  We present a wave-function based method to solve the time-dependent
many-electron Schr\"odinger equation (TDSE) with special emphasis on
strong-field ionization phenomena. The theory builds on the
configuration-interaction (CI) approach supplemented by the
generalized-active-space (GAS) concept from quantum chemistry. The latter
allows for a controllable reduction in the number of configurations in the CI
expansion by imposing restrictions on the active orbital space. The method is
similar to the recently formulated time-dependent restricted-active-space
(TD-RAS) CI method [D. Hochstuhl, and M. Bonitz, Phys. Rev. A 86, 053424
(2012)]. We present details of our implementation and address convergence
properties with respect to the active spaces and the associated account of
electron correlation in both ground state and excitation scenarios. We apply
the TD-GASCI theory to strong-field ionization of polar diatomic molecules and
illustrate how the method allows us to uncover a strong correlation-induced
shift of the preferred direction of emission of photoelectrons.


  Digital images and videos play a very important role in everyday life.
Nowadays, people have access the affordable mobile devices equipped with
advanced integrated cameras and powerful image processing applications.
Technological development facilitates not only the generation of multimedia
content, but also the intentional modification of it, either with recreational
or malicious purposes. This is where forensic techniques to detect manipulation
of images and videos become essential. This paper proposes a forensic technique
by analysing compression algorithms used by the H.264 coding. The presence of
recompression uses information of macroblocks, a characteristic of the
H.264-MPEG4 standard, and motion vectors. A Vector Support Machine is used to
create the model that allows to accurately detect if a video has been
recompressed.


  Anisotropy is a fundamental property of particle interactions. It occupies a
central role in cold and ultra-cold molecular processes, where long range
forces have been found to significantly depend on orientation in ultra-cold
polar molecule collisions. Recent experiments have demonstrated the emergence
of quantum phenomena such as scattering resonances in the cold collisions
regime due to quantization of the intermolecular degrees of freedom. Although
these states have been shown to be sensitive to interaction details, the effect
of anisotropy on quantum resonances has eluded experimental observation so far.
Here, we directly measure the anisotropy in atom-molecule interactions via
quantum resonances by changing the quantum state of the internal molecular
rotor. We observe that a quantum scattering resonance at a collision energy of
$k_B$ x 270 mK appears in the Penning ionization of molecular hydrogen with
metastable helium only if the molecule is rotationally excited. We use state of
the art ab initio and multichannel quantum molecular dynamics calculations to
show that the anisotropy contributes to the effective interaction only for
$H_2$ molecules in the first excited rotational state, whereas rotationally
ground state $H_2$ interacts purely isotropically with metastable helium.
Control over the quantum state of the internal molecular rotation allows us to
switch the anisotropy on or off and thus disentangle the isotropic and
anisotropic parts of the interaction. These quantum phenomena provide a
challenging benchmark for even the most advanced theoretical descriptions,
highlighting the advantage of using cold collisions to advance the microscopic
understanding of particle interactions.


  This paper investigates cross correlation properties of sequences derived
from GH sequences modulo p, where p is a prime number and presents comparison
with cross correlation properties of pseudo noise sequences. For GH sequences
modulo prime, a binary random sequence B(n) is constructed, based on whether
the period is p-1 (or a divisor) or 2p+2 (or a divisor). We show that B(n)
sequences have much less peak cross correlation compared to PN sequence
fragments obtained from the same generator. Potential applications of these
sequences to cryptography are sketched.


  There is increasing realization in neuroscience that information is
represented in the brain, e.g., neocortex, hippocampus, in the form sparse
distributed codes (SDCs), a kind of cell assembly. Two essential questions are:
a) how are such codes formed on the basis of single trials, and how is
similarity preserved during learning, i.e., how do more similar inputs get
mapped to more similar SDCs. I describe a novel Modular Sparse Distributed Code
(MSDC) that provides simple, neurally plausible answers to both questions. An
MSDC coding field (CF) consists of Q WTA competitive modules (CMs), each
comprised of K binary units (analogs of principal cells). The modular nature of
the CF makes possible a single-trial, unsupervised learning algorithm that
approximately preserves similarity and crucially, runs in fixed time, i.e., the
number of steps needed to store an item remains constant as the number of
stored items grows. Further, once items are stored as MSDCs in superposition
and such that their intersection structure reflects input similarity, both
fixed time best-match retrieval and fixed time belief update (updating the
probabilities of all stored items) also become possible. The algorithm's core
principle is simply to add noise into the process of choosing a code, i.e.,
choosing a winner in each CM, which is proportional to the novelty of the
input. This causes the expected intersection of the code for an input, X, with
the code of each previously stored input, Y, to be proportional to the
similarity of X and Y. Results demonstrating these capabilities for spatial
patterns are given in the appendix.


  Self-supervised learning on graphs has recently drawn a lot of attention due
to its independence from labels and its robustness in representation. Current
studies on this topic mainly use static information such as graph structures
but cannot well capture dynamic information such as timestamps of edges.
Realistic graphs are often dynamic, which means the interaction between nodes
occurs at a specific time. This paper proposes a self-supervised dynamic graph
representation learning framework (DySubC), which defines a temporal subgraph
contrastive learning task to simultaneously learn the structural and
evolutional features of a dynamic graph. Specifically, a novel temporal
subgraph sampling strategy is firstly proposed, which takes each node of the
dynamic graph as the central node and uses both neighborhood structures and
edge timestamps to sample the corresponding temporal subgraph. The subgraph
representation function is then designed according to the influence of
neighborhood nodes on the central node after encoding the nodes in each
subgraph. Finally, the structural and temporal contrastive loss are defined to
maximize the mutual information between node representation and temporal
subgraph representation. Experiments on five real-world datasets demonstrate
that (1) DySubC performs better than the related baselines including two graph
contrastive learning models and four dynamic graph representation learning
models in the downstream link prediction task, and (2) the use of temporal
information can not only sample more effective subgraphs, but also learn better
representation by temporal contrastive loss.


  We consider the problem of estimating the mean vector of a p-variate normal
$(\theta,\Sigma)$ distribution under invariant quadratic loss,
$(\delta-\theta)'\Sigma^{-1}(\delta-\theta)$, when the covariance is unknown.
We propose a new class of estimators that dominate the usual estimator
$\delta^0(X)=X$. The proposed estimators of $\theta$ depend upon X and an
independent Wishart matrix S with n degrees of freedom, however, S is singular
almost surely when p>n. The proof of domination involves the development of
some new unbiased estimators of risk for the p>n setting. We also find some
relationships between the amount of domination and the magnitudes of n and p.


  Given a state of light, how do its properties change when only some of the
constituent photons are observed and the rest are neglected (traced out)? By
developing formulae for mode-agnostic removal of photons from a beam, we show
how the expectation value of any operator changes when only $q$ photons are
inspected from a beam, ignoring the rest. We use this to reexpress expectation
values of operators in terms of the state obtained by randomly selecting $q$
photons. Remarkably, this only equals the true expectation value for a unique
value of $q$: expressing the operator as a monomial in normally ordered form,
$q$ must be equal to the number of photons annihilated by the operator. A
useful corollary is that the coefficients of any $q$-photon state chosen at
random from an arbitrary state are exactly the $q$th order correlations of the
original state; one can inspect the intensity moments to learn what any random
photon will be doing and, conversely, one need only look at the $n$-photon
subspace to discern what all of the $n$th order correlation functions are. The
astute reader will be pleased to find no surprises here, only mathematical
justification for intuition. Our results hold for any completely symmetric
state of any type of particle with any combination of numbers of particles and
can be used wherever bosonic correlations are found.


  In this review we present the recent advances for calculations of the
reactions $NN\to NN\pi$ using chiral effective field theory. Discussed are the
next-to-next-to leading order loop contributions with nucleon and Delta-isobar
for near threshold s-wave pion production. Results of recent experimental
pion-production data for energies close to the threshold are analyzed. Several
particular applications are discussed: (i) it is shown how the measured charge
symmetry violating pion-production reaction can be used to extract the
strong-interaction contribution to the proton-neutron mass difference; (ii) the
role of $NN\to NN\pi$ for the extraction of the pion-nucleon scattering lengths
from pionic atoms data is illuminated.


  We review some recent progress in understanding the relation between a six
dimensional topological Yang-Mills theory and the enumerative geometry of
Calabi-Yau threefolds. The gauge theory localizes on generalized instanton
solutions and is conjecturally equivalent to Donaldson-Thomas theory. We
evaluate the partition function of the U(N) theory in its Coulomb branch on
flat space by employing equivariant localization techniques on its
noncommutative deformation. Geometrically this corresponds to a higher
dimensional generalization of the ADHM formalism. This formalism can be
extended to a generic toric Calabi-Yau.


  During the operational life of the Italian/Dutch X-ray satellite (1996-2002),
BeppoSAX, its two Wide Field Cameras performed observations that covered the
full sky at different epochs. Although the majority of analysis performed on
BeppoSAX WFC data concentrated on the detection of transient sources, we have
now applied the same techniques developed for the INTEGRAL/IBIS survey to
produce the same work with the BeppoSAX WFC data. This work represents the
first unbiased source list compilation produced from the overall WFC data set
optimised for faint persistent sources detection. This approach recovers 182
more sources compared to the previous WFC catalogue reported in Verrecchia et
al. (2007). The catalogue contains 404 sources detected between 3-17 keV, 10 of
which are yet to be seen by the new generation of telescopes.


  Normalization Layers (NLs) are widely used in modern deep-learning
architectures. Despite their apparent simplicity, their effect on optimization
is not yet fully understood. This paper introduces a spherical framework to
study the optimization of neural networks with NLs from a geometric
perspective. Concretely, the radial invariance of groups of parameters, such as
filters for convolutional neural networks, allows to translate the optimization
steps on the $L_2$ unit hypersphere. This formulation and the associated
geometric interpretation shed new light on the training dynamics. Firstly, the
first effective learning rate expression of Adam is derived. Then the
demonstration that, in the presence of NLs, performing Stochastic Gradient
Descent (SGD) alone is actually equivalent to a variant of Adam constrained to
the unit hypersphere, stems from the framework. Finally, this analysis outlines
phenomena that previous variants of Adam act on and their importance in the
optimization process are experimentally validated.


  A study of charm fragmentation into $D_s^{*+}$ and $D_s^+$ in $e^+e^-$
annihilations at $\sqrt{s}$=10.5 GeV is presented. This study using $4.72 \pm
0.05$ fb$^{-1}$ of CLEO II data reports measurements of the cross-sections
$\sigma(D_s^{*+})$ and $\sigma(D_s^+)$ in momentum regions above $x=0.44$,
where $x$ is the $D_s$ momentum divided by the maximum kinematically allowed
$D_s$ momentum. The $D_s$ vector to vector plus pseudoscalar production ratio
is measured to be $P_V(x(D_s^+)>0.44)=0.44\pm0.04$


  In this paper, we detail the main simulation methods used in practice to
measure one-year reserve risk, and describe the bootstrap method providing an
empirical distribution of the Claims Development Result (CDR) whose variance is
identical to the closed-form expression of the prediction error proposed by
W\"uthrich et al. (2008). In particular, we integrate the stochastic modeling
of a tail factor in the bootstrap procedure. We demonstrate the equivalence
with existing analytical results and develop closed-form expressions for the
error of prediction including a tail factor. A numerical example is given at
the end of this study.


  We have carried out 12CO, 13CO, and C18O observations toward the mixed
morphology supernova remnant (SNR) IC 443. The observations cover a 1.5*1.5
deg^2 area and allow us to investigate the overall molecular environment of the
remnant. Some northern and northeastern partial shell structure of CO gas is
around the remnant. One of the partial shells, about 5' extending beyond the
northeastern border of the remnant's bright radio shell, seems to just confine
the faint radio halo. On the other hand, some faint CO clumps can be discerned
along the eastern boundary of the faint remnant's radio halo. Connecting the
eastern CO clumps, the northeastern partial shell structures, and the northern
CO partial shell, we can see that a half molecular ring structure appears to
surround the remnant. The LSR velocity of the half-ring structure is in the
range of -5 km/s to -2 km/s, which is consistent with that of the -4 km/s
molecular clouds. We suggest that the half-ring structure of the CO emission at
V_LSR -4 km/s is associated with the SNR. The structures are possibly swept up
by the stellar winds of SNR IC 443's massive progenitor. Based on the
Wide-field Infrared Survey Explorer and the Two Micron All Sky Survey near-IR
database, 62 young stellar object (YSO) candidates are selected within the
radio halo of the remnant. These YSO candidates concentrated along the boundary
of the remnant's bright radio shell are likely to be triggered by the stellar
winds from the massive progenitor of SNR IC 443.


  We consider discretized two-dimensional PDE-constrained shape optimization
problems, in which shapes are represented by triangular meshes. Given the
connectivity, the space of admissible vertex positions was recently identified
to be a smooth manifold, termed the manifold of planar triangular meshes. The
latter can be endowed with a complete Riemannian metric, which allows large
mesh deformations without jeopardizing mesh quality; see arXiv:2012.05624.
Nonetheless, the discrete shape optimization problem of finding optimal vertex
positions does not, in general, possess a globally optimal solution. To
overcome this ill-possedness, we propose to add a mesh quality penalization
term to the objective function. This allows us to simultaneously render the
shape optimization problem solvable, and keep track of the mesh quality. We
prove the existence of a globally optimal solution for the penalized problem
and establish first-order necessary optimality conditions independently of the
chosen Riemannian metric.
  Because of the independence of the existence results of the choice of the
Riemannian metric, we can numerically study the impact of different Riemannian
metrics on the steepest descent method. We compare the Euclidean, elasticity,
and a novel complete metric, combined with Euclidean and geodesic retractions
to perform the mesh deformation.


  We assess the importance of the magneto-rotational instability in
core-collapse supernovae by an analysis of the growth rates of unstable modes
in typical post-collapse systems and by numerical simulations of simplified
models. The interplay of differential rotation and thermal stratification
defines different instability regimes which we confirm in our simulations. We
investigate the termination of the growth of the MRI by parasitic
instabilities, establish scaling laws characterising the termination amplitude,
and study the long-term evolution of the saturated turbulent state.


  A highly organized and densely packed lattice of molecular machinery within
the sarcomeres of muscle cells powers contraction. Although many of the
proteins that drive contraction have been studied extensively, the mechanical
impact of fluid shearing within the lattice of molecular machinery has received
minimal attention. It was recently proposed that fluid flow augments substrate
transport in the sarcomere, however, this analysis used analytical models of
fluid flow in the molecular machinery that could not capture its full
complexity. By building a finite element model of the sarcomere, we estimate
the explicit flow field, and contrast it with analytical models. Our results
demonstrate that viscous drag forces on sliding filaments are surprisingly
small in contrast to the forces generated by single myosin molecular motors.
This model also indicates that the energetic cost of fluid flow through viscous
shearing with lattice proteins is likely minimal. The model also highlights a
steep velocity gradient between sliding filaments and demonstrates that the
maximal radial fluid velocity occurs near the tips of the filaments. To our
knowledge, this is the first computational analysis of fluid flow within the
highly structured sarcomere.


  In this work we investigate an inverse coefficient problem for the
one-dimensional subdiffusion model, which involves a Caputo fractional
derivative in time. The inverse problem is to determine two coefficients and
multiple parameters (the order, and length of the interval) from one pair of
lateral Cauchy data. The lateral Cauchy data are given on disjoint sets in time
with a single excitation and the measurement is made on a time sequence located
outside the support of the excitation. We prove two uniqueness results for
different lateral Cauchy data. The analysis is based on the solution
representation, analyticity of the observation and a refined version of inverse
Sturm-Liouville theory due to Sini [35]. Our results heavily exploit the memory
effect of fractional diffusion for the unique recovery of the coefficients in
the model. Several numerical experiments are also presented to complement the
analysis.


  Providing service continuity to the end users with best quality is a very
important issue in the next generation wireless communications. With the
evolution of the mobile devices towards a multimode architecture and the
coexistence of multitude of radio access technologies (RAT's), the users are
able to benefit simultaneously from these RAT's. However, the major issue in
heterogeneous wireless communications is how to choose the most suitable access
network for mobile's user which can be used as long as possible for
communication. To achieve this issue, this paper proposes an intelligent
network selection strategy which combines two multi attribute decision making
(MADM) methods such as analytic network process (ANP) and the technique for
order preference by similarity to an ideal solution (TOPSIS) method. The ANP
method is used to find the differentiate weights of available networks by
considering each criterion and the TOPSIS method is applied to rank the
alternatives. Our new strategy for network selection can dealing with the
limitations of MADM methods which are the ranking abnormality and the ping-ponf
effect.


  It is suggested that magnetars eventually become unstable to a dynamic
overturning instability that destroys most of their dipole moment in a single
event. It is further suggested that such an instability would produce a
supergiant version of the largest soft gamma ray bursts that have thus far been
observed, and that they could be observed out to tens or even $10^2$ Mpc.
Persistent emission and afterglows from the fireball might confirm positive
identification with nearby galaxies and perhaps provide other distinguishing
features as well.


  We study the low temperature quench dynamics of the two-dimensional Potts
model in the limit of large number of states, q >> 1. We identify a
q-independent crossover temperature (the pseudo spinodal) below which no
high-temperature metastability stops the curvature driven coarsening process.
At short length scales, the latter is decorated by freezing for some lattice
geometries, notably the square one. With simple analytic arguments we evaluate
the relevant time-scale in the coarsening regime, which turns out to be of
Arrhenius form and independent of q for large q. Once taken into account
dynamic scaling is universal.


  Cosmic rays (CR) play an important role in dense molecular cores, affecting
their thermal and dynamical evolution and initiating the chemistry. Several
studies have shown that the formation of protostellar discs in collapsing
clouds is severely hampered by the braking torque exerted by the entrained
magnetic field on the infalling gas, as long as the field remains frozen to the
gas. We examine the possibility that the concentration and twisting of the
field lines in the inner region of collapse can produce a significant reduction
of the ionisation fraction. To check whether the CR ionisation rate (CRir) can
fall below the critical value required to maintain good coupling, we first
study the propagation of CRs in a model of a static magnetised cloud varying
the relative strength of the toroidal/poloidal components and the mass-to-flux
ratio. We then follow the path of CRs using realistic magnetic field
configurations generated by numerical simulations of a rotating collapsing
core. We find that an increment of the toroidal component of the magnetic
field, or, in general, a more twisted configuration of the field lines, results
in a decrease in the CR flux. This is mainly due to the magnetic mirroring
effect that is stronger where larger variations in the field direction are
present. In particular, we find a decrease of the CRir below 10^-18 s-1 in the
central 300-400 AU, where density is higher than about 10^9 cm-3. This very low
value of the CRir is attained in the cases of intermediate and low
magnetisation (mass-to-flux ratio lambda=5 and 17, respectively) and for
toroidal fields larger than about 40% of the total field. Magnetic field
effects can significantly reduce the ionisation fraction in collapsing clouds.
We provide a handy fitting formula to compute approximately the attenuation of
the CRir in a molecular cloud as a function of the density and the magnetic
configuration.


  The segmentation of retinal vessels is of significance for doctors to
diagnose the fundus diseases. However, existing methods have various problems
in the segmentation of the retinal vessels, such as insufficient segmentation
of retinal vessels, weak anti-noise interference ability, and sensitivity to
lesions, etc. Aiming to the shortcomings of existed methods, this paper
proposes the use of conditional deep convolutional generative adversarial
networks to segment the retinal vessels. We mainly improve the network
structure of the generator. The introduction of the residual module at the
convolutional layer for residual learning makes the network structure sensitive
to changes in the output, as to better adjust the weight of the generator. In
order to reduce the number of parameters and calculations, using a small
convolution to halve the number of channels in the input signature before using
a large convolution kernel. By used skip connection to connect the output of
the convolutional layer with the output of the deconvolution layer to avoid
low-level information sharing. By verifying the method on the DRIVE and STARE
datasets, the segmentation accuracy rate is 96.08% and 97.71%, the sensitivity
reaches 82.74% and 85.34% respectively, and the F-measure reaches 82.08% and
85.02% respectively. The sensitivity is 4.82% and 2.4% higher than that of
R2U-Net.


  Owing to its application in solving the difficult and diverse clustering or
outlier detection problem, support-based clustering has recently drawn plenty
of attention. Support-based clustering method always undergoes two phases:
finding the domain of novelty and performing clustering assignment. To find the
domain of novelty, the training time given by the current solvers is typically
over-quadratic in the training size, and hence precluding the usage of
support-based clustering method for large-scale datasets. In this paper, we
propose applying Stochastic Gradient Descent (SGD) framework to the first phase
of support-based clustering for finding the domain of novelty and a new
strategy to perform the clustering assignment. However, the direct application
of SGD to the first phase of support-based clustering is vulnerable to the
curse of kernelization, that is, the model size linearly grows up with the data
size accumulated overtime. To address this issue, we invoke the budget approach
which allows us to restrict the model size to a small budget. Our new strategy
for clustering assignment enables a fast computation by means of reducing the
task of clustering assignment on the full training set to the same task on a
significantly smaller set. We also provide a rigorous theoretical analysis
about the convergence rate for the proposed method. Finally, we validate our
proposed method on the well-known datasets for clustering to show that the
proposed method offers a comparable clustering quality while simultaneously
achieving significant speedup in comparison with the baselines.


  The decay of Burgers turbulence with compactly supported Gaussian "white
noise" initial conditions is studied in the limit of vanishing viscosity and
large time. Probability distribution functions and moments for both velocities
and velocity differences are computed exactly, together with the "time-like"
structure functions .
  The analysis of the answers reveals both well known features of Burgers
turbulence, such as the presence of dissipative anomaly, the extreme anomalous
scaling of the velocity structure functions and self similarity of the
statistics of the velocity field, and new features such as the extreme
anomalous scaling of the "time-like" structure functions and the non-existence
of a global inertial scale due to multiscaling of the Burgers velocity field.
  We also observe that all the results can be recovered using the one point
probability distribution function of the shock strength and discuss the
implications of this fact for Burgers turbulence in general.


  Sequence prediction models can be learned from example sequences with a
variety of training algorithms. Maximum likelihood learning is simple and
efficient, yet can suffer from compounding error at test time. Reinforcement
learning such as policy gradient addresses the issue but can have prohibitively
poor exploration efficiency. A rich set of other algorithms such as RAML, SPG,
and data noising, have also been developed from different perspectives. This
paper establishes a formal connection between these algorithms. We present a
generalized entropy regularized policy optimization formulation, and show that
the apparently distinct algorithms can all be reformulated as special instances
of the framework, with the only difference being the configurations of a reward
function and a couple of hyperparameters. The unified interpretation offers a
systematic view of the varying properties of exploration and learning
efficiency. Besides, inspired from the framework, we present a new algorithm
that dynamically interpolates among the family of algorithms for scheduled
sequence model learning. Experiments on machine translation, text
summarization, and game imitation learning demonstrate the superiority of the
proposed algorithm.


  Physics-inspired regularization is desired for intra-patient image
registration since it can effectively capture the biomechanical characteristics
of anatomical structures. However, a major challenge lies in the reliance on
physical parameters: Parameter estimations vary widely across the literature,
and the physical properties themselves are inherently subject-specific. In this
work, we introduce a novel data-driven method that leverages hypernetworks to
learn the tissue-dependent elasticity parameters of an elastic regularizer.
Notably, our approach facilitates the estimation of patient-specific parameters
without the need to retrain the network. We evaluate our method on three
publicly available 2D and 3D lung CT and cardiac MR datasets. We find that with
our proposed subject-specific tissue-dependent regularization, a higher
registration quality is achieved across all datasets compared to using a global
regularizer. The code is available at
https://github.com/compai-lab/2024-miccai-reithmeir.


  We consider the problem of finding lower bounds on the I/O complexity of
arbitrary computations in a two level memory hierarchy. Executions of complex
computations can be formalized as an evaluation order over the underlying
computation graph. However, prior methods for finding I/O lower bounds leverage
the graph structures for specific problems (e.g matrix multiplication) which
cannot be applied to arbitrary graphs. In this paper, we first present a novel
method to bound the I/O of any computation graph using the first few
eigenvalues of the graph's Laplacian. We further extend this bound to the
parallel setting. This spectral bound is not only efficiently computable by
power iteration, but can also be computed in closed form for graphs with known
spectra. We apply our spectral method to compute closed-form analytical bounds
on two computation graphs (the Bellman-Held-Karp algorithm for the traveling
salesman problem and the Fast Fourier Transform), as well as provide a
probabilistic bound for random Erdos Renyi graphs. We empirically validate our
bound on four computation graphs, and find that our method provides tighter
bounds than current empirical methods and behaves similarly to previously
published I/O bounds.


  We study the role played by topological textures and antitextures during the
phase ordering of a two-dimensional system described by the discretised
nonlinear O(3) sigma model with purely dissipative dynamics. We identify and
characterise two distinct mechanisms for the decay of the order parameter
variations --- single texture unwinding, and topological charge annihilation.
Our results show that while at early times after the quench, the annihilation
process dominates, the unwinding processes become of comparable importance at
later times. We calculate the correlations in the order parameter and in the
topological charge density, and show that dynamical scaling is strongly
violated due to the occurence of multiple length scales growing differently in
time.


  Using the sub-supersolution method we study the existence of positive
solutions for the anisotropic problem \begin{equation}
-\sum_{i=1}^N\frac{\partial}{\partial x_i}\left( \left|\frac{\partial
u}{\partial x_i}\right|^{p_i-2}\frac{\partial u}{\partial x_i}\right)=\lambda
u^{q-1} \end{equation} where $\Omega$ is a bounded and regular domain of
$\mathbb{R}^N$, $q>1$ and $\lambda>0$.


  Multi-objective optimization is the problem of optimizing simultaneously
multiple objective functions and several techniques exist to deal with this
problem. This paper aims to present the main methods that can be used to solve
this issue in the context of relational databases. In particular, this work
examines Top-k query to get the k best result from a dataset and Skyline query
that provides a more general overview of the best results. We also discuss
Flexible-skyline, a new method designed to improve upon the previous
techniques, mitigating their shortcomings. For each method, we describe the
main characteristics and present an overview of the algorithms implementing
such thecniques, while comparing advantages and disadvantages.


  We have investigated how the Coulomb blockade of a mesoscopic Josephson
junction in a high-impedance environment is suppressed by shot noise from an
adjacent junction. The presented theoretical analysis is an extension of the
phase correlation theory for the case of a non-Gaussian noise. Asymmetry of the
non-Gaussian noise should result in the shift of the conductance minimum from
zero voltage and the ratchet effect (nonzero current at zero voltage), which
have been experimentally observed. The analysis demonstrates that a Coulomb
blockaded tunnel junction in a high impedance environment can be used as an
effective noise detector.


  We present the results of our analysis of six orbits of HST/STIS time-tagged
spectroscopy of the intermediate polar, EX Hydrae. The high time and wavelength
resolution of the HST/STIS spectra provided an excellent opportunity to study
the UV properties of EX Hya. Measurements of the continuum and emission line
fluxes corroborate earlier studies that show that the emission line fluxes are
modulated more strongly than the continuum flux and originate from the
accretion curtains, while the continuum flux originates from the white dwarf
photosphere. The measured K amplitude of the narrow emission line radial
velocity curve is used to calculate a white dwarf mass of 0.91+/-0.05 M_sun.
Synthetic white dwarf photosphere and accretion disk spectral models are used
to further refine the white dwarf and accretion disk properties. Using the
spectral models, it is determined that EX Hya has a white dwarf of mass 0.9
M_sun, T=23000 K, an accretion disk truncated at 2.5 R_WD, and is at a distance
of 60 pc.


  Covert transmission is investigated for a cooperative deception strategy,
where a cooperative jammer (Jammer) tries to attract a multi-antenna adversary
(Willie) and degrade the adversary's reception ability for the signal from a
transmitter (Alice). For this strategy, we formulate an optimization problem to
maximize the covert rate when three different types of channel state
information (CSI) are available. The total power is optimally allocated between
Alice and Jammer subject to Kullback-Leibler (KL) divergence constraint.
Different from the existing literature, in our proposed strategy, we also
determine the optimal transmission power at the jammer when Alice is silent,
while existing works always assume that the jammer's power is fixed.
Specifically, we apply the S-procedure to convert infinite constraints into
linear-matrix-inequalities (LMI) constraints. When statistical CSI at Willie is
available, we convert double integration to single integration using asymptotic
approximation and substitution method. In addition, the transmission strategy
without jammer deception is studied as a benchmark. Finally, our simulation
results show that for the proposed strategy, the covert rate is increased with
the number of antennas at Willie. Moreover, compared to the benchmark, our
proposed strategy is more robust in face of imperfect CSI.


  Effective-medium theory pertains to the theoretical modelling of
homogenization, which aims to replace an inhomogeneous structure of
subwavelength-scale constituents with a homogeneous effective medium. The
effective-medium theory is fundamental to various realms, including
electromagnetics and material science, since it can largely decrease the
complexity in the exploration of light-matter interactions by providing simple
acceptable approximation. Generally, the effective-medium theory is thought to
be applicable to any all-dielectric system with deep-subwavelength
constituents, under the condition that the effective medium does not have a
critical angle, at which the total internal reflection occurs. Here we reveal a
fundamental breakdown of the effective-medium theory that can be applied in
very general conditions: showing it for deep-subwavelength all-dielectric
multilayers even without critical angle. Our finding relies on an exotic
photonic spin Hall effect, which is shown to be ultra-sensitive to the stacking
order of deep-subwavelength dielectric layers, since the spin-orbit interaction
of light is dependent on slight phase accumulations during the wave
propagation. Our results indicate that the photonic spin Hall effect could
provide a promising and powerful tool for measuring structural defects for
all-dielectric systems even in the extreme nanometer scale.


  We study the cosmology with the running dark energy. The parametrization of
dark energy with the respect to the redshift is derived from the first
principles of quantum mechanics. Energy density of dark energy is obtained from
the quantum process of transition from the false vacuum state to the true
vacuum state. This is the class of the extended interacting $\Lambda$CDM
models. We consider the energy density of dark energy parametrization
$\rho_\text{de}(t)$, which follows from the Breit-Wigner energy distribution
function which is used to model the quantum unstable systems. The idea that
properties of the process of the quantum mechanical decay of unstable states
can help to understand the properties of the observed universe was formulated
by Krauss and Dent and this idea was used in our considerations. In the
cosmological model with the mentioned parametrization there is an energy
transfer between the dark matter and dark energy. In such a evolutional
scenario the universe is starting from the false vacuum state and going to the
true vacuum state of the present day universe. We find that the intermediate
regime during the passage from false to true vacuum states takes place. The
intensity of the analyzed process is measured by a parameter $\alpha$. For the
small value of $\alpha$ ($0<\alpha <0.4$) this intermediate (quantum) regime is
characterized by an oscillatory behavior of the density of dark energy while
the for $\alpha > 0.4$ the density of the dark energy simply jumps down. In
both cases (independent from the parameter $\alpha$) the today value of density
of dark energy is reached at the value of $0.7$. We estimate the cosmological
parameters for this model with visible and dark matter. This model becomes in
good agreement with the astronomical data and is practically indistinguishable
from $\Lambda$CDM model.


  An order ideal is a finite poset X of (monic) monomials such that, whenever M
is in X and N divides M, then N is in X. If all, say t, maximal monomials of X
have the same degree, then X is pure (of type t). A pure O-sequence is the
vector, h=(1,h_1,...,h_e), counting the monomials of X in each degree.
Equivalently, in the language of commutative algebra, pure O-sequences are the
h-vectors of monomial Artinian level algebras. Pure O-sequences had their
origin in one of Richard Stanley's early works in this area, and have since
played a significant role in at least three disciplines: the study of
simplicial complexes and their f-vectors, level algebras, and matroids. This
monograph is intended to be the first systematic study of the theory of pure
O-sequences. Our work, making an extensive use of algebraic and combinatorial
techniques, includes: (i) A characterization of the first half of a pure
O-sequence, which gives the exact converse to an algebraic g-theorem of Hausel;
(ii) A study of (the failing of) the unimodality property; (iii) The problem of
enumerating pure O-sequences, including a proof that almost all O-sequences are
pure, and the asymptotic enumeration of socle degree 3 pure O-sequences of type
t; (iv) The Interval Conjecture for Pure O-sequences (ICP), which represents
perhaps the strongest possible structural result short of an (impossible?)
characterization; (v) A pithy connection of the ICP with Stanley's matroid
h-vector conjecture; (vi) A specific study of pure O-sequences of type 2,
including a proof of the Weak Lefschetz Property in codimension 3 in
characteristic zero. As a corollary, pure O-sequences of codimension 3 and type
2 are unimodal (over any field); (vii) An analysis of the extent to which the
Weak and Strong Lefschetz Properties can fail for monomial algebras; (viii)
Some observations about pure f-vectors, an important special case of pure
O-sequences.


  We introduce the Generalized Preconditioned Locally Harmonic Residual (GPLHR)
method for solving standard and generalized non-Hermitian eigenproblems. The
method is particularly useful for computing a subset of eigenvalues, and their
eigen- or Schur vectors, closest to a given shift. The proposed method is based
on block iterations and can take advantage of a preconditioner if it is
available. It does not need to perform exact shift-and-invert transformation.
Standard and generalized eigenproblems are handled in a unified framework. Our
numerical experiments demonstrate that GPLHR is generally more robust and
efficient than existing methods, especially if the available memory is limited.


  By assuming that tau protein can be in seven kinetic states, we developed a
model of tau protein transport in the axon and in the axon initial segment
(AIS). Two separate sets of kinetic constants were determined, one in the axon
and the other in the AIS. This was done by fitting the model predictions in the
axon with experimental results and by fitting the model predictions in the AIS
with the assumed linear increase of the total tau concentration in the AIS. The
calibrated model was used to make predictions about tau transport in the axon
and in the AIS. To the best of our knowledge, this is the first paper that
presents a mathematical model of tau transport in the AIS. Our modeling results
suggest that binding of free tau to MTs creates a negative gradient of free tau
in the AIS. This leads to diffusion-driven tau transport from the soma into the
AIS. The model further suggests that slow axonal transport and diffusion-driven
transport of tau work together in the AIS, moving tau anterogradely. Our
numerical results predict an interplay between these two mechanisms: as the
distance from the soma increases, the diffusion-driven transport decreases,
while motor-driven transport becomes larger. Thus, the machinery in the AIS
works as a pump, moving tau into the axon.


  A congruence is a surface in the Grassmannian ${\rm Gr}(2, 4)$. In this
paper, we consider the normalization of congruence of bitangents to a
hypersurface in $\mathbb P^3$. We call it the Fano congruence of bitangents. We
give a criterion for smoothness of the Fano congruence of bitangents and
describe explicitly their degenerations in a general Lefschetz pencil in the
space of hypersurfaces in $\mathbb P^3$.


  End-to-end speech translation relies on data that pair source-language speech
inputs with corresponding translations into a target language. Such data are
notoriously scarce, making synthetic data augmentation by back-translation or
knowledge distillation a necessary ingredient of end-to-end training. In this
paper, we present a novel approach to data augmentation that leverages audio
alignments, linguistic properties, and translation. First, we augment a
transcription by sampling from a suffix memory that stores text and audio data.
Second, we translate the augmented transcript. Finally, we recombine
concatenated audio segments and the generated translation. Besides training an
MT-system, we only use basic off-the-shelf components without fine-tuning.
While having similar resource demands as knowledge distillation, adding our
method delivers consistent improvements of up to 0.9 and 1.1 BLEU points on
five language pairs on CoVoST 2 and on two language pairs on Europarl-ST,
respectively.


  Intrusion research frequently collects data on attack techniques currently
employed and their potential symptoms. This includes deploying honeypots,
logging events from existing devices, employing a red team for a sample attack
campaign, or simulating system activity. However, these observational studies
do not clearly discern the cause-and-effect relationships between the design of
the environment and the data recorded. Neglecting such relationships increases
the chance of drawing biased conclusions due to unconsidered factors, such as
spurious correlations between features and errors in measurement or
classification. In this paper, we present the theory and empirical data on
methods that aim to discover such causal relationships efficiently. Our
adaptive design (AD) is inspired by the clinical trial community: a variant of
a randomized control trial (RCT) to measure how a particular ``treatment''
affects a population. To contrast our method with observational studies and
RCT, we run the first controlled and adaptive honeypot deployment study,
identifying the causal relationship between an ssh vulnerability and the rate
of server exploitation. We demonstrate that our AD method decreases the total
time needed to run the deployment by at least 33%, while still confidently
stating the impact of our change in the environment. Compared to an analogous
honeypot study with a control group, our AD requests 17% fewer honeypots while
collecting 19% more attack recordings than an analogous honeypot study with a
control group.


  A simple construction of pseudorandom generator is appear.This pseudorandom
generator is always passed by NIST statistical test.This paper reports a
pseudorandom number generator which has good property is able to construct
using only permutation and data rewriting by XOR.


  General amplitude equations for reaction-diffusion systems near to the soft
onset of birhythmicity described by a supercritical pitchfork-Hopf bifurcation
are derived. Using these equations and applying singular perturbation theory,
we show that stable autonomous pacemakers represent a generic kind of
spatiotemporal patterns in such systems. This is verified by numerical
simulations, which also show the existence of breathing and swinging pacemaker
solutions. The drift of self-organized pacemakers in media with spatial
parameter gradients is analytically and numerically investigated.


  Current anomaly detection algorithms are typically challenged by either
accuracy or efficiency. More accurate nonlinear detectors are typically slow
and not scalable. In this letter, we propose two families of techniques to
improve the efficiency of the standard kernel Reed-Xiaoli (RX) method for
anomaly detection by approximating the kernel function with either {\em
data-independent} random Fourier features or {\em data-dependent} basis with
the Nystr\"om approach. We compare all methods for both real multi- and
hyperspectral images. We show that the proposed efficient methods have a lower
computational cost and they perform similar (or outperform) the standard kernel
RX algorithm thanks to their implicit regularization effect. Last but not
least, the Nystr\"om approach has an improved power of detection.


  Magneto-inertial range dominated by magnetic helicity has been studied using
results of numerical simulations, laboratory measurements, solar, solar wind,
the Earth's and planets' magnetosphere observations (spacecraft measurements),
and the global magnetic observatory network. The spectral data have been
compared with the theoretical results based on the distributed chaos notion in
the frames of the Kolmogorov-Iroshnikov phenomenology. The transition from
magnetohydrodynamics to kinetics in the electron and Hall magnetohydrodynamics,
and in a fully kinetic 3D approach, as well as in the solar wind, solar
photosphere, and at the special events (reconnections, Kelvin-Helmholtz
instability, isolated flux tube interchanges, etc.) in the magnetosphere of
Earth, Saturn, Jupiter, and Mercury has been studied using the above-mentioned
data. Despite the considerable differences in the physical parameters and
scales, the results of numerical simulations are in quantitative agreement with
the observational data in the frames of the magneto-inertial range notion.
Temporal variability of the magnetic field at Earth's surface under the
influence of the ionosphere, magnetosphere, and solar wind has been also
briefly discussed in this context.


It is shown that plactic monoids satisfy nontrivial identities.


  An extended text of the talk given at the conference ``2001: A Spacetime
Odyssey'', to be published in the Proceedings of the Inaugural Conference of
the Michigan Center for Theoretical Physics, University of Michigan, Ann Arbor,
21-25 May 2001, M.J. Duff and J.T. Liu eds., World Scientific, Singapore, 2002;
and of Historical Lecture ``Vacuum as seen from Moscow'' at the CERN Summer
School, 10 August, 2001. Contents: Introduction; Pomeranchuk on vacuum; Landau
on parity, P, and combined parity, CP; Search and discovery of $K_L^0 \to \pi^+
\pi^-$; "Mirror world"; Zeldovich and cosmological term; QCD vacuum
condensates; Sakharov and baryonic asymmetry of the universe, BAU; Kirzhnits
and phase transitions; Vacuum domain walls; Monopoles, strings, instantons, and
sphalerons; False vacuum; Inflation; Brane and Bulk; Acknowledgments;
References.


  Let $p$ be a prime and let $g(p)$ be the least primitive root modulo $p$. We
prove that for any $\epsilon>0$ and $p$ large enough the bound \begin{align}
g(p)\ll p^{\frac{1}{4\sqrt{e}}+\epsilon} \nonumber
  \end{align} holds for most prime $p$ such that $p-1$ does not have small
prime factors, but $2$. We also give an explicit description of the exceptional
set.


  We calculated the superconducting transition temperature $T_{\rm c}$ of
hole-doped CuBO$_2$, CuAlO$_2$, CuGaO$_2$ and CuInO$_2$ using first-principles.
The calculated $T_{\rm c}$ are about 50 K for CuAlO$_2$, 10 K for CuBO$_2$ and
CuGaO$_2$ and 1 K for CuInO$_2$ at maximum in the optimum hole-doping
concentration. The low $T_{\rm c}$ of CuInO$_2$ is attributed to the weak
electron-phonon interaction caused by the low covalency and heavy atomic mass.


  Semi-Global Exponential Stability (SGES) is proved for the combined attitude
and position rigid body motion tracking problem, which was previously only
known to be asymptotically stable. Dual quaternions are used to jointly
represent the rotational and translation tracking error dynamics of the rigid
body. A novel nonlinear feedback tracking controller is proposed and a Lyapunov
based analysis is provided to prove the semi-global exponential stability of
the closed-loop dynamics. Our analysis does not place any restrictions on the
reference trajectory or the feedback gains. This stronger SGES result aids in
further analyzing the robustness of the rigid body system by establishing
Input-to-State Stability (ISS) in the presence of time-varying additive and
bounded external disturbances. Motivated by the fact that in many aerospace
applications, stringent adherence to safety constraints such as approach path
and input constraints is critical for overall mission success, we present a
framework for safe control of spacecraft that combines the proposed feedback
controller with Control Barrier Functions. Numerical simulations are provided
to verify the SGES and ISS results and also showcase the efficacy of the
proposed nonlinear feedback controller in several non-trivial scenarios
including the Mars Cube One (MarCO) mission, Apollo transposition and docking
problem, Starship flip maneuver, collision avoidance of spherical robots, and
the rendezvous of SpaceX Dragon 2 with the International Space Station.


  The Jahn-Teller system E x b_1 + b_2 has a particular degeneracy, where the
vibronic potential has an elliptical minimum. In the general case where the
ellipse does not reduce to a circle, the classical motion in the potential is
chaotic, tending to trapping near one of the extrema of the ellipse. In the
quantum problem, the motion consists of correlated tunneling from one extremum
to the opposite, leading to an average angular momentum reminiscent of that of
the better known E x e dynamic Jahn-Teller system.


  We investigate the large-$N$ asymptotics of the topologically twisted index
of $\mathcal N=4$ SU($N$) Super-Yang-Mills (SYM) theory on $T^2\times S^2$ and
provide its holographic interpretation based on the black hole Farey tail. In
the field theory side, we use the Bethe-Ansatz (BA) formula, which gives the
twisted index of $\mathcal N=4$ SYM theory as a discrete sum over Bethe vacua,
to compute the large-$N$ asymptotics of the twisted index. In a dual $\mathcal
N=2$ gauged STU model, we construct a family of 5d extremal solutions uplifted
from the 3d black hole Farey tail, and compute the regularized on-shell
actions. The gravitational partition function given in terms of these
regularized on-shell actions is then compared with a canonical partition
function derived from the twisted index by the inverse Laplace transform, in
the large-$N$ limit. This extends the previous microstate counting of an
AdS$_5$ black string by the twisted index and thereby improves holographic
understanding of the twisted index.


  In this paper we show that the entropy of cosmological horizon in
4-dimensional Topological Kerr-Newman-de Sitter spaces can be described by the
Cardy-Verlinde formula, which is supposed to be an entropy formula of conformal
field theory in any dimension. Furthermore, we find that the entropy of black
hole horizon can also be rewritten in terms of the Cardy-Verlinde formula for
these black holes in de Sitter spaces, if we use the definition due to Abbott
and Deser for conserved charges in asymptotically de Sitter spaces. Such result
presume a well-defined dS/CFT correspondence, which has not yet attained the
credibility of its AdS analogue.


  For general dimension $d$ we prove the equidistribution of energy at the
micro-scale in $\mathbb R^d$, for the optimal point configurations appearing in
Coulomb gases at zero temperature. At the microscopic scale, i.e. after blow-up
at the scale corresponding to the interparticle distance, in the case of
Coulomb gases we show that the energy concentration is precisely determined by
the macroscopic density of points, independently of the scale. This uses the
"jellium energy" which was previously shown to control the next-order term in
the large particle number asymptotics of the minimum energy. As a corollary, we
obtain sharp error bounds on the discrepancy between the number of points and
its expected average of optimal point configurations for Coulomb gases,
extending previous results valid only for $2$-dimensional log-gases. For Riesz
gases with interaction potentials $g(x)=|x|^{-s}, s\in]\min\{0,d-2\},d[$ and
one-dimensional log-gases, we prove the same equidistribution result under an
extra hypothesis on the decay of the localized energy, which we conjecture to
hold for minimizing configurations. In this case we use the
Caffarelli-Silvestre description of the non-local fractional Laplacians in
$\mathbb R^d$ to localize the problem.


  The issue of how epistemic uncertainties affect the outcome of Monte Carlo
simulation is discussed by means of a concrete use case: the simulation of the
longitudinal energy deposition profile of low energy protons. A variety of
electromagnetic and hadronic physics models is investigated, and their effects
are analyzed. Possible systematic effects are highlighted. The results identify
requirements for experimental measurements capable of reducing epistemic
uncertainties in the simulation.


  The Asymptotically Safe Gravity provides a framework for the description of
gravity from the trans-Planckian regime to cosmological scales. According to
this scenario, the cosmological constant and Newton's coupling are functions of
the energy scale whose evolution is dictated by the renormalization group
equations. The formulation of the renormalization group equations on foliated
spacetimes, based on the Arnowitt-Deser-Misner (ADM) formalism, furnishes a
natural way to construct the RG energy scale from the spectrum of the laplacian
operator on the spatial slices. Combining this idea with a Renormalization
Group improvement procedure, in this work we study quantum gravitational
corrections to the Einstein-Hilbert action on
Friedmann-Lema\^{i}tre-Robertson-Walker (FLRW) backgrounds. The resulting
quantum-corrected Friedmann equations can give rise to both bouncing
cosmologies and emergent universe solutions. Our bouncing models do not require
the presence of exotic matter and emergent universe solutions can be
constructed for any allowed topology of the spatial slices.


  In \cite{s=0}, the new formula for $L^p(\mathbb{R}^N)$ norms was given by Gu
and Yung which is characterized by the standard weak-$L^p(\mathbb{R}^{2N})$
norms. At first glance, it seems to be able to measure the degree of fractional
smoothness of functions. In this paper, our proof goes in parallel as in
\cite{s=0}, but gives another different representation which is obviously
independent of the smoothness of function.


  We consider infinite sequences of positive numbers. The connection between
log-concavity and the Bessenrodt--Ono inequality had been in the focus of
several papers. This has applications in the white noise distribution theory
and combinatorics. We improve a recent result of Benfield and Roy and show that
for the sequence of partition numbers $\{p(n)\}$ Nicolas' log-concavity result
implies the result of Bessenrodt and Ono towards $p(n) \, p(m) > p(n+m)$.


  We show how one can define novel gauge-theoretic Floer homologies of four,
three and two-manifolds from the physics of a certain topologically-twisted 5d
${\cal N}=2$ gauge theory via its supersymmetric quantum mechanics
interpretation. They are associated with Vafa-Witten, Hitchin and
$G_{\mathbb{C}}$-BF configurations on the four, three and two-manifolds,
respectively. We also show how one can define novel symplectic Floer homologies
of Hitchin spaces, which in turn will allow us to derive novel Atiyah-Floer
correspondences that relate our gauge-theoretic Floer homologies to symplectic
intersection Floer homologies of Higgs bundles. Furthermore, topological
invariance and 5d "S-duality" suggest a web of relations and a Langlands
duality amongst these novel Floer homologies and their loop/toroidal group
generalizations. Last but not least, via a 2d gauged Landau-Ginzburg model
interpretation of the 5d theory, we derive, from the soliton string theory that
it defines and the 5d partition function, a Fukaya-Seidel type
$A_\infty$-category of Hitchin configurations on three-manifolds and its novel
Atiyah-Floer correspondence. Our work therefore furnishes purely physical
proofs and generalizations of the mathematical conjectures of Haydys [1],
Abouzaid-Manolescu [2], and Bousseau [3], and more.


  Gaits and transitions are key components in legged locomotion. For legged
robots, describing and reproducing gaits as well as transitions remain
longstanding challenges. Reinforcement learning has become a powerful tool to
formulate controllers for legged robots. Learning multiple gaits and
transitions, nevertheless, is related to the multi-task learning problems. In
this work, we present a novel framework for training a simple control policy
for a quadruped robot to locomote in various gaits. Four independent phases are
used as the interface between the gait generator and the control policy, which
characterizes the movement of four feet. Guided by the phases, the quadruped
robot is able to locomote according to the generated gaits, such as walk, trot,
pacing and bounding, and to make transitions among those gaits. More general
phases can be used to generate complex gaits, such as mixed rhythmic dancing.
With the control policy, the Black Panther robot, a medium-dog-sized quadruped
robot, can perform all learned motor skills while following the velocity
commands smoothly and robustly in natural environment.


  Since the introduction of fifth-generation new radio (5G-NR) in Third
Generation Partnership Project (3GPP) Release 15, swift progress has been made
to evolve 5G with 3GPP Release 18 emerging. A critical aspect is the design of
massive multiple-input multiple-output (MIMO) technology. In this line, this
paper makes several important contributions: We provide a comprehensive
overview of the evolution of standardized massive MIMO features from 3GPP
Release 15 to 17 for both time/frequency-division duplex operation across bands
FR-1 and FR-2. We analyze the progress on channel state information (CSI)
frameworks, beam management frameworks and present enhancements for uplink CSI.
We shed light on emerging 3GPP Release 18 problems requiring imminent
attention. These include advanced codebook design and sounding reference signal
design for coherent joint transmission (CJT) with multiple
transmission/reception points (multi- TRPs). We discuss advancements in uplink
demodulation reference signal design, enhancements for mobility to provide
accurate CSI estimates, and unified transmission configuration indicator
framework tailored for FR-2 bands. For each concept, we provide system level
simulation results to highlight their performance benefits. Via field trials in
an outdoor environment at Shanghai Jiaotong University, we demonstrate the
gains of multi-TRP CJT relative to single TRP at 3.7 GHz.


  A piecewise linear function can be described in different forms: as an
arbitrarily nested expression of $\min$- and $\max$-functions, as a difference
of two convex piecewise linear functions, or as a linear combination of maxima
of affine-linear functions. In this paper, we provide two main results: first,
we show that for every piecewise linear function there exists a linear
combination of $\max$-functions with at most $n+1$ arguments, and give an
algorithm for its computation. Moreover, these arguments are contained in the
finite set of affine-linear functions that coincide with the given function in
some open set. Second, we prove that the piecewise linear function $\max(0,
x_{1}, \ldots, x_{n})$ cannot be represented as a linear combination of maxima
of less than $n+1$ affine-linear arguments. This was conjectured by Wang and
Sun in 2005 in a paper on representations of piecewise linear functions as
linear combination of maxima.


  We present sharp interpolation theorems, including all limiting cases, for a
class of quasilinear operators of joint weak type acting between
Lorentz-Karamata spaces over $\sigma$-finite measure. This class contains many
of the important integral operators. The optimality in the scale of
Lorentz-Karamata spaces is also discussed. The proofs of our results rely on a
characterization of Hardy-type inequalities restricted to monotone functions
and with power-slowly varying weights. Some of the limiting cases of these
inequalities have not been considered in the literature so far.


  Using a sample of 1.31 billion $J/\psi$ events collected with the BESIII
detector at the BEPCII collider, the decays $J/\psi \to \phi
\pi^{+}\pi^{-}\pi^{0}$ and $J/\psi \to \phi \pi^{0}\pi^{0}\pi^{0}$ are
investigated. The isospin violating decay $J/\psi \to \phi \pi^{0} f_{0}(980)$
with $f_{0}(980) \to \pi\pi$, is observed for the first time. The width of the
$f_{0}(980)$ obtained from the dipion mass spectrum is found to be much smaller
than the world average value. In the $\pi^{0} f_{0}(980)$ mass spectrum, there
is evidence of $f_1(1285)$ production. By studying the decay $J/\psi \to
\phi\eta'$, the branching fractions of $\eta' \to \pi^{+}\pi^{-}\pi^{0}$ and
$\eta' \to \pi^{0}\pi^{0}\pi^{0}$, as well as their ratio, are also measured.


  The most familiar formalism for the description of geometry applicable to
physics comprises operations among 4-component vectors and complex real
numbers; few people realize that this formalism has indeed 32 degrees of
freedom and can thus be called 32-dimensional. We will revise this formalism
and we will briefly show that it is best accommodated in the Clifford or
geometric algebra G(1,3) x C, the algebra of 4-dimensional spacetime over the
complex field. We will then explore other algebras isomorphic to that one,
namely G(2,3), G(4,1) and Q x Q x C, all of which have been used in the past by
PIRT participants to formulate their respective approaches to physics. G(2,3)is
the algebra of 3-space with two time dimensions, which John Carroll used
implicitely in his formulation of electromagnetism in 3 + 3 spacetime, G(4,1)
was and it still is used by myself in a tentative to unify the formulation of
physics and Q x Q x C is the choice of Peter Rowlands for his nilpotent
formulation of quantum mechanics. We will show how the equations can be
converted among isomorphic algebras and we also examine how the monogenic
functions that I use are equivalent in many ways to Peter Rowlands nilpotent
entities.


  In this paper, we review the preliminary results on the propagation effects
and interplanetary consequences of fast and wide coronal mass ejection (CME)
events, occurred during 18--25 June 2015, in the Sun-Earth distance range. The
interplanetary scintillation (IPS) images reveal that the large-scale
structures of CME-driven disturbances filled nearly the entire inner
heliosphere with a range of speeds, $\sim$300--1000 {\kmps}. The comparison of
speed data sets, from IPS technique results in the inner heliosphere and {\it
in-situ} measurements at 1 AU, indicates that the drag force imposed by the
low-speed wind dominated heliosphere on the propagation of CMEs may not be
effective. The arrival of shocks at 1 AU suggests that a shock can be driven in
the interplanetary medium by the central part of the moving CME and also by a
different part away from its centre. The increased flux of proton at energies
$>$10 MeV is consistent with the acceleration of particles by the shock ahead
of the CME.


  A new class of generalized backward doubly stochastic differential equations
(GBDSDEs in short) driven by Teugels martingales associated with L\'evy process
are investigated. We establish a comparison theorem which allows us to derive
an existence result of solutions under continuous and linear growth conditions.


  Copying the quantum states is contradictory to classical information
processing since the fundamental difference between classical and quantum
information is that while classical information can be copied perfectly,
quantum information cannot. However, this statement does not rule out the risk
of building a device that can reproduce a set of quantum states. This paper
investigates the naturally arising question of how well or under what
conditions one can copy and measure an arbitrary quantum superposition of
states. The CNOT and XOR operation-based quantum circuit is presented that
exhibits entanglement of states and allows for measuring the doubled qubits.


  Using density functional theory (DFT), this work explores barium zirconate
doped with nitrogen. In addition, we used density functional theory (DFT) to
study the BaZrO$_3$'s electrical, optical, and structural properties, and we
found that the BaZrO$_3$ has intrinsic vacancy defects by employing the
supercell approach. Integrating testability into hardware devices is the goal
of testing design, an approach to integrated circuit design that draws on
density functional theory. This technology simplifies production testing and
implementation. The study strategy incorporates the following methods: LSDA+U,
Exchange Correlation Approximations, Hohenberg Kohn Theorem, and Local Spin
Density Approximation. We tracked the evolution of barium zirconate's protonic,
nitrogen ionic, and electronic conductivities using Density Functional Theory
(DFT). We found low electrical conductivity despite the fact that nitrogen
doping successfully lowered energy barriers for oxygen and proton ion
migration. The conductivity of barium zirconate increased in proportion to the
supercell's nitrogen content. Furthermore, we investigated the local
arrangements of octahedral sites in Pm3m cubic frameworks and utilized Density
Functional Theory to dope BaZrO$_3$. Nitrogen doping caused a lot of changes to
oxygen sites, revealing three groups of oxygen atoms with different structural
properties.


  A new simulation box setup is introduced for the precise description of the
wavepacket evolution of two electronic systems in intense laser pulses. In this
box, the regions of the hydrogen molecule H$_{2} $, and singly and doubly
ionized species, H$_{2}^+ $ and H$_{2}^{+2} $, are well recognized and their
time-dependent populations are calculated at different laser field intensities.
In addition, some new regions are introduced and characterized as quasi-double
ionization and their time-dependencies on the laser field intensity are
calculated and analyzed. The adopted simulation box setup is special in that it
assures proper evaluation of the second ionization. In this study, the dynamics
of the electrons and nuclei of the hydrogen molecule are separated based on the
adiabatic approximation. The time-dependent Schr\"{o}dinger and Newton
equations are solved simultaneously for the electrons and the nuclei,
respectively. Laser pulses of 390 nm wavelength at four different intensities
(i.e. $ 1\times10^{14} $, $ 5\times10^{14} $, $ 1\times10^{15} $, and $
5\times10^{15} $ W cm$^{-2}$) are used in these simulations. Details of the
central H$_{2} $ region is also presented and discussed. This region is divided
into four sub-regions related to the ionic state H$^+$H$^-$ and covalent
(natural) state HH. The effect of the motion of nuclei on the enhanced
ionization is discussed. Finally, some different time-dependent properties are
calculated and their dependencies on the intensity of the laser pulse are
studied, and their correlations with the populations of different regions are
analyzed.


  Differences in the density dependence of the symmetry energy predicted by
nonrelativistic and relativistic models are suggested, at least in part, as the
culprit for the discrepancy in the values of the compression modulus of
symmetric nuclear matter extracted from the energy of the giant monopole
resonance in 208Pb. ``Best-fit'' relativistic models, with stiffer symmetry
energies than Skyrme interactions, consistently predict higher compression
moduli than nonrelativistic approaches. Relativistic models with compression
moduli in the physically acceptable range of K=200-300 MeV are used to compute
the distribution of isoscalar monopole strength in 208Pb. When the symmetry
energy is artificially softened in one of these models, in an attempt to
simulate the symmetry energy of Skyrme interactions, a lower value for the
compression modulus is indeed obtained. It is concluded that the proposed
measurement of the neutron skin in 208Pb, aimed at constraining the density
dependence of the symmetry energy and recently correlated to the structure of
neutron stars, will also become instrumental in the determination of the
compression modulus of nuclear matter.


  We have developed a fast method for predicting the angular power spectrum,
C_l, of the cosmic microwave background given cosmological parameters and a
primordial power spectrum of perturbations. After pre--computing the radiation
temperature and gravitational potential transfer functions over a small
sub--space of the total model parameter space, the rest of the model space (six
or more cosmological parameters and arbitrarily many primordial power spectrum
parameters) is reached via rapid analytic and semi--analytic approximations
which are highly accurate on all angular scales for which linear perturbation
theory applies. A single power spectrum can be calculated in ~ 1 second on a
desktop computer. We discuss applications to cosmological parameter estimation.


  We have recently completed a detailed scan of the 19-dimensional parameter
space of the phenomenological MSSM, i.e., the CP-conserving MSSM assuming
Minimal Flavor Violation(MFV) with the first two sfermion generations
degenerate. We found a large set of parameter space points that satisfied all
of the existing experimental and theoretical constraints. This analysis allows
us to examine the general features of the MSSM without reference to any
particular SUSY breaking scenario or any other assumptions about physics at
higher scales. This study opens up new possibilities for SUSY phenomenology
both at colliders and in astrophysical observations.


  The largest Lyapunov exponent $\lambda^+$ for a dilute gas with short range
interactions in equilibrium is studied by a mapping to a clock model, in which
every particle carries a watch, with a discrete time that is advanced at
collisions. This model has a propagating front solution with a speed that
determines $\lambda^+$, for which we find a density dependence as predicted by
Krylov, but with a larger prefactor. Simulations for the clock model and for
hard sphere and hard disk systems confirm these results and are in excellent
mutual agreement. They show a slow convergence of $\lambda^+$ with increasing
particle number, in good agreement with a prediction by Brunet and Derrida.


  A brief reference to the two Schwarzschild solutions and what Petrov had to
say about them is given. Comments on how the Schwarzschild vacuum solution
describes a black hole are also provided. Then we compare the properties,
differences and similarities between black holes and quasiblack holes. Black
holes are well known. Quasiblack hole is a new concept. A quasiblack hole,
either nonextremal or extremal, can be broadly defined as the limiting
configuration of a body when its boundary approaches the body's own
gravitational radius (the quasihorizon). They are objects that are on the verge
of being black holes but actually are distinct from them in many ways. We
display some of their properties: there are infinite redshift whole regions;
the curvature invariants remain perfectly regular everywhere, in the quasiblack
hole limit; a free-falling observer finds in his own frame infinitely large
tidal forces in the whole inner region, showing some form of degeneracy; outer
and inner regions become mutually impenetrable and disjoint, although, in
contrast to the usual black holes, this separation is of a dynamical nature,
rather than purely causal; for external far away observers the spacetime is
virtually indistinguishable from that of extremal black holes. Other important
properties, such as the mass formula, and the entropy, are also discussed and
compared to the corresponding properties of black holes.


  Thermal rate coefficients for the astrochemical reaction C + CH$^+$ $\to$
C$_2^+$ + H were computed in the temperature range 20-300 K by using novel rate
theory based on ring polymer molecular dynamics (RPMD) on a recently published
bond-order based potential energy surface and compared with previous Langevin
capture model (LCM) and quasi-classical trajectory (QCT) calculations. Results
show that there is a significant discrepancy between the RPMD rate coefficients
and the previous theoretical results which can lead to overestimation of the
rate coefficients for the title reaction by several orders of magnitude at very
low temperatures. We argue that this can be attributed to a very challenging
energy profile along the reaction coordinate for the title reaction, not taken
into account in extenso by either the LCM or QCT approximation. In the absence
of any rigorous quantum mechanical or experimental results, the computed RPMD
rate coefficients represent state-of-the-art estimates to be included in
astrochemical databases and kinetic networks.


  SrMnSb$_2$ is suggested to be a magnetic topological semimetal. It contains
square, 2D Sb planes with non-symmorphic crystal symmetries that could protect
band crossings, offering the possibility of a quasi-2D, robust Dirac semi-metal
in the form of a stable, bulk (3D) crystal. Here, we report a combined and
comprehensive experimental and theoretical investigation of the electronic
structure of SrMnSb$_2$, including the first ARPES data on this compound.
SrMnSb$_2$ possesses a small Fermi surface originating from highly 2D, sharp
and linearly dispersing bands (the Y-states) around the (0,$\pi$/a)-point in
$k$-space. The ARPES Fermi surface agrees perfectly with that from
bulk-sensitive Shubnikov de Haas data from the same crystals, proving the
Y$-$states to be responsible for electrical conductivity in SrMnSb$_2$. DFT and
tight binding (TB) methods are used to model the electronic states, and both
show good agreement with the ARPES data. Despite the great promise of the
latter, both theory approaches show the Y-states to be gapped above E$_F$,
suggesting trivial topology. Subsequent analysis within both theory approaches
shows the Berry phase to be zero, indicating the non-topological character of
the transport in SrMnSb$_2$, a conclusion backed up by the analysis of the
quantum oscillation data from our crystals.


  Massive stars at redshifts z > 6 are predicted to have played a pivotal role
in cosmological reionization as luminous sources of ultra-violet (UV) photons.
However, the remnants of these massive stars could be equally important as
X-ray luminous (L_X 1e38 erg/s) high-mass X-ray binaries (HMXBs). Because the
absorption cross section of neutral hydrogen decreases sharply with photon
energy (proportional to the inverse cube), X-rays can escape more freely than
UV photons from the star-forming regions in which they are produced, allowing
HMXBs to make a potentially significant contribution to the ionizing X-ray
background during reionization. In this paper, we explore the ionizing power of
HMXBs at redshifts z > 6 using a Monte Carlo model for a coeval stellar
population of main sequence stars and HMXBs. Using the archetypal Galactic HMXB
Cygnus X-1 as our template, we propose a composite HMXB spectral energy
distribution consisting of black-body and power-law components, whose
contributions depend on the accretion state of the system. We determine the
time-dependent ionizing power of a combined population of UV-luminous stars and
X-ray luminous HMXBs, and deduce fitting formulae for the boost in the
population's ionizing power arising from HMXBs; these fits allow for simple
implementation of HMXB feedback in numerical simulations. Based on this
analysis, we estimate the contribution of high redshift HMXBs to the
present-day soft X-ray background, and we show that it is a factor of ~100-1000
smaller than the observed limit. Finally, we discuss the implications of our
results for the role of HMXBs in reionization and in high redshift galaxy
formation.


  Fault-tolerant distributed systems offer high reliability because even if
faults in their components occur, they do not exhibit erroneous behavior.
Depending on the fault model adopted, hardware and software errors that do not
result in a process crashing are usually not tolerated. To tolerate these
rather common failures the usual solution is to adopt a stronger fault model,
such as the arbitrary or Byzantine fault model. Algorithms created for this
fault model, however, are considerably more complex and require more system
resources than the ones developed for less strict fault models. One approach to
reach a middle ground is the non-malicious arbitrary fault model. This model
assumes it is possible to detect and filter faults with a given probability, if
these faults are not created with malicious intent, allowing the isolation and
mapping of these faults to benign faults. In this paper we describe how we
incremented an implementation of active replication in the non-malicious fault
model with a basic type of distributed validation, where a deviation from the
expected algorithm behavior will make a process crash. We experimentally
evaluate this implementation using a fault injection framework showing that it
is feasible to extend the concept of non-malicious failures beyond hardware
failures.


  Biomolecular networks have to perform their functions robustly. A robust
function may have preferences in the topological structures of the underlying
network. We carried out an exhaustive computational analysis on network
topologies in relation to a patterning function in Drosophila embryogenesis. We
found that while the vast majority of topologies can either not perform the
required function or only do so very fragilely, a small fraction of topologies
emerges as particularly robust for the function. The topology adopted by
Drosophila, that of the segment polarity network, is a top ranking one among
all topologies with no direct autoregulation. Furthermore, we found that all
robust topologies are modular--each being a combination of three kinds of
modules. These modules can be traced back to three sub-functions of the
patterning function and their combinations provide a combinatorial variability
for the robust topologies. Our results suggest that the requirement of
functional robustness drastically reduces the choices of viable topology to a
limited set of modular combinations among which nature optimizes its choice
under evolutionary and other biological constraints.


  The study of entanglement in the symmetry sectors of a theory has recently
attracted a lot of attention since it provides better understanding of some
aspects of quantum many-body systems. In this paper, we extend this analysis to
the case of non-Hermitian models, in which the reduced density matrix $\rho_A$
may be non-positive definite and the entanglement entropy negative or even
complex. Here we examine in detail the symmetry-resolved entanglement in the
ground state of the non-Hermitian Su-Schrieffer-Heeger chain at the critical
point, a model that preserves particle number and whose scaling limit is a
$bc$-ghost non-unitary CFT. By combining bosonization techniques in the field
theory and exact lattice numerical calculations, we analytically derive the
charged moments of $\rho_A$ and $|\rho_A|$. From them, we can understand the
origin of the non-positiveness of $\rho_A$ and naturally define a
positive-definite reduced density matrix in each charge sector, which gives a
well-defined symmetry-resolved entanglement entropy. As byproduct, we also
obtain the analytical distribution of the critical entanglement spectrum.


  Let X be a 1-connected space with free loop space LX. We introduce two
spectral sequences converging towards H^*(LX;Z/p) and H^*((LX)_hT;Z/p). The
E2-terms are certain non Abelian derived functors applied to H^*(X;Z/p). When
H^*(X;Z/p) is a polynomial algebra, the spectral sequences collapse for more or
less trivial reasons. If X is a sphere it is a surprising fact that the
spectral sequences collapse for p=2.


  Let $A_n$ be the $n$-th Weyl algebra, and let
$G\subset\Sp_{2n}(\C)\subset\Aut(A_n)$ be a finite group of linear
automorphisms of $A_n$. In this paper we compute the multiplicative structure
on the Hochschild cohomology $\HH^*(A_n^G)$ of the algebra of invariants of
$G$. We prove that, as a graded algebra, $\HH^*(A_n^G)$ is isomorphic to the
graded algebra associated to the center of the group algebra $\C G$ with
respect to a filtration defined in terms of the defining representation of $G$.


  A one-sided shift of finite type $(X_A,\sigma_A)$ determines on the one hand
a Cuntz-Krieger algebra $\mathcal{O}_A$ with a distinguished abelian subalgebra
$\mathcal{D}_A$ and a certain completely positive map $\tau_A$ on
$\mathcal{O}_A$. On the other hand, $(X_A,\sigma_A)$ determines a groupoid
$\mathcal{G}_A$ together with a certain homomorphism $\epsilon_A$ on
$\mathcal{G}_A$. We show that this data completely characterizes the one-sided
conjugacy class of $X_A$. This strengthens a result of Cuntz and Krieger. We
also exhibit an example of two irreducible shifts of finite type which are
eventually conjugate but not conjugate. This answers a question of Matsumoto of
whether eventual conjugacy implies conjugacy in the negative.


  Single crystals of EuPtSi$_3$, which crystallize in the BaNiSn$_3$-type
crystal structure, have been grown by high temperature solution growth method
using molten Sn as the solvent. EuPtSi$_3$ which lacks the inversion symmetry
and has only one Eu site in the unit cell is found to be an antiferromagnet
with two successive magnetic transitions at $T_{\rm N1}$ = 17 K and $T_{\rm
N2}$ = 16 K, as inferred from magnetic susceptibility, heat capacity and
$^{151}$Eu M\"ossbauer measurements. The isothermal magnetization data for $H
\parallel$ [001] reveal a metamagnetic transition at a critical field $H_{\rm
c}$ = 1 T. The magnetization saturates to a moment value of 6.43 $\mu_{\rm
B}$/Eu above 5.9 T (9.2 T) for $H \parallel $ [001] ([100]), indicating that
these fields are spin-flip fields for the divalent Eu moments along the two
axes. The origin of this anisotropic behaviour is discussed. A magnetic (H, T)
phase diagram has been constructed from the temperature dependence of
isothermal magnetization data. The reduced jump in the heat capacity at $T_{\rm
N1}$ indicates a transition to an incommensurate, amplitude modulated
antiferromagnetic structure. The shape of the hyperfine field split M\"ossbauer
spectrum at $T_{\rm N1}$ provides additional support for the proposed nature of
this magnetic transition.


  We introduce Reeb complexes in order to capture how generators of homology
flow along sections of a real valued continuous function. This intuition
suggests a close relation of Reeb complexes to established methods in
topological data analysis such as levelset zigzags and persistent homology. We
make this relation precise and in particular explain how Reeb complexes and
levelset zigzags can be extracted from the first pages of respective spectral
sequences with the same termination.


  A phenomenological model for the unbinding transition of multi-component
fluid membranes is proposed, where the unbinding transition is described using
a theory analogous to Flory-Huggins theory for polymers. The coupling between
the lateral phase separation of inclusion molecules and the membrane-substrate
distance explains the phase coexistence between two unbound phases as observed
in recent experiments by Marx et al. [Phys. Rev. Lett. 88, 138102 (2002)].
Bellow a critical end-point temperature, we find that the unbinding transition
becomes first-order for multi-component membranes.


  Malwares are becoming persistent by creating full- edged variants of the same
or different family. Malwares belonging to same family share same
characteristics in their functionality of spreading infections into the victim
computer. These similar characteristics among malware families can be taken as
a measure for creating a solution that can help in the detection of the malware
belonging to particular family. In our approach we have taken the advantage of
detecting these malware families by creating the database of these
characteristics in the form of n-grams of API sequences. We use various
similarity score methods and also extract multiple API sequences to analyze
malware effectively.


  The paper describes ergodic (with respect to the Haar measure) functions in
the class of all functions, which are defined on (and take values in) the ring
of p-adic integers, and which satisfy (at least, locally) Lipschitz condition
with coefficient 1. Equiprobable (in particular, measure-preserving) functions
of this class are described also. In some cases (and especially for p=2) the
descriptions are given by explicit formulae. Some of the results may be viewed
as descriptions of ergodic isometric dynamical systems on p-adic unit disk. The
study was motivated by the problem of pseudorandom number generation for
computer simulation and cryptography. From this view the paper describes
nonlinear congruential pseudorandom generators modulo M which produce stricly
periodic uniformly distributed sequences modulo M with maximal possible period
length (i.e., exactly M). Both the state change function and the output
function of these generators could be, e.g., meromorphic functions (in
particular, polynomials with rational, but not necessarily integer
coefficients, or rational functions), or compositions of arithmetical
operations (like addition, multiplication, exponentiation, raising to integer
powers, including negative ones) with standard computer operations, such as
bitwise logical operations (XOR, OR, AND, etc.). The linear complexity of the
produced sequences is also studied.


  The Cu nanowires were electrodeposited in polycarbonate track-etched (PCT)
membrane. SEM, TEM and XPS techniques were used to characterize the morphology,
structure and size of nanowires as well as chemical Composition. The absorption
spectrum of copper nanowires embedded in PCT was measured and calculated for
different incident angles and wavelengths. Our results showed that there is a
broad peak due to excitation surface plasmon at {\theta} = 70\degree for
wavelength {\lambda}= 730 nm. We applied the transfer matrix method and
Bruggeman homogenization formalism for optical modeling. The results of
absorption spectra showed that exist good agreement between the experimental
and our used model. The results of this work may be useful in study of surface
plasmon resonance of copper nanowires.


  Automated fact-checking based on machine learning is a promising approach to
identify false information distributed on the web. In order to achieve
satisfactory performance, machine learning methods require a large corpus with
reliable annotations for the different tasks in the fact-checking process.
Having analyzed existing fact-checking corpora, we found that none of them
meets these criteria in full. They are either too small in size, do not provide
detailed annotations, or are limited to a single domain. Motivated by this gap,
we present a new substantially sized mixed-domain corpus with annotations of
good quality for the core fact-checking tasks: document retrieval, evidence
extraction, stance detection, and claim validation. To aid future corpus
construction, we describe our methodology for corpus creation and annotation,
and demonstrate that it results in substantial inter-annotator agreement. As
baselines for future research, we perform experiments on our corpus with a
number of model architectures that reach high performance in similar problem
settings. Finally, to support the development of future models, we provide a
detailed error analysis for each of the tasks. Our results show that the
realistic, multi-domain setting defined by our data poses new challenges for
the existing models, providing opportunities for considerable improvement by
future systems.


  It is known that the limiting gap distribution of the directions to visible
points in planar quasicrystals of cut-and-project type exists as a continuous
function $F(s)$. In this article we study the asymptotic behaviour of said
limiting gap distribution in the particular case of an Ammann--Beenker-like
quasicrystal $\mathcal{P}$; more precisely we show that in this case
$F(s)=C_{\mathcal{P}}s^{-2}+\mathcal{O}(s^{-17/8})$ as $s\to \infty$ with an
explicit constant $C_{\mathcal{P}}>0$.


  We call a (not necessarily planar) embedding of a graph $G$ in the plane
\emph{sequential} if its vertices lie in $\mathbb Z^2$ and the line segments
between adjacent vertices contain no interior integer points. In this note, we
prove (i) a graph $G$ has a sequential embedding if and only if $G$ is
4-colorable, and (ii) if $G$ is planar, then $G$ has a sequential planar
embedding.


  As a category of transfer learning, domain adaptation plays an important role
in generalizing the model trained in one task and applying it to other similar
tasks or settings. In speech enhancement, a well-trained acoustic model can be
exploited to obtain the speech signal in the context of other languages,
speakers, and environments. Recent domain adaptation research was developed
more effectively with various neural networks and high-level abstract features.
However, the related studies are more likely to transfer the well-trained model
from a rich and more diverse domain to a limited and similar domain. Therefore,
in this study, the domain adaptation method is proposed in unsupervised speech
enhancement for the opposite circumstance that transferring to a larger and
richer domain. On the one hand, the importance-weighting (IW) approach is
exploited with a variance constrained autoencoder to reduce the shift of shared
weights between the source and target domains. On the other hand, in order to
train the classifier with the worst-case weights and minimize the risk, the
minimax method is proposed. Both the proposed IW and minimax methods are
evaluated from the VOICE BANK and IEEE datasets to the TIMIT dataset. The
experiment results show that the proposed methods outperform the
state-of-the-art approaches.


  The reduced state of a small system strongly coupled to a charger in thermal
equilibrium may be athermal and used as a small battery once disconnected. By
harnessing the battery-charger correlations, the battery's extractable energy
can increase above the ergotropy. We introduce a protocol that uses a quantum
system as a memory that measures the charger and leaves the battery intact in
its charged state. Using the information gained from the measurement, the
daemonic ergotropy of the battery is extracted. Then the battery is reconnected
to the charger, thermalizing and charging it. However, the memory should return
to its initial standard state to close the thermodynamic cycle. Thus, on the
one hand, the work cost of the cycle is the sum of the disconnecting and
reconnecting battery-charger work plus the measurement and erasure work. On the
other hand, the extracted energy is the daemonic ergotropy of the battery plus
the ergotropy of the memory. The ratio of these quantities defines the
efficiency of the cycle. The protocol is exemplified by a modified transverse
spin 1/2 Ising chain, one spin functioning as the battery and the others as the
charger. The memory is another auxiliary spin 1/2. We found pairs of
measurement schemes from which we extract the same daemonic ergotropy from the
battery, they dissipate the same amount of energy, and one leaves the memory in
an active state, the other in a passive state. We study the memory's ergotropy
and the daemonic ergotropy of the battery. We find that with measurements, the
efficiency can surpass that of the unmeasured protocol, given conditions on
temperature, coupling, and choice of the measurement operators.


  Quantum states of light can enable sensing configurations with sensitivities
beyond the shot-noise limit (SNL). In order to better take advantage of
available quantum resources and obtain the maximum possible sensitivity, it is
necessary to determine fundamental sensitivity limits for different possible
configurations for a given sensing system. Here, due to their wide
applicability, we focus on optical resonance sensors, which detect a change in
a parameter of interest through a resonance shift. We compare their fundamental
sensitivity limits set by the quantum Cram\'er-Rao bound (QCRB) based on the
estimation of changes in transmission or phase of a probing bright two-mode
squeezed state (bTMSS) of light. We show that the fundamental sensitivity
results from an interplay between the QCRB and the transfer function of the
system. As a result, for a resonance sensor with a Lorentzian lineshape a
phase-based scheme outperforms a transmission-based one for most of the
parameter space; however, this is not the case for lineshapes with steeper
slopes, such as higher order Butterworth lineshapes. Furthermore, such an
interplay results in conditions under which the phase-based scheme provides a
higher sensitivity than the transmission-based one but a smaller degree of
quantum enhancement. We also study the effect of losses external to the sensor
on the degree of quantum enhancement and show that for certain conditions
probing with a classical state can provide a higher sensitivity than probing
with a bTMSS. Finally, we discuss detection schemes, namely optimized
intensity-difference and optimized homodyne detection, that can achieve the
fundamental sensitivity limits even in the presence of external losses.


  This paper establishes the necessary and sufficient conditions for the
reality of all the zeros in a polynomial sequence $\{P_i\}_{i=1}^{\infty}$
generated by a three-term recurrence relation $P_i(x)+ Q_1(x)P_{i-1}(x) +Q_2(x)
P_{i-2}(x)=0$ with the standard initial conditions $P_{0}(x)=1, P_{-1}(x)=0,$
where $Q_1(x)$ and $Q_2(x)$ are arbitrary real polynomials.


  Numerical simulations of the inflationary dynamics are presented here for a
single canonical scalar field minimally coupled to gravity. We spell out the
basic equations governing the inflationary dynamics in terms of cosmic time $t$
and define a set of dimensionless variables convenient for numerical analysis.
We then provide a link to our simple numerical Python code on GitHub that can
be used to simulate the background dynamics as well as the evolution of linear
perturbations during inflation. The code computes both scalar and tensor power
spectra for a given inflaton potential $V(\phi)$. We discuss a concrete
algorithm to use the code for various purposes, especially for computing the
enhanced scalar power spectrum in the context of Primordial Black Holes and
scalar-induced Gravitational Waves. We also compare the efficiency of different
variables used in the literature to compute the scalar fluctuations. We intend
to extend the framework to simulate the dynamics of a number of different
quantities, including the computation of scalar-induced second-order tensor
power spectrum in the near future.