  Creation procedure of associative patterns ensemble in terms of formal logic
with using neural net-work (NN) model is formulated. It is shown that the
associative patterns set is created by means of unique procedure of NN work
which having individual parameters of entrance stimulus transformation. It is
ascer-tained that the quantity of the selected associative patterns possesses
is a constant.


  We present VLA HI imaging of four LSB galaxies which were thought to strongly
deviate from the TF relation based on Arecibo single-dish observations. We do
not detect three of the four targeted LSB galaxies in HI down to a 4-sigma
limit of 0.08Jy km/s. We find that two of the four of these LSBs have bright
galaxies which have contaminated the Arecibo signal. A further examination of
the Arecibo sample shows that five out of the six galaxies that were found to
deviate from TF have nearby bright galaxies and we conclude that possibly all
but one of the non-TF galaxies are contaminated by HI from nearby galaxies. The
sixth galaxy was not detected by us. A new observation by Arecibo did not
confirm the earlier detection. The integrated profiles of the bright galaxies
are consistent with the Arecibo results both in velocity range and amplitude,
which indicates that most of the extreme deviators from the TF relation must
have been affected by bright companions in this earlier HI survey. A more
recent determination of the sidelobe structure of the Arecibo beam supports our
conclusion and shows that the degree of sidelobe contamination was much larger
than could have been initially predicted. Hence, we have corrected the results
found in O'Neil et al. (2000) and have reconstructed the TF relation. These new
observations then show a) a reconstructed TF relation that has relatively large
scatter at all values of rotational velocity (possibly indicating the true
range in disk galaxy properties) and b) the presence of at least some red, gas
poor, LSB disks that indeed may be in an advanced evolutionary state as the
faded remnants of their former high surface brightness actively star forming
state.


  In our earlier work math.QA/9808015 some results on integral representations
of functions in quantum disc were announced. It was then shown in
math.QA/9808037 that the validity of those results is related to the invariance
of kernels of some integral operators. We introduce here a method which allows
us to prove the invariance of the above kernels.


  Collective cell migration is key during development, wound healing and
metastasis and relies on coordinated cell behaviors at the group level. Src
kinase is a signalling enzyme regulating many cellular processes including
adhesion and motility and its deregulated activation has been associated to
aggressiveness of different cancers. Here, we take advantage of optogenetics to
precisely control Src activation in time to study the effect of its over
activation on collective rotation of confined monolayers. We show that Src
activation slows down collective rotation of epithelial cells confined into
circular adhesive patches. We interpret velocity, force and stress data during
period of non-activation and period of activation of Src thanks to an
hydrodynamic description of the cell assembly as a polar active fluid. Src
activation leads to a 2-fold decrease in the ratio of polar angle to friction,
which could result from increased adhesive bonds at the cell-substrate
interface. Our work reveals the importance of fine-tuning the level of Src
activity for coordinated collective behaviors.


  One of the primary challenges of visual storytelling is developing techniques
that can maintain the context of the story over long event sequences to
generate human-like stories. In this paper, we propose a hierarchical deep
learning architecture based on encoder-decoder networks to address this
problem. To better help our network maintain this context while also generating
long and diverse sentences, we incorporate natural language image descriptions
along with the images themselves to generate each story sentence. We evaluate
our system on the Visual Storytelling (VIST) dataset and show that our method
outperforms state-of-the-art techniques on a suite of different automatic
evaluation metrics. The empirical results from this evaluation demonstrate the
necessities of different components of our proposed architecture and shows the
effectiveness of the architecture for visual storytelling.


  In many real-world settings, an agent must learn to act in environments where
no reward signal can be specified, but a set of expert demonstrations is
available. Imitation learning (IL) is a popular framework for learning policies
from such demonstrations. However, in some cases, differences in observability
between the expert and the agent can give rise to an imitation gap such that
the expert's policy is not optimal for the agent and a naive application of IL
can fail catastrophically. In particular, if the expert observes the Markov
state and the agent does not, then the expert will not demonstrate the
information-gathering behavior needed by the agent but not the expert. In this
paper, we propose a Bayesian solution to the Imitation Gap (BIG), first using
the expert demonstrations, together with a prior specifying the cost of
exploratory behavior that is not demonstrated, to infer a posterior over
rewards with Bayesian inverse reinforcement learning (IRL). BIG then uses the
reward posterior to learn a Bayes-optimal policy. Our experiments show that
BIG, unlike IL, allows the agent to explore at test time when presented with an
imitation gap, whilst still learning to behave optimally using expert
demonstrations when no such gap exists.


  The Haldane phase for antiferromagnetic spin-1 chains is a celebrated
topological state of matter, featuring gapped excitations and fractional
spin-1/2 edge states. Here, we provide numerical evidence that this phase can
be realized with a Hubbard model at half filling, where each $s=1$ spin is
stored in a four-site fermionic structure. We find that the noninteracting
limit of our proposed model describes a one-dimensional topological insulator,
and we conjecture it to be adiabatically connected to the Haldane phase. Our
work suggests a route to build spin-1 networks using Hubbard model quantum
simulators.


  We propose Neural Cellular Automata (NCA) to simulate the microstructure
development during the solidification process in metals. Based on convolutional
neural networks, NCA can learn essential solidification features, such as
preferred growth direction and competitive grain growth, and are up to six
orders of magnitude faster than the conventional Cellular Automata (CA).
Notably, NCA delivers reliable predictions also outside their training range,
which indicates that they learn the physics of the solidification process.
While in this study we employ data produced by CA for training, NCA can be
trained based on any microstructural simulation data, e.g. from phase-field
models.


  We investigate the effect of redshift-space distortions in the power spectrum
parallel and perpendicular to the observer's line of sight, P(k_par,k_perp),
using the optically selected Durham/UKST Galaxy Redshift Survey. On small,
non-linear scales anisotropy in the power-spectrum is dominated by the galaxy
velocity dispersion; the `Finger of God' effect. On larger, linear scales
coherent peculiar velocities due to the infall of galaxies into overdense
regions are the main cause of anisotropy. According to gravitational
instability theory these distortions depend only on the density and bias
parameters via beta. Geometrical distortions also occur if the wrong cosmology
is assumed, although these would be relatively small given the low redshift of
the survey. To quantify these effects, we assume the real-space power spectrum
of the APM Galaxy Survey, and fit a simple model for the redshift-space and
geometrical distortions. Assuming a flat Omega = 1 universe, we find values for
the one-dimensional pairwise velocity dispersion of sigma_p = 410 +- 170 km/s,
and beta = 0.38 +- 0.17. An open Omega = 0.3, and a flat Omega = 0.3, Lambda =
0.7 universe yield sigma_p = 420 km/s, beta = 0.40, and sigma_p = 440 km/s,
beta = 0.45 respectively, with comparable errors. These results are consistent
with estimates using the two-point galaxy correlation function, xi(sigma,pi),
and favour either a low-density universe with Omega ~ 0.3 if galaxies trace the
underlying mass distribution, or a bias factor of b ~ 2.5 if Omega = 1.


  We study the dynamics of colliding domain walls including self-gravity. The
initial data is set up by applying a BPS domain wall in five-dimensional
supergravity, and we evolve the system determining the final outcome of
collisions. After a collision, a spacelike curvature singularity covered by a
horizon is formed in the bulk, resulting in a black brane with trapped domain
walls. This is a generic consequence of collisions, except for non-relativistic
weak field cases, in which the walls pass through one another or multiple
bounces take place without singularity formation. These results show that
incorporating the self-gravity drastically changes a naive picture of colliding
branes.


  We present our results on the non-perturbative evaluation of the
renormalization constant for the quark field, $Z_q$, in Landau gauge within
RI-MOM scheme. Using three lattice spacing we are able to isolate lattice
artefacts of various origin, both perturbative and non-perturbative. In
particular, the existence of the dimension-two gluon-condensate is discussed,
and confirmed.


  We give some examples of EP and non-EP operators to show that the main
results of Mohammadzadeh Karizakia {\it et al} [Some results about EP modular
operators, {\it Linear and Multilinear Algebra}, DOI:
10.1080/03081087.2020.1844613] are not correct even in the case of Hilbert
spaces.


  Measurements of heavy flavor production in heavy-ion collisions have played
an important role in understanding the properties of the quark-gluon plasma
created in such collision. Due to their large masses, heavy flavor quarks
present unique sensitivity to the kinematics as well as the dynamics of the hot
and dense medium. In this article, a selection of recent measurements on heavy
flavor production in p+p, p+A and A+A collisions at both RHIC and LHC energies
will be presented. The measurements in p+p collisions serve as benchmarks to
fundamental theories, and as references to similar studies in A+A collisions
where the hot medium effects are present. On the other hand, the measurements
in p+A collisions can help to quantify the cold nuclear matter effects which
are also in effect in A+A collisions and thus need to be taken into account
when interpreting the measurements in heavy-ion collisions. The experimental
results from A+A collisions are discussed and compared to theoretical
calculations, which can shed lights on the understanding of the quark-gluon
plasma.


  Given a sample of a random variable supported by a smooth compact manifold
$M\subset \mathbb{R}^d$, we propose a test to decide whether the boundary of
$M$ is empty or not with no preliminary support estimation. The test statistic
is based on the maximal distance between a sample point and the average of its
$k_n$-nearest neighbors. We prove that the level of the test can be estimated,
that, with probability one, its power is one for $n$ large enough, and that
there exists a consistent decision rule. Heuristics for choosing a convenient
value for the $k_n$ parameter and identifying observations close to the
boundary are also given. We provide a simulation study of the test.


  A method is presented for the evaluation of the permeability-porosity
relationship in a low-permeability porous material using the results of a
single transient test. This method accounts for both elastic and non-elastic
deformations of the sample during the test and is applied to a hardened class G
oil well cement paste. An initial hydrostatic undrained loading is applied to
the sample. The generated excess pore pressure is then released at one end of
the sample while monitoring the pore pressure at the other end and the radial
strain in the middle of the sample during the dissipation of the pore pressure.
These measurements are back analysed to evaluate the permeability and its
evolution with porosity change. The effect of creep of the sample during the
test on the measured pore pressure and volume change is taken into account in
the analysis. This approach permits to calibrate a power law
permeability-porosity relationship for the tested hardened cement paste. The
porosity sensitivity exponent of the power-law is evaluated equal to 11 and is
shown to be mostly independent of the stress level and of the creep strains.


  The odd-even staggering of neighboring nuclear masses is very useful in
calculating local mass relations and nucleon-pair correlations. During the past
decades, there has been an increasing interest in the odd-even features of the
mass relations and related quantities exhibited in masses of neighboring
nuclei. In this work, after choosing a nucleus, we made an analysis of its
neighboring nuclei on the upper left corner and the lower right corner
respectively. We empirically obtained a new residual interaction formula of
even-$A$ ($A$ is the mass number) nuclei, and it is an revision based on the
existing empirical local formula of the proton-neutron interactions between the
last proton and the last neutron ($\delta V_{1p-1n}$). We then calculated the
even-$A$ nuclear masses. The differences between our calculated values and the
AME2012 database show that the root-mean-squared deviations (RMSD) are small
(for even-$A$ nuclei: $A$ $\geq$ 42, RMSD $\approx$ 161 keV; $A$ $\geq$ 100,
RMSD $\approx$ 125 keV), while for heavy nuclei, some of our calculated values
can reach an accuracy of a few tens of keV. With our residual interaction
formula including one parameter, we have successfully predicted some unknown
masses. Some of our predicted values compared well with the experimental values
(AME2016). In addition, the accuracy and simplicity of our predicted masses for
medium and heavy nuclei are comparable to those of the AME2012 (AME2016)
extrapolations.


  This paper is the second in a series of five that together prove the
geometric Langlands conjecture. Our goals are two-fold:
  (1) Formulate and prove the Fundamental Local Equivalence (FLE) at the
critical level;
  (2) Study the interaction between Kac-Moody localization and the global
geometric Langlands functor of ref. [GLC1].
  This paper contains an extensive Appendix, whose primary goals are:
  (a) Development the theory of ind-coherent sheaves in infinite type;
  (b)Development of the formalism of factorization categories.


  We review the phenomenology of classical Cepheids (CCs), Anomalous Cepheids
(ACs) and type II Cepheids (TIICs) in the Milky Way (MW) and in the Magellanic
Clouds (MCs).
  We also examine the Hertzsprung progression in different stellar systems by
using the shape of I-band light curves (Fourier parameters) and observables
based on the difference in magnitude and in phase between the bump and the
minimum in luminosity.
  The distribution of Cepheids in optical and in optical-near infrared (NIR)
color--magnitude diagrams is investigated to constrain the topology of the
instability strip. The use of Cepheids as tracers of young (CCs), intermediate
(ACs) and old (TIICs) stellar populations are brought forward by the comparison
between observations (MCs) and cluster isochrones covering a broad range in
stellar ages and in chemical compositions.
  The different diagnostics adopted to estimate individual distances
(period--luminosity, period--Wesenheit, period--luminosity--color relations)
are reviewed together with pros and cons in the use of fundamental and
overtones, optical and NIR photometric bands, and reddening free pseudo
magnitudes (Wesenheit). We also discuss the use of CCs as stellar tracers and
the radial gradients among the different groups of elements (iron, alpha,
neutron-capture) together with their age-dependence.
  Finally, we briefly outline the role that near-future space and ground-based
facilities will play in the astrophysical and cosmological use of Cepheids.


  Ordinal scores occur commonly in medical imaging studies and in black-box
forensic studies \citep{Phillips:2018}. To assess the accuracy of raters in the
studies, one needs to estimate the receiver operating characteristic (ROC)
curve while accounting for covariates of raters. In this paper, we propose a
covariate-adjusted homogeneity test to determine differences in accuracy among
multiple rater groups. We derived the theoretical results of the proposed test
and conducted extensive simulation studies to evaluate the finite sample
performance of the proposed test. Our proposed test is applied to a face
recognition study to identify statistically significant differences among five
participant groups.


  We prove variation and oscillation $L^p$-inequalities associated with
fractional derivatives of certain semigroups of operators and with the family
of truncations of Riesz transforms in the inverse Gaussian setting. We also
study these variational $L^p$-inequalities in a Banach-valued context by
considering Banach spaces with the UMD-property and whose martingale cotype is
fewer than the variational exponent. We establish $L^p$-boundedness properties
for weighted difference involving the semigroups under consideration.


  Differential privacy (DP), as a rigorous mathematical definition quantifying
privacy leakage, has become a well-accepted standard for privacy protection.
Combined with powerful machine learning techniques, differentially private
machine learning (DPML) is increasingly important. As the most classic DPML
algorithm, DP-SGD incurs a significant loss of utility, which hinders DPML's
deployment in practice. Many studies have recently proposed improved algorithms
based on DP-SGD to mitigate utility loss. However, these studies are isolated
and cannot comprehensively measure the performance of improvements proposed in
algorithms. More importantly, there is a lack of comprehensive research to
compare improvements in these DPML algorithms across utility, defensive
capabilities, and generalizability.
  We fill this gap by performing a holistic measurement of improved DPML
algorithms on utility and defense capability against membership inference
attacks (MIAs) on image classification tasks. We first present a taxonomy of
where improvements are located in the machine learning life cycle. Based on our
taxonomy, we jointly perform an extensive measurement study of the improved
DPML algorithms. We also cover state-of-the-art label differential privacy
(Label DP) algorithms in the evaluation. According to our empirical results, DP
can effectively defend against MIAs, and sensitivity-bounding techniques such
as per-sample gradient clipping play an important role in defense. We also
explore some improvements that can maintain model utility and defend against
MIAs more effectively. Experiments show that Label DP algorithms achieve less
utility loss but are fragile to MIAs. To support our evaluation, we implement a
modular re-usable software, DPMLBench, which enables sensitive data owners to
deploy DPML algorithms and serves as a benchmark tool for researchers and
practitioners.


  We study the background risk model under a various forms of dependence and
some distribution classes of heavy tails. First, we study the asymptotic
behavior of tail expectation of a portfolios with unequal heavytailedness, of
non-random sums and randomly stopped sums, under some dependence structure
which contains the independence as a special case. Further we investigate the
asymptotic behavior of a pair of randomly weighted sums, generalizing the
dependence structure among random vector components, our results contains the
finite ruin probability in bi-dimensional discrete time risk model with unequal
heavytailedness. Next, we carry out asymptotic analysis of the tail distortion
risk measures in background risk model under various forms of dependence, with
multivariate regularly varying risk distributions in each portfolio.


  In this paper, we first study infinitesimal deformations of a Lie conformal
algebra and a Lie conformal algebra with a module (called an $\mathsf{LCMod}$
pair), which lead to the notions of Nijenhuis operator on the Lie conformal
algebra and Nijenhuis structure on the $\mathsf{LCMod}$ pair, respectively.
Then by adding compatibility conditions between Nijenhuis structures and
$\mathcal{O}$-operators, we introduce the notion of an $\mathcal{O}
N$-structure on an $\mathsf{LCMod}$ pair and show that an $\mathcal{O}
N$-structure gives rise to a hierarchy of pairwise compatible
$\mathcal{O}$-operators. In particular, we show that compatible
$\mathcal{O}$-operators on a Lie conformal algebra can be characterized by
Nijenhuis operators on Lie conformal algebras. Finally, we introduce the
notions of conformal $r$-matrix-Nijenhuis structure and symplectic-Nijenhuis
structure on the Lie conformal algebra and study their relations.


  The alpha and theta frequency brainwave activity in Electroencephalogram
(EEG) signal has been correlated with attention, inhibitory processes, memory,
perceptual abilities, and sleep. The enhanced alpha and theta brainwave
activity may bring positive behavioral modifications such as promoting
creativity and a quick sleep. Herein, we discover that infrared radiation from
multilayer graphene electrothermal film can obviously promote the appearance of
alpha and theta brainwave in human mind. In particular, the occurrence
frequency of the alpha and theta waves in EEG can be effectively enhanced up to
2.3 and 3.0 times, respectively. And the duration time of the alpha and theta
waves in EEG can also be effectively extended. The mechanism may be attributed
to the efficient infrared radiation caused by graphene mainly focused on the
range from 7 to 14 micron, coinciding with the radiation wavelength of natural
human body, which can be effectively absorbed by the human skin and speed up
the blood microcirculation and metabolism. The comparative effect of different
working temperature and heating materials such as water, Cu and even monolayer
graphene are systematically investigated, indicating the infrared radiation
from the multilayer graphene electrothermal film at 50 degrees has the largest
enhancement effect of alpha and theta brainwaves. The multilayer graphene film
electrical heater represents a convenient and surprising way for triggering the
alpha and theta brainwaves, which has many potential applications in the area
of enlarged health cerements.


  An inductive probabilistic classification rule must generally obey the
principles of Bayesian predictive inference, such that all observed and
unobserved stochastic quantities are jointly modeled and the parameter
uncertainty is fully acknowledged through the posterior predictive
distribution. Several such rules have been recently considered and their
asymptotic behavior has been characterized under the assumption that the
observed features or variables used for building a classifier are conditionally
independent given a simultaneous labeling of both the training samples and
those from an unknown origin. Here we extend the theoretical results to
predictive classifiers acknowledging feature dependencies either through
graphical models or sparser alternatives defined as stratified graphical
models. We also show through experimentation with both synthetic and real data
that the predictive classifiers based on stratified graphical models have
consistently best accuracy compared with the predictive classifiers based on
either conditionally independent features or on ordinary graphical models.


  I present theoretical results through three loops and N$^3$LO for soft-gluon
corrections in a variety of processes involving top-quark production. In
particular, I present results for total cross sections and differential
distributions in single-top production and top-pair production as well as in
top-quark processes with electroweak bosons and new physics.


  We investigate the influence of a perpendicular magnetic field on the
spectral and spin properties of a ballistic quasi-one-dimensional electron
system with Rashba effect. The magnetic field strongly alters the spin-orbit
induced modification to the subband structure when the magnetic length becomes
comparable to the lateral confinement. A new subband-dependent energy splitting
at k=0 is found which can be much larger than the Zeeman splitting. This is due
to the breaking of a combined spin orbital-parity symmetry.


  We derive fundamental limits on measurements of position, arising from
quantum mechanics and classical general relativity. First, we show that any
primitive probe or target used in an experiment must be larger than the Planck
length, $l_P$. This suggests a Planck-size {\it minimum ball} of uncertainty in
any measurement. Next, we study interferometers (such as LIGO) whose precision
is much finer than the size of any individual components and hence are not
obviously limited by the minimum ball. Nevertheless, we deduce a fundamental
limit on their accuracy of order $l_P$. Our results imply a {\it device
independent} limit on possible position measurements.


  The first obstacle that regular users encounter when setting up a node for a
public blockchain is the time taken for downloading all the data needed for the
node to start operating correctly. In fact, this may last from hours to weeks
for the major networks. Our contribution is twofold. Firstly, we show a design
that enables mining and validation of new blocks keeping only a very small
state. Secondly, we show that it is possible to store the state of the
blockchain in a distributed hash table obtaining a wide spectrum of trade-offs
between storage committed by the nodes and replication factor. Our proposal is
independent from the consensus algorithm adopted, and copes well with
transactions that involve smart contracts.


  We study "random surfaces," which are random real (or integer) valued
functions on Z^d. The laws are determined by convex, nearest neighbor,
difference potentials that are invariant under translation by a full-rank
sublattice L of Z^d; they include many discrete and continuous height models
(e.g., domino tilings, square ice, the harmonic crystal, the Ginzburg-Landau
grad-phi interface model, the linear solid-on-solid model) as special cases.
  A gradient phase is an L-ergodic gradient Gibbs measure with finite specific
free energy. A gradient phase is smooth if it is the gradient of an ordinary
Gibbs measure; otherwise it is rough. We prove a variational
principle--characterizing gradient phases of a given slope as minimizers of the
specific free energy--and an empirical measure large deviations principle (with
a unique rate function minimizer) for random surfaces on mesh approximations of
bounded domains.
  Using a geometric technique called "cluster swapping" (a variant of the
Swendsen-Wang update for Fortuin-Kasteleyn clusters), we also prove that the
surface tension is strictly convex and that if u is in the interior of the
space of finite-surface tension slopes, then there exists a minimal energy
gradient phase mu_u of slope u. This mu_u is always unique for real valued
random surfaces.
  In the discrete models, mu_u is unique if at least one of the following
holds: d is in {1, 2}, there exists a rough gradient phase of slope u, or u is
irrational. When d=2, the slopes of all smooth phases (a.k.a. crystal facets)
lie in the dual lattice of L.


  Let Rat_k be the space of based holomorphic maps from S^2 to itself of degree
k. Let beta_k denote the Artin's braid group on k strings and let Bbeta_k be
the classifying space of beta_k. Let C_k denote the space of configurations of
length less than or equal to k of distinct points in R^2 with labels in S^1.
The three spaces Rat_k, Bbeta_{2k}, C_k are all stably homotopy equivalent to
each other. For an odd prime p, the F_p-cohomology ring of the three spaces are
isomorphic to each other. The F_2-cohomology ring of Bbeta_{2k} is isomorphic
to that of C_k. We show that for all values of k except 1 and 3, the
F_2-cohomology ring of Rat_k is not isomorphic to that of Bbeta_{2k} or C_k.
This in particular implies that the HF_2-localization of Rat_k is not homotopy
equivalent to HF_2-localization of Bbeta_{2k} or C_k. We also show that for k
>= 1, Bbeta_{2k} and Bbeta_{2k+1} have homotopy equivalent HF_2-localizations.


  Anisotropic ideal strength is a fundamental and important plasticity
parameter in scaling the intrinsic strength of strong crystalline materials,
and is a potential descriptor in searching and designing novel hard/superhard
materials. However, to the best of our knowledge, an automatic derivation of
anisotropic ideal strength has not been implemented in any open-source code
available so far. In this paper, we present our developed ADAIS code, an
automatic derivation of anisotropic ideal strength via high-throughput
first-principles computations for both three-dimensional and two-dimensional
crystalline materials with any symmetry, as well as for an ideal interface
model. Several fundamental mechanical quantities can be automatically derived,
including ideal tensile and shear strengths through affine deformation,
universal binding energy and generalized stacking fault energy, as well as the
ideal cleavage and slide stresses through alias deformation. The implementation
of this code has been comprehensively demonstrated and critically validated by
a lot of evaluations and tests of various crystalline materials with different
symmetry, indicating that our code could provide a high-efficiency solution to
quantify the strength of strong solids.


  Engineering materials to include nanoscale porosity or other nanoscale
structures has become a well-established strategy for enhancing the
thermoelectric performance of dielectrics. However, the approach is only
considered beneficial for materials where the intrinsic phonon mean-free path
is much longer than that of the charge carriers. As such, the approach would
not be expected to provide significant performance gains in polycrystalline
semiconducting alloys, such as SixGe1-x, where mass disorder and grains provide
strong phonon scattering. In this manuscript, we demonstrate that the addition
of nanoscale porosity to even ultrafine-grained Si0.8Ge0.2 may be worthwhile.
The semiclassical Boltzmann transport equation was used to model electrical and
phonon transport in polycrystalline Si0.8Ge0.2 containing prismatic pores
perpendicular to the transport current. The models are free of tuning
parameters and were validated against experimental data. The models reveal that
a combination of pores and grain boundaries suppresses phonon conductivity to a
magnitude comparable with the electronic thermal conductivity. In this regime,
ZT can be further enhanced by reducing carrier concentration to the electrical
and electronic thermal conductivity and simultaneously increasing thermopower.
Although increases in ZT are modest, the optimal carrier concentration is
significantly lowered, meaning semiconductors need not be so strongly
supersaturated with dopants.


  We show that the translation length of any parabolic isometry on a complete
semi-uniformly visible CAT(0) space is always zero. As a consequence, we will
classify the isometries on visible CAT(0) spaces in terms of translation
lengths. We will also show that the moduli space $\mathbb{M}(S_{g,n})$ of
surface $S_{g,n}$ of $g$ genus with $n$ punctures admits no complete visible
CAT(0) Riemannian metric if $3g+n\geq 5$, which answers the Brock-Farb-McMullen
question in the visible case.


  Monotone systems, also known as order-preserving or cooperative systems, are
prevalent in models of engineering applications such as transportation and
biological networks. In this paper, we investigate the problem of finding a
control strategy for a discrete time monotone system with bounded uncertainties
such that the evolution of the system is guaranteed to be confined to a safe
set in the state space for all times. By exploiting monotonicity, we propose an
approach to this problem which is based on constraint programming. We find
control strategies that are based on repetitions of finite sequences of control
actions. We show that, under assumptions made in the paper, safety control of
monotone systems does not require state measurement. We demonstrate the results
on a signalized urban traffic network, where the safety objective is to keep
the traffic flow free of congestion.


  We prove the existence of multiple positive radial solutions to the
sign-indefinite elliptic boundary blow-up problem \[ \left\{\begin{array}{ll}
\Delta u + \bigl(a^+(\vert x \vert) - \mu a^-(\vert x \vert)\bigr) g(u) = 0, &
\; \vert x \vert < 1, \\ u(x) \to \infty, & \; \vert x \vert \to 1, \end{array}
\right. \] where $g$ is a function superlinear at zero and at infinity, $a^+$
and $a^-$ are the positive/negative part, respectively, of a sign-changing
function $a$ and $\mu > 0$ is a large parameter. In particular, we show how the
number of solutions is affected by the nodal behavior of the weight function
$a$. The proof is based on a careful shooting-type argument for the equivalent
singular ODE problem. As a further application of this technique, the existence
of multiple positive radial homoclinic solutions to $$ \Delta u +
\bigl(a^+(\vert x \vert) - \mu a^-(\vert x \vert)\bigr) g(u) = 0, \qquad x \in
\mathbb{R}^N, $$ is also considered.


  Cromwell's rule (also known as the zero priors paradox) refers to the
constraint of classical probability theory that if one assigns a prior
probability of 0 or 1 to a hypothesis, then the posterior has to be 0 or 1 as
well (this is a straightforward implication of how Bayes's rule works).
Relatedly, hypotheses with a very low prior cannot be updated to have a very
high posterior without a tremendous amount of new evidence to support them (or
to make other possibilities highly improbable). Cromwell's rule appears at odds
with our intuition of how humans update probabilities. In this work, we report
two simple decision making experiments, which seem to be inconsistent with
Cromwell's rule. Quantum probability theory, the rules for how to assign
probabilities from the mathematical formalism of quantum mechanics, provides an
alternative framework for probabilistic inference. An advantage of quantum
probability theory is that it is not subject to Cromwell's rule and it can
accommodate changes from zero or very small priors to significant posteriors.
We outline a model of decision making, based on quantum theory, which can
accommodate the changes from priors to posteriors, observed in our experiments.


  We present an explicit classical dyon solution for the noncommutative version
of the Yang-Mills-Higgs model (in the Prasad-Sommerfield limit) with a tehta
term. We show that the relation between classical electric and magnetic charges
also holds in noncommutative space. Extending the Noether approach to the case
of a noncommutative gauge theory, we analyze the effect of CP violation at the
quantum level, induced both by the theta term and by noncommutativity and we
prove that the Witten effect formula for the dyon charge remains the same as in
ordinary space.


  We propose a new method for defragmenting the module layout of a
reconfigurable device, enabled by a novel approach for dealing with
communication needs between relocated modules and with inhomogeneities found in
commonly used FPGAs. Our method is based on dynamic relocation of module
positions during runtime, with only very little reconfiguration overhead; the
objective is to maximize the length of contiguous free space that is available
for new modules. We describe a number of algorithmic aspects of good
defragmentation, and present an optimization method based on tabu search.
Experimental results indicate that we can improve the quality of module layout
by roughly 50 % over static layout. Among other benefits, this improvement
avoids unnecessary rejections of modules


  We present deep optical imaging of the z=4.1 radio galaxy TN J1338--1942
obtained using the ACS on-board HST. The radio galaxy is known to reside within
a large galaxy overdensity (both in physical extent and density contrast).
There is good evidence that this `protocluster' region is the progenitor of a
present-day rich galaxy cluster. TN J1338 is the dominant galaxy in the
protocluster, in terms of size and luminosity and therefore seems destined to
evolve into the brightest cluster galaxy. The high spatial-resolution ACS
images reveal several kpc-scale features within and around the radio galaxy.
The continuum light is aligned with the radio axis and is resolved into two
clumps in the i-band and z-band bands. These components have luminosities ~10^9
L_sun and sizes of a few kpc. The estimated star-formation rate for the whole
radio galaxy is ~200 M_sun/yr. A simple model in which the jet has triggered
star-formation in these continuum knots is consistent with the available data.
An unusual feature is seen in Lyman-alpha emission. A wedge-shaped extension
emanates from the radio galaxy perpendicularly to the radio axis. This `wedge'
naturally connects to the surrounding, asymmetric, large-scale (~100 kpc)
Lyman-alpha halo. We posit that the wedge is a starburst-driven superwind,
associated with the first major epoch of formation of the brightest cluster
galaxy. The shock and wedge are examples of feedback processes due to both AGN
and star-formation in the earliest stages of massive galaxy formation.


  We investigate monogenicity and prime splitting in extensions generated by
roots of iterated quadratic polynomials. Let $f(x)\in\mathbb{Z}[x]$ be an
irreducible, monic, quadratic polynomial, and write $f^n(x)$ for the
$n^{\text{th}}$ iterate. We obtain necessary and sufficient conditions for
$f^n(x)$ to be monogenic for each $n$. We use this to construct multiple
families where $f^n(x)$ is monogenic for every $n>0$.


  Extracting environmental forces from noisy data is a common yet challenging
task in complex physical systems. Machine learning represents a robust approach
to this problem, yet is mostly tested on simulated data with known parameters.
Here we use supervised machine learning to extract the electrostatic,
hydrodynamic, and stochastic forces acting on micron-sized charged particles
levitated in an argon plasma. Trained on simulated particle trajectories using
more than 100 dynamical and statistical features, the model predicts system
parameters with 50\% better accuracy than conventional methods, and provides
non-contact measurements of the particle charge and Debye length.


  Many dynamical systems, such as the Lotka-Volterra predator-prey model and
the Euler equations for the free rotation of a rigid body, are PT symmetric.
The standard and well-known real solutions to such dynamical systems constitute
an infinitessimal subclass of the full set of complex solutions. This paper
examines a subset of the complex solutions that contains the real solutions,
namely, those having PT symmetry. The condition of PT symmetry selects out
complex solutions that are periodic.


  We investigate numerically the model proposed in Sahoo et al [Phys. Rev.
Lett. 118, 164501, (2017)] where a parameter $\lambda$ is introduced in the
Navier-Stokes equations such that the weight of homochiral to heterochiral
interactions is varied while preserving all original scaling symmetries and
inviscid invariants. Decreasing the value of $\lambda$ leads to a change in the
direction of the energy cascade at a critical value $\lambda_c \sim 0.3$. In
this work, we perform numerical simulations at varying $\lambda$ in the forward
energy cascade range and at changing the Reynolds number $\mathrm{Re}$. We show
that for a fixed injection rate, as $\lambda \to \lambda_c$, the kinetic energy
diverges with a scaling law $\mathcal{E} \propto (\lambda-\lambda_c)^{-2/3}$.
The energy spectrum is shown to display a larger bottleneck as $\lambda$ is
decreased. The forward heterochiral flux and the inverse homochiral flux both
increase in amplitude as $\lambda_c$ is approached while keeping their
difference fixed and equal to the injection rate. As a result, very close to
$\lambda_c$ a stationary state is reached where the two opposite fluxes are of
much higher amplitude than the mean flux and large fluctuations are observed.
Furthermore, we show that intermittency as $\lambda_c$ is approached is
reduced. The possibility of obtaining a statistical description of regular
Navier-Stokes turbulence as an expansion around this newly found critical point
is discussed.


  In polymeric quantum theories, a natural question pertains to the so called
continuum limit, corresponding to the limit where the `discreteness parameter'
$\lambda$ approaches zero. In particular one might ask whether the limit exists
and, in that case, what the limiting theory is. Here we review recent results
on the classical formulation of the problem for a soluble model in loop quantum
cosmology. We show that it is only through the introduction of a particular
$\lambda$-dependent internal time function that the limit $\lambda\to 0$ can be
well defined. We then compare this result with the existing analysis in the
quantum theory, where the dynamics was cast in terms of an internal
($\lambda$-independent) parameter for which the limit does not exist. We
briefly comment on the steps needed to define the corresponding time parameter
in the quantum theory for which the limit was shown to exist classically.


  We derive simple relations between the polarized and unpolarized valence
quark distributions in a light-cone SU(6) quark-spectator model for nucleons.
The explicit x-dependent Wigner rotation effect for the light-flavor quarks is
calculated. It is shown that the mass difference between the scalar and vector
spectators could reproduce the up and down valence quark asymmetry that
accounts for the observed ratio $F_2^{n}/F_2^{p}$. The proton, neutron, and
deuteron polarization asymmetries, $A_1^p$, $A_1^n$, and $A_1^d$, are in
agreement with the available data by taking into account the Wigner rotation
effect. The calculated $x$-dependent helicity distributions of the up and down
valence quarks are compared with the recent results from semi-inclusive hadron
asymmetries in polarized deep inelastic scattering by the Spin Muon
Collaboration.


  In the context of arithmetic surfaces, Bost defined a generalized Arithmetic
Chow Group
  (ACG) using the Sobolev space L^2_1. We study the behavior of these groups
under pull-back and push-forward and we prove a projection formula.
  We use these results to define an action of the Hecke operators on the ACG of
modular curves and to show that they are self-adjoint with respect to the
arithmetic intersection product. The decomposition of the ACG in
eigencomponents which follows allows us to define new numerical invariants,
which are refined versions of the self-intersection of the dualizing sheaf.
Using the Gross-Zagier formula and a calculation due independently to Bost and
Kuehn we compute these invariants in terms of special values of L series. On
the other hand, we obtain a proof of the fact that Hecke correspondences acting
on the Jacobian of the modular curves are self-adjoint with respect to the
N\'eron-Tate height pairing.


  We study assortative mixing in networks, the tendency for vertices in
networks to be connected to other vertices that are like (or unlike) them in
some way. We consider mixing according to discrete characteristics such as
language or race in social networks and scalar characteristics such as age. As
a special example of the latter we consider mixing according to vertex degree,
i.e., according to the number of connections vertices have to other vertices:
do gregarious people tend to associate with other gregarious people? We propose
a number of measures of assortative mixing appropriate to the various mixing
types, and apply them to a variety of real-world networks, showing that
assortative mixing is a pervasive phenomenon found in many networks. We also
propose several models of assortatively mixed networks, both analytic ones
based on generating function methods, and numerical ones based on Monte Carlo
graph generation techniques. We use these models to probe the properties of
networks as their level of assortativity is varied. In the particular case of
mixing by degree, we find strong variation with assortativity in the
connectivity of the network and in the resilience of the network to the removal
of vertices.


  Scientific machine learning (SciML) is a field of increasing interest in
several different application fields. In an optimization context, SciML-based
tools have enabled the development of more efficient optimization methods.
However, implementing SciML tools for optimization must be rigorously evaluated
and performed with caution. This work proposes the deductions of a robustness
test that guarantees the robustness of multiobjective SciML-based optimization
by showing that its results respect the universal approximator theorem. The
test is applied in the framework of a novel methodology which is evaluated in a
series of benchmarks illustrating its consistency. Moreover, the proposed
methodology results are compared with feasible regions of rigorous
optimization, which requires a significantly higher computational effort.
Hence, this work provides a robustness test for guaranteed robustness in
applying SciML tools in multiobjective optimization with lower computational
effort than the existent alternative.


  In most attempts to compute the Hartle-Hawking ``wave function of the
universe'' in Euclidean quantum gravity, two important approximations are made:
the path integral is evaluated in a saddle point approximation, and only the
leading (least action) extremum is taken into account. In (2+1)-dimensional
gravity with a negative cosmological constant, the second assumption is shown
to lead to incorrect results: although the leading extremum gives the most
important single contribution to the path integral, topologically inequivalent
instantons with larger actions occur in great enough numbers to predominate.
One can thus say that in 2+1 dimensions --- and possibly in 3+1 dimensions as
well --- entropy dominates action in the gravitational path integral.


  Crew pairing optimization (CPO) is critically important for any airline,
since its crew operating costs are second-largest, next to the fuel-cost. CPO
aims at generating a set of flight sequences (crew pairings) covering a
flight-schedule, at minimum-cost, while satisfying several legality
constraints. For large-scale complex flight networks, billion-plus legal
pairings (variables) are possible, rendering their offline enumeration
intractable and an exhaustive search for their minimum-cost full
flight-coverage subset impractical. Even generating an initial feasible
solution (IFS: a manageable set of legal pairings covering all flights), which
could be subsequently optimized is a difficult (NP-complete) problem. Though,
as part of a larger project the authors have developed a crew pairing optimizer
(AirCROP), this paper dedicatedly focuses on IFS-generation through a novel
heuristic based on divide-and-cover strategy and Integer Programming. For
real-world large and complex flight network datasets (including over 3200
flights and 15 crew bases) provided by GE Aviation, the proposed heuristic
shows upto a ten-fold speed improvement over another state-of-the-art approach.
Unprecedentedly, this paper presents an empirical investigation of the impact
of IFS-cost on the final (optimized) solution-cost, revealing that too low an
IFS-cost does not necessarily imply faster convergence for AirCROP or even
lower cost for the optimized solution.


  We determine exactly the mass-coupling relation for the simplest multi-scale
quantum integrable model, the homogenous sine-Gordon model with two independent
mass-scales. We first reformulate its perturbed coset CFT description in terms
of the perturbation of a projected product of minimal models. This
representation enables us to identify conserved tensor currents on the UV side.
These UV operators are then mapped via form factor perturbation theory to
operators on the IR side, which are characterized by their form factors. The
relation between the UV and IR operators is given in terms of the sought-for
mass-coupling relation. By generalizing the $\Theta$ sum rule Ward identity we
are able to derive differential equations for the mass-coupling relation, which
we solve in terms of hypergeometric functions. We check these results against
the data obtained by numerically solving the thermodynamic Bethe Ansatz
equations, and find a complete agreement.


  It is known that ground states of the pseudo-relativistic Boson stars exist
if and only if the stellar mass $N>0$ satisfies $N<N^*$, where the finite
constant $N^*$ is called the critical stellar mass. Lieb and Yau conjecture in
[Comm. Math. Phys., 1987] that ground states of the pseudo-relativistic Boson
stars are unique for each $N<N^*$. In this paper, we prove that the above
uniqueness conjecture holds for the particular case where $N>0$ is small
enough.


  We introduce the concept of unconstrained real-time 3D facial performance
capture through explicit semantic segmentation in the RGB input. To ensure
robustness, cutting edge supervised learning approaches rely on large training
datasets of face images captured in the wild. While impressive tracking quality
has been demonstrated for faces that are largely visible, any occlusion due to
hair, accessories, or hand-to-face gestures would result in significant visual
artifacts and loss of tracking accuracy. The modeling of occlusions has been
mostly avoided due to its immense space of appearance variability. To address
this curse of high dimensionality, we perform tracking in unconstrained images
assuming non-face regions can be fully masked out. Along with recent
breakthroughs in deep learning, we demonstrate that pixel-level facial
segmentation is possible in real-time by repurposing convolutional neural
networks designed originally for general semantic segmentation. We develop an
efficient architecture based on a two-stream deconvolution network with
complementary characteristics, and introduce carefully designed training
samples and data augmentation strategies for improved segmentation accuracy and
robustness. We adopt a state-of-the-art regression-based facial tracking
framework with segmented face images as training, and demonstrate accurate and
uninterrupted facial performance capture in the presence of extreme occlusion
and even side views. Furthermore, the resulting segmentation can be directly
used to composite partial 3D face models on the input images and enable
seamless facial manipulation tasks, such as virtual make-up or face
replacement.


  We consider a general discretization strategy for Hamiltonian field theories
generated by Lie-Poisson brackets which we call dual PIC (DPIC). This method
involves prescribing two different discrete representations of the dynamical
variable which are constrained as a Casimir invariant of the flow to coincide
with one another via an L2 projection throughout the entire simulation. This
allows one to leverage the relative advantages of each discrete representation.
We begin by describing DPIC as applied to a general Lie-Poisson system and then
provide illustrative examples: the discretization of the two-dimensional
vorticity equations and the Vlasov-Poisson equation.


  In this paper we consider the non-variational system $$
  \begin{cases}
  -\Delta u_i = \sum\limits_{j=1}^k a_{ij} u_j^{(N+2)/(N-2)}
  &\text{in }\mathbb R^N,\newline
  u_i>0 &\text{in }\mathbb R^N,\newline
  u_i\in D^{1,2}(\mathbb R^N).
  \end{cases} $$ and we give some sufficient conditions on the matrix
$(a_{ij})_{i,j=1,\dotsc ,k}$ which ensure the existence of solutions
bifurcating from the bubble of the critical Sobolev equation.


  Direct contour regression for instance segmentation is a challenging task.
Previous works usually achieve it by learning to progressively refine the
contour prediction or adopting a shape representation with limited
expressiveness. In this work, we argue that the difficulty in regressing the
contour points in one pass is mainly due to the ambiguity when discretizing a
smooth contour into a polygon. To address the ambiguity, we propose a novel
differentiable rendering-based approach named \textbf{ContourRender}. During
training, it first predicts a contour generated by an invertible shape
signature, and then optimizes the contour with the more stable silhouette by
converting it to a contour mesh and rendering the mesh to a 2D map.
  This method significantly improves the quality of contour without iterations
or cascaded refinements. Moreover, as optimization is not needed during
inference, the inference speed will not be influenced.
  Experiments show the proposed ContourRender outperforms all the contour-based
instance segmentation approaches on COCO, while stays competitive with the
iteration-based state-of-the-art on Cityscapes. In addition, we specifically
select a subset from COCO val2017 named COCO ContourHard-val to further
demonstrate the contour quality improvements. Codes, models, and dataset split
will be released.


  We give an overview of complementarity and synergy in cosmology between the
Square Kilometre Array and future survey projects in other wavelengths. In the
SKA era, precision cosmology will be limited by systematic errors and cosmic
variance, rather than statistical errors. However, combining and/or
cross-correlating multi-wavelength data, from the SKA to the cosmic microwave
background, optical/infrared and X-ray, substantially reduce these limiting
factors. In this chapter, we summarize future survey projects and show
highlights of complementarity and synergy, which can be very powerful to probe
major cosmological problems such as dark energy, modified gravity and
primordial non-Gaussianity.


  Let $M$ be complete nonpositively curved Riemannian manifold of finite volume
whose fundamental group $\Gamma$ does not contain a finite index subgroup which
is a product of infinite groups. We show that the universal cover $\tilde M$ is
a higher rank symmetric space iff $H^2_b(M;\R)\to H^2(M;\R)$ is injective (and
otherwise the kernel is infinite-dimensional). This is the converse of a
theorem of Burger-Monod. The proof uses the celebrated Rank Rigidity Theorem,
as well as a new construction of quasi-homomorphisms on groups that act on
CAT(0) spaces and contain rank 1 elements.


  In order to deal with the sparse and unstructured raw point clouds, LiDAR
based 3D object detection research mostly focuses on designing dedicated local
point aggregators for fine-grained geometrical modeling. In this paper, we
revisit the local point aggregators from the perspective of allocating
computational resources. We find that the simplest pillar based models perform
surprisingly well considering both accuracy and latency. Additionally, we show
that minimal adaptions from the success of 2D object detection, such as
enlarging receptive field, significantly boost the performance. Extensive
experiments reveal that our pillar based networks with modernized designs in
terms of architecture and training render the state-of-the-art performance on
the two popular benchmarks: Waymo Open Dataset and nuScenes. Our results
challenge the common intuition that the detailed geometry modeling is essential
to achieve high performance for 3D object detection.


  Automotive software is increasingly complex and critical to safe vehicle
operation, and related embedded systems must remain up-to-date to ensure
long-term system performance. Update mechanisms and data modification tools
introduce opportunities for malicious actors to compromise these cyber-physical
systems, and for trusted actors to mistakenly install incompatible software
versions. A distributed and stratified "black box" audit trail for automotive
software and data provenance is proposed to assure users, service providers,
and original equipment manufacturers (OEMs) of vehicular software integrity and
reliability. The proposed black box architecture is both layered and diffuse,
employing distributed hash tables (DHT), a parity system and a public
blockchain to provide high resilience, assurance, scalability, and efficiency
for automotive and other high-assurance systems.


  We consider dynamics of Dicke models, with and without counterrotating terms,
under slow variations of parameters which drive the system through a quantum
phase transition. The model without counterrotating terms and sweeped detuning
is seen in the contexts of a many-body generalization of the Landau-Zener model
and the dynamical passage through a second-order quantum phase transition
(QPT). Adiabaticity is destroyed when the parameter crosses a critical value.
Applying semiclassical analysis based on concepts of classical adiabatic
invariants and mapping to the second Painleve equation (PII), we derive a
formula which accurately describes particle distributions in the Hilbert space
at wide range of parameters and initial conditions of the system. We find
striking universal features in the particle distributions which can be probed
in an experiment on Feshbach resonance passage or a cavity QED experiment. The
dynamics is found to be crucially dependent on the direction of the sweep. The
model with counterrotating terms has been realized recently in an experiment
with ultracold atomic gases in a cavity. Its semiclassical dynamics is
described by a Hamiltonian system with two degrees of freedom. Passage through
a QPT corresponds to passage through a bifurcation, and can also be described
by PII (after averaging over fast variables), leading to similar universal
distributions. Under certain conditions, the Dicke model is reduced to the
Lipkin-Meshkov-Glick model.


  We consider the gravity-mediated SUSY breaking within the effective theory of
six-dimensional brane-world supergravity. We construct the supersymmetric
bulk-brane action by Noether method and find the nontrivial moduli coupling of
the brane F- and D-terms. We find that the low energy Kahler potential is not
of sequestered form, so gravity mediation may occur at tree level. In moduli
stabilization with anomaly effects included, the scalar soft mass squared can
be positive at tree level and it can be comparable to the anomaly mediation.


  Transverse spin diffusion in a polarized, interacting Fermi gas leads to the
Leggett-Rice effect, where the spin current precesses around the local
magnetization. With a spin-echo sequence both the transverse diffusivity and
the spin-rotation parameter $\gamma$ are obtained; the sign of $\gamma$ reveals
the repulsive or attractive character of the effective interaction. In a
trapped Fermi gas the spin diffusion equations become nonlinear, and their
numerical solution exhibits an inhomogeneous spin state even at the spin echo
time. While the microscopic diffusivity and $\gamma$ increase at weak coupling,
their apparent values inferred from the trap-averaged magnetization saturate in
agreement with a recent experiment for a dilute ultracold Fermi gas.


  The essential properties of graphite-based 3D systems are thoroughly
investigated by the first-principles method. Such materials cover a simple
hexagonal graphite, a Bernal graphite, and the stage-1 to stage-4 Li/Li$^+$
graphite intercalation compounds. The delicate calculations and the detailed
analyses are done for their optimal stacking configurations, bong lengths,
interlayer distances, free electron $\&$ hole densities, Fermi levels,
transferred charges in chemical bondings, atom- or ion-dominated energy bands,
spatial charge distributions and the significant variations after
intercalation, Li-/Li$^+$- $\&$ C-orbital-decomposed DOSs. The above-mentioned
physical quantities are sufficient in determining the critical orbital
hybridizations responsible for the unusual fundamental properties. How to
dramatically alter the low-lying electronic structures by modulating the
quest-atom/quest-ion concentration is one of focuses, e.g., the drastic changes
on the Fermi level, band widths, and number of energy bands. The theoretical
predictions on the stage-n-dependent band structures could be examined by the
high-resolution angle-resolved photoemission spectroscopy (ARPES). Most
important, the low-energy DOSs near the Fermi might provide the reliable data
for estimating the free carrier density due to the interlayer atomic
interactions or the quest-atom/quest-ion intercalation. The van Hove
singularities, which mainly arise from the critical points in
energy-wave-vector space, could be directly examined by the experimental
measurements of scanning tunneling spectroscopy (STS). Their features should be
very useful in distinguishing the important differences among the stage-$n$
graphite intercalation compounds, and the distinct effects due to the atom or
ion decoration.


  Publications in the life sciences are characterized by a large technical
vocabulary, with many lexical and semantic variations for expressing the same
concept. Towards addressing the problem of relevance in biomedical literature
search, we introduce a deep learning model for the relevance of a document's
text to a keyword style query. Limited by a relatively small amount of training
data, the model uses pre-trained word embeddings. With these, the model first
computes a variable-length Delta matrix between the query and document,
representing a difference between the two texts, which is then passed through a
deep convolution stage followed by a deep feed-forward network to compute a
relevance score. This results in a fast model suitable for use in an online
search engine. The model is robust and outperforms comparable state-of-the-art
deep learning approaches.


  We study the longitudinal polarization of the tau lepton in B -> D tau nu
decay. After discussing possible sensitivities of tau decay modes to the tau
polarization, we examine the effect of charged Higgs boson on the tau
polarization in B -> D tau nu. We find a relation between the decay rate and
the tau polarization, and clarify the role of the tau polarization measurement
in the search for the charged Higgs boson.


  Nonstandard on-shell decays of $W^\pm$ and $Z$ bosons are possible within the
framework of extended supersymmetric models, i.e., with singlet states and/or
new couplings compared to the minimal supersymmetric standard model. These
modes are typically encountered in regions of the parameter space with light
singlet-like scalars, pseudoscalars, and neutralinos. In this letter we
emphasize how these states can lead to novel signals at colliders from $Z$- or
$W^\pm$-boson decays with prompt or displaced multileptons/tau
jets/jets/photons in the final states. These new modes would give distinct
evidence of new physics even when direct searches remain unsuccessful. We
discuss the possibilities of probing these new signals using the existing LHC
run-I data set. We also address the same in the context of the LHC run-II, as
well as for the future colliders. We exemplify our observations with the "$\mu$
from $\nu$" supersymmetric standard model, where three generations of
right-handed neutrino superfields are used to solve shortcomings of the minimal
supersymmetric standard model. We also extend our discussion for other variants
of supersymmetric models that can accommodate similar signatures.


  We perform a Monte Carlo calculation of the second moment of the polarised
valence quark distributions in the nucleon, using quenched Wilson fermions. The
special feature of this moment is that it is directly accessible
experimentally. At a scale of $\mu \approx 2$GeV we find $\Delta^{(1)}u =
0.198(8)$, $\Delta^{(1)}d = -0.0477(33)$. We compare these numbers with recent
experimental results of the SMC collaboration.


  Background: Pion production gives information on the axial form factors of
nucleon resonances. It also introduces a noticeable background to quasi-elastic
measurements on nuclear targets and thus has a significant impact on precision
studies of neutrino oscillation parameters. Purpose: To clarify
neutrino-induced pion production on nucleons and nuclei. Method: The Giessen
Boltzmann--Uehling--Uhlenbeck (GiBUU) model is used for the description of
neutrino-nucleus reactions. Results: Theoretical results for differential cross
sections for the T2K neutrino flux at the ND280 detector and integrated cross
sections as a function of neutrino energy are given. Two sets of pion
production data on elementary targets are used as inputs to obtain limits for
pion production in neutrino-nucleus reactions. Conclusions: Pion production in
the T2K ND280 detector can help to narrow down the uncertainties in the
elementary pion production cross sections. It can also give valuable
information on the nucleon-Delta axial form factor.


  We examine the thermodynamic properties of recently constructed black hole
solutions in SL(3,R) x SL(3,R) Chern-Simons theory in the presence of a
chemical potential for spin-3 charge, which acts as an irrelevant deformation
of the dual CFT with W_3 x W_3 symmetry. The smoothness or holonomy conditions
admit four branches of solutions describing a flow between two AdS_3
backgrounds corresponding to two different CFTs. The dominant branch at low
temperatures, connected to the BTZ black hole, merges smoothly with a
thermodynamically unstable branch and disappears at higher temperatures. We
confirm that the UV region of the flow satisfies the Ward identities of a CFT
with W_3^(2) x W_3^(2) symmetry deformed by a spin-3/2 current. This allows to
identify the precise map between UV and IR thermodynamic variables. We find
that the high temperature regime is dominated by a black hole branch whose
thermodynamics can only be consistently inferred with reference to this W_3^(2)
x W_3^(2) CFT.


  Given a>0, we construct a weighted Lebesgue measure on R^n for which the
family of non constant curves has p-modulus zero for p\leq 1+a but the weight
is a Muckenhoupt A_p weight for p>1+a. In particular, the p-weak gradient is
trivial for small p but non trivial for large p. This answers an open question
posed by several authors. We also give a full description of the p-weak
gradient for any locally finite Borel measure on the real line.


  Circular Synthetic aperture sonars (CSAS) capture multiple observations of a
scene to reconstruct high-resolution images. We can characterize resolution by
modeling CSAS imaging as the convolution between a scene's underlying point
scattering distribution and a system-dependent point spread function (PSF). The
PSF is a function of the transmitted waveform's bandwidth and determines a
fixed degree of blurring on reconstructed imagery. In theory, deconvolution
overcomes bandwidth limitations by reversing the PSF-induced blur and
recovering the scene's scattering distribution. However, deconvolution is an
ill-posed inverse problem and sensitive to noise. We propose a self-supervised
pipeline (does not require training data) that leverages an implicit neural
representation (INR) for deconvolving CSAS images. We highlight the performance
of our SAS INR pipeline, which we call SINR, by implementing and comparing to
existing deconvolution methods. Additionally, prior SAS deconvolution methods
assume a spatially-invariant PSF, which we demonstrate yields subpar
performance in practice. We provide theory and methods to account for a
spatially-varying CSAS PSF, and demonstrate that doing so enables SINR to
achieve superior deconvolution performance on simulated and real acoustic SAS
data. We provide code to encourage reproducibility of research.


  With the increased penetration of wind energy into the power grid, it has
become increasingly important to be able to predict the expected power
production for larger wind farms. Deep learning (DL) models can learn complex
patterns in the data and have found wide success in predicting wake losses and
expected power production. This paper proposes a modular framework for
attention-based graph neural networks (GNN), where attention can be applied to
any desired component of a graph block. The results show that the model
significantly outperforms a multilayer perceptron (MLP) and a bidirectional
LSTM (BLSTM) model, while delivering performance on-par with a vanilla GNN
model. Moreover, we argue that the proposed graph attention architecture can
easily adapt to different applications by offering flexibility into the desired
attention operations to be used, which might depend on the specific
application. Through analysis of the attention weights, it was showed that
employing attention-based GNNs can provide insights into what the models learn.
In particular, the attention networks seemed to realise turbine dependencies
that aligned with some physical intuition about wake losses.


  We theoretically model the electronic dynamics of a coupled quantum dot pair
in a static electric field. We then investigate the possibility of
polarization-entangled photon emission from the radiative cascade of the
molecular biexciton state. Through numerical simulations, we analyze the
dependence of entanglement fidelity on temperature and electric field, as well
as tunnel coupling. We establish a regime of direct-indirect exciton detunings
for which coupled quantum dots are superior to single dots for entangled photon
generation, yielding near-unit fidelity over a larger range of exchange
splittings.


  We give a derivation of the thermodynamic restrictions on the constitutive
relations of an electrically polarizable and finitely deformable heat
conducting elastic continuum, interacting with the electric field. This is made
following the method of Coleman-Noll in a thermodynamic theory with the
Clausius-Duhem inequality.


  Traditional methods of collecting user feedback through transit surveys are
often time-consuming, resource intensive, and costly. In this paper, we propose
a novel NLP-based framework that harnesses the vast, abundant, and inexpensive
data available on social media platforms like Twitter to understand users'
perceptions of various service issues. Twitter, being a microblogging platform,
hosts a wealth of real-time user-generated content that often includes valuable
feedback and opinions on various products, services, and experiences. The
proposed framework streamlines the process of gathering and analyzing user
feedback without the need for costly and time-consuming user feedback surveys
using two techniques. First, it utilizes few-shot learning for tweet
classification within predefined categories, allowing effective identification
of the issues described in tweets. It then employs a lexicon-based sentiment
analysis model to assess the intensity and polarity of the tweet sentiments,
distinguishing between positive, negative, and neutral tweets. The
effectiveness of the framework was validated on a subset of manually labeled
Twitter data and was applied to the NYC subway system as a case study. The
framework accurately classifies tweets into predefined categories related to
safety, reliability, and maintenance of the subway system and effectively
measured sentiment intensities within each category. The general findings were
corroborated through a comparison with an agency-run customer survey conducted
in the same year. The findings highlight the effectiveness of the proposed
framework in gauging user feedback through inexpensive social media data to
understand the pain points of the transit system and plan for targeted
improvements.


  Tropical cyclones can be of varied intensity and cause a huge loss of lives
and property if the intensity is high enough. Therefore, the prediction of the
intensity of tropical cyclones advance in time is of utmost importance. We
propose a novel stacked bidirectional long short-term memory network (BiLSTM)
based model architecture to predict the intensity of a tropical cyclone in
terms of Maximum surface sustained wind speed (MSWS). The proposed model can
predict MSWS well advance in time (up to 72 h) with very high accuracy. We have
applied the model on tropical cyclones in the North Indian Ocean from 1982 to
2018 and checked its performance on two recent tropical cyclones, namely, Fani
and Vayu. The model predicts MSWS (in knots) for the next 3, 12, 24, 36, 48,
60, and 72 hours with a mean absolute error of 1.52, 3.66, 5.88, 7.42, 8.96,
10.15, and 11.92, respectively.


  The 3X3 Maki-Nakagawa-Sakata-Pontecorvo (MNSP) lepton flavor mixing matrix
may be slightly non-unitary if the three active neutrinos are coupled with
sterile neutrinos. We show that it is in principle possible to test whether the
relation |V_{e1}|^2 + |V_{e2}|^2 + |V_{e3}|^2 = 1 holds or not in a precision
reactor antineutrino oscillation experiment, such as the recently proposed Daya
Bay II experiment. We explore three categories of non-unitary effects on the
3X3 MNSP matrix: 1) the indirect effect in the (3+ 3) flavor mixing scenario
where the three heavy sterile neutrinos do not take part in neutrino
oscillations; 2) the direct effect in the (3+\mathbbm{1}) scenario where the
light sterile neutrino can oscillate into the active ones; and 3) the interplay
of both of them in the (3+\mathbbm{1}+ 2) scenario. We find that both the
zero-distance effect and flavor mixing factors of different oscillation modes
can be used to determine or constrain the sum of |V_{e1}|^2, |V_{e2}|^2 and
|V_{e3}|^2 and its possible deviation from one, and the active neutrino mixing
angles \theta_{12} and \theta_{13} can be cleanly extracted even in the
presence of light or heavy sterile neutrinos. Some useful analytical results
are obtained for each of the three scenarios.


  We present precise V and Ks-band transit photometry for the planetary host
star OGLE-TR-113. Using the Ks-band photometry, we confirm the dwarf nature of
OGLE-TR-113, and obtain new estimates for its effective temperature, distance
and reddening. We employ the V-band photometry to obtain planetary and orbit
parameters from the transit fit, a= (0.0232 \pm 0.0038) AU, orbital period P=
(1.4324752 \pm 0.0000015) days, i= 86.7 - 90, R_p= (1.09 \pm 0.09) R_J. These
values are in excellent agreement with previous works. Assuming a mass M_p=
(1.32 \pm 0.19) M_J for the planet we obtain its mean density \rho= (1.26 \pm
0.50) g cm^{-3}, also in agreement with previous works. The transit observed in
the Ks-band has a larger scatter and we find its amplitude to be consistent
with that in the V-band. In this way, we find an independent confirmation of
the planetary nature of OGLE-TR-113b.


  We propose a new method for the calculation of the statistical properties, as
e.g. the entropy, of unknown generators of symbolic sequences. The probability
distribution p(k) of the elements k of a population can be approximated by the
frequencies f(k) of a sample provided the sample is long enough so that each
element k occurs many times. Our method yields an approximation if this
precondition does not hold. For a given f(k) we recalculate the Zipf-ordered
probability distribution by optimization of the parameters of a guessed
distribution. We demonstrate that our method yields reliable results.


  Li1.5Al0.5Ge1.5(PO4)3 (LAGP) is a promising oxide solid electrolyte for
all-solid-state batteries due to its excellent air stability, wide
electrochemical stability window and cost-effective precursor materials.
However, further improvement in their ionic conductivity performance is
hindered by the presence of inter-grain phases leading to a major obstacle to
the advanced design of oxide based solid-state electrolytes. This study
establishes and quantifies the influence of inter-grain phases, their 3D
morphology, and formed compositions on the overall ion conductivity properties
of LAGP pellets fabricated under different Spark plasma sintering conditions.
Based on complementary techniques, such as PEIS, XRD, 3D FIB-SEM tomography and
solid-state MAS NMR coupled with DFT modelling, a deep insight into the
inter-grain phase microstructures is obtained revealing that the inter-grain
region is comprised of Li4P2O7 and a disordered Li9Al3(P2O7)3(PO4)2 phase. We
demonstrate that optimal ionic conductivity for the LAGP system is achieved for
the 680 {\deg}C SPS preparation when the disordered Li9Al3(P2O7)3(PO4)2 phase
dominates the inter-grain region composition with reduced contributions from
the highly ordered Li4P2O7 phases.


  In this paper, we discuss the noncommutative QED$_2$ in the S-matrix
framework. We are interested in perturbatively proving that the exact Schwinger
mass $\mu^2=\frac{e^2}{\pi}$ does not receive noncommutative corrections to any
order in loop expansion. In this sense, the S-matrix approach is useful since
it allows us to work with the effective action $\Gamma[A]$ (interaction term)
to compute the corresponding gauge field 1PI two-point function at higher
orders. Furthermore, by means of $\alpha^*$-cohomology, we generalize the
QED$_2$ S-matrix analysis in the Moyal star product to all
translation-invariant star products.


  We investigate for the first time a certain class of non-factorisable
contributions of the four-quark operators ${\cal O}_{3-6}$ in the weak
effective Hamiltonian to the $\Lambda_b \to \Lambda \ell^+\ell^-$ decay
amplitude. We focus on the case where a virtual photon is radiated from one of
the light constituents of the $\Lambda_b$ baryon, in the kinematic situation of
large hadronic recoil with an energetic $\Lambda$ baryon in the final state.
The effect on the suitably defined ``non-local form factors'' is calculated
using the light-cone sum rule approach for a correlator with an interpolating
current for the light $\Lambda$ baryon. We find that this approach requires the
introduction of new soft functions that generalise the standard light-cone
distribution amplitudes (LCDAs) for the heavy $\Lambda_b$ baryon. We give a
heuristic discussion of their properties and a model that relates them to the
standard LCDAs. Within this framework, we provide numerical results for the
size of the non-local form factors considered.


  Supermassive black holes (SMBHs) can capture and tidally disrupt stars or
sub-stellar objects orbiting nearby. The detections of Sw J1644+57-like events
suggest that at least some TDEs can launch a relativistic jet beaming towards
Earth. A natural expectation would be the existence of TDEs with a relativistic
jet beaming away from Earth. The nearby TDE candidate IGR J12580+0134 provides
new insights into the jet phenomenon. Combining several constraints, we find
that the event invokes a $8-40$ Jupiter mass object tidally disrupted by a $3
\times 10^5 - 1.8 \times 10^7 M_\sun$ SMBH. Recently, a bright radio transient
was discovered by Irwin et al. in association with IGR J12580+0134. We perform
detailed modeling of the event based on a numerical jet model previously
developed for the radio emission of Sw J1644+57. We find that the radio data of
IGR J12580+0134 can be interpreted within an external forward shock model in
the Newtonian regime. Using Sw J1644+57 as a template and properly correcting
for its luminosity, we argue that the observed X-ray flux in early times is too
faint to allow an on-beam relativistic jet unless the Lorentz factor is very
small. Rather, the X-ray emission is likely from the disk or corona near the
black hole. From various constraints, we find that the data are consistent with
an off-beam relativistic jet with a viewing angle $\theta_{\rm obs} \gtrsim
30^{\rm o}$, and an initial Lorentz factor $\Gamma_j \gtrsim $ a few.This
scenario can readily be tested in the upcoming VLBI observations.


  Extreme mass ratio inspirals (EMRIs) occur when stellar-mass compact objects
begin a gravitational wave (GW) driven inspiral into massive black holes. EMRI
waveforms can precisely map the surrounding spacetime, making them a key target
for future space-based GW interferometers such as {\it LISA}, but their event
rates and parameters are massively uncertain. One of the largest uncertainties
is the ratio of true EMRIs (which spend at least thousands of orbits in the
{\it LISA} band) and direct plunges, which are in-band for at most a handful of
orbits and are not detectable in practice. In this paper, we show that the
traditional dichotomy between EMRIs and plunges -- EMRIs originate from small
semimajor axes, plunges from large -- does not hold for intermediate-mass black
holes with masses $M_\bullet \lesssim 10^5 M_\odot$. In this low-mass regime, a
plunge always has an $\mathcal{O}(1)$ probability of failing and transitioning
into a novel ``cliffhanger'' EMRI. Cliffhanger EMRIs are more easily produced
for larger stellar-mass compact objects, and are less likely for smaller ones.
This new EMRI production channel can dominate volumetric EMRI rates
$\dot{n}_{\rm EMRI}$ if intermediate-mass black holes are common in dwarf
galactic nuclei, potentially increasing $\dot{n}_{\rm EMRI}$ by an order of
magnitude.


  Radiative processes lead to important corrections to (e,e'p) experiments.
While radiative corrections can be calculated exactly in QED and to a good
accuracy also including hadronic corrections, these corrections cannot be
included into data analyses to arbitrary orders exactly. Nevertheless
consideration of multi-photon bremsstrahlung above the low-energy cut-off is
important for many (e,e'p) experiments. To date, higher-order bremsstrahlung
effects concerning electron scattering experiments have been implemented
approximately by employing the soft-photon approximation (SPA). In this paper
we propose a novel approach to multi-photon emission which partially removes
the SPA from (e,e'p) experiments. In this combined approach one hard photon is
treated exactly; and additional softer bremsstrahlung photons are taken into
account resorting to the soft-photon approximation. This partial removal of the
soft-photon approximation is shown to be relevant for the missing-energy
distribution for several kinematic settings at MAMI and TJNAF energies.


  TASTE (The Asiago Search for Transit timing variations of Exoplanets) project
is collecting high-precision, short-cadence light curves for a selected sample
of transiting exoplanets. It has been claimed that the hot jupiter HAT-P-13b
suddenly deviated from a linear ephemeris by $\sim 20$ min, implying that there
is a perturber in the system. Using five new transits, we discuss the
plausibility of this transit time variation (TTV), and show that a periodic
signal should not be excluded. More follow-up observations are required to
constrain the mass and the orbit of the hypothetical perturber.


  Retrieval-augmented large language models (R-LLMs) combine pre-trained large
language models (LLMs) with information retrieval systems to improve the
accuracy of factual question-answering. However, current libraries for building
R-LLMs provide high-level abstractions without sufficient transparency for
evaluating and optimizing prompts within specific inference processes such as
retrieval and generation. To address this gap, we present RaLLe, an open-source
framework designed to facilitate the development, evaluation, and optimization
of R-LLMs for knowledge-intensive tasks. With RaLLe, developers can easily
develop and evaluate R-LLMs, improving hand-crafted prompts, assessing
individual inference processes, and objectively measuring overall system
performance quantitatively. By leveraging these features, developers can
enhance the performance and accuracy of their R-LLMs in knowledge-intensive
generation tasks. We open-source our code at https://github.com/yhoshi3/RaLLe.


  The complex elastic compliance s11(w,T) of SrTiO3-d has been measured as a
function of the O deficiency d < 0.01. The two main relaxation peaks in the
absorption are identified with hopping of isolated O vacancies over a barrier
of 0.60 eV and reorientation of pairs of vacancies involving a barrier of 1 eV.
The pair binding energy is ~0.2 eV and indications for additional clustering,
possibly into chains, is found already at d ~0.004. The anistropic component of
the elastic dipole of an O vacancy is Deltalambda = 0.026.


  We examine the Brown-Rho scaling for meson masses in the strong coupling
limit of lattice QCD with one species of staggered fermion. Analytical
expression of meson masses is derived at finite temperature and chemical
potential. We find that meson masses are approximately proportional to the
equilibrium value of the chiral condensate, which evolves as a function of
temperature and chemical potential.


  Two ground-based experiments have recently independently detected TeV
$\gamma$-rays from the direction of the Galactic center. The observations made
by the VERITAS and CANGAROO collaborations are unexpected, although not
impossible to interpret in terms of astrophysical sources. Here we examine in
detail whether the observed $\gamma$-rays may arise from the more exotic
alternative of annihilations of dark matter particles clustered in the center
of the Galaxy.


  In several mechanisms proposed for multiquark binding, the flavor content of
the quark configuration plays a very important role. We shall review some past
or recent results on multiquarks dealing with the chromomagnetic interaction
and with the spin-independent potential among quarks.


  We present the collective excitations spectrum (magnetoplasmon spectrum) of
  Dirac electrons in a weakly modulated single graphene layer in the presence
of a uniform magnetic field. We consider electric modulation in one-dimension
and the magnetic field applied perpendicular to graphene.We derive analytical
results for the intra-Landau band plasmon spectrum within the
self-consistent-field approach. We find Weiss oscillations in the
magnetoplasmon spectrum which is the primary focus of this work. Results are
presented for the intra-Landau band magnetoplasmon spectrum as a function of
inverse magnetic field. These results are also compared with those of
conventional 2DEG. We have found that the Weiss oscillations in the
magnetoplasmon spectrum are larger in amplitude compared to those in
conventional 2DEG for the same modulation strength, period of modulation and
electron density.


  Gas inflow into galaxies should affect the star formation and hence the
evolution of galaxies across cosmic time. In this work, we use TNG100 of the
IllustrisTNG simulations to understand the role of environment on gas inflow
rates in massive galaxies at z >= 2. We divide our galaxies (log(M*/Msolar )>=
10.5) into cluster (log Mhalo/Msolar >= 13) and field (log Mhalo/Msolar < 13)
galaxies at z = 2 and further divide into centrals and satellites. We track
their gas inflow rates from z = 6 to 2 and find that the total gas inflow rates
of satellite galaxies rapidly decline after their infall into cluster halos and
as they reach the cluster center. At z = 2, the gas inflow rate of cluster
satellite galaxies is correlated with the cluster-centric radii and not the
host halo mass. In contrast, the gas inflow rate in centrals is strongly
correlated with the host halo mass at z >= 2. Our study indicates that between
redshifts 6 to 2, the gas that normally is accreted by the satellite galaxies
is redirected to the center of the cluster halo as inflows to the cluster
centrals and forming the intra-cluster medium. Our analysis suggest that the
inequality of gas accretion between massive satellite and central galaxies is
responsible for the starvation of cluster satellite galaxies that evolve into
the massive quenched cluster galaxies observed at z<0.5.


  The recent discovery of photometric variations in L dwarfs has opened a
discussion on the cause of the variations. We argue against the existence of
magnetic spots in these atmospheres and favor the idea that non-uniform
condensate coverage (i.e. clouds) is responsible for the variations. The
magnetic Reynolds number (Rm) in the atmosphere of L dwarfs, which describes
how well the gas couples with the magnetic field, is too small (<<1) to support
the formation of magnetic spots. In constrast silicate and iron clouds form in
the photospheres of L dwarfs. Inhomogeneities in such cloud decks can plausibly
produce the observed photometric variations. Further evidence in support of
clouds is the tendency for variable L dwarfs to be bluer in J-Ks than the
average L dwarf of a given spectral type. This color effect is expected if
clear holes appear in an otherwise uniform cloud layer.


  Algorithms for frequent pattern mining, a popular informatics application,
have unique requirements that are not met by any of the existing parallel
tools. In particular, such applications operate on extremely large data sets
and have irregular memory access patterns. For efficient parallelization of
such applications, it is necessary to support dynamic load balancing along with
scheduling mechanisms that allow users to exploit data locality. Given these
requirements, task parallelism is the most promising of the available parallel
programming models. However, existing solutions for task parallelism schedule
tasks implicitly and hence, custom scheduling policies that can exploit data
locality cannot be easily employed. In this paper we demonstrate and
characterize the speedup obtained in a frequent pattern mining application
using a custom clustered scheduling policy in place of the popular Cilk-style
policy. We present PFunc, a novel task parallel library whose customizable task
scheduling and task priorities facilitated the implementation of our clustered
scheduling policy.


  In a trapped Bose-Einstein condensate, subject to the action of an
alternating external field, coherent topological modes can be resonantly
excited. Depending on the amplitude of the external field and detuning
parameter, there are two principally different regimes of motion, with mode
locking and without it. The change of the dynamic regime corresponds to a
dynamic phase transition. This transition can be characterized by an effective
order parameter defined as the difference between fractional mode populations
averaged over the temporal period of oscillations. The behavior of this order
parameter, as a function of detuning, pumping amplitude, and atomic
interactions is carefully analyzed. A special attention is payed to numerical
calculations for the realistic case of a quadrupole exciting field and the
system parameters accessible in current experiments.


  We propose a scheme to restore spatial symmetry of Hamiltonian in the
variational-quantum-eigensolver (VQE) algorithm for which the quantum circuit
structures used usually break the Hamiltonian symmetry. The symmetry-adapted
VQE scheme introduced here simply applies the projection operator, which is
Hermitian but not unitary, to restore the spatial symmetry in a desired
irreducible representation of the spatial group. The entanglement of a quantum
state is still represented in a quantum circuit but the nonunitarity of the
projection operator is treated classically as postprocessing in the VQE
framework. By numerical simulations for a spin-$1/2$ Heisenberg model on a
one-dimensional ring, we demonstrate that the symmetry-adapted VQE scheme with
a shallower quantum circuit can achieve significant improvement in terms of the
fidelity of the ground state and has a great advantage in terms of the
ground-state energy with decent accuracy, as compared to the
non-symmetry-adapted VQE scheme. We also demonstrate that the present scheme
can approximate low-lying excited states that can be specified by symmetry
sectors, using the same circuit structure for the ground-state calculation.


  We explore the construction and stability of asymptotically anti-de Sitter
Euclidean wormholes in a variety of models. In simple ad hoc low-energy models,
it is not hard to construct two-boundary Euclidean wormholes that dominate over
disconnected solutions and which are stable (lacking negative modes) in the
usual sense of Euclidean quantum gravity. Indeed, the structure of such
solutions turns out to strongly resemble that of the Hawking-Page phase
transition for AdS-Schwarzschild black holes, in that for boundary sources
above some threshold we find both a `large' and a `small' branch of wormhole
solutions with the latter being stable and dominating over the disconnected
solution for large enough sources. We are also able to construct two-boundary
Euclidean wormholes in a variety of string compactifications that dominate over
the disconnected solutions we find and that are stable with respect to
field-theoretic perturbations. However, as in classic examples investigated by
Maldacena and Maoz, the wormholes in these UV-complete settings always suffer
from brane-nucleation instabilities (even when sources that one might hope
would stabilize such instabilities are tuned to large values). This indicates
the existence of additional disconnected solutions with lower action. We
discuss the significance of such results for the factorization problem of
AdS/CFT.


  In this paper, we address a sub-topic of the broad domain of audio
enhancement, namely musical audio bandwidth extension. We formulate the
bandwidth extension problem using deep neural networks, where a band-limited
signal is provided as input to the network, with the goal of reconstructing a
full-bandwidth output. Our main contribution centers on the impact of the
choice of low pass filter when training and subsequently testing the network.
For two different state of the art deep architectures, ResNet and U-Net, we
demonstrate that when the training and testing filters are matched,
improvements in signal-to-noise ratio (SNR) of up to 7dB can be obtained.
However, when these filters differ, the improvement falls considerably and
under some training conditions results in a lower SNR than the band-limited
input. To circumvent this apparent overfitting to filter shape, we propose a
data augmentation strategy which utilizes multiple low pass filters during
training and leads to improved generalization to unseen filtering conditions at
test time.


  We report on the systematic investigation of the optical properties of a
selectively grown quantum dot gain material assisted by block-copolymer
lithography for potential applications in active optical devices operating in
the wavelength range around 1.55 um and above. We investigated a new type of
diblock copolymer PS-b-PDMS (polystyrene-block-polydimethylsiloxane) for the
fabrication of silicon oxycarbide hard mask for selective area epitaxy of
InAs/InP quantum dots. An array of InAs/InP quantum dots was selectively grown
via droplet epitaxy. Our detailed investigation of the quantum dot carrier
dynamics in the 10-300 K temperature range indicates the presence of a density
of states located within the InP bandgap in the vicinity of quantum dots. Those
defects have a substantial impact on the optical properties of quantum dots.


  N = 3 Weyl multiplet in four dimensions was first constructed in J van Muiden
et al (2017) where the authors used the current multiplet approach to obtain
the linearized transformation rules and completed the nonlinear variations
using the superconformal algebra. The multiplet of currents was obtained by a
truncation of the multiplet of currents for the N = 4 vector multiplet. While
the procedure seems to be correct, the result suffers from several
inconsistencies. The inconsistencies are observed in the transformation rules
as well as the field dependent structure constants in the corresponding soft
algebra. We take a different approach, and compute the transformation rule as
well as the corresponding soft algebra by demanding consistency.


  We associate a signed digraph with a list of matrices whose dimensions permit
them to be multiplied, and whose product is square. Cycles in this graph have a
parity, that is, they are either even (termed e-cycles) or odd (termed
o-cycles). The absence of e-cycles in the graph is shown to imply that the
matrix product is a P0-matrix, i.e., all of its principal minors are
nonnegative. Conversely, the presence of an e-cycle is shown to imply that
there exists a list of matrices associated with the graph whose product fails
to be a P0-matrix. The results generalise a number of previous results relating
P- and P0-matrices to graphs.


  Hybrid inflation can be realised in low-energy effective string theory, as
described using supergravity. We find that the coupling of moduli to F-term
hybrid inflation in supergravity leads to a slope and a curvature for the
inflaton potential. The epsilon and eta parameters receive contributions at
tree and one loop level which are not compatible with slow roll inflation.
Furthermore the coupling to the moduli sector can even prevent inflation from
ending at all. We show that introducing shift symmetries in the inflationary
sector and taking the moduli sector to be no-scale removes most of these
problems. If the moduli fields are fixed during inflation, as is usually
assumed, it appears that viable slow-roll inflation can then be obtained with
just one fine-tuning of the moduli sector parameters. However, we show this is
not a reasonable assumption, and that the small variation of the moduli fields
during inflation gives a significant contribution to the effective inflaton
potential. This typically implies that eta is approximately -6, although it may
be possible to obtain smaller values with heavy fine-tuning.


  Global Navigation Satellite Systems (GNSS) provide precise location, while
Real Time Kinematics (RTK) allow mobile receivers (termed rovers), leveraging
fixed stations, to correct errors in their Position Navigation and Timing (PNT)
solution. This allows compensating for multi-path effects, ionospheric errors,
and observation biases, enabling consumer receivers to achieve centimeter-level
accuracy. While network distribution of correction streams can be protected
with common secure networking practices, the reference stations can still be
attacked by GNSS spoofing or jamming. This work investigates (i) the effect RTK
reference station spoofing has on the rover's PNT solution quality and (ii) the
potential countermeasures towards hardening the RTK infrastructure.