  A new method of absolute calibration of sky noise temperature using a
three-position switched spectrometer, measurements of antenna and low noise
amplifier impedance with a vector network analyzer, and ancillary measurements
of the amplifier noise waves is described. The details of the method and its
application to accurate wideband measurements of the spectral index of the sky
noise are described and compared with other methods.


  This work proposes a novel resource allocation strategy for anti-jamming in
Cognitive Radio using Active Inference ($\textit{AIn}$), and a cognitive-UAV is
employed as a case study. An Active Generalized Dynamic Bayesian Network
(Active-GDBN) is proposed to represent the external environment that jointly
encodes the physical signal dynamics and the dynamic interaction between UAV
and jammer in the spectrum. We cast the action and planning as a Bayesian
inference problem that can be solved by avoiding surprising states (minimizing
abnormality) during online learning. Simulation results verify the
effectiveness of the proposed $\textit{AIn}$ approach in minimizing
abnormalities (maximizing rewards) and has a high convergence speed by
comparing it with the conventional Frequency Hopping and Q-learning.


  Rare B decays permit stringent tests of the Standard Model and allow searches
for new physics. Several rare radiative-decay studies of the B meson from the
BaBar collaboration are described. So far no sign for new physics was
discovered.


  The Jack polynomials with prescribed symmetry are obtained from the
nonsymmetric polynomials via the operations of symmetrization,
antisymmetrization and normalization. After dividing out the corresponding
antisymmetric polynomial of smallest degree, a symmetric polynomial results. Of
interest in applications is the value of the latter polynomial when all the
variables are set equal. Dunkl has obtained this evaluation, making use of a
certain skew symmetric operator. We introduce a simpler operator for this
purpose, thereby obtaining a new derivation of the evaluation formula. An
expansion formula of a certain product in terms of Jack polynomials with
prescribed symmetry implied by the evaluation formula is used to derive a
generalization of a constant term identity due to Macdonald, Kadell and Kaneko.
Although we don't give the details in this work, the operator introduced here
can be defined for any reduced crystallographic root system, and used to
provide an evaluation formula for the corresponding Heckman-Opdam polynomials
with prescribed symmetry.


  We prove that if $f$ is a partially hyperbolic diffeomorphism on 3-torus
$\mathbb{T}^3$ and isotopic to Anosov, then $f$ is chain transitive.


  In this paper, we propose a simple hybrid WENO scheme to increase
computational efficiency and decrease numerical dissipation. Based on the
characteristic-wise approach, the scheme switches the numerical flux of each
characteristic variables between that of WENO scheme and its optimal linear
scheme according to a discontinuity detector measuring the non-resolvability of
the linear scheme. A number of numerical examples computed with 5th-order WENO
scheme suggested that, while achieving very small numerical dissipation and
good robustness, the computational effort on WENO flux used in the hybrid
scheme is negligible.


  Quantum computing is the process of performing calculations using quantum
mechanics. This field studies the quantum behavior of certain subatomic
particles for subsequent use in performing calculations, as well as for
large-scale information processing. These capabilities can give quantum
computers an advantage in terms of computational time and cost over classical
computers. Nowadays, there are scientific challenges that are impossible to
perform by classical computation due to computational complexity or the time
the calculation would take, and quantum computation is one of the possible
answers. However, current quantum devices have not yet the necessary qubits and
are not fault-tolerant enough to achieve these goals. Nonetheless, there are
other fields like machine learning or chemistry where quantum computation could
be useful with current quantum devices. This manuscript aims to present a
Systematic Literature Review of the papers published between 2017 and 2023 to
identify, analyze and classify the different algorithms used in quantum machine
learning and their applications. Consequently, this study identified 94
articles that used quantum machine learning techniques and algorithms. The main
types of found algorithms are quantum implementations of classical machine
learning algorithms, such as support vector machines or the k-nearest neighbor
model, and classical deep learning algorithms, like quantum neural networks.
Many articles try to solve problems currently answered by classical machine
learning but using quantum devices and algorithms. Even though results are
promising, quantum machine learning is far from achieving its full potential.
An improvement in the quantum hardware is required since the existing quantum
computers lack enough quality, speed, and scale to allow quantum computing to
achieve its full potential.


  The anisotropic XY-model in a transverse field (s=1/2) on the one-dimensional
alternating superlattice (closed chain) is considered. The solution of the
model is obtained by introducing a generalized Jordan-Wigner transformation
which maps the system onto a non-interacting fermion gas. The exact excitation
spectrum is determined by reducing the problem to a diagonalization of a block
matrix, and it is shown that it is numerically identical to the one obtained by
using the approximate transfer matrix method . The induced magnetization and
the susceptibility $\chi ^{zz}$ are determined as a function of the transverse
field, and it is shown that, at T=0, the susceptibility presents multiple
singularities. It is also shown, as expected, that this critical behaviour
driven by transverse field belongs to the same universality class of the model
on the alternating chain.


  Understanding the physical and chemical mechanisms occurring during the
forming process and operation of an organic resistive memory device is a major
issue for better performances. Various mechanisms were suggested in vertically
stacked memory structures, but the analysis remains indirect and needs
destructive characterization (e.g. cross-section to access the organic layers
sandwiched between electrodes). Here, we report a study on a planar, monolayer
thick, hybrid nanoparticle/molecule device (10 nm gold nanoparticles embedded
in an electro-generated poly(2-thienyl-3,4-(ethylenedioxy)thiophene) layer),
combining, in situ, on the same device, physical (scanning electron microscope,
physico-chemical (thermogravimetry and mass spectroscopy, Raman spectroscopy)
and electrical (temperature dependent current-voltage) characterizations. We
demonstrate that the forming process causes an increase in the gold particle
size, almost 4 times larger than the starting nanoparticles, and that the
organic layer undergoes a significant chemical rearrangement from a sp3 to sp2
amorphous carbon material. Temperature dependent electrical characterizations
of this nonvolatile memory confirm that the charge transport mechanism in the
device is consistent with a trap-filled space charge limited current in the off
state, the sp2 amorphous carbon material containing many electrically active
defects.


  In complex environments with large discrete action spaces, effective
decision-making is critical in reinforcement learning (RL). Despite the
widespread use of value-based RL approaches like Q-learning, they come with a
computational burden, necessitating the maximization of a value function over
all actions in each iteration. This burden becomes particularly challenging
when addressing large-scale problems and using deep neural networks as function
approximators. In this paper, we present stochastic value-based RL approaches
which, in each iteration, as opposed to optimizing over the entire set of $n$
actions, only consider a variable stochastic set of a sublinear number of
actions, possibly as small as $\mathcal{O}(\log(n))$. The presented stochastic
value-based RL methods include, among others, Stochastic Q-learning, StochDQN,
and StochDDQN, all of which integrate this stochastic approach for both
value-function updates and action selection. The theoretical convergence of
Stochastic Q-learning is established, while an analysis of stochastic
maximization is provided. Moreover, through empirical validation, we illustrate
that the various proposed approaches outperform the baseline methods across
diverse environments, including different control problems, achieving
near-optimal average returns in significantly reduced time.


  In a system of noisy self-propelled particles with interactions that favor
directional alignment, collective motion will appear if the density of
particles increases beyond a certain threshold. In this paper, we argue that
such a threshold may depend also on the profiles of the perturbation in the
particle directions. Specifically, we perform mean-field, linear stability,
perturbative and numerical analyses on an approximated form of the
Fokker-Planck equation describing the system. We find that if an angular
perturbation to an initially homogeneous system is large in magnitude and
highly localized in space, it will be amplified and thus serves as an
indication of the onset of collective motion. Our results also demonstrate that
high particle speed promotes collective motion.


  We study the Coulomb drag effect in double layer electronic systems with
local tunneling links. The possibility of tunneling between the layers leads to
a pronounced exchange contribution to the transconductance, which is negative
and non-vanishing at zero temperature. The diffusive motion of the electrons
inside each layer in interplay with the electron-electron interaction cause a
distinguishable singular temperature dependence of the transconductance at low
temperatures.


  We investigate a one-dimensional wire of interacting electrons connected to
semi-infinite leads in the absence and in the presence of a backscattering
potential. An incident electron on the clean wire is perfectly transmitted into
spatially separated spin and charge parts in the noninteracting leads, a result
we extend to any finite-range interactions. The backscattering potential is
renormalized in a non-universal way and therefore the reduction in the
conductance is more complicated than the laws derived up to now: it has power
laws as a function of temperature, wire length, and also the distance of a
barrier to the contacts.


  In this paper, we consider compressed sensing (CS) of block-sparse signals,
i.e., sparse signals that have nonzero coefficients occurring in clusters. An
efficient algorithm, called zero-point attracting projection (ZAP) algorithm,
is extended to the scenario of block CS. The block version of ZAP algorithm
employs an approximate $l_{2,0}$ norm as the cost function, and finds its
minimum in the solution space via iterations. For block sparse signals, an
analysis of the stability of the local minimums of this cost function under the
perturbation of noise reveals an advantage of the proposed algorithm over its
original non-block version in terms of reconstruction error. Finally, numerical
experiments show that the proposed algorithm outperforms other state of the art
methods for the block sparse problem in various respects, especially the
stability under noise.


  We consider the weakly asymmetric simple exclusion process in the presence of
a slow bond and starting from the invariant state, namely the Bernoulli product
measure of parameter $\rho\in(0,1)$. The rate of passage of particles to the
right (resp. left) is
$\frac1{\vphantom{n^\beta}2}+\frac{a}{2n^{\vphantom{\beta}\gamma}}$ (resp.
$\frac1{\vphantom{n^\beta}2}-\frac{a}{2n^{\vphantom{\beta}\gamma}}$) except at
the bond of vertices $\{-1,0\}$ where the rate to the right (resp. left) is
given by $\frac{\alpha}{2n^\beta}+\frac{a}{2n^{\vphantom{\beta}\gamma}}$ (resp.
$\frac{\alpha}{2n^\beta}-\frac{a}{2n^{\vphantom{\beta}\gamma}}$). Above,
$\alpha>0$, $\gamma\geq \beta\geq 0$, $a\geq 0$. For $\beta<1$, we show that
the limit density fluctuation field is an Ornstein-Uhlenbeck process defined on
the Schwartz space if $\gamma>\frac12$, while for $\gamma = \frac12$ it is an
energy solution of the stochastic Burgers equation. For $\gamma\geq\beta=1$, it
is an Ornstein-Uhlenbeck process associated to the heat equation with Robin's
boundary conditions. For $\gamma\geq\beta> 1$, the limit density fluctuation
field is an Ornstein-Uhlenbeck process associated to the heat equation with
Neumann's boundary conditions.


  We numerically investigate the Olami-Feder-Christensen model for earthquakes
in order to characterise its scaling behaviour. We show that ordinary finite
size scaling in the model is violated due to global, system wide events.
Nevertheless we find that subsystems of linear dimension small compared to the
overall system size obey finite (subsystem) size scaling, with universal
critical coefficients, for the earthquake events localised within the
subsystem. We provide evidence, moreover, that large earthquakes responsible
for breaking finite size scaling are initiated predominantly near the boundary.


  Directed acyclic graphs (DAGs) are directed graphs in which there is no path
from a vertex to itself. DAGs are an omnipresent data structure in computer
science and the problem of counting the DAGs of given number of vertices and to
sample them uniformly at random has been solved respectively in the 70's and
the 00's. In this paper, we propose to explore a new variation of this model
where DAGs are endowed with an independent ordering of the out-edges of each
vertex, thus allowing to model a wide range of existing data structures. We
provide efficient algorithms for sampling objects of this new class, both with
or without control on the number of edges, and obtain an asymptotic equivalent
of their number. We also show the applicability of our method by providing an
effective algorithm for the random generation of classical labelled DAGs with a
prescribed number of vertices and edges, based on a similar approach. This is
the first known algorithm for sampling labelled DAGs with full control on the
number of edges, and it meets a need in terms of applications, that had already
been acknowledged in the literature.


  The Lorentzian type IIB matrix model has been studied as a promising
candidate for a nonperturbative formulation of superstring theory. In
particular, the emergence of (3+1)D expanding space-time was observed by Monte
Carlo studies of this model. It has been found recently, however, that the
matrix configurations generated by the simulation is singular in that the
submatrices representing the expanding 3D space have only two large eigenvalues
associated with the Pauli matrices. This problem has been attributed to the
approximation used to avoid the sign problem in simulating the model. Here we
investigate the model using the complex Langevin method to overcome the sign
problem instead of using the approximation. Our results indicate a clear
departure from the Pauli-matrix structure, while the (3+1)D expanding behavior
is kept intact.


  There has been recently a growing interest for implicit shape
representations. Contrary to explicit representations, they have no resolution
limitations and they easily deal with a wide variety of surface topologies. To
learn these implicit representations, current approaches rely on a certain
level of shape supervision (e.g., inside/outside information or
distance-to-shape knowledge), or at least require a dense point cloud (to
approximate well enough the distance-to-shape). In contrast, we introduce
NeeDrop, a self-supervised method for learning shape representations from
possibly extremely sparse point clouds. Like in Buffon's needle problem, we
"drop" (sample) needles on the point cloud and consider that, statistically,
close to the surface, the needle end points lie on opposite sides of the
surface. No shape knowledge is required and the point cloud can be highly
sparse, e.g., as lidar point clouds acquired by vehicles. Previous
self-supervised shape representation approaches fail to produce good-quality
results on this kind of data. We obtain quantitative results on par with
existing supervised approaches on shape reconstruction datasets and show
promising qualitative results on hard autonomous driving datasets such as
KITTI.


  Cold atomic gases have provided us with a great number of opportunities for
studying various physical systems under controlled conditions that are seldom
offered in other fields. We are thus at the point where one can truly do
quantum simulation of models that are relevant for instance in condensed-matter
or high-energy physics, i.e. we are on the verge of a 'cool' quantum simulator
as envisioned by Feynman. One of the avenues under exploration is the physics
of one-dimensional systems. Until recently this was mostly in the many-body
limit but now experiments can be performed with controllable particle numbers
all the way down to the few-body regime. After a brief introduction to some of
the relevant experiments, I will review recent theoretical work on
one-dimensional quantum systems containing bosons, fermions, or mixtures of the
two, with a particular emphasis on the case where the particles are held by an
external trap.


  We investigate naturalness in the Standard Model (SM) Higgs sector using
effective field theory (EFT) techniques and find the requirements on the new
heavy physics that can potentially cure the little hierarchy problem below a
scale $\Lambda \gg O(1 ~{\rm TeV})$, assuming the new heavy particles have a
mass larger than $ \Lambda $. In particular, we determine the conditions under
which the 1-loop corrections to $ m_h $ from the heavy new physics can balance
those created by SM loop effects up to the naturalness scale $\Lambda$, a
condition we denote by "EFT Naturalness". We obtain the higher dimensional ($n
\ge 5$) operators in the effective Lagrangian that can lead to EFT Naturalness,
and classify the underlying heavy theories that can generate such operators at
tree-level. We also address the experimental constraints on our EFT Naturalness
setup and discuss the expected experimental signals of the new heavy physics
associated with EFT Naturalness.


  We simulate neutrino-antineutrino oscillations caused by strong magnetic
fields in dense matter. With the strong magnetic fields and large neutrino
magnetic moments, Majorana neutrinos can reach flavor equilibrium. We find that
the flavor equilibration of neutrino-antineutrino oscillations is sensitive to
the values of the baryon density and the electron fraction inside the matter.
The neutrino-antineutrino oscillations are suppressed in the case of the large
baryon density in neutron (proton)-rich matter. On the other hand, the flavor
equilibration occurs when the electron fraction is close to $0.5$ even in the
large baryon density. From the simulations, we propose a necessary condition
for the equilibration of neutrino-antineutrino oscillations in dense matter. We
also study whether such necessary condition is satisfied near the proto-neutron
star by using results of neutrino hydrodynamic simulations of core-collapse
supernovae. In our explosion model, the flavor equilibration would be possible
if the magnetic field on the surface of the proto-neutron star is larger than
$10^{14}$ G which is the typical value of the magnetic fields of magnetars.


  We present a complete calculation of nucleon-deuteron scattering as well as
ground and low-lying excited states of light nuclei in the mass range A=3-16 up
through next-to-next-to-leading order in chiral effective field theory using
semilocal coordinate-space regularized two- and three-nucleon forces. It is
shown that both of the low-energy constants entering the three-nucleon force at
this order can be reliably determined from the triton binding energy and the
differential cross section minimum in elastic nucleon-deuteron scattering. The
inclusion of the three-nucleon force is found to improve the agreement with the
data for most of the considered observables.


  Lorentz symmetry violation (LSV) can be generated at the Planck scale, or at
some other fundamental length scale, and naturally preserve Lorentz symmetry as
a low-energy limit (deformed Lorentz symmetry, DLS). DLS can have important
implications for ultra-high energy cosmic-ray physics (see papers
physics/0003080, astro-ph/0011181 and astro-ph/0011182, and references quoted
in these papers). A crucial question is how DLS can be extended to a deformed
Poincare symmetry (DPS), and what can be the dynamical origin of this
phenomenon. We discuss recent proposals to identify DPS with a symmetry
incorporating the Planck scale (doubly special relativity, DSR) and suggest new
ways in this direction. Implications for models of quadratically deformed
relativistic kinematics (QDRK) and linearly deformed relativistic kinematics
(LDRK) are also discussed.


  One-loop corrections to the self-coupling constant of the lightest CP-even
Higgs boson are studied in the two Higgs doublet model. After renormalization
is performed, quartic contributions of heavy particle's mass can appear in the
effective coupling. We find that these non-decoupling effects can yield ${\cal
O}(100)$ % deviations from the Standard Model prediction, even when all the
other couplings of the lightest Higgs boson to gauge bosons and fermions are in
good agreement with the Standard Model.


  Current video summarization methods primarily depend on supervised computer
vision techniques, which demands time-consuming manual annotations. Further,
the annotations are always subjective which make this task more challenging. To
address these issues, we analyzed the feasibility in transforming the video
summarization into a text summary task and leverage Large Language Models
(LLMs) to boost video summarization. This paper proposes a novel
self-supervised framework for video summarization guided by LLMs. Our method
begins by generating captions for video frames, which are then synthesized into
text summaries by LLMs. Subsequently, we measure semantic distance between the
frame captions and the text summary. It's worth noting that we propose a novel
loss function to optimize our model according to the diversity of the video.
Finally, the summarized video can be generated by selecting the frames whose
captions are similar with the text summary. Our model achieves competitive
results against other state-of-the-art methods and paves a novel pathway in
video summarization.


  The opacity of alkali atoms, most importantly of Na and K, plays a crucial
role in the atmospheres of brown dwarfs and exoplanets. We present a
comprehensive study of NaH2 collisional profiles at temperatures from 500 to
3000 K, the temperatures prevailing in the atmosphere of brown dwarfs and
Jupiter-mass planets.The relevant H2 perturber densities reach several 10^19
cm^-3 in hot Teff > 1500 K Jupiter-mass planets and can exceed 10^20 cm^-3 for
more massive or cooler objects. Accurate pressure-broadened profiles that are
valid at high densities of H2 should be incorporated into spectral models.
Unified profiles of sodium perturbed by molecular hydrogen were calculated in
the semi-classical approach using up-to-date molecular data.New NaH2
collisional profiles and their effects on the synthetic spectra of brown dwarfs
and hot Jupiters computed with petitCODE are presented.


  Advances in the field of numerical relativity now make it possible to
calculate the final, most powerful merger phase of binary black-hole
coalescence for generic binaries. The state of the art has advanced well beyond
the equal-mass case into the unequal-mass and spinning regions of parameter
space. We present a study of the nonspinning portion of parameter space,
primarily using an analytic waveform model tuned to available numerical data,
with an emphasis on observational implications. We investigate the impact of
varied mass ratio on merger signal-to-noise ratios (SNRs) for several
detectors, and compare our results with expectations from the test-mass limit.
We note a striking similarity of the waveform phasing of the merger waveform
across the available mass ratios. Motivated by this, we calculate the match
between our 1:1 (equal mass) and 4:1 mass-ratio waveforms during the merger as
a function of location on the source sky, using a new formalism for the match
that accounts for higher harmonics. This is an indicator of the amount of
degeneracy in mass ratio for mergers of moderate-mass-ratio systems.


  In this note we consider a system with a large angular momentum l whose state
we can store using some log_2(l) qubits. The problem then is how to carry out
spatial rotations of the system in this representation. In other words we are
looking at a unitary representation of SU(2) with dimension 2l+1 and want to
implement these transformations with resources polynomial in log(l). We only
give a sketch of our solution which involves ``storing'' discretised spherical
harmonic functions Y_{l,m}(Theta,phi) in a quantum register. Also there are
some technical gaps in the construction, but they are based on plausible
assumptions. Our approach is rather cumbersome and we hope somebody will find a
nicer solution. For a nice, elementary explanation of what we are trying to do
(not involving physics or representation theory) see section 4.6.2.


  In the area of networks, a common method to enforce a security policy
expressed in a high-level language is based on an ad-hoc and manual rewriting
process. We argue that it is possible to build a formal link between concrete
and abstract terms, which can be dynamically computed from the environment
data. In order to progressively introduce configuration data and then simplify
the proof obligations, we use the B refinement process. We present a case study
modeling a network monitor. This program, described by refinement following the
layers of the TCP/IP suite protocol, has to warn for all observed events which
do not respect the security policy. To design this model, we use the event-B
method because it is suitable for modeling network concepts. This work has been
done within the framework of the POTESTAT project, based on the research of
network testing methods from a high-level security policy.


  Hybrid Automatic ReQuest (HARQ) protocol enables reliable communications in
wireless systems. Usually, several parallel streams are sent in successive
timeslots following a time-sharing approach. Recently, multi-layer HARQ has
been proposed by superposing packets within a timeslot. In this paper, we
evaluate the potential of this multi-layer HARQ by playing with some design
parameters. We show that a gain in throughput is only obtained at
mid-Signal-to-Noise Ratio (SNR).


  With a light dilaton $\sigma$ and the light-quark vector mesons
$V=(\rho,\omega)$ incorporated into an effective scale-invariant hidden local
symmetric Lagrangian, scale-chiral symmetry -- hidden in QCD -- arises at a
high density, $n_{1/2}$, as an "emergent" symmetry, a phenomenon absent in
standard chiral perturbative approaches but highly relevant for massive compact
stars. What takes place as the density increases beyond $n_{1/2}\sim 2n_0$ in
compressed baryonic matter is (1) a topology change from skyrmions to
half-skyrmions, (2) parity doubling in the nucleon structure, (3) the maximum
neutron star mass $M\simeq 2.01 M_{\odot}$ and the radius $R\simeq 12.0$ km and
(4) the sound velocity $v_s^2/c^2\simeq 1/3$ due to the "vector manifestation
(VM)" fixed point of $\rho$ and a "walking" dilaton condensate, which is
intricately connected to the source of the proton mass.


  Recent inspection of liquid-like state in ultracold atomic gases due to the
stabilization mechanism through the delicate balance between effective
mean-field and beyond mean-field (BMF) interactions, has motivated us to study
the modified/extended Gross-Pitaevskii (eGP) equation which includes the BMF
contribution. In this article, we focus on variational analysis of solitonic
regime with eGP equation while the soliton is subjected to an obstacle. This
reveals different scattering scenarios of the soliton with explicit dependence
of the BMF interaction. The results show the existence of tunneling, partial
and complete trappings, in different parameter domains. These observations are
further corroborated by the fast-Fourier transform method. In the later part we
also extend our analysis to trapped systems. The controlled trapping in defect
potential and its release can be potentially useful for quantum information
storage.


  This paper is devoted to the construction of analogues of higher
Ekeland-Hofer symplectic capacities for $P$-symmetric subsets in the standard
symplectic space $(\mathbb{R}^{2n},\omega_0)$, which is motivated by Long and
Dong's study $P$-symmetric closed characteristics on $P$-symmetric convex
bodies. We study the relationship between these capacities and other
capacities, and give some computation examples. Moreover, we also define higher
real symmetric Ekeland-Hofer capacities as a complement of Jin and the second
named author's recent study of the real symmetric analogue about the first
Ekeland-Hofer capacity.


  Reliable and accurate localization is crucial for mobile autonomous systems.
Pole-like objects, such as traffic signs, poles, lamps, etc., are ideal
landmarks for localization in urban environments due to their local
distinctiveness and long-term stability. In this paper, we present a novel,
accurate, and fast pole extraction approach that runs online and has little
computational demands such that this information can be used for a localization
system. Our method performs all computations directly on range images generated
from 3D LiDAR scans, which avoids processing 3D point cloud explicitly and
enables fast pole extraction for each scan. We test the proposed pole
extraction and localization approach on different datasets with different LiDAR
scanners, weather conditions, routes, and seasonal changes. The experimental
results show that our approach outperforms other state-of-the-art approaches,
while running online without a GPU. Besides, we release our pole dataset to the
public for evaluating the performance of pole extractor, as well as the
implementation of our approach.


  Using finite-temperature determinantal quantum Monte Carlo calculations, we
re-examine the pairing susceptibilities in the Hubbard model on the honeycomb
lattice, focusing on doping levels onto and away from the van Hove singularity
(VHS) filling. For this purpose, electronic densities of $0.75$ (at the
hole-doping VHS) and $0.4$ (well below the VHS) are considered in detail, where
due to a severe sign problem at strong coupling strengths, we focus on the weak
interaction region of the Hubbard model Hamiltonian. From analyzing the
temperature dependence of pairing susceptibilities in various symmetry
channels, we find the singlet $d$+$id$-wave to be the dominant pairing channel
both at and away from the VHS filling. We furthermore investigate the
electronic susceptibility to a specific chiral spin density wave (SDW) order,
which we find to be similarly relevant at the VHS, while it extenuates upon
doping away from the VHS filling.


  Network congestion games are a well-understood model of multi-agent strategic
interactions. Despite their ubiquitous applications, it is not clear whether it
is possible to design information structures to ameliorate the overall
experience of the network users. We focus on Bayesian games with atomic
players, where network vagaries are modeled via a (random) state of nature
which determines the costs incurred by the players. A third-party entity---the
sender---can observe the realized state of the network and exploit this
additional information to send a signal to each player. A natural question is
the following: is it possible for an informed sender to reduce the overall
social cost via the strategic provision of information to players who update
their beliefs rationally? The paper focuses on the problem of computing optimal
ex ante persuasive signaling schemes, showing that symmetry is a crucial
property for its solution. Indeed, we show that an optimal ex ante persuasive
signaling scheme can be computed in polynomial time when players are symmetric
and have affine cost functions. Moreover, the problem becomes NP-hard when
players are asymmetric, even in non-Bayesian settings.


  It is well known that for a first order system of linear difference equations
with rational function coefficients, a solution that is holomorphic in some
left half plane can be analytically continued to a meromorphic solution in the
whole complex plane. The poles stem from the singularities of the rational
function coefficients of the system. Just as for differential equations, not
all of these singularities necessarily lead to poles in solutions, as they
might be what is called removable. In our work, we show how to detect and
remove these singularities and further study the connection between poles of
solutions and removable singularities. We describe two algorithms to
(partially) desingularize a given difference system and present a
characterization of removable singularities in terms of shifts of the original
system.


  We analyze Darboux transformations in very general settings for
multidimensional linear partial differential operators. We consider all known
types of Darboux transformations, and present a new type. We obtain a full
classification of all operators that admit Wronskian type Darboux
transformations of first order and a complete description of all possible
first-order Darboux transformations. We introduce a large class of invertible
Darboux transformations of higher order, which we call Darboux transformations
of continued Type I. This generalizes the class of Darboux transformations of
Type I, which was previously introduced. There is also a modification of this
type of Darboux transformations, continued Wronskian type, which generalize
Wronskian type Darboux transformations.


  We present a new lattice model for proteins that incorporates a tube-like
anisotropy by introducing a preference for mutually parallel alignments in the
conformations. The model is demonstrated to capture many aspects of real
proteins.


  In this paper we discuss an abstract iteration scheme for the calculation of
the smallest eigenvalue of an elliptic operator eigenvalue problem. A short and
geometric proof based on the preconditioned inverse iteration (PINVIT) for
matrices [Knyazev and Neymeyr, (2009)] is extended to the case of operators. We
show that convergence is retained up to any tolerance if one only uses
approximate applications of operators which leads to the perturbed
preconditioned inverse iteration (PPINVIT). We then analyze the Besov
regularity of the eigenfunctions of the Poisson eigenvalue problem on a
polygonal domain, showing the advantage of an adaptive solver to uniform
refinement when using a stable wavelet base. A numerical example for PPINVIT,
applied to the model problem on the L-shaped domain, is shown to reproduce the
predicted behaviour.


  A new term describing interactions between charge and potentials may be added
to the right hand side of the Einstein equations. In the proposed term an
additional tensor has been introduced containing a charge density, analogous to
the energy-momentum tensor containing a mass density. (The contribution of the
electromagnetic fields has not been considered in this work.) The metric
components in the new equations may contain charge and mass contributions. In
the special relativistic case a set of four vacuum Maxwell equations is
obtained from the new equations containing a special relativistic charge
density. A related result was recently found by Jefimenko from a special
relativistic transformation. Moreover, from the postulated equations the usual
special relativistic electric energy and Lorentz force can be calculated, when
the approximated electromagnetic metric is used. In the non-relativistic case
the usual Maxwell equations with rest charge density are obtained. In the
presence of a static gravitational field a set of four Maxwell equations is
obtained applying in the general relativistic case. From these equations the
generally accepted isotropic velocity of light can be deduced. In addition,
calculated generalized Maxwell equations show that vacuum permittivity and
permeability may differ from unity value in the presence of a big charge Q or a
big mass M.


  By analyzing the longitudinal conductivity in a quantizing magnetic field
directed perpendicularly to the crystal lattice layers, it has been
demonstrated that the layered-structure effects can be observed not only in
crystals with highly open Fermi surfaces, as was conventionally believed
earlier, but also in crystals with closed ones. The calculations were carried
out in the constant-relaxation-time approximation. In weak magnetic fields,
layered-structure effects manifest themselves as a phase retardation of
Shubnikov--de Haas oscillations and a certain increase of the relative
contribution made by the latter. In the range of high magnetic fields, there
exists an optimal interval, in which the layered-structure effects reveal
themselves in the form of a sharp non-monotonous dependence of conductivity on
the magnetic field. In addition, it has been shown that the layered-structure
effects result in a decrease of the proportionality factor between the
magnetoresistance and the magnetic induction in the longitudinal Kapitsa
effect. The longitudinal conductivity of layered crystals in ultra-quantum
magnetic fields has also been analyzed. It is shown that the following
dependences of the magnetoresistance on the magnetic field can be obtained,
depending on the model used for the filling of the single Landau subband and on
whether the longitudinal conductivity is considered to be of either the drift
or diffusion type: $\rho_{zz}\propto TB^{2}$,\ $\rho_{zz}\propto B^{3}$, and
$\rho_{zz}\propto B^{4}$.


  We present a new method for improving the performances of variational
autoencoder (VAE). In addition to enforcing the deep feature consistent
principle thus ensuring the VAE output and its corresponding input images to
have similar deep features, we also implement a generative adversarial training
mechanism to force the VAE to output realistic and natural images. We present
experimental results to show that the VAE trained with our new method
outperforms state of the art in generating face images with much clearer and
more natural noses, eyes, teeth, hair textures as well as reasonable
backgrounds. We also show that our method can learn powerful embeddings of
input face images, which can be used to achieve facial attribute manipulation.
Moreover we propose a multi-view feature extraction strategy to extract
effective image representations, which can be used to achieve state of the art
performance in facial attribute prediction.


  State space models (SSMs) have demonstrated state-of-the-art sequence
modeling performance in some modalities, but underperform attention in language
modeling. Moreover, despite scaling nearly linearly in sequence length instead
of quadratically, SSMs are still slower than Transformers due to poor hardware
utilization. In this paper, we make progress on understanding the expressivity
gap between SSMs and attention in language modeling, and on reducing the
hardware barrier between SSMs and attention. First, we use synthetic language
modeling tasks to understand the gap between SSMs and attention. We find that
existing SSMs struggle with two capabilities: recalling earlier tokens in the
sequence and comparing tokens across the sequence. To understand the impact on
language modeling, we propose a new SSM layer, H3, that is explicitly designed
for these abilities. H3 matches attention on the synthetic languages and comes
within 0.4 PPL of Transformers on OpenWebText. Furthermore, a hybrid
125M-parameter H3-attention model that retains two attention layers
surprisingly outperforms Transformers on OpenWebText by 1.0 PPL. Next, to
improve the efficiency of training SSMs on modern hardware, we propose
FlashConv. FlashConv uses a fused block FFT algorithm to improve efficiency on
sequences up to 8K, and introduces a novel state passing algorithm that
exploits the recurrent properties of SSMs to scale to longer sequences.
FlashConv yields 2$\times$ speedup on the long-range arena benchmark and allows
hybrid language models to generate text 2.4$\times$ faster than Transformers.
Using FlashConv, we scale hybrid H3-attention language models up to 2.7B
parameters on the Pile and find promising initial results, achieving lower
perplexity than Transformers and outperforming Transformers in zero- and
few-shot learning on a majority of tasks in the SuperGLUE benchmark.


  We study the charged impurity limited mobility in black phosphorus, a highly
anisotropic layered material. We compute the mobility within the Boltzmann
transport equation under detailed balance condition, and taking into account
the anisotropy in transport and electronic structure. For carrier densities
accessible in experiments, we obtained an anisotropy ratio of 3 ~ 4 at zero
temperature, two-folds larger than that observed in experiments on multilayers
samples. We discuss also how the anisotropy depends on carrier density and
impurity distribution.


  An $\infty$-step nilsystem is an inverse limit of minimal nilsystems. In this
article is shown that a minimal distal system is an $\infty$-step nilsystem if
and only if it has no nontrivial pairs with arbitrarily long finite
IP-independence sets. Moreover, it is proved that any minimal system without
nontrivial pairs with arbitrarily long finite IP-independence sets is an almost
one to one extension of its maximal $\infty$-step nilfactor, and each invariant
ergodic measure is isomorphic (in the measurable sense) to the Haar measure on
some $\infty$-step nilsystem. The question if such a system is uniquely ergodic
remains open. In addition, the topological complexity of an $\infty$-step
nilsystem is computed, showing that it is polynomial for each nontrivial open
cover.


  The energy losses at collisions of heavy multiplycharged ions with light
atoms have been considered under circumstances the ion charge Z>>1 and the
relative colliding velocity v>>1, so that Z~v=<c, where c - the light velocity
(atomic units are used). In this region of parameters the Born approximation
are not justificative. The simple formulas for effective stopping are obtained,
the comparison with effective stopping calculated in the Born approximation are
carried out.


  In a series of three papers we develop an end space theory for directed
graphs. As for undirected graphs, the ends of a digraph are points at infinity
to which its rays converge. Unlike for undirected graphs, some ends are joined
by limit edges; these are crucial for obtaining the end space of a digraph as a
natural (inverse) limit of its finite contraction minors. As our main result in
this first paper of our series we show that the notion of directions of an
undirected graph, a tangle-like description of its ends, extends to digraphs:
there is a one-to-one correspondence between the `directions' of a digraph and
its ends and limit edges. In the course of this we extend to digraphs a number
of fundamental tools and techniques for the study of ends of graphs, such as
the star-comb lemma and Schmidt's ranking of rayless graphs.


  The galactic central black hole Sgr A* exhibits outbursts of radiation in the
near infrared (so-called IR flares). One model of these events consists in a
hotspot orbiting on the innermost stable circular orbit (ISCO) of the hole.
These outbursts can be used as a probe of the central gravitational potential.
One main scientific goal of the second generation VLTI instrument GRAVITY is to
observe these flares astrometrically. Here, the astrometric precision of
GRAVITY is investigated in imaging mode, which consists in analysing the image
computed from the interferometric data. The capability of the instrument to put
in light the motion of a hotspot orbiting on the ISCO of our central black hole
is then discussed.
  We find that GRAVITY's astrometric precision for a single star in imaging
mode is smaller than the Schwarzschild radius of Sgr A*. The instrument can
also demonstrate that a body orbiting on the last stable orbit of the black
hole is indeed moving. It yields a typical size of the orbit, if the source is
as bright as m_K=14.
  These results show that GRAVITY allows one to study the close environment of
Sgr A*. Having access to the ISCO of the central massive black hole probably
allows constraining general relativity in its strong regime. Moreover, if the
hotspot model is appropriate, the black hole spin can be constrained.


  We derive a spectral representation for the oblate spheroidal wave operator
which is holomorphic in the aspherical parameter $\Omega$ in a neighborhood of
the real line. For real $\Omega$, estimates are derived for all eigenvalue gaps
uniformly in $\Omega$.
  The proof of the gap estimates is based on detailed estimates for complex
solutions of the Riccati equation. The spectral representation for complex
$\Omega$ is derived using the theory of slightly non-selfadjoint perturbations.


  The dual of a map is a fundamental construction on combinatorial maps, but
many other combinatorial objects also possess their notion of duality. For
instance, the Tamari lattice is isomorphic to its order dual, which induces an
involution on the set of so-called "synchronized intervals" introduced by
Pr\'eville-Ratelle and the present author. Another example is the class of
$\beta$-(1,0) trees, which has a mysterious involution $h$ proposed by
Claesson, Kitaev and Steingr\'imsson (2009). These two classes of combinatorial
objects are all in bijection with the class of non-separable planar maps, which
is closed by map duality. In this article, we show that we can identify the
notions of duality in these three classes of objects using previously known
natural bijections, which leads to a bijective proof of a result from Kitaev
and de Mier (2013). We also discuss how various statistics are transferred by
duality and by the bijections we used.


  We study the Hubbard model on the AB-stacked bilayer honeycomb lattice with a
repulsive onsite interaction U in second order perturbation theory and in
self-consistent random phase approximation. We determine the changes in the
antiferromagnetic magnetic ordering tendencies due to the real and imaginary
parts of the selfenergy at the band crossing points. In particular we present
an estimate for the threshold value U* below which the magnetic order is
endangered by the splitting of the quadratic band touching points into four
Dirac points by an interaction-induced interlayer skew hopping. For most of the
parameter space however, the quasiparticle degradation by the
frequency-dependence of the sublattice-diagonal selfenergies and the Dirac-cone
steepening are more essential for suppressing the AF ordering tendencies
considerably. Our results might help to understand to understand the energy
scales obtained in renormalization group treatments of the same model and shed
light on recent quantum Monte Carlo investigations about the fate of the
magnetic ordering down to lower U.


  A mathematical proof is given that Maxwell's equations are an {\it artifact}
of Hodge theory together with the laws of Gauss and Amp\`ere, taken as axioms.
They are thus geometric in nature, independent of any specific physical
mechanisms, and valid for any force field -- attractive or repulsive --
generated by a material density and current. In particular, with appropriate
sign changes to reflect the attractive nature of the field, they apply to
gravitational fields on Minkowski space-time as well.
  The linearization of the Einstein Field Equations on Minkowksi space-time
leads also to a linear theory of gravity; but this theory is spin 2, while
Maxwell's field theory is spin 1. Hence the two theories are distinct. The
relationship of Maxwell's field theory to Einstein's geometric theory is
explained for weak fields.


  Dijet production is studied in collisions of quasi-real photons radiated by
the LEP beams at e+e- centre-of-mass energies sqrt(s)_ee=161 and 172 GeV. Jets
are reconstructed using a cone jet finding algorithm in the range |eta(jet)|<2
and E_T(jet)>3 GeV. The angular distributions of direct and double-resolved
processes and the inclusive two-jet cross-section are measured. They are
compared to next-to-leading order perturbative QCD calculations and the
prediction of the leading order Monte Carlo generators PYTHIA and PHOJET.


  As suggested by some extensions of the Standard Model of particle physics,
dark matter may be a super-weakly interacting lightest stable particle, while
the next-to-lightest particle (NLP) is charged and meta-stable. One could test
such a possibility with neutrino telescopes, by detecting the charged NLPs
produced in high-energy neutrino collisions with Earth matter. We study the
production of charged NLPs by both atmospheric and astrophysical neutrinos;
only the latter, which is largely uncertain and has not been detected yet, was
the focus of previous studies. We compute the resulting fluxes of the charged
NLPs, compare those of different origins, and analyze the dependence on the
underlying particle physics setup. We point out that even if the astrophysical
neutrino flux is very small, atmospheric neutrinos, especially those from the
prompt decay of charmed mesons, may provide a detectable flux of NLP pairs at
neutrino telescopes such as IceCube. We also comment on the flux of charged
NLPs expected from proton-nucleon collisions, and show that, for theoretically
motivated and phenomenologically viable models, it is typically sub-dominant
and below detectable rates.


  In this paper we study the Hartree-Fock type system as follows:
\begin{equation*} \left\{ \begin{array}{ll} -\Delta u+V\left( x\right) u+\rho
\left( x\right) \phi _{\rho ,\left(u,v\right) }u=\left\vert u\right\vert
^{p-2}u+\beta \left\vert v\right\vert^{\frac{p}{2}}\left\vert u\right\vert
^{\frac{p}{2}-2}u & \text{ in }\mathbb{R}^{3}, \\ -\Delta v+V\left( x\right)
v+\rho \left( x\right) \phi _{\rho ,\left( u,v\right) }v=\left\vert
v\right\vert ^{p-2}v+\beta \left\vert u\right\vert ^{\frac{p}{2}}\left\vert
v\right\vert ^{\frac{p}{2}-2}v & \text{ in }\mathbb{R}^{3}, \end{array} \right.
\end{equation*} where $\phi _{\rho ,\left( u,v\right)
}=\int_{\mathbb{R}^{3}}\frac{\rho \left( y\right) \left( u^{2}(y)+v^{2}\left(
y\right) \right) }{|x-y|}dy,$ the potentials $V(x),\rho (x)$ are positive
continuous functions in $\mathbb{R}^{3},$ the parameter $\beta \in \mathbb{R}$
and $2<p<4$. Such system is viewed as an approximation of the Coulomb system
with two particles appeared in quantum mechanics, whose main characteristic is
the presence of the double coupled terms. When $2<p<3,$ under suitable
assumptions on potentials, we shed some light on the behavior of the
corresponding energy functional on $H^{1}(\mathbb{R}^{3})\times
H^{1}(\mathbb{R}^{3}),$ and prove the existence of a global minimizer with
negative energy. When $3\leq p<4,$ we find vectorial ground states by
developing a new analytic method and exploring the conditions on potentials.
Finally, we study the phenomenon of symmetry breaking of ground states when
$2<p<3.$


  We show that all PL manifolds of dimension $\geq 3$ have spines similar to
Bing's house with two rooms. Beyond this we explore approximation rigidity and
an $h$-principle.


  We consider the Hamiltonian theory for the multi-component KP hierarchy. We
show that the second Hamiltonian structures constructed by Sidorenko and
Strampp[J. Math. Phys. {\bf 34}, 1429(1993)] are not Hamiltonian. A candidate
for the second Hamiltonian Structures is proposed and is proved to lead to
hereditary operators.


  We provide a new framework for the joint analysis of cluster observations
(JACO) using simultaneous fits to X-ray, Sunyaev-Zel'dovich (SZ), and weak
lensing data. Our method fits the mass models simultaneously to all data,
provides explicit separation of the gaseous, dark, and stellar components,
and--for the first time--allows joint constraints on all measurable physical
parameters. JACO includes additional improvements to previous X-ray techniques,
such as the treatment of the cluster termination shock and explicit inclusion
of the BCG's stellar mass profile. An application of JACO to the rich galaxy
cluster Abell 478 shows excellent agreement among the X-ray, lensing, and SZ
data. We find that Abell 478 is consistent with a cuspy dark matter profile
with inner slope n=1. Accounting for the stellar mass profile of the BCG allows
us to rule out inner dark matter slopes n>1.1 at the 99% confidence level. At
large radii, an 1/r^3 asymptotic slope is preferred over an 1/r^4 behavior. All
single power law dark matter models are ruled out at greater than the 99%
confidence level. JACO shows that self-consistent modeling of multiwavelength
data can provide powerful constraints on the shape of the dark profile.


  We report the results of a study of the exclusive charmless semileptonic
B0->pilnu decay undertaken with approximately 227 million BBbar pairs collected
at the Upsilon(4S) resonance with the BABAR detector. The analysis uses events
in which the signal B mesons are reconstructed with a novel loose neutrino
reconstruction technique. We obtain partial branching fractions in 12 bins of
q2, the l+nu invariant mass squared, from which we extract the f+(q2) form
factor shape and the total branching fraction: BF(B0->pilnu) = (1.44 +-
0.08(stat) +- 0.10(syst))x 10-4. Based on a recent theoretical calculation of
the form factor, we find the magnitude of the CKM matrix element |Vub| to be
(4.1 +- 0.2(stat) +- 0.2(syst) +0.6-0.4(FF))x 10-3, where the last uncertainty
is due to the normalization of the form factor.


  Accurate uncertainty quantification of model predictions is a crucial problem
in machine learning. Existing Bayesian methods, being highly iterative, are
expensive to implement and often fail to accurately capture a model's true
posterior because of their tendency to select only central moments. We propose
a fast single-shot uncertainty quantification framework where, instead of
working with the conventional Bayesian definition of model weight probability
density function (PDF), we utilize physics inspired functional operators over
the projection of model weights in a reproducing kernel Hilbert space (RKHS) to
quantify their uncertainty at each model output. The RKHS projection of model
weights yields a potential field based interpretation of model weight PDF which
consequently allows the definition of a functional operator, inspired by
perturbation theory in physics, that performs a moment decomposition of the
model weight PDF (the potential field) at a specific model output to quantify
its uncertainty. We call this representation of the model weight PDF as the
quantum information potential field (QIPF) of the weights. The extracted
moments from this approach automatically decompose the weight PDF in the local
neighborhood of the specified model output and determine, with great
sensitivity, the local heterogeneity of the weight PDF around a given
prediction. These moments therefore provide sharper estimates of predictive
uncertainty than central stochastic moments of Bayesian methods. Experiments
evaluating the error detection capability of different uncertainty
quantification methods on covariate shifted test data show our approach to be
more precise and better calibrated than baseline methods, while being faster to
compute.


  We propose a novel interpretation of the collapsed variational Bayes
inference with a zero-order Taylor expansion approximation, called CVB0
inference, for latent Dirichlet allocation (LDA). We clarify the properties of
the CVB0 inference by using the alpha-divergence. We show that the CVB0
inference is composed of two different divergence projections: alpha=1 and -1.
This interpretation will help shed light on CVB0 works.


  We prove a duality formula between two elliptic determinants. We present a
proof which is a variant of the Izergin-Korepin method which is a method
originally introduced to analyze and compute partition functions of integrable
lattice models.


  By the nonstandard analysis theory of turbulence, the governing equations of
compressible turbulence are given. The equations can hold at non-uniform
points, in fact, are new kind of equations. There are three choices. In the
choice one, the second-order infinitesimal quantities are neglected, the closed
equations about the point(monad)-average quantities are obtained. In other two
choices, the closed equations, in which the third-order infinitesimal
quantities are omitted, are given and about the instantaneous, point-averaged
and fluctuant quantities.


  A standard assumption in the fitting of unordered multinomial response models
for $J$ mutually exclusive nominal categories, on cross-sectional or
longitudinal data, is that the responses arise from the same set of $J$
categories between subjects. However, when responses measure a choice made by
the subject, it is more appropriate to assume that the distribution of
multinomial responses is conditioned on a subject-specific consideration set,
where this consideration set is drawn from the power set of $\{1,2,\ldots,J\}$.
Because the cardinality of this power set is exponential in $J$, estimation is
infeasible in general. In this paper, we provide an approach to overcoming this
problem. A key step in the approach is a probability model over consideration
sets, based on a general representation of probability distributions on
contingency tables, which results in mixtures of independent consideration
models. Although the support of this distribution is exponentially large, the
posterior distribution over consideration sets given parameters is typically
sparse, and is easily sampled in an MCMC scheme. We show posterior consistency
of the parameters of the conditional response model and the distribution of
consideration sets. The effectiveness of the methodology is documented in
simulated longitudinal data sets with $J=100$ categories and real data from the
cereal market with $J=68$ brands.


  We report re-analyses of the Suzaku observations of the Galactic supernova
remnant (SNR), G272.2$-$3.2, for which the previous studies were limited below
3 keV. With careful data reduction and background subtraction, we discover the
K-shell lines of Ar, Ca, and Fe above 3 keV. The X-ray spectrum of G272.2$-$3.2
consists of two components, a low-temperature collisional ionization
equilibrium (CIE) plasma ($kT_{\rm e} \sim 0.2$ keV) and a high-temperature
non-equilibrium ionization (NEI) plasma ($kT_{\rm e} = 0.6$-$3$ keV). The CIE
plasma has solar abundances over the entire area, hence it would originate from
the interstellar medium. On the other hand, the abundances of the NEI plasma
increase toward the inner region, suggesting the ejecta origin. The line center
energy of the Fe K-shell emission ($\sim 6.4$ keV) suggests that the ejecta are
recently heated by the reverse shock, a common feature in Type Ia SNRs.


  We prove the existence and uniqueness of the fundamental solution for
Kolmogorov operators associated to some stochastic processes, that arise in the
Black & Scholes setting for the pricing problem relevant to path dependent
options. We improve previous results in that we provide a closed form
expression for the solution of the Cauchy problem under weak regularity
assumptions on the coefficients of the differential operator. Our method is
based on a limiting procedure, whose convergence relies on some barrier
arguments and uniform a priori estimates recently discovered.


  We consider a periodic system of domains coupled by small windows. In such
domain we study the band spectrum of a Schroedinger operator subject to Neumann
condition. We show that near each isolated eigenvalue of the similar operator
but in the periodicity cell, there are several non-intersecting bands of the
spectrum for the perturbed operator. We also discuss the position of the points
at which the band functions attain the edges of each band.


  Large format arrays of transition edge sensor (TES) are crucial for the next
generation of X-ray space observatories. Such arrays are required to achieve an
energy resolution of $\mathrm{\Delta}E<$3 eV full-width-half-maximum (FWHM) in
the soft X-ray energy range. We are currently developing X-ray microcalorimeter
arrays as a backup option for the X-IFU instrument on board of ATHENA space
telescope, led by ESA and foreseen to be launched in 2031. In this
contribution, we report on the development and the characterization of a
uniform 32$\times$32 pixel array with (length$\times $width) 140$\times$30
$\mu$m$^2$ TiAu TESs, which have \textcolor{black}{a 2.3 $\mu$m} thick Au
absorber for X-ray photons. The pixels have a typical normal resistance
$R_\mathrm{n}$ = 121 m$\Omega$ and a critical temperature $T_\mathrm{c}\sim$ 90
mK. We performed extensive measurements on 60 pixels out of the array in order
to show the uniformity of the array. We obtained an energy resolutions between
2.4 and 2.6 eV (FWHM) at 5.9 keV, measured in a single-pixel mode at AC bias
frequencies ranging from 1 to 5 MHz, with a frequency domain multiplexing (FDM)
readout system, which is developed at SRON/VTT. We also present the detector
energy resolution at X-ray with different photon energies generated by a
modulated external X-ray source from 1.45 keV up to 8.9 keV. Multiplexing
readout across several pixels has also been performed to evaluate the impact of
the thermal crosstalk to the instrument's energy resolution budget requirement.
This value results in a derived requirement, for the first neighbour, that is
less than 1$\times$10$^{-3}$ when considering the ratio between the amplitude
of the crosstalk signal to an X-ray pulse (for example at 5.9 keV)


  We present results for the strangeness contribution to the nucleon, <N|ss|N>,
and to the spin of the nucleon, Delta s. By combining several variance
reduction techniques for all-to-all propagators we are able to obtain gains in
terms of computer time of factors of 25-30 for the disconnected loop that is
needed within the calculation of Delta s, relative to the standard approach of
just employing time partitioning/dilution. For <N|ss|n>, the error is dominated
by the gauge noise.


  We introduce a method for generating realistic pedestrian trajectories and
full-body animations that can be controlled to meet user-defined goals. We draw
on recent advances in guided diffusion modeling to achieve test-time
controllability of trajectories, which is normally only associated with
rule-based systems. Our guided diffusion model allows users to constrain
trajectories through target waypoints, speed, and specified social groups while
accounting for the surrounding environment context. This trajectory diffusion
model is integrated with a novel physics-based humanoid controller to form a
closed-loop, full-body pedestrian animation system capable of placing large
crowds in a simulated environment with varying terrains. We further propose
utilizing the value function learned during RL training of the animation
controller to guide diffusion to produce trajectories better suited for
particular scenarios such as collision avoidance and traversing uneven terrain.
Video results are available on the project page at
https://nv-tlabs.github.io/trace-pace .


  We explore the nature of the quantum phase transition between a magnetically
ordered state with collinear spin pattern and a gapless $Z_2$ spin liquid in
the Heisenberg-Kitaev model. We construct a slave particle mean field theory
for the Heisenberg-Kitaev model in terms of complex fermionic spinons. It is
shown that this theory, formulated in the appropriate basis, is capable of
describing the Kitaev spin liquid as well as the transition between the gapless
$Z_2$ spin liquid and the so-called stripy antiferromagnet. In particular,
within a mean field theory, we have a discontinuous transition from the $Z_2$
spin liquid to the stripy antiferromagnet. We argue, however, that subtle
spinon confinement effects, associated with the instability of gapped U(1) spin
liquid in two spatial dimensions, are playing an important role at the
transition. The possibility of an exotic continuous transition is briefly
addressed.


  We discuss some topological constraints on Type IIB string theory that cannot
be described by elementary characteristic classes. Anomaly cancellation of the
worldvolume theory of a D3-brane requires a shifted Dirac quantization
condition of the Ramond-Ramond 5-form flux. However, the required shift is
sometimes inconsistent depending on the topology of spacetime backgrounds. The
obstruction to the existence of a shifted quantization is described by a
degree-6 cohomology class whose definition involves spin structure of spacetime
manifolds. The cohomology class is interpreted as a background D3-charge, and
the Gauss law constraint requires inclusion of additional D3-branes to cancel
it.


  We propose and study two second-order in time implicit-explicit (IMEX)
methods for the coupled Stokes-Darcy system that governs flows in karst
aquifers. The first is a combination of a second-order backward differentiation
formula and the second-order Gear's extrapolation approach. The second is a
combination of the second-order Adams-Moulton and second-order Adams-Bashforth
methods. Both algorithms only require the solution of two decoupled problems at
each time step, one Stokes and the other Darcy. Hence, these schemes are very
efficient and can be easily implemented using legacy codes. We establish the
unconditional and uniform in time stability for both schemes. The uniform in
time stability leads to uniform in time control of the error which is highly
desirable for modeling physical processes, e.g., contaminant sequestration and
release, that occur over very long time scales. Error estimates for
fully-discretized schemes using finite element spatial discretizations are
derived. Numerical examples are provided that illustrate the accuracy,
efficiency, and long-time stability of the two schemes.


  In this paper we present two parallel Monte Carlo based algorithms for
pricing multi--dimensional Bermudan/American options. First approach relies on
computation of the optimal exercise boundary while the second relies on
classification of continuation and exercise values. We also evaluate the
performance of both the algorithms in a desktop grid environment. We show the
effectiveness of the proposed approaches in a heterogeneous computing
environment, and identify scalability constraints due to the algorithmic
structure.


  The structure of finite-area topological defects in graphene is described in
terms of both the direct honeycomb lattice and its dual triangular lattice.
Such defects are equivalent to cutting out a patch of graphene and replacing it
with a different patch with the same number of dangling bonds. An important
subset of these defects, bound by a closed loop of alternating 5- and
7-membered carbon rings, explains most finite-area topological defects that
have been experimentally observed. Previously unidentified defects seen in
scanning tunneling microscope (STM) images of graphene grown on SiC are
identified as isolated divacancies or divacancy clusters.


  Coude spectroscopic data of a poorly-studied peculiar supergiant, HD327083,
are presented. Halpha and Hbeta line profiles have been fitted employing a
non-LTE code adequate for spherically expanding atmospheres. Line fits lead to
estimates of physical parameters. These parameters suggest that HD327083 may be
close to the Luminous Blue Variable phase but it is also possible that it could
be a B[e] Supergiant.


  We introduce an innovative wavelet-based approach to dynamically adjust the
local grid resolution to maintain a uniform specified error tolerance.
Extending the work of Dubos and Kevlahan (2013), a wavelet multi-scale
approximation is used to make dynamically adaptive the TRiSK model (Ringler et
al. 2010) for the rotating shallow water equations on the sphere. This paper
focuses on the challenges encountered when extending the adaptive wavelet
method to the sphere and ensuring an efficient parallel implementation using
MPI. The wavelet method is implemented in Fortran95 with an emphasis on
computational efficiency and scales well up to O(10^2) processors for
load-unbalanced scenarios and up to at least O(10^3) processors for
load-balanced scenarios. The method is verified using standard smooth test
cases (Williamson et al. 1992) and a nonlinear test case proposed by (Galewsky
te al. 2004). The dynamical grid adaption provides compression ratios of up to
50 times in a challenging homogenous turbulence test case. The adaptive code is
about three times slower per active grid point than the equivalent non-adaptive
TRiSK code and about four times slower per active grid point than an equivalent
spectral code. This computationally efficient adaptive dynamical core could
serve as the foundation on which to build a complete climate or weather model.


  We give a classification of the cuspidal automorphic representations attached
to rational elliptic curves with a non-trivial torsion point of odd order. Such
elliptic curves are parameterizable, and in this paper, we find the necessary
and sufficient conditions on the parameters to determine when split or
non-split multiplicative reduction occurs. Using this and the known results on
when additive reduction occurs for these parametrized curves, we classify the
automorphic representations in terms of the parameters.


  We have made an 8.7 GHz image of a sky region with a resolution of 8 arcmin
and high brightness sensitivity using the Australia Telescope Compact Array
(ATCA). in an ultra compact configuration. The foreground discrete-source
confusion was estimated from observations with higher resolution at the same
frequency and in a scaled array at a lower frequency. Following the subtraction
of the foreground confusion, the field shows no features in excess of the
instrument noise. This limits the CMB anisotropy flat-band power to Q_flat <
23.6 microK with 95 per cent confidence; the ATCA filter function F_l in
multipole l-space peaks at l_eff = 4700 and has half maximum values at l = 3350
and 6050.


  Lynx is the next-generation observatory which will provide unprecedented
X-ray vision into the otherwise invisible Universe to gain understanding of
origins and physics of the cosmos. Lynx will see the dawn of black holes,
reveal what drives galaxy formation and evolution, and unveil the energetic
side of stellar evolution and stellar ecosystems. Lynx science payload will
enables radical advances and leaps in capability over NASA's existing flagship
Chandra and the ESA's planned Athena mission: 100-fold increase in sensitivity
via coupling superb angular resolution with high throughput; 16 times larger
field of view (FOV) for sub-arcsecond imaging; and 10-20 times higher spectral
resolution for both point-like and extended sources. The Lynx Design Reference
Mission has been designed to meet the science objectives of the future while
capitalizing where appropriate on decades of experience, and especially from
efficient, flight-proven approaches, design choices, and mission operations
software and procedures developed for Chandra. While the science program
outlined for Lynx in this report is already very broad, the observatory is
designed such that there will be ample resources to execute many other
programs, even those not anticipated today. Virtually all astronomers will be
able to use Lynx for their own particular science.


  An embedding method for solving the time-dependent Schr\"odinger equation is
developed using the Dirac-Frenkel variational principle. Embedding allows the
time-evolution of the wavefunction to be calculated explicitly in a limited
region of space, the region of physical interest, the embedding potential
ensuring that the wavefunction satisfies the correct boundary conditions for
matching on to the rest of the system. This is applied to a study of the
excitation of electrons at a metal surface, represented by a one-dimensional
model potential for Cu(111). Time-dependent embedding potentials are derived
for replacing the bulk substrate, and the image potential and vacuum region
outside the surface, so that the calculation of electron excitation by a
surface perturbation can be restricted to the surface itself. The excitation of
the Shockley surface state and a continuum bulk state is studied, and the
time-structure of the resulting currents analysed. Non-linear effects and the
time taken for the current to arrive outside the surface are discussed. The
method shows a clear distinction between emission from the localized surface
state, where the charge is steadily depleted, and the extended continuum state
where the current emitted into the vacuum is compensated by current approaching
the surface from the bulk.


  Atomic force microscopy (AFM) can be used to characterise several aspects of
the surface degradation and reinforcement mechanisms of zirconia based
ceramics, such as crack propagation, martensitic relief formation, grains
pull-out and transformation toughening. AFM can also be used to quantify
precisely the transformation and provide reliable parameters for long term
degradation prediction. In particular, the tetragonal to monoclinic (t-m) phase
transformation of zirconia has been the object of extensive investigations of
the last twenty years, and is now recognised as being of martensitic nature.
New strong evidences supporting the martensitic nature of the transformation
are reported here. These observations, considering their scale and precision,
are a new step toward the understanding of the t-m phase transformation of
zirconia and related degradation mechanisms.


  We present a deterministic incremental algorithm for \textit{exactly}
maintaining the size of a minimum cut with $\widetilde{O}(1)$ amortized time
per edge insertion and $O(1)$ query time. This result partially answers an open
question posed by Thorup [Combinatorica 2007]. It also stays in sharp contrast
to a polynomial conditional lower-bound for the fully-dynamic weighted minimum
cut problem. Our algorithm is obtained by combining a recent sparsification
technique of Kawarabayashi and Thorup [STOC 2015] and an exact incremental
algorithm of Henzinger [J. of Algorithm 1997]. We also study space-efficient
incremental algorithms for the minimum cut problem. Concretely, we show that
there exists an ${O}(n\log n/\varepsilon^2)$ space Monte-Carlo algorithm that
can process a stream of edge insertions starting from an empty graph, and with
high probability, the algorithm maintains a $(1+\varepsilon)$-approximation to
the minimum cut. The algorithm has $\widetilde{O}(1)$ amortized update-time and
constant query-time.


  Building equitable and inclusive NLP technologies demands consideration of
whether and how social attitudes are represented in ML models. In particular,
representations encoded in models often inadvertently perpetuate undesirable
social biases from the data on which they are trained. In this paper, we
present evidence of such undesirable biases towards mentions of disability in
two different English language models: toxicity prediction and sentiment
analysis. Next, we demonstrate that the neural embeddings that are the critical
first step in most NLP pipelines similarly contain undesirable biases towards
mentions of disability. We end by highlighting topical biases in the discourse
about disability which may contribute to the observed model biases; for
instance, gun violence, homelessness, and drug addiction are over-represented
in texts discussing mental illness.


  If the $X(3872)$ is described by the picture as a mixture of the charmonium
and molecular $D^{\ast} D$ states; $Y(3940)$ as a mixture of the $\chi_{c0}$
and $D^\ast D^\ast$ states; and $X(4260)$ as a mixture of the tetra-quark and
charmonium sates, their orthogonal combinations should also exist. We estimate
the mass and residues of the states within the QCD sum rules method. We find
that the mass splitting among $X$, $Y$ and their orthogonal states is at most
$200MeV$. Experimental search of these new states can play critical role for
establishing the nature of the new charmonium states.


  The paper investigates the Tsallis holographic dark energy (THDE) model in
accordance with the apparent horizon as an infrared cut-off, in a non-flat
universe. The cosmological evolution of the deceleration parameter and equation
of state of THDE model are calculated. The evolutionary trajectories are
plotted for the THDE model for distinct values of the Tsallis parameter
$\delta$ besides distinct spatial curvature contributions, in the statefinder
$(r, s)$ parameter-pairs and $\omega_{D}-\omega^{'}_{D}$ plane, considering the
present value of dark energy density parameter $\Omega_{D0} $,
$\Omega_{D0}=0.72$, in the light of $WMAP + eCMB + BAO + H_{0}$ observational
data. The statefinder and $\omega_{D}-\omega^{'}_{D}$ plane plots specify the
feature of the THDE and demonstrate the separation between this framework and
other models of dark energy.


  In this article we introduce the notion of badly approximable matrices of
higher order using higher sucessive minima in $\mathbb R^d$. We prove that for
order less than $d$, they have Lebesgue measure zero and the gaps between them
still have full Hausdorff dimension.


  Chen and Risen pointed out a logical flaw affecting the conclusions of a
number of past experiments that used the free-choice paradigm to measure
choice-induced attitude change. They went on to design and implement a
free-choice experiment that used a novel type of control group in order to
avoid this logical pitfall. In this paper, we describe a method by which a
free-choice experiment can be correctly conducted even without a control group.


  We have conducted long-slit spectroscopic observations and analyzed archival
radio data for the ultraluminous X-ray source (ULX) NGC 4861 X-1. Our spectral
line analysis unveils that NGC 4861 X-1 is the fourth ULX situated within an
X-ray photoionized nebula, following three previous findings made approximately
two decades ago. Remarkably, we discover NGC 4861 X-1 also possesses a radio
nebula emitting optically thin synchrotron radiation, which contradicts its
X-ray photoionization and raises doubts about the four ULXs being a mere
coincidence. Instead of gradually accumulating from different bands bit by bit,
our multi-band discovery is made all at once. Moreover, we tentatively perceive
a faint continuum spectrum of the optical nebula. Further observations are
needed to ascertain its radio structures and verify the optical continuum.


  Universal source coding at short blocklengths is considered for an
exponential family of distributions. The \emph{Type Size} code has previously
been shown to be optimal up to the third-order rate for universal compression
of all memoryless sources over finite alphabets. The Type Size code assigns
sequences ordered based on their type class sizes to binary strings ordered
lexicographically. To generalize this type class approach for parametric
sources, a natural scheme is to define two sequences to be in the same type
class if and only if they are equiprobable under any model in the parametric
class. This natural approach, however, is shown to be suboptimal. A variation
of the Type Size code is introduced, where type classes are defined based on
neighborhoods of minimal sufficient statistics. Asymptotics of the overflow
rate of this variation are derived and a converse result establishes its
optimality up to the third-order term. These results are derived for parametric
families of $i.i.d.$ sources as well as Markov sources.


  In this paper the q-deformed $W$ algebra $\WW_q$ is constructed, whose
nontrivial quantum group structure is presented.


  We compute the Renormalization Group functions of a Landau-Ginzburg-Wilson
Hamiltonian with O(n)x O(m) symmetry up to five-loop in Minimal Subtraction
scheme. The line n^+(m,d), which limits the region of second-order phase
transition, is reconstructed in the framework of the epsilon=4-d expansion for
generic values of $m$ up to O(epsilon^5). For the physically interesting case
of noncollinear but planar orderings (m=2) we obtain n^+(2,3)=6.1(6) by
exploiting different resummation procedures. We substantiate this results
re-analyzing six-loop fixed dimension series with pseudo-epsilon expansion,
obtaining n^+(2,3)=6.22(12). We also provide predictions for the critical
exponents characterizing the second-order phase transition occurring for n>n^+.


  The CDF and D0 experiments probe the high-energy frontier and as they do so
have accumulated hundreds of Terabytes of data on the way to petabytes of data
over the next two years. The experiments have made a commitment to use the
developing Grid based on the SAM system to handle these data. The D0 SAM has
been extended for use in CDF as common patterns of design emerged to meet the
similar requirements of these experiments. The process by which the merger was
achieved is explained with particular emphasis on lessons learned concerning
the database design patterns plus realization of the use cases.


  Researchers in psychology characterize decision-making as a process of
eliminating options. While statistical modelling typically focuses on the
eventual choice, we analyze consideration sets describing, for each survey
participant, all options between which the respondent is pondering. Using a
German pre-election poll as a prototypical example, we give a proof of concept
that consideration set sampling is easy to implement and provides the basis for
an insightful structural analysis of the respondents' positions. The set-valued
observations forming the consideration sets are naturally modelled as random
sets, allowing to transfer regression modelling as


  In the present paper, we consider a rotating black hole moving in a
homogeneous massless scalar field. We assume that the field is weak and neglect
its backreaction, so that the metric at far distance from the black hole is
practically flat. In this domain one can introduce two reference frames, $K$
and $\tilde{K}$. The frame $\tilde{K}$ is associated with the homogeneous
scalar field, in which its constant gradient has only time component. The other
frame, $K$, is the frame in which the black hole is at rest. To describe the
Kerr metric of the black hole we use its Kerr-Schild form
$g_{\mu\nu}=\eta_{\mu\nu}+\Phi l_{\mu}l_{\mu}$, where $\eta_{\mu\nu}$ is the
(asymptotic) flat metric in $K$ frame. We find an explicit solution of the
scalar field equation which is regular at the horizon and properly reproduce
the asymptotic form of the scalar field at the infinity. Using this solution we
calculate the fluxes of the energy, momentum and the angular momentum of the
scalar field into the black hole. This allows us to derive the equation of
motion of the rotating black hole. We discuss main general properties of
solutions of these equations and obtain explicit solutions for special type of
the motion of the black hole.


  Nationality identification unlocks important demographic information, with
many applications in biomedical and sociological research. Existing name-based
nationality classifiers use name substrings as features and are trained on
small, unrepresentative sets of labeled names, typically extracted from
Wikipedia. As a result, these methods achieve limited performance and cannot
support fine-grained classification.
  We exploit the phenomena of homophily in communication patterns to learn name
embeddings, a new representation that encodes gender, ethnicity, and
nationality which is readily applicable to building classifiers and other
systems. Through our analysis of 57M contact lists from a major Internet
company, we are able to design a fine-grained nationality classifier covering
39 groups representing over 90% of the world population. In an evaluation
against other published systems over 13 common classes, our F1 score (0.795) is
substantial better than our closest competitor Ethnea (0.580). To the best of
our knowledge, this is the most accurate, fine-grained nationality classifier
available.
  As a social media application, we apply our classifiers to the followers of
major Twitter celebrities over six different domains. We demonstrate stark
differences in the ethnicities of the followers of Trump and Obama, and in the
sports and entertainments favored by different groups. Finally, we identify an
anomalous political figure whose presumably inflated following appears largely
incapable of reading the language he posts in.


  The immune system recognizes a myriad of invading pathogens and their toxic
products. It does so with a finite repertoire of antibodies and T cell
receptors. We here describe theories that quantify the immune system dynamics.
We describe how the immune system recognizes antigens by searching the large
space of receptor molecules. We consider in some detail the theories that
quantify the immune response to influenza and dengue fever. We review
theoretical descriptions of the complementary evolution of pathogens that
occurs in response to immune system pressure. Methods including bioinformatics,
molecular simulation, random energy models, and quantum field theory contribute
to a theoretical understanding of aspects of immunity.


  In the previous paper [arXiv:0911.0679], we showed that the
Reissner-Nordstrom black hole in the 5-dimensional anti-de Sitter space coupled
to the Maxwell theory with the Chern-Simons term is unstable when the
Chern-Simons coupling is sufficiently large. In the dual conformal field
theory, the instability suggests a spatially modulated phase transition. In
this paper, we construct and analyze non-linear solutions which describe the
end-point of this phase transition. In the limit where the Chern-Simons
coupling is large, we find that the phase transition is of the second order
with the mean field critical exponent. However, the dispersion relation with
the Van Hove singularity enhances quantum corrections in the bulk, and we argue
that this changes the order of the phase transition from the second to the
first. We compute linear response functions in the non-linear solution and find
an infinite off-diagonal DC conductivity in the new phase.


  Ferroelectric materials contain a switchable spontaneous polarization that
persists even in the absence of an external electric field. The coexistence of
ferroelectricity and metallicity in a material appears to be illusive, since
polarization is ill-defined in metals, where the itinerant electrons are
expected to screen the long-range dipole interactions necessary for dipole
ordering. The surprising discovery of the polar metal, LiOsO3 has generated
interest in searching for new polar metals motivated by the prospects of exotic
quantum phenomena such as unconventional pairing mechanisms giving rise to
superconductivity, topological spin currents, anisotropic upper critical
fields, and Mott multiferroics. Previous studies have suggested that the
coordination preferences of the Li atom play a key role in stabilizing the
polar metal phase of LiOsO3, but a thorough understanding of how polar order
and metallicity can coexist remains elusive. Here, we use XUV-SHG as novel
technique to directly probe the broken inversion-symmetry around the Li atom.
Our results agree with previous theories that the primary structural distortion
that gives rise to the polar metal phase in LiOsO3 is a consequence of a
sub-Angstrom Li atom displacement along the polar axis. A remarkable agreement
between our experimental results and ab initio calculations provide physical
insights for connecting the nonlinear response to unit-cell spatial
asymmetries. It is shown that XUV-SHG can selectively probe inversion-breaking
symmetry in a bulk material with elemental specificity. Compared to optical SHG
methods, XUV-SHG fills a key gap for studying structural asymmetries when the
structural distortion is energetically separated from the Fermi surface.
Further, these results pave the way for time-resolved probing of
symmetry-breaking structural phase transitions on femtosecond timescales with
element specificity.


  Near-field radiative heat transfer (NFRHT) between rough surfaces, due to its
widespread presence in engineering practice of near-field energy utilization,
requires indepth studies, especially from the perspective of physical
mechanism. In this paper, an effective multilayer model is built to approach
the NFRHT between random rough surfaces of silicon carbide (SiC). Using the
effective medium theory (EMT), the effective dielectric function of each layer
is obtained, which forms a gradient distribution of dielectric function along
the depth of the medium. The influence of the effective dielectric function on
surface phonon polaritons (SPhPs) is analyzed, showing that the effective
layers with small filling fraction of SiC feature lower SPhP resonance
frequencies than SiC bulk. The coupling of SPhPs from the gradient distribution
of dielectric function produces new surface modes that dominates the NFRHT.
Investigation on the effect of root mean square height (RMS height, {\sigma})
reveals that the peaks of local density of states (LDOS) and spectral heat flux
are red-shifted as {\sigma} increases, while the spectral heat flux below the
peak frequency gets larger. This can be attributed to the coupling of SPhPs
inside the rough layer. We also found the total net heat flux between rough
surfaces separated by an average distance exceeds that between smooth plates
and increases with increasing {\sigma}, which offer a new way to enhance NFRHT.
This work provides a reference for the simulation and understanding of the
NFRHT between rough surfaces.


  We quantify the impact that a variety of galactic and environmental
properties have on the quenching of star formation. We collate a sample of
$\sim$ 400,000 central and $\sim$ 100,000 satellite galaxies from the Sloan
Digital Sky Survey Data Release 7 (SDSS DR7). Specifically, we consider central
velocity dispersion ($\sigma_{c}$), stellar, halo, bulge and disk mass, local
density, bulge-to-total ratio, group-centric distance and galaxy-halo mass
ratio. We develop and apply a new statistical technique to quantify the impact
on the quenched fraction ($f_{\rm Quench}$) of varying one parameter, while
keeping the remaining parameters fixed. For centrals, we find that the $f_{\rm
Quench} - \sigma_{c}$ relationship is tighter and steeper than for any other
variable considered. We compare to the Illustris hydrodynamical simulation and
the Munich semi-analytic model (L-Galaxies), finding that our results for
centrals are qualitatively consistent with their predictions for quenching via
radio-mode AGN feedback, hinting at the viability of this process in explaining
our observational trends. However, we also find evidence that quenching in
L-Galaxies is too efficient and quenching in Illustris is not efficient enough,
compared to observations. For satellites, we find strong evidence that
environment affects their quenched fraction at fixed central velocity
dispersion, particularly at lower masses. At higher masses, satellites behave
identically to centrals in their quenching. Of the environmental parameters
considered, local density affects the quenched fraction of satellites the most
at fixed central velocity dispersion.


  Decentralized policy optimization has been commonly used in cooperative
multi-agent tasks. However, since all agents are updating their policies
simultaneously, from the perspective of individual agents, the environment is
non-stationary, resulting in it being hard to guarantee monotonic policy
improvement. To help the policy improvement be stable and monotonic, we propose
model-based decentralized policy optimization (MDPO), which incorporates a
latent variable function to help construct the transition and reward function
from an individual perspective. We theoretically analyze that the policy
optimization of MDPO is more stable than model-free decentralized policy
optimization. Moreover, due to non-stationarity, the latent variable function
is varying and hard to be modeled. We further propose a latent variable
prediction method to reduce the error of the latent variable function, which
theoretically contributes to the monotonic policy improvement. Empirically,
MDPO can indeed obtain superior performance than model-free decentralized
policy optimization in a variety of cooperative multi-agent tasks.


  In this article, we consider the set of points for the holding of the
equality in a weighted version of Suita conjecture for higher derivatives, and
give relations between the set and the integer valued points of a class of
harmonic functions (maybe multi-valued). For planar domains bounded by finite
analytic closed curves, we give relations between the set and Dirichlet
problem.


  We study "the Caged Anisotropic Harmonic Oscillator", which is a new example
of a superintegrable, or accidentally degenerate Hamiltonian. The potential is
that of the harmonic oscillator with rational frequency ratio (l:m:n), but
additionally with barrier terms describing repulsive forces from the principal
planes. This confines the classical motion to a sector bounded by the principal
planes, or cage. In 3 degrees, there are five isolating integrals of motion,
ensuring that all bound trajectories are closed and strictly periodic. Three of
the integrals are quadratic in the momenta, the remaining two are polynomials
of order 2(l+m-1) and 2(l+n-1). In the quantum problem, the eigenstates are
multiply degenerate, exhibiting multiple copies of the fundamental pattern of
the symmetry group SU(3).


  Achieving control over light-matter interaction in custom-tailored
nanostructures is at the core of modern quantum electrodynamics [1-15]. In
ultrastrongly coupled systems [5-15], excitation is repeatedly exchanged
between a resonator and an electronic transition at a rate known as the vacuum
Rabi frequency $\Omega_R$. For $\Omega_R$ approaching the resonance frequency
$\omega_c$, novel quantum phenomena including squeezed states [16], Dicke
superradiant phase transitions [17,18], the collapse of the Purcell effect
[19], and a population of the ground state with virtual photon pairs [16,20]
are predicted. Yet, the experimental realization of optical systems with
$\Omega_R$/$\omega_c$ has remained elusive. Here, we introduce a paradigm
change in the design of light-matter coupling by treating the electronic and
the photonic components of the system as an entity instead of optimizing them
separately. Using the electronic excitation to not only boost the oscillator
strength but furthermore tailor the shape of the vacuum mode, we push
$\Omega_R$/$\omega_c$ of cyclotron resonances ultrastrongly coupled to
metamaterials far beyond unity. As one prominent illustration of the unfolding
possibilities, we calculate a ground state population of 0.37 virtual photons
for our best structure with $\Omega_R$/$\omega_c$ = 1.43, and suggest a
realistic experimental scenario for measuring vacuum radiation by cutting-edge
terahertz quantum detection [21,22].


  We revisit one of the classic problems in the data stream literature, namely,
that of estimating the frequency moments $F_p$ for $0 < p < 2$ of an underlying
$n$-dimensional vector presented as a sequence of additive updates in a stream.
It is well-known that using $p$-stable distributions one can approximate any of
these moments up to a multiplicative $(1+\epsilon)$-factor using
$O(\epsilon^{-2} \log n)$ bits of space, and this space bound is optimal up to
a constant factor in the turnstile streaming model. We show that surprisingly,
if one instead considers the popular random-order model of insertion-only
streams, in which the updates to the underlying vector arrive in a random
order, then one can beat this space bound and achieve $\tilde{O}(\epsilon^{-2}
+ \log n)$ bits of space, where the $\tilde{O}$ hides poly$(\log(1/\epsilon) +
\log \log n)$ factors. If $\epsilon^{-2} \approx \log n$, this represents a
roughly quadratic improvement in the space achievable in turnstile streams. Our
algorithm is in fact deterministic, and we show our space bound is optimal up
to poly$(\log(1/\epsilon) + \log \log n)$ factors for deterministic algorithms
in the random order model. We also obtain a similar improvement in space for $p
= 2$ whenever $F_2 \gtrsim \log n\cdot F_1$.


  We present a detailed multi-wavelength characterization of the multi-ring
disk of HD 169142. We report new ALMA observations at 3 mm and analyze them
together with archival 0.89 and 1.3 mm data. Our observations resolve three out
of the four rings in the disk previously seen in high-resolution ALMA data. A
simple parametric model is used to estimate the radial profile of the dust
optical depth, temperature, density, and particle size distribution. We find
that the multiple ring features of the disk are produced by annular
accumulations of large particles, probably associated with gas pressure bumps.
Our model indicates that the maximum dust grain size in the rings is $\sim1$
cm, with slightly flatter power-law size distributions than the ISM-like size
distribution ($p\sim3.5$) found in the gaps. In particular, the inner ring
($\sim26$ au) is associated with a strong and narrow buildup of dust particles
that could harbor the necessary conditions to trigger the streaming
instability. According to our analysis, the snowlines of the most important
volatiles do not coincide with the observed substructures. We explore different
ring formation mechanisms and find that planet-disk interactions are the most
likely scenario to explain the main features of HD 169142. Overall, our
multi-wavelength analysis provides some of the first unambiguous evidence of
the presence of radial dust traps in the rings of HD 169142. A similar analysis
in a larger sample of disks could provide key insights on the impact that disk
substructures have on the dust evolution and planet formation processes.


A characterization of real numbers constructible by paper folding.