  The high pressure structural and electronic evolution of bulk MoS$_2$, an
important transition metal layered dichalchogenide, is currently under active
investigation. Recent theoretical and experimental work predicted and verified
a 2H$_c \to$ 2H$_a$ layer sliding structural transition at 20 GPa and a band
overlap semiconductor-semimetal transition in the same pressure range. The
2H$_a$ structure is known to persist up to pressure of 81 GPa but properties at
higher pressures remain experimentally unknown. Here we predict, with a
reliable first-principles evolutionary search, that major structural
transformations should take place in equilibrium at higher pressures near
130-140 GPa. The main motif is a decomposition into MoS + S, also heralded in a
small bimolecular cell by the appearance of a metastable non-layered metallic
MoS$_2$ structure with space group \textit{P4/mmm}. Unlike semimetallic
2H$_a$-MoS$_2$, both this phase and sulphur in the fully phase separated system
are fully metallic and superconducting with higher critical temperatures than
alkali-intercalated MoS$_2$.


  We determine the gyromagnetic factor of the positronium ion, a three-body
system consisting of two electrons and a positron, including first relativistic
corrections. We find that the g-factor is modified by a term -0.51(1)alpha^2,
exceeding 15 times the alpha^2 correction for a free electron. We compare this
effect with analogous results found previously in atomic positronium and in
hydrogen-like ions.


  In this paper, a class of resampling techniques for finite populations under
complex sampling design is introduced. The basic idea on which it rests is a
two-step procedure consisting in : (i) constructing a pseudo-population on the
basis of sample data; (ii) drawing a sample from the predicted population
according to an appropriate resampling design. From a logical point of view,
this approach is essentially based on the plug-in principle by Efron, at the
"sampling design level". Theoretical justifications based on large sample
theory are provided. New approaches to construct pseudo-populations based on
various forms of calibrations are proposed. Finally, a simulation study is
performed.


  State-of-the-art automatic speech recognition (ASR) systems perform well on
healthy speech. However, the performance on impaired speech still remains an
issue. The current study explores the usefulness of using Wav2Vec
self-supervised speech representations as features for training an ASR system
for dysarthric speech. Dysarthric speech recognition is particularly difficult
as several aspects of speech such as articulation, prosody and phonation can be
impaired. Specifically, we train an acoustic model with features extracted from
Wav2Vec, Hubert, and the cross-lingual XLSR model. Results suggest that speech
representations pretrained on large unlabelled data can improve word error rate
(WER) performance. In particular, features from the multilingual model led to
lower WERs than filterbanks (Fbank) or models trained on a single language.
Improvements were observed in English speakers with cerebral palsy caused
dysarthria (UASpeech corpus), Spanish speakers with Parkinsonian dysarthria
(PC-GITA corpus) and Italian speakers with paralysis-based dysarthria (EasyCall
corpus). Compared to using Fbank features, XLSR-based features reduced WERs by
6.8%, 22.0%, and 7.0% for the UASpeech, PC-GITA, and EasyCall corpus,
respectively.


  Understanding and predicting pedestrian crossing behavior is essential for
enhancing automated driving and improving driving safety. Predicting gap
selection behavior and the use of zebra crossing enables driving systems to
proactively respond and prevent potential conflicts. This task is particularly
challenging at unsignalized crossings due to the ambiguous right of way,
requiring pedestrians to constantly interact with vehicles and other
pedestrians. This study addresses these challenges by utilizing simulator data
to investigate scenarios involving multiple vehicles and pedestrians. We
propose and evaluate machine learning models to predict gap selection in
non-zebra scenarios and zebra crossing usage in zebra scenarios. We investigate
and discuss how pedestrians' behaviors are influenced by various factors,
including pedestrian waiting time, walking speed, the number of unused gaps,
the largest missed gap, and the influence of other pedestrians. This research
contributes to the evolution of intelligent vehicles by providing predictive
models and valuable insights into pedestrian crossing behavior.


  Understanding the natal kicks, or birth velocities, of neutron stars are
essential for understanding the evolution of massive binaries as well as double
neutron star formation. We use maximum likelihood methods as published in
Verbunt et al. to analyse a new large dataset of parallaxes and proper motions
measured by Deller et al. This sample is roughly three times larger than number
of measurements available before. For both the complete sample and its younger
part (spin-down ages $\tau < 3$ Myr), we find that a bimodal Maxwellian
distribution describes the measured parallaxes and proper motions better than a
single Maxwellian with probability of 99.3 and 95.0 per cent respectively. The
bimodal Maxwellian distribution has three parameters: fraction of low-velocity
pulsars and distribution parameters $\sigma_1$ and $\sigma_2$ for low and
high-velocity modes. For a complete sample, these parameters are as follows:
$42_{-15}^{+17}$ per cent, $\sigma_1=128_{-18}^{+22}$ km s$^{-1}$ and $\sigma_2
= 298\pm 28$ km s$^{-1}$. For younger pulsars, which are assumed to represent
the natal kick, these parameters are as follows: $20_{-10}^{+11}$ per cent,
$\sigma_1=56_{-15}^{+25}$ km s$^{-1}$ and $\sigma_2=336\pm 45$ km s$^{-1}$. In
the young population, $5\pm 3$ per cent of pulsars has velocities less than 60
km s$^{-1}$. We perform multiple Monte Carlo tests for the method taking into
account realistic observational selection. We find that the method reliably
estimates all parameters of the natal kick distribution. Results of the
velocity analysis are weakly sensitive to the exact values of scale-lengths of
the Galactic pulsar distribution.


  Stimulated emission tomography is a powerful and successful technique to both
improve the resolution and experimentally simplify the task of determining the
modal properties of biphotons. In the present manuscript we provide a
theoretical description of SET valid for any quadratic coupling regime between
a non-linear medium and pump fields generating photons by pairs. We use our
results to obtain not only information about the associated modal function
modulus but also its phase, for any mode, and we discuss the specific case of
time-frequency variables as well as the quantities and limitations involved in
the measurement resolution.


  The distribution of the squared momentum difference |P_A|^2 - |P_B|^2 between
the momenta in the laboratory system of two experimentally observed particles A
and B provides a test for whether an observed mass peak indicates a real
resonance rather than nonresonant background or kinematic reflection. The
angular distribution of the relative momenta in the center-of-mass system
exhibits a forward-backward symmetry in the production and decay of any
resonance with a definite parity. This symmetry is not expected in other
nonresonant processes and can be expressed without needing angular
distributions in terms of the easily measured momenta in the laboratory frame
that are already measured and used to calculate the invariant mass of the
system. Our test is especially useful for low statistics experiments where the
full angular distribution cannot be determined. It can be applied to both
fixed-target and collider searches for the Theta^+ and Theta_c pentaquarks.


  We analyze the evolution of the vertical composition profile during
hydrodynamic-evaporative film thinning as it typically occurs during spin
casting mixtures of non-volatile solutes and volatile solvents. We assume that
the solvent dominates the hydrodynamic-evaporative film thinning. The internal
spatio-temporal evolution of the composition is analyzed with a
diffusive-advective approach. The analysis provides transparent physical
insights into the influence of the experimental conditions on the evolution of
the internal composition. We present power laws that link the process control
parameters to the composition evolution, process duration, and final solute
coverage. The analysis reveals a characteristic Sherwood Number as fundamental
process parameter. It identifies for which stages of the process our analysis
is quantitatively relevant and discloses the dominance of either diffusion or
evaporation. The analysis is valid for dilute solutions e.g., for the
deposition of solute (sub)monolayers. But it is also relevant for the
deposition of thicker (polymer) films.


  The quantum Schrodinger-Newton equation is solved for a self-gravitating Bose
gas at zero temperature. It is derived that the density is non-uniform and a
central hollow cavity exists. The radial distribution of the particle momentum
is uniform. It is shown that a quantum black hole can be formed only above a
certain critical mass. The temperature effect is accounted for via the
Schrodinger-Poisson-Boltzmann equation, where low and high temperature
solutions are obtained. The theoretical analysis is extended to a strong
interacting gas via the Schrodinger-Yukawa equation, showing that the atomic
nuclei are also hollow. Hollow self-gravitating Fermi gases are described by
the Thomas-Fermi equation.


  Dialect classification is used in a variety of applications, such as machine
translation and speech recognition, to improve the overall performance of the
system. In a real-world scenario, a deployed dialect classification model can
encounter anomalous inputs that differ from the training data distribution,
also called out-of-distribution (OOD) samples. Those OOD samples can lead to
unexpected outputs, as dialects of those samples are unseen during model
training. Out-of-distribution detection is a new research area that has
received little attention in the context of dialect classification. Towards
this, we proposed a simple yet effective unsupervised Mahalanobis distance
feature-based method to detect out-of-distribution samples. We utilize the
latent embeddings from all intermediate layers of a wav2vec 2.0
transformer-based dialect classifier model for multi-task learning. Our
proposed approach outperforms other state-of-the-art OOD detection methods
significantly.


  Brain computer interfaces (BCI) provide a direct communication link between
the brain and a computer or other external devices. They offer an extended
degree of freedom either by strengthening or by substituting human peripheral
working capacity and have potential applications in various fields such as
rehabilitation, affective computing, robotics, gaming and artificial
intelligence. Significant research efforts on a global scale have delivered
common platforms for technology standardization and help tackle highly complex
and nonlinear brain dynamics and related feature extraction and classification
challenges. Psycho-neurophysiological phenomena and their impact on brain
signals impose another challenge for BCI researchers to transform the
technology from laboratory experiments to plug-and-play daily life. This review
summarizes progress in BCI field and highlights critical challenges.


  A study of B+ to J/psi pi+ and B+ to psi(2S) pi+ decays is performed with
data corresponding to 0.37 fb-1 of proton-proton collisions at sqrt(s)=7 TeV.
Their branching fractions are found to be B(B+ to J/psi pi+) = (3.88 +- 0.11 +-
0.15) x 10^{-5} and B(B+ to psi(2S) pi+) = (2.52 +- 0.26 +- 0.15) x 10^{-5},
where the first uncertainty is related to the statistical size of the sample
and the second quantifies systematic effects. The measured CP asymmetries in
these modes are ACP(J/psi pi) = 0.005 +- 0.027 +- 0.011 and ACP(psi(2S) pi) =
0.048 +- 0.090 +- 0.011 with no evidence of direct CP violation seen.


  We have performed $^{69,71}$Ga nuclear magnetic resonance (NMR) and nuclear
quadrupole resonance (NQR) and muon spin rotation/resonance on the quasi
two-dimensional antiferromagnet (AFM) NiGa$_2$S$_4$, in order to investigate
its spin dynamics and magnetic state at low temperatures. Although there exists
only one crystallographic site for Ga in NiGa$_2$S$_4$, we found two distinct
Ga signals by NMR and NQR. The origin of the two Ga signals is not fully
understood, but possibly due to stacking faults along the c axis which induce
additional broad Ga NMR and NQR signals with different local symmetries. We
found the novel spin freezing occurring at $T_{\rm f}$, at which the specific
heat shows a maximum, from a clear divergent behavior of the nuclear
spin-lattice relaxation rate $1/T_{1}$ and nuclear spin-spin relaxation rate
$1/T_{2}$ measured by Ga-NQR as well as the muon spin relaxation rate
$\lambda$. The main sharp NQR peaks exhibit a stronger tendency of divergence,
compared with the weak broader spectral peaks, indicating that the spin
freezing is intrinsic in NiGa$_2$S$_4$. The behavior of these relaxation rates
strongly suggests that the Ni spin fluctuations slow down towards $T_{\rm f}$,
and the temperature range of the divergence is anomalously wider than that in a
conventional magnetic ordering. A broad structureless spectrum and
multi-component $T_1$ were observed below 2 K, indicating that a static
magnetic state with incommensurate magnetic correlations or inhomogeneously
distributed moments is realized at low temperatures. However, the wide
temperature region between 2 K and $T_{\rm f}$, where the NQR signal was not
observed, suggests that the Ni spins do not freeze immediately below $T_{\rm
f}$, but keep fluctuating down to 2 K with the MHz frequency range.


  We study the static and spherical symmetric (SSS) configurations in the
non-minimal model of the de Rham-Gabadadze-Tolley (dRGT) massive gravity with a
flat reference metric. Considering the modified Tolman-Oppenheimer-Volkoff
(TOV) equation, the Bianchi identity, and energy-momentum conservation, we find
a new algebraic equation for the radial coordinate of the reference metric. We
demonstrate that this equation suggests an absence of the Vainshtein mechanism
in the minimal model of the dRGT massive gravity, while it has two branches of
solutions where one connects with the Schwarzschild space-time and another
implies the significant deviation from the asymptotically flat space-time in
the non-minimal model. We also briefly discuss the boundary conditions for the
relativistic stars in the dRGT massive gravity and a potential relation with
the mass-radius relation of the stars.


  We have been conducting the GMRT High Resolution Southern Sky (GHRSS) survey
for the last four years and have discovered 18 pulsars to date. The GHRSS
survey is an off-Galactic-plane survey at 322 MHz in a region of the sky
(declination range -40 degrees to -54 degrees) complementary to other ongoing
low-frequency surveys. In this paper we report the discovery of three pulsars,
PSRs J1239-48, J1516-43 and J1726-52. We also present timing solutions for
three pulsars previously discovered with the GHRSS survey: PSR J2144-5237, a
millisecond pulsar with a period P=5 ms in a 10 day orbit around a < 0.18 Msun
companion; PSR J1516-43, a mildly recycled P=36 ms pulsar in a 228 day orbit
with a companion of mass ~0.4 Msun; and the P=320 ms PSR J0514-4408 which we
show is a source of pulsed $\gamma$-ray emission. We also report radio
polarimetric observations of three of the GHRSS discoveries, PSRs J0418-4154,
J0514-4408 and J2144-5237.


  A supersymmetric affinization of the algebra of octonions is introduced. It
satisfies a super-Malcev property and is N=8 supersymmetric. Its Sugawara
construction recovers, in a special limit, the non-associative N=8 superalgebra
of Englert et al. This paper extends to supersymmetry the results obtained by
Osipov in the bosonic case.


  In the pivotal variable selection problem, we derive the exact non-asymptotic
minimax selector over the class of all $s$-sparse vectors, which is also the
Bayes selector with respect to the uniform prior. While this optimal selector
is, in general, not realizable in polynomial time, we show that its tractable
counterpart (the scan selector) attains the minimax expected Hamming risk to
within factor 2, and is also exact minimax with respect to the probability of
wrong recovery. As a consequence, we establish explicit lower bounds under the
monotone likelihood ratio property and we obtain a tight characterization of
the minimax risk in terms of the best separable selector risk. We apply these
general results to derive necessary and sufficient conditions of exact and
almost full recovery in the location model with light tail distributions and in
the problem of group variable selection under Gaussian noise.


  The overwhelming majority of survivable (fault-tolerant) network design
models assume a uniform fault model. Such a model assumes that every subset of
the network resources (edges or vertices) of a given cardinality $k$ may fail.
While this approach yields problems with clean combinatorial structure and good
algorithms, it often fails to capture the true nature of the scenario set
coming from applications. One natural refinement of the uniform model is
obtained by partitioning the set of resources into vulnerable and safe
resources. The scenario set contains every subset of at most $k$ faulty
resources. This work studies the Fault-Tolerant Path (FTP) problem, the
counterpart of the Shortest Path problem in this fault model and the
Fault-Tolerant Flow problem (FTF), the counterpart of the $\ell$-disjoint
Shortest $s$-$t$ Path problem. We present complexity results alongside exact
and approximation algorithms for both models. We emphasize the vast increase in
the complexity of the problem with respect to the uniform analogue, the
Edge-Disjoint Paths problem.


  The CDF and D0 collaborations have results on a large number of searches for
beyond-the-standard-model phenomena. This talk focuses on searches for
non-supersymmetric model signatures. These results, based on between 1--2.5
fb-1 of data from p pbar collisions at the Fermilab Tevatron, include some of
the world's best limits on extra dimensions models and heavy resonances.


  The plasmonic properties of sphere-like bcc Na nanoclusters ranging from
Na$_{15}$ to Na$_{331}$ have been studied by real-time time-dependent local
density approximation calculations. The optical absorption spectrum, density
response function and static polarizability are evaluated. It is shown that the
effect of the ionic background (ionic species and lattice) of the clusters
accounts for the remaining discrepancy in the principal (surface plasmon)
absorption peak energy between the experiments and previous calculations based
on a jellium background model. The ionic background effect also pushes the
critical cluster size where the maximum width of the principal peak occurs from
Na$_{40}$ predicted by the previous jellium model calculations to Na$_{65}$. In
the volume mode clusters (Na$_{27}$, Na$_{51}$, Na$_{65}$, Na$_{89}$ and
Na$_{113}$) in which the density response function is dominated by an intense
volume mode, a multiple absorption peak structure also appears next to the
principal peak. In contrast, the surface mode clusters of greater size
(Na$_{169}$, Na$_{229}$, Na$_{283}$ and Na$_{331}$) exhibit a smoother and
narrower principal absorption peak because their surface plasmon energy is
located well within that of the unperturbed electron-hole transitions, and
their density responses already bear resemblance to that of classical Mie
theory. Moreover, it is found that the volume plasmon that exist only in finite
size particles, gives rise to the long absorption tail in the UV region. This
volume plasmon manifests itself in the absorption spectrum even for clusters as
large as Na$_{331}$ with an effective diameter of $\sim$3.0 nm.


  We give the first polylogarithmic-competitive randomized online algorithm for
the $k$-server problem on an arbitrary finite metric space. In particular, our
algorithm achieves a competitive ratio of O(log^3 n log^2 k log log n) for any
metric space on n points. Our algorithm improves upon the deterministic
(2k-1)-competitive algorithm of Koutsoupias and Papadimitriou [J.ACM'95]
whenever n is sub-exponential in k.


  Code generation tools driven by artificial intelligence have recently become
more popular due to advancements in deep learning and natural language
processing that have increased their capabilities. The proliferation of these
tools may be a double-edged sword because while they can increase developer
productivity by making it easier to write code, research has shown that they
can also generate insecure code. In this paper, we perform a user-centered
evaluation GitHub's Copilot to better understand its strengths and weaknesses
with respect to code security. We conduct a user study where participants solve
programming problems (with and without Copilot assistance) that have
potentially vulnerable solutions. The main goal of the user study is to
determine how the use of Copilot affects participants' security performance. In
our set of participants (n=25), we find that access to Copilot accompanies a
more secure solution when tackling harder problems. For the easier problem, we
observe no effect of Copilot access on the security of solutions. We also
observe no disproportionate impact of Copilot use on particular kinds of
vulnerabilities. Our results indicate that there are potential security
benefits to using Copilot, but more research is warranted on the effects of the
use of code generation tools on technically complex problems with security
requirements.


  We propose a geometric relation between closed and open string amplitudes at
one-loop. After imposing a homological splitting on the world-sheet torus
twisted intersection theory is used to establish a one-loop double copy
relation. The latter expresses a closed string amplitude by a pair of open
string amplitudes and twisted intersection numbers. These inner products on the
vector space of allowed differential forms are related to the twisted homology
and cohomology groups associated with the Riemann-Wirtinger integral.


  We have studied the scalar $\phi^4$-model in the symmetric phase and the
non--compact $U(1)$ gauge theory on a momentum lattice using the Langevin
equation for generating configurations. In the $\phi^4$-model we have analyzed
the renormalized mass and in the $U(1)$-model we have analyzed the Wilson loop
operator. We used a second order algorithm for solving the Langevin equation,
and we looked for the convergence rate of the method. We studied the stochastic
time needed to generate equilibrium configurations and compared first and
second order schemes for both models.


  We give a simpler proof of a result of Hodkinson in the context of a blow and
blur up construction argueing that the idea at heart is similar to that adopted
by Andr\'eka et all \cite{sayed}. The idea is to blow up a finite structure,
replacing each 'colour or atom' by infinitely many, using blurs to represent
the resulting term algebra, but the blurs are not enough to blur the structure
of the finite structure in the complex algebra. A reverse of this process
exists in the literature, it builds algebras with infinite blurs converging to
one with finite blurs. This idea due to Hirsch and Hodkinson, uses
probabilistic methods of Erdos to construct a sequence of graphs with infinite
chromatic number one that is 2 colourable. This construction, which works for
both relation and cylindric algebras, further shows that the class of strongly
representable atom structures is not elementary. We will generalize such a
result for any class of algebras between diagonal free algebras and polyadic
algebras with and without equality, then we further discuss possibilities for
the infinite dimensional case.
  Finally, we suggest a very plausible equivalence, and that is: If $n>2$, is
finite, and $\A\in \CA_n$ is countable and atomic, then $\Cm\At\A$ is
representable if and only if $\A\in \Nr_n\CA_{\omega}$. We could prove one
side.


  Secure communications is becoming increasingly relevant in the development of
space technology. Well established cryptographic technology is already in place
and is expected to continue to be so. On the other hand, information
theoretical security emerges as a post-quantum versatile candidate to
complement overall security strength. In order to prove such potential,
performance analysis methods are needed that consider realistic legitimate and
eavesdropper system assumptions and non-asymptotic coding lengths. In this
paper we propose the design of secure radio frequency (RF) satellite links with
realistic system assumptions. Our contribution is three-fold. First, we propose
a wiretap channel model for the finite-length regime. The model includes an
stochastic wiretap encoding method using existing practical linear error
correcting codes and hash codes. Secrecy is provided with privacy
amplification, for which the finite-length secrecy metric is given that upper
bounds semantic secrecy. Second, we derive a novel RF (broadcast) satellite
wiretap channel model that parameterizes the stochastic degraded channel around
the legitimate channel, a necessary condition to enable secure communication.
Finally, we show the design of a secure satellite physical layer and
finite-length performance evaluation. In doing so, we define as sacrifice rate
the fixed fraction of the overall coding rate budget for reliability that needs
to be allocated to secrecy. Our methodology does not make use of channel side
information of the eavesdropper, only assumes worst case system assumptions. We
illustrate our proposed design method with numerical results using practical
error correcting codes in current standards of satellite communication.


  We provide explicit holographic duals of M5-branes wrapped on a sphere with
one irregular puncture and one regular puncture of arbitrary type. The
solutions generalise the solutions corresponding to M5-branes wrapped on a disc
recently constructed by Bah-Bonetti-Minasian-Nardoni by allowing for a general
choice of regular puncture. We show that the central charges, flavour central
charges and conformal dimensions of BPS operators match with a class of
Argyres-Douglas theory.


  In this paper, we study an important class of Finsler metrics--square
metrics. We give two expressions of such metrics in terms of a Riemannian
metric and a 1-form. We show that Einstein square metrics can be classified up
to the classification of Einstein Riemannian metrics.


  At the low temperatures ($\sim$10 K) and high densities ($\sim$100,000 H$_2$
molecules per cc) of molecular cloud cores and protostellar envelopes, a large
amount of molecular species (in particular those containing C and O) freeze-out
onto dust grain surfaces. It is in these regions that the deuteration of
H$_3^+$ becomes very efficient, with a sharp abundance increase of H$_2$D$^+$
and D$_2$H$^+$. The multi-deuterated forms of H$_3^+$ participate in an active
chemistry: (i) their collision with neutral species produces deuterated
molecules such as the commonly observed N$_2$D$^+$, DCO$^+$ and
multi-deuterated NH$_3$; (ii) their dissociative electronic recombination
increases the D/H atomic ratio by several orders of magnitude above the D
cosmic abundance, thus allowing deuteration of molecules (e.g. CH$_3$OH and
H$_2$O) on the surface of dust grains. Deuterated molecules are the main
diagnostic tools of dense and cold interstellar clouds, where the first steps
toward star and protoplanetary disk formation take place. Recent observations
of deuterated molecules are reviewed and discussed in view of astrochemical
models inclusive of spin-state chemistry. We present a new comparison between
models based on complete scrambling (to calculate branching ratio tables for
reactions between chemical species that include protons and/or deuterons) and
models based on non-scrambling (proton hop) methods, showing that the latter
best agree with observations of NH$_3$ deuterated isotopologues and their
different nuclear spin symmetry states.


  Combining model-based and model-free learning systems has been shown to
improve the sample efficiency of learning to perform complex robotic tasks.
However, dual-system approaches fail to consider the reliability of the learned
model when it is applied to make multiple-step predictions, resulting in a
compounding of prediction errors and performance degradation. In this paper, we
present a novel dual-system motor learning approach where a meta-controller
arbitrates online between model-based and model-free decisions based on an
estimate of the local reliability of the learned model. The reliability
estimate is used in computing an intrinsic feedback signal, encouraging actions
that lead to data that improves the model. Our approach also integrates
arbitration with imagination where a learned latent-space model generates
imagined experiences, based on its local reliability, to be used as additional
training data. We evaluate our approach against baseline and state-of-the-art
methods on learning vision-based robotic grasping in simulation and real world.
The results show that our approach outperforms the compared methods and learns
near-optimal grasping policies in dense- and sparse-reward environments.


  We experimentally demonstrate that the statistical properties of distances
between pedestrians which are hindered from avoiding each other are described
by the Gaussian Unitary Ensemble of random matrices. The same result has
recently been obtained for an $n$-tuple of non-intersecting (one-dimensional,
unidirectional) random walks. Thus, the observed behavior of autonomous walkers
conditioned not to cross their trajectories (or, in other words, to stay in
strict order at any time) resembles non-intersecting random walks.


  The upper tail problem in the Erd\H{o}s--R\'enyi random graph
$G\sim\mathcal{G}_{n,p}$ asks to estimate the probability that the number of
copies of a graph $H$ in $G$ exceeds its expectation by a factor $1+\delta$.
Chatterjee and Dembo showed that in the sparse regime of $p\to 0$ as
$n\to\infty$ with $p \geq n^{-\alpha}$ for an explicit $\alpha=\alpha_H>0$,
this problem reduces to a natural variational problem on weighted graphs, which
was thereafter asymptotically solved by two of the authors in the case where
$H$ is a clique. Here we extend the latter work to any fixed graph $H$ and
determine a function $c_H(\delta)$ such that, for $p$ as above and any fixed
$\delta>0$, the upper tail probability is $\exp[-(c_H(\delta)+o(1))n^2 p^\Delta
\log(1/p)]$, where $\Delta$ is the maximum degree of $H$. As it turns out, the
leading order constant in the large deviation rate function, $c_H(\delta)$, is
governed by the independence polynomial of $H$, defined as $P_H(x)=\sum i_H(k)
x^k $ where $i_H(k)$ is the number of independent sets of size $k$ in $H$. For
instance, if $H$ is a regular graph on $m$ vertices, then $c_H(\delta)$ is the
minimum between $\frac12 \delta^{2/m}$ and the unique positive solution of
$P_H(x) = 1+\delta$.


  The $n$-queens puzzle is to place $n$ mutually non-attacking queens on an $n
\times n$ chessboard. We present a simple two stage randomized algorithm to
construct such configurations. In the first stage, a random greedy algorithm
constructs an approximate \textit{toroidal} $n$-queens configuration. In this
well-known variant the diagonals wrap around the board from left to right and
from top to bottom. We show that with high probability this algorithm succeeds
in placing $(1-o(1))n$ queens on the board. In the second stage, the method of
absorbers is used to obtain a complete solution to the non-toroidal problem. By
counting the number of choices available at each step of the random greedy
algorithm we conclude that there are more than $\left( \left( 1 - o(1) \right)
n e^{-3} \right)^n$ solutions to the $n$-queens problem. This proves a
conjecture of Rivin, Vardi, and Zimmerman in a strong form.


  Partial Redundancy Elimination (PRE) is a compiler optimization that
eliminates expressions that are redundant on some but not necessarily all paths
through a program. In this project, we implemented a PRE optimization pass in
LLVM and measured results on a variety of applications. We chose PRE because it
is a powerful technique that subsumes Common Subexpression Elimination (CSE)
and Loop Invariant Code Motion (LICM), and hence has the potential to greatly
improve performance.


  Voltage gated channel proteins cooperate in the transmission of membrane
potentials between nerve cells. With the recent progress in atomic-scaled
biological chemistry it has now become established that these channel proteins
provide highly correlated atomic environments that may maintain electronic
coherences even at warm temperatures. Here we demonstrate solutions of the
Schr\"{o}dinger equation that represent the interaction of a single potassium
ion within the surrounding carbonyl dipoles in the Berneche-Roux model of the
bacterial \textit{KcsA} model channel. We show that, depending on the
surrounding carbonyl derived potentials, alkali ions can become highly
delocalized in the filter region of proteins at warm temperatures. We provide
estimations about the temporal evolution of the kinetic energy of ions
depending on their interaction with other ions, their location within the
oxygen cage of the proteins filter region and depending on different
oscillation frequencies of the surrounding carbonyl groups. Our results provide
the first evidence that quantum mechanical properties are needed to explain a
fundamental biological property such as ion-selectivity in trans-membrane
ion-currents and the effect on gating kinetics and shaping of classical
conductances in electrically excitable cells.


  We present estimates of the basic physical properties (size and albedo) of
(90377) Sedna, a prominent member of the detached trans-Neptunian object
population and the recently discovered scattered disk object 2010 EK139, based
on the recent observations acquired with the Herschel Space Observatory, within
the "TNOs are Cool!" key programme. Our modeling of the thermal measurements
shows that both objects have larger albedos and smaller sizes than the previous
expectations, thus their surfaces might be covered by ices in a significantly
larger fraction. The derived diameter of Sedna and 2010 EK139 are 995 +/- 80 km
and 470 +35/-10 km, while the respective geometric albedos are pV 0.32 +/- 0.06
and 0.25 +0.02/-0.05. These estimates are based on thermophysical model
techniques.


  The first-order transition at $T_{\rm 0} = 270$ K for the platinum-based
SrPt$_2$Sb$_2$ superconductor was investigated using X-ray diffraction and
magnetic susceptibility measurements. When polycrystalline SrPt$_2$Sb$_2$ was
cooled down through $T_{\rm 0}$, the structure was transformed from monoclinic
to a modulated orthorhombic structure, and no magnetic order was formed, which
illustrates the possibility of a charge density wave (CDW) transition at
$T_{\rm 0}$. SrPt$_2$Sb$_2$ can thus be a new example to examine the interplay
of CDW and superconductivity in addition to SrPt$_2$As$_2$, BaPt$_2$As$_2$ and
LaPt$_2$Si$_2$. It is unique that the average structure of the low-temperature
phase has higher symmetry than that of the high-temperature phase.


  The equation of state of two-dimensional $^3$He at zero temperature has been
calculated using the diffusion Monte Carlo method. By means of a combination of
the fixed-node and released-node techniques it is shown that backflow
correlations provide a very accurate equation of state. The results prove
unambiguously the non-self-bound character of two-dimensional $^3$He due to its
Fermi statistics. We present solid evidence that the gas phase, predicted for
the two-dimensional system, can be extrapolated to the case of $^3$He adsorbed
on a strong substrate like graphite.


  We study the appearance of structures in the decay of the $B^-$ into $K^-
\pi^- D_{s0}^+(2317)$ and $K^- \pi^- D_{s1}^+(2460)$ final states by forming
invariant mass distributions of $\pi^- D_{s0}^+$ and $\pi^- D_{s1}^+$ pairs,
respectively. The structure in the distribution is associated to the
kinematical triangle singularity that appears when the $B^- \to K^- K^{*\,0}
D^0$ ($B^- \to K^- K^{*\,0} D^{*\,0}$) decay process is followed by the decay
of the $K^{*\,0}$ into $\pi^- K^+$ and the subsequent rescattering of the $K^+
D^0$ ($K^+ D^{*\,0}$) pair forming the $D_{s0}^+(2317)$ ($D_{s1}^+(2460)$)
resonance. We find this type of non-resonant peaks at 2850 MeV in the invariant
mass of $\pi^- D_{s0}$ pairs from $B^- \to K^- \pi^- D_{s0}^+(2317)$ decays and
around 3000 MeV in the invariant mass of $\pi^- D_{s1}^+$ pairs from $B^- \to
K^- \pi^- D_{s1}^+(2460)$ decays. By employing the measured branching ratios of
the $B^- \to K^- K^{*\,0} D^0$ and $B^- \to K^- K^{*\,0} D^{*\,0}$ decays, we
predict the branching ratios for the processes $B^-$ into $K^-
\pi^-D_{s0}^+(2317)$ and $K^- \pi^- D_{s1}^+(2460)$, in the vicinity of the
triangle singularity peak, to be about $8\times10^{-6}$ and $1\times 10^{-6}$,
respectively. The observation of this reaction would also give extra support to
the molecular picture of the $D_{s0}^+(2317)$ and $D_{s1}^+(2460)$.


  The presence of a weak second-harmonic field in an intense-laser ionization
experiment affects the momentum-resolved electron yield, depending on the
relative phase between the $\omega$ and the $2\omega$ component. The proposed
two-color 'phase-of-the-phase spectroscopy' quantifies for each final electron
momentum a relative-phase contrast (RPC) and a 'phase of the phase' (PP),
describing how much and with which phase lag, respectively, the yield changes
as function of relative phase. Experimental results for RPC and PP spectra for
rare gas atoms and CO$_2$ are presented. The spectra demonstrate a rather
universal structure that is analyzed with the help of a simple model based on
electron trajectories, wave-packet spreading, and (multiple) rescattering.
Details in the PP and RPC spectra are target sensitive and thus may be used to
extract structural (or even dynamical) information with high accuracy.


This paper has been withdrawn as the proof of Lemma 4.1 is incomplete.


  Given a set of interacting components with non-deterministic variable update
and given safety requirements, the goal of priority synthesis is to restrict,
by means of priorities, the set of possible interactions in such a way as to
guarantee the given safety conditions for all possible runs. In distributed
priority synthesis we are interested in obtaining local sets of priorities,
which are deployed in terms of local component controllers sharing intended
next moves between components in local neighborhoods only. These possible
communication paths between local controllers are specified by means of a
communication architecture. We formally define the problem of distributed
priority synthesis in terms of a multi-player safety game between players for
(angelically) selecting the next transition of the components and an
environment for (demonically) updating uncontrollable variables; this problem
is NP-complete. We propose several optimizations including a solution-space
exploration based on a diagnosis method using a nested extension of the usual
attractor computation in games together with a reduction to corresponding SAT
problems. When diagnosis fails, the method proposes potential candidates to
guide the exploration. These optimized algorithms for solving distributed
priority synthesis problems have been integrated into our VissBIP framework. An
experimental validation of this implementation is performed using a range of
case studies including scheduling in multicore processors and modular robotics.


  Let $V$ be a variety in $\mathbb{F}_q^d$ and $E\subset V$. It is known that
if any line passing through the origin contains a bounded number of points from
$E$, then $|\prod(E)|=|\{x\cdot y\colon x, y\in E\}|\gg q$ whenever $|E|\gg
q^{\frac{d}{2}}$. In this paper, we show that the barrier $\frac{d}{2}$ can be
broken when $V$ is a paraboloid in some specific dimensions. The main novelty
in our approach is to link this question to the distance problem in one lower
dimensional vector space, allowing us to use recent developments in this area
to obtain improvements.


  This paper proposes Federated Learning (FL) based smart healthcare system
where Medical Centers (MCs) train the local model using the data collected from
patients and send the model weights to the miners in a blockchain-based robust
framework without sharing raw data, keeping privacy preservation into
deliberation. We formulate an optimization problem by maximizing the utility
and minimizing the loss function considering energy consumption and FL process
delay of MCs for learning effective models on distributed healthcare data
underlying a blockchain-based framework. We propose a solution in two stages:
first, offer a stable matching-based association algorithm to maximize the
utility of both miners and MCs and then solve loss minimization using
Stochastic Gradient Descent (SGD) algorithm employing FL under Differential
Privacy (DP) and blockchain technology. Moreover, we incorporate blockchain
technology to provide tempered resistant and decentralized model weight sharing
in the proposed FL-based framework. The effectiveness of the proposed model is
shown through simulation on real-world healthcare data comparing other
state-of-the-art techniques.


  We contribute a deep-learning-based method that assists in designing
analytical dashboards for analyzing a data table. Given a data table, data
workers usually need to experience a tedious and time-consuming process to
select meaningful combinations of data columns for creating charts. This
process is further complicated by the need of creating dashboards composed of
multiple views that unveil different perspectives of data. Existing automated
approaches for recommending multiple-view visualizations mainly build on
manually crafted design rules, producing sub-optimal or irrelevant suggestions.
To address this gap, we present a deep learning approach for selecting data
columns and recommending multiple charts. More importantly, we integrate the
deep learning models into a mixed-initiative system. Our model could make
recommendations given optional user-input selections of data columns. The
model, in turn, learns from provenance data of authoring logs in an offline
manner. We compare our deep learning model with existing methods for
visualization recommendation and conduct a user study to evaluate the
usefulness of the system.


  In this paper we prove that the fractional derivative or the fractional
primitive of a $T$-periodic function cannot be a $\tilde{T}$-periodic function,
for any period $\tilde{T}$, with the exception of the zero function.


  This work presents a novel approach for robust PCA with total variation
regularization for foreground-background separation and denoising on noisy,
moving camera video. Our proposed algorithm registers the raw (possibly
corrupted) frames of a video and then jointly processes the registered frames
to produce a decomposition of the scene into a low-rank background component
that captures the static components of the scene, a smooth foreground component
that captures the dynamic components of the scene, and a sparse component that
can isolate corruptions and other non-idealities. Unlike existing methods, our
proposed algorithm produces a panoramic low-rank component that spans the
entire field of view, automatically stitching together corrupted data from
partially overlapping scenes. The low-rank portion of our robust PCA model is
based on a recently discovered optimal low-rank matrix estimator (OptShrink)
that requires no parameter tuning. We demonstrate the performance of our
algorithm on both static and moving camera videos corrupted by noise and
outliers.


  We apply machine learning to version control data to measure the quantity of
effort required to produce source code changes. We construct a model of a
`standard coder' trained from examples of code changes produced by actual
software developers together with the labor time they supplied. The effort of a
code change is then defined as the labor hours supplied by the standard coder
to produce that change. We therefore reduce heterogeneous, structured code
changes to a scalar measure of effort derived from large quantities of
empirical data on the coding behavior of software developers. The standard
coder replaces traditional metrics, such as lines-of-code or function point
analysis, and yields new insights into what code changes require more or less
effort.


  A family of stabilizer-free $P_k$ virtual elements are constructed on
triangular meshes. When choosing an accurate and proper interpolation, the
stabilizer of the virtual elements can be dropped while the quasi-optimality is
kept. The interpolating space here is the space of continuous $P_k$ polynomials
on the Hsieh-Clough-Tocher macro-triangle, where the macro-triangle is defined
by connecting three vertices of a triangle with its barycenter. We show that
such an interpolation preserves $P_k$ polynomials locally and enforces the
coerciveness of the resulting bilinear form. Consequently the stabilizer-free
virtual element solutions converge at the optimal order. Numerical tests are
provided to confirm the theory and to be compared with existing virtual
elements.


  We address the strong-coupling regime effects in the light-like quark jets
where the radiated gluons are hard but highly collinear. These may lead to
additional contributions in the invariant mass (or recoil energy) spectra, on
top of the Fermi motion of the initial heavy quark in decays like b->s+\gamma.
It is shown that the integer moments are nevertheless free from such effects;
perturbation theory corrections for the moments are driven by \alpha_s in the
small coupling regime. They are modified nonperturbatively by the soft modes
but not by the collinear modes.


  We introduce a metric on the set of all subsets of natural numbers which
converts it into a cantor set.On this set endowed with the metric, we introduce
a very simple map which exhibits chaotic behaviour.This simple map is almost
like a nursery rhyme of chaos.


  We present a technique to determine the polarization properties of a
telescope through observations of spectral lines that have no intrinsic linear
polarization signals. For such spectral lines, any observed linear polarization
must be induced by the telescope optics. We apply the technique to observations
taken with the SPINOR at the DST and demonstrate that we can retrieve the
characteristic polarization properties of the DST at three wavelengths of 459,
526, and 615 nm. We determine the amount of crosstalk between the intensity
Stokes I and the linear and circular polarization states Stokes Q, U, and V,
and between Stokes V and Stokes Q and U. We fit a set of parameters that
describe the polarization properties of the DST to the observed crosstalk
values. The values for the ratio of reflectivities X and the retardance tau
match those derived with the telescope calibration unit within the error bars.
Residual crosstalk after applying a correction for the telescope polarization
stays at a level of 3-10%. We find that it is possible to derive the parameters
that describe the polarization properties of a telescope from observations of
spectral lines without intrinsic linear polarization signal. Such spectral
lines have a dense coverage (about 50 nm separation) in the visible part of the
spectrum (400-615 nm), but none were found at longer wavelengths. Using
spectral lines without intrinsic linear polarization is a promising tool for
the polarimetric calibration of current or future solar telescopes such as
DKIST.


  Extreme head postures pose a common challenge across a spectrum of facial
analysis tasks, including face detection, facial landmark detection (FLD), and
head pose estimation (HPE). These tasks are interdependent, where accurate FLD
relies on robust face detection, and HPE is intricately associated with these
key points. This paper focuses on the integration of these tasks, particularly
when addressing the complexities posed by large-angle face poses. The primary
contribution of this study is the proposal of a real-time multi-task detection
system capable of simultaneously performing joint detection of faces, facial
landmarks, and head poses. This system builds upon the widely adopted YOLOv8
detection framework. It extends the original object detection head by
incorporating additional landmark regression head, enabling efficient
localization of crucial facial landmarks. Furthermore, we conduct optimizations
and enhancements on various modules within the original YOLOv8 framework. To
validate the effectiveness and real-time performance of our proposed model, we
conduct extensive experiments on 300W-LP and AFLW2000-3D datasets. The results
obtained verify the capability of our model to tackle large-angle face pose
challenges while delivering real-time performance across these interconnected
tasks.


  The contribution of this paper is to provide a semantic model (using soft
constraints) of the words used by web-users to describe objects in a language
game; a game in which one user describes a selected object of those composing
the scene, and another user has to guess which object has been described. The
given description needs to be non ambiguous and accurate enough to allow other
users to guess the described shape correctly.
  To build these semantic models the descriptions need to be analyzed to
extract the syntax and words' classes used. We have modeled the meaning of
these descriptions using soft constraints as a way for grounding the meaning.
  The descriptions generated by the system took into account the context of the
object to avoid ambiguous descriptions, and allowed users to guess the
described object correctly 72% of the times.


  We report observations of a bright dumb-bell system of galaxies ($z =0.162$)
with the upgraded Giant Metrewave Radio Telescope ($u$GMRT), which show that
each member of this gravitationally bound pair of galaxies hosts bipolar radio
jets extended on 100 kiloparsec scales. Only two cases of such radio morphology
have been reported previously, both being dumb-bell systems, as well. The
famous first example, 3C 75, was discovered 4 decades ago, and the second case
was discovered 3 decades ago. This implies that such `Twin-Radio-Galaxies'
(TRGs) are an exceedingly rare phenomenon. As in the case of its two senior
cousins, the bi-polar radio jets of the present TRG (J104454+354055) exhibit
strong wiggles and are edge-darkened (Fanaroff-Riley class I). However, there
are important differences, too. For instance, the jets in the present TRG do
not merge and, moreover, show no signs of distortion due to an external
crosswind. This makes the present TRG a much neater laboratory for studying the
physics of (sideway) colliding jets of relativistic plasma. This TRG has a
Wide-Angle-Tail (WAT) neighbour hosted by another bright galaxy belonging to
the same group, which appears to be moving towards the TRG.


  X-ray observations of clusters of galaxies reveal the presence of edges in
surface brightness and temperature, known as "cold fronts". In relaxed clusters
with cool cores, these commonly observed edges have been interpreted as
evidence for the "sloshing" of the core gas in the cluster's gravitational
potential. Such sloshing may provide a source of heat to the cluster core by
mixing hot gas from the cluster outskirts with the cool core gas. Using
high-resolution $N$-body/Eulerian hydrodynamics simulations, we model gas
sloshing in galaxy clusters initiated by mergers with subclusters. The
simulations include merger scenarios with gas-filled and gasless subclusters.
The effect of changing the viscosity of the intracluster medium is also
explored. We find that sloshing can facilitate heat inflow to the cluster core,
provided that there is a strong enough disturbance. In adiabatic simulations,
we find that sloshing can raise the entropy floor of the cluster core by nearly
an order of magnitude in the strongest cases. If the ICM is viscous, the mixing
of gases with different entropies is decreased and consequently the heat flux
to the core is diminished. In simulations where radiative cooling is included,
we find that though eventually a cooling flow develops, sloshing can prevent
the significant buildup of cool gas in the core for times on the order of a Gyr
for small disturbances and a few Gyr for large ones. If repeated encounters
with merging subclusters sustain the sloshing of the central core gas as is
observed, this process can provide a relatively steady source of heat to the
core, which can help to prevent a significant cooling flow.


  We develop a finite temperature perturbation theory (beyond the mean field)
for a Bose-condensed gas and calculate temperature-dependent damping rates and
energy shifts for Bogolyubov excitations of any energy. The theory is
generalized for the case of excitations in a spatially inhomogeneous (trapped)
Bose-condensed gas, where we emphasize the principal importance of
inhomogeneouty of the condensate density profile and develop the method of
calculating the self-energy functions. The use of the theory is demonstrated by
calculating the damping rates and energy shifts of low-energy quasiclassical
excitations, i.e. the quasiclassical excitations with energies much smaller
than the mean field interaction between particles. In this case the boundary
region of the condensate plays a crucial role, and the result for the damping
rates and energy shifts is completely different from that in spatially
homogeneous gases. We also analyze the frequency shifts and damping of sound
waves in cylindrical Bose condensates and discuss the role of damping in the
recent MIT experiment on the sound propagation.


  A multifractal analysis (MFA) is performed on three-dimensional grayscale
images associated with natural porous structures (soil samples). First,
computed tomography (CT) scans are carried out on the samples to generate 3D
grayscale images. Then, a preliminary analysis is conducted to evaluate key
quantities associated with the porosity, such as void fraction, pore volume,
connectivity, and surface area. Finally, the samples are successfully
identified and separated into two different structure families by using the
MFA. A new software (Munari) to carry out the MFA of 3D grayscale images is
also presented.


  We investigate the appearance of pi lapses in the transmission phase theta of
a two-level quantum dot with Coulomb interaction U. Using the numerical and
functional renormalization group methods we study the entire parameter space
for spin-polarized as well as spin-degenerate dots, modeled by spinless or
spinful electrons, respectively. We investigate the effect of finite
temperatures T. For small T and sufficiently small single-particle spacings
delta of the dot levels we find pi phase lapses between two transmission peaks
in an overwhelming part of the parameter space of the level-lead couplings. For
large delta the appearance or not of a phase lapse between resonances depends
on the relative sign of the level-lead couplings in analogy to the U=0 case. We
show that this generic scenario is the same for spin-polarized and
spin-degenerate dots. We emphasize that in contrast to dots with more levels,
for a two-level dot with small delta and generic dot-lead couplings (that is up
to cases with special symmetry) the "universal" phase lapse behavior is already
established at U=0. The most important effect of the Coulomb interaction is to
increase the separation of the transmission resonances. The relation of the
appearance of phase lapses to the inversion of the population of the dot levels
is discussed. For the spin-polarized case and low temperatures we compare our
results to recent mean-field studies. For small delta correlations are found to
strongly alter the mean-field picture.


  In practice, optimization models are often prone to unavoidable inaccuracies
due to dubious assumptions and corrupted data. Traditionally, this placed
special emphasis on risk-based and robust formulations, and their focus on
``conservative" decisions. We develop, in contrast, an ``optimistic" framework
based on Rockafellian relaxations in which optimization is conducted not only
over the original decision space but also jointly with a choice of model
perturbation. The framework enables us to address challenging problems with
ambiguous probability distributions from the areas of two-stage stochastic
optimization without relatively complete recourse, probability functions
lacking continuity properties, expectation constraints, and outlier analysis.
We are also able to circumvent the fundamental difficulty in stochastic
optimization that convergence of distributions fails to guarantee convergence
of expectations. The framework centers on the novel concepts of exact and
limit-exact Rockafellians, with interpretations of ``negative'' regularization
emerging in certain settings. We illustrate the role of Phi-divergence, examine
rates of convergence under changing distributions, and explore extensions to
first-order optimality conditions. The main development is free of assumptions
about convexity, smoothness, and even continuity of objective functions.
Numerical results in the setting of computer vision and text analytics with
label noise illustrate the framework.


  A technique for rapidly detecting microwave phase has been developed which
uses a spintronic device that can directly rectify microwave fields into a dc
voltage signal. Use of a voltage-controlled phase shifter enables the
development of a spintronic device that can simultaneously 'read' the magnitude
and phase of incident continuous-wave (CW) microwaves when combined with a
lock-in amplifier. As an example of many possible practical applications of
this device, the resonance phase in a complementary electric
inductive-capacitive (CELC) resonator has been characterized using a spintronic
sensor based on a magnetic tunnel junction (MTJ). This sensor device is not
limited for use only with spintronic devices such as MTJs, but can also be used
with semiconductor devices such as microwave detectors, and hence offers a
useful alternative to existing microwave imaging and characterization
technologies.


  The principle of strong induction, also known as k-induction is one of the
first techniques for unbounded SAT-based Model Checking (SMC). While elegant
and simple to apply, properties as such are rarely k-inductive and when they
can be strengthened, there is no effective strategy to guess the depth of
induction. It has been mostly displaced by techniques that compute inductive
strengthenings based on interpolation and property directed reachability (Pdr).
In this paper, we present kAvy, an SMC algorithm that effectively uses
k-induction to guide interpolation and Pdr-style inductive generalization.
Unlike pure k-induction, kAvy uses Pdr-style generalization to compute and
strengthen an inductive trace. Unlike pure Pdr, kAvy uses relative k-induction
to construct an inductive invariant. The depth of induction is adjusted
dynamically by minimizing a proof of unsatisfiability. We have implemented kAvy
within the Avy Model Checker and evaluated it on HWMCC instances. Our results
show that kAvy is more effective than both Avy and Pdr, and that using
k-induction leads to faster running time and solving more instances. Further,
on a class of benchmarks, called shift, kAvy is orders of magnitude faster than
Avy, Pdr and k-induction.


  Iron-based hexaferrites are critical-element-free permanent magnet components
of magnetic devices. Of particular interest is electron-doped M-type
hexaferrite i.e., LaFe$_{12}$O$_{19}$ (LaM) in which extra electrons introduced
by lanthanum substitution of barium/strontium play a key role in uplifting the
magnetocrystalline anisotropy. We investigate the electronic structure of
lanthanum hexaferrite using a \textit{localized} density functional theory
which reproduces semiconducting behavior and identifies the origin of the very
large magnetocrystalline anisotropy. Localized charge transfer from lanthanum
to the iron at the crystal's $2a$ site produces a narrow $3d_{z^2}$ valence
band strongly locking the magnetization along the $c$ axis. The calculated
uniaxial magnetic anisotropy energies from fully self-consistent calculations
are nearly double the single-shot values, and agree well with available
experiments. The chemical similarity of lanthanum to other rare earths suggests
that LaM can host for other rare earths possessing non-trivial $4f$ electronic
states for, \textit{e.g.,} microwave-optical quantum transduction.


  In previous papers it was shown that in a quasi-spherical Szekeres (QSS)
metric, impulses of gamma radiation can arise that have several properties in
common with the observed gamma-ray bursts. This happens when the bang-time
function $t_B(r)$ has a gate-shaped hump around the origin of the QSS region.
The gamma rays arise along two preferred directions of the QSS geometry
(coincident with dipole extrema when axially symmetric, otherwise unrelated).
In these directions, the rays of the relic radiation are blueshifted rather
than redshifted. The blueshift is generated in a thin region between the Big
Bang (BB) and the extremum-redshift hypersurface (ERH). But the Szekeres models
can describe the real Universe only forward in time from the last-scattering
hypersurface (LSH) because the matter in them has zero pressure. The ERH is
tangent to the BB at the origin, so in a neighbourhood thereof the ERH lies
earlier than the LSH and no blueshift is generated in the physical region. The
question thus arose whether the BB and ERH can be ``unglued'' if the QSS region
has no origin, but the areal radius function $\Phi$ has a local maximum or
minimum somewhere. In the present paper it is demonstrated that this is indeed
the case. If the hump in $t_B(r)$ is centered around the minimum of $\Phi$,
then the BB and ERH in general do not coincide there and a stronger blueshift
is generated on rays passing nearby. It follows that a lower and narrower hump
on the BB set can generate sufficient blueshift to move the initial frequencies
of the relic radiation to the gamma range. These facts are demonstrated by
numerical calculations in an explicit example of a QSS region.


  We derive the spectra of the cosmic X-ray background (CXB) and of the
Galactic ridge X-ray emission (GRXE) in the ~20-200 keV range from the data of
the IBIS instrument aboard the INTEGRAL satellite obtained during the four
dedicated Earth-occultation observations of early 2006. We analyse the
modulation of the IBIS/ISGRI detector counts induced by the passage of the
Earth through the field of view of the instrument. Unlike previous studies, we
do not fix the spectral shape of the various contributions, but model instead
their spatial distribution and derive for each of them the expected modulation
of the detector counts. The spectra of the diffuse emission components are
obtained by fitting the normalizations of the model lightcurves to the observed
modulation in different energy bins. The obtained CXB spectrum is consistent
with the historic HEAO-1 results and falls slightly below the spectrum derived
with Swift/BAT. A 10% higher normalization of the CXB cannot be completely
excluded, but it would imply an unrealistically high albedo of the Earth. The
derived spectrum of the GRXE confirms the presence of a minimum around 80 keV
with improved statistics and yields an estimate of ~0.6 M_Sun for the average
mass of white dwarfs in the Galaxy. The analysis also provides updated
normalizations for the spectra of the Earth's albedo and the cosmic-ray induced
atmospheric emission.


  Fermions with the internal degrees of freedom described in Clifford space
carry in any dimension a half integer spin. There are two kinds of spins in
Clifford space. The spin-charge-family theory,assuming even d=13+1, uses one
kind of spins to describe in d=3+1 spins and charges of quarks and leptons and
antiquarks and antileptons, while the other kind is used to describe families.
The new way of second quantization, suggested by the spin-charge-family theory,
is presented. It is shown that the creation and annihilation operators of
1-fermion states, written as products of nilpotents and projectors of an odd
Clifford character, fulfill the anticommutation relations as required in the
second quantization procedure for fermions: 1-fermion states are in Clifford
space already second quantized, the creation operators for any n-fermion second
quantized vectors are products of one fermion creation operators, operating on
the empty vacuum state. It is demonstrated that also in Grassmann space there
exist the creation and annihilation operators of an odd Grassmann character,
generating "fermions", which fulfill as well the anticommutation relations for
fermions, representing correspondingly the second quantized 1-"fermion" states,
in this case with integer spins. Grassmann space offers no families. We discuss
the new second quantization procedure of the fields in both spaces. For the
Grassmann case we present the action, basic states, solutions of the Weyl
equation for free massless "fermions" and discrete symmetry operators. A short
overview of the achievements of the spin-charge-family theory is done, and open
problems of this theory still waiting to be solved are presented. The Grassmann
and the Clifford case are compared in order to better understand open questions
in physics of elementary fermion and boson fields and in cosmology.


  Context. Strong lenses are a biased subset of the general population of
galaxies.
  Aims. The goal of this work is to quantify how lens galaxies and lensed
sources differ from their parent distribution, namely the strong lensing bias.
  Methods. We first studied how the strong lensing cross-section varies as a
function of lens and source properties. Then, we simulated strong lensing
surveys with data similar to that expected for Euclid and measured the strong
lensing bias in different scenarios. We focused particularly on two quantities:
the stellar population synthesis mismatch parameter, $\alpha_{sps}$, defined as
the ratio between the true stellar mass of a galaxy and the stellar mass
obtained from photometry, and the central dark matter mass at fixed stellar
mass and size.
  Results. Strong lens galaxies are biased towards larger stellar masses,
smaller half-mass radii and larger dark matter masses. The amplitude of the
bias depends on the intrinsic scatter in the mass-related parameters of the
galaxy population and on the completeness in Einstein radius of the lens
sample. For values of the scatter that are consistent with observed scaling
relations and a minimum detectable Einstein radius of $0.5''$, the strong
lensing bias in $\alpha_{sps}$ is $10\%$, while that in the central dark matter
mass is $5\%$. The bias has little dependence on the properties of the source
population: samples of galaxy-galaxy lenses and galaxy-quasar lenses that probe
the same Einstein radius distribution are biased in a very similar way.
  Conclusions. Given current uncertainties, strong lensing observations can be
used directly to improve our current knowledge of the inner structure of
galaxies, without the need to correct for selection effects. Time-delay
measurements of $H_0$ from lensed quasars can take advantage of prior
information obtained from galaxy-galaxy lenses with similar Einstein radii.


  Classical information loading is an essential task for many processing
quantum algorithms, constituting a cornerstone in the field of quantum machine
learning. In particular, the embedding techniques based on Hamiltonian
simulation techniques enable the loading of matrices into quantum computers. A
representative example of these methods is the Lloyd-Mohseni-Rebentrost
protocol, which efficiently implements matrix exponentiation when multiple
copies of a quantum state are available. However, this is a quite ideal set up,
and in a realistic scenario, the copies are limited and the non-cloning theorem
prevents from producing more exact copies in order to increase the accuracy of
the protocol. Here, we propose a method to circumvent this limitation by
introducing imperfect quantum copies that significantly enhance the performance
of previous proposals.


  For a Hamiltonian $K \in C^2(\mathbb{R}^{N \times n})$ and a map $u:\Omega
\subseteq \mathbb{R}^n \longrightarrow \mathbb{R}^N$, we consider the supremal
functional \[ \label{1} \tag{1} E_\infty (u,\Omega) \ :=\
\big\|K(Du)\big\|_{L^\infty(\Omega)} . \] The "Euler-Lagrange" PDE associated
to \eqref{1} is the quasilinear system
  \[ \label{2} A_\infty u \, :=\, \Big(K_P \otimes K_P + K[K_P]^\bot
K_{PP}\Big)(Du):D^2 u \, = \, 0. \tag{2} \] Here $K_P$ is the derivative and
$[K_P]^\bot$ is the projection on its nullspace. \eqref{1} and \eqref{2} are
the fundamental objects of vector-valued Calculus of Variations in $L^\infty$
and first arose in recent work of the author \cite{K1}-\cite{K6}. Herein we
apply our results to Geometric Analysis by choosing as $K$ the dilation
function \[ K(P)={|P|^2}{\det(P^\top P)^{-1/n}} \] which measures the deviation
of $u$ from being conformal. Our main result is that appropriately defined
minimisers of \eqref{1} solve \eqref{2}. Hence, PDE methods can be used to
study optimised quasiconformal maps. Nonconvexity of $K$ and appearance of
interfaces where $[K_P]^\bot$ is discontinuous cause extra difficulties. When
$n=N$, this approach has previously been followed by Capogna-Raich \cite{CR}
and relates to Teichm\"uller's theory. In particular, we disprove a conjecture
appearing therein.


  Channel covariance is emerging as a critical ingredient of the acquisition of
instantaneous channel state information (CSI) in multi-user Massive MIMO
systems operating in frequency division duplex (FDD) mode. In this context,
channel reciprocity does not hold, and it is generally expected that covariance
information about the downlink channel must be estimated and fed back by the
user equipment (UE). As an alternative CSI acquisition technique, we propose to
infer the downlink covariance based on the observed uplink covariance. This
inference process relies on a dictionary of uplink/downlink covariance
matrices, and on interpolation in the corresponding Riemannian space; once the
dictionary is known, the estimation does not rely on any form of feedback from
the UE. In this article, we present several variants of the interpolation
method, and benchmark them through simulations.


  There are no ``unknown quantum states.'' It's a contradiction in terms.
Moreover, Alice and Bob are only inanimate objects. They know nothing. What is
teleported instantaneously from one system (Alice) to another system (Bob) is
the applicability of the preparer's knowledge to the state of a particular
qubit in these systems. The operation necessitates dual classical and quantum
channels. Other examples of dual transmission, including ``unspeakable
information,'' will be presented and discussed. This article also includes a
narrative of how I remember that quantum teleportation was conceived.


  In the Bak-Sneppen model, the lowest fitness particle and its two nearest
neighbors are renewed at each temporal step with a uniform (0,1) fitness
distribution. The model presents a critical value that depends on the
interaction criteria (two nearest neighbors) and on the update procedure
(uniform). Here we calculate the critical value for models where one or both
properties are changed. We study models with non-uniform updates, models with
random neighbors and models with binary fitness and obtain exact results for
the average fitness and for $p_c$.


  Eleven dimensional supergravity has electric type currents arising from the
Chern-Simon and anomaly terms in the action. However the bulk charge integrates
to zero for asymptotically flat solutions with topological trivial spatial
sections. We show that by relaxing the boundary conditions to generalisations
of the ALE and ALF boundary conditions in four dimensions one can obtain static
solutions with a bulk charge preserving between 1/16 and 1/4 of the
supersymmetries. One can introduce membranes with the same sign of charge into
these backgrounds. This raises the possibility that these generalized membranes
might decay quantum mechanically to leave just a bulk distribution of charge.
Alternatively and more probably, a bulk distribution of charge can decay into a
collection of singlely charged membranes. Dimensional reductions of these
solutions lead to novel representations of extreme black holes in four
dimensions with up to four charges. We discuss how the eleven-dimensional
Kaluza-Klein monopole wrapped around a space with non-zero first Pontryagin
class picks up an electric charge proportional to the Pontryagin number.


  In orthogonal-frequency division multiplexing (OFDM) systems, carrier and
sampling frequency offsets (CFO and SFO, respectively) can destroy the
orthogonality of the subcarriers and degrade system performance. In the
literature, Nguyen-Le, Le-Ngoc, and Ko proposed a simple maximum-likelihood
(ML) scheme using two long training symbols for estimating the initial CFO and
SFO of a recursive least-squares (RLS) estimation scheme. However, the results
of Nguyen-Le's ML estimation show poor performance relative to the Cramer-Rao
bound (CRB). In this paper, we extend Moose's CFO estimation algorithm to joint
ML estimation of CFO and SFO using two long training symbols. In particular, we
derive CRBs for the mean square errors (MSEs) of CFO and SFO estimation.
Simulation results show that the proposed ML scheme provides better performance
than Nguyen-Le's ML scheme.


  Neutrino-driven winds following core collapse supernovae have been proposed
as a suitable site where the so-called light heavy elements (between Sr to Ag)
can be synthetized. For moderately neutron-rich winds, ($\alpha,n$) reactions
play a critical role in the weak r process, becoming the main mechanism to
drive nuclear matter towards heavier elements. In this paper we summarize the
sensitivity of network-calculated abundances to the astrophysical conditions,
and to uncertainties in the ($\alpha,n$) reaction rates. A list of few
($\alpha,n$) reactions were identified to dominate the uncertainty in the
calculated elemental abundances. Measurements of these reactions will allow to
identify the astrophysical conditions of the weak r process by comparing
calculated/observed abundances in r-limited stars.


  We investigate the phase diagram of an extended Kondo lattice model for doped
manganese oxides in the presence of strong but finite Hund's coupling and
on-site Coulomb interaction. By means of the Schwinger-boson mean-field
approach, it is found that, besides magnetic ordering, there will be
non-uniform charge distributions, such as charge ordering and phase separation,
if the interaction between electrons prevails over the hybridization. Which of
the charge ordering and phase separation appears is determined by a competition
between effective repulsive and attractive interactions due to virtual
processes of electron hopping. Calculated results show that strong electron
correlations caused by the on-site Coulomb interaction as well as the finite
Hund's coupling play an important role in the magnetic ordering and charge
distribution at low temperatures.


  Particulate air pollution is taking a huge toll on modern society, being
associated with more than three million deaths per year. In addition, airborne
infectious microorganism can spread dangerous diseases, further elevating the
problem. A common way to mitigate the risks of airborne particles is by air
filtration. However, conventional air filters usually do not provide any
functionality beyond particle removal. They are unable to inactivate
accumulated contaminants and therefore need periodic maintenance and
replacement to remain operational and safe. This work presents a
multifunctional, self-cleaning air filtration system which utilizes a novel
graphene-enhanced air filter medium (GeFM). The hybrid network of the GeFM
combines the passive structure-based air filtration properties of an underlying
ceramic network with additional active features based on the functional
properties of a graphene thin film. The GeFM is able to capture >95 % of
microorganisms and particles larger than 1 $\mu$m and can be repetitively
Joule-heated to >300 {\deg}C for several hours without signs of degradation.
Hereby, built-up organic particulate matter and microbial contaminants are
effectively decomposed, regenerating the GeFM. Additionally, the GeFM provides
unique options to monitor the filter's air troughput and loading status during
operation. The active features of the GeFM can drastically improve filter
life-time and safety, offering great potential for the development of safer and
more sustainable air filtration solutions to face the future challenges of air
pollution and pandemics.


  In this work we provide an exhaustive study of the photemission spectrum of
paramagnetic FeO under pressure using a refined version of our recently derived
many-body effective energy theory (MEET). We show that, within a nonmagnetic
description of the paramagnetic phase, the MEET gives an overall good
description of the photoemission spectrum at ambient pressure as well as the
changes it undergoes by increasing pressure. In particular at ambient pressure
the band gap opens between the mixed Fe $t_{2g}$ and O $2p$ states and the Fe
4s states and, moreover, a $d$-$d$ gap opens, which is compatible with a
high-spin configuration (hence nonzero local magnetic moments as observed in
experiment), whereas decreasing pressure the band gap tends to close, $t_{2g}$
states tend to become fully occupied and $e_{g}$ fully unoccupied, which is
compatible with a low-spin configuration (hence a collapse of the magnetic
moments as observed in experiment). This is a remarkable result, since, within
a nonmagnetic description of the paramagnetic phase, the MEET is capable to
correctly describe the photoemission spectrum and the spin configuration at
ambient as well as high pressure. For comparison we report the band gap values
obtained using density-functional theory with a hybrid functional containing
screened exchange (HSE06) and a variant of the $GW$ method (self-consistent
COHSEX), which are reliable for the description of the antiferromagnetic phase.
Both methods open a gap at ambient pressure, although, by construction, they
give a low-spin configuration; increasing pressure they correctly describes the
band gap closing. We also report the photoemission spectrum of the metallic
phase obtained with one-shot fully-dynamical $GW$ on top of LDA, which gives a
spectrum very similar to DMFT results from literature.


  We report on a search for a new, short-range, spin-dependent interaction
using a modified version of the experimental apparatus used to measure the
permanent neutron electric dipole moment at the Paul Scherrer Institute. This
interaction, which could be mediated by axion-like particles, concerned the
unpolarized nucleons (protons and neutrons) near the material surfaces of the
apparatus and polarized ultracold neutrons stored in vacuum. The dominant
systematic uncertainty resulting from magnetic-field gradients was controlled
to an unprecedented level of approximately 4 pT/cm using an array of
optically-pumped cesium vapor magnetometers and magnetic-field maps
independently recorded using a dedicated measurement device. No signature of a
theoretically predicted new interaction was found, and we set a new limit on
the product of the scalar and the pseudoscalar couplings $g_sg_p\lambda^2 < 8.3
\times 10^{-28}\,\text{m}^2$ (95% C.L.) in a range of $5\,\mu\text{m} < \lambda
< 25\,\text{mm}$ for the monopole-dipole interaction. This new result confirms
and improves our previous limit by a factor of 2.7 and provides the current
tightest limit obtained with free neutrons.


  Community search has been extensively studied in the past decades. In recent
years, there is a growing interest in attributed community search that aims to
identify a community based on both the query nodes and query attributes. A set
of techniques have been investigated. Though the recent methods based on
advanced learning models such as graph neural networks (GNNs) can achieve
state-of-the-art performance in terms of accuracy, we notice that 1) they
suffer from severe efficiency issues; 2) they directly model community search
as a node classification problem and thus cannot make good use of
interdependence among different entities in the graph. Motivated by these, in
this paper, we propose a new neurAL attrIbuted Community sEarch model for
large-scale graphs, termed ALICE. ALICE first extracts a candidate subgraph to
reduce the search scope and subsequently predicts the community by the
Consistency-aware Net , termed ConNet. Specifically, in the extraction phase,
we introduce the density sketch modularity that uses a unified form to combine
the strengths of two existing powerful modularities, i.e., classical modularity
and density modularity. Based on the new modularity metric, we first adaptively
obtain the candidate subgraph, formed by the k-hop neighbors of the query
nodes, with the maximum modularity. Then, we construct a node-attribute
bipartite graph to take attributes into consideration. After that, ConNet
adopts a cross-attention encoder to encode the interaction between the query
and the graph. The training of the model is guided by the structure-attribute
consistency and the local consistency to achieve better performance. Extensive
experiments over 11 real-world datasets including one billion-scale graph
demonstrate the superiority of ALICE in terms of accuracy, efficiency, and
scalability.


  In this paper, we announce results from our thesis, which studies for the
first time the categorification of the theory of generalized permutohedra. The
vector spaces in the categorification are tightly constrained by certain
continuity relations which appeared in physics in the mid 20th century. We
describe here the action of the symmetric group on the vector spaces in this
categorification. Generalized permutohedra are replaced by vector spaces of
characteristic functions of polyhedral cones about faces of permutohedra,
called plates, due to A. Ocneanu. The symmetric group acts on plates by
coordinate permutation.
  In combinatorics, the Eulerian numbers count the number of permutations with
a given number of ascent and descents. The classical Worpitzky identity expands
a power $r^p$ as a sum of Eulerian numbers, with binomial coefficients. In our
thesis, for the main result we generalize the classical Worpitzky identity to
an isomorphism of symmetric group modules, corresponding geometrically to the
tiling of a scaled simplex by unit hypersimplices. In the categorification, the
volume of a hypersimplex is replaced by the complex-linear dimension of a
vector space associated to it. The main technical aspect of the proof of the
character formula for the simplex involves a partition of unity of a
commutative algebra of translations on a discrete torus, and a certain modular
Diophantine equation.
  A detailed paper is in preparation.


  We investigate the problem of identifying $\nu_\tau$-induced reactions in
large neutrino telescopes. We concentrate on events with tracks and showers
where the respective energies $E_\mu$ and $E_X$ are measured separately. Then
we compute analytically and numerically event distributions in two variables
$r_l = E_X/E_l$ and $y'=E_{\text{X}}/(E_{\mu}+E_{X})$. We find that the
$y'$-distribution is especially useful because in the $\nu_\tau$-induced
reactions the distribution has a minimum at $y'=0.75$ and then increases as
$y'\rightarrow1$. This is different in $\nu_\mu$-induced reactions where the
$y'$-distribution decreases monotonically. The results are demonstrated with
figures where one can estimate the required sensitivity of the experiments.
Another attractive property is that in several ratios the neutrino flux
factorizes and drops out. We hope the results of this article will be useful
for searches of tau (anti)neutrinos of energies above 100 GeV to several TeV in
the present and planned large volume neutrino telescopes.


  We investigate the magnetic polarization of the Ir $5d$ dopant states in the
pnictide superconductor Ba(Fe$_{1-x}$Ir$_x$)$_2$As$_2$ with $x=0.027(2)$ using
Ir $L_3$ edge x-ray resonant magnetic scattering (XRMS). Despite the fact that
doping partially suppresses the antiferromagnetic transition, we find that
magnetic order survives around the Ir dopant sites. The Ir states are
magnetically polarized with commensurate stripe-like antiferromagnetic order
and long correlations lengths, $\xi_{\text{mag}}>$ 2800 and $>$850 \AA{}, in
the $ab$-plane and along the c-axis, respectively, driven by their interaction
with the Fe spins. This Ir magnetic order persists up to the N\'{e}el
transition of the majority Fe spins at $T_N=74(2)$ K. At 5 K we find that
magnetic order co-exists microscopically with superconductivity in
Ba(Fe$_{1-x}$Ir$_x$)$_2$As$_2$. The energy dependence of the XRMS through the
Ir $L_3$ edge shows a non-Lorentzian lineshape, which we explain in terms of
interference between Ir resonant scattering and Fe non-resonant magnetic
scattering.


  It is known from \cite{LW} that the solvability of the mean field equation
$\Delta u+e^{u}=8n\pi \delta_{0}$ with $n\in\mathbb{N}_{\geq 1}$ on a flat
torus $E_{\tau}$ essentially depends on the geometry of $E_{\tau}$. A
conjecture is the non-existence of solutions for this equation if $E_{\tau}$ is
a rectangular torus, which was proved for $n=1$ in \cite{LW}. For any $n\in
\mathbb{N}_{\geq2}$, this conjecture seems challenging from the viewpoint of
PDE theory. In this paper, we prove this conjecture for $n=2$ (i.e. at critical
parameter $16\pi$).


  The resurgence of machine learning has increased the demand for
high-performance basic linear algebra subroutines (BLAS), which have long
depended on libraries to achieve peak performance on commodity hardware.
High-performance BLAS implementations rely on a layered approach that consists
of tiling and packing layers, for data (re)organization, and micro kernels that
perform the actual computations. The creation of high-performance micro kernels
requires significant development effort to write tailored assembly code for
each architecture. This hand optimization task is complicated by the recent
introduction of matrix engines by IBM's POWER10 MMA, Intel AMX, and Arm ME to
deliver high-performance matrix operations. This paper presents a compiler-only
alternative to the use of high-performance libraries by incorporating, to the
best of our knowledge and for the first time, the automatic generation of the
layered approach into LLVM, a production compiler. Modular design of the
algorithm, such as the use of LLVM's matrix-multiply intrinsic for a clear
interface between the tiling and packing layers and the micro kernel, makes it
easy to retarget the code generation to multiple accelerators. The use of
intrinsics enables a comprehensive performance study. In processors without
hardware matrix engines, the tiling and packing delivers performance up to 22x
(Intel), for small matrices, and more than 6x (POWER9), for large matrices,
faster than PLuTo, a widely used polyhedral optimizer. The performance also
approaches high-performance libraries and is only 34% slower than OpenBLAS and
on-par with Eigen for large matrices. With MMA in POWER10 this solution is, for
large matrices, over 2.6x faster than the vector-extension solution, matches
Eigen performance, and achieves up to 96% of BLAS peak performance.


  In quasi-one- or quasi-two-dimensional traps with strong transverse
confinements, quantum gases behave like strictly one- or two-dimensional
systems at large length scales. However, at short distance, the two-body
scattering intrinsically has three-dimensional characteristics such that an
exact description of any universal thermodynamic relation requires
three-dimensional contacts, no matter how strong the confinement is. A
fundamental question arises as to whether one- or two-dimensional contacts,
which were originally defined for strictly one or two dimensions, are capable
of describing quantum gases in quasi-one- or quasi-two-dimensional traps. Here,
we point out an exact relation between the three- and low-dimensional contacts
in these highly anisotropic traps. Such relation allows us to directly connect
physical quantities at different length scales, and to characterise the
quasi-one- or quasi-two-dimensional traps using universal thermodynamic
relations that were derived for strict one or two dimensions.


  We give results on when a finitely generated group has only indiscrete
embeddings in SL(2,C), with particular reference to 3-manifold groups. For
instance if we glue two copies of the figure 8 knot along its torus boundary
then the fundamental group of the resulting closed 3-manifold sometimes embeds
in SL(2,C) and sometimes does not, depending on the identification. We also
give another quick counterexample to Minsky's simple loop question.


  We employed {\it in-situ} pulsed laser deposition (PLD) and angle-resolved
photoemission spectroscopy (ARPES) to investigate the mechanism of the
metal-insulator transition (MIT) in NdNiO$_3$ (NNO) thin films, grown on
NdGaO$_3$(110) and LaAlO$_3$(100) substrates. In the metallic phase, we observe
three dimensional hole and electron Fermi surface (FS) pockets formed from
strongly renormalized bands with well-defined quasiparticles. Upon cooling
across the MIT in NNO/NGO sample, the quasiparticles lose coherence via a
spectral weight transfer from near the Fermi level to localized states forming
at higher binding energies. In the case of NNO/LAO, the bands are apparently
shifted upward with an additional holelike pocket forming at the corner of the
Brillouin zone. We find that the renormalization effects are strongly
anisotropic and are stronger in NNO/NGO than NNO/LAO. Our study reveals that
substrate-induced strain tunes the crystal field splitting, which changes the
FS properties, nesting conditions, and spin-fluctuation strength, and thereby
controls the MIT via the formation of an electronic order parameter with
Q$_{AF}\sim$(1/4, 1/4, 1/4$\pm$$\delta$).


  We explore how questions related to developing a sustainable human
civilization can be cast in terms of astrobiology. In particular we show how
ongoing astrobiological studies of the coupled relationship between life,
planets and their co-evolution can inform new perspectives and direct new
studies in sustainability science. Using the Drake Equation as a vehicle to
explore the gamut of astrobiology, we focus on its most import factor for
sustainability: the mean lifetime <L> of an ensemble of Species with
Energy-Intensive Technology (SWEIT). We then cast the problem into the language
of dynamical system theory and introduce the concept of a trajectory bundle for
SWEIT evolution and discuss how astrobiological results usefully inform the
creation of dynamical equations, their constraints and initial conditions.
Three specific examples of how astrobiological considerations can be folded
into discussions of sustainability are discussed: (1) concepts of planetary
habitability, (2) mass extinctions and their possible relation to the current,
so-called Anthropocene epoch, and (3) today's changes in atmospheric chemisty
(and the climate change it entails) in the context of pervious epochs of
biosphere-driven atmospheric and climate alteration (i.e. the Great Oxidation
Event).


  In this paper, online convex optimization is applied to the problem of
controlling linear dynamical systems. An algorithm similar to online gradient
descent, which can handle time-varying and unknown cost functions, is proposed.
Then, performance guarantees are derived in terms of regret analysis. We show
that the proposed control scheme achieves sublinear regret if the variation of
the cost functions is sublinear. In addition, as a special case, the system
converges to the optimal equilibrium if the cost functions are invariant after
some finite time. Finally, the performance of the resulting closed loop is
illustrated by numerical simulations.


  We present a fully nonlinear theory for dust acoustic (DA) shocks and DA
solitary pulses in a strongly coupled dusty plasma, which have been recently
observed experimentally by Heinrich et al. [Phys. Rev. Lett. 103, 115002
(2009)], Teng et al. [Phys. Rev. Lett. 103, 245005 (2009)], and Bandyopadhyay
et al. [Phys. Rev. Lett. 101, 065006 (2008)]. For this purpose, we use a
generalized hydrodynamic model for the strongly coupled dust grains, accounting
for arbitrary large amplitude dust number density compressions and potential
distributions associated with fully nonlinear nonstationary DA waves.
Time-dependent numerical solutions of our nonlinear model compare favorably
well with the recent experimental works (mentioned above) that have reported
the formation of large amplitude non-stationary DA shocks and DA solitary
pulses in low-temperature dusty plasma discharges.


  Ashby's law of requisite variety allows a comparison of systems with their
environments, providing a necessary (but not sufficient) condition for system
efficacy: a system must possess at least as much complexity as any set of
environmental behaviors that require distinct responses from the system.
However, the complexity of a system depends on the level of detail, or scale,
at which it is described. Thus, the complexity of a system can be better
characterized by a complexity profile (complexity as a function of scale) than
by a single number. It would therefore be useful to have a multi-scale
generalization of Ashby's law that requires that a system possess at least as
much complexity as the relevant set of environmental behaviors *at each scale*.
We construct a formalism for a class of complexity profiles that is the first,
to our knowledge, to exhibit this multi-scale law of requisite variety. This
formalism not only provides a characterization of multi-scale complexity but
also generalizes the single constraint on system behaviors provided by Ashby's
law to an entire class of multi-scale constraints. We show that these
complexity profiles satisfy a sum rule, which reflects the important tradeoff
between smaller- and larger-scale degrees of freedom, and we extend our results
to subdivided systems and systems with a continuum of components.


  Long-range time series forecasting is usually based on one of two existing
forecasting strategies: Direct Forecasting and Iterative Forecasting, where the
former provides low bias, high variance forecasts and the latter leads to low
variance, high bias forecasts. In this paper, we propose a new forecasting
strategy called Generative Forecasting (GenF), which generates synthetic data
for the next few time steps and then makes long-range forecasts based on
generated and observed data. We theoretically prove that GenF is able to better
balance the forecasting variance and bias, leading to a much smaller
forecasting error. We implement GenF via three components: (i) a novel
conditional Wasserstein Generative Adversarial Network (GAN) based generator
for synthetic time series data generation, called CWGAN-TS. (ii) a transformer
based predictor, which makes long-range predictions using both generated and
observed data. (iii) an information theoretic clustering algorithm to improve
the training of both the CWGAN-TS and the transformer based predictor. The
experimental results on five public datasets demonstrate that GenF
significantly outperforms a diverse range of state-of-the-art benchmarks and
classical approaches. Specifically, we find a 5% - 11% improvement in
predictive performance (mean absolute error) while having a 15% - 50% reduction
in parameters compared to the benchmarks. Lastly, we conduct an ablation study
to further explore and demonstrate the effectiveness of the components
comprising GenF.


  A study of collisionless external shocks in gamma-ray bursts is presented.
The shock structure, electromagnetic fields, and process of electron
acceleration are assessed by performing a self-consistent 3D particle-in-cell
(PIC) simulation. In accordance with hydrodynamic shock systems, the shock
consists of a reverse shock (RS) and forward shock (FS) separated by a contact
discontinuity (CD). The development and structure are controlled by the ion
Weibel instability. The ion filaments are sources of strong transverse
electromagnetic fields at both sides of the double shock structure over a
length of 30 - 100 ion skin depths. Electrons are heated up to a maximum energy
$\epsilon_{\rm ele}\approx \sqrt{\epsilon_{\rm b}}$, where $\epsilon$ is the
energy normalized to the total incoming energy. Jet electrons are trapped in
the RS transition region due to the presence of an ambipolar electric field and
reflection by the strong transverse magnetic fields in the shocked region. In a
process similar to shock surfing acceleration (SSA) for ions, electrons
experience drift motion and acceleration by ion filament transverse electric
fields in the plane perpendicular to the shock propagation direction.
Ultimately accelerated jet electrons are convected back into the upstream.


  The one-dimensional Hubbard model with arbitrary boundary magnetic fields is
solved exactly via the Bethe ansatz methods. With the coordinate Bethe ansatz
in the charge sector, the second eigenvalue problem associated with the spin
sector is constructed. It is shown that the second eigenvalue problem can be
transformed into that of the inhomogeneous XXX spin chain with arbitrary
boundary fields which can be solved via the off-diagonal Bethe ansatz method.


  We construct a duality for F-manifolds with eventual identities and special
families of connections and we describe its interactions with several
well-known constructions from the theory of Frobenius and F-manifolds.


  A possibility of applying 2MASS J, H, Ks, IPHAS r, i and MegaCam u, g
photometry of red giants for determining distances to dark clouds is
investigated. Red clump giants with a small admixture of G5-K1 and M2-M3 stars
of the giant branch can be isolated and used in determining distances to
separate clouds or spiral arms. The method is applied to an area of the North
America and Pelican nebulae complex. Interstellar extinctions of background red
giants can be also used for mapping dust surface density in the cloud.