  The origin of Galactic cosmic rays remains a matter of debate, but supernova
remnants are commonly considered to be the main place where high-energy cosmic
rays are accelerated. Nevertheless, current models predict cosmic-ray spectra
that do not match observations and the efficiency of the acceleration mechanism
is still undetermined. On the other hand, the contribution of other kinds of
sources to the Galactic cosmic-ray population is still unclear, and merits
investigation. In this work we explore a novel mechanism through which
microquasars might produce cosmic rays. In this scenario, microquasar jets
generate relativistic neutrons, which escape and decay outside the system;
protons and electrons, created when these neutrons decay, escape to the
interstellar medium as cosmic rays. The most promising scenarios arise in
extremely luminous systems ($L_\mathrm{jet} \sim 10^{40}\,\mathrm{erg \,
s}^{-1}$), in which the fraction of jet power deposited in cosmic rays can
reach $\sim 0.001$. Slow jets ($\Gamma \lesssim 2$, where $\Gamma$ is the bulk
Lorentz factor) favour neutron production. The resulting cosmic-ray spectrum is
similar for protons and electrons, which share the power in the ratio given by
neutron decay. The spectrum peaks at roughly half the minimum energy of the
relativistic protons in the jet; it is soft (spectral index $\sim 3$) above
this energy, and almost flat below. Values of spectral index steeper than $2$
are possible for cosmic rays in our model and these indeed agree with those
required to explain the spectral signatures of Galactic cosmic rays, although
only the most extreme microquasars provide power comparable to that of a
typical supernova remnant. The mechanism explored in this work may provide
stronger and softer cosmic-ray sources in the early Universe, and therefore
contribute to the heating and reionisation of the intergalactic medium.


  We show that the angular range of the transmission through magnetic barrier
structures can be efficiently controlled in single-layer and bilayer graphenes
and this renders the structure's efficient wavevector filters. As the number of
magnetic barriers increases, this range shrinks, the gaps in the transmission
versus energy become wider, and the conductance oscillates with the Fermi
energy.


  In this paper, detection of deception attack on deep neural network (DNN)
based image classification in autonomous and cyber-physical systems is
considered. Several studies have shown the vulnerability of DNN to malicious
deception attacks. In such attacks, some or all pixel values of an image are
modified by an external attacker, so that the change is almost invisible to the
human eye but significant enough for a DNN-based classifier to misclassify it.
This paper first proposes a novel pre-processing technique that facilitates the
detection of such modified images under any DNN-based image classifier as well
as the attacker model. The proposed pre-processing algorithm involves a certain
combination of principal component analysis (PCA)-based decomposition of the
image, and random perturbation based detection to reduce computational
complexity. Next, an adaptive version of this algorithm is proposed where a
random number of perturbations are chosen adaptively using a doubly-threshold
policy, and the threshold values are learnt via stochastic approximation in
order to minimize the expected number of perturbations subject to constraints
on the false alarm and missed detection probabilities. Numerical experiments
show that the proposed detection scheme outperforms a competing algorithm while
achieving reasonably low computational complexity.


  We study the dynamics of an open membrane with a cylindrical topology, in the
background of a constant three form. We use the action, due to Bergshoeff,
London and Townsend, to study the noncommutativity properties of the boundary
string coordinates. The constrained Hamiltonian formalism due to Dirac is used
to derive the noncommutativity of coordinates. The chain of constraints is
found to be finite for a suitable gauge choice.


  Basic idea presented in Parts (I) and (II) for the deformed boson scheme is
applied to the case of the su(2,1)-algebra for describing many-body systems
consisting of three kinds of boson operators. A possible form of the coherent
state for the su(2,1)-algebra is generalized and the deformed su(2,1)-algebra
is presented. As an application, the time-evolution of the statistically mixed
state in a certain boson system, which has been already investigated by the
present authors, is reinvestigated.


  Proper training and analytics in eSports require accurately collected and
annotated data. Most eSports research focuses exclusively on in-game data
analysis, and there is a lack of prior work involving eSports athletes'
psychophysiological data. In this paper, we present a dataset collected from
professional and amateur teams in 22 matches in League of Legends video game
with more than 40 hours of recordings. Recorded data include the players'
physiological activity, e.g. movements, pulse, saccades, obtained from various
sensors, self-reported aftermatch survey, and in-game data. An important
feature of the dataset is simultaneous data collection from five players, which
facilitates the analysis of sensor data on a team level. Upon the collection of
dataset we carried out its validation. In particular, we demonstrate that
stress and concentration levels for professional players are less correlated,
meaning more independent playstyle. Also, we show that the absence of team
communication does not affect the professional players as much as amateur ones.
To investigate other possible use cases of the dataset, we have trained
classical machine learning algorithms for skill prediction and player
re-identification using 3-minute sessions of sensor data. Best models achieved
0.856 and 0.521 (0.10 for a chance level) accuracy scores on a validation set
for skill prediction and player re-id problems, respectively. The dataset is
available at https://github.com/smerdov/eSports Sensors Dataset.


  Two essential ingredients of modern mixed-integer programming (MIP) solvers
are diving heuristics that simulate a partial depth-first search in a
branch-and-bound search tree and conflict analysis of infeasible subproblems to
learn valid constraints. So far, these techniques have mostly been studied
independently: primal heuristics under the aspect of finding high-quality
feasible solutions early during the solving process and conflict analysis for
fathoming nodes of the search tree and improving the dual bound. Here, we
combine both concepts in two different ways. First, we develop a diving
heuristic that targets the generation of valid conflict constraints from the
Farkas dual. We show that in the primal this is equivalent to the optimistic
strategy of diving towards the best bound with respect to the objective
function. Secondly, we use information derived from conflict analysis to
enhance the search of a diving heuristic akin to classical coefficient diving.
The computational performance of both methods is evaluated using an
implementation in the source-open MIP solver SCIP. Experiments are carried out
on publicly available test sets including Miplib 2010 and Cor@l.


  The study of anisotropic harmonic flow coefficients $ v_{n}$(n=2,3,4) is
performed in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV under Monte Carlo
HYDJET++ model (HYDrodynamics plus JETs) framework. Anisotropic flow of
identified particles and correlation between the azimuthal harmonic flow
amplitudes is presented. Here, we have considered body-body and tip-tip type of
geometrical configurations for Xe-Xe collision systems. The kinematic ranges
$|\eta|<0.8$, $0<p_{T}<5.0$ GeV/c, and $|\delta / \eta|> 2$ are considered. The
results have been shown for seven classes of centrality and compared with the
ALICE experimental data. The anisotropic flow of identified charged particles
show a strong centrality dependence. Mass ordering is observed for
$v_{2},v_{3}$ and $v_{4}$. Mass ordering is different for different ranges of
transverse momentum $p_{T}$. Strong correlation is observed between
$v_{3}-v_{2}$, $v_{4}-v_{2}$, and $v_{4}-v_{3}$. Such correlation is centrality
dependent and is different in different centrality windows. The anisotropic
flow coefficients show a clear dependence on the total charged particle
multiplicity. HYDJET++ model justifies experimental data well enough.


  Progress toward characterization of structural and biophysical properties of
neural dendrites together with recent findings emphasizing their role in neural
computation, has propelled growing interest in refining existing theoretical
models of electrical propagation in dendrites while advocating novel analytic
tools. In this paper we focus on the cable equation describing electric
propagation in dendrites with different geometry. When the geometry is
cylindrical we show that the cable equation is invariant under the
Schr\"odinger group and by using the dendrite parameters, a representation of
the Schr\"odinger algebra is provided. Furthermore, when the geometry profile
is parabolic we show that the cable equation is equivalent to the Schr\"odinger
equation for the 1-dimensional free particle, which is invariant under the
Schr\"odinger group. Moreover, we show that there is a family of dendrite
geometries for which the cable equation is equivalent to the Schr\"odinger
equation for the 1-dimensional conformal quantum mechanics.


  Fast scramblers are quantum systems which thermalize in a time scale
logarithmic in the number of degrees of freedom of the system. Non-locality has
been argued to be an essential feature of fast scramblers. We provide evidence
in support of the crucial role of non-locality in such systems by considering
the approach to thermalization in a (strongly-coupled) high temperature
non-commutative gauge theory. We show that non-locality inherent to
non-commutative gauge theories does indeed accelerate the rate of dissipation
in the heat bath in stark contrast to the slow random walk diffusive behavior
prevalent in local field theories.


  In computational pathology, whole slide image (WSI) classification presents a
formidable challenge due to its gigapixel resolution and limited fine-grained
annotations. Multiple instance learning (MIL) offers a weakly supervised
solution, yet refining instance-level information from bag-level labels remains
complex. While most of the conventional MIL methods use attention scores to
estimate instance importance scores (IIS) which contribute to the prediction of
the slide labels, these often lead to skewed attention distributions and
inaccuracies in identifying crucial instances. To address these issues, we
propose a new approach inspired by cooperative game theory: employing Shapley
values to assess each instance's contribution, thereby improving IIS
estimation. The computation of the Shapley value is then accelerated using
attention, meanwhile retaining the enhanced instance identification and
prioritization. We further introduce a framework for the progressive assignment
of pseudo bags based on estimated IIS, encouraging more balanced attention
distributions in MIL models. Our extensive experiments on CAMELYON-16, BRACS,
and TCGA-LUNG datasets show our method's superiority over existing
state-of-the-art approaches, offering enhanced interpretability and class-wise
insights. We will release the code upon acceptance.


  Robust detection of vulnerable road users is a safety critical requirement
for the deployment of autonomous vehicles in heterogeneous traffic. One of the
most complex outstanding challenges is that of partial occlusion where a target
object is only partially available to the sensor due to obstruction by another
foreground object. A number of leading pedestrian detection benchmarks provide
annotation for partial occlusion, however each benchmark varies greatly in
their definition of the occurrence and severity of occlusion. Recent research
demonstrates that a high degree of subjectivity is used to classify occlusion
level in these cases and occlusion is typically categorized into 2 to 3 broad
categories such as partially and heavily occluded. This can lead to inaccurate
or inconsistent reporting of pedestrian detection model performance depending
on which benchmark is used. This research introduces a novel, objective
benchmark for partially occluded pedestrian detection to facilitate the
objective characterization of pedestrian detection models. Characterization is
carried out on seven popular pedestrian detection models for a range of
occlusion levels from 0-99%, in order to demonstrate the efficacy and increased
analysis capabilities of the proposed characterization method. Results
demonstrate that pedestrian detection performance degrades, and the number of
false negative detections increase as pedestrian occlusion level increases. Of
the seven popular pedestrian detection routines characterized, CenterNet has
the greatest overall performance, followed by SSDlite. RetinaNet has the lowest
overall detection performance across the range of occlusion levels.


  We discuss two ways to construct standard probability measures, called
push-down measures, from internal probability measures. We show that the
Wasserstein distance between an internal probability measure and its push-down
measure is infinitesimal. As an application to standard probability theory, we
show that every finitely-additive Borel probability measure $P$ on a separable
metric space is a limit of a sequence of countably-additive Borel probability
measures if and only if the space is totally bounded.


  For a smooth projective variety X, let CH(X) be the Chow ring (with rational
coefficients) of algebraic cycles modulo rational equivalence. The conjectures
of Bloch and Beilinson predict the existence of a functorial ring filtration of
CH(X). We want to investigate for which varieties this filtration splits, that
is, comes from a graduation on CH(X) -- this occurs for K3 surfaces and,
conjecturally, for abelian varieties.
  We observe that, though the Bloch-Beilinson filtration is only conjectural,
the fact that it splits has some simple consequences which can be tested in
concrete examples. Namely, for a regular variety X, it implies that the
sub-Q-algebra of CH(X) spanned by divisor classes injects into the cohomology
of X . We give examples of Calabi-Yau threefolds which do not satisfy this
property. On the other hand we conjecture that the property does indeed hold
for (holomorphic) symplectic manifolds, and we give some (weak) evidence in
favour of this conjecture.


  In this paper we study the combined effects of size and shape of small solid
state particles on the absorption, emission and scattering characteristics. We
use the statistical approach to calculate these optical properties. In this
approach the average optical properties of an ensemble of particles in random
orientation are represented by the average optical properties of an ensemble of
simple shapes. The validity of this approach is studied in detail for a uniform
distribution of hollow spheres where the fractional volume of the central
inclusion is varied. We apply the results to two different areas of interest,
i) infrared spectroscopy and ii) polarization of scattered light. The effects
of particle size and shape on the optical characteristics are discussed. We
compare the results using the distribution of hollow spheres with those
obtained by using randomly oriented spheroids. Also we compare the results with
observations and laboratory measurements. The distribution of hollow spheres is
very successful in reproducing laboratory measurements of the scattering angle
distribution of the degree of linear polarization for incident unpolarized
light of randomly oriented irregular quartz particles. Furthermore, we show
that we are able to derive the size distribution of dust grains by fitting the
measured degree of linear polarization using computational result for hollow
spheres. It is shown that the distribution of hollow spheres is a powerful tool
for studying light scattering, absorption and emission by cosmic dust grains
and in particular when large numbers of particle parameters need to be
considered since the computational demand of the distribution of hollow spheres
is small.


  We determine the structure of the bigraded ring of weak Jacobi forms with
integral Fourier coefficients. This ring is the target ring of a map
generalising the Witten and elliptic genera and a partition function of
$(0,2)$-model in string theory. We also determine the structure of the graded
ring of all weakly holomorphic Jacobi forms of weight zero and integral index
with integral Fourier coefficients. These forms are the data for Borcherds
products for the Siegel paramodular groups.


  We study soliton interaction in the Modified Kadomtsev-Petviashvili-(II)
equation (MKP-(II)) using the totally non-negative Grassmannian. One constructs
the multi-kink soliton of MKP equation using the $\tau$-function and the
Binet-Cauchy formula, and then investigates the interaction between kink
solitons and line solitons. Especially, Y-type kink-soliton resonance, O-type
kink soliton and P-type kink soliton of X-shape are investigated. Their
amplitudes of interaction are computed after choosing appropriate phases.


  A high priority in light spectroscopy is to seek out and characterize various
types of non-$(Q\bar{Q}$) meson. The large quantity of new data now appearing
will present a great opportunity. To identify the non-$(Q\bar{Q}$) intruders
one needs to know the regular $(Q\bar{Q}$) pattern well; whole meson families
thus become a target for close investigation. A powerful discovery strategy is
to observe the same meson in a variety of reactions. Because mesons appear as
resonances, other dynamics can distort the signal in a particular decay
channel. Unitarity is the master principle for co- ordinating various sightings
of the same resonance. Much of the new spectroscopic information in prospect
will come from inferring two-body dynamics from three-body final states.
Conventional methods of analysis via the isobar model use approximations to
unitarity that need validation. Of all the meson families, the scalars should
be a prime hunting ground for non-$(Q\bar{Q}$)'s. Even before the advent of the
new results, some revisions of the `official' classifications are urged. In
particular, it is argued that the lightest broad $I=0$ scalar is a very broad
$f_0$ (1000). One unfinished task is to decide whether $f_0$ (975) and $a_0$
(980) are alike or different; several non-$(Q\bar{Q}$) scalar scenarios hinge
on this. To settle this, much better data


  The angle-resolved photoemission (ARPES) technique has been developed rapidly
over the last decay, accompanied by the improvement of energy and momentum
resolutions. This technique has been established as the most powerful tool to
investigate the high Tc cuprate superconductors. We review recent ARPES data on
the cuprates from a theoretical point of view, with emphasis on the systematic
evolution of the spectral weight near the momentum (pi,0) from insulator to
overdoped systems. The effects of charge stripes on the ARPES spectra are also
reviewed. Some recent experimental and theoretical efforts to understand the
superconducting state and the pseudogap phenomenon are discussed.


  These lecture notes are concerned with the solvability of the second boundary
value problem of the prescribed affine mean curvature equation and related
regularity theory of the Monge-Amp\`ere and linearized Monge-Amp\`ere
equations. The prescribed affine mean curvature equation is a fully nonlinear,
fourth order, geometric partial differential equation of the following form
  $$\sum_{i, j=1}^n U^{ij}\frac{\partial^2}{\partial
{x_i}\partial{x_j}}\left[(\det D^2 u)^{-\frac{n+1}{n+2}}\right]=f$$ where
$(U^{ij})$ is the cofactor matrix of the Hessian matrix $D^2 u$ of a locally
uniformly convex function $u$. Its variant is related to the problem of finding
K\"ahler metrics of constant scalar curvature in complex geometry. We first
introduce the background of the prescribed affine mean curvature equation which
can be viewed as a coupled system of Monge-Amp\`ere and linearized
Monge-Amp\`ere equations. Then we state key open problems and present the
solution of the second boundary value problem that prescribes the boundary
values of the solution $u$ and its Hessian determinant $\det D^2 u$. Its proof
uses important tools from the boundary regularity theory of the Monge-Amp\`ere
and linearized Monge-Amp\`ere equations that we will present in the lecture
notes.


  In this work, we investigate the capacity of multi-antenna fading channels
with 1-bit quantized output per receive antenna. Specifically, leveraging
Bayesian statistical tools, we analyze the asymptotic regime with a large
number of receive antennas. In the coherent case, where the channel state
information (CSI) is known at the receiver's side, we completely characterize
the asymptotic capacity and provide the exact scaling in the extreme regimes of
signal-to-noise ratio (SNR) and the number of transmit antennas. In the
non-coherent case, where the CSI is unknown but remains constant during T
symbol periods, we first obtain the exact asymptotic capacity for T<=3. Then,
we propose a scheme involving uniform signaling in the covariance space and
derive a non-asymptotic lower bound on the capacity for an arbitrary block size
T. Furthermore, we propose a genie-aided upper bound where the channel is
revealed to the receiver. We show that the upper and lower bounds coincide when
T is large. In the low SNR regime, we derive the asymptotic capacity up to a
vanishing term, which, remarkably, matches our capacity lower bound.


  Learned embeddings are widely used to obtain concise data representation and
enable transfer learning between different data sets and tasks. In this paper,
we present Silhouette, our approach that leverages publicly-available
performance data sets to learn CPU embeddings. We show how these embeddings
enable transfer learning between data sets of different types and sizes. Each
of these scenarios leads to an improvement in accuracy for the target data set.


  In this paper, we revisit \textsf{ROOT-SGD}, an innovative method for
stochastic optimization to bridge the gap between stochastic optimization and
statistical efficiency. The proposed method enhances the performance and
reliability of \textsf{ROOT-SGD} by integrating a carefully designed
\emph{diminishing stepsize strategy}. This approach addresses key challenges in
optimization, providing robust theoretical guarantees and practical benefits.
Our analysis demonstrates that \textsf{ROOT-SGD} with diminishing achieves
optimal convergence rates while maintaining computational efficiency. By
dynamically adjusting the learning rate, \textsf{ROOT-SGD} ensures improved
stability and precision throughout the optimization process. The findings of
this study offer valuable insights for developing advanced optimization
algorithms that are both efficient and statistically robust.


  We have performed x-ray absorption spectroscopy (XAS) and x-ray photoemission
spectroscopy (XPS) studies of single crystal Ba_{1-x}K_{x}BiO_{3} (BKBO)
covering the whole composition range $0 \leq x \leq 0.60$. Several features in
the oxygen 1\textit{s} core XAS spectra show systematic changes with $x$.
Spectral weight around the absorption threshold increases with hole doping and
shows a finite jump between $x=0.30$ and 0.40, which signals the
metal-insulator transition. We have compared the obtained results with
band-structure calculations. Comparison with the XAS results of
BaPb_{1-x}Bi_{x}O_{3} has revealed quite different doping dependences between
BKBO and BPBO. We have also observed systematic core-level shifts in the XPS
spectra as well as in the XAS threshold as functions of $x$, which can be
attributed to a chemical potential shift accompanying the hole doping. The
observed chemical potential shift is found to be slower than that predicted by
the rigid band model based on the band-structure calculations.


  Because calibrated light curves of Type Ia supernovae have become a major
tool to determine the local expansion rate of the Universe and also its
geometrical structure, considerable attention has been given to models of these
events over the past couple of years. There are good reasons to believe that
perhaps most Type Ia supernovae are the explosions of white dwarfs that have
approached the Chandrasekhar mass, M_ch ~ 1.39 M_sun, and are disrupted by
thermonuclear fusion of carbon and oxygen. However, the mechanism whereby such
accreting carbon-oxygen white dwarfs explode continues to be uncertain. Recent
progress in modeling Type Ia supernovae as well as several of the still open
questions are addressed in this review. Although the main emphasis will be on
studies of the explosion mechanism itself and on the related physical
processes, including the physics of turbulent nuclear combustion in degenerate
stars, we also discuss observational constraints.


  The $k$-method is the isogeometric method based on splines (or NURBS, etc.)
with maximum regularity. When implemented following the paradigms of classical
finite element methods, the computational resources required by the $k-$method
are prohibitive even for moderate degree. In order to address this issue, we
propose a matrix-free strategy combined with weighted quadrature, which is an
ad-hoc strategy to compute the integrals of the Galerkin system. Matrix-free
weighted quadrature (MF-WQ) speeds up matrix operations, and, perhaps even more
important, greatly reduces memory consumption. Our strategy also requires an
efficient preconditioner for the linear system iterative solver. In this work
we deal with an elliptic model problem, and adopt a preconditioner based on the
Fast Diagonalization method, an old idea to solve Sylvester-like equations. Our
numerical tests show that the isogeometric solver based on MF-WQ is faster than
standard approaches (where the main cost is the matrix formation by standard
Gaussian quadrature) even for low degree. But the main achievement is that,
with MF-WQ, the $k$-method gets orders of magnitude faster by increasing the
degree, given a target accuracy. Therefore, we are able to show the
superiority, in terms of computational efficiency, of the high-degree
$k$-method with respect to low-degree isogeometric discretizations. What we
present here is applicable to more complex and realistic differential problems,
but its effectiveness will depend on the preconditioner stage, which is as
always problem-dependent. This situation is typical of modern high-order
methods: the overall performance is mainly related to the quality of the
preconditioner.


  To explain the unusual richness and compactness of the Abell 2744, we propose
a hypothesis that it may be a rich supercluster aligned along the sightline,
and present a supporting evidence obtained numerically from the MultiDark
Planck 2 simulations with a linear box size of $1\,h^{-1}$Gpc. Applying the
friends-of-friends (FoF) algorithm with a linkage length of $0.33$ to a sample
of the cluster-size halos from the simulations, we identify the superclusters
and investigate how many superclusters have filamentary branches that would
appear to be similar to the Abell 2744 if the filamentary axis is aligned with
the sightline. Generating randomly a unit vector as a sightline at the position
of the core member of each supercluster and projecting the positions of the
members onto the plane perpendicular to the direction of the sightline, we
measure two dimensional distances ($R_{2d}$) of the member halos from the core
for each supercluster. Defining a Abell 2744-like spuercluster as the one
having a filamentary branch composed of eight or more members with $R_{2d}\le
1\,$Mpc and masses comparable to those of the observed Abell 2744
substructures, we find one Abell 2744-like supercluster at $z=0.3$ and two at
$z=0$. Repeating the same analysis but with the data from the Big MultiDark
Planck simulations performed on a larger box of linear size of
$2.5\,h^{-1}$Mpc, we find that the number of the Abell 2744-like superclusters
at $z=0$ increases up to eighteen, among which three are found more massive
than $5\times 10^{15}\,M_{\odot}$.


  For a given Lagrangian $L:[0,T]\times M\times M^\ast\rightarrow \mathbb{R}_+$
and probability measures $\mu\in\mathcal{P}(M^\ast)$, $\nu\in \mathcal{P}(M)$,
we introduce the stochastic ballistic transportation problems
\begin{align}\tag{$\star$}
  \underline{B}(\mu,\nu):=\inf\left\{\mathbb{E}\left[\langle V,X_0\rangle
+\int_0^T L(t,X,\beta(t,X))\,dt\right]\middle\rvert V\sim\mu,X_T\sim
\nu\right\}\\\tag{$\star\star$}
  \overline{B}(\nu,\mu):=\sup\left\{\mathbb{E}\left[\langle V,X_T\rangle
-\int_0^T L(t,X,\beta(t,X))\,dt\right]\middle\rvert V\sim\mu,X_0\sim
\nu\right\} \end{align} where $X$ is a diffusion process with drift $\beta$.
This cost is based on the stochastic optimal transport problem presented by
Mikami and the deterministic ballistic transport introduced by Ghoussoub. We
obtain a Kantorovich-style duality result that reformulates this problem in
terms of solutions to the Hamilton-Jacobi-Bellman equation \begin{equation*}
  \frac{\partial\phi}{\partial t}+\frac{1}{2}\Delta \phi+H(t,x,\nabla\phi)=0,
\end{equation*} and show how optimal processes may be thereby attained.


  We study the phenomenon of length scale competition, an instability of
solitons and other coherent structures that takes place when their size is of
the same order of some characteristic scale of the system in which they
propagate. Working on the framework of nonlinear Klein-Gordon models as a
paradigmatic example, we show that this instability can be understood by means
of a collective coordinate approach in terms of soliton position and width. As
a consequence, we provide a quantitative, natural explanation of the phenomenon
in much simpler terms than any previous treatment of the problem. Our technique
allows to study the existence of length scale competition in most soliton
bearing nonlinear models and can be extended to coherent structures with more
degrees of freedom, such as breathers.


  Carleson's Theorem asserts the pointwise convergence of Fourier series of
square integrable functions. We give a complete proof, following joint work of
the author and C. Thiele. Over 20 exercises are also detailed. We also discuss
the derviation of the theorem on L^p spaces. And discuss a number of
complements and extensions of the theorem and proof of Carleson's theorem.


  We consider regret minimization in repeated games with a very large number of
actions. Such games are inherent in the setting of AI Safety via Debate
\cite{irving2018ai}, and more generally games whose actions are language-based.
Existing algorithms for online game playing require per-iteration computation
polynomial in the number of actions, which can be prohibitive for large games.
  We thus consider oracle-based algorithms, as oracles naturally model access
to AI agents. With oracle access, we characterize when internal and external
regret can be minimized efficiently. We give a novel efficient algorithm for
simultaneous external and internal regret minimization whose regret depends
logarithmically on the number of actions. We conclude with experiments in the
setting of AI Safety via Debate that shows the benefit of insights from our
algorithmic analysis.


  The ability to synthesise Computed Tomography images - commonly known as
pseudo CT, or pCT - from MRI input data is commonly assessed using an
intensity-wise similarity, such as an L2-norm between the ground truth CT and
the pCT. However, given that the ultimate purpose is often to use the pCT as an
attenuation map ($\mu$-map) in Positron Emission Tomography Magnetic Resonance
Imaging (PET/MRI), minimising the error between pCT and CT is not necessarily
optimal. The main objective should be to predict a pCT that, when used as
$\mu$-map, reconstructs a pseudo PET (pPET) which is as close as possible to
the gold standard PET. To this end, we propose a novel multi-hypothesis deep
learning framework that generates pCTs by minimising a combination of the
pixel-wise error between pCT and CT and a proposed metric-loss that itself is
represented by a convolutional neural network (CNN) and aims to minimise
subsequent PET residuals. The model is trained on a database of 400 paired
MR/CT/PET image slices. Quantitative results show that the network generates
pCTs that seem less accurate when evaluating the Mean Absolute Error on the pCT
(69.68HU) compared to a baseline CNN (66.25HU), but lead to significant
improvement in the PET reconstruction - 115a.u. compared to baseline 140a.u.


  We calculate the band gaps of 12 inorganic semiconductors and insulators
composed of atoms from the first three rows of the periodic table using
periodic equation-of-motion coupled-cluster theory with single and double
excitations (EOM-CCSD). Our calculations are performed with atom-centered
triple-zeta basis sets and up to 64 $k$-points in the Brillouin zone. We
analyze the convergence behavior with respect to number of orbitals and number
of $k$-points sampled, using composite corrections and extrapolations to
produce our final values. When accounting for electron-phonon corrections to
experimental band gaps, we find that EOM-CCSD has a mean signed error of
$-0.12$ eV and a mean absolute error of $0.42$ eV; the largest outliers are C
(error of $-0.93$ eV), BP ($-1.00$ eV), and LiH ($+0.78$ eV). Surprisingly, we
find that the more affordable partitioned EOM-MP2 theory performs as well as
EOM-CCSD.


  In structural pattern recognition, given a set of graphs, the computation of
a Generalized Median Graph is a well known problem. Some methods approach the
problem by assuming a relation between the Generalized Median Graph and the
Common Labelling problem. However, this relation has still not been formally
proved. In this paper, we analyse such relation between both problems. The main
result proves that the cost of the common labelling upper-bounds the cost of
the median with respect to the given set. In addition, we show that the two
problems are equivalent in some cases.


  We derive a factorization theorem for the differential distributions of
electroweak gauge bosons in Drell-Yan processes, valid at low transverse
momentum, using the Soft-Collinear Effective Theory (SCET). We present the
next-to-leading logarithmic (NLL) transverse momentum distribution for the
Z-boson and find good agreement with Tevatron data collected by the CDF and D0
collaborations. We also give predictions for the Higgs boson differential
distributions at NLL based on a factorization theorem derived in earlier work.
We derive formulae for all quantities needed to study low transverse momentum
production of color-neutral particles within the effective theory. This
effective field theory approach is free of Landau poles and can be formulated
entirely in momentum space. Consequently, our results are free of the
Landau-pole prescriptions necessary in the standard approach.


  Cellwise contamination remains a challenging problem for data scientists,
particularly in research fields that require the selection of sparse features.
Traditional robust methods may not be feasible nor efficient in dealing with
such contaminated datasets. We propose CR-Lasso, a robust Lasso-type cellwise
regularization procedure that performs feature selection in the presence of
cellwise outliers by minimising a regression loss and cell deviation measure
simultaneously. To evaluate the approach, we conduct empirical studies
comparing its selection and prediction performance with several sparse
regression methods. We show that CR-Lasso is competitive under the settings
considered. We illustrate the effectiveness of the proposed method on real data
through an analysis of a bone mineral density dataset.


  We present libvdwxc, a general library for evaluating the energy and
potential for the family of vdW-DF exchange--correlation functionals. libvdwxc
provides an efficient implementation of the vdW-DF method and can be interfaced
with various general-purpose DFT codes. Currently, the GPAW and Octopus codes
implement interfaces to libvdwxc. The present implementation emphasizes
scalability and parallel performance, and thereby enables \textit{ab initio}
calculations of nanometer-scale complexes. The numerical accuracy is
benchmarked on the S22 test set whereas parallel performance is benchmarked on
ligand-protected gold nanoparticles
($\text{Au}_{144}(\text{SC}_{11}\text{NH}_{25})_{60}$) up to 9696 atoms.


  Biological membranes are capacitors that can be charged by applying a field
across the membrane. The charges on the capacitor exert a force on the membrane
that leads to electrostriction, i.e. a thinning of the membrane. Since the
force is quadratic in voltage, negative and positive voltage have an identical
influence on the physics of symmetric membranes. However, this is not the case
for a membrane with an asymmetry leading to a permanent electric polarization.
Positive and negative voltages of identical magnitude lead to different
properties. Such an asymmetry can originate from a lipid composition that is
different on the two monolayers of the membrane, or from membrane curvature.
The latter effect is called 'flexoelectricity'. As a consequence of permanent
polarization, the membrane capacitor is discharged at a voltage different from
zero. This leads to interesting electrical phenomena such as outward or inward
rectification of membrane permeability.
  Here, we introduce a generalized theoretical framework, that treats
capacitance, polarization, flexoelectricity and piezoelectricity in the same
language.


  We study Coulomb interacting electrons confined in polygonal quantum rings.
We focus on the interplay of localization at the polygon corners and Coulomb
repulsion. Remarkably, the Coulomb repulsion allows the formation of in-gap
states, i.e. corner-localized states of electron pairs or clusters shifted to
energies that were forbidden for uncoupled electrons, but below the energies of
side-localized states. We also specify conditions allowing optical excitation
of those states.


  Basic elements of the exact renormalization group method and recent results
within this approach are reviewed. Topics covered are the derivation of
equations for the effective action and relations between them, derivative
expansion, solutions of fixed point equations and the calculation of the
critical exponents, construction of the c-function and a description of the
chiral phase transition.


  We determine the evolution of a cluster of quantum vortices initially placed
at the centre of a larger vortex-free region. We find that the cluster spreads
out spatially. This spreading motion consists of two effects: the rapid
evaporation of vortex dipoles from the cluster and the slow expansion of the
cluster itself. The latter is akin to a diffusion process controlled by the
quantum of circulation. Numerical simulations of the Gross-Pitaevskii equation
show that this phenomenon is qualitatively unaffected by the presence of sound
waves, vortex annihilations, and boundaries, and it should be possible to
create it in the laboratory.


  The fundamental multidimensional line spectral estimation problem is
addressed utilizing the Bayesian methods. Motivated by the recently proposed
variational line spectral estimation (VALSE) algorithm, multidimensional VALSE
(MDVALSE) is developed. MDVALSE inherits the advantages of VALSE such as
automatically estimating the model order, noise variance and providing
uncertain degrees of frequency estimates. Compared to VALSE, the
multidimensional frequencies of a single component is treated as a whole, and
the probability density function is projected as independent univariate von
Mises distribution to perform tractable inference. Besides, for the
initialization, efficient fast Fourier transform (FFT) is adopted to
significantly reduce the computation complexity of MDVALSE. Numerical results
demonstrate the effectiveness of the MDVALSE, compared to state-of-art methods.


  The combination of nonlinear and integrated photonics has recently seen a
surge with Kerr frequency comb generation in micro-resonators as the most
significant achievement. Efficient nonlinear photonic chips have myriad
applications including high speed optical signal processing, on-chip
multi-wavelength lasers, metrology, molecular spectroscopy, and quantum
information science. Aluminium gallium arsenide (AlGaAs) exhibits very high
material nonlinearity and low nonlinear loss when operated below half its
bandgap energy. However, difficulties in device processing and low device
effective nonlinearity made Kerr frequency comb generation elusive. Here, we
demonstrate AlGaAs-on-insulator as a nonlinear platform at telecom wavelengths.
Using newly developed fabrication processes, we show high-quality-factor
(Q>100,000) micro-resonators with integrated bus waveguides in a planar circuit
where optical parametric oscillation is achieved with a record low threshold
power of 3 mW and a frequency comb spanning 350 nm is obtained. Our
demonstration shows the huge potential of the AlGaAs-on-insulator platform in
integrated nonlinear photonics.


  The recent decades have seen a surge of interests in distributed computing.
Existing work focus primarily on either distributed computing platforms, data
query tools, or, algorithms to divide big data and conquer at individual
machines etc. It is, however, increasingly often that the data of interest are
inherently distributed, i.e., data are stored at multiple distributed sites due
to diverse collection channels, business operations etc. We propose to enable
learning and inference in such a setting via a general framework based on the
distortion minimizing local transformations. This framework only requires a
small amount of local signatures to be shared among distributed sites,
eliminating the need of having to transmitting big data. Computation can be
done very efficiently via parallel local computation. The error incurred due to
distributed computing vanishes when increasing the size of local signatures. As
the shared data need not be in their original form, data privacy may also be
preserved. Experiments on linear (logistic) regression and Random Forests have
shown promise of this approach. This framework is expected to apply to a
general class of tools in learning and inference with the continuity property.


  Bounds of the neutral current sector parameters of the left-right symmetric
model are investigated taking into account the low-energy data, LEP-data and
CDF-result for the top mass $m_t=174\pm 10^{+13}_{-12}$. It is found that in
the case of the minimal scalar sector with a left- and a right-handed triplet
and a bidoublet Higgses the mass of the heavy neutral gauge boson $M_{Z'}$
should be larger than 1.2 TeV, assuming equal left- and right-handed gauge
couplings and a negligible VEV of the left-handed triplet. For larger values of
the ratio $g_L/g_R$ smaller values of $M_{Z'}$ are allowed.


  For each integer $D\ge3$, we give a sharp bound on the number of lines
contained in a smooth complex $2D$-polarized $K3$-surface in
$\mathbb{P}^{D+1}$. In the two most interesting cases of sextics in
$\mathbb{P}^4$ and octics in $\mathbb{P}^5$, the bounds are $42$ and $36$,
respectively, as conjectured in an earlier paper.


  The cat code is a promising encoding scheme for bosonic quantum error
correction as it allows for correction against losses--the dominant error
mechanism in most bosonic systems. However, for losses to be detected
efficiently without disturbing the encoded logical information, one needs to
implement a parity measurement of the excitation number. While such a
measurement has been demonstrated in the microwave regime using a
superconducting transmon ancilla, it has remained unclear how it can be
implemented in the optical regime. Here, we introduce a teleportation-based
error-correction scheme for the cat code, using elements suitable for an
optical setting. The scheme detects and corrects single-photon losses while
restoring the amplitude of the cat states, thereby greatly suppressing the
accumulation of errors in lossy channels.


  Patronizing and condescending language (PCL) is everywhere, but rarely is the
focus on its use by media towards vulnerable communities. Accurately detecting
PCL of this form is a difficult task due to limited labeled data and how subtle
it can be. In this paper, we describe our system for detecting such language
which was submitted to SemEval 2022 Task 4: Patronizing and Condescending
Language Detection. Our approach uses an ensemble of pre-trained language
models, data augmentation, and optimizing the threshold for detection.
Experimental results on the evaluation dataset released by the competition
hosts show that our work is reliably able to detect PCL, achieving an F1 score
of 55.47% on the binary classification task and a macro F1 score of 36.25% on
the fine-grained, multi-label detection task.


  Machine learning techniques have been shown to be effective to recognize
different phases of matter and produce phase diagrams in the parameter space
interested, while they usually require prior labeled data to perform well.
Here, we propose a machine learning procedure, mainly in an unsupervised
manner, which can first identify topological/non-topological phases and then
refine the locations of phase boundaries. By following this proposed procedure,
we expand our previous work on the one-dimensional $p$-wave superconductor
[Phys. Rev. B 102, 054512 (2020)] and further on the Su-Schrieffer-Heeger
model, with an emphasis on using the quantum entanglement-based quantities as
the input features. We find that our method not only reproduces similar results
to the previous work with sharp phase boundaries but importantly it also does
not rely on prior knowledge of the phase space, e.g., the number of phases
present. We conclude with a few remarks about its potential, limitations, and
explainabilities.


  In this paper we establish a fractional generalization of Einstein field
equations based on the Riemann-Liouville fractional generalization of the
ordinary differential operator $\partial_\mu$. We show some elementary
properties and prove that the field equations correspond to the regular
Einstein field equations for the fractional order $\alpha = 1$. In addition to
this we show that the field theory is inherently non-local in this approach. We
also derive the linear field equations and show that they are a generalized
version of the time fractional diffusion-wave equation. We show that in the
Newtonian limit a fractional version of Poisson's equation for gravity arises.
Finally we conclude open problems such as the relation of the non-locality of
this theory to quantum field theories and the possible relation to fractional
mechanics.


  The well-rounded retract for $\mathrm{SL}_n(\mathbb{Z})$ is defined as the
set of flat tori of unit volume and dimension $n$ whose systoles generate a
finite-index subgroup in homology. This set forms an equivariant spine of
minimal dimension for the space of flat tori.
  For both the Outer space $X_n$ of metric graphs of rank $n$ and the
Teichm\"uller space $\mathcal{T}_g$ of closed hyperbolic surfaces of genus $g$,
we show that the literal analogue of the well-rounded retract does not contain
an equivariant spine. We also prove that the sets of graphs whose systoles fill
either topologically or geometrically (two analogues of a set proposed as a
spine for $\mathcal{T}_g$ by Thurston) are spines for $X_n$ but that their
dimension is larger than the virtual cohomological dimension of
$\mathrm{Out}(F_n)$ in general.


  We demonstrate that almost degenerate Dirac neutrinos of mass of few eV and
transition magnetic moment of the order of ${10}^{-11}$ $\mu_B$ can be obtained
in an ${SU(2)}_L\times {U(1)}_Y$ model with $S_3\times Z_3\times Z_4$ discrete
symmetry and appropriate Higgs fields. Transition magnetic moment of the Dirac
neutrino arises from to the contribution of leptons and charged Higgs fields at
the one loop level.


  We study the applicability of the Peaceman-Rachford (PR) splitting method for
solving nonconvex optimization problems. When applied to minimizing the sum of
a strongly convex Lipschitz differentiable function and a proper closed
function, we show that if the strongly convex function has a large enough
strong convexity modulus and the step-size parameter is chosen below a
threshold that is computable, then any cluster point of the sequence generated,
if exists, will give a stationary point of the optimization problem. We also
give sufficient conditions guaranteeing boundedness of the sequence generated.
We then discuss one way to split the objective so that the proposed method can
be suitably applied to solving optimization problems with a coercive objective
that is the sum of a (not necessarily strongly) convex Lipschitz differentiable
function and a proper closed function; this setting covers a large class of
nonconvex feasibility problems and constrained least squares problems. Finally,
we illustrate the proposed algorithm numerically.


  We study the vacuum alignment of the top-mode pseudo-Nambu-Goldstone boson
Higgs (TMpNGBH) model, which has recently been proposed as a variant of the top
quark condensate model in light of the 126 GeV Higgs boson discovered at the
LHC. It is shown that the vacuum of the model, determined from the one-loop
effective potential with all the explicit breaking effects included, realizes
the electroweak symmetry breaking with the appropriate breaking scale.
Phenomenologies of two characteristic particles in the TMpNGBH model, namely
the CP-odd partner of the Higgs and the vectorlike partner of the top quark are
also studied based on the newly identified vacuum.


  We study the role played by noise on the QW introduced in [1], a 1D model
that is inspired by a two particle interacting QW. The noise is introduced by a
random change in the value of the phase during the evolution, from a constant
probability distribution within a given interval. The consequences of
introducing such kind of noise depend on both the center value and the width of
that interval: a wider interval manifests as a higher level of noise. For some
range of parameters, one obtains a quasi-localized state, with a diffusive
speed that can be controlled by varying the parameters of the noise. The
existence of this (approximately) localized state for such kind of
time-dependent noise is, to the best of our knowledge, totally new, since
localization (i.e., Anderson localization) is linked in the literature to a
spatial random noise.


  In this paper, we show that any subgroup of a semidirect product of Z^n with
Z has bounded packing as long as the action of Z on Z^n is by diagonalizable
automorphisms all of whose eigenvalues are real. We use this result to show
that any subgroup in a polycyclic group of length 3 or less has bounded
packing. We also introduce the notion of coset growth and obtain a bound for
the coset growth of subgroup H=<t> in the semidirect product of Z^2 with Z.


  For a locally compact group $G$ and a strongly self-absorbing $G$-algebra
$(\mathcal{D},\delta)$, we obtain a new characterization of absorption of a
strongly self-absorbing action using almost equivariant completely positive
maps into the underlying algebra. The main technical tool to obtain this
characterization is the existence of almost equivariant lifts for equivariant
completely positive maps, proved in recent work of the authors.
  This characterization is then used to show that an equivariant
$C_0(X)$-algebra with $\mathrm{dim}_{\mathrm{cov}}(X)<\infty$ is
$(\mathcal{D},\delta)$-stable if and only if all of its fibers are, extending a
result of Hirshberg, R{\o}rdam and Winter to the equivariant setting. The
condition on the dimension of $X$ is known to be necessary, and we show that it
can be removed if, for example, the bundle is locally trivial.


  We analyze the spin Hall effect in CuIr alloys in theory by the combined
approach of the density functional theory (DFT) and Hartree-Fock (HF)
approximation. The SHA is obtained to be negative without the local correlation
effects. After including the local correlation effects of the 5d orbitals of Ir
impurities, the SHA becomes positive with realistic correlation parameters, and
consistent with experiment [Niimi et al., Phys. Rev. Lett. 106, 126601 (2011)].
Moreover, our analysis shows that the DFT+HF approach is a convenient and
general method to study the influence of local correlation effects on the spin
Hall effect.


  Neural Architecture Search (NAS) methods are widely used in various
industries to obtain high quality taskspecific solutions with minimal human
intervention. Event Sequences find widespread use in various industrial
applications including churn prediction customer segmentation fraud detection
and fault diagnosis among others. Such data consist of categorical and
real-valued components with irregular timestamps. Despite the usefulness of NAS
methods previous approaches only have been applied to other domains images
texts or time series. Our work addresses this limitation by introducing a novel
NAS algorithm SeqNAS specifically designed for event sequence classification.
We develop a simple yet expressive search space that leverages commonly used
building blocks for event sequence classification including multihead self
attention convolutions and recurrent cells. To perform the search we adopt
sequential Bayesian Optimization and utilize previously trained models as an
ensemble of teachers to augment knowledge distillation. As a result of our work
we demonstrate that our method surpasses state of the art NAS methods and
popular architectures suitable for sequence classification and holds great
potential for various industrial applications.


  The nebular spectra of the broad-lined, SN 1998bw-like Type Ic SN 2002ap are
studied by means of synthetic spectra. Two different modelling techniques are
employed. In one technique, the SN ejecta are treated as a single zone, while
in the other a density and abundance distribution in velocity is used from an
explosion model. In both cases, heating caused by gamma-ray and positron
deposition is computed (in the latter case using a Monte Carlo technique to
describe the propagation of gamma-rays and positrons), as is cooling via
forbidden-line emission. The results are compared, and although general
agreement is found, the stratified models are shown to reproduce the observed
line profiles much more accurately than the single-zone model. The explosion
produced ~ 0.1 Msun of 56Ni. The distribution in velocity of the various
elements is in agreement with that obtained from the early-time models, which
indicated an ejected mass of ~ 2.5 Msun with a kinetic energy of 4 x 10^{51}
erg. Nebular spectroscopy confirms that most of the ejected mass (~ 1.2 Msun)
was oxygen. The presence of an oxygen-rich inner core, combined with that of
56Ni at high velocities as deduced from early-time models, suggests that the
explosion was asymmetric, especially in the inner part.


  A necessary condition for the probabilities of a set of events to exhibit
Bell nonlocality or Kochen-Specker contextuality is that the graph of
exclusivity of the events contains induced odd cycles with five or more
vertices, called odd holes, or their complements, called odd antiholes. From
this perspective, events whose graph of exclusivity are odd holes or antiholes
are the building blocks of contextuality. For any odd hole or antihole, any
assignment of probabilities allowed by quantum mechanics can be achieved in
specific contextuality scenarios. However, here we prove that, for any odd
hole, the probabilities that attain the quantum maxima cannot be achieved in
Bell scenarios. We also prove it for the simplest odd antiholes. This leads us
to the conjecture that the quantum maxima for any of the building blocks cannot
be achieved in Bell scenarios. This result sheds light on why the problem of
whether a probability assignment is quantum is decidable, while whether a
probability assignment within a given Bell scenario is quantum is, in general,
undecidable. This also helps to undertand why identifying principles for
quantum correlations is simpler when we start by identifying principles for
quantum sets of probabilities defined with no reference to specific scenarios.


  Higher order terms in the effective action of noncommutative gauge theories
exhibit generalizations of the *-product (e.g. *' and *-3). These terms do not
manifestly respect the noncommutative gauge invariance of the tree level
action. In U(1) gauge theories, we note that these generalized *-products occur
in the expansion of some quantities that are invariant under noncommutative
gauge transformations, but contain an infinite number of powers of the
noncommutative gauge field. One example is an open Wilson line. Another is the
expression for a commutative field strength tensor in terms of the
noncommutative gauge field. Seiberg and Witten derived differential equations
that relate commutative and noncommutative gauge transformations, gauge fields
and field strengths. In the U(1) case we solve these equations neglecting terms
of fourth order in the gauge field but keeping all orders in the noncommutative
parameter.


  Surface wrinkling is an instability mode that is often observed in a wide
variety of multilayer tubes under bending deformation. When the degree of
applied bending exceeds a critical value, wrinkles appear at the intrados of
the tube and release a large amount of in-plane strain energy stored by bending
deformation. In the present work, we propose a simple theoretical model for
evaluating the critical curvature and critical bending moment for the
occurrence of wrinkling in multilayer tubes and apply the model to carbon
nanotubes in a case study. Results indicate an inverse proportional
relationship between the two critical properties, which holds true regardless
of the number of layers and the size of the hollow core.


  By introducing a simplified transport model of outer layers of white dwarfs
we derive an analytical semi-empirical relation which constrains effective
temperature-mass-radius for white dwarfs. This relation is used to classify
recent data of white dwarfs according to their time evolution in non-accretion
process of cooling. This formula permit us to study the population map of white
dwarfs in the central temperature and mass plane, and discuss the relation with
the ignition temperature for C-O material. Our effective
temperature-mass-radius relation provide a quick method to estimate the mass of
newly observed white dwarfs from their spectral measurements of effective
temperature and superficial gravity.


  The vertical profiles of chain and spiral galaxies in the Hubble Space
Telescope Ultra Deep Field (UDF) are fit to sech^2(z/z_0) functions convolved
with stellar profiles in order to measure the disk scale heights z_0 in four
passbands. The bulge regions of the spirals are avoided. Photometric redshifts
give absolute scales. The rms heights of the giant clumps in these galaxies are
also measured. The results indicate that UDF disks are thick with an average
z_0 of 1.0\pm0.4 kpc. The ratio of radial exponential scale length to z_0 is
\~3\pm1.5. The scale heights are only 20% larger than the radii of the giant
star-forming clumps and a factor of ~10 larger than the rms clump deviations
around the midplanes. This suggests the clumps formed from midplane gas and
dissolved to make the thick disks. Redshifted stellar population models suggest
ages of ~1 Gy and mass column densities from 4 to 40 Msun pc^{-2}. The UDF
disks look like young versions of modern thick disks. This resemblance is
difficult to understand if galaxies grow over time or if subsequent accretion
of thin disks gravitationally shrinks the observed thick disks. More likely,
high redshift disks are thick because their mass column densities are low; a
velocity dispersion of only 14 km/s reproduces the observed thickness. Modern
thick disks require more heating at high redshift. This is possible if the gas
that eventually makes the thin disk is in place before the youngest age of a
modern thick disk, and if the existing stars are heated during the delivery of
this gas.


  We discuss the concept of composite fields in flat CFT as well as in the
context of AdS/CFT. Furthermore we show how to represent Green functions using
generalized hypergeometric functions and apply these techniques to four-point
functions. Finally we prove an identity of $U(1)_Y$ symmetry for four-point
functions.


  Objective:Computer vision-based up-to-date accurate damage classification and
localization are of decisive importance for infrastructure monitoring, safety,
and the serviceability of civil infrastructure. Current state-of-the-art deep
learning (DL)-based damage detection models, however, often lack superior
feature extraction capability in complex and noisy environments, limiting the
development of accurate and reliable object distinction. Method: To this end,
we present DenseSPH-YOLOv5, a real-time DL-based high-performance damage
detection model where DenseNet blocks have been integrated with the backbone to
improve in preserving and reusing critical feature information. Additionally,
convolutional block attention modules (CBAM) have been implemented to improve
attention performance mechanisms for strong and discriminating deep spatial
feature extraction that results in superior detection under various challenging
environments. Moreover, additional feature fusion layers and a Swin-Transformer
Prediction Head (SPH) have been added leveraging advanced self-attention
mechanism for more efficient detection of multiscale object sizes and
simultaneously reducing the computational complexity. Results: Evaluating the
model performance in large-scale Road Damage Dataset (RDD-2018), at a detection
rate of 62.4 FPS, DenseSPH-YOLOv5 obtains a mean average precision (mAP) value
of 85.25 %, F1-score of 81.18 %, and precision (P) value of 89.51 %
outperforming current state-of-the-art models. Significance: The present
research provides an effective and efficient damage localization model
addressing the shortcoming of existing DL-based damage detection models by
providing highly accurate localized bounding box prediction. Current work
constitutes a step towards an accurate and robust automated damage detection
system in real-time in-field applications.


  In this article, we obtain existence and uniqueness results to some problems
involving complex nonlinear fractional differential equations (FDEs) in the
closed unit disc of C. By help of these results, we prove that some IVPs for
some fractional differential equations with Caputo or Riemann-Liouville
derivative admit at least one local (or unique) solution continuous on a closed
interval $[0,R]$ and real analytic on $(0,R),$ where $0<R\leq 1.$


  The AdS/CFT correspondence is a powerful tool to study the properties of
conformal QCD at strong coupling in terms of a higher dimensional dual gravity
theory. The power-law falloff of scattering amplitudes in the non-perturbative
regime and calculable hadron spectra follow from holographic models dual to QCD
with conformal behavior at short distances and confinement at large distances.
String modes and fluctuations about the AdS background are identified with QCD
degrees of freedom and orbital excitations at the AdS boundary limit. A
description of form factors in space and time-like regions and the behavior of
light-front wave functions can also be understood in terms of a dual gravity
description in the interior of AdS.


  The canonical approach to quantum gravity has been put on a firm mathematical
foundation in the recent decades. Even the quantum dynamics can be rigorously
defined, however, due to the tremendously non-polynomial character of the
gravitational interaction, the corresponding Wheeler-DeWitt operator valued
distribution suffers from quantisation ambiguities that need to be fixed.
  In a very recent series of works we have employed methods from constructive
quantum field theory in order to address those ambiguities. Constructive QFT
trades quantum fields for random variables and measures thereby phrasing the
theory in the language of quantum statistical physics. The connection to the
canonical formulation is made via Osterwalder-Schrader reconstruction. It is
well known in quantum statistics that the corresponding ambiguities in measures
can be fixed using renormalisation. The associated renormalisation flow can
thus be used to define a canonical renormalisation programme.
  The purpose of this article is to review and further develop these ideas and
to put them into context with closely related earlier and parallel programmes.


  Picture yourself in the wave zone of a gravitational scattering event of two
massive, spinning compact bodies (black holes, neutron stars or stars). We show
that this system of genuine astrophysical interest enjoys a hidden
$\mathcal{N}=2$ supersymmetry, at least to the order of spin-squared
(quadrupole) interactions in arbitrary $D$ spacetime dimensions. Using the
${\mathcal N}=2$ supersymmetric worldline action, augmented by finite-size
corrections for the non-Kerr black hole case, we build a quadratic-in-spin
extension to the worldline quantum field theory (WQFT) formalism introduced in
our previous work, and calculate the two bodies' deflection and spin kick to
sub-leading order in the post-Minkowskian expansion in Newton's constant $G$.
For spins aligned to the normal vector of the scattering plane we also obtain
the scattering angle. All $D$-dimensional observables are derived from an
eikonal phase given as the free energy of the WQFT, that is invariant under the
$\mathcal{N}=2$ supersymmetry transformations.


  We prove a conjecture of Liu and Wang on the q-log-convexity of the
polynomial sequence $\{\sum_{k=0}^n{n\choose k}^2q^k\}_{n\geq 0}$. By using
Pieri's rule and the Jacobi-Trudi identity for Schur functions, we obtain an
expansion of a sum of products of elementary symmetric functions in terms of
Schur functions with nonnegative coefficients. Then the principal
specialization leads to the q-log-convexity. We also prove that a technical
condition of Liu and Wang holds for the squares of the binomial coefficients.
Hence we deduce that the linear transformation with respect to the triangular
array $\{{n\choose k}^2\}_{0\leq k\leq n}$ is log-convexity preserving.


  The paper presents a new cross-ratio of hypercomplex numbers based on
projective geometry. We discuss the essential properties of the projective
cross-ratio, notably its invariance under Mobius transformations. Applications
to the geometry of conic sections and Mobius-invariant metrics on the upper
half-plane are also given.


  We present a new approach to the dynamics of interacting particles with
reaction and diffusion. Starting from the underlying discrete stochastic jump
process we derive a general field theory describing the dynamics of the density
field, which we relate to an exact stochastic equation on the density field. We
show how our field theory maps onto the original Doi-Peliti formalism, allowing
us to clarify further the issue of the 'imaginary' Langevin noise that appears
in the context of reaction/diffusion processes. Our procedure applies to a wide
class of problems and is related to large deviation functional techniques
developed recently to describe fluctuations of non-equilibrium systems in the
hydrodynamic limit.


  We analyze the dynamics of the neural circuit of the lamprey central pattern
generator (CPG). This analysis provides insights into how neural interactions
form oscillators and enable spontaneous oscillations in a network of damped
oscillators, which were not apparent in previous simulations or abstract phase
oscillator models. We also show how the different behaviour regimes
(characterized by phase and amplitude relationships between oscillators) of
forward/backward swimming, and turning, can be controlled using the neural
connection strengths and external inputs.


  Double-fetch bugs are a special type of race condition, where an unprivileged
execution thread is able to change a memory location between the time-of-check
and time-of-use of a privileged execution thread. If an unprivileged attacker
changes the value at the right time, the privileged operation becomes
inconsistent, leading to a change in control flow, and thus an escalation of
privileges for the attacker. More severely, such double-fetch bugs can be
introduced by the compiler, entirely invisible on the source-code level.
  We propose novel techniques to efficiently detect, exploit, and eliminate
double-fetch bugs. We demonstrate the first combination of state-of-the-art
cache attacks with kernel-fuzzing techniques to allow fully automated
identification of double fetches. We demonstrate the first fully automated
reliable detection and exploitation of double-fetch bugs, making manual
analysis as in previous work superfluous. We show that cache-based triggers
outperform state-of-the-art exploitation techniques significantly, leading to
an exploitation success rate of up to 97%. Our modified fuzzer automatically
detects double fetches and automatically narrows down this candidate set for
double-fetch bugs to the exploitable ones. We present the first generic
technique based on hardware transactional memory, to eliminate double-fetch
bugs in a fully automated and transparent manner. We extend defensive
programming techniques by retrofitting arbitrary code with automated
double-fetch prevention, both in trusted execution environments as well as in
syscalls, with a performance overhead below 1%.


  In-growth or post-deposition treatment of $Cu_{2}ZnSnS_{4}$ (CZTS) absorber
layer had led to improved photovoltaic efficiency, however, the underlying
physical mechanism of such improvements are less studied. In this study, the
thermodynamics of Na and K related defects in CZTS are investigated from first
principle approach using hybrid functional, with chemical potential of Na and K
established from various phases of their polysulphides. Both Na and K
predominantly substitute on Cu sites similar to their behavior in
$Cu(In,Ga)Se_{2}$, in contrast to previous results using the generalized
gradient approximation (GGA). All substitutional and interstitial defects are
shown to be either shallow levels or highly energetically unfavorable. Defect
complexing between Na and abundant intrinsic defects did not show possibility
of significant incorporation enhancement or introducing deep n-type levels. The
possible benefit of Na incorporation on enhancing photovoltaic efficiency is
discussed. The negligible defect solubility of K in CZTS also suggests possible
surfactant candidate.


  We consider the problem of embedding the semi-ring of Schur-positive
symmetric polynomials into its analogue for the classical types $B/C/D$. If we
preserve highest weights and add the additional Lie-theoretic parity assumption
that the weights in images of Schur functions lie in a single translate of the
root lattice, there are exactly two solutions. These naturally extend the
Kirillov--Reshetikhin decompositions of representations of symplectic and
orthogonal quantum affine algebras $U_q(\hat{g})$ (some still conjectural, some
recently proven).


  Treatment effect estimates are often available from randomized controlled
trials as a single average treatment effect for a certain patient population.
Estimates of the conditional average treatment effect (CATE) are more useful
for individualized treatment decision making, but randomized trials are often
too small to estimate the CATE. Examples in medical literature make use of the
relative treatment effect (e.g. an odds-ratio) reported by randomized trials to
estimate the CATE using large observational datasets. One approach to
estimating these CATE models is by using the relative treatment effect as an
offset, while estimating the covariate-specific untreated risk. We observe that
the odds-ratios reported in randomized controlled trials are not the
odds-ratios that are needed in offset models because trials often report the
marginal odds-ratio. We introduce a constraint or regularizer to better use
marginal odds-ratios from randomized controlled trials and find that under the
standard observational causal inference assumptions this approach provides a
consistent estimate of the CATE. Next, we show that the offset approach is not
valid for CATE estimation in the presence of unobserved confounding. We study
if the offset assumption and the marginal constraint lead to better
approximations of the CATE relative to the alternative of using the average
treatment effect estimate from the randomized trial. We empirically show that
when the underlying CATE has sufficient variation, the constraint and offset
approaches lead to closer approximations to the CATE.


  Light hypothetical particles with masses up to $\mathcal{O}(100)\ {\rm MeV}$
can be produced in the core of supernovae. Their subsequent decays to neutrinos
can produce a flux component with higher energies than the standard flux. We
study the impact of heavy neutral leptons, $Z'$ bosons, in particular ${\rm
U(1)}_{L_\mu-L_\tau}$ and ${\rm U(1)}_{B-L}$ gauge bosons, and majorons coupled
to neutrinos flavor-dependently. We obtain new strong limits on these particles
from no events of high-energy SN 1987A neutrinos and their future sensitivities
from observations of galactic supernova neutrinos.


  In this work we perform the symmetry classification of the Klein Gordon
equation in Bianchi I spacetime. We apply a geometric method which relates the
Lie symmetries of the Klein Gordon equation with the conformal algebra of the
underlying geometry. Furthermore, we prove that the Lie symmetries which follow
from the conformal algebra are also and Noether symmetries for the Klein Gordon
equation. We use these resutls in order to determine all the potentials in
which the Klein Gordon admits Lie and Noether symmetries. Due to the large
number of cases and for easy reference the results are presented in the form of
tables. For some of the potentials we use the Lie admitted symmetries to
determine the corresponding invariant solution of the Klein Gordon equation.
Finally, we show that the results also solve the problem of classification of
Lie/Noether point symmetries of the wave equation in Bianchi I spacetime and
can be used for the determination of invariant solutions of the wave equation.


  We derive conditions for a nonholonomic system subject to nonlinear
constraints (obeying Chetaev's rule) to preserve a smooth volume form. When
applied to affine constraints, these conditions dictate that a basic invariant
density exists if and only if a certain 1-form is exact and a certain function
vanishes (this function automatically vanishes for linear constraints).
Moreover, this result can be extended to geodesic flows for arbitrary metric
connections and the sufficient condition manifests as integrability of the
torsion. As a consequence, volume-preservation of a nonholonomic system is
closely related to the torsion of the nonholonomic connection. Examples of
nonlinear/affine/linear constraints are considered.


  We review the properties of six families of orthogonal polynomials that form
the main bulk of the collection called the Askey--Wilson scheme of polynomials.
We give connection coefficients between them as well as the so-called
linearization formulae and other useful important finite and infinite
expansions and identities. An important part of the paper is the presentation
of probabilistic models where most of these families of polynomials appear.
These results were scattered within the literature in recent 15 years. We put
them together to enable an overall outlook on these families and understand
their crucial r\^{o}le in the attempts to generalize Gaussian distributions and
find their bounded support generalizations. The paper is based on 65 items in
the predominantly recent literature.


  We study the magnitudes of soft SUSY breaking parameters in heterotic string
models with anomalous U(1) symmetry. In most cases, D-term contribution to soft
scalar masses is expected to be comparable to or dominant over other
contributions provided that supersymmetry breaking is mediated by the
gravitational interaction and/or an anomalous U(1) symmetry and the magnitude
of vacuum energy is not more than of order $m_{3/2}^2 M^2$.


  We present the first sample of 31-GHz selected sources to flux levels of 1
mJy. From late 2005 to mid 2007, the Sunyaev-Zel'dovich Array (SZA) observed
7.7 square degrees of the sky at 31 GHz to a median rms of 0.18 mJy/beam. We
identify 209 sources at greater than 5 sigma significance in the 31 GHz maps,
ranging in flux from 0.7 mJy to ~200 mJy. Archival NVSS data at 1.4 GHz and
observations at 5 GHz with the Very Large Array are used to characterize the
sources. We determine the maximum-likelihood integrated source count to be
N(>S) = (27.2 +- 2.5) deg^-2 x (S_mJy)^(-1.18 +- 0.12) over the flux range 0.7
- 15 mJy. This result is significantly higher than predictions based on 1.4-GHz
selected samples, a discrepancy which can be explained by a small shift in the
spectral index distribution for faint 1.4-GHz sources. From comparison with
previous measurements of sources within the central arcminute of massive
clusters, we derive an overdensity of 6.8 +- 4.4, relative to field sources.


  This paper presents a case study of Agile Scrum process followed in Retail
Domain project. This paper also reveals the impacts of Cost of Software
Quality, when agile scrum process is not followed efficiently. While analyzing
the case study, the gaps were found and guidelines for process improvements
were also suggested in this paper.


  Subspace learning is an important problem, which has many applications in
image and video processing. It can be used to find a low-dimensional
representation of signals and images. But in many applications, the desired
signal is heavily distorted by outliers and noise, which negatively affect the
learned subspace. In this work, we present a novel algorithm for learning a
subspace for signal representation, in the presence of structured outliers and
noise. The proposed algorithm tries to jointly detect the outliers and learn
the subspace for images. We present an alternating optimization algorithm for
solving this problem, which iterates between learning the subspace and finding
the outliers. This algorithm has been trained on a large number of image
patches, and the learned subspace is used for image segmentation, and is shown
to achieve better segmentation results than prior methods, including least
absolute deviation fitting, k-means clustering based segmentation in DjVu, and
shape primitive extraction and coding algorithm.


  Let $G$ be a simple graph of order $n$. The domination polynomial of $G$ is
the polynomial $D(G, x)=\sum_{i=\gamma(G)}^{n} d(G,i) x^{i}$, where $d(G,i)$ is
the number of dominating sets of $G$ of size $i$ and $\gamma(G)$ is the
domination number of $G$. It is conjectured that the domination polynomial of
any graph is unimodal. In this paper we present some families of graphs whose
domination polynomials are unimodal.


  A search is presented for massive narrow resonances decaying either into two
Higgs bosons, or into a Higgs boson and a W or Z boson. The decay channels
considered are HH $\to \mathrm{b\overline{b}}\tau^{+}\tau^{-}$ and VH $\to
\mathrm{q\overline{q}}\tau^{+}\tau^{-}$, where H denotes the Higgs boson, and V
denotes the W or Z boson. This analysis is based on a data sample of
proton-proton collisions collected at a center-of-mass energy of 13 TeV by the
CMS Collaboration, corresponding to an integrated luminosity of 35.9 fb$^{-1}$.
For the TeV-scale mass resonances considered, substructure techniques provide
ways to differentiate among the hadronization products from vector boson decays
to quarks, Higgs boson decays to bottom quarks, and quark- or gluon-induced
jets. Reconstruction techniques are used that have been specifically optimized
to select events in which the tau lepton pair is highly boosted. The observed
data are consistent with standard model expectations and upper limits are set
at 95% confidence level on the product of cross section and branching fraction
for resonance masses between 0.9 and 4.0 TeV. Exclusion limits are set in the
context of bulk radion and graviton models: spin-0 radion resonances are
excluded below a mass of 2.7 TeV at 95% confidence level. In the spin-1 heavy
vector triplet framework, mass-degenerate W' and Z' resonances with dominant
couplings to the standard model gauge bosons are excluded below a mass of 2.8
TeV at 95% confidence level. There are the first limits for these decay
channels at $\sqrt{s} =$ 13 TeV.


  A compact Lie group G and a faithful complex representation V determine a
Sato-Tate measure, defined as the direct image of Haar measure on G with
respect to the character of V. We give a necessary and sufficient condition for
a Sato-Tate measure to be an isolated point in the set of such measures,
regarded as a subset of the space of distributions. In particular we prove that
the Sato-Tate measure of a connected and semisimple group with respect to an
irreducible representation is an isolated point.


  We study here the interaction of $D \bar D^*$ in the isospin $I=1$ channel in
the light of recent theoretical advances that allow to combine elements of the
local hidden gauge approach with heavy quark spin symmetry. We find that the
exchange of light $q \bar q$ is OZI suppressed and, thus, we concentrate on the
exchange of heavy vectors and of two pion exchange. The latter is found to be
small compared to the exchange of heavy vectors, which then determines the
strength of the interaction. A barely $D\bar{D}^*$ bound state decaying into
$\eta_c\rho$ and $\pi J/\psi$ is found. At the same time we reanalyze the data
of the BESIII experiment on $e^+ e^- \to \pi^{\pm} (D \bar D^*)^\mp$, from
where a $Z_c(3885)$ state was claimed, associated to a peak in the $(D \bar
D^*)^\mp$ invariant mass distribution close to threshold, and we find the data
compatible with a resonance with mass around $3875$ MeV and width around $30$
MeV. We discuss the possibility that this and the $Z_c(3900)$ state found at
BESIII, reconfirmed at 3896 MeV at Belle, or 3885 MeV at CLEO, could all be the
same state and correspond to the one that we find theoretically.


  In this note we give a detailed proof of a result (sketched by Torsten
Ekedahl in a discussion with the first author several years ago), describing
complex tori admitting a rigid group action and showing explicitly their
projectivity and their structure in terms of CM-fields. In the appendix, joint
with Benoit Claudon, we show, using a method of Green-Voisin, that all group
actions on complex tori deform to projective ones.


  This thesis reports on work undertaken in comparing the effects of the
phenomenon of radiation reaction in classical and quantum theories of
electrodynamics. Specifically, it is concerned with the prediction of the
change in position of a particle due to the inclusion of the self-force in the
theory. We calculate this position shift for the classical theory, treating
radiation reaction as a perturbation in line with the reduction of order
procedure. We calculate the contributions to the position shift in the
$\hbar\to 0$ limit of quantum field theory to order $e^2$ in the coupling, the
order of the classical self-force. These calculations contain the emission and
forward scattering one loop processes of quantum electrodynamics. The quantum
calculations are completed for the case of a particle represented by a scalar
field wave packet and then for a particle represented by the Dirac spinor
field. We additionally give an alternative derivation of the scalar results
using the interpretation of radiation reaction via a Green's function
decomposition, in order to explain and contrast the results achieved.


  Consider a "simplicial molecule": $n$ equal point masses placed at the
vertices of a regular $(n-1)$-simplex, connected by ${n \choose 2}$ identical
springs. We apply the representation theory of the symmetric group $S_n$ to
compute its vibrational modes.


  In this paper we introduce a new fractional derivative with respect to
another function the so-called $\psi$-Hilfer fractional derivative. We discuss
some properties and important results of the fractional calculus. In this
sense, we present some uniformly convergent sequence of function results and
examples involving the Mittag-Leffler function with one parameter. Finally, we
present a wide class of integrals and fractional derivatives, by means of the
fractional integral with respect to another function and the $\psi$-Hilfer
fractional derivative.


  We study integrable models in the Bianchi I metric case with scalar fields
minimally and non-minimally coupled with gravity and the correspondence between
their general solutions. Using the model with a minimally coupled scalar field
and a constant potential as an example, we demonstrate how to obtain the
general solutions of the corresponding models in the Jordan frame.


  The dynamic time warping (DTW) distance has been used as a misfit function
for wave-equation inversion to mitigate the local minima issue. However, the
original DTW distance is not smooth; therefore it can yield a strong
discontinuity in the adjoint source. Such a weakness does not help nonlinear
inverse problems converge to a plausible minimum by any means. We therefore
introduce for the first time in geophysics the smooth DTW distance, which has
demonstrated its performance in time series classification, clustering, and
prediction as the loss function. The fundamental idea of such a distance is to
replace the $\min$ operator with its smooth relaxation. Then it becomes
possible to define the analytic derivative of DTW distance. The new misfit
function is entitled to the differentiable DTW distance. Moreover, considering
that the warping path is an indicator of the traveltime difference between the
observed and synthetic trace, a penalization term is constructed based on the
warping path such that the misfit accumulation by the penalized differentiable
DTW distance is weighted in favor of the traveltime difference. Numerical
examples demonstrate the advantage of the penalized differentiable DTW misfit
function over the conventional non-differentiable one.


  The aim of this paper is to construct accelerated, stationary and
axisymmetric exact solutions of the Einstein theory with self interacting
scalar fields in (A)dS4. To warm up, the backreaction of the (non)-minimally
coupled scalar field is solved, the scalar field equations are integrated and
all the potentials compatible with the metric ansatz and Einstein gravity are
found. With these results at hand the non-linear sigma model is tackled. The
scalar field Lagrangian is generic; neither the coupling to the curvature,
neither the metric in the scalar manifold nor the potential, are fixed ab
initio. The unique assumption in the analysis is the metric ansatz: it has the
form of the most general Petrov type D vacuum solution of general relativity;
it is a a cohomogeneity two Weyl rescaling of the Carter metric and therefore
it has the typical Plebanski-Demianski form with two arbitrary functions of one
variable and one arbitrary functions of two variables. It is shown, by an
straightforward manipulation of the field equations, that the metric is
completely integrable without necessity of specifiying anything in the scalar
Lagrangian. This results in that the backreaction of the scalar fields, within
this class of metrics, is universal. The metric functions generically show an
explicit dependence on a dynamical exponent that allows to smoothly connect
this new family of solutions with the actual Plebanski-Demianski spacetime. The
remaining field equations imply that the scalar fields follow geodesics in the
scalar manifold with an affine parameter given by a non-linear function of the
spacetime coordinates and define the on-shell form of the potential plus a
functional equation that it has to satisfy. Finally, a general family of (A)dS4
static hairy black holes is explicitly constructed and its properties are
outlined.


  A nuciferous graph is a simple graph with a non-singular $0$-$1$ adjacency
matrix $A$ such that all the diagonal entries of $A^{-1}$ are zero and all the
off-diagonal entries of $A^{-1}$ are non-zero. Sciriha et al. conjectured that
except $K_2$, no nuciferous graph exists. We disprove this conjecture.
Moreover, we conjecture that there infinitely many nuciferous Cayley graphs.


  Insulator-to-metal transition in Ca$_{2}$RuO$_{4}$ has drawn keen attention
because of its sensitivity to various stimulation and its potential
controllability. Here, we report a direct observation of Fermi surface, which
emerges upon introducing excess oxygen into an insulating Ca$_{2}$RuO$_{4}$, by
using angle-resolved photoemission spectroscopy. Comparison between energy
distribution curves shows that the Mott insulating gap is closed by eV-scale
spectral-weight transfer with excess oxygen. Momentum-space mapping exhibits
two square-shaped sheets of the Fermi surface. One is a hole-like $\alpha$
sheet around the corner of a tetragonal Brillouin zone, and the other is an
electron-like $\beta$ sheet around the $\Gamma$ point. The electron occupancies
of the $\alpha$ and $\beta$ bands are determined to be $n_{\alpha}=1.6$ and
$n_{\beta}=0.6$, respectively. Our result indicates that the insulator-to-metal
transition occurs selectively in $d_{xz}$ and $d_{yz}$ bands and not yet in
$d_{xy}$ band. This orbital selectivity is most likely explained in terms of
the energy level of $d_{xy}$, which is deeper for Ca$_{2}$RuO$_{4+\delta}$ than
for Ca$_{1.8}$Sr$_{0.2}$RuO$_{4}$. Consequently, we found substantial
differences from the Fermi surface of other ruthenates, shedding light on a
unique role of excess oxygen among the metallization methods of
Ca$_{2}$RuO$_{4}$.


  Motivated by string theory connection, a covariant procedure for perturbative
calculation of the partition function of the two-dimensional generalized
$\sigma$-model is considered. The importance of a consistent regularization of
the measure in the path integral is emphasized. The partition function is
computed for a number of specific 2-manifolds: sphere, disk and torus.


  We use the $1/N_c$ expansion of QCD to analyze the spectrum of positive
parity resonances with strangeness $S = 0, -1, -2$ and -3 in the 2--3 GeV mass
region, supposed to belong to the $[\textbf{56},4^+]$ multiplet. The mass
operator is similar to that of $[\textbf{56},2^+]$, previously studied in the
literature. The analysis of the latter is revisited. In the $[\textbf{56},4^+]$
multiplet we find that the spin-spin term brings the dominant contribution and
that the spin-orbit term is entirely negligible in the hyperfine interaction,
in agreement with constituent quark model results. More data are strongly
desirable, especially in the strange sector in order to fully exploit the power
of this approach.}


  This Letter proposes a new signature for confining dark sectors at the LHC.
Under the assumption of a QCD-like hidden sector, hadronic jets containing
stable dark bound states originating from hidden strong dynamics, known as
semi-visible jets, could manifest in proton-proton collisions. In the proposed
simplified model, a heavy $Z'$ mediator coupling to SM quarks allows the
resonant production of dark quarks, subsequently hadronizing in stable and
unstable dark bound states. The unstable dark bound states can then decay back
to SM quarks via the same $Z'$ portal or photons via a lighter pseudo-scalar
portal (such as an axion-like particle). This mechanism creates a new signature
where semi-visible jets are enriched in non-isolated photons. We show that
these exotic jets evade the phase space probed by current LHC searches
exploiting jets or photons due to the expected high jet neutral electromagnetic
fraction and photons candidates non-isolation, respectively. In the proposed
analysis strategy to tackle such signature, we exploit jets as final state
objects to represent the underlying QCD-like hidden sector. We show that, by
removing any selection on the neutral electromagnetic fraction from the jet
identification criteria, higher signal efficiency can be reached. To enhance
the signal-to-background discrimination, we train a deep neural network as a
jet tagger that exploits differences in the substructure of signal and
background jets. We estimate that with the available triggers for Run 2 and
this new strategy, a high mass search can claim a $5 \sigma$ discovery
(exclusion) of the $Z'$ boson with a mass up to 5 TeV (5 TeV) with the full Run
2 data of the LHC when the fraction of unstable dark hadrons decaying to
photons pairs is around 30 %, and with a coupling of the $Z'$ to SM quarks of
0.25.


  The equation of state of QCD at finite temperatures and baryon densities has
a wide range of applications in many fields of modern particle and nuclear
physics. It is the main ingredient to describe the dynamics of experimental
heavy ion collisions, the expansion of the early universe in the standard model
era and the interior of compact stars. On most scales of interest, QCD is
strongly coupled and not amenable to perturbative investigations. Over the last
decade, first principles calculations using lattice QCD have reached maturity,
in the sense that for particular discretisation schemes simulations at the
physical point have become possible, finite temperature results near the
continuum limit are available and systematic errors begin to be controlled.
This review summarises the current theoretical and numerical state of the art
based on staggered and Wilson fermions.


  We study the quantum thermal transport of elastic excitations through a
two-dimensional elastic waveguide between two thermal reservoirs. We solve the
classical Kirchhoff-Love equation for rectangular wires and explore the
dispersion relation for both the symmetric and antisymmetric solutions. Then,
we study the phonon transport of these modes within the second quantization
framework by analyzing the mean quadratic displacement, from which the energy
density current, the temperature field, and conductance are determined. We
identify the relevant modes contributing to thermal transport and explore the
average temperature difference to reach the high-temperature limit. We expect
our results to pave the way for understanding phonon-mediated thermal transport
in two-dimensional mesoscopic quantum devices.


  This study broadens the scope of theoretical frameworks in deep learning by
delving into the dynamics of neural networks with inputs that demonstrate the
structural characteristics to Gaussian Mixture (GM). We analyzed how the
dynamics of neural networks under GM-structured inputs diverge from the
predictions of conventional theories based on simple Gaussian structures. A
revelation of our work is the observed convergence of neural network dynamics
towards conventional theory even with standardized GM inputs, highlighting an
unexpected universality. We found that standardization, especially in
conjunction with certain nonlinear functions, plays a critical role in this
phenomena. Consequently, despite the complex and varied nature of GM
distributions, we demonstrate that neural networks exhibit asymptotic behaviors
in line with predictions under simple Gaussian frameworks.


  After the detection of GRB 170817A, the first unambiguous off-axis gamma-ray
burst (GRB), several studies tried to understand the structure of GRB jets. The
initial jet structure (directly produced by the central engine) can be
partially preserved, or can be completely modified by the interaction with the
environment. In this study, we perform three-dimensional, special relativistic
hydrodynamics simulations of long GRB jets evolving through a massive
progenitor star. Different jet scenarios were considered: Top-hat, Gaussian
jets dominated by pressure or by kinetic energy, as well as a model of a
supernova (SN) plus a jet both propagating through the progenitor. We found
that, while propagating inside the progenitor star, jets with different initial
structures are nearly indistinguishable. Kinetic dominated jets are faster and
more collimated than pressure dominated jets. The dynamics of jets inside the
progenitor star strongly depends on the presence of an associated SN, which can
substantially decelerate the jet propagation. We show that the initial
structure of GRB jets is preserved, or not, mainly depending on the jet
collimation. The initial structure is preserved in uncollimated jets, i.e. jets
which move through low density environments. Meanwhile, jets which move through
dense environments are shaped by the interaction with the medium and remain
collimated.


  Detection of AC magnetic fields at the nanoscale is critical in applications
ranging from fundamental physics to materials science. Isolated quantum spin
defects, such as the nitrogen-vacancy center in diamond, can achieve the
desired spatial resolution with high sensitivity. Still, vector AC magnetometry
currently relies on using different orientations of an ensemble of sensors,
with degraded spatial resolution, and a protocol based on a single NV is
lacking. Here we propose and experimentally demonstrate a protocol that
exploits a single NV to reconstruct the vectorial components of an AC magnetic
field by tuning a continuous driving to distinct resonance conditions. We map
the spatial distribution of an AC field generated by a copper wire on the
surface of the diamond. The proposed protocol combines high sensitivity, broad
dynamic range, and sensitivity to both coherent and stochastic signals, with
broad applications in condensed matter physics, such as probing spin
fluctuations.


  Typical users are known to use and reuse weak passwords. Yet, as
cybersecurity concerns continue to rise, understanding the password practices
of software developers becomes increasingly important. In this work, we examine
developers' passwords on public repositories. Our dedicated crawler collected
millions of passwords from public GitHub repositories; however, our focus is on
their unique characteristics. To this end, this is the first study
investigating the developer traits in password selection across different
programming languages and contexts, e.g. email and database. Despite the fact
that developers may have carelessly leaked their code on public repositories,
our findings indicate that they tend to use significantly more secure
passwords, regardless of the underlying programming language and context.
Nevertheless, when the context allows, they often resort to similar password
selection criteria as typical users. The public availability of such
information in a cleartext format indicates that there is still much room for
improvement and that further targeted awareness campaigns are necessary.