  After a discussion on the state of local equilibrium with temperature
inhomogeneity, comparing mixture state reprsentation in statistical mechanics
and pure state representation in thermo field dynamics, a simple model is
solved to show that a reversible equation of motion with the initial condition
having inhomogeneous temperature can lead to irreversible, viz. diffusive,
behaviour. Yet, the solution is time symmetric exhibiting diffusion both
towards future and past.


  The most existing studies in the facial age estimation assume training and
test images are captured under similar shooting conditions. However, this is
rarely valid in real-world applications, where training and test sets usually
have different characteristics. In this paper, we advocate a cross-dataset
protocol for age estimation benchmarking. In order to improve the cross-dataset
age estimation performance, we mitigate the inherent bias caused by the
learning algorithm itself. To this end, we propose a novel loss function that
is more effective for neural network training. The relative smoothness of the
proposed loss function is its advantage with regards to the optimisation
process performed by stochastic gradient descent (SGD). Compared with existing
loss functions, the lower gradient of the proposed loss function leads to the
convergence of SGD to a better optimum point, and consequently a better
generalisation. The cross-dataset experimental results demonstrate the
superiority of the proposed method over the state-of-the-art algorithms in
terms of accuracy and generalisation capability.


  A matrix representation of the evolution operator associated with a nonlinear
stochastic flow with additive noise is used to compute its spectrum. In the
weak noise limit a perturbative expansion for the spectrum is formulated in
terms of local matrix representations of the evolution operator centered on
classical periodic orbits. The evaluation of perturbative corrections is easier
to implement in this framework than in the standard Feynman diagram
perturbation theory. The result are perturbative corrections to a stochastic
analog of the Gutzwiller semiclassical spectral determinant computed to several
orders beyond what has so far been attainable in stochastic and
quantum-mechanical applications.


  Matrix theory and its applications make wide use of the eigenprojections of
square matrices. The present paper demonstrates that the eigenprojection of a
matrix $A$ can be calculated with the use of any annihilating polynomial of
A^u, where u >= ind A. This enables one to find the components and the minimal
polynomial of A, as well as the Drazin inverse A^D.


  Exploring and understanding the functioning of the human brain is one of the
greatest challenges for current research. Neuromorphic engineering tries to
address this challenge by abstracting biological mechanisms and translating
them into technology. Via the abstraction process and experiments with the
resulting technical system, an attempt is made to obtain information about the
biological counterpart. One subsection of Neuromorphic Engineering (NE) are
Spiking Neural Networks (SNN), which describe the structures of the human brain
more and more closely than Artificial Neural Networks (ANN). Together with
their dedicated hardware, SNNs provide a good platform for developing new
algorithms for information processing. In the context of these neuromorphic
hardware platforms, this paper aims to develop an interface for a digital
hardware platform (SPINN-3 Development Board) to enable the use of industrial
or conventional sensors and thus create new approaches for experimental
research. The basis for this endeavor is a Field Programmable Gate Array
(FPGA), which is placed as a gateway between the sensors and the neuromorphic
hardware. Overall, the developed system provides a robust solution for a wide
variety of investigations related to neuromorphic hardware and SNNs.
Furthermore, the solution also offers suitable possibilities to monitor all
processes within the system in order to obtain suitable measurements, which can
be examined in search of meaningful results.


  Negative capacitance (NC) in ferroelectrics, which stems from the imperfect
screening of polarization, is considered a viable approach to lower voltage
operation in the field-effect transistors (FETs) used in logic switches. In
this paper, we discuss the implications of the transient nature of negative
capacitance for its practical application. It is suggested that the NC effect
needs to be characterized at the proper time scale to identify the type of
circuits where functional NC-FETs can be used effectively.


  At finite density parity can be spontaneously broken in strong interactions
with far reaching implications. In particular, a time-dependent pseudoscalar
background would modify QED by adding a Chern-Simons term to the lagrangian. As
a striking consequence we propose a novel explanation for the dilepton excess
observed in heavy ion collisions at low invariant masses. The presence of local
parity breaking due to a time-dependent pseudoscalar condensate substantially
modifies the dispersion relation of photons and vector mesons propagating in
such a medium, changing the $\rho$ spectral function and resulting in a
potentially large excess of dileptons with respect to the predictions based in
a `cocktail' of known processes.


  We investigate the interaction-induced superfluid-to-Mott insulator
transition in the one-dimensional Bose-Hubbard model (BHM) for fillings $n=1$,
$n=2$, and $n=3$ by studying the single-particle gap, the fidelity
susceptibility, and the amplitude of Bloch oscillations via density-matrix
renormalization-group methods. We apply a generic scaling procedure for the
gap, which allows us to determine the critical points with very high accuracy.
We also study how the fidelity susceptibility behaves across the phase
transition. Furthermore, we show that in the BHM, and in a system of spinless
fermions, the amplitude of Bloch oscillations after a tilt of the lattice
vanishes at the critical points. This indicates that Bloch oscillations can
serve as a tool to detect the transition point in ongoing experiments with
ultracold gases.


  We present the technical details on how large-scale structure (LSS) catalogs
are constructed from redshifts measured from spectra observed by the Dark
Energy Spectroscopic Instrument (DESI). The LSS catalogs provide the
information needed to determine the relative number density of DESI tracers as
a function of redshift and celestial coordinates and, e.g., determine
clustering statistics. We produce catalogs that are weighted subsamples of the
observed data, each matched to a weighted `random' catalog that forms an
unclustered sampling of the probability density that DESI could have observed
those data at each location.
  Precise knowledge of the DESI observing history and associated hardware
performance allows for a determination of the DESI footprint and the number of
times DESI has covered it at sub-arcsecond level precision. This enables the
completeness of any DESI sample to be modeled at this same resolution. The
pipeline developed to create LSS catalogs has been designed to easily allow
robustness tests and enable future improvements. We describe how it allows
ongoing work improving the match between galaxy and random catalogs, such as
including further information when assigning redshifts to randoms, accounting
for fluctuations in target density, accounting for variation in the redshift
success rate, and accommodating blinding schemes.


  The rapid growth of transformer-based models increases the concerns about
their integrity and ownership insurance. Watermarking addresses this issue by
embedding a unique identifier into the model, while preserving its performance.
However, most existing approaches require to optimize the weights to imprint
the watermark signal, which is not suitable at scale due to the computational
cost. This paper explores watermarks with virtually no computational cost,
applicable to a non-blind white-box setting (assuming access to both the
original and watermarked networks). They generate functionally equivalent
copies by leveraging the models' invariance, via operations like dimension
permutations or scaling/unscaling. This enables to watermark models without any
change in their outputs and remains stealthy. Experiments demonstrate the
effectiveness of the approach and its robustness against various model
transformations (fine-tuning, quantization, pruning), making it a practical
solution to protect the integrity of large models.


  The devil is in the detail: Periodic and aperiodic spin-state concentration
waves form during "Devil's staircase"-type spincrossover in a new bimetallic 2D
coordination polymer {Fe[(Hg(SCN)3)2](4,4'-bipy)2}n.The unprecedented
bimetallic 2D coordination polymer {Fe[(Hg(SCN)3)2](4,4'-bipy)2}n exhibits a
thermal high-spin (HS)$low-spin (LS) staircase-like conversion characterized by
a multi-step dependence of the HS molar fraction gHS. Between the fully HS
(gHS=1) and LS (gHS=0) phases, two steps associated with different ordering
appear in terms of spin-state concentration waves (SSCW). On the gHS=0.5 step,
a periodic SSCW forms with a HS-LS-HS-LS sequence. On the gHS=0.34 step, the 4D
superspace crystallography structural refinement reveals an aperiodic SSCW,
with a HS-LS sequence incommensurate with the molecular lattice. The formation
of these different long-range spatially ordered structures of LS and HS states
during the multi-step spin-crossover is discussed within the framework of
"Devil's staircase"-type transitions. Spatially modulated phases are known in
various types of materials but are uniquely related to molecular HS/LS
bistability in this case.


  In low-energy effective string theory and modified gravity theories, the
propagating speed $c_T$ of primordial gravitational waves may deviate from
unity. We find that the step-like variation of $c_T$ during slow-roll inflation
may result in an oscillating modulation to the B-mode polarization spectrum,
which can hardly be imitated by adjusting other cosmological parameters, and
the intensity of the modulation is determined by the dynamics of $c_T$. Thus
provided that the foreground contribution is under control, high-precision CMB
polarization observations will be able to put tight constraint on the variation
of $c_T$, and so the corresponding theories.


  In this paper we describe splitting methods for solving Levitron, which is
motivated to simulate magnetostatic traps of neutral atoms or ion traps. The
idea is to levitate a magnetic spinning top in the air repelled by a base
magnet.
  The main problem is the stability of the reduced Hamiltonian, while it is not
defined at the relative equilibrium. Here it is important to derive stable
numerical schemes with high accuracy. For the numerical studies, we propose
novel splitting schemes and analyze their behavior. We deal with a Verlet
integrator and improve its accuracy with iterative and extrapolation ideas.
Such a Hamiltonian splitting method, can be seen as geometric integrator and
saves computational time while decoupling the full equation system.
  Experiments based on the Levitron model are discussed.


  Rotational modulation of stellar light curves due to dark spots encloses
information on spot properties and, thus, on magnetic activity. In particular,
the decay of the autocorrelation function (ACF) of light curves is presumed to
be linked to spot/active-region lifetimes, given that some coherence of the
signal is expected throughout their lifetime. In the literature, an exponential
decay has been adopted to describe the ACF. Here, we investigate the relation
between the ACF and the active-region lifetimes. For this purpose, we produce
artificial light curves of rotating spotted stars with different observation,
stellar, and spot properties. We find that a linear decay and respective
timescale better represent the ACF than the exponential decay. We therefore
adopt a linear decay. The spot/active-region timescale inferred from the ACF is
strongly restricted by the observation length of the light curves. For 1-year
light curves our results are consistent with no correlation between the
inferred and the input timescales. The ACF decay is also significantly affected
by differential rotation and spot evolution: strong differential rotation and
fast spot evolution contribute to a more severe underestimation of the
active-region lifetimes. Nevertheless, in both circumstances the observed
timescale is still correlated with the input lifetimes. Therefore, our analysis
suggests that the ACF decay can be used to obtain a lower limit of the
active-region lifetimes for relatively long-term observations. However,
strategies to avoid or flag targets with fast active-region evolution or
displaying stable beating patterns associated with differential rotation should
be employed.


  A fundamental challenge to our current understanding of metals is the
frequent observation of qualitative departures from Fermi liquid behavior. The
standard view attributes such non-Fermi liquid phenomena to the scattering of
electrons off quantum critical fluctuations of an underlying order parameter.
While the possibility of non-Fermi liquid behavior isolated from the border of
magnetism has long been speculated, no experimental confirmation has been made.
Here we report on the observation of a strange metal region in the absence of a
magnetic instability in an ultrapure single crystal. In particular, we show
that the heavy fermion superconductor $\beta$-YbAlB$_4$ forms a possible phase
with strange metallic behavior across an extensive pressure regime, distinctly
separated from a high-pressure magnetic quantum phase transition by a Fermi
liquid phase.


  Most of the previous studies on the well-known Gray-Scott model view it as an
irreversible chemical reaction system. In this paper, we derive a four-species
reaction-diffusion system using the energetic variational approach based on the
law of mass action. This is a reversible Gray-Scott type model, which has a
natural entropy structure. We establish the local well-posedness of this
system, and justify the limit to the corresponding irreversible Gray-Scott type
system as some backward coefficients tend to zero. Furthermore, under some
smallness assumption on the initial data, we obtain the global-in-time
existence of classical solutions of the reversible system.


  Quantile regression is used to study effects of covariates on a particular
quantile of the data distribution. Here we are interested in the question
whether a covariate has any effect on the entire data distribution, i.e., on
any of the quantiles. To this end, we treat all the quantiles simultaneously
and consider global tests for the existence of the covariate effect in the
presence of nuisance covariates. This global quantile regression can be used as
the extension of linear regression or as the extension of distribution
comparison in the sense of Kolmogorov-Smirnov test. The proposed method is
based on pointwise coefficients, permutations and global envelope tests. The
global envelope test serves as the multiple test adjustment procedure under the
control of the family-wise error rate and provides the graphical interpretation
which automatically shows the quantiles or the levels of categorical covariate
responsible for the rejection. The Freedman-Lane permutation strategy showed
liberality of the test for extreme quantiles, therefore we propose four
alternatives that work well even for extreme quantiles and are suitable in
different conditions. We present a simulation study to inspect the performance
of these strategies, and we apply the chosen strategies to two data examples.


  The Maximum Balanced Subgraph Problem (MBSP) is the problem of finding a
subgraph of a signed graph that is balanced and maximizes the cardinality of
its vertex set. We are interested in the exact solution of the problem: an
improved version of a branch-and-cut algorithm is proposed. Extensive
computational experiments are carried out on a set of instances from three
applications previously discussed in the literature as well as on a set of
random instances.


  Based on a recent experimental determination of the static polarizability and
a first-principles calculation of the frequency-dependent dipole polarizability
of argon, this work presents, by use of a Fabry-P\'erot refractometer operated
at 1550 nm, a realization of the SI unit of pressure, the pascal, for pressures
up to 100 kPa, with an uncertainty of [(0.98 mPa)$^2 + (5.8 \times 10^{-6} P)^2
+ (26\times10^{-12}P^2)^2]^{1/2}$. The work also presents a value of the molar
polarizability of N$_2$ at 1550 nm of 4.396572(26)$\times 10^{-6}$m$^{3}$/mol,
which agrees well with previously determined ones in the literature.


  Recently, 2D convolution has been found unqualified in sound event detection
(SED). It enforces translation equivariance on sound events along frequency
axis, which is not a shift-invariant dimension. To address this issue, dynamic
convolution is used to model the frequency dependency of sound events. In this
paper, we proposed the first full-dynamic method named \emph{full-frequency
dynamic convolution} (FFDConv). FFDConv generates frequency kernels for every
frequency band, which is designed directly in the structure for
frequency-dependent modeling. It physically furnished 2D convolution with the
capability of frequency-dependent modeling. FFDConv outperforms not only the
baseline by 6.6\% in DESED real validation dataset in terms of PSDS1, but
outperforms the other full-dynamic methods. In addition, by visualizing
features of sound events, we observed that FFDConv could effectively extract
coherent features in specific frequency bands, consistent with the vocal
continuity of sound events. This proves that FFDConv has great
frequency-dependent perception ability.


  French recommendations for the screening of hepatitis B virus (HBV) infection
were updated in 2019 with the association of three markers: HBs Ag, anti-HBs Ab
and anti-HBc Ab. These three markers allow identification of infected patients,
vaccinated patients and patients who have been in contact with HBV. A positive
HBs Ag is usually associated with HBV infection but this interpretation must
take into account the clinical context. In particular, the absence of anti-HBc
Ab, normal ALAT levels and the absence of jaundice can be associated with
recent HBV vaccination or false-positive HBs Ag. Recent HBV vaccination can
usually be confirmed by patient questioning, while confirmatory tests are
useful to detect false positive HBs Ag. If necessary, a second sample can be
requested to confirm the interpretation.


  We present a new method for the optimization of large configuration
interaction (CI) expansions in the quantum Monte Carlo (QMC) framework. The
central idea here is to replace the non-orthogonal variational optimization of
CI coefficients performed in usual QMC calculations by an orthogonal
non-Hermitian optimization thanks to the so-called transcorrelated (TC)
framework, the two methods yielding the same results in the limit of a complete
basis set. By rewriting the TC equations as an effective self-consistent
Hermitian problem, our approach requires the sampling of a single quantity per
Slater determinant, leading to minimal memory requirements in the QMC code.
Using analytical quantities obtained from both the TC framework and the usual
CI-type calculations, we also propose improved estimators which reduce the
statistical fluctuations of the sampled quantities by more than an order of
magnitude. We demonstrate the efficiency of this method on wave functions
containing $10^5-10^6$ Slater determinants, using effective core potentials or
all-electron calculations. In all the cases, a sub-milliHartree convergence is
reached within only two or three iterations of optimization.


  We study real sequences $\{a_{n}\}_{n\in \mathbb{N}}$ that eventually agree
with a polynomial. We show that if the numerator polynomial of its rational
generating series is of degree $s$ and has only nonnegative coefficients, then
the numerator polynomial of the subsequence $\{ a_{rn+i}\}_{n\in \mathbb{N}}$,
$0\leq i<r$, has only nonpositive, real roots for all $r\geq s-i$. We apply our
results to combinatorially positive valuations on polytopes and to Hilbert
functions of Veronese submodules of graded Cohen-Macaulay algebras. In
particular, we prove that the Ehrhart $h^\ast$-polynomial of the $r$-th dilate
of a $d$-dimensional polytope has only distinct, negative, real roots if $r\geq
\min \{s+1,d\}$. This proves a conjecture of Beck and Stapledon (2010).


  Results of high resolution x-ray diffraction experiments are presented for
single crystals of the spin gap compound BaCuSi$_2$O$_6$ in the temperature
range from 16 to 300 K. The data show clear evidence of a transition from the
room temperature tetragonal phase into an incommensurately modulated
orthorhombic structure below $\sim$100 K. This lattice modulation is
characterized by a resolution limited wave vector {\bf
q}$_{IC}$=(0,$\sim$0.13,0) and its 2$^{nd}$ and 3$^{rd}$ harmonics. The phase
transition is first order and exhibits considerable hysteresis. This
observation implies that the spin Hamiltonian representing the system is more
complex than originally thought.


  High-energy cosmic rays are one of the primary sources of information for
scientists investigating the elementary properties of matter. The need to study
cosmic rays, with energies thousands of times larger than those encountered in
particle accelerators, led to the development of modern detection hardware and
experimental methodologies. We present a low power, low complexity data
acquisition (DAQ) system with 100 ps resolution, suitable for particle and
radiation detection experiments. The system uses a Multiple-Time-over-Threshold
(MToT) technique for the treatment of the output signal of Photo Multiplier
Tubes (PMTs). The use of three thresholds compensates for the slewing effects
and offers a more accurate measurement of the PMT pulses' width. For the
evaluation of the pulse the system uses comparators and a Time-to-Digital (TDC)
converter, whereas the pulses are time-stamped using the GPS signal. The
prototype card is analyzed for its noise behavior and is tested to verify its
performance. The system has been designed for the HEllenic LYceum Cosmic
Observatories Network (HELYCON) Extensive Air Showers (EAS) detector.


  A proof of quantumness is a method for provably demonstrating (to a classical
verifier) that a quantum device can perform computational tasks that a
classical device with comparable resources cannot. Providing a proof of
quantumness is the first step towards constructing a useful quantum computer.
There are currently three approaches for exhibiting proofs of quantumness: (i)
Inverting a classically-hard one-way function (e.g. using Shor's algorithm).
This seems technologically out of reach. (ii) Sampling from a
classically-hard-to-sample distribution (e.g. BosonSampling). This may be
within reach of near-term experiments, but for all such tasks known
verification requires exponential time. (iii) Interactive protocols based on
cryptographic assumptions. The use of a trapdoor scheme allows for efficient
verification, and implementation seems to require much less resources than (i),
yet still more than (ii).
  In this work we propose a significant simplification to approach (iii) by
employing the random oracle heuristic. (We note that we do not apply the
Fiat-Shamir paradigm.) We give a two-message (challenge-response) proof of
quantumness based on any trapdoor claw-free function. In contrast to earlier
proposals we do not need an adaptive hard-core bit property. This allows the
use of smaller security parameters and more diverse computational assumptions
(such as Ring Learning with Errors), significantly reducing the quantum
computational effort required for a successful demonstration.


  The Lyman-alpha forest at z >~ 5.5 shows strong scatter in the mean
transmission even when smoothed over very large spatial scales, >~ 50 Mpc/h.
This has been interpreted as a signature of strongly fluctuating radiation
fields, or patchy reionization. To test this claim, we calculate the scatter
arising solely from density fluctuations, with a uniform ionizing background,
using analytic arguments and simulations. This scatter alone is comparable to
that observed. It rises steeply with redshift and is of order unity by z ~ 6,
even on ~ 50 Mpc/h scales. This arises because: i) at z ~ 6, transmission
spectra, which are sensitive mainly to rare voids, are highly biased (with a
linear bias factor b >~ 4-5) tracers of underlying density fluctuations, and
ii) projected power from small-scale transverse modes is aliased to long
wavelength line-of-sight modes. Inferring patchy reionization from quasar
spectra is therefore subtle and requires much more detailed modeling.
Similarly, we expect order unity transmission fluctuations in the z ~ 3 HeII
Lyman-alpha forest from density fluctuations alone, on the scales over which
these measurements are typically made.


  Non-contrastive methods of self-supervised learning (such as BYOL and
SimSiam) learn representations by minimizing the distance between two views of
the same image. These approaches have achieved remarkable performance in
practice, but the theoretical understanding lags behind. Tian et al. 2021
explained why the representation does not collapse to zero, however, how the
feature is learned still remains mysterious. In our work, we prove in a linear
network, non-contrastive methods learn a desirable projection matrix and also
reduce the sample complexity on downstream tasks. Our analysis suggests that
weight decay acts as an implicit threshold that discards the features with high
variance under data augmentations, and keeps the features with low variance.
Inspired by our theory, we design a simpler and more computationally efficient
algorithm DirectCopy by removing the eigen-decomposition step in the original
DirectPred algorithm in Tian et al. 2021. Our experiments show that DirectCopy
rivals or even outperforms DirectPred on STL-10, CIFAR-10, CIFAR-100, and
ImageNet.


  We explicitly determine the automorphism groups of all self-similar trees
(a.k.a. trees with finitely many cone types). We show that any such
automorphism group is a direct limit of certain finite products of finite
symmetric groups, which are parametrized by a certain deterministic finite
automaton.


  We prove homological stability for both general linear groups of modules over
a ring with finite stable rank and unitary groups of quadratic modules over a
ring with finite unitary stable rank. In particular, we do not assume the
modules and quadratic modules to be well-behaved in any sense: for example, the
quadratic form may be singular. This extends results by van der Kallen and
Mirzaii--van der Kallen respectively. Combining these results with the
machinery introduced by Galatius--Randal-Williams to prove homological
stability for moduli spaces of simply-connected manifolds of dimension 2n > 4,
we get an extension of their result to the case of virtually polycyclic
fundamental groups.


  In this paper, we explore the concept of adding learn-able slope and mean
shift parameters to an activation function to improve the total response
region. The characteristics of an activation function depend highly on the
value of parameters. Making the parameters learn-able, makes the activation
function more dynamic and capable to adapt as per the requirements of its
neighboring layers. The introduced slope parameter is independent of other
parameters in the activation function. The concept was applied to ReLU to
develop Dual Line and DualParametric ReLU activation function. Evaluation on
MNIST and CIFAR10 show that the proposed activation function Dual Line achieves
top-5 position for mean accuracy among 43 activation functions tested with
LENET4, LENET5, and WideResNet architectures. This is the first time more than
40 activation functions were analyzed on MNIST andCIFAR10 dataset at the same
time. The study on the distribution of positive slope parameter beta indicates
that the activation function adapts as per the requirements of the neighboring
layers. The study shows that model performance increases with the proposed
activation functions


  In this paper, we address the problem of fair sharing of the total value of a
crowd-sourced network system between major participants (founders) and minor
participants (crowd) using cooperative game theory. Shapley allocation is
regarded as a fair way for computing the shares of all participants in a
cooperative game when the values of all possible coalitions could be
quantified. We define a class of value functions for crowd-sourced systems
which capture the contributions of the founders and the crowd plausibly and
derive closed-form expressions for Shapley allocations to both. These value
functions are defined for different scenarios, such as presence of oligopolies
or geographic spread of the crowd, taking network effects, including Metcalfe's
law, into account. A key result we obtain is that under quite general
conditions, the crowd participants are collectively owed a share between
$\frac{1}{2}$ to $\frac{2}{3}$ of the total value of the crowd-sourced system.
We close with an empirical analysis demonstrating consistency of our results
with the compensation offered to the crowd participants in some public internet
content sharing companies.


  The imaging performance of an optical microscope can be degraded by
sample-induced aberrations. A general strategy to undo the effect of these
aberrations is to apply wavefront correction with a deformable mirror (DM). In
most cases, the DM is placed conjugate to the microscope pupil, called pupil
adaptive optics (AO). When the aberrations are spatially variant, an
alternative configuration involves placing the DM conjugate to the main source
of aberrations, called conjugate AO. We provide theoretical and experimental
comparison of both configurations for the simplified case where spatially
variant aberrations are produced by a well defined phase screen. We pay
particular attention to the resulting correction field of view (FOV). Conjugate
AO is found to provide a significant FOV advantage. While this result is well
known in the astronomy community, our goal here is to recast it specifically
for the optical microscopy community.


  For the manufacturing of thin films of solution-processable organic
semiconductors, e.g. for organic photovoltaics (OPV), meniscus guided-coating
techniques are the method of choice for large-scale industrial applications.
However, the process requires an in-depth understanding of the respective fluid
dynamics to control the resulting film thickness. In this article, we derive an
analytical expression to describe the layer thickness of coatings manufactured
with a trapezoidal-shaped applicator as a function of various fluid and process
parameters. The analytical calculations are compared with results from
computational fluid dynamics (CFD) simulations and experimental data for an
industrially relevant OPV active material system. The analytical calculations
are compared with results from computational fluid dynamics (CFD) simulations
and experimental data for an industrially relevant OPV active material system.
The good agreement of all three approaches demonstrates the potential of the
analytical and simulative methods to reduce time- and resource-consuming
experiments to a minimum. Furthermore, our theoretical model can be used to
enhance the homogeneity of large-area coatings by means of an acceleration
profile of the applicator that can compensate the liquid loss during the
coating process. The respective analytical expression is validated by simulated
and experimentally obtained data for long-distance coatings. Finally, this
approach is used to fabricate a large-area OPV module with new world record
efficiency.


  The quantum stress-energy tensor of a massless scalar field propagating in
the two-dimensional Vaidya-de Sitter metric, which describes a classical model
spacetime for a dynamical evaporating black hole in an inflationary universe,
is analyzed. We present a possible way to obtain the Hawking radiation terms
for the model with arbitrary functions of mass. It is used to see how the
expansion of universe will affect the dynamical process of black hole
evaporation. The results show that the cosmological inflation has an
inclination to depress the black hole evaporation. However, if the cosmological
constant is sufficiently large then the back-reaction effect has the
inclination to increase the black hole evaporation. We also present a simple
method to show that it will always produce a divergent flux of outgoing
radiation along the Cauchy horizon where the curvature is a finite value. This
means that the Hawking radiation will be very large in there and shall modify
the classical spacetime drastically. Therefore the black hole evaporation
cannot be discussed self-consistently on the classical Vaidya-type spacetime.
Our method can also be applied to analyze the quantum stress-energy tensor in
the more general Vaidya-type spacetimes.


  If both Alice and Bob have access to a two-qubit "background state" then, by
simulating Everett's many worlds interpretation of measurement, Alice can
teleport a qubit to Bob, each using fixed unitaries. The Everett picture
unifies unitaries, measurements, and classical communication into just
unitaries, provided there are background states shared by all parties. We
review some of the literature on this theme and point out an additional fact:
If Bob has access to only one of the background qubits, teleportation is still
possible by Alice sending Bob one classical bit of information gained from a
measurement of the other qubit.


  We study the natural question of constructing pseudorandom generators (PRGs)
for low-degree polynomial threshold functions (PTFs). We give a PRG with
seed-length log n/eps^{O(d)} fooling degree d PTFs with error at most eps.
Previously, no nontrivial constructions were known even for quadratic threshold
functions and constant error eps. For the class of degree 1 threshold functions
or halfspaces, we construct PRGs with much better dependence on the error
parameter eps and obtain a PRG with seed-length O(log n + log^2(1/eps)).
Previously, only PRGs with seed length O(log n log^2(1/eps)/eps^2) were known
for halfspaces. We also obtain PRGs with similar seed lengths for fooling
halfspaces over the n-dimensional unit sphere.
  The main theme of our constructions and analysis is the use of invariance
principles to construct pseudorandom generators. We also introduce the notion
of monotone read-once branching programs, which is key to improving the
dependence on the error rate eps for halfspaces. These techniques may be of
independent interest.


  Linear mixed models (LMMs) are a powerful and established tool for studying
genotype-phenotype relationships. A limiting assumption of LMMs is that the
residuals are Gaussian distributed, a requirement that rarely holds in
practice. Violations of this assumption can lead to false conclusions and
losses in power, and hence it is common practice to pre-process the phenotypic
values to make them Gaussian, for instance by applying logarithmic or other
non-linear transformations. Unfortunately, different phenotypes require
different specific transformations, and choosing a "good" transformation is in
general challenging and subjective. Here, we present an extension of the LMM
that estimates an optimal transformation from the observed data. In extensive
simulations and applications to real data from human, mouse and yeast we show
that using such optimal transformations lead to increased power in genome-wide
association studies and higher accuracy in heritability estimates and phenotype
predictions.


  Recent results from the KLOE experiment at the DAPHNE e+e- collider are
presented. KLOE has collected about 500 pb^-1 of data in the years from 2000 to
2002. Preliminary results are obtained using wide samples of the full
statistics and include: the BR of the Ke3 decay of the K_S and the first
measurement of its charge asymmetry, the ratio
BR(K_S-->pi+pi-(gamma))/BR(K_S-->pi^0pi^0), the ratio
BR(K_L-->gammagamma)/BR(K_L-->3pi^0), a detailed study of the decay
phi-->pi+pi-pi^0, the ratio BR(phi-->eta' gamma)/BR(phi-->eta gamma) and the
pseudoscalar mixing angle phi_P, the phi-->f_0 gamma and the phi-->a_0 gamma
BR's.


  A model for stationary, radiatively driven winds from X--ray bursting neutron
stars is presented. General relativistic hydrodynamical and radiative transfer
equations are integrated from the neutron star surface outwards, taking into
account for helium nuclear burning in the inner, dense, nearly hydrostatic
shells. Radiative processes include both bremsstrahlung emission--absorption
and Compton scattering; only the frequency--integrated transport is considered
here. It is shown that each solution is characterized by just one parameter:
the mass loss rate $\Mdot$, or, equivalently, the envelope mass $\Menv$. We
found that, owing to the effects of Comptonization, steady, supersonic winds
can exist only for $\Mdot$ larger than a limiting value $\Mdot_{min}
\approx\Mdot_{E}$. Several models, covering about two decades in mass loss
rate, have been computed for given neutron star parameters. We discuss how the
sequence of our solutions with decreasing $\Menv$ can be used to follow the
time evolution of a strong X--ray burst during the expansion/contraction phase
near to the luminosity maximum. The comparison between our numerical results
and the observational data of Haberl {\it et al.\/} (1987) for the bursts in
4U/MXB 1820-30 gives an estimate for both the spectral hardening factor and the
accretion rate in this source.


  Hybrid MPI+threads programming is gaining prominence as an alternative to the
traditional "MPI everywhere'" model to better handle the disproportionate
increase in the number of cores compared with other on-node resources. Current
implementations of these two models represent the two extreme cases of
communication resource sharing in modern MPI implementations. In the
MPI-everywhere model, each MPI process has a dedicated set of communication
resources (also known as endpoints), which is ideal for performance but is
resource wasteful. With MPI+threads, current MPI implementations share a single
communication endpoint for all threads, which is ideal for resource usage but
is hurtful for performance.
  In this paper, we explore the tradeoff space between performance and
communication resource usage in MPI+threads environments. We first demonstrate
the two extreme cases---one where all threads share a single communication
endpoint and another where each thread gets its own dedicated communication
endpoint (similar to the MPI-everywhere model) and showcase the inefficiencies
in both these cases. Next, we perform a thorough analysis of the different
levels of resource sharing in the context of Mellanox InfiniBand. Using the
lessons learned from this analysis, we design an improved resource-sharing
model to produce \emph{scalable communication endpoints} that can achieve the
same performance as with dedicated communication resources per thread but using
just a third of the resources.


  These are the lecture notes of guest lectures for Artur Ekert's course
Introduction to Quantum Information at the Mathematical Institute of Oxford
University, Hilary Term 2023. Some basic familiarity with Dirac notation is
assumed. For the readers of Quantum in Pictures (QiP) who have some basic
quantum background, these notes also constitute the shortest path to an
explanation of how what they learn in QIP relates to the traditional quantum
formalism.


  A brief report on the QCD factorization approach to exclusive B decays and
its applications is presented. In an appendix a subtle issue concerning partial
integration in the parameterization of infrared-sensitive power corrections is
clarified.


  Recent works have impressively demonstrated that there exists a subnetwork in
randomly initialized convolutional neural networks (CNNs) that can match the
performance of the fully trained dense networks at initialization, without any
optimization of the weights of the network (i.e., untrained networks). However,
the presence of such untrained subnetworks in graph neural networks (GNNs)
still remains mysterious. In this paper we carry out the first-of-its-kind
exploration of discovering matching untrained GNNs. With sparsity as the core
tool, we can find \textit{untrained sparse subnetworks} at the initialization,
that can match the performance of \textit{fully trained dense} GNNs. Besides
this already encouraging finding of comparable performance, we show that the
found untrained subnetworks can substantially mitigate the GNN over-smoothing
problem, hence becoming a powerful tool to enable deeper GNNs without bells and
whistles. We also observe that such sparse untrained subnetworks have appealing
performance in out-of-distribution detection and robustness of input
perturbations. We evaluate our method across widely-used GNN architectures on
various popular datasets including the Open Graph Benchmark (OGB).


  Diffractive screens are high-resolution elements with capability for
generating holographic-like images from a sequence of planes where TV frames
are seen oblique to it. If we project a sequence of contour lines of an object
it could be seen in continuous horizontal parallax to a size of 1m3.


  We present the complete analytical result for the two-loop logarithmically
enhanced contributions to the high energy asymptotic behavior of the vector
form factor and the four-fermion cross section in a spontaneously broken SU(2)
gauge model. On the basis of this result we derive the dominant two-loop
electroweak corrections to the neutral current four-fermion processes at high
energies. Previously neglected effects of the gauge boson mass difference are
included through the next-to-next-to-leading logarithmic approximation.


  Pulsating variable $\delta$ Scuti stars are intermediate-mass stars with
masses in the range of $1-3$ $M_{\odot}$ and spectral types between $A2$ and
$F2$. They can be found at the intersection of the Cepheid instability strip
with the main sequence. They can be used as astrophysical laboratories to test
theories of stellar evolution and pulsation. In this contribution, we
investigate the observed period-colour and amplitude-colour (PCAC) relations at
maximum/mean/minimum light of Galactic bulge and Large Magellanic Cloud
$\delta$ Scuti stars for the first time and test the hydrogen ionization front
(HIF)-photosphere interaction theory using the MESA- RSP code. The PCAC
relations, as a function of pulsation phase, are crucial probes of the
structure of the outer stellar envelope and provide insight into the physics of
stellar pulsation and evolution. The observed behaviour of the $\delta$ Scuti
PCAC relations is consistent with the theory of the interaction between the HIF
and the stellar photosphere.


  We distinguish finitarily between algorithmic verifiability, and algorithmic
computability, to show that Goedel's 'formally' unprovable, but 'numeral-wise'
provable, arithmetical proposition [(Ax)R(x)] can be finitarily evidenced as:
algorithmically verifiable as 'always' true, but not algorithmically computable
as 'always' true. Hence, though [R(x)] is algorithmically verifiable as a
tautology, it is not algorithmically computable as a tautology by any Turing
machine, whether deterministic or non-deterministic. By interpreting the PvNP
problem arithmetically, rather than set-theoretically, we conclude that the
clkasses P and NP are not well-defined finitarily since it immediately follows
that SAT is neither in P nor in NP.


  We study the Kondo screening of a single magnetic impurity inside a
non-magnetic quantum corral located on the surface of a metallic host system.
We show that the spatial structure of the corral's eigenmodes lead to a
spatially dependent Kondo effect whose signatures are spatial variations of the
Kondo temperature, $T_K$. Moreover, we predict that the Kondo screening is
accompanied by the formation of multiple Kondo resonances with characteristic
spatial patterns. Our results open new possibilities to manipulate and explore
the Kondo effect by using quantum corrals.


  We study differential equations, describing interaction of electromagnetic
field with moving sidebars and surfaces, coming from integral electrodynamics
laws. It is shown that differential equations contain but the such features of
electromagnetic field as E, H, distributions of charges and currents, as well
as features of surfaces, to which sidebar is leaning, changing its form with a
time.


  The Pierre Auger Observatory is exploring the potential of the radio
detection technique to study extensive air showers induced by ultra-high energy
cosmic rays. The Auger Engineering Radio Array (AERA) addresses both
technological and scientific aspects of the radio technique. A first phase of
AERA has been operating since September 2010 with detector stations observing
radio signals at frequencies between 30 and 80 MHz. In this paper we present
comparative studies to identify and optimize the antenna design for the final
configuration of AERA consisting of 160 individual radio detector stations. The
transient nature of the air shower signal requires a detailed description of
the antenna sensor. As the ultra-wideband reception of pulses is not widely
discussed in antenna literature, we review the relevant antenna characteristics
and enhance theoretical considerations towards the impulse response of antennas
including polarization effects and multiple signal reflections. On the basis of
the vector effective length we study the transient response characteristics of
three candidate antennas in the time domain. Observing the variation of the
continuous galactic background intensity we rank the antennas with respect to
the noise level added to the galactic signal.


  Lasers with injected spin-polarized carriers show an outstanding performance
in both static and dynamic operation. In addition to the intensity response of
conventional lasers, without spin-polarized carriers, both intensity and
polarization of light can be exploited for optical communication in
spin-lasers. However, the polarization dynamics of spin-lasers under amplitude
modulation has been largely overlooked. Here we reveal, analytically and
numerically, a nontrivial polarization response that accompanies the well-known
intensity dynamics of a spin-laser under amplitude modulation. We evaluate the
polarization and intensity response under the same amplitude modulation, and
further assess the capability of such a polarization response in digital data
transfer with eye diagram simulations. Our results provide a more complete
understanding of the modulation response in spin-lasers and open up unexplored
opportunities in optical communication and spintronics.


  Suppose that a real nonatomic function space on $[0,1]$ is equipped with two
re\-arran\-ge\-ment-invariant norms $\|\cdot\|$ and $|||\cdot|||$. We study the
question whether or not the fact that $(X,\|\cdot\|)$ is isometric to
$(X,|||\cdot|||)$ implies that $\|f\|= |||f|||$ for all $f$ in $X$. We show
that in strictly monotone Orlicz and Lorentz spaces this is equivalent to
asking whether or not the norms are defined by equal Orlicz functions, resp.
Lorentz weights.
  We show that the above implication holds true in most rearrangement-invariant
spaces, but we also identify a class of Orlicz spaces where it fails. We
provide a complete description of Orlicz functions $\varphi \neq\psi$ with the
property that $L_\varphi$ and $L_\psi$ are isometric.


  We give a brief introduction to the Gauge Theory of Arbitrage. Treating a
calculation of Net Present Values (NPV) and currencies exchanges as a parallel
transport in some fibre bundle, we give geometrical interpretation of the
interest rate, exchange rates and prices of securities as a proper connection
components. This allows us to map the theory of capital market onto the theory
of quantized gauge field interacted with a money flow field. The gauge
transformations of the matter field correspond to a dilatation of security
units which effect is eliminated by a gauge transformation of the connection.
The curvature tensor for the connection consists of the excess returns to the
risk-free interest rate for the local arbitrage operation. Free quantum gauge
theory is equivalent to the assumption about the log-normal walks of assets
prices. In general case the consideration maps the capital market onto lattice
QED.


  The structured winds of single massive stars can be classified into two broad
groups: stochastic structure and organized structure. While the former is
typically identified with clumping, the latter is typically associated with
rotational modulations, particularly the paradigm of Co-rotating Interaction
Regions (CIRs). While CIRs have been explored extensively in the UV band, and
moderately in the X-ray and optical, here we evaluate radio variability from
CIR structures assuming free-free opacity in a dense wind. Our goal is to
conduct a broad parameter study to assess the observational feasibility, and to
this end, we adopt a phenomenological model for a CIR that threads an otherwise
spherical wind. We find that under reasonable assumptions, it is possible to
obtain radio variability at the 10% level. The detailed structure of the folded
light curve depends not only on the curvature of the CIR, the density contrast
of the CIR relative to the wind, and viewing inclination, but also on
wavelength. Comparing light curves at different wavelengths, we find that the
amplitude can change, that there can be phase shifts in the waveform, and the
the entire waveform itself can change. These characterstics could be exploited
to detect the presence of CIRs in dense, hot winds.


  Artificial intelligence (AI) based device identification improves the
security of the internet of things (IoT), and accelerates the authentication
process. However, existing approaches rely on the assumption that we can learn
all the classes from the training set, namely, closed-set classification. To
overcome the closed-set limitation, we propose a novel open set RF device
identification method to classify unseen classes in the testing set. First, we
design a specific convolution neural network (CNN) with a short-time Fourier
transforming (STFT) pre-processing module, which efficiently recognizes the
differences of feature maps learned from various RF device signals. Then to
generate a representation of known class bounds, we estimate the probability
map of the open-set via the OpenMax function. We conduct experiments on sampled
data and voice signal sets, considering various pre-processing schemes, network
structures, distance metrics, tail sizes, and openness degrees. The simulation
results show the superiority of the proposed method in terms of robustness and
accuracy.


  The extension of Majorana neutrino mass mechanism of the neutrinoless
double-beta decay ($0\nu\beta\beta$) with the inclusion of right-handed
leptonic and hadronic currents is revisited. While only the exchange of light
neutrinos is assumed, the $s_{1/2}$ and $p_{1/2}$-states of emitted electrons
as well as recoil corrections to the nucleon currents are taken into account.
Within the standard approximations the decay rate is factorized into a sum of
products of kinematical phase-space factors, nuclear matrix elements and the
fundamental parameters that characterize the lepton number violation. Unlike in
the previous treatments the induced pseudoscalar term of hadron current is
included, resulting in additional nuclear matrix elements. An improved
numerical computation of the phase-space factors is presented, based on the
exact Dirac wave functions of the $s_{1/2}$ and $p_{1/2}$ electrons with finite
nuclear size and electron screening taken into account. The dependence of
values of these phase-space factors on the different approximation schemes used
in evaluation of electron wave functions is discussed. The upper limits for
effective neutrino mass and the parameters $\langle\lambda\rangle$ and
$\langle\eta\rangle$ characterizing the right-handed current mechanism are
deduced from data on the $0\nu\beta\beta$-decay of $^{76}$Ge and $^{136}$Xe
using nuclear matrix elements calculated within the nuclear shell model and
quasiparticle random phase approximation. The differential decay rates, i.e.
the angular correlations and the single electron energy distributions for
various combinations of the total lepton number violating parameters that can
help to disentangle the possible mechanism are described and discussed.


  We consider the Vertex Cover problem in intersection graphs of axis-parallel
rectangles on the plane. We present two algorithms: The first is an EPTAS for
non-crossing rectangle families, rectangle families $\calR$ where $R_1
\setminus R_2$ is connected for every pair of rectangles $R_1,R_2 \in \calR$.
This algorithm extends to intersection graphs of pseudo-disks. The second
algorithm achieves a factor of $(1.5 + \varepsilon)$ in general rectangle
families, for any fixed $\varepsilon > 0$, and works also for the weighted
variant of the problem. Both algorithms exploit the plane properties of
axis-parallel rectangles in a non-trivial way.


  In this work we study the radiative corrections to the mass of the lightest
Higgs boson of the MSSM from three generations of Majorana neutrinos and
sneutrinos. The spectrum of the MSSM is augmented by three right handed
neutrinos and their supersymmetric partners. A seesaw mechanism of type I is
used to generate the physical neutrino masses and oscillations that we require
to be in agreement with present neutrino data. We present a full one-loop
computation of these Higgs mass corrections, and analyze in full detail their
numerical size in terms of both the MSSM and the new (s)neutrino parameters. A
critical discussion on the different possible renormalization schemes and their
implications is included.


  We prove a Desch-Schappacher type perturbation theorem for strongly
continuous and locally equicontinuous one-parameter semigroups which are
defined on a sequentially complete locally convex space.


  We develop an analog of classical oscillation theory for Sturm-Liouville
operators which, rather than measuring the spectrum of one single operator,
measures the difference between the spectra of two different operators.
  This is done by replacing zeros of solutions of one operator by weighted
zeros of Wronskians of solutions of two different operators. In particular, we
show that a Sturm-type comparison theorem still holds in this situation and
demonstrate how this can be used to investigate the finiteness of eigenvalues
in essential spectral gaps. Furthermore, the connection with Krein's spectral
shift function is established.


  The interplay between electrochemical surface charges and bulk
ferroelectricity in thin films gives rise to a continuum of coupled ferro-ionic
states. These states are exquisitely sensitive to chemical and electric
conditions at the surfaces, applied voltage, and oxygen pressure. Using the
analytical approach combining the Ginzburg-Landau-Devonshire description of the
ferroelectricity with Langmuir adsorption isotherm for the ions at the film
surface, we have studied the temperature-, time- and field- dependent
polarization changes and electromechanical response of the ferro-ionic states.
The responses are found to be inseparable in thermodynamic equilibrium and at
low frequencies of applied voltage. The states become separable in high
frequency dynamic mode due to the several orders of magnitude difference in the
relaxation times of ferroelectric polarization and surface ions charge density.
These studies provide an insight into dynamic behavior of nanoscale
ferroelectrics with open surface exposed to different kinds of
electrochemically active gaseous surrounding.


  We establish sufficient conditions for exponential convergence to a unique
quasi-stationary distribution in the total variation norm. These conditions
also ensure the existence and exponential ergodicity of the Q-process, the
process conditionned upon never being absorbed. The technique relies on a
coupling procedure that is related to Harris recurrence (for Markov Chains). It
applies to general continuous-time and continuous-space Markov processes. The
main novelty is that we modulate each coupling step depending both on a final
horizon of time (for survival) and on the initial distribution. By this way, we
could notably include in the convergence a dependency on the initial condition.
As an illustration, we consider a continuous-time birth-death process with
catastrophes and a diffusion process describing a (localized) population
adapting to its environment.


  The cyberthreat landscape is continuously evolving. Hence, continuous
monitoring and sharing of threat intelligence have become a priority for
organizations. Threat reports, published by cybersecurity vendors, contain
detailed descriptions of attack Tactics, Techniques, and Procedures (TTP)
written in an unstructured text format. Extracting TTP from these reports aids
cybersecurity practitioners and researchers learn and adapt to evolving attacks
and in planning threat mitigation. Researchers have proposed TTP extraction
methods in the literature, however, not all of these proposed methods are
compared to one another or to a baseline. \textit{The goal of this study is to
aid cybersecurity researchers and practitioners choose attack technique
extraction methods for monitoring and sharing threat intelligence by comparing
the underlying methods from the TTP extraction studies in the literature.} In
this work, we identify ten existing TTP extraction studies from the literature
and implement five methods from the ten studies. We find two methods, based on
Term Frequency-Inverse Document Frequency(TFIDF) and Latent Semantic Indexing
(LSI), outperform the other three methods with a F1 score of 84\% and 83\%,
respectively. We observe the performance of all methods in F1 score drops in
the case of increasing the class labels exponentially. We also implement and
evaluate an oversampling strategy to mitigate class imbalance issues.
Furthermore, oversampling improves the classification performance of TTP
extraction. We provide recommendations from our findings for future
cybersecurity researchers, such as the construction of a benchmark dataset from
a large corpus; and the selection of textual features of TTP. Our work, along
with the dataset and implementation source code, can work as a baseline for
cybersecurity researchers to test and compare the performance of future TTP
extraction methods.


  Oscillator phase noise has been shown to be one of the main performance
limiting factors in full-duplex systems. In this paper, we consider the problem
of self-interference cancellation with phase noise suppression in full-duplex
systems. The feasibility of performing phase noise suppression in full-duplex
systems in terms of both complexity and achieved gain is analytically and
experimentally investigated. First, the effect of phase noise on full-duplex
systems and the possibility of performing phase noise suppression are studied.
Two different phase noise suppression techniques with a detailed complexity
analysis are then proposed. For each suppression technique, both free-running
and phase locked loop based oscillators are considered. Due to the fact that
full-duplex system performance highly depends on hardware impairments,
experimental analysis is essential for reliable results. In this paper, the
performance of the proposed techniques is experimentally investigated in a
typical indoor environment. The experimental results are shown to confirm the
results obtained from numerical simulations on two different experimental
research platforms. At the end, the tradeoff between the required complexity
and the gain achieved using phase noise suppression is discussed.


  In this work, we developed a wearable, head-mounted device that automatically
calculates the precise Relative Afferent Pupillary Defect (RAPD) value of a
patient. The device consists of two RGB LEDs, two infrared cameras, and one
microcontroller. In the RAPD test, the parameters like LED on-off durations,
brightness level, and color of the light can be controlled by the user. Upon
data acquisition, a computational unit processes the data, calculates the RAPD
score and visualizes the test results with a user-friendly
interface.Multiprocessing methods used on GUI to optimize the processing
pipeline. We have shown that our head-worn instrument is easy to use, fast, and
suitable for early-diagnostics and screening purposes for various neurological
conditions such as RAPD, glaucoma, asymmetric glaucoma, and anisocoria.


  We examine the possibility of a confinement-deconfinement phase transition at
finite temperature in both parity invariant and topologically massive
three-dimensional quantum electrodynamics. We review an argument showing that
the Abelian version of the Polyakov loop operator is an order parameter for
confinement, even in the presence of dynamical electrons. We show that, in the
parity invariant case, where the tree-level Coulomb potential is logarithmic,
there is a Berezinskii-Kosterlitz-Thouless transition at a critical temperature
($T_c=e^2/8\pi+{\cal O}(e^4/m)$, when the ratio of the electromagnetic coupling
and the temperature to the electron mass is small). Above $T_c$ the electric
charge is not confined and the system is in a Debye plasma phase, whereas below
$T_c$ the electric charges are confined by a logarithmic Coulomb potential,
qualitatively described by the tree-level interaction. When there is a
topological mass, no matter how small, in a strict sense the theory is not
confining at any temperature; the model exhibits a screening phase, analogous
to that found in the Schwinger model and two-dimensional QCD with massless
adjoint matter. However, if the topological mass is much smaller than the other
dimensional parameters, there is a temperature for which the range of the
Coulomb interaction changes from the inverse topological mass to the inverse
electron mass. We speculate that this is a vestige of the BKT transition of the
parity-invariant system, separating regions with screening and deconfining
behavior.


  The shadows cast by non-rotating and rotating modified gravity (MOG) black
holes are determined by the two parameters mass $M$ and angular momentum
$J=Ma$. The sizes of the shadows cast by the spherically symmetric static
Schwarzschild-MOG and Kerr-MOG rotating black holes increase significantly as
the free parameter $\alpha$ is increased from zero. The Event Horizon Telescope
(EHT) shadow image measurements can determine whether Einstein's general
relativity is correct or whether it should be modified in the presence of
strong gravitational fields.


  We present a critical analysis of the Canonical approach to quantum gravity,
which relies on the ambiguity of implementing a space-time slicing on the
quantum level. We emphasize that such a splitting procedure is consistent only
if a real matter fluid is involved in the dynamics.


  It continues to be alleged that superluminal influences of any sort would be
inconsistent with special relativity for the following three reasons: (i) they
would imply the existence of a distinguished' frame; (ii) they would allow the
detection of absolute motion; and (iii) they would violate the relativity of
simultaneity. This paper shows that the first two objections rest upon very
elementary misunderstandings of Minkowski geometry and lingering Newtonian
intuitions about instantaneity. The third objection has a basis, but rather
than invalidating the notion of faster than light influences it points the way
to more general conceptions of simultaneity that could allow for quantum
nonlocality in a natural way.


  Radiography is often used to probe complex, evolving density fields in
dynamic systems and in so doing gain insight into the underlying physics. This
technique has been used in numerous fields including materials science, shock
physics, inertial confinement fusion, and other national security applications.
In many of these applications, however, complications resulting from noise,
scatter, complex beam dynamics, etc. prevent the reconstruction of density from
being accurate enough to identify the underlying physics with sufficient
confidence. As such, density reconstruction from static/dynamic radiography has
typically been limited to identifying discontinuous features such as cracks and
voids in a number of these applications.
  In this work, we propose a fundamentally new approach to reconstructing
density from a temporal sequence of radiographic images. Using only the robust
features identifiable in radiographs, we combine them with the underlying
hydrodynamic equations of motion using a machine learning approach, namely,
conditional generative adversarial networks (cGAN), to determine the density
fields from a dynamic sequence of radiographs. Next, we seek to further enhance
the hydrodynamic consistency of the ML-based density reconstruction through a
process of parameter estimation and projection onto a hydrodynamic manifold. In
this context, we note that the distance from the hydrodynamic manifold given by
the training data to the test data in the parameter space considered both
serves as a diagnostic of the robustness of the predictions and serves to
augment the training database, with the expectation that the latter will
further reduce future density reconstruction errors. Finally, we demonstrate
the ability of this method to outperform a traditional radiographic
reconstruction in capturing allowable hydrodynamic paths even when relatively
small amounts of scatter are present.


  We explore some experimentally testable predictions of an $SO(10)$ axion
model which includes two 10-plets of fermions in order to resolve the axion
domain wall problem. The axion symmetry can be safely broken after inflation,
so that the isocurvature perturbations associated with the axion field are
negligibly small. An unbroken gauge $Z_2$ symmetry in $SO(10)$ ensures the
presence of a stable WIMP-like dark matter, a linear combination of the
electroweak doublets in the fermion 10-plets and an $SO(10)$ singlet fermion
with mass $\sim 62.5 \; {\rm GeV}\; (1 \; {\rm TeV}) $ when it is mostly the
singlet (doublet) fermion, that co-exists with axion dark matter. We also
discuss gauge coupling unification, proton decay, inflation with non-minimal
coupling to gravity and leptogenesis. With the identification of the SM singlet
Higgs field in the $126$ representation of $SO(10)$ as inflaton, the magnetic
monopoles are inflated away, and we find $0.963 \lesssim n_s \lesssim 0.965$
and $0.003 \lesssim r \lesssim 0.036$, where $n_s$ and $r$ denote the scalar
spectral index and tensor-to-scalar ratio, respectively. These predictions can
be tested in future experiments such as CMB-S4.


  At the intersection of quantum computing and machine learning, this review
paper explores the transformative impact these technologies are having on the
capabilities of data processing and analysis, far surpassing the bounds of
traditional computational methods. Drawing upon an in-depth analysis of 32
seminal papers, this review delves into the interplay between quantum computing
and machine learning, focusing on transcending the limitations of classical
computing in advanced data processing and applications. This review emphasizes
the potential of quantum-enhanced methods in enhancing cybersecurity, a
critical sector that stands to benefit significantly from these advancements.
The literature review, primarily leveraging Science Direct as an academic
database, delves into the transformative effects of quantum technologies on
machine learning, drawing insights from a diverse collection of studies and
scholarly articles. While the focus is primarily on the growing significance of
quantum computing in cybersecurity, the review also acknowledges the promising
implications for other sectors as the field matures. Our systematic approach
categorizes sources based on quantum machine learning algorithms, applications,
challenges, and potential future developments, uncovering that quantum
computing is increasingly being implemented in practical machine learning
scenarios. The review highlights advancements in quantum-enhanced machine
learning algorithms and their potential applications in sectors such as
cybersecurity, emphasizing the need for industry-specific solutions while
considering ethical and security concerns. By presenting an overview of the
current state and projecting future directions, the paper sets a foundation for
ongoing research and strategic advancement in quantum machine learning.


  In this work, we introduce the challenging problem of joint multi-person pose
estimation and tracking of an unknown number of persons in unconstrained
videos. Existing methods for multi-person pose estimation in images cannot be
applied directly to this problem, since it also requires to solve the problem
of person association over time in addition to the pose estimation for each
person. We therefore propose a novel method that jointly models multi-person
pose estimation and tracking in a single formulation. To this end, we represent
body joint detections in a video by a spatio-temporal graph and solve an
integer linear program to partition the graph into sub-graphs that correspond
to plausible body pose trajectories for each person. The proposed approach
implicitly handles occlusion and truncation of persons. Since the problem has
not been addressed quantitatively in the literature, we introduce a challenging
"Multi-Person PoseTrack" dataset, and also propose a completely unconstrained
evaluation protocol that does not make any assumptions about the scale, size,
location or the number of persons. Finally, we evaluate the proposed approach
and several baseline methods on our new dataset.


  We demonstrate how to explore phase diagrams with automated and unsupervised
machine learning to find regions of interest for possible new phases. In
contrast to supervised learning, where data is classified using predetermined
labels, we here perform anomaly detection, where the task is to differentiate a
normal data set, composed of one or several classes, from anomalous data. Asa
paradigmatic example, we explore the phase diagram of the extended Bose Hubbard
model in one dimension at exact integer filling and employ deep neural networks
to determine the entire phase diagram in a completely unsupervised and
automated fashion. As input data for learning, we first use the entanglement
spectra and central tensors derived from tensor-networks algorithms for
ground-state computation and later we extend our method and use experimentally
accessible data such as low-order correlation functions as inputs. Our method
allows us to reveal a phase-separated region between supersolid and superfluid
parts with unexpected properties, which appears in the system in addition to
the standard superfluid, Mott insulator, Haldane-insulating, and density wave
phases.


  One way to characterize and understand HI-selected galaxies is to study their
metallicity properties. In particular, we show that the metallicity of
absorbers is a bivariate function of the HI column density (NHI) and the MgII
equivalent width (Wr(2796)). Thus, a selection upon Wr(2796) is not equivalent
to a HI selection for intervening absorbers. A direct consequence for damped
absorbers with NHI>20.3 from the bivariate metallicity distribution is that any
correlation between the metallicity [X/H] and velocity width (or Wr(2796))
arises from the HI cut and therefore can not be interpreted as a signature of
the mass-metallicity relation akin to normal field galaxies. Thus DLA samples
are intrinsically heterogeneous. On the other hand, a sample of MgII-selected
absorbers, which are statistically dominated by lowest NHI systems (sub-DLAs),
are found to have a more uniform metallicity distribution. We postulate that
the bivariate metallicity distribution can be explained by two different
physical origins of absorbers, namely sight-lines through the ISM of small
galaxies and sight-lines through out-flowing material.
  Several published results follow from this bivariate [X/H] distribution such
as (a) the two classes of DLAs, reported by Wolfe et al., and (b) the constant
dust-to-gas ratio for MgII-absorbers.


  Decoupling of c-quark loops in b-quark HQET is considered. The decoupling
coefficients for the HQET heavy-quark field and the heavy-light quark current
are calculated with the three-loop accuracy. The last result can be used to
improve the accuracy of extracting f_B from HQET lattice simulations (without
c-quark loops). The decoupling coefficient for the flavour-nonsinglet QCD
current with n antisymmetrized gamma-matrices is also obtained at three loops;
the result for the tensor current (n=2) is new.


  Insider threats have become reality for civilian firms such as Tesla, which
experienced sabotage and intellectual property theft, and Capital One, which
suffered from fraud. Even greater social impact was caused by the data breach
at the US Department of Defense, perpetrated by well-known attackers Chelsea
Manning and Edward Snowden, whose espionage and hacktivist activities are
widely known. The dramatic increase of such incidents in recent years and the
incalculable damage committed by insiders must serve as a warning for all
members of the cyber security community. It is no longer acceptable to continue
to underestimate the problem of insider threats. Firms, organizations,
institutions and governments need to lead and embrace a cultural change in
their security posture. Through the adoption of an Insider Threat Program that
engages all the strategic branches (including HR, Legal, Information Assurance,
Cyber Security and Intelligence), coordinated by the chief information security
officer and supported by c-level executive, it is possible to implement a
framework that can prevent, detect, and respond to disloyal and/or
unintentional insider threats. Hence, defending your enterprise from insider
threats is a vital part of information security best practices. It is essential
that your company highly valuable classified data and assets are protected from
its greatest threat: the enemy within the gates.


  We present a compact and robust transportable ultra-stable laser system with
minimum fractional frequency instability of $1\times10^{-15}$ at integration
times between 1 to 10 s. The system was conceived as a prototype of a subsystem
of a microwave-optical local oscillator to be used on the satellite mission
STE-QUEST (Space-Time Explorer and QUantum Equivalence Principle Space Test,
http://sci.esa.int/ste-quest/). It was therefore designed to be compact, to
sustain accelerations occurring during rocket launch, to exhibit low vibration
sensitivity, and to reach a low frequency instability. Overall dimensions of
the optical system are $40\textrm{ cm}\times20\textrm{ cm}\times30\textrm{
cm}$. The acceleration sensitivities of the optical frequency in the three
directions were measured to be $1.7\times10^{-11}/g$, $8.0\times10^{-11}/g$,
and $3.9\times10^{-10}/g$, and the absolute frequency instability was
determined via a three-cornered hat measurement. The design is also appropriate
and useful for terrestrial applications.


  In this paper we investigate the numerical solution of stochastic partial
differential equations (SPDEs) for a wider class of stochastic equations. We
focus on non-diagonal colored noise instead of the usual space-time white
noise. By applying a spectral Galerkin method for spatial discretization and a
numerical scheme in time introduced by Jentzen $\&$ Kloeden, we obtain the rate
of path-wise convergence in the uniform topology. The main assumptions are
either uniform bounds on the spectral Galerkin approximation or uniform bounds
on the numerical data. Numerical examples illustrate the theoretically
predicted convergence rate.


  Block cipher ARIA was first proposed by some South Korean experts in 2003,
and later, it was established as a Korean Standard block cipher algorithm by
Korean Agency for Technology and Standards. In this paper, we focus on the
security evaluation of ARIA block cipher against the recent zero-correlation
linear cryptanalysis. In addition, Partial-sum technique and FFT (Fast Fourier
Transform) technique are used to speed up the cryptanalysis, respectively.
  We first introduce some 4-round linear approximations of ARIA with
zero-correlation, and then present some key-recovery attacks on 6/7-round
ARIA-128/256 with Partial-sum technique and FFT technique.The key-recovery
attack with Partial-sum technique on 6-round ARIA-128 needs 2^{123.6}known
plaintexts (KPs), 2^{121} encryptions and 2^{90.3} bytes memory, and the attack
with FFT technique requires 2^{124.1} KPs, 2^{121.5} encryptions and
2^{90.3}bytes memory. Moreover, applying Partial-sum technique, we can attack
7-round ARIA-256 with 2^{124.6} KPs, 2^{203.5} encryptions and 2^{152} bytes
and 7-round ARIA-256 employing FFT technique, requires 2^{124.7} KPs, 2^{209.5}
encryptions and 2^{152} bytes. Our results are the first zero-correlation
linear cryptanalysis results on ARIA.


  An updated classification scheme for transition O2-3.5If*/WN5-7 stars is
presented, following recent revisions to the spectral classifications for O and
WN stars. We propose that O2-3.5If*, O2-3.5If*/WN5-7 and WN5-7 stars may be
discriminated using the morphology of Hbeta to trace increasing wind density as
follows: purely in absorption for O2-3.5If* stars in addition to the usual
diagnostics from Walborn et al.; P Cygni for O2-3.5If*/WN5-7 stars; purely in
emission for WN stars in addition to the usual diagnostics from Smith et al. We
also discuss approximate criteria to discriminate between these subtypes from
near-IR spectroscopy. The physical and wind properties of such stars are
qualitatively discussed together with their evolutionary significance. We
suggest that the majority of O2-3.5If*/WN5-7 stars are young, very massive
hydrogen-burning stars, genuinely intermediate between O2-3.5If* and WN5-7
subtypes, although a minority are apparently core helium-burning stars evolving
blueward towards the classical WN sequence. Finally, we reassess
classifications for stars exhibiting lower ionization spectral features plus
Hbeta emission.


  Classical and recurrent nova explosions occur on top of white dwarfs
accreting H-rich matter from a companion main sequence or red giant star, in a
close binary system. In the recent years, since the launch of the Fermi
gamma-ray satellite by NASA in 2008, several novae have been detected by
Fermi/LAT (LAT: Large Area Telescope) in high-energy (HE) gamma rays, with
energies larger than 100 MeV. This emission is known to be related to the
acceleration of particles in the internal and/or external shocks occurring
early after the thermonuclear nova explosion. However, very-high-energy (VHE)
gamma-rays, with energies larger than 100 GeV, produced as a consequence of
nova explosions have only been discovered very recently, in the recurrent nova
RS Oph, that had an outburst in August 2021. These require the acceleration of
protons, and not only of electrons; this was in fact predicted theoretically -
based in observations at other wavelengths - in the previous eruption of RS
Oph, in 2006, but has not been confirmed observationally until now. We review
the origin of the different types of gamma-ray emission in novae and highlight
the relevance of the recent VHE gamma-ray emission discoveries for the nova
theory, mainly in the field of the mass ejection and the associated particle
(electrons and protons) acceleration processes.


  We clarify the argument on the how (nonlocal) degenerate Bell measurement can
be replaced by local measurements in the modified Lo-Chau quantum key
distribution protocol. Discussing security criterion for users, we describe how
eavesdropper's refined information on the final state is not helpful. We argue
that current discussions on the equivalence of the Bell and the local
measurements are not clear. We show how the problem of equivalence can be
resolved using the fact that eavesdropper's refined information is not helpful
for her.


  We give a new approach, inspired by H\"ormander's $L^2$-method, to weighted
variance inequalities which extend results obtained by Bobkov and Ledoux. It
provides in particular a local proof of the dimensional functional forms of the
Brunn-Minkowski inequalities. We also present several applications of these
variance inequalities, including reverse H\"older inequalities for convex
functions, weighted Brascamp-Lieb inequalities and sharp weighted Poincar\'{e}
inequalities for generalized Cauchy measures.


  We predict the distribution of hypervelocity stars (HVSs) ejected from the
Large Magellanic Cloud (LMC), under the assumption that the dwarf galaxy hosts
a central massive black hole (MBH). For the majority of stars ejected from the
LMC the orbital velocity of the LMC has contributed a significant fraction of
their galactic rest frame velocity, leading to a dipole density distribution on
the sky. We quantify the dipole using spherical harmonic analysis and contrast
with the monopole expected for HVSs ejected from the Galactic Center. There is
a tendril in the density distribution that leads the LMC which is coincident
with the well-known and unexplained clustering of HVSs in the constellations of
Leo and Sextans. Our model is falsifiable, since it predicts that Gaia will
reveal a large density of HVSs in the southern hemisphere.


  We derive the stationary fluctuations for the Facilitated Exclusion Process
(FEP) in one dimension in the symmetric, weakly asymmetric and asymmetric
cases. Our proof relies on the mapping between the FEP and the zero-range
process, and extends the strategy in \cite{erignoux2022mapping}, where
hydrodynamic limits were derived for the FEP, to its stationary fluctuations.
Our results thus exploit works on the zero-range process's fluctuations
\cite{gonccalves2010equilibrium,gonccalves2015stochastic}, but we also provide
a direct proof in the symmetric case, for which we derive a sharp estimate on
the equivalence of ensembles for the FEP's stationary states.


  Scene graph aims to faithfully reveal humans' perception of image content.
When humans analyze a scene, they usually prefer to describe image gist first,
namely major objects and key relations in a scene graph. This humans' inherent
perceptive habit implies that there exists a hierarchical structure about
humans' preference during the scene parsing procedure. Therefore, we argue that
a desirable scene graph should be also hierarchically constructed, and
introduce a new scheme for modeling scene graph. Concretely, a scene is
represented by a human-mimetic Hierarchical Entity Tree (HET) consisting of a
series of image regions. To generate a scene graph based on HET, we parse HET
with a Hybrid Long Short-Term Memory (Hybrid-LSTM) which specifically encodes
hierarchy and siblings context to capture the structured information embedded
in HET. To further prioritize key relations in the scene graph, we devise a
Relation Ranking Module (RRM) to dynamically adjust their rankings by learning
to capture humans' subjective perceptive habits from objective entity saliency
and size. Experiments indicate that our method not only achieves
state-of-the-art performances for scene graph generation, but also is expert in
mining image-specific relations which play a great role in serving downstream
tasks.


  Watermarking is crucial for protecting the copyright of AI-generated images.
We propose WMAdapter, a diffusion model watermark plugin that takes
user-specified watermark information and allows for seamless watermark
imprinting during the diffusion generation process. WMAdapter is efficient and
robust, with a strong emphasis on high generation quality. To achieve this, we
make two key designs: (1) We develop a contextual adapter structure that is
lightweight and enables effective knowledge transfer from heavily pretrained
post-hoc watermarking models. (2) We introduce an extra finetuning step and
design a hybrid finetuning strategy to further improve image quality and
eliminate tiny artifacts. Empirical results demonstrate that WMAdapter offers
strong flexibility, exceptional image generation quality and competitive
watermark robustness.


  We describe a model named No-Scale F-SU(5) which is simultaneously capable of
explaining the dual signals emerging at the LHC of i) a 124-126 GeV Higgs boson
mass m_h, and ii) tantalizing low-statistics excesses in the multi-jet data
which may attributable to supersymmetry. These targets tend to be mutually
exclusive in more conventional approaches. The unified mechanism responsible
for both effects is the introduction of a rather unique set of vector-like
multiplets at the TeV scale, dubbed flippons, which i) can elevate m_h by
around 3-4 GeV via radiative loop corrections, and ii) flatten the running of
the strong coupling and color-charged gaugino, resulting in a prominent
collider signal from production of light gluino pairs. This well motivated
theoretical framework maintains consistency with all key phenomenological
constraints, and all residual parameterization freedom may in principle be
fixed by a combination of the two experiments described. We project that the
already collected luminosity of 5 fb^-1 may be sufficient to definitively
establish the status of this model, given appropriate data selection cuts.


  We study the possibility of the scalar charmonium and glueball mixing in $e^+
e^-$ annihilation at $\sqrt{s}=10.6$ GeV. The effects can be used to explain
the unexpected large cross section ($12\pm 4$ fb) and the anomalous angular
distribution ($\alpha= -1.1^{+0.8}_{-0.6}$) of the exclusive $e^+e^-\to
J/\psi\chi_{c0}$ process observed by Belle experiments at KEKB. We calculate
the helicity amplitudes for the process $e^+ e^- \to J/\psi H(0^{++})$ in
NRQCD, where $H(0^{++})$ is the mixed state. We present a detailed analysis on
the total cross section and various angular asymmetries which could be useful
to reveal the existence of the scalar glueball state.


  Previous studies measuring the clustering of submillimeter galaxies (SMGs)
have based their measurements on single-dish detected sources, finding evidence
for strong clustering. However, ALMA has revealed that, due to the coarse
angular resolution of these instruments, single-dish sources can be comprised
of multiple sources. This implies that the clustering inferred from single-dish
surveys may be overestimated. Here, we measure the clustering of SMGs based on
the ALESS survey, an ALMA follow-up of sources previously identified in the
LABOCA ECDFS Submillimeter Survey (LESS). We present a method to measure the
clustering of ALMA sources that have been previously identified using
single-dish telescopes, based on forward modeling both the single-dish and the
ALMA observations. We constrain upper limits for the median mass of halos
hosting SMGs at $1<z<3$, finding
$M_{\rm{halo}}\leq2.4\times10^{12}\,\rm\,M_{\odot}$ for SMGs with flux
densities $S_{870}\geq4.0\,$mJy, which is at least $3.8^{+3.8}_{-2.6}$ times
lower than the mass inferred based on the clustering of the LESS sources alone.
This suggests that the strength of SMG clustering based on single-dish
observations was overestimated and therefore SMGs might be hosted by dark
matter halos less massive than has previously been estimated. By extrapolating
our models down to flux densities of $S_{870}\geq1.2\,\rm\,$mJy, we find that
such SMGs inhabit halos with median mass
$M_{\rm{halo}}\leq3.2\times10^{11}\,\rm\,M_{\odot}$. We conclude that only the
brightest ($S_{870}\gtrsim5-6\,\rm\,$mJy) SMGs would trace massive structures
at $z\sim2$ and only SMGs with $S_{870}\gtrsim6\,\rm\,$mJy may be connected to
massive local elliptical galaxies, quasars at intermediate redshifts and
high-redshift star-forming galaxies, whereas fainter SMGs are unlikely linked
to these populations.


  The atmospheric and solar neutrino problems can be explained in a
supersymmetric scenario where R-parity is broken bilinearly. Within this
context we explore the decays of the top squark. We find that the Rp violating
decay $\tilde t_1 -> b \tau$ can easily dominate over the Rp conserving decay
$\tilde t_1 -> c \tilde\chi^0_1$ and sometimes also over the decay $\tilde t_1
-> b \tilde\chi^+_1$. We study the implications of non-universal boundary
conditions at the GUT scale.


  We investigate dissipative nonlinear dynamics in graphene-based active
metamaterials composed of randomly dispersed graphene nano-flakes embedded
within an externally pumped gain medium. We observe that graphene saturable
nonlinearity produces a sub-critical bifurcation of nonlinear modes, enabling
self-organization of the emitted radiation into several dissipative soliton
structures with distinct topological charges. We systematically investigate the
existence domains of such nonlinear waves and their spatio-temporal dynamics,
finding that soliton vortices are unstable, thus enabling self-organization
into single dissipative structures with vanishing topological charge,
independently of the shape of the graphene nano-flakes. Our results shed light
on self-organization of coherent radiation structures in disordered systems and
are relevant for future cavity-free lasers and amplifier designs.


  Sponsored search in E-commerce platforms such as Amazon, Taobao and Tmall
provides sellers an effective way to reach potential buyers with most relevant
purpose. In this paper, we study the auction mechanism optimization problem in
sponsored search on Alibaba's mobile E-commerce platform. Besides generating
revenue, we are supposed to maintain an efficient marketplace with plenty of
quality users, guarantee a reasonable return on investment (ROI) for
advertisers, and meanwhile, facilitate a pleasant shopping experience for the
users. These requirements essentially pose a constrained optimization problem.
Directly optimizing over auction parameters yields a discontinuous, non-convex
problem that denies effective solutions. One of our major contribution is a
practical convex optimization formulation of the original problem. We devise a
novel re-parametrization of auction mechanism with discrete sets of
representative instances. To construct the optimization problem, we build an
auction simulation system which estimates the resulted business indicators of
the selected parameters by replaying the auctions recorded from real online
requests. We summarized the experiments on real search traffics to analyze the
effects of fidelity of auction simulation, the efficacy under various
constraint targets and the influence of regularization. The experiment results
show that with proper entropy regularization, we are able to maximize revenue
while constraining other business indicators within given ranges.


  We re-evaluate the constraints on the parameter space of the minimal
supersymmetric standard model from tunneling to charge- and/or color-breaking
minima, taking into account thermal corrections. We pay particular attention to
the region known as the Natural MSSM, where the masses of the scalar partners
of the top quarks are within an order of magnitude or so of the electroweak
scale. These constraints arise from the interaction between these scalar tops
and the Higgs fields, which allows the possibility of parameter points having
deep charge- and color-breaking true vacua. In addition to requiring that our
electro-weak-symmetry-breaking, yet QCD- and electromagnetism-preserving vacuum
has a sufficiently long lifetime at zero temperature, also demanding stability
against thermal tunneling further restricts the allowed parameter space.


  A hidden gauge theory structure of quantum mechanics which is invisible in
its conventional formulation is uncovered. Quantum mechanics is shown to be
equivalent to a certain Yang-Mills theory with an infinite-dimensional gauge
group and a nondynamical connection. It is defined over an arbitrary symplectic
manifold which constitutes the phase-space of the system under consideration.
The ''matter fields'' are local generalizations of states and observables; they
assume values in a family of local Hilbert spaces (and their tensor products)
which are attached to the points of phase-space. Under local frame rotations
they transform in the spinor representation of the metaplectic group Mp(2N),
the double covering of Sp(2N). The rules of canonical quantization are replaced
by two independent postulates with a simple group theoretical and differential
geometrical interpretation. A novel background-quantum split symmetry plays a
central role.


  Real-world datasets often contain outliers, and the presence of outliers can
make the clustering problems to be much more challenging. In this paper, we
propose a simple uniform sampling framework for solving three representative
center-based clustering with outliers problems: $k$-center/median/means
clustering with outliers. Our analysis is fundamentally different from the
previous (uniform and non-uniform) sampling based ideas. To explain the
effectiveness of uniform sampling in theory, we introduce a measure of
"significance" and prove that the performance of our framework depends on the
significance degree of the given instance. In particular, the sample size can
be independent of the input data size $n$ and the dimensionality $d$, if we
assume the given instance is "significant", which is in fact a fairly
reasonable assumption in practice. Due to its simplicity, the uniform sampling
approach also enjoys several significant advantages over the non-uniform
sampling approaches in practice. To the best of our knowledge, this is the
first work that systematically studies the effectiveness of uniform sampling
from both theoretical and experimental aspects.


  Entanglement is a key resource in many quantum information applications and
achieving high values independently of the initial conditions is an important
task. Here we address the problem of generating highly entangled states in a
discrete time quantum walk irrespective of the initial state using two
different approaches. First, we present and analyze a deterministic sequence of
coin operators which produces high values of entanglement in a universal manner
for a class of localized initial states. In a second approach, we directly
optimize the sequence of coin operators using a reinforcement learning
algorithm. While the amount of entanglement produced by the deterministic
sequence is fully independent of the initial states considered, the optimized
sequences achieve in general higher average values of entanglement that do
however depend on the initial state parameters. Our proposed sequence and
optimization algorithm are especially useful in cases where the initial state
is not fully known or entanglement has to be generated in a universal manner
for a range of initial states.


  We develop series expansions for the ground state properties of the Hubbard
model, by introducing an Ising anisotropy into the Hamiltonian. For the
two-dimensional (2D) square lattice half-filled Hubbard model, the ground state
energy, local moment, sublattice magnetization, uniform magnetic susceptibility
and spin stiffness are calculated as a function of $U/t$, where $U$ is the
Coulomb constant and $t$ is the hopping parameter. Magnetic susceptibility data
indicate a crossover around $U\approx 4$ between spin density wave
antiferromagnetism and Heisenberg antiferromagnetism. Comparisons with Monte
Carlo simulations, RPA result and mean field solutions are also made.


  Team and player evaluation in professional sport is extremely important given
the financial implications of success/failure. It is especially critical to
identify and retain elite shooters in the National Basketball Association
(NBA), one of the premier basketball leagues worldwide because the ultimate
goal of the game is to score more points than one's opponent. To this end we
propose two novel basketball metrics: "expected points" for team-based
comparisons and "expected points above average (EPAA)" as a player-evaluation
tool. Both metrics leverage posterior samples from Bayesian hierarchical
modeling framework to cluster teams and players based on their shooting
propensities and abilities. We illustrate the concepts for the top 100 shot
takers over the last decade and offer our metric as an additional metric for
evaluating players.


  Using the classical argument about tree level unitarity breakdown in
combination with the precision electroweak data, it is shown, that if part of
the Higgs sector is strongly interacting, this part is small and is out of
range of the LHC.


  This paper studies multi-antenna-aided covert communications coexisting with
randomly located wardens and interferers, considering both centralized and
distributed antenna systems (CAS/DAS). The throughput performance of the covert
communication is analyzed and optimized under a stochastic geometry framework,
where the joint impact of the small-scale channel fading and the large-scale
path loss is examined. To be specific, two probabilistic metrics, namely, the
covert outage probability and the connectivity probability, are adopted to
characterize the covertness and reliability of the transmission, respectively,
and analytically tractable expressions for the two metrics are derived. The
worst-case covert communication scenario is then investigated, {where the
wardens invariably can maximize the covert outage probability by adjusting the
detection thresholds for their detectors}. Afterwards, the optimal transmit
power and transmission rate are jointly designed to maximize the covert
throughput subject to a covertness constraint. Interestingly, it is found that
the maximal covert throughput for both the CAS and DAS is invariant to the
density of interferers and the interfering power, regardless of the number of
transmit antennas. Numerical results demonstrate that the CAS outperforms the
DAS in terms of the covert throughput for the random network of interest, and
the throughput gap between the two systems increases dramatically when the
number of transmit antennas becomes larger.