
decreasing ratios of the particle to bubble radii. We perform numerical
simulations that mimic dissolution, and show that the faceted shape represents
a local minimum of energy during volume reduction. This minimum is marked by
the vanishing of the Laplace overpressure $\Delta P$, which together with the
existence of a $V$-interval where $d\Delta P/dV>0$ guarantees stability against
dissolution. The reduction of $\Delta P$ is due to the saddle-shape deformation
of most of the interface which accompanies the reduction in the mean curvature
of the interface.


  While perception systems in Connected and Autonomous Vehicles (CAVs), which
encompass both communication technologies and advanced sensors, promise to
significantly reduce human driving errors, they also expose CAVs to various
cyberattacks. These include both communication and sensing attacks, which
potentially jeopardize not only individual vehicles but also overall traffic
safety and efficiency. While much research has focused on communication
attacks, sensing attacks, which are equally critical, have garnered less
attention. To address this gap, this study offers a comprehensive review of
potential sensing attacks and their impact on target vehicles, focusing on
commonly deployed sensors in CAVs such as cameras, LiDAR, Radar, ultrasonic
sensors, and GPS. Based on this review, we discuss the feasibility of
integrating hardware-in-the-loop experiments with microscopic traffic
simulations. We also design baseline scenarios to analyze the macro-level
impact of sensing attacks on traffic flow. This study aims to bridge the
research gap between individual vehicle sensing attacks and broader macroscopic
impacts, thereby laying the foundation for future systemic understanding and
mitigation.


  Suppose $G$ is a tree. Graham's "Tree Reconstruction Conjecture" states that
$G$ is uniquely determined by the integer sequence $|G|$, $|L(G)|$,
$|L(L(G))|$, $|L(L(L(G)))|$, $\ldots$, where $L(H)$ denotes the line graph of
the graph $H$. Little is known about this question apart from a few simple
observations. We show that the number of trees on $n$ vertices which can be
distinguished by their associated integer sequences is $e^{\Omega((\log
n)^{3/2})}$. The proof strategy involves constructing a large collection of
caterpillar graphs using partitions arising from the Prouhet-Tarry-Escott
problem.


  The AdS/CFT correspondence defines a sector with universal strongly coupled
dynamics in the field theory as the dual of pure gravity in AdS described by
Einstein's equation with a negative cosmological constant. We explain here,
from the field-theoretic viewpoint how the dynamics in this sector gets
determined by the expectation value of the energy-momentum tensor \emph{alone}.
We first show that the Boltzmann equation has very special solutions which
could be \textit{functionally} completely determined in terms of the
energy-momentum tensor alone. We call these solutions \textit{conservative
solutions}. We indicate why conservative solutions should also exist when we
refine this kinetic description to go closer to the exact microscopic theory or
even move away from the regime of weak coupling so that no kinetic description
could be employed. We argue that these \textit{conservative solutions} form the
universal sector dual to pure gravity at strong coupling and large $N$. Based
on this observation, we propose a \textit{regularity condition} on the
energy-momentum tensor so that the dual solution in pure gravity has a smooth
future horizon. We also study if irreversibility emerges only at long time
scales of observation, unlike the case of the Boltzmann equation.


  We calculate the most massive object in the Universe, finding it to be a
cluster of galaxies with total mass M_200=3.8e15 Msun at z=0.22, with the 1
sigma marginalized regions being 3.3e15 Msun<M<4.4e15 Msun and 0.12<z<0.36. We
restrict ourselves to self-gravitating bound objects, and base our results on
halo mass functions derived from N-body simulations. Since we consider the very
highest mass objects, the number of candidates is expected to be small, and
therefore each candidate can be extensively observed and characterized. If
objects are found with excessively large masses, or insufficient objects are
found near the maximum expected mass, this would be a strong indication of the
failure of LambdaCDM. The expected range of the highest masses is very
sensitive to redshift, providing an additional evolutionary probe of LambdaCDM.
We find that the three most massive clusters in the recent SPT 178 deg^2
catalog match predictions, while XMMU J2235.3--2557 is roughly 3 sigma
inconsistent with LambdaCDM. We discuss Abell 2163 and Abell 370 as candidates
for the most massive cluster in the Universe, although uncertainties in their
masses preclude definitive comparisons with theory. Our findings motivate
further observations of the highest mass end of the mass function. Future
surveys will explore larger volumes, and the most massive object in the
Universe may be identified within the next decade. The mass distribution of the
largest objects in the Universe is a potentially powerful test of LambdaCDM,
probing non-Gaussianity and the behavior of gravity on large scales.


  For the shape control of deformable free-form surfaces, simulation plays a
crucial role in establishing the mapping between the actuation parameters and
the deformed shapes. The differentiation of this forward kinematic mapping is
usually employed to solve the inverse kinematic problem for determining the
actuation parameters that can realize a target shape. However, the free-form
surfaces obtained from simulators are always different from the physically
deformed shapes due to the errors introduced by hardware and the simplification
adopted in physical simulation. To fill the gap, we propose a novel deformation
function based sim-to-real learning method that can map the geometric shape of
a simulated model into its corresponding shape of the physical model. Unlike
the existing sim-to-real learning methods that rely on completely acquired
dense markers, our method accommodates sparsely distributed markers and can
resiliently use all captured frames -- even for those in the presence of
missing markers. To demonstrate its effectiveness, our sim-to-real method has
been integrated into a neural network-based computational pipeline designed to
tackle the inverse kinematic problem on a pneumatically actuated deformable
mannequin.


  We give a Lie-theoretic explanation for the convex polytope which
parametrizes the globally smooth solutions of the topological-antitopological
fusion equations of Toda type (tt$^*$-Toda equations) which were introduced by
Cecotti and Vafa. It is known from [GL] [GIL1] [M1] [M2] that these solutions
can be parametrized by monodromy data of a certain flat
$SL_{n+1}\mathbb{R}$-connection. Using Boalch's Lie-theoretic description of
Stokes data, and Steinberg's description of regular conjugacy classes of a
linear algebraic group, we express this monodromy data as a convex subset of a
Weyl alcove of $SU_{n+1}$.


  It is believed that the core of a neutron star can be host to various novel
phases of matter, from nucleon superfluid phase to exotic high baryon density
quantum chromodynamics (QCD) phases. Different observational signals for such
phase transitions have been discussed in the literature. Here, we point out a
unique phenomenon associated with phase transition to a superfluid phase, which
may be the nucleon superfluid phase or a phase like the CFL phase, allowing for
superfluid vortices. In any superfluid phase transition, a random network of
vortices forms via the so-called Kibble-Zurek mechanism, which eventually
mostly decays away, finally leaving primarily vortices arising from the initial
angular momentum of the core. This transient, random vortex network can have a
non-zero net angular momentum for the superfluid component, which will
generally be oriented in an arbitrary direction. This is in contrast to the
final vortices, which arise from initial rotation and hence have the initial
angular momentum of the neutron star. The angular momentum of the random vortex
network is balanced by an equal and opposite angular momentum in the normal
fluid due to the conservation of angular momentum, thereby imparting an
arbitrarily oriented angular momentum component to the outer shell of the
neutron star. This will affect the pulse timing and pulse profile of a pulsar.
These changes in the pulses will decay away in a characteristic manner such
that the random vortex network decays, obeying specific scaling laws leading to
universal features for the detection of superfluid transitions occurring in a
pulsar core.


  We describe iterated integrals as unipotent periods on families of marked
elliptic curves in terms of multiple zeta values and elliptic multiple zeta
values.


  The spectral weight evolution of the low-dimensional Mott insulator TiOCl
upon alkali-metal dosing has been studied by photoelectron spectroscopy. We
observe a spectral weight transfer between the lower Hubbard band and an
additional peak upon electron-doping, in line with quantitative expectations in
the atomic limit for changing the number of singly and doubly occupied sites.
This observation is an unconditional hallmark of correlated bands and has not
been reported before. In contrast, the absence of a metallic quasiparticle peak
can be traced back to a simple one-particle effect.


  Epidemiological models may give some basic guidelines for public health
practitioners, allowing to analyze issues that can influence the strategies to
prevent and fight a disease. To be used in decision-making, however, a
mathematical model must be carefully parameterized and validated with
epidemiological and entomological data. Here a SIR (S for susceptible, I for
infectious, R for recovered individuals) and ASI (A for the aquatic phase of
the mosquito, S for susceptible and I for infectious mosquitoes)
epidemiological model describing a dengue disease is presented, as well as the
associated basic reproduction number. A sensitivity analysis of the
epidemiological model is performed in order to determine the relative
importance of the model parameters to the disease transmission.


  We present a new method for showing that groups are virtually special. This
is done by considering finite quotients and linear characters. We use this to
show that an infinite family of groups, related to Bestvina-Brady groups and
branching, provides new examples of virtually special groups outside of a
hyperbolic context.


  The notion of $\times$-homotopy from \cite{DocHom} is investigated in the
context of the category of pointed graphs. The main result is a long exact
sequence that relates the higher homotopy groups of the space $\Hom_*(G,H)$
with the homotopy groups of $\Hom_*(G,H^I)$. Here $\Hom_*(G,H)$ is a space
which parametrizes pointed graph maps from $G$ to $H$ (a pointed version of the
usual $\Hom$ complex), and $H^I$ is the graph of based paths in $H$. As a
corollary it is shown that $\pi_i \big(\Hom_*(G,H) \big) \cong [G,\Omega^i
H]_{\times}$, where $\Omega H$ is the graph of based closed paths in $H$ and
$[G,K]_{\times}$ is the set of $\times$-homotopy classes of pointed graph maps
from $G$ to $K$. This is similar in spirit to the results of \cite{BBLL}, where
the authors seek a space whose homotopy groups encode a similarly defined
homotopy theory for graphs. The categorical connections to those constructions
are discussed.


  We explore the ability of the Tevatron to probe Minimal Supersymmetry with
high energy scale boundary conditions motivated by supersymmetry breaking in
the context of supergravity/superstring theory. A number of boundary condition
possibilities are considered: dilaton-like string boundary conditions applied
at the standard GUT unification scale or alternatively at the string scale; and
extreme (``no-scale'') minimal supergravity boundary conditions imposed at the
GUT scale or string scale. For numerous specific cases within each scenario the
sparticle spectra are computed and then fed into ISAJET 7.07 so that explicit
signatures can be examined in detail. We find that, for some of the boundary
condition choices, large regions of parameter space can be explored via
same-sign dilepton and isolated trilepton signals. For other choices, the mass
reach of Tevatron collider experiments is much more limited. We also compare
mass reach of Tevatron experiments with the corresponding reach at LEP 200.


  Recent Herschel observations of nearby clouds have shown that filamentary
structures are ubiquitous and that most prestellar cores form in filaments.
Probing the density ($n$) and velocity ($V$) structure of filaments is crucial
for the understanding of the star formation process. To characterize both the
$n$ and the $V$ field of a fragmenting filament, we mapped NGC2024. 13CO, C18O,
and H13CO+ trace the filament seen in the $N_{H_2}$ data. The radial profile
from the $N_{H_2}$ data shows $D_{HP}$~0.081 pc, which is similar to the
Herschel findings. The $D_{HP}$ from 13CO and C18O are broader, while the
$D_{HP}$ from H13CO+ is narrower, than $D_{HP}$ from Herschel. These results
suggest that 13CO and C18O trace only the outer part of the filament and H13CO+
only the inner part. The H13CO+ $V_{centroid}$ map reveals $V$ gradients along
both filament axis, as well as $V$ oscillations with a period $\lambda$~0.2 pc
along the major axis. Comparison between the $V$ and the $n$ distribution shows
a tentative $\lambda$/4 shift in H13CO+ or C18O. This $\lambda$/4 shift is not
simultaneously observed for all cores in any single tracer but is tentatively
seen in either H13CO+ or C18O. We produced a toy model taking into account a
transverse $V$ gradient, a longitudinal $V$ gradient, and a longitudinal
oscillation mode caused by fragmentation. Examination of synthetic data shows
that the oscillation component produces an oscillation pattern in the velocity
structure function (VSF) of the model. The H13CO+ VSF shows an oscillation
pattern, suggesting that our observations are partly tracing core-forming
motions and fragmentation. We also found that the mean $M_{core}$ corresponds
to the effective $M_{BE}$ in the filament. This is consistent with a scenario
in which higher-mass cores form in higher line-mass filaments.


  How to effectively interact audio with vision has garnered considerable
interest within the multi-modality research field. Recently, a novel
audio-visual segmentation (AVS) task has been proposed, aiming to segment the
sounding objects in video frames under the guidance of audio cues. However,
most existing AVS methods are hindered by a modality imbalance where the visual
features tend to dominate those of the audio modality, due to a unidirectional
and insufficient integration of audio cues. This imbalance skews the feature
representation towards the visual aspect, impeding the learning of joint
audio-visual representations and potentially causing segmentation inaccuracies.
To address this issue, we propose AVSAC. Our approach features a Bidirectional
Audio-Visual Decoder (BAVD) with integrated bidirectional bridges, enhancing
audio cues and fostering continuous interplay between audio and visual
modalities. This bidirectional interaction narrows the modality imbalance,
facilitating more effective learning of integrated audio-visual
representations. Additionally, we present a strategy for audio-visual
frame-wise synchrony as fine-grained guidance of BAVD. This strategy enhances
the share of auditory components in visual features, contributing to a more
balanced audio-visual representation learning. Extensive experiments show that
our method attains new benchmarks in AVS performance.


  This paper presents new analytical formulae for flow in a channel with one or
both walls patterned with a longitudinal array of ridges and arbitrarily
protruding menisci. Derived from a matched asymptotic expansion, they extend
results by Crowdy (J. Fluid Mech., vol. 791, 2016, R7) for shear flow, and thus
make no restriction on the protrusion into or out of the liquid. The slip
length formula is compared against full numerical solutions and, despite the
assumption of small ridge period in its derivation, is found to have a very
large range of validity; relative errors are small even for periods large
enough for the protruding menisci to degrade the flow and touch the opposing
wall.


  It has been observed that certain classical chains admit topologically
protected zero-energy modes that are localized on the boundaries. The static
features of such localized modes are captured by linearized equations of
motion, but the dynamical features are governed by its nonlinearity. We study
quasi-periodic solutions of nonlinear equations of motion of one-dimensional
classical chains. Such quasi-periodic solutions correspond to periodic
trajectories in the configuration space of the discrete systems, which allows
us to define solitons without relying on a continuum theory. Furthermore, we
study the dynamics of solitons in inhomogeneous systems by connecting two
chains with distinct parameter sets, where transmission or reflection of
solitons occurs at the boundary of the two chains.


  We consider the proximity effect between a singlet s-wave superconductor and
the edge of a Quantum Spin Hall (QSH) topological insulator. We establish that
Andreev reflection at a QSH edge state/superconductor interface is perfect
while nonlocal Andreev processes through the superconductor are totally
suppressed. We compute the corresponding conductance and noise.


  The recent discovery at the LHC by the CMS and ATLAS collaborations of the
Higgs boson presents, at long last, direct probes of the mechanism for
electroweak symmetry breaking. While it is clear from the observations that the
new particle plays some role in this process, it is not yet apparent whether
the couplings and widths of the observed particle match those predicted by the
Standard Model. In this paper, we perform a global fit of the Higgs results
from the LHC and Tevatron. While these results could be subject to
as-yet-unknown systematics, we find that the data are significantly better fit
by a Higgs with a suppressed width to gluon-gluon and an enhanced width to
gamma gamma, relative to the predictions of the Standard Model. After
considering a variety of new physics scenarios which could potenially modify
these widths, we find that the most promising possibility is the addition of a
new colored, charged particle, with a large coupling to the Higgs. Of
particular interest is a light, and highly mixed, stop, which we show can
provide the required alterations to the combination of gg and gamma gamma
widths.


  The 5-year project Supernova Legacy Survey (SNLS) delivers $\sim 100$ Type-Ia
supernovae (SNe Ia) per year, in the redshift range $0.3 < z < 1.0$, with
well-sampled $g'r'i'z'$ lightcurves. The SNLS Collaboration uses the 1 deg$^2$
Megacam imager (36 $2048 \times 4612$ thinned CCDs) mounted on the 3.6-m
Canada-France-Hawaii Telescope (CFHT) to observe four fields around the sky, in
four filters. The primary goal of the project is to measure the dark energy
equation of state with a final statistical precision of $\pm 0.05$. We have
shown, using the first year dataset that the calibration uncertainties are
currently the dominant contribution to the systematic error budget. The
calibration of the SNLS dataset is challenging in several aspects. First,
Megacam is a wide-field imager, and only a handful of its 36 CCDs can be
directly calibrated using standard star observations. Second, measuring the
rest-frame $B$-band luminosity of SNe Ia over the $0.3<z<1.0$ redshift range
requires an excellent flux intercalibration of the Megacam bands. Finally, the
SN Ia SED differs significantly from that of stars and transfering the stellar
calibration to the SNLS data requires a precise knowledge of the SN Ia spectra
and the instrument transmissions. We present and discuss the SNLS calibration
strategy used to analyze the first year data set. We present the calibration
aspects which impact most the cosmological measurements. We also discuss the
intercalibration of the SNLS with other surveys, such as the CFHTLS-Wide and
the SDSS.


  It is argued that it is valid to use QCD sum rules to determine the scalar
and pseudoscalar two-point functions at zero momentum, which in turn determine
the ratio of the strange to non-strange quark condensates $R_{su} =
\frac{<\bar{s} s>}{<\bar{q} q>}$ with ($q=u,d$). This is done in the framework
of a new set of QCD Finite Energy Sum Rules (FESR) that involve as integration
kernel a second degree polynomial, tuned to reduce considerably the systematic
uncertainties in the hadronic spectral functions. As a result, the parameters
limiting the precision of this determination are $\Lambda_{QCD}$, and to a
major extent the strange quark mass. From the positivity of $R_{su}$ there
follows an upper bound on the latter: $\bar{m_{s}} (2 {GeV}) \leq 121 (105)
{MeV}$, for $\Lambda_{QCD} = 330 (420) {MeV} .$


  The effect of non-magnetic impurities is discussed for both the two-leg
Heisenberg ladder system and other spin liquids with excitation gap. It is
shown that the random depletion of spins introduces a random Berry phase term
to the non-linear sigma model. The classical nature of the antiferromagnetic
correlation is enhanced by the topological decoherence, and the staggered
susceptibility shows more singular behavior at low temperatures than the
uniform antiferromagnetic Heisenberg chain.


  We derive an extended empirical likelihood for parameters defined by
estimating equations which generalizes the original empirical likelihood for
such parameters to the full parameter space. Under mild conditions, the
extended empirical likelihood has all asymptotic properties of the original
empirical likelihood. Its contours retain the data-driven shape of the latter.
It can also attain the second order accuracy. The first order extended
empirical likelihood is easy-to-use yet it is substantially more accurate than
other empirical likelihoods, including second order ones. We recommend it for
practical applications of the empirical likelihood method.


  In this paper, using a basic algebraic approach, we demonstrate that, if the
integers $x,y$ and $z$ are pairwise relatively prime, and $x^p-my^p=zw$ where
$m$ is an integer and $p$ is a prime, then we can write $x,y,m,z$ and $w$ as
explicit expressions in 7 integers.


  The current COVID-19 pandemic is having detrimental consequences worldwide.
The pandemic started to develop strongly by the end of January and beginning of
February 2020, first in China with subsequent rapid spread to other countries
with new epicenters of the outbreaks concentrated mainly within the 30-50
degrees North latitudinal band (e.g., South Korea, Japan, Iran, Italy, Spain).
Simultaneously, an unusual persistent anticyclonic situation prevailing at
latitudes around 40 degrees North was observed on global scale, in line with an
anomalously strong positive phase of the Arctic Oscillation. This atypical
situation could have resulted in favorable meteorological conditions for a
quicker spread of the virus over the latitude band detailed above. This
possible connection needs further attention in order to understand the
meteorological and climatological factors related to the COVID-19 outbreak, and
for anticipating the spatio-temporal distribution of possible future pandemics.


  Valley degrees of freedom offer a potential resource for quantum information
processing if they can be effectively controlled. We discuss an optical
approach to this problem in which intense light breaks electronic symmetries of
a two-dimensional Dirac material. The resulting quasienergy structures may then
differ for different valleys, so that the Floquet physics of the system can be
exploited to produce highly polarized valley currents. This physics can be
utilized to realize a valley valve whose behavior is determined optically. We
propose a concrete way to achieve such valleytronics in graphene as well as in
a simple model of an inversion-symmetry broken Dirac material. We study the
effect numerically and demonstrate its robustness against moderate disorder and
small deviations in optical parameters.


  The charge of microparticles immersed in the dc discharge of the
Plasmakristall-4 experimental facility has been estimated using the particle
velocities from experiments performed on Earth and under microgravity
conditions on the International Space Station. The theoretical model used for
these estimates is based on the balance of the forces acting on a single
particle in the discharge. The model takes into account the radial dependence
of the discharge parameters and describes reasonably well the experimental
measurements.


  In this paper we make an attempt to study right loops $(S, o)$ in which, for
each $y\in S$, the map $\sigma_y$ from the inner mapping group $G_S$ of $(S,
o)$ to itself given by $\sigma_y (h)(x) o\ h(y)= h(xoy)$, $x\in S, h\in G_S$ is
a homomorphism. The concept of twisted automorphisms of a right loop and also
the concept of twisted right gyrogroup appears naturally and it turns out that
the study is almost equivalent to the study of twisted automorphisms and a
twisted right gyrogroup. A representation theorem for twisted right gyrogroup
is established. We also study relationship between twisted gyrotransversals and
twisted subgroups (a concept which arose as a tool to study computational
complexity involving class NP).


  Drone susceptibility to jamming or spoofing attacks of GPS, RF, Wi-Fi, and
operator signals presents a danger to future medical delivery systems. A
detection framework capable of sensing attacks on drones could provide the
capability for active responses. The identification of interference attacks has
applicability in medical delivery, disaster zone relief, and FAA enforcement
against illegal jamming activities. A gap exists in the literature for solo or
swarm-based drones to identify radio frequency spectrum attacks. Any
non-delivery specific function, such as attack sensing, added to a drone
involves a weight increase and additional complexity; therefore, the value must
exceed the disadvantages. Medical delivery, high-value cargo, and disaster zone
applications could present a value proposition which overcomes the additional
costs. The paper examines types of attacks against drones and describes a
framework for designing an attack detection system with active response
capabilities for improving the reliability of delivery and other medical
applications.


  The inception of the Relational Graph Convolutional Network (R-GCN) marked a
milestone in the Semantic Web domain as a widely cited method that generalises
end-to-end hierarchical representation learning to Knowledge Graphs (KGs).
R-GCNs generate representations for nodes of interest by repeatedly aggregating
parameterised, relation-specific transformations of their neighbours. However,
in this paper, we argue that the the R-GCN's main contribution lies in this
"message passing" paradigm, rather than the learned weights. To this end, we
introduce the "Random Relational Graph Convolutional Network" (RR-GCN), which
leaves all parameters untrained and thus constructs node embeddings by
aggregating randomly transformed random representations from neighbours, i.e.,
with no learned parameters. We empirically show that RR-GCNs can compete with
fully trained R-GCNs in both node classification and link prediction settings.


  Particle-stabilized emulsions are commonly used in various industrial
applications. These emulsions can present in different forms, such as Pickering
emulsions or bijels, which can be distinguished by their different topologies
and rheology. We numerically investigate the effect of the volume fraction and
the uniform wettability of the stabilizing spherical particles in mixtures of
two fluids. For this, we use the well-established three-dimensional lattice
Boltzmann method, extended to allow for the added colloidal particles with
non-neutral wetting properties. We obtain data on the domain sizes in the
emulsions by using both structure functions and the Hoshen-Kopelman (HK)
algorithm, and demonstrate that both methods have their own (dis-)advantages.
We confirm an inverse dependence between the concentration of particles and the
average radius of the stabilized droplets. Furthermore, we demonstrate the
effect of particles detaching from interfaces on the emulsion properties and
domain size measurements.


  A method for determining the positions of hologram dislocations relative to
the optical axes of entangled Laguerre Gaussian modes is proposed. In our
method, the coincidence count rate distribution was obtained by scanning the
position of one of the holograms in two dimensions. Then, the relative position
of the hologram dislocation was determined quantitatively from the positions of
the minimum and maximum coincidence count rates. The validity of the method was
experimentally verified, and in addition, an experiment demonstrating the
violation of the Clauser-Horne-Shimony-Holt inequality was performed using the
well-identified optical axes of the entangled modes.


  We investigate transport properties of a double quantum dot based Cooper pair
splitter, where the superconducting lead consists of Sr$_2$RuO$_4$. The
proposed device can be used to explore the symmetry of the superconducting
order parameter in Sr$_2$RuO$_4$ by testing the presence of gapless chiral edge
states, which are predicted to exist if the bulk superconductor is described by
a chiral $p$--wave state. The odd orbital symmetry of the bulk order parameter
ensures that we can realize a regime where the electrons tunneling into the
double dot system come from the chiral edge states and thereby leave their
signature in the conductance. The proposed Cooper pair splitter has the
potential to probe order parameters in unconventional superconductors.


  Any-to-any singing voice conversion (SVC) is confronted with the challenge of
``timbre leakage'' issue caused by inadequate disentanglement between the
content and the speaker timbre. To address this issue, this study introduces
NeuCoSVC, a novel neural concatenative SVC framework. It consists of a
self-supervised learning (SSL) representation extractor, a neural harmonic
signal generator, and a waveform synthesizer. The SSL extractor condenses audio
into fixed-dimensional SSL features, while the harmonic signal generator
leverages linear time-varying filters to produce both raw and filtered harmonic
signals for pitch information. The synthesizer reconstructs waveforms using SSL
features, harmonic signals, and loudness information. During inference, voice
conversion is performed by substituting source SSL features with their nearest
counterparts from a matching pool which comprises SSL features extracted from
the reference audio, while preserving raw harmonic signals and loudness from
the source audio. By directly utilizing SSL features from the reference audio,
the proposed framework effectively resolves the ``timbre leakage" issue caused
by previous disentanglement-based approaches. Experimental results demonstrate
that the proposed NeuCoSVC system outperforms the disentanglement-based speaker
embedding approach in one-shot SVC across intra-language, cross-language, and
cross-domain evaluations.


  We present a top-down approach to the study of the dynamics of icosahedral
virus capsids, in which each protein is approximated by a point mass. Although
this represents a rather crude coarse-graining, we argue that it highlights
several generic features of vibrational spectra which have been overlooked so
far. We furthermore discuss the consequences of approximate inversion symmetry
as well as the role played by Viral Tiling Theory in the study of virus capsid
vibrations.


  Given two holomorphic functions $f$ and $g$ defined in two respective germs
of complex analytic manifolds $(X,x)$ and $(Y,y)$, we know thanks to M. Saito
that, as long as one of them is Euler homogeneous, the reduced (or microlocal)
Bernstein-Sato polynomial of the Thom-Sebastiani sum $f+g$ can be expressed in
terms of those of $f$ and $g$. In this note we give a purely algebraic proof of
a similar relation between the whole functional equations that can be applied
to any setting (not necessarily analytic) in which Bernstein-Sato polynomials
can be defined.


  The effects of real-world events on the dynamics and sentiment expressed
through online conversations is not entirely understood. In particular, the
dynamics of highly polarized communities, deeply invested in the outcome of a
particular event naturally tend to have a contrasting emotional sensitivity to
exogenous events. In this study, we analyze Twitter conversations during the
Mexico vs Germany group match of the 2018 FIFA World Cup, and investigate the
effect of the live game outcomes on the conversation dynamics and sentiment. We
find that the exogenous events influence conversation volume and virality less,
while having high influence on user responsiveness. Interestingly, we observe a
shift in the influence that exogenous events have on fans immediately following
the only goal scored in the game. The emotional resilience of fans of the
advantaged team increased following this exogenous shock. In contrast, the
sentiment of the disadvantaged team was left more susceptible to further
exogenous events following the exogenous shock. These results support the fact
that user engagement and emotional resilience of an online population holding
highly polarized stances can be manipulated through an exogenous event of high
importance.


  We present a next-to-next-to-leading order (NNLO) global QCD analysis of the
proton's helicity parton distribution functions (PDFs), the first of its kind.
To obtain the distributions, we use data for longitudinal spin asymmetries in
inclusive and semi-inclusive lepton-nucleon scattering as well as in weak-boson
and hadron or jet production in proton-proton scattering. We analyze the data
using QCD perturbation theory at NNLO accuracy, employing approximations
provided by the threshold resummation formalism in cases where full NNLO
results for partonic hard-scattering functions are not readily available. Our
numerical results suggest a remarkable perturbative stability of the extracted
helicity PDFs.


  We study the interface between Regge behavior and DGLAP evolution in a
non-perturbative model for the nucleon structure function based on a multipole
pomeron exchange. This model provides the input for a subsequent DGLAP
evolution that we calculate numerically. The soft input and its evolution give
a good fit to the experimental data in the whole available range of x and Q^2.


  The atomically precise method has become an important technique to adjust the
core of thiolate-protected gold nanoclusters to improve physical and chemical
properties. But the doping effect on the structural stability has not been
systematically summarized. In this work, the H2S-nanoalloy molecules with
different doping metal atoms has been investigated to elucidate the impact of
the dopant on the structures. With DFT simulation results, the zinc group atoms
as dopants may be influenced by surrounded gold atoms and the binding of the
thiolate units are enhanced. The simulated zinc group data when combined to the
gold group and plantinum group data can be summarized in the perspective of
balance between the ligand-core binding and core cohesive energies. Most of
dopants drive the modeled nanoclusters away from the balance especially when
the metal atom replaced the gold atom in gold-sulfur bindings. But when cores
of the nanoclusters are dominated by gold atoms, the dopants may achieve
"saturation" such that the balance in the doped clusters may be corrected. This
work provide a simple profile to understand the internal shift of the structure
introduced by the atomically precise method.


  We report on the experimental demonstration of light dragging effect due to
atomic motion in a rubidium vapor cell. We found that the minimum group
velocity is achieved for light red-shifted from the center of the atomic
resonance, and that the value of this shift increases with decreasing group
velocity, in agreement with the theoretical predictions by Kocharovskaya,
Rostovtsev, and Scully [Phys. Rev. Lett. {\bf 86}, 628 (2001)].


  The adversarial patch attack aims to fool image classifiers within a bounded,
contiguous region of arbitrary changes, posing a real threat to computer vision
systems (e.g., autonomous driving, content moderation, biometric
authentication, medical imaging) in the physical world. To address this problem
in a trustworthy way, proposals have been made for certified patch defenses
that ensure the robustness of classification models and prevent future patch
attacks from breaching the defense. State-of-the-art certified defenses can be
compatible with any model architecture, as well as achieve high clean and
certified accuracy. Although the methods are adaptive to arbitrary patch
positions, they inevitably need to access the size of the adversarial patch,
which is unreasonable and impractical in real-world attack scenarios. To
improve the feasibility of the architecture-agnostic certified defense in a
black-box setting (i.e., position and size of the patch are both unknown), we
propose a novel two-stage Iterative Black-box Certified Defense method, termed
IBCD.In the first stage, it estimates the patch size in a search-based manner
by evaluating the size relationship between the patch and mask with pixel
masking. In the second stage, the accuracy results are calculated by the
existing white-box certified defense methods with the estimated patch size. The
experiments conducted on two popular model architectures and two datasets
verify the effectiveness and efficiency of IBCD.


  We study the family of holomorphic maps from the polydisk to the disk which
restrict to the identity on the diagonal. In particular, we analyze the
asymptotics of the orbit of such a map under the conjugation action of a
unipotent subgroup of $\text{PSL}_2(\mathbb{R})$. We discuss an application our
results to the study of the Caratheodory metric on Teichmuller space.


  Recent experiments on imbalanced Fermi gases have raised interest in the
physics of an impurity immersed in a Fermi sea, the so-called Fermi polaron. In
this letter, a simple theory is devised to describe dilute Fermi-polaron
ensembles corresponding to the normal phase of an imbalanced Fermi gas. An
exact formula is obtained for the dominant interaction between polarons,
expressed solely in terms of a single polaron parameter. The physics of this
interaction is identified as a signature of the Pauli exclusion principle.


  We study theoretically the mixed state properties of a strong
uniaxially-anisotropic type II superconductor with the Pauli paramagnetic
effect, focusing on their behaviors when the magnetic field orientation is
tilted from the conduction layer ab plane. On the basis of Eilenberger theory,
we quantitatively estimate significant contributions of the Pauli paramagnetic
effects on a variety of physical observables, including transverse and
longitudinal components of the flux line lattice form factors, magnetization
curves, Sommerfeld coefficient, field distributions and magnetic torques. We
apply these studies to Sr_2_RuO_4_ and quantitatively explain several seemingly
curious behaviors, including the H_c2_ suppression for the ab plane direction,
the larger anisotropy ratio and intensity found by the spin-flip small angle
neutron scattering, and the first order transition observed recently in
magneto-caloric, specific heat and magnetization measurements in a coherent and
consistent manner. Those lead us to conclude that Sr_2_RuO_4_ is either a
spin-singlet or a spin-triplet pairing with the d-vector components in the ab
plane.


  LSB method is one of the well-known steganography methods which hides the
message bits into the least significant bit of pixel values. This method
changes the statistical information of images, which causes to have an
unsecured channel. To increase the security of this method against the
steganalysis methods, in this paper an adaptive method for hiding data into
images will be proposed. So, the amount of data and the method which is used
for hiding data in each area of image will be different. Experimental results
show that the security of the proposed method is higher than general LSB method
and in some cases the capacity of the carrier signal is increased.


  Fluid mixing usually involves the interplay between advection and diffusion,
which together cause any initial distribution of passive scalar to homogenize
and ultimately reach a uniform state. However, this scenario only holds when
the velocity field is nondivergent and has no normal component to the boundary.
If either condition is unmet, such as for active particles in a bounded region,
floating particles, or for filters, then the ultimate state after a long time
is not uniform, and may be time dependent. We show that in those cases of
nonuniform mixing it is preferable to characterize the degree of mixing in
terms of an f-divergence, which is a generalization of relative entropy, or to
use the $L^1$ norm. Unlike concentration variance ($L^2$ norm), the
f-divergence and $L^1$ norm always decay monotonically, even for nonuniform
mixing, which facilitates measuring the rate of mixing. We show by an example
that flows that mix well for the nonuniform case can be drastically different
from efficient uniformly mixing flows.


  We study semi-classical limits of eigenfunctions of a quantized linear
hyperbolic automorphism of the torus ("cat map"). For some values of Planck's
constant, the spectrum of the quantized map has large degeneracies. Our first
goal in this paper is to show that these degeneracies are coupled to the
existence of quantum symmetries. There is a commutative group of unitary
operators on the state-space which commute with the quantized map and therefore
act on its eigenspaces. We call these "Hecke operators", in analogy with the
setting of the modular surface.
  We call the eigenstates of both the quantized map and of all the Hecke
operators "Hecke eigenfunctions". Our second goal is to study the semiclassical
limit of the Hecke eigenfunctions. We will show that they become
equidistributed with respect to Liouville measure, that is the expectation
values of quantum observables in these eigenstates converge to the classical
phase-space average of the observable.


  We derive a manifestly gauge invariant low energy blocked action for
Yang-Mills theory using operator cutoff regularization, a prescription which
renders the theory finite with a regulating smearing function constructed for
the proper-time integration. By embedding the momentum cutoff scales in the
smearing function, operator cutoff formalism allows for a direct application of
Wilson-Kadanoff renormalization group to Yang-Mills theory in a completely
gauge symmetry preserving manner. In particular, we obtain a renormalization
group flow equation which takes into consideration the contributions of higher
dimensional operators and provides a systematic way of exploring the influence
of these operators as the strong coupling, infrared limit is approached.


  With the growing importance of corporate viral marketing campaigns on online
social networks, the interest in studies of influence propagation through
networks is higher than ever. In a viral marketing campaign, a firm initially
targets a small set of pioneers and hopes that they would influence a sizeable
fraction of the population by diffusion of influence through the network. In
general, any marketing campaign might fail to go viral in the first try. As
such, it would be useful to have some guide to evaluate the effectiveness of
the campaign and judge whether it is worthy of further resources, and in case
the campaign has potential, how to hit upon a good pioneer who can make the
campaign go viral. In this paper, we present a diffusion model developed by
enriching the generalized random graph (a.k.a. configuration model) to provide
insight into these questions. We offer the intuition behind the results on this
model, rigorously proved in Blaszczyszyn & Gaurav(2013), and illustrate them
here by taking examples of random networks having prototypical degree
distributions - Poisson degree distribution, which is commonly used as a kind
of benchmark, and Power Law degree distribution, which is normally used to
approximate the real-world networks. On these networks, the members are assumed
to have varying attitudes towards propagating the information. We analyze three
cases, in particular - (1) Bernoulli transmissions, when a member influences
each of its friend with probability p; (2) Node percolation, when a member
influences all its friends with probability p and none with probability 1-p;
(3) Coupon-collector transmissions, when a member randomly selects one of his
friends K times with replacement. We assume that the configuration model is the
closest approximation of a large online social network, when the information
available about the network is very limited. The key insight offered by this
study from a firm's perspective is regarding how to evaluate the effectiveness
of a marketing campaign and do cost-benefit analysis by collecting relevant
statistical data from the pioneers it selects. The campaign evaluation
criterion is informed by the observation that if the parameters of the
underlying network and the campaign effectiveness are such that the campaign
can indeed reach a significant fraction of the population, then the set of good
pioneers also forms a significant fraction of the population. Therefore, in
such a case, the firms can even adopt the naive strategy of repeatedly picking
and targeting some number of pioneers at random from the population. With this
strategy, the probability of them picking a good pioneer will increase
geometrically fast with the number of tries.


  The multivariate resultant is a fundamental tool of computational algebraic
geometry. It can in particular be used to decide whether a system of n
homogeneous equations in n variables is satisfiable (the resultant is a
polynomial in the system's coefficients which vanishes if and only if the
system is satisfiable). In this paper we present several NP-hardness results
for testing whether a multivariate resultant vanishes, or equivalently for
deciding whether a square system of homogeneous equations is satisfiable. Our
main result is that testing the resultant for zero is NP-hard under
deterministic reductions in any characteristic, for systems of low-degree
polynomials with coefficients in the ground field (rather than in an
extension). We also observe that in characteristic zero, this problem is in the
Arthur-Merlin class AM if the generalized Riemann hypothesis holds true. In
positive characteristic, the best upper bound remains PSPACE.


  We calculate the density of states in the half-filled Hubbard model on a
Bethe lattice with infinite connectivity. Based on our analytical results to
second order in $t/U$, we propose a new `Fixed-Energy Exact Diagonalization'
scheme for the numerical study of the Dynamical Mean-Field Theory. Corroborated
by results from the Random Dispersion Approximation, we find that the gap opens
at $U_{\rm c}=4.43 \pm 0.05$. Moreover, the density of states near the gap
increases algebraically as a function of frequency with an exponent
$\alpha=1/2$ in the insulating phase. We critically examine other analytical
and numerical approaches and specify their merits and limitations when applied
to the Mott--Hubbard insulator.


  The magnetar SGR 1935+2154 is reported to have an anti-glitch, accompanied by
fast radio bursts, and transient pulsed radio emission. In the wind braking
model, this triplet event tells people that (1) SGR 1935+2154 does not have a
strong particle wind and can be approximated by magnetic dipole braking in the
persistent state; (2) Its anti-glitch is due to an enhanced particle wind,
similar to the first anti-glitch in magnetars; (3) Its transient pulsed radio
emission may be due to a decreasing emission beam during the outburst; (4) The
enhanced particle acceleration potential and pulsar death line may not be the
dominate factor.


  Large-scale power outages caused by extreme weather events are one of the
major factors weakening grid resilience. In order to prevent the critical
infrastructure from cascading failure, power lines are often proactively
de-energized under the threat of a progressing wildfire. In this context, the
potential of microgrid (MG) functioning in islanded mode can be exploited to
enhance the resiliency of the power grid. However, there are numerous
uncertainties originating from these types of events and an accurate modeling
of the MG is required to harness its full potential. In this paper, we consider
the uncertainty in line outages depending on fire propagation and reduced solar
power generation due to the particulate matter in wildfire smoke. We formulate
a two-stage stochastic MG optimal power flow problem by utilizing a
second-order cone relaxation of the DistFlow model. Leveraging an effective
approximation of the resistive heat gain, we separate the complicating
constraints of dynamic line rating from the resulting optimization problem.
Extensive simulation results corroborate the merits of our proposed framework,
which is tested on a modified IEEE 22-bus system.


  We investigate the soliton dynamics for the Schrodinger-Newton system by
proving a suitable modulational stability estimates in the spirit of those
obtained by Weinstein for local equations.


  The two-dimensional cluster state, a universal resource for measurement-based
quantum computation, is also the gapped ground state of a short-ranged
Hamiltonian. Here, we examine the effect of perturbations to this Hamiltonian.
We prove that, provided the perturbation is sufficiently small and respects a
certain symmetry, the perturbed ground state remains a universal resource. We
do this by characterising the operation of an adaptive measurement protocol
throughout a suitable symmetry-protected quantum phase, relying on generic
properties of the phase rather than any analytic control over the ground state.


  We present new measurements of the temperature-density (T-rho) relation for
neutral hydrogen in the 2.0 < z < 2.8 intergalactic medium (IGM) using a sample
of ~6000 individual HI absorbers fitted with Voigt profiles constrained in all
cases by multiple Lyman series transitions. We find model independent evidence
for a positive correlation between the column density of HI (NHI) and the
minimum observed velocity width of absorbers (bmin). With minimal
interpretation, this implies that the temperature-density relation in the IGM
is not "inverted", contrary to many recent studies. Fitting bmin as a function
of NHI results in line width - column density dependence of the form bdmin =
b_0 [NHI/N_(HI,0)]^(Gamma-1) with a minimum line width at mean density rhobar
[N_(HI, 0) = 10^13.6 cm^-2] of b_0 = 17.9 +- 0.2 km/s and a power-law index of
(Gamma-1) = 0.15 +- 0.02. Using analytic arguments, these measurements imply an
"equation of state" for the IGM at <z>= 2.4 of the form T = T_0
(rho/rhobar)^(gamma-1) with a temperature at mean density of T_0 = (1.94 +-
0.05) x 10^4 K and a power-law index (gamma -1) = 0.46 +- 0.05.


  Integrated photonics is a leading platform for quantum technologies including
nonclassical state generation \cite{Vergyris:2016-35975:SRP,
Solntsev:2014-31007:PRX, Silverstone:2014-104:NPHOT, Solntsev:2016:RPH},
demonstration of quantum computational complexity \cite{Lamitral_NJP2016} and
secure quantum communications \cite{Zhang:2014-130501:PRL}. As photonic
circuits grow in complexity, full quantum tomography becomes impractical, and
therefore an efficient method for their characterization
\cite{Lobino:2008-563:SCI, Rahimi-Keshari:2011-13006:NJP} is essential. Here we
propose and demonstrate a fast, reliable method for reconstructing the
two-photon state produced by an arbitrary quadratically nonlinear optical
circuit. By establishing a rigorous correspondence between the generated
quantum state and classical sum-frequency generation measurements from laser
light, we overcome the limitations of previous approaches for lossy multimode
devices \cite{Liscidini:2013-193602:PRL, Helt:2015-1460:OL}. We applied this
protocol to a multi-channel nonlinear waveguide network, and measured a
99.28$\pm$0.31\% fidelity between classical and quantum characterization. This
technique enables fast and precise evaluation of nonlinear quantum photonic
networks, a crucial step towards complex, large-scale, device production.


  3D-aware image synthesis encompasses a variety of tasks, such as scene
generation and novel view synthesis from images. Despite numerous task-specific
methods, developing a comprehensive model remains challenging. In this paper,
we present SSDNeRF, a unified approach that employs an expressive diffusion
model to learn a generalizable prior of neural radiance fields (NeRF) from
multi-view images of diverse objects. Previous studies have used two-stage
approaches that rely on pretrained NeRFs as real data to train diffusion
models. In contrast, we propose a new single-stage training paradigm with an
end-to-end objective that jointly optimizes a NeRF auto-decoder and a latent
diffusion model, enabling simultaneous 3D reconstruction and prior learning,
even from sparsely available views. At test time, we can directly sample the
diffusion prior for unconditional generation, or combine it with arbitrary
observations of unseen objects for NeRF reconstruction. SSDNeRF demonstrates
robust results comparable to or better than leading task-specific methods in
unconditional generation and single/sparse-view 3D reconstruction.


  We consider a class of iterative numerical methods and introduce the notion
of semiglobally, practically, strictly pseudogradient (SPSP) search directions.
We demonstrate the relevance of the SPSP property in modelling a variety of
optimization algorithms, including those subject to absolute and relative
errors. We show that the attractors of iterative methods with SPSP search
directions exhibit semiglobal, practical, asymptotic stability. Moreover, the
SPSP property is robust in the sense that perturbations of SPSP search
directions also have the SPSP property.


  We consider weakly interacting bosonic gases with local and non-local
multi-body interactions. By using the Bogoliubov approximation, we first
investigate contact interactions, studying the case in which the interparticle
potential can be written as a sum of N-body {\delta}-interactions, and then
considering general contact potentials. Results for the quasi-particle spectrum
and the stability are presented. We then examine non-local interactions,
focusing on two different cases of 3-body non-local interactions. Our results
are used for systems with 2- and 3-body {\delta}-interactions and applied for
realistic values of the trap parameters. Finally, the effect of conservative
3-body terms in dipolar systems and soft-core potentials (that can be simulated
with Rydberg dressed atoms) is also studied.


  This is a version (less professional editing, more details and jokes) of an
APS Physics Viewpoint about three recent papers extending charge-vortex duality
to fermionic vortices.


  In high-Tc cuprates, the orbital magnetoresistance in plane (MR,
$\Delta\rho/\rho$) is anomalously enhanced at lower tempemeratures compared
with conventional Fermi liquids, and thus Kohler's rule is strongly violated.
Moreover, it should be noted that an intimate relation between the MR and the
Hall coefficient ($R_H$), $\Delta\rho/\rho \propto (R_H/\rho)^2$, holds well
experimentally, and is called the "modified Kohler's rule". In this letter, we
study this long-standing problem in terms of the nearly antiferromagnetic (AF)
Fermi liquid. We analyze the exact expression for the MR by including the
vertex corrections (VC's) to keep the conservation laws, and find the
approximate "scaling relation" $\Delta\rho/\rho \propto \xi_{AF}^4 /\rho^2$
($\xi_{AF}$ being the AF correlation length.) in the presence of AF
fluctuations. The factor $\xi_{AF}^4$, which comes from the VC's for the
current, gives the additional temperature dependence. By taking account of the
relation $R_H \propto \xi_{AF}^2$ [Kontani et al., PRB 59 (1999) 14723.], we
can naturally explain the modified Kohler's rule. In conclusion, based on the
Fermi liquid theory, the famous {\it seemingly} non-Fermi liquid behaviors of
the Hall coefficient and the MR in high-Tc cuprates are naturally understood on
an equal footing.


  We consider an independent and identically distributed (i.i.d.) random
dynamical system of simple linear transformations on the unit interval
$T_{\beta}(x)=\beta x$ (mod $1$), $x\in[0,1]$, $\beta>0$, which are the
so-called beta-transformations. For such a random dynamical system, including
the case that it is generated by uncountably many maps, we give an explicit
formula for the density function of a unique stationary measure under the
assumption that the random dynamics is expanding in mean. As an application, in
the case that the random dynamics is generated by finitely many maps and the
maps are chosen according to a Bernoulli measure, we show that the density
function is analytic as a function of parameter in the Bernoulli measure and
give its derivative explicitly. Furthermore, for a non-i.i.d. random dynamical
system of beta-transformations, we also give an explicit formula for the random
densities of a unique absolutely continuous invariant measure under a certain
strong expanding condition or under the assumption that the maps randomly
chosen are close to the beta-transformation for a non-simple number in the
sense of parameter $\beta$.


  Starting from the Dirac equation, the relativistic quantum hydrodynamic
equations for Dirac electrons on a surface of a three dimensional-topological
insulator (TI) are derived and numerically solved to study the spin plasmons.
The surface of the TI is modulated by a perpendicular magnetic field and a
pulsed exchange field provided by an array of ferromagnetic insulating (FI)
stripes. The collective density and velocity oscillations in the
two-dimensional Dirac electron gas are simulated and analyzed. It is shown that
in spin plasmons, the collective electron density and momentum are modulated by
the spin state. Direct experimental observations of such oscillations are
possible at laboratory conditions.


  We study the influence of an additional scalar potential on various geometric
and analytic properties of Dirac-harmonic maps. We will create a mathematical
wish list of the possible benefits from inducing the potential term and point
out that the latter cannot be achieved in general. Finally, we focus on several
potentials that are motivated from supersymmetric quantum field theory.


  For every set of parabolic weights, we construct a Harder-Narasimhan
stratification for the moduli stack of parabolic vector bundles on a curve. It
is based on the notion of parabolic slope, introduced by Mehta and Seshadri. We
also prove that the stratification is schematic, that each stratum is complete,
and establish an analogue of Behrend's conjecture for parabolic vector bundles.
A comparison with recent $\Theta$-stratification approaches is discussed.


  In cloud computing environment, load balancing is a key issue which is
required to distribute the dynamic workload over multiple machines to make
certain that no single machine is overloaded. In recent research, many
organizations lose significant part of their revenues in handling the requests
given by the clients over the web servers i.e. unable to balance the load for
web servers which results in loss of data, delay in time and increased costs.
Various static and dynamic algorithms have been proposed and implemented in the
past but this have not been fully efficient for load balancing. This gave room
to hybrid algorithms. Hybrid methods inherit the properties from both static
and dynamic load balancing techniques and attempts at overcoming the limitation
of both algorithms. This paper is a study of various hybrid load balancing
algorithms in cloud computing environment.


  By using a different quantum-to-classical mapping from the Trotter-Suzuki
decomposition, we identify the entanglement structure of the maximal
eigenvectors for the associated quantum transfer matrix. This observation
provides a deeper insight into the problem of linear growth of the entanglement
entropy in time evolution using conventional methods. Based on this
observation, we propose a general method for arbitrary temperatures using the
biorthonormal transfer-matrix renormalization group. Our method exhibits a
competitive accuracy with a much cheaper computational cost in comparison with
two recent proposed methods for long-time dynamics based on a folding algorithm
[Phys. Rev. Lett. 102, 240603 (2009)] and a modified time-dependent
density-matrix renormalization group [Phys. Rev. Lett. 108, 227206 (2012)].


  The concurrent refinement algebra has been developed to support
rely/guarantee reasoning about concurrent programs. The algebra supports atomic
commands and defines parallel composition as a synchronous operation, as in
Milner's SCCS. In order to allow specifications to be combined, the algebra
also provides a weak conjunction operation, which is also a synchronous
operation that shares many properties with parallel composition. The three main
operations, sequential composition, parallel composition and weak conjunction,
all respect a (weak) quantale structure over a lattice of commands. Further
structure involves combinations of pairs of these operations:
sequential/parallel, sequential/weak conjunction and parallel/weak conjunction,
each pair satisfying a weak interchange law similar to Concurrent Kleene
Algebra. Each of these pairs satisfies a common biquantale structure.
Additional structure is added via compatible sets of commands, including tests,
atomic commands and pseudo-atomic commands. These allow stronger (equality)
interchange and distributive laws. This paper describes the result of
restructuring the algebra to better exploit these commonalities. The algebra is
implemented in Isabelle/HOL.


  In this paper, we prove that the double inequality \begin{equation*} 1+\alpha
r'^2<\frac{\mathcal{K}_{a}(r)}{\sin(\pi a)\log(e^{R(a)/2}/r')}<1+\beta r'^2
\end{equation*} holds for all $a\in (0, 1/2]$ and $r\in (0, 1)$ if and only if
$\alpha\leq \pi/[R(a)\sin(\pi a)]-1$ and $\beta\geq a(1-a)$, where
$r'=\sqrt{1-r^2}$, $\mathcal{K}_{a}(r)$ is the generalized elliptic integral of
the first kind and $R(x)$ is the Ramanujan constant function. Besides, as the
key tool, the series expression for the Ramanujan constant function $R(x)$ is
given.


  We investigate student comfort with the material in an upper-division
spins-first quantum mechanics course. Pre-lecture surveys probing students'
comfort were administered weekly, in which students assigned themselves a
"discomfort level" on a scale of 0--10 and provided a written explanation for
their choice. The weekly class-wide average discomfort level was effectively
constant over the semester, suggesting that the class found no single unit
especially jarring nor especially easy. Student written responses were coded
according to their reported source of discomfort---math, math-physics
connection, physics, and notation. The relative prevalence of these categories
varied significantly over the semester, indicating that students find that
different units present different challenges, and also that some of these
challenges fade in importance as the semester progresses. Semi-structured
interviews with students in a similar quantum mechanics course at a different
institution provided additional context and insight into these results.


  Object categorization is a hot issue of an image mining. Contextual
information between objects is one of the important semantic knowledge of an
image. However, the previous researches for an object categorization have not
made full use of the contextual information, especially the spatial relations
between objects. In addition, the object categorization methods, which
generally use the probabilistic graphical models to implement the incorporation
of contextual information with appearance of objects, are almost inevitable to
evaluate the intractable partition function for normalization. In this work, we
introduced fully-connected fuzzy spatial relations including directional,
distance and topological relations between object regions, so the spatial
relational information could be fully utilized. Then, the spatial relations
were considered as well as co-occurrence and appearance of objects by using
energy-based model, where the energy function was defined as the region-object
association potential and the configuration potential of objects. Minimizing
the energy function of whole image arrangement, we obtained the optimal label
set about the image regions and addressed the evaluation of intractable
partition function in conditional random fields. Experimental results show the
validity and reliability of this proposed method.


  Photoassociation and the Feshbach resonance are, in principle, feasible means
for creating a molecular Bose-Einstein condensate from an
already-quantum-degenerate gas of atoms; however, mean-field shifts and
irreversible decay place practical constraints on the efficient delivery of
stable molecules using either mechanism alone. We therefore propose
Feshbach-stimulated Raman photoproduction, i.e., a combination of magnetic and
optical methods, as a viable means to collectively convert degenerate atoms
into a stable molecular condensate with near-unit efficiency.


  The observation of coherent elastic neutrino nucleus scattering has opened
the window to many physics opportunities. This process has been measured by the
COHERENT Collaboration using two different targets, first CsI and then argon.
Recently, the COHERENT Collaboration has updated the CsI data analysis with a
higher statistics and an improved understanding of systematics. Here we perform
a detailed statistical analysis of the full CsI data and combine it with the
previous argon result. We discuss a vast array of implications, from tests of
the Standard Model to new physics probes. In our analyses we take into account
experimental uncertainties associated to the efficiency as well as the timing
distribution of neutrino fluxes, making our results rather robust. In
particular, we update previous measurements of the weak mixing angle and the
neutron root mean square charge radius for CsI and argon. We also update the
constraints on new physics scenarios including neutrino nonstandard
interactions and the most general case of neutrino generalized interactions, as
well as the possibility of light mediators. Finally, constraints on neutrino
electromagnetic properties are also examined, including the conversion to
sterile neutrino states. In many cases, the inclusion of the recent CsI data
leads to a dramatic improvement of bounds.


  Open attribute value extraction for emerging entities is an important but
challenging task. A lot of previous works formulate the problem as a
\textit{question-answering} (QA) task. While the collections of articles from
web corpus provide updated information about the emerging entities, the
retrieved texts can be noisy, irrelevant, thus leading to inaccurate answers.
Effectively filtering out noisy articles as well as bad answers is the key to
improving extraction accuracy. Knowledge graph (KG), which contains rich, well
organized information about entities, provides a good resource to address the
challenge. In this work, we propose a knowledge-guided reinforcement learning
(RL) framework for open attribute value extraction. Informed by relevant
knowledge in KG, we trained a deep Q-network to sequentially compare extracted
answers to improve extraction accuracy. The proposed framework is applicable to
different information extraction system. Our experimental results show that our
method outperforms the baselines by 16.5 - 27.8\%.


  Blind quantum computation (BQC) allows that a client who has limited quantum
abilities can delegate quantum computation to a server who has advanced quantum
technologies but learns nothing about the client's private information.
However, it still remains a challenge to directly encrypt quantum algorithms in
circuits model. To solve the problem, we propose GTUBQC, the first gate
teleportation-based universal BQC protocol. In this paper, we consider a
scenario where a trusted center is responsible for preparing initial states, a
client with the ability to perform X, Z does not require any quantum memory,
and two servers conducting UBQC (universal BQC) and Bell measurements. GTUBQC
can hide the universal quantum gates by encrypting the rotation angles, because
arbitrary unitary operation can be decomposed into a combination of arbitrary
rotation operators. We prove the blindness and correctness of GTUBQC, and apply
our approach to other types of computational tasks, such as quantum Fourier
transform.


  From a general model of the Mn oxides R_{1-x}A_{x}MnO_3, we derive an
effective Hamiltonian in the low-energy subspace using the projection operator
method, in which a novel coupling between the spin and orbital degrees of
freedom is included. A phase diagram for temperature T versus doping
concentration x is computed by means of Monte Carlo simulation. Our result is
consistent with experimental observations in the Mn oxides with relatively wide
conduction band, such as Pr_{1-x}Sr_{x} MnO_{3} and La_{1-x}Sr_{x}MnO_{3}.
According to the obtained orbital ordering, we also predict that the motion of
charge carriers transforms from three-dimensional to two-dimensional as x is
increased beyond a critical value.


  We study the Renyi entanglement entropies of two disjoint intervals in XY
chains. We exploit the exact solution of the model in terms of free Majorana
fermions and we show how to construct the reduced density matrix in the spin
variables by taking properly into account the Jordan-Wigner string between the
two blocks. From this we can evaluate any Renyi entropy of finite integer
order. We study in details critical XX and Ising chains and we show that the
asymptotic results for large blocks agree with recent conformal field theory
predictions if corrections to the scaling are included in the analysis
correctly. We also report results in the gapped phase and after a quantum
quench.


  We employ an effective kinetic description, based on the Boltzmann equation
in the relaxation time approximation, to study the space-time dynamics and
development of transverse flow of small and large collision systems. By
combining analytical insights in the small opacity limit with numerical
simulations at larger opacities, we are able to describe the development of
transverse flow from very small to very large opacities. Suprisingly, we find
that deviations between kinetic theory and hydrodynamics persist even in the
limit of very large opacities, which can be attributed to the presence of the
early pre-equilibrium phase.


  Information diffusion, spreading of infectious diseases, and spreading of
rumors are fundamental processes occurring in real-life networks. In many
practical cases, one can observe when nodes become infected, but the underlying
network, over which a contagion or information propagates, is hidden. Inferring
properties of the underlying network is important since these properties can be
used for constraining infections, forecasting, viral marketing, and so on.
Moreover, for many applications, it is sufficient to recover only coarse
high-level properties of this network rather than all its edges. This article
conducts a systematic and extensive analysis of the following problem: Given
only the infection times, find communities of highly interconnected nodes. This
task significantly differs from the well-studied community detection problem
since we do not observe a graph to be clustered. We carry out a thorough
comparison between existing and new approaches on several large datasets and
cover methodological challenges specific to this problem. One of the main
conclusions is that the most stable performance and the most significant
improvement on the current state-of-the-art are achieved by our proposed simple
heuristic approaches agnostic to a particular graph structure and epidemic
model. We also show that some well-known community detection algorithms can be
enhanced by including edge weights based on the cascade data.


  Motivated by the embedding problem of canonical models in small codimension,
we extend Severi's double point formula to the case of surfaces with rational
double points, and we give more general double point formulae for varieties
with isolated singularities.
  A concrete application is for surfaces with geometric genus $p_g=5$: the
canonical model is embedded in $\mathbb{P}^4$ if and only if we have a complete
intersection of type $(2,4)$ or $(3,3)$.


  The lifetimes of doubly charmed hadrons are analyzed within the framework of
the heavy quark expansion (HQE). Lifetime differences arise from spectator
effects such as $W$-exchange and Pauli interference. The $\Xi_{cc}^{++}$ baryon
is longest-lived in the doubly charmed baryon system owing to the destructive
Pauli interference absent in the $\Xi_{cc}^+$ and $\Omega_{cc}^+$. In the
presence of dimension-7 contributions, its lifetime is reduced from
$\sim5.2\times 10^{-13}s$ to $\sim3.0\times 10^{-13}s$. The $\Xi_{cc}^{+}$
baryon has the shortest lifetime of order $0.45\times 10^{-13}s$ due to a large
contribution from the $W$-exchange box diagram. It is difficult to make a
precise quantitative statement on the lifetime of $\Omega_{cc}^+$. Contrary to
$\Xi_{cc}$ baryons, $\tau(\Omega_{cc}^+)$ becomes longer in the presence of
dimension-7 effects and the Pauli interference $\Gamma^{\rm int}_+$ even
becomes negative. This implies that the subleading corrections are too large to
justify the validity of the HQE. Demanding the rate $\Gamma^{\rm int}_+$ to be
positive for a sensible HQE, we conjecture that the $\Omega_c^0$ lifetime lies
in the range of $(0.75\sim 1.80)\times 10^{-13}s$. The lifetime hierarchy
pattern is $\tau(\Xi_{cc}^{++})>\tau(\Omega_{cc}^+)>\tau(\Xi_{cc}^+)$ and the
lifetime ratio $\tau(\Xi_{cc}^{++})/\tau(\Xi_{cc}^+)$ is predicted to be of
order 6.7.


  We show that the problem of determining the existence of an inductive
invariant in the language of quantifier free linear integer arithmetic (QFLIA)
is undecidable, even for transition systems and safety properties expressed in
QFLIA.


  We study simultaneous collisions of two, three, and four kinks and antikinks
of the $\phi^6$ model at the same spatial point. Unlike the $\phi^4$ kinks, the
$\phi^6$ kinks are asymmetric and this enriches the variety of the collision
scenarios. In our numerical simulations we observe both reflection and bound
state formation depending on the number of kinks and on their spatial ordering
in the initial configuration. We also analyze the extreme values of the energy
densities and the field gradient observed during the collisions. Our results
suggest that very high energy densities can be produced in multi-kink
collisions in a controllable manner. Appearance of high energy density spots in
multi-kink collisions can be important in various physical applications of the
Klein-Gordon model.


  The rare decays $B^+\to K^+ \mu\bar \mu$ and $B^0\to K^{*0} \mu\bar\mu$
provide the strongest constraints on the mixing of a light scalar with the
Higgs boson for GeV-scale masses. The constraints sensitively depend on the
branching ratio to muons. Additional decay channels like an invisible partial
width may substantially weaken the constraints. This scenario will be probed at
Belle II in $B\to K^{(*)} + \mathrm{inv}$. We illustrate the complementarity of
scalar decays to muons and invisible decays using the currently available
results of LHCb and BaBar. We provide two simple model realisations providing a
sizeable invisible scalar width, one based on a real scalar and one based on a
$U(1)_{B-L}$ gauge symmetry. In both examples the scalar decays into heavy
neutral leptons which can be motivated by the seesaw mechanism for neutrino
masses.


  The transferability of deep neural networks (DNNs) has made significant
progress in image and language processing. However, due to the heterogeneity
among tables, such DNN bonus is still far from being well exploited on tabular
data prediction (e.g., regression or classification tasks). Condensing
knowledge from diverse domains, language models (LMs) possess the capability to
comprehend feature names from various tables, potentially serving as versatile
learners in transferring knowledge across distinct tables and diverse
prediction tasks, but their discrete text representation space is inherently
incompatible with numerical feature values in tables. In this paper, we present
TP-BERTa, a specifically pre-trained LM for tabular data prediction.
Concretely, a novel relative magnitude tokenization converts scalar numerical
feature values to finely discrete, high-dimensional tokens, and an
intra-feature attention approach integrates feature values with the
corresponding feature names. Comprehensive experiments demonstrate that our
pre-trained TP-BERTa leads the performance among tabular DNNs and is
competitive with Gradient Boosted Decision Tree models in typical tabular data
regime.


  Shell-wise orbital slotting in Low Earth Orbit (LEO) can improve space
safety, simplify space traffic coordination and management, and optimize
orbital capacity. This paper describes two methods to generate 2D Lattice
Flower Constellations (2D-LFCs) that are defined with respect to either an
arbitrary degree or an arbitrary degree and order Earth geopotential. By
generating shells that are quasi-periodic and frozen with respect to the Earth
geopotential, it is possible to safely stack shells with vertical separation
distances smaller than the osculating variation in semi-major axis of each
shell or a corresponding Keplerian 2D-LFC propagated under an aspherical
geopotential. This helps mitigate the single inclination per shell requirement
in prior work by admitting more shells for a given orbital volume while
retaining self-safe phasing in each shell. These methods exploit previous work
on the Time Distribution Constellation formulation and designs of closed
2D-LFCs under arbitrary Earth geopotentials using repeating ground track
orbits. Factors that influence the widths and shapes of these frozen shells are
identified. Simplified formulas for estimating shell geometry and thickness are
presented. It is shown that sequencing shells to group similar or ascending
inclinations improves capacity versus arbitrary inclination ordering.


  We study rare radiative leptonic decays $B_{(s)}\to e^+e^-\gamma$ and
$B_{(s)}\to \mu^+\mu^-\gamma$ within relativistic quark model. In addition to
previous analysis we give the estimations of the branching ratios for four
values of the minimal photon energy, which correspond to photon selection
criteria of the Belle and LHCb detectors. We find out that the branching ratios
only slightly change. The highest values corresponding to $E^\gamma_{min}=80
\textrm{MeV}$ are ${\cal B}(\bar B^0_s\to e^+e^-\gamma)=18.5\times10^{-9}$ and
${\cal B}(B^0_s\to \mu^+\mu^-\gamma)=11.9\times10^{-9}$. We present the
distribution of the forward-backward asymmetry.


  When studying multi-body protein complexes, biochemists use computational
tools that can suggest hundreds or thousands of their possible spatial
configurations. However, it is not feasible to experimentally verify more than
only a very small subset of them. In this paper, we propose a novel multiscale
visual drilldown approach that was designed in tight collaboration with
proteomic experts, enabling a systematic exploration of the configuration
space. Our approach takes advantage of the hierarchical structure of the data
-- from the whole ensemble of protein complex configurations to the individual
configurations, their contact interfaces, and the interacting amino acids. Our
new solution is based on interactively linked 2D and 3D views for individual
hierarchy levels and at each level, we offer a set of selection and filtering
operations enabling the user to narrow down the number of configurations that
need to be manually scrutinized. Furthermore, we offer a dedicated filter
interface, which provides the users with an overview of the applied filtering
operations and enables them to examine their impact on the explored ensemble.
This way, we maintain the history of the exploration process and thus enable
the user to return to an earlier point of the exploration. We demonstrate the
effectiveness of our approach on two case studies conducted by collaborating
proteomic experts.


  We investigate the effect of dephasing/decoherence on quantum transport
through open chaotic ballistic conductors in the semiclassical limit of small
Fermi wavelength to system size ratio, $\lambda_F/L << 1$. We use the
trajectory-based semiclassical theory to study a two-terminal chaotic dot with
decoherence originating from:
  (i) an external closed quantum chaotic environment,
  (ii) a classical source of noise,
  (iii) a voltage probe, i.e. an additional current-conserving terminal.
  We focus on the pure dephasing regime, where the coupling to the external
source of dephasing is so weak that it does not induce energy relaxation. In
addition to the universal algebraic suppression of weak localization, we find
an exponential suppression of weak-localization $\propto
\exp[-\tilde{\tau}/\tau_\phi]$, with the dephasing rate $\tau_\phi^{-1}$. The
parameter $\tilde{\tau}$ depends strongly on the source of dephasing. For a
voltage probe, $\tilde{\tau}$ is of order the Ehrenfest time $\propto \ln
[L/\lambda_F ]$. In contrast, for a chaotic environment or a classical source
of noise, it has the correlation length $\xi$ of the coupling/noise potential
replacing the Fermi wavelength $\lambda_F $. We explicitly show that the Fano
factor for shot noise is unaffected by decoherence. We connect these results to
earlier works on dephasing due to electron-electron interactions, and
numerically confirm our findings.


  Compared to agile legged animals, wheeled and tracked vehicles often suffer
large performance loss on granular surfaces like sand and gravel. Understanding
the mechanics of legged locomotion on granular media can aid the development of
legged robots with improved mobility on granular surfaces; however, no general
force model yet exists for granular media to predict ground reaction forces
during complex limb intrusions. Inspired by a recent study of sand-swimming, we
develop a resistive force model in the vertical plane for legged locomotion on
granular media. We divide an intruder of complex morphology and kinematics,
e.g., a bio-inspired robot L-leg rotated through uniform granular media
(loosely packed ~ 1 mm diameter poppy seeds), into small segments, and measure
stresses as a function of depth, orientation, and direction of motion using a
model leg segment. Summation of segmental forces over the intruder predicts the
net forces on both an L-leg and a reversed L-leg rotated through granular media
with better accuracy than using simple one-dimensional penetration and drag
force models. A multi-body dynamic simulation using the resistive force model
predicts the speeds of a small legged robot (15 cm, 150 g) moving on granular
media using both L-legs and reversed L-legs.