  We present an X-ray spectroscopic study of the nuclear region of the M31
bulge, based on observations of the Xmm-Newton Reflection Grating
Spectrometers. The obtained high-resolution grating spectra clearly show
individual emission lines of highly-ionized iron and oxygen, which
unambiguously confirm the presence of diffuse hot gas in the bulge, as
indicated from previous X-ray CCD imaging studies. We model the spectra with
detailed Monte-Carlo simulations, which provide a robust spectroscopic estimate
of the hot gas temperature $\sim0.29$ keV and the O/Fe ratio $\sim0.3$ solar.
The results indicate that iron ejecta of type Ia supernovae are partly-mixed
with the hot gas. The observed spectra show an intensity excess at the OVII
triplet, which most likely represents emission from charge exchanges at the
interface between the hot gas and a known cool gas spiral in the same nuclear
region.


  This paper will cover several studies and design changes that will eventually
be implemented to the Fermi National Accelerator Laboratory (FNAL) magnetron
ion source. The topics include tungsten cathode insert, solenoid gas valves,
current controlled arc pulser, cesium boiler redesign, gas mixtures of hydrogen
and nitrogen, and duty factor reduction. The studies were performed on the FNAL
test stand, with the aim to improve source lifetime, stability, and reducing
the amount of tuning needed.


  Federated learning, a distributed learning paradigm, utilizes multiple
clients to build a robust global model. In real-world applications, local
clients often operate within their limited domains, leading to a `domain shift'
across clients. Privacy concerns limit each client's learning to its own domain
data, which increase the risk of overfitting. Moreover, the process of
aggregating models trained on own limited domain can be potentially lead to a
significant degradation in the global model performance. To deal with these
challenges, we introduce the concept of federated feature diversification. Each
client diversifies the own limited domain data by leveraging global feature
statistics, i.e., the aggregated average statistics over all participating
clients, shared through the global model's parameters. This data
diversification helps local models to learn client-invariant representations
while preserving privacy. Our resultant global model shows robust performance
on unseen test domain data. To enhance performance further, we develop an
instance-adaptive inference approach tailored for test domain data. Our
proposed instance feature adapter dynamically adjusts feature statistics to
align with the test input, thereby reducing the domain gap between the test and
training domains. We show that our method achieves state-of-the-art performance
on several domain generalization benchmarks within a federated learning
setting.


  In this paper we propose a new kind of high order numerical scheme for
backward stochastic differential equations(BSDEs). Unlike the traditional
$\theta$-scheme, we reduce truncation errors by taking $\theta$ carefully for
every subinterval according to the characteristics of integrands. We give error
estimates of this nonlinear scheme and verify the order of scheme through a
typical numerical experiment.


  Ultracold polar molecules, with their long-range electric dipolar
interactions, offer a unique platform for studying correlated quantum many-body
phenomena such as quantum magnetism. However, realizing a highly degenerate
quantum gas of molecules with a low entropy per particle has been an
outstanding experimental challenge. In this paper, we report the synthesis of a
low entropy molecular quantum gas by creating molecules at individual sites of
a three-dimensional optical lattice that is initially loaded from a low entropy
mixture of K and Rb quantum gases. We make use of the quantum statistics and
interactions of the initial atom gases to load into the optical lattice,
simultaneously and with good spatial overlap, a Mott insulator of bosonic Rb
atoms and a single-band insulator of fermionic K atoms. Then, using
magneto-association and optical state transfer, we efficiently produce
ground-state molecules in the lattice at those sites that contained one Rb and
one K atom. The achieved filling fraction of 25% indicates an entropy as low as
$2.2\,k_B$ per molecule. This low-entropy molecular quantum gas opens the door
to novel studies of transport and entanglement propagation in a many-body
system with long-range dipolar interactions.


  The classical (overdamped) Langevin dynamics provide a natural algorithm for
sampling from its invariant measure, which uniquely minimizes an energy
functional over the space of probability measures, and which concentrates
around the minimizer(s) of the associated potential when the noise parameter is
small. We introduce analogous diffusion dynamics that sample from an
entropy-regularized optimal transport, which uniquely minimizes the same energy
functional but constrained to the set $\Pi(\mu,\nu)$ of couplings of two given
marginal probability measures $\mu$ and $\nu$ on $\mathbb{R}^d$, and which
concentrates around the optimal transport coupling(s) for small regularization
parameter. More specifically, our process satisfies two key properties: First,
the law of the solution at each time stays in $\Pi(\mu,\nu)$ if it is
initialized there. Second, the long-time limit is the unique solution of an
entropic optimal transport problem. In addition, we show by means of a new
log-Sobolev-type inequality that the convergence holds exponentially fast, for
sufficiently large regularization parameter and for a class of marginals which
strictly includes all strongly log-concave measures. By studying the induced
Wasserstein geometry of the submanifold $\Pi(\mu,\nu)$, we argue that the SDE
can be viewed as a Wasserstein gradient flow on this space of couplings, at
least when $d=1$, and we identify a conjectural gradient flow for $d \ge 2$.
The main technical difficulties stems from the appearance of conditional
expectation terms which serve to constrain the dynamics to $\Pi(\mu,\nu)$.


  In this paper, we consider a L\'evy-driven fluid queueing system where the
server may subject to breakdowns and repairs. In addition, the server will
leave for a vacation each time when he finds an empty system. We cast the
queueing process as a L\'evy process modified to have random jumps at two
classes of stopping times. By using the Kella-Whitt martingale method, we
obtain the limiting distribution of the virtual waiting time process. Moreover,
we investigate the busy period, the correlation structure and the stochastic
decomposition properties. These results may be generalized to L\'evy processes
with multi-class jump inputs or L\'evy-driven queues with multiple input
classes.


  Based on the classical Langevin equation, we have re-visited the problem of
orbital motion of a charged particle in two dimensions for a normal magnetic
field crossed with or without an in-plane electric bias. We are led to two
interesting fluctuation effects: First, we obtain not only a longitudinal
"work-fluctuation" relation as expected for a barotropic type system, but also
a transverse work-fluctuation relation perpendicular to the electric bias. This
"Hall fluctuation" involves the product of the electric and the magnetic
fields. And second, for the case of harmonic confinement without bias, the
calculated probability density for the orbital magnetic moment gives non-zero
even moments, not derivable as field derivatives of the classical free energy.


  Lorentz invariance is broken for the non-Abelian monopoles. Here we will
consider the case of 't Hooft-Polyakov monopole and show that the Lorentz
invariance of its field will be restored using Dirac quantization.


  This study critically reevaluates the Harlow-Hayden (HH) solution to the
black hole information paradox and its articulation in the firewall paradox.
The exploration recognizes the HH solution as a revolutionary approach in black
hole physics, steering away from traditional constraints to depict the event
horizon as a computational rather than a physical barrier. The paper first maps
the initial physical dilemma that instigated the HH journey, introducing Alice,
an observer facing intricate computational challenges as she approaches the
black hole. I then depict the evolution of the narrative, describing how Alice
was facilitated with a quantum computer to surmount the computational
challenges and further detailing the augmented complexities arising from the
integration of the physical dynamics of the black hole. Yet, HH's research
applies the AdS/CFT correspondence to explore the dynamic unitary
transformation in solving the firewall paradox through decoding Hawking
radiation. However, it identifies a contradiction; the eternal perspective of
black holes from the AdS/CFT theory challenges the firewall paradox's
foundation. Finally, I narrate a paradigm shift as HH reframes Alice's task
within the realms of error-correcting codes, illustrating a remarkable
transition from a physical problem in black hole physics to a computational
predicament in computer science. The study revisits pivotal moments in
understanding black hole physics ten years later through this reexamination.


  The Refined Gribov-Zwanziger framework takes into account the existence of
equivalent gauge field configurations in the gauge-fixing quantization
procedure of Euclidean Yang-Mills theories. Recently, this setup was extended
to the family of linear covariant gauges giving rise to a local and
BRST-invariant action. In this paper, we give an algebraic proof of the
renormalizability of the resulting action to all orders in perturbation theory.


  As software systems grow in complexity, the space of possible configurations
grows exponentially. Within this increasing complexity, developers,
maintainers, and users cannot keep track of the interactions between all the
various configuration options. Finding the optimally performing configuration
of a software system for a given setting is challenging. Recent approaches
address this challenge by learning performance models based on a sample set of
configurations. However, collecting enough data on enough sample configurations
can be very expensive since each such sample requires configuring, compiling
and executing the entire system against a complex test suite. The central
insight of this paper is that choosing a suitable source (a.k.a. "bellwether")
to learn from, plus a simple transfer learning scheme will often outperform
much more complex transfer learning methods. Using this insight, this paper
proposes BEETLE, a novel bellwether based transfer learning scheme, which can
identify a suitable source and use it to find near-optimal configurations of a
software system. BEETLE significantly reduces the cost (in terms of the number
of measurements of sample configuration) to build performance models. We
evaluate our approach with 61 scenarios based on 5 software systems and
demonstrate that BEETLE is beneficial in all cases. This approach offers a new
highwater mark in configuring software systems. Specifically, BEETLE can find
configurations that are as good or better as those found by anything else while
requiring only 1/7th of the evaluations needed by the state-of-the-art.


  In this note we deduce a new lower bound for the convergence radius of the
Virial series of a continuous system of classical particles interacting via a
stable and tempered pair potential using the estimates on the Mayer
coefficients obtained in the recent paper by Procacci and Yuhjtman (Lett Math
Phys 107:31-46, 2017). This corrects the wrongly optimistic lower bound for the
same radius claimed (but not proved) in the above cited paper (in Remark 2
below Theorem 1). The lower bound for the convergence radius of the Virial
series provided here represents a strong improvement on the classical estimate
given by Lebowitz and Penrose in 1964.


  The Transformer architecture has proven to be highly effective for Automatic
Speech Recognition (ASR) tasks, becoming a foundational component for a
plethora of research in the domain. Historically, many approaches have leaned
on fixed-length attention windows, which becomes problematic for varied speech
samples in duration and complexity, leading to data over-smoothing and neglect
of essential long-term connectivity. Addressing this limitation, we introduce
Echo-MSA, a nimble module equipped with a variable-length attention mechanism
that accommodates a range of speech sample complexities and durations. This
module offers the flexibility to extract speech features across various
granularities, spanning from frames and phonemes to words and discourse. The
proposed design captures the variable length feature of speech and addresses
the limitations of fixed-length attention. Our evaluation leverages a parallel
attention architecture complemented by a dynamic gating mechanism that
amalgamates traditional attention with the Echo-MSA module output. Empirical
evidence from our study reveals that integrating Echo-MSA into the primary
model's training regime significantly enhances the word error rate (WER)
performance, all while preserving the intrinsic stability of the original
model.


  Dalitz decays of a hyperon resonance to a ground-state hyperon and an
electron-positron pair can give access to some information about the composite
structure of hyperons. We present expressions for the multi-differential decay
rates in terms of general transition form factors for spin-parity combinations
J^P = 1/2^+/-, 3/2^+/- of the hyperon resonance. Even if the spin of the
initial hyperon resonance is not measured, the self-analyzing weak decay of the
"final" ground-state hyperon contains information about the relative phase
between combinations of transition form factors. This relative phase is
non-vanishing because of the unstable nature of the hyperon resonance. If all
form factor combinations in the differential decay formulae are replaced by
their respective values at the photon point, one obtains a QED type
approximation, which might be interpreted as characterizing hypothetical
hyperons with point-like structure. We compare the QED type approximation to a
more realistic form factor scenario for the lowest-lying singly-strange hyperon
resonances. In this way we explore which accuracy in the measurements of the
differential Dalitz decay rates is required in order to distinguish the
composite-structure case from the pointlike case. Based on the QED type
approximation we obtain as a by-product a rough prediction for the ratio
between the Dalitz decay width and the corresponding photon decay width.


  Fake audio detection is expected to become an important research area in the
field of smart speakers such as Google Home, Amazon Echo and chatbots developed
for these platforms. This paper presents replay attack vulnerability of
voice-driven interfaces and proposes a countermeasure to detect replay attack
on these platforms. This paper presents a novel framework to model replay
attack distortion, and then use a non-learning-based method for replay attack
detection on smart speakers. The reply attack distortion is modeled as a
higher-order nonlinearity in the replay attack audio. Higher-order spectral
analysis (HOSA) is used to capture characteristics distortions in the replay
audio. Effectiveness of the proposed countermeasure scheme is evaluated on
original speech as well as corresponding replayed recordings. The replay attack
recordings are successfully injected into the Google Home device via Amazon
Alexa using the drop-in conferencing feature.


  Flow delegation is a flexible technique to mitigate flow table capacity
bottlenecks in Software-defined Networks (SDN). Such bottlenecks occur when SDN
switches provide insufficient flow table capacity which leads to performance
degradation and network failures. Flow delegation addresses this problem by
automatically relocating flow rules from a bottlenecked switch to neighboring
switches with spare capacity. This paper introduces a new algorithm to
efficiently perform flow delegation based on a novel delegation template
abstraction and multi-period multi-objective optimization. Different from
existing work, our approach can include estimated knowledge about future
network situations and deal with different optimization criteria such as link
and control overhead. We discuss the problem decomposition for the new
algorithm and introduce an efficient two-step heuristic. Results show, that our
approach performs significantly better than the simple greedy algorithm used in
earlier work and is capable of handling flow delegation for networks with
hundreds of switches.


  Employing the high spatio-temporal Interface Region Imaging Spectrograph 1330
{\AA} observations, we investigated the jet-like features that occurred during
the X8.2 class flare in NOAA active region (AR) 12673 on 2017 September 10.
These jet-like features were rooted in the flare ribbons. We examined 15
features, and the mean values of the lifetimes, projected widths, lengths and
velocities of these features were 87 s, 890 km, 2.7 Mm and 70 km s$^{-1}$,
respectively. We also observed many jet-like features which happened during the
X1.0 class flare on 2014 October 25. We studied the spectra at the base of a
jet-like feature during its development. The Fe XXI 1354.08 {\AA} line in the
corona displays blueshift, while the Si IV 1402.77 {\AA} line in the transition
region exhibits redshift, which indicates the chromospheric evaporation. This
is the first time that the jet-like features are reported to be rooted in the
flare ribbons, and we suggest that these jet-like features were driven by the
mechanism of chromospheric evaporation.


  We propose a novel algorithm for testing the hypothesis of nonstationarity in
complex-valued signals. The implementation uses both the bootstrap and the Fast
Fourier Transform such that the algorithm can be efficiently implemented in
O(NlogN) time, where N is the length of the observed signal. The test procedure
examines the second-order structure and contrasts the observed power variance -
i.e. the variability of the instantaneous variance over time - with the
expected characteristics of stationary signals generated via the bootstrap
method. Our algorithmic procedure is capable of learning different types of
nonstationarity, such as jumps or strong sinusoidal components. We illustrate
the utility of our test and algorithm through application to turbulent flow
data from fluid dynamics.


  Recently, we proposed a method that converts the force between two-large
colloids into the pressure on the surface element (FPSE conversion) in a system
of a colloidal solution. Using it, the density distribution of the small
colloids around the large colloid is calculated. In a similar manner, in this
letter, we propose a transform theory for colloidal probe atomic force
microscopy (colloidal probe AFM), which transforms the force acting on the
colloidal probe into the density distribution of the small colloids on a flat
surface. If measured condition is proper one, in our view, it is possible for
the transform theory to be applied for liquid AFM and obtain the liquid
structure. The transform theory we derived is briefly explained in this letter.


  We study experimentally the dynamical and decay properties of the Stimulated
Nutation Echo (SNE) in a two-level spin system. This is the signal which
appears in the transient response of the system to the second pulse at time
tau_1 elapsed from its beginning and coinciding with the duration of the first
pulse. The information about the first pulse duration is imprinted into the
population difference of the inhomogeneously broadened ensemble of the
two-level absorbers. The decay of the SNE signal has two contributions. One
originates from the population decay during the time tau between the pulses.
Another is caused by the coherence loss during the excitation by the first
pulse and the reading time of the second pulse. Experimental results on the
decay properties induced by these mechanisms are presented. The dependence of
these decay rates on the pulse intensity is discussed, and its relationship
with the anomalous (non-Bloch) decay of other coherent transients in solids is
examined.


  The Higgs boson is the missing link of the Standard Model of elementary
particle physics. We review its decay properties and production mechanisms at a
future e^+ e^- linear collider and its e^- e^-, e^+- gamma, and gamma gamma
modes, with special emphasis on the influence of quantum corrections. We also
discuss how its quantum numbers and couplings can be extracted from the study
of appropriate final states.


  In order to understand the formation mechanism of the disks around Be stars
it is imperative to have a good overview of both the differences and
similarities between normal B stars and the Be stars. Here we investigate a
previous report that there may be a large population of sub-arcsecond
companions to Be stars. We present the first systematic, comparative imaging
study of the binary properties of matched samples of B and Be stars observed
using the same equipment. We obtained high angular resolution (0.07-0.1 arcsec)
K band Adaptive Optics data of 40 B stars and 39 Be stars. The separations that
can be probed range from 0.1 to 8 arcsec (corresponding to 20-1000 AU), and
magnitude differences up to 10 magnitudes can in principle be covered. We
detect 11 binaries out of 37 Be targets (corresponding to a binary fraction of
30 +/- 8%) and 10 binaries out of 36 B targets (29 +/- 8%). Further tests
demonstrate that the B and Be binary systems are not only similar in frequency
but also remarkably similar in terms of binary separations, flux differences
and mass ratios. We find that any hypotheses invoking binary companions as
responsible for the formation of a disk need the companions to be closer than
20 AU. Close companions are known to affect the circumstellar disks of Be
stars, but as not all Be stars have been found to be close binaries, the data
suggest that binarity can not be responsible for the Be phenomenon in all Be
stars. Finally, the similarities of the binary parameters themselves also shed
light on the Be formation mechanism. They strongly suggest that the initial
conditions that gave rise to B and Be star formation must, to all intents and
purposes, be similar. This in turn indicates that the Be phenomenon is not the
result of a different star formation mechanism.


  The existence of the invariant measure in nonlocal regularized actions is
discussed. It is shown that the measure for nonlocally regularized QED, as
presented in\cite{Moff-Wood}, exists to all orders, and is precisely what is
required to maintain gauge invariance at one loop and guarantees perturbative
unitarity. We also demonstrate how the given procedure breaks down in anomalous
theories, and discuss its generalization to other actions.


  Using J/psi and open charm photoproduction data, we apply the vector meson
dominance model to obtain constraints on the energy dependence of the inelastic
J/psi-nucleon cross section. Predictions of short distance QCD are in accord
with these constraints, while recently proposed hadronic models for J/psi
dissociation strongly violate them.


  We study the extremal process associated with the Discrete Gaussian Free
Field on the square lattice and elucidate how the conformal symmetries manifest
themselves in the scaling limit. Specifically, we prove that the joint process
of spatial positions ($x$) and centered values ($h$) of the extreme local
maxima in lattice versions of a bounded domain $D\subset\mathbb C$ converges,
as the lattice spacing tends to zero, to a Poisson point process with intensity
measure $Z^D(dx)\otimes e^{-\alpha h}d h$, where $\alpha$ is a constant and
$Z^D$ is a random a.s.-finite measure on $D$. The random measures $\{Z^D\}$ are
naturally interrelated; restrictions to subdomains are governed by a
Gibbs-Markov property and images under analytic bijections $f$ by the
transformation rule $(Z^{f(D)}\circ f)(d x)\overset{\text{law}}=|f'(x)|^4\,
Z^D(d x)$. Conditions are given that determine the laws of these measures
uniquely. These identify $Z^D$ with the critical Liouville Quantum Gravity
associated with the Continuum Gaussian Free Field.


  We discuss polarization characteristics of the deuteron disintegration near
the threshold energy. Due to the small relative energy of the outgoing $np$
pair, the dominant amplitude for this process is a 1+ -> 0^+ transition.
Relativistic covariance requires only one electromagnetic transition form
factor for this amplitude. Subsequently this leads to substantial
simplifications in the formulas of the polarization observables and allows to
draw conclusions independent of the details of the interaction.


  Black hole superradiance, which only relies on gravitational interactions,
can provide a powerful probe of the existence of ultralight bosons that are
weakly coupled to ordinary matter. However, as a boson cloud grows through
superradiance, nonlinear effects from interactions with itself or other fields
may become important. As a representative example of this, we use nonlinear
evolutions to study black hole superradiance of a vector boson that attains a
mass, via a coupling to a complex scalar, through the Higgs mechanism. For the
cases considered, we find that the superradiant instability can lead to a
transient period where the scalar field reaches its symmetry restoration value,
leading to the formation of closed vortex strings, the temporary disruption of
the exponential growth of the cloud, and an explosive outburst of energy. After
the cloud loses sufficient mass, the superradiant growth resumes, and the cycle
repeats. Thus, the black hole will be spun down but, potentially, at a much
lower rate compared to when nonlinear effects are unimportant, and with the
liberated energy going primarily into bosonic radiation instead of
gravitational waves.


  The lattice size $\operatorname{ls}_{\Delta}(P)$ of a lattice polygon $P$
with respect to the standard simplex $\Delta$ was introduced and studied by
Castryck and Cools in the context of simplification of the defining equation of
an algebraic curve. Earlier, Schicho provided an "onion skins" algorithm for
mapping a lattice polygon $P$ into a small integer multiple of the standard
simplex, based on passing successively to the convex hull of the interior
lattice points of $P$. Castryck and Cools showed that this algorithm computes
the lattice size of $P$.
  In this paper we show that for a plane convex body $P$ a reduced basis of
$\mathbb{Z}^2$ computes the lattice size. This provides a lattice reduction
algorithm for computing the lattice size, which works for any convex body
$P\subset\mathbb{R}^2$ and outperforms the "onion skins" algorithm in the case
when $P$ is a lattice polygon.


  We study theoretically the quenching of a charge-density-wave phase in a
model system of a quasi-two dimensional material, which includes both
electron-hole and electron-phonon interactions leading, respectively to
excitonic and coherent-phonon contributions. We discuss how interaction
processes affect anomalous expectation values and present a microscopic
dynamical picture of the quenching of the phase. We use projection techniques
to illustrate the time-dependent appearance of additional bands and anomalous
expectation values. We propose an optical amplification effect with a high
modulation frequency in the mid-infrared regime.


  We consider the $C^1$-Virtual Element Method (VEM) for the conforming
numerical approximation of some variants of the Cahn-Hilliard equation on
polygonal meshes. In particular, we focus on the discretization of the
advective Cahn-Hilliard problem and the Cahn-Hilliard inpainting problem. We
present the numerical approximation and several numerical results to assess the
efficacy of the proposed methodology.


  We analyse configurations of compact stars in the so-called R-squared gravity
in the Palatini formalism. Using a realistic equation of state we show that the
mass-radius configurations are lighter than their counterparts in General
Relativity. We also obtain the internal profiles, which run in strong
correlation with the derivatives of the equation of state, leading to regions
where the mass parameter decreases with the radial coordinate in a
counter-intuitive way. In order to analyse such correlation, we introduce a
parametrisation of the equation of state given by multiple polytropes, which
allows us to explicitly control its derivatives. We show that, even in a
limiting case where hard phase transitions in matter are allowed, the internal
profile of the mass parameter still presents strange features and the
calculated M-R configurations also yield NSs lighter than those obtained in
General Relativity.


  We simulate lattice models in the three-dimensional XY universality class in
the low and the high temperature phase. This allows us to compute a number of
universal amplitude ratios with unprecedented precision: R_{\Upsilon}=0.411(2),
R_B=2.83(1), R_{\xi}^+=0.3562(10) and R_{\xi}^-=0.850(5). These results can be
compared with those obtained from other theoretical methods, such as field
theoretic methods or the high temperature series expansion and also with
experimental results for the lambda-transition of $^4$He. In addition to the XY
model, we study the three-dimensional two-component $\phi^4$ model on the
simple cubic lattice. The parameter of the $\phi^4$ model is chosen such that
leading corrections to scaling are small.


  We study $\mathbb{Z}_2$ topologically ordered states enriched by
translational symmetry by employing a recently developed 2D bosonization
approach that implements an exact $\mathbb{Z}_2$ charge-flux attachment in the
lattice. Such states can display `weak symmetry breaking' of translations, in
which both the Hamiltonian and ground state remain fully translational
invariant but the symmetry is `broken' by its anyon quasi-particles, in the
sense that its action maps them into a different super-selection sector. We
demonstrate that this phenomenon occurs when the fermionic spinons form a weak
topological superconductor in the form of a 2D stack of 1D Kitaev wires,
leading to the amusing property that there is no local operator that can
transport the $\pi$-flux quasi-particle across a single Kitaev wire of fermonic
spinons without paying an energy gap in spite of the vacuum remaining fully
translational invariant. We explain why this phenomenon occurs hand-in-hand
with other previously identified peculiar features such as ground state
degeneracy dependence on the size of the torus and the appearance of dangling
boundary Majorana modes in certain $\mathbb{Z}_2$ topologically ordered states.
Moreover, by extending the $\mathbb{Z}_2$ charge-flux attachment to open
lattices and cylinders, we construct a plethora of exactly solvable models
providing an exact description of their dispersive Majorana gapless boundary
modes. We also review the $\mathbb{Z}\times (\mathbb{Z}_2)^3$ classification of
2D BdG Hamiltonians (Class D) enriched by translational symmetry and provide
arguments on its robust stability against interactions and self-averaging
disorder that preserves translational symmetry.


  Several families of continual learning techniques have been proposed to
alleviate catastrophic interference in deep neural network training on
non-stationary data. However, a comprehensive comparison and analysis of
limitations remains largely open due to the inaccessibility to suitable
datasets. Empirical examination not only varies immensely between individual
works, it further currently relies on contrived composition of benchmarks
through subdivision and concatenation of various prevalent static vision
datasets. In this work, our goal is to bridge this gap by introducing a
computer graphics simulation framework that repeatedly renders only upcoming
urban scene fragments in an endless real-time procedural world generation
process. At its core lies a modular parametric generative model with adaptable
generative factors. The latter can be used to flexibly compose data streams,
which significantly facilitates a detailed analysis and allows for effortless
investigation of various continual learning schemes.


  The variational autoencoder (VAE) is a well-studied, deep, latent-variable
model (DLVM) that efficiently optimizes the variational lower bound of the log
marginal data likelihood and has a strong theoretical foundation. However, the
VAE's known failure to match the aggregate posterior often results in
\emph{pockets/holes} in the latent distribution (i.e., a failure to match the
prior) and/or \emph{posterior collapse}, which is associated with a loss of
information in the latent space. This paper addresses these shortcomings in
VAEs by reformulating the objective function associated with VAEs in order to
match the aggregate/marginal posterior distribution to the prior. We use kernel
density estimate (KDE) to model the aggregate posterior in high dimensions. The
proposed method is named the \emph{aggregate variational autoencoder} (AVAE)
and is built on the theoretical framework of the VAE. Empirical evaluation of
the proposed method on multiple benchmark data sets demonstrates the
effectiveness of the AVAE relative to state-of-the-art (SOTA) methods.


  From a streaming video, online action detection aims to identify actions in
the present. For this task, previous methods use recurrent networks to model
the temporal sequence of current action frames. However, these methods overlook
the fact that an input image sequence includes background and irrelevant
actions as well as the action of interest. For online action detection, in this
paper, we propose a novel recurrent unit to explicitly discriminate the
information relevant to an ongoing action from others. Our unit, named
Information Discrimination Unit (IDU), decides whether to accumulate input
information based on its relevance to the current action. This enables our
recurrent network with IDU to learn a more discriminative representation for
identifying ongoing actions. In experiments on two benchmark datasets, TVSeries
and THUMOS-14, the proposed method outperforms state-of-the-art methods by a
significant margin. Moreover, we demonstrate the effectiveness of our recurrent
unit by conducting comprehensive ablation studies.


  Spontaneous flame acceleration leading to explosion triggering in open
tubes/channels due to wall friction was analytically and computationally
studied. It was first demonstrated that the acceleration is effected when the
thermal expansion across the flame exceeds a critical value depending on the
combustion configuration. For the axisymmetric flame propagation in cylindrical
tubes with both ends open, a theory of the initial (exponential) stage of flame
acceleration in the quasi-isobaric limit was developed and substantiated by
extensive numerical simulation of the hydrodynamics and combustion with an
Arrhenius reaction. The dynamics of the flame shape, velocity, and acceleration
rate, as well as the velocity profile ahead and behind the flame, have been
determined.


  By an automorphism of a topological group G we mean an isomorphism of G onto
itself which is also a homeomorphism. In this article, we study the
automorphism group Aut(G) of a dense subgroup G of R^n, n>=1. We show that
Aut(G) can be naturally identified with the subgroup I(G)={A in GL(n,R): G A
=G} of the group GL(n,R) of all non-degenerated (n x n)-matrices over R, where
G A={g A:g in G}. We describe $I(G) for many dense subgroups G of either R or
R^2. We consider also an inverse problem of which symmetric subgroups of
GL(n,R) can be realized as I(G) for some dense subgroup G of R^n. For example,
for n>=2, we show that the group {A in GL(n,R): det A=+-1} cannot be realized
in this way. The realization problem is quite non-trivial even in the
one-dimensional case and has deep connections to number theory.


  In order to accommodate nonzero and relatively large of mixing angle
$\theta_{13}$, we modified the tribimaximal mixing(TBM) matrix by introducing a
simple perturbation matrix to perturb TBM matrix. The modified TBM can
reproduce nonzero mixing angle $\theta_{13}=7.9^{0}$ which is in agreement with
the present experimental results. By imposing two zeros texture into the
obtained neutrino mass matrix from modified TBM, we then have the neutrino mass
spectrum in normal hierarchy. Some phenomenological implications are also
discussed


  Atomic-scale smooth thin films are keys to successful integration and proper
function of many multilayer-structured devices. However, the intrinsic
island-like growth mode prevents human being from realizing such ultrasmooth
films of many important functional materials. To solve this problem, we propose
a negative entropy-infusing method that employs evanescent waves to enhance the
downward interlayer diffusion of adatoms and thus transform the island-like
growth mode to the layer-by-layer growth mode. The formulas of the optical
force and the lowered diffusion barrier were derived, and the application of
this theory on a simplified example demonstrates significantly improved surface
morphologies through numerical simulations.


  Datasets serve as crucial training resources and model performance trackers.
However, existing datasets have exposed a plethora of problems, inducing biased
models and unreliable evaluation results. In this paper, we propose a
model-agnostic dataset evaluation framework for automatic dataset quality
evaluation. We seek the statistical properties of the datasets and address
three fundamental dimensions: reliability, difficulty, and validity, following
a classical testing theory. Taking the Named Entity Recognition (NER) datasets
as a case study, we introduce $9$ statistical metrics for a statistical dataset
evaluation framework. Experimental results and human evaluation validate that
our evaluation framework effectively assesses various aspects of the dataset
quality. Furthermore, we study how the dataset scores on our statistical
metrics affect the model performance, and appeal for dataset quality evaluation
or targeted dataset improvement before training or testing models.


  We show that the quantum stochastic unitary dynamics Langevin model for
continuous in time measurements provides an exact formulation of the Heisenberg
uncertainty error-disturbance principle. Moreover, as it was shown in the 80's,
this Markov model induces all stochastic linear and non-linear equations of the
phenomenological "quantum trajectories" such as quantum state diffusion and
spontaneous localization by a simple quantum filtering method. Here we prove
that the quantum Langevin equation is equivalent to a Dirac type boundary-value
problem for the second-quantized input "offer waves from future" in one extra
dimension, and to a reduction of the algebra of the consistent histories of
past events to an Abelian subalgebra for the "trajectories of the output
particles". This result supports the wave-particle duality in the form of the
thesis of Eventum Mechanics that everything in the future is constituted by
quantized waves, everything in the past by trajectories of the recorded
particles. We demonstrate how this time arrow can be derived from the principle
of quantum causality for nondemolition continuous in time measurements.


  Hydrodynamic models for spherically-symmetric winds driven by young stellar
clusters with a generalized Schuster stellar density profile are explored. For
this we use both semi-analytic models and 1D numerical simulations. We
determine the properties of quasi-adiabatic and radiative stationary winds and
define the radius at which the flow turns from subsonic into supersonic for all
stellar density distributions. Strongly radiative winds diminish significantly
their terminal speed and thus their mechanical luminosity is strongly reduced.
This also reduces their potential negative feedback into their host galaxy ISM.
The critical luminosity above which radiative cooling becomes dominant within
the clusters, leading to thermal instabilities which make the winds
non-stationary, is determined, and its dependence on the star cluster density
profile, core radius and half mass radius is discussed.


  Linear and non-linear surface waves on a ferrofluid cylinder surrounding a
current-carrying wire are investigated. Suppressing the Rayleigh-Plateau
instability of the fluid column by the magnetic field of a sufficiently large
current in the wire axis-symmetric surface deformations are shown to propagate
without dispersion in the long wavelength limit. Using multiple scale
perturbation theory the weakly non-linear regime may be described by a
Korteweg-de Vries equation with coefficients depending on the magnetic field
strength. For different values for the current in the wire hence different
solutions such as hump or hole solitons may be generated. The possibility to
observe these structures in experiments is also elucidated.


  In this paper an asymmetrical operator of generalised translation is
introduced, the generalised modulus of smoothness is defined by its means and
the direct and inverse theorems in approximation theory are proved for that
modulus.
  -----
  V danno\v{i} rabote vvoditsya nesimmetrichny\v{i} operator obobshchennogo
sdviga, s ego pomoshchyu opredelyaetsya obobshchenny\v{i} modul' gladkosti i
dlya nego dokazyvaetsya pryamaya i obratnaya teoremy teorii priblizheni\v{i}.


  The trend toward autonomous robot deployments is on an upward growth curve.
These robots are undertaking new tasks and are being integrated into society.
Examples of this trend are autonomous vehicles, humanoids, and eldercare. The
movement from factory floors to streets and homes has also increased the number
of vulnerabilities that adversaries can utilize. To improve security, Robot
Operating System (ROS) 2 has standardized on using Data Distributed Services
(DDS) as the messaging layer, which supports a security standard for protecting
messages between parties with access control enforcement. DDS security is
dependent on the OpenSSL and a security configuration file that specifies
sensitive data location. DSS Security assumes that the underlining Operating
System (OS) is secure and that the dependencies are consistent, but ongoing
integrity checks are not performed. This paper looks at two vulnerabilities
that we exploit using an OpenSSL spy process and a security property file
manipulation. An overview of each exploit is provided with an evaluation of
mitigation technologies that may be employed in client computers, servers, and
other areas. Since, ROS 2 and DDS run in user space, these processes are prone
to vulnerabilities. We provide recommendations about mitigation technology, as
currently autonomous platforms are being deployed without safe-guards for on or
off-line threats. The Trust Platform Module (TPM) is new to robotic systems,
but the standard usage model does not provide risk mitigation above the OS
layer for the types of attacks we discuss.


  We present a new approach for calculating electromagnetic excitation of
nuclei as well as probabilities of emission and distributions of neutrons from
decays of excited nuclear systems for ultrarelativistic, ultraperipheral heavy
ion collisions. Excitation functions for $\gamma$ + Pb $\to$ Pb$^*$ are
parametrized using physics-motivated components: excitation of giant
resonances, quasi-deuteron absorption mechanism, excitation of nucleon
resonances as well as high-energy dissociation of protons and neutrons. Neutron
emission (up to 10 neutrons) from low-energy excitations of $^{208}$Pb is
modelled in terms of the Hauser-Feshbach formalism. The probabilities of a
given number of neutrons are calculated as a function of excitation energy in a
Monte-Carlo code GEMINI. These functions are parametrized by smooth analytical
functions. The results are compared to appropriate data for the $\gamma$ Pb
$\to$ Pb$^*$ $\to$ k n reaction. As an example the approach is used for
calculating electromagnetic excitation in UPC processes. Both single photon and
double photon excitations are included and discussed. Topological cross
sections with a given number of neutrons in forward and backward directions are
calculated in the calculation at the LHC energies. Excitation functions are
presented. The results of calculation are compared with SPS and more recent
ALICE experimental data and good agreement is achieved.


  We consider type IIB string theory on a seven dimensional orbifold with
holonomy in G2. The motivation is to use D1-branes as probes of the geometry.
The low energy theory on the D1-brane is a sigma-model with two real
supercharges (N = (1,1) in two dimensional language). We study in detail the
closed and open string sectors and propose a coupling of the twisted fields to
the brane that modifies the vacuum moduli space so that the singularity at the
origin is removed. Instead of coming from D-terms, which are not present here,
the modification comes from a ``twisted'' mass term for the seven scalar
multiplets on the brane. The proposed mechanism involves a generalization of
the moment map.


  The use of coordinate processes for the modelling of impulse control for
general Markov processes typically involves the construction of a probability
measure on a countable product of copies of the path space. In addition,
admissibility of an impulse control policy requires that the random times of
the interventions be stopping times with respect to different filtrations
arising from the different component coordinate processes. When the underlying
Markov process has continuous paths, however, a simpler model can be developed
which takes the single path space as its probability space and uses the natural
filtration with respect to which the intervention times must be stopping times.
Moreover, this model construction allows for impulse control with random
effects whereby the decision maker selects a distribution of the new state.
This paper gives the construction of the probability measure on the path space
for an admissible intervention policy subject to a randomized impulse
mechanism. In addition, a class of polices is defined for which the paths
between interventions are independent and a further subclass for which the
cycles following the initial cycle are identically distributed. A benefit of
this smaller subclass of policies is that one is allowed to use classical
renewal arguments to analyze long-term average control problems. Further, the
paper defines a class of {\em stationary}\/ impulse policies for which the
family of models gives a Markov family. The decision to use an $(s,S)$ ordering
policy in inventory management provides an example of an impulse policy for
which the process has i.i.d.~cycles and the family of models forms a Markov
family.


  We propose a novel technique to separate the late-time, post-reionization
component of the kinetic Sunyaev-Zeldovich (kSZ) effect from the contribution
to it from a (poorly understood and probably patchy) reionization history. The
kSZ effect is one of the most promising probe of the {\em missing baryons} in
the Universe. We study the possibility of reconstructing it in three dimensions
(3D), using future spectroscopic surveys such as the Euclid survey. By
reconstructing a 3D template from galaxy density and peculiar velocity fields
from spectroscopic surveys we cross-correlate the estimator against CMB maps.
The resulting cross-correlation can help us to map out the kSZ contribution to
CMB in 3D as a function of redshift thereby extending previous results which
use tomographic reconstruction. This allows the separation of the late time
effect from the contribution owing to reionization. By construction, it avoids
contamination from foregrounds, primary CMB, tSZ effect as well as from star
forming galaxies. Due to a high number density of galaxies the signal-to-noise
(S/N) for such cross-correlational studies are higher, compared to the studies
involving CMB power spectrum analysis. Using a spherical Bessel-Fourier (sFB)
transform we introduce a pair of 3D power-spectra: ${\cal
C}^{\parallel}_\ell(k)$ and ${\cal C}^{\perp}_\ell(k)$ that can be used for
this purpose. We find that in a future spectroscopic survey with near all-sky
coverage and a survey depth of $z\approx 1$, reconstruction of ${\cal
C}^{\perp}_\ell(k)$ can be achieved in a few radial wave bands
$k\approx(0.01-0.5 h^{-1}\rm Mpc)$ with a S/N of upto ${\cal O}(10)$ for
angular harmonics in the range $\ell=(200-2000)$ (abrdiged).


  In this paper, we study the dynamics of a linear control system with given
state feedback control law in the presence of fast periodic sampling at
temporal frequency $1/\delta$ ($0 < \delta \ll 1$), together with small white
noise perturbations of size $\varepsilon$ ($0<\varepsilon \ll 1$) in the state
dynamics. For the ensuing continuous-time stochastic process indexed by two
small parameters $\varepsilon,\delta$, we obtain effective ordinary and
stochastic differential equations describing the mean behavior and the typical
fluctuations about the mean in the limit as $\varepsilon,\delta \searrow 0$.
The effective fluctuation process is found to vary, depending on whether
$\delta \searrow 0$ faster than/at the same rate as/slower than $\varepsilon
\searrow 0$. The most interesting case is found to be the one where
$\delta,\varepsilon$ are comparable in size; here, the limiting stochastic
differential equation for the fluctuations has both a diffusive term due to the
small noise and an effective drift term which captures the cumulative effect of
the fast sampling. In this regime, our results yield a time-inhomogeneous
Markov process which provides a strong (pathwise) approximation of the original
non-Markovian process, together with estimates on the ensuing error. A simple
example involving an infinite time horizon linear quadratic regulation problem
illustrates the results.


  Providing minimum quality-of-service (QoS) in crowded wireless communications
systems, with high user density, is challenging due to the network structure
with limited transmit power budget and resource blocks. Smart resource
allocation methods, such as user scheduling, power allocation, and modulation
and coding scheme selection, must be implemented to cope with the challenge.
Aiming to enhance the number of served users with minimum QoS in the downlink
(DL) channel of crowded extra-large scale massive multiple-input
multiple-output (XL-MIMO) systems, in this paper we propose a QoS-aware joint
user scheduling and power allocation technique. The proposed technique is
constituted by two sequential procedures: the clique search-based scheduling
(CBS) algorithm for user scheduling followed by optimal power allocation with
transmit power budget and minimum achievable rate per user constraints. To
accurately evaluate the proposed technique in the XL-MIMO scenario, we propose
a generalized non-stationary multi-state channel model based on spherical-wave
propagation assuming that users under LoS and NLoS transmission coexist in the
same communication cell. Such model considers that users under different
channel states experience different propagation aspects both in the multipath
fading model and the path loss rule. Numerical results on the achievable
sum-rate, number of scheduled users, and distribution of the scheduled users
reveal that the proposed CBS algorithm provides a fair coverage over the whole
cell area, achieving remarkable numbers of scheduled users when users under the
LoS and NLoS channel states coexist in the communication cell.


  Due to structural incommensurability, the emergence of a quasicrystal from a
crystalline phase represents a challenge to computational physics. Here the
nucleation of quasicrystals is investigated by using an efficient computational
method applied to a Landau free-energy functional. Specifically, transition
pathways connecting different local minima of the Lifshitz-Petrich model are
obtained by using the high-index saddle dynamics. Saddle points on these paths
are identified as the critical nuclei of the 6-fold crystals and 12-fold
quasicrystals. The results reveal that phase transitions between the
crystalline and quasicrystalline phases could follow two possible pathways,
corresponding to a one-stage phase transition and a two-stage phase transition
involving a metastable lamellar quasicrystalline state, respectively.


  In this letter, we present a new method that quantitatively identifies the
occurrence probability of equations of state (EoS) beyond "standard" EoS models
that disfavor sharp and strong phase-transitions, based on neutron star mass
and radius observations. The radii of two neutron stars with different masses
are naturally correlated, in part because both of them are sensitive to the
symmetry energy of the EoS. We show the radii of two neutron stars observed by
NICER (PSR J0740+6620 and PSR 0030+0451) are correlated if these two neutron
stars are built upon EoSs with no sharp and strong first-order phase
transitions. We further show that the linear correlation of the neutron star
radii can be significantly weakened, when strong and sharp first-order phase
transitions occur. We propose a new quantity, ${D}_{\mathrm{L}}$, which
measures the extent to which the linear correlation of the radii of two neutron
stars is weakened. Our method gives a 48% identification probability (with a 5%
false alarm rate) that the NICER observations indicate the necessity for a
sharp and strong phase transition. Future observations can confirm or rule out
this identification. Our method is generalizable to any pair of neutron star
masses and can be employed with other sets of observations in the future.


  The thermodynamics of quarks and gluons strongly depends on the vacuum
colormagnetic field, which grows with the temperature $T$, so that spatial
string tension $\sigma_s ={\rm const}~ g^4 (T) T^2$. We investigate below what
happens when one imposes in addition constant magnetic field and discover
remarkable structure of the resulting thermodynamic potential.


  In this work, we study the branching ratios of B^{0}_{s}\rightarrow
a_{0}(980)[ \rightarrow K\overline{K}, \pi\eta]a_{0}(980), B^{0}_{s}
\rightarrow f_{0}(980)[ \rightarrow \pi^{+}\pi^{-}, K^{+}K^{-}]f_{0}(980) and
B^{0}_{s} \rightarrow f_{0}(500)[ \rightarrow \pi^{+}\pi^{-}]f_{0}(500) decays
in the pQCD approach, in which the scalar mesons a_{0}(980), f_{0}(980) and
f_{0}(500) are regarded as the lowest-lying q\overline{q} state. In the SU(3)
nonet, there exists a mixing between the scalars f_{0}(980) and f_{0}(500), so
we have considered the mixing effect in our calculations to obtain more
reliable data, and the mixing angle \theta is set at [15^{\circ}, 82^{\circ}]
and [105^{\circ}, 171^{\circ}]. Based on the isospin symmetry, we also estimate
the branching ratios of the B^{0}_{s} \rightarrow f_{0}(980)[ \rightarrow
\pi^{0}\pi^{0}]f_{0}(980) and B^{0}_{s} \rightarrow f_{0}(500)[ \rightarrow
\pi^{0}\pi^{0}]f_{0}(500) decays. The branching ratios of the
B^{0}_{s}\rightarrow a_{0}(980)[ \rightarrow K\overline{K}, \pi\eta]a_{0}(980)
decays are much small, while the results of the B^{0}_{s} \rightarrow
f_{0}(980)[ \rightarrow \pi\pi, K\overline{K}]f_{0}(980) and B^{0}_{s}
\rightarrow f_{0}(500)[ \rightarrow \pi\pi]f_{0}(500) decays are at the order
of 10^{-6}\sim10^{-5}, which can be tested in the LHCb and Belle II
experiments, hopefully.


  We use a local theory of photons purely as particles to model the
single-photon experiment proposed by Tan, Walls, and Collett. Like Tan et al.
we are able to derive a violation of Bell's inequalities for photon counts
coincidence measurements. Our local probabilistic theory does not use any
specific quantum mechanical calculations.


  Galaxy bias, the unknown relationship between the clustering of galaxies and
the underlying dark matter density field is a major hurdle for cosmological
inference from large-scale structure. While traditional analyses focus on the
absolute clustering amplitude of high-density regions mapped out by galaxy
surveys, we propose a relative measurement that compares those to the
underdense regions, cosmic voids. On the basis of realistic mock catalogs we
demonstrate that cross correlating galaxies and voids opens up the possibility
to calibrate galaxy bias and to define a static ruler thanks to the observable
geometric nature of voids. We illustrate how the clustering of voids is related
to mass compensation and show that volume-exclusion significantly reduces the
degree of stochasticity in their spatial distribution. Extracting the
spherically averaged distribution of galaxies inside voids from their cross
correlations reveals a remarkable concordance with the mass-density profile of
voids.


  The Chandra X-ray Observatory has now discovered nearly 10,000 X-ray point
sources in the 2 x 0.8 degree region around the Galactic Center (Muno 2009).
The sources are likely to be a population of accreting binaries in the Galactic
Center, but little else is known of their nature. We obtained JHKs imaging of
the 17'x 17' region around Sgr A*, an area containing 4339 of these X-ray
sources, with the ISPI camera on the CTIO 4-m telescope. We cross-correlate the
Chandra and ISPI catalogs to find potential IR counterparts to the X-ray
sources. The extreme IR source crowding in the field means that it is not
possible to establish the authenticity of the matches with astrometry and
photometry alone. We find 2137 IR/X-ray astrometrically matched sources:
statistically we estimate that our catalog contains 289 +/- 13 true matches to
soft X-ray sources and 154 +/- 39 matches to hard X-ray sources. However, the
fraction of true counterparts to candidate counterparts for hard sources is
just 11 %, compared to 60 % for soft sources, making hard source NIR matches
particularly challenging for spectroscopic follow-up. We calculate a
color-magnitude diagram (CMD) for the matches to hard X-ray sources, and find
regions where significant numbers of the IR matches are real. We use their CMD
positions to place limits on the absolute Ks band magnitudes of the potential
NIR counterparts to hard X-ray sources. We find regions of the counterpart CMD
with 9 +/- 3 likely Wolf-Rayet/supergiant binaries (with 4 spectroscopically
confirmed in the literature) as well as 44 +/- 13 candidates that could consist
of either main sequence high mass X-ray binaries or red giants with an
accreting compact companion. (abridged)


  We comment on various incorrect claims made in a recent paper by Grosu et al.
(cond-mat/0101392).


  This paper presents a study using the Bayesian approach in stochastic
volatility models for modeling financial time series, using Hamiltonian Monte
Carlo methods (HMC). We propose the use of other distributions for the errors
in the observation equation of stochastic volatility models, besides the
Gaussian distribution, to address problems as heavy tails and asymmetry in the
returns. Moreover, we use recently developed information criteria WAIC and LOO
that approximate the cross-validation methodology, to perform the selection of
models. Throughout this work, we study the quality of the HMC methods through
examples, simulation studies and applications to real data sets.


  We consider the shape of crystals which are soft in the sense that their
elastic modulus $\mu$ is small compared to their surface tension $\gamma$, more
precisely $ \mu a < \gamma$ where $a$ is the lattice spacing. We show that
their surface steps penetrate inside the crystal as edge dislocations. As a
consequence, these steps are broad with a small energy which we calculate. We
also calculate the elastic interaction between steps a distance $d$ apart,
which is a $1/d^2$ repulsion. We finally calculate the roughening temperatures
of successive facets in order to compare with the remarkable shapes of
lyotropic crystals recently observed by P. Pieranski et al. Good agreement is
found.


  The population of clearly identified anomalous X-ray pulsars has recently
grown to seven, however, one candidate anomalous X-ray pulsar (AXP) still
eludes re-confirmation. Here, we present a set of seven Chandra ACIS-S
observations of the transient pulsar AX J1845.0-0258, obtained during 2003. Our
observations reveal a faint X-ray point source within the ASCA error circle of
AX J1845.0-0258's discovery, which we designate CXOU J184454.6-025653 and
tentatively identify as the quiescent AXP. Its spectrum is well described by an
absorbed single-component blackbody (kT~2.0 keV) or power law (Gamma~1.0) that
is steady in flux on timescales of at least months, but fainter than AX
J1845.0-0258 was during its 1993 period of X-ray enhancement by at least a
factor of 13. Compared to the outburst spectrum of AX J1845.0-0258, CXOU
J184454.6-025653 is considerably harder: if truly the counterpart, then its
spectral behaviour is contrary to that seen in the established transient AXP
XTE J1810-197, which softened from kT~0.67 keV to ~0.18 keV in quiescence. This
unexpected result prompts us to examine the possibility that we have observed
an unrelated source, and we discuss the implications for AXPs, and magnetars in
general.


  We present a new approach to coherent parton showers in the decays of
coloured resonances, based on the notion of "resonance-final" (RF) QCD
antennae. A full set of mass- and helicity-dependent $2\to 3$ antenna functions
are defined, with the additional requirement of positivity over the respective
branching phase spaces. Their singularity structure is identical to that of
initial-final (IF) antennae in $2\to N$ hard processes (once mass terms
associated with the incoming legs are allowed for), but the phase-space
factorisations are different. The consequent radiation patterns respect QCD
coherence (at leading colour) and reduce to
Dokshitzer-Gribov-Lipatov-Altarelli-Parisi and eikonal kernels in the
respective collinear and soft limits. The main novelty in the phase-space
factorisation is that branchings in RF antennae impart a collective recoil to
the other partons within the same decay system. An explicit implementation of
these ideas, based on the Sudakov veto algorithm, is provided in the VINCIA
antenna-shower plug-in to the PYTHIA 8 Monte Carlo event generator. We apply
our formalism, matched to next-to-leading order accuracy using POWHEG, to top
quark production at the LHC, and investigate implications for direct
measurement of the top quark mass. Finally, we make recommendations for
assessing theoretical uncertainties arising from parton showers in this
context.


  Precise manipulation of the direction and re-direction of vibrational wave
energy is a key demand in wave physics and engineering. We consider the
paradigm of a finite frame-like structure and the requirement to channel energy
away from critical regions, leaving them vibration-free, and redirect energy
along edges towards energy concentrators for damping or energy harvesting. We
design an exemplar frame metamaterial, combining two distinct areas of wave
physics. Firstly, topological edge states taking an unconventional tetrachiral
lattice. We control these highly localised protected edge states leveraging a
hierarchy of scales through the addition of micro-resonators that impose
tuneable symmetry breaking and reconfigurable mass. This allows us to achieve
precise positional control in the macro-scale frame lattice, thereby opening
opportunities for robust signal transport and vibration control. Experiments,
theory, simulation are all utilised to provide a comprehensive analysis and
interpretation of the physics.


  Let X be a projective curve over Q and t a non-constant Q-rational function
on X of degree n>1. For every integer a pick a points P(a) on X such that
t(P(a))=a. Dvornicich and Zannier (1994) proved that for large N the field
Q(P(1), ..., P(N)) is of degree at least exp(cN/log N) over Q, where c>0
depends only on X and t. In this note we extend this result, replacing Q by an
arbitrary number field.


  In this article, we study the structure of the global attractor for a
non-local one-dimensional quasilinear problem. The strong relation of our
problem with a non-local version of the Chafee-Infante problem allows us to
describe the structure of its attractor. For that, we made use of the Conley
index and the connection matrix theories in order to find geometric information
such as the existence of heteroclinic connections between the equilibria. In
this way, the structure of the attractor is completely described.


  We study a model with Majorana neutrino masses generated through doubly
charged scalars at two-loop level. We give explicit relationships between the
neutrino masses and the same sign dilepton decays of the doubly charged
scalars. In particular, we demonstrate that at the tribimaximal limit of the
neutrino mixings, the absolute neutrino masses and Majorana phases can be
extracted through the measurements of the dilepton modes at colliders.


  The performance of a machine learning model degrades when it is applied to
data from a similar but different domain than the data it has initially been
trained on. To mitigate this domain shift problem, domain adaptation (DA)
techniques search for an optimal transformation that converts the (current)
input data from a source domain to a target domain to learn a domain-invariant
representation that reduces domain discrepancy. This paper proposes a novel
supervised DA based on two steps. First, we search for an optimal
class-dependent transformation from the source to the target domain from a few
samples. We consider optimal transport methods such as the earth mover's
distance, Sinkhorn transport and correlation alignment. Second, we use
embedding similarity techniques to select the corresponding transformation at
inference. We use correlation metrics and higher-order moment matching
techniques. We conduct an extensive evaluation on time-series datasets with
domain shift including simulated and various online handwriting datasets to
demonstrate the performance.


  We show that the number of harmonics of the Wigner function, recently
proposed as a measure of quantum complexity, can be also used to characterize
quantum phase transitions. The non-analytic behavior of this quantity in the
neighborhood of a quantum phase transition is illustrated by means of the Dicke
model and is compared to two well-known measures of the (in)stability of
quantum motion, the quantum Loschmidt echo and the fidelity.


  We study the magnetic field dependence of the dielectric response of large
cylindrical molecules such as nanotubes. When a field-induced level crossing
takes place, an applied electric field causes a linear instead of the usual
quadratic Stark effect. This results in a large dielectric response. Explicit
calculations are performed for doped nanotubes and a rich structure in the real
part of the low-frequency dielectric function $\epsilon'(H)$ is found when a
magnetic field is applied along the cylinder axis. It is suggested that studies
of $\epsilon'(H, T)$ can serve as a spectroscopic tool for the investigation of
large ring-shaped or cylindrical molecules.


  Indian currency coins come in a variety of denominations. Off all the
varieties Rs.1, RS.2, and Rs.5 have similar diameters. Majority of the coin
styles in market circulation for denominations of Rs.1 and Rs.2 coins are
nearly the same except for numerals on its reverse side. If a coin is resting
on its obverse side, the correct denomination is not distinguishable by humans.
Therefore, it was hypothesized that a digital image of a coin resting on its
either size could be classified into its correct denomination by training a
deep neural network model. The digital images were generated by using cheap
cell phone cameras. To find the most suitable deep neural network architecture,
four were selected based on the preliminary analysis carried out for
comparison. The results confirm that two of the four deep neural network models
can classify the correct denomination from either side of a coin with an
accuracy of 97%.


  Quantum deformations of sets of points of the real and the complexified
projective line are constructed. These deformations depend on the deformation
parameter q and certain further parameters \lambda_{ij}. The deformations for
which the subspace of polynomials of degree three has a basis of ordered
monomials are selected. We show that the corresponding algebras of three points
have "polynomiality". Invariant elements which turn out to be cross ratios in
the classical limit are defined. For the special case |\lambda_{ij}| = 1 a
quantum cross ratio with properties similar to the classical case is presented.
As an application a quantum version of the real Euclidean distance is given.


  In this work, we focus on distance-based outliers in a metric space, where
the status of an entity as to whether it is an outlier is based on the number
of other entities in its neighborhood. In recent years, several solutions have
tackled the problem of distance-based outliers in data streams, where outliers
must be mined continuously as new elements become available. An interesting
research problem is to combine the streaming environment with massively
parallel systems to provide scalable streambased algorithms. However, none of
the previously proposed techniques refer to a massively parallel setting. Our
proposal fills this gap and investigates the challenges in transferring
state-of-the-art techniques to Apache Flink, a modern platform for intensive
streaming analytics. We thoroughly present the technical challenges encountered
and the alternatives that may be applied. We show speed-ups of up to 117 (resp.
2076) times over a naive parallel (resp. non-parallel) solution in Flink, by
using just an ordinary four-core machine and a real-world dataset. When moving
to a three-machine cluster, due to less contention, we manage to achieve both
better scalability in terms of the window slide size and the data
dimensionality, and even higher speed-ups, e.g., by a factor of 510. Overall,
our results demonstrate that oulier mining can be achieved in an efficient and
scalable manner. The resulting techniques have been made publicly available as
open-source software.


  Sumner's universal tournament conjecture states that every $(2n-2)$-vertex
tournament should contain a copy of every $n$-vertex oriented tree. If we know
the number of leaves of an oriented tree, or its maximum degree, can we
guarantee a copy of the tree with fewer vertices in the tournament? Due to work
initiated by H\"aggkvist and Thomason (for number of leaves) and K\"uhn,
Mycroft and Osthus (for maximum degree), it is known that improvements can be
made over Sumner's conjecture in some cases, and indeed sometimes an
$(n+o(n))$-vertex tournament may be sufficient.
  In this paper, we give new results on these problems. Specifically, we show
  i) for every $\alpha>0$, there exists $n_0\in\mathbb{N}$ such that, whenever
$n\geqslant n_0$, every $((1+\alpha)n+k)$-vertex tournament contains a copy of
every $n$-vertex oriented tree with $k$ leaves, and
  ii) for every $\alpha>0$, there exists $c>0$ and $n_0\in\mathbb{N}$ such
that, whenever $n\geqslant n_0$, every $(1+\alpha)n$-vertex tournament contains
a copy of every $n$-vertex oriented tree with maximum degree
$\Delta(T)\leqslant cn$.
  Our first result gives an asymptotic form of a conjecture by Havet and
Thomass\'e, while the second improves a result of Mycroft and Naia which
applies to trees with polylogarithmic maximum degree.


  The Painleve first equation can be represented as the equation of
isomonodromic deformation of a Schrodinger equation with a cubic potential. We
introduce a new algorithm for computing the direct monodromy problem for this
Schrodinger equation. The algorithm is based on the geometric theory of
Schrodinger equation due to Nevanlinna


  The interfacial Dzyaloshinksii-Moriya interaction (iDMI) is of great interest
in thin-film magnetism because of its ability to stabilize chiral spin
textures. It can be quantified by investigating the frequency non-reciprocity
of oppositely propagating spin waves. However, as the iDMI is an interface
interaction the relative effect reduces when the films become thicker making
quantification more difficult. Here, we utilize all-electrical Propagating Spin
Wave Spectroscopy (PSWS) to disentangle multiple contributions to spin wave
frequency non-reciprocity to determine the iDMI. This is done by investigating
non-reciprocities across a wide range of magnetic layer thicknesses (from 4 to
26 nm) in Pt/Co/Ir, Pt/Co/Pt, and Ir/Co/Pt stacks. We find the expected sign
change in the iDMI when inverting the stack order, and a negligible iDMI for
the symmetric Pt/Co/Pt. We additionally extract a difference in surface
anisotropies and find a large contribution due to the formation of different
crystalline phases of the Co, which is corroborated using nuclear magnetic
resonance and high-resolution transmission-electron-microscopy measurements.
These insights will open up new avenues to investigate, quantify and
disentangle the fundamental mechanisms governing the iDMI, and pave a way
towards engineered large spin-wave non-reciprocities for magnonic applications.


  LSTM language models have been shown to capture syntax-sensitive grammatical
dependencies such as subject-verb agreement with a high degree of accuracy
(Linzen et al., 2016, inter alia). However, questions remain regarding whether
they do so using spurious correlations, or whether they are truly able to match
verbs with their subjects. This paper argues for the latter hypothesis. Using
layer-wise relevance propagation (Bach et al., 2015), a technique that
quantifies the contributions of input features to model behavior, we show that
LSTM performance on number agreement is directly correlated with the model's
ability to distinguish subjects from other nouns. Our results suggest that LSTM
language models are able to infer robust representations of syntactic
dependencies.


  The reliability prognosis of one-shot devices is drawing increasing attention
because of their wide applicability. The present study aims to determine the
lifetime prognosis of highly durable one-shot device units under a step-stress
accelerated life testing (SSALT) experiment applying a cumulative risk model
(CRM). In an SSALT experiment, CRM retains the continuity of hazard function by
allowing the lag period before the effects of stress change emerge. In an
analysis of such lifetime data, plentiful datasets might have outliers where
conventional methods like maximum likelihood estimation or likelihood-based
Bayesian estimation frequently fail. This work develops a robust estimation
method based on density power divergence in classical and Bayesian frameworks.
The hypothesis is tested by implementing the Bayes factor based on a
robustified posterior. In Bayesian estimation, we exploit Hamiltonian Monte
Carlo, which has certain advantages over the conventional Metropolis-Hastings
algorithms. Further, the influence functions are examined to evaluate the
robust behaviour of the estimators and the Bayes factor. Finally, the
analytical development is validated through a simulation study and a real data
analysis.


  This is the second in a series of papers aiming to test how the mass ($M_{\rm
BH}$), accretion rate ($\dot{M}$) and spin ($a_{*}$) of super massive black
holes (SMBHs) determine the observed properties of type-I active galactic
nuclei (AGN). Our project utilizes a sample of 39 unobscured AGN at
$z\simeq1.55$ observed by VLT/X-shooter, selected to map a large range in
$M_{\rm BH}$ and $L/L_{\rm edd}$ and covers the most prominent UV-optical
(broad) emission lines, including H$\alpha$, H$\beta$, MgII, and CIV. This
paper focuses on single-epoch, "virial" $M_{\rm BH}$ determinations from broad
emission lines and examines the implications of different continuum modeling
approaches in line width measurements. We find that using a "local" power-law
continuum instead of a physically-motivated thin disk continuum leads to only
slight underestimation of the FWHM of the lines and the associated $M_{\rm
BH}\left({\rm FWHM}\right)$. However, the line dispersion $\sigma_{\rm line}$
and associated $M_{\rm BH}\left(\sigma_{\rm line}\right)$ are strongly affected
by the continuum placement and provides less reliable mass estimates than
FWHM-based methods. Our analysis shows that H$\alpha$, H$\beta$ and MgII can be
safely used for virial $M_{\rm BH}$ estimation. The CIV line, on the other
hand, is not reliable in the majority of the cases, this may indicate that the
gas emitting this line is not virialized. While H$\alpha$ and H$\beta$ show
very similar line widths, the mean ${\rm FWHM\left(MgII\right)}$ is about 30%
narrower than ${\rm FWHM\left(H\beta\right)}$. We confirm several recent
suggestions to improve the accuracy in CIV-based mass estimates, relying on
other UV emission lines. Such improvements do not reduce the scatter between
CIV-based and Balmer-line-based mass estimates.


  Suspensions of elongated micelles under shear display complex non-linear
behaviour including shear banding, spatio-temporal oscillatory patterns and
chaotic response. Based on a suitable rheological model [S. M. Fielding and P.
D. Olmsted, Phys. Rev. Lett. 92, 084502 (2004)], we here explore possibilities
to manipulate the dynamical behaviour via closed-loop (feedback) control
involving a time delay $\tau$. The model considered relates the viscoelastic
stress of the system to a structural variable, that is, the length of the
micelles, yielding two time- and space-dependent dynamical variables $\xi_1$,
$\xi_2$. As a starting point we perform a systematic linear stability analysis
of the uncontrolled system for (i) an externally imposed average shear rate and
(ii) an imposed total stress, and compare the results to those from extensive
numerical simulations. We then apply the so-called Pyragas feedback scheme
where the equations of motion are supplemented by a control term of the form
$K\left(a(t)-a(t-\tau)\right)$ with $a$ being a measurable quantity depending
on the rheological protocol. For the choice of an imposed shear rate, the
Pyragas scheme for the total stress reduces to a non-diagonal scheme
concentrating on the viscoelastic stress. Focusing on parameters close to a
Hopf bifurcation, where the uncontrolled system displays oscillatory states as
well as hysteresis in the shear rate controlled protocol, we demonstrate that
(local) Pyragas control leads to a full stabilization to the steady state
solution of the total stress, while a global control scheme does not work. In
contrast, for the case of imposed total stress, global Pyragas control fully
stabilizes the system. In both cases, the control does not change the space of
solutions, rather it selects the steady state solutions out of the existing
solutions. This underlines the non-invasive character of the Pyragas scheme.


  In this paper, we associate, to any submartingale of class $(\Sigma)$,
defined on a filtered probability space $(\Omega, \mathcal{F}, \mathbb{P},
(\mathcal{F}_t)_{t \geq 0})$, which satisfies some technical conditions, a
$\sigma$-finite measure $\mathcal{Q}$ on $(\Omega, \mathcal{F})$, such that for
all $t \geq 0$, and for all events $\Lambda_t
  \in \mathcal{F}_t$: $$ \mathcal{Q} [\Lambda_t, g\leq t] =
\mathbb{E}_{\mathbb{P}} [\mathds{1}_{\Lambda_t} X_t]$$ where $g$ is the last
hitting time of zero of the process $X$. This measure $\mathcal{Q}$ has already
been defined in several particular cases, some of them are involved in the
study of Brownian penalisation, and others are related with problems in
mathematical finance. More precisely, the existence of $\mathcal{Q}$ in the
general case solves a problem stated by D. Madan, B. Roynette and M. Yor, in a
paper studying the link between Black-Scholes formula and last passage times of
certain submartingales. Moreover, the equality defining $\mathcal{Q}$ remains
true if one replaces the fixed time $t$ by any bounded stopping time. This
generalization can be viewed as an extension of Doob's optional stopping
theorem.


  Semiclassical approximations are implemented in the calculation of position
and width of low energy resonances for radial barriers. The numerical
integrations are delimited by t/T<<8, with t the period of a classical particle
in the barrier trap and T the resonance lifetime. These energies are used in
the construction of `haired' short range potentials as the supersymmetric
partners of a given radial barrier. The new potentials could be useful in the
study of the transient phenomena which give rise to the Moshinsky's diffraction
in time.


  In this paper, we study a system of two Rossler oscillators coupled through a
time-varying link, periodically switching between two values. We analyze the
system behavior with respect to the frequency of the switching. By applying an
averaging technique under the hypothesis of a high switching frequency, we find
that although each value of the coupling does not produce synchronization,
switching between the two at a high frequency stabilizes the synchronization
manifold. However, we also find windows of synchronization below the value
predicted by this technique, and we develop a master stability function to
explain the appearance of these windows. Spectral properties of the system are
a useful tool for understanding the dynamical properties and the
synchronization failure in some intervals of the switching frequency. Numerical
and experimental results in agreement with the analysis are presented.


  The current approach of information hiding based on deep learning model can
not directly use the original data as carriers, which means the approach can
not make use of the existing data in big data to hiding information. We
proposed a novel method of information hiding in big data based on deep
learning. Our method uses the existing data in big data as carriers and uses
deep learning models to hide and extract secret messages in big data. The data
amount of big data is unlimited and thus the data amount of secret messages
hided in big data can also be unlimited. Before opponents want to extract
secret messages from carriers, they need to find the carriers, however finding
out the carriers from big data is just like finding out a box from the sea.
Deep learning models are well known as deep black boxes in which the process
from the input to the output is very complex, and thus the deep learning model
for information hiding is almost impossible for opponents to reconstruct. The
results also show that our method can hide secret messages safely,
conveniently, quickly and with no limitation on the data amount.


  To study transport properties of complex networks, we analyze the equivalent
conductance $G$ between two arbitrarily chosen nodes of random scale-free
networks with degree distribution $P(k)\sim k^{-\lambda}$ in which each link
has the same unit resistance. We predict a broad range of values of $G$, with a
power-law tail distribution $\Phi_{\rm SF}(G)\sim G^{-g_G}$, where
$g_G=2\lambda -1$, and confirm our predictions by simulations. The power-law
tail in $\Phi_{\rm SF}(G)$ leads to large values of $G$, thereby significantly
improving the transport in scale-free networks, compared to Erd\H{o}s-R\'{e}nyi
random graphs where the tail of the conductivity distribution decays
exponentially. Based on a simple physical ``transport backbone'' picture we
show that the conductances are well approximated by $ck_Ak_B/(k_A+k_B)$ for any
pair of nodes $A$ and $B$ with degrees $k_A$ and $k_B$. Thus, a single
parameter $c$ characterizes transport on scale-free networks.


  The inner moons of Jupiter and Saturn migrate outwards due to tidal energy
dissipation within the planets, the details of which remain poorly understood.
We demonstrate that resonance locking between moons and internal oscillation
modes of the planet can produce rapid tidal migration. Resonance locking arises
due to the internal structural evolution of the planet and typically produces
an outward migration rate comparable to the age of the solar system. Resonance
locking predicts a similar migration timescale but a different effective tidal
quality factor $Q$ governing the migration of each moon. It also predicts
nearly constant migration timescales a function of semi-major axis, such that
effective $Q$ values were larger in the past. Recent measurements of Jupiter
and Saturn's moon systems find effective $Q$ values that are smaller than
expected (and are different between moons), and which correspond to migration
timescales of $\sim$10 Gyr. If confirmed, the measurements are broadly
consistent with resonance locking as the dominant source of tidal dissipation
in Jupiter and Saturn. Resonance locking also provides solutions to several
problems posed by current measurements: it naturally explains the exceptionally
small $Q$ governing Rhea's migration, it allows the large heating rate of
Enceladus to be achieved in an equilibrium eccentricity configuration, and it
resolves evolutionary problems arising from present-day migration/heating
rates.


  Given prior knowledge of the spectral statistics, the SNR of optical
waveforms can be manipulated in a reversible manner. We introduce this concept
and discuss its potential application to encryption and context-aware detection
of weak signals in noisy environments. The same technology performs single shot
sparse sampling for optical data compression.


  We have measured the normalized gradient of the Casimir force between
Au-coated surfaces of the sphere and the plate and equivalent Casimir pressure
between two parallel Au plates at T=77K. These measurements have been performed
by means of dynamic force microscope adapted for operating at low temperatures
in the frequency shift technique. It was shown that the measurement results at
T=77K are in a very good agreement with those at T=300K and with computations
at T=77K using both theoretical approaches to the thermal Casimir force
proposed in the literature. No thermal effect in the Casimir pressure was
observed in the limit of experimental errors with the increase of temperature
from T=77K to T=300K. Taking this into account, we have discussed the possible
role of patch potentials in the comparison between measured and calculated
Casimir pressures.


  Local environment of fluorescent dyes could strongly affect emission dynamics
of the latter. In particular, both signal intensities and emission lifetimes
are highly sensitive to solvent temperatures. Here, temperature-dependent
behavior Rhodamine B fluorescence in water and ethanol solutions was
experimentally investigated. Phase transition point of liquid water to ice was
shown to have a dramatic impact on both in intensity (30-fold drop) and in
lifetime (from 2.68ns down to 0.13ns) of the dye luminescence along with the
spectral shift of spectral maxima from 590 to 625nm. At the same time, ethanol
solvent does not lead any similar behavior. The reported results and approaches
enable further investigations of dye-solvent interactions and studies of
physical properties of liquids at phase transition points.


  We give short, closure-theoretic proofs for uniform bounds on the growth of
symbolic powers of ideals in regular rings. The author recently proved these
bounds in mixed characteristic using various versions of perfectoid/big
Cohen-Macaulay test ideals, with special cases obtained earlier by Ma and
Schwede. In mixed characteristic, we instead use Heitmann's full extended plus
(epf) closure, Jiang's weak epf (wepf) closure, and R.G.'s results on closure
operations that induce big Cohen-Macaulay algebras. Our strategy also applies
to any Dietz closure satisfying R.G.'s algebra axiom and a
Brian\c{c}on-Skoda-type theorem, and hence yields new proofs of these results
on uniform bounds on the growth of symbolic powers of ideals in regular rings
of all characteristics. In equal characteristic, these results on symbolic
powers are due to Ein-Lazarsfeld-Smith, Hochster-Huneke, Takagi-Yoshida, and
Johnson.


  The ability of Language Models (LMs) to understand natural language makes
them a powerful tool for parsing human instructions into task plans for
autonomous robots. Unlike traditional planning methods that rely on
domain-specific knowledge and handcrafted rules, LMs generalize from diverse
data and adapt to various tasks with minimal tuning, acting as a compressed
knowledge base. However, LMs in their standard form face challenges with
long-horizon tasks, particularly in partially observable multi-agent settings.
We propose an LM-based Long-Horizon Planner for Multi-Agent Robotics (LLaMAR),
a cognitive architecture for planning that achieves state-of-the-art results in
long-horizon tasks within partially observable environments. LLaMAR employs a
plan-act-correct-verify framework, allowing self-correction from action
execution feedback without relying on oracles or simulators. Additionally, we
present MAP-THOR, a comprehensive test suite encompassing household tasks of
varying complexity within the AI2-THOR environment. Experiments show that
LLaMAR achieves a 30% higher success rate compared to other state-of-the-art
LM-based multi-agent planners.


  The operator space $\text{OUMD}$ property was introduced by Pisier in the
context of vector-valued noncommutative $L_p$-spaces. It is an open problem
whether the column Hilbert space has this property. Based on some complex
interpolation techniques, we are able to relate this problem to the study of
the $\text{OUMD}_q$ property for non-commutative $L_p$-spaces.


  In the manuscript arXiv:2210.01114, Dodge and co-authors discuss the
influence of pump-probe profile deformations on the reconstructed
non-equilibrium optical conductivity of K$_3$C$_{60}$. They state that when
pump-induced saturation of the probe response is taken into account, the
reconstructed optical properties are not superconducting-like, as was claimed
in a number of experimental reports by our group. We show here that the
conclusion reached by Dodge et al. is unjustified. In fact, independent of the
specific model, including the problematic saturation profile proposed by the
authors, the reconstructed optical properties are those of a finite temperature
superconductor. The true fingerprint of superconductivity, which is the
$1/\omega$ divergence of the imaginary conductivity, $\sigma_{2}(\omega)$, is
retained and is virtually independent of the chosen model. The only
model-dependent feature is the degree of gapping in $\sigma_{1}(\omega)$. In
all cases the extracted optical properties reflect the presence of residual
quasiparticles, which at finite temperatures are inevitably present alongside
the superfluid.


  We formulate and study a novel multi-armed bandit problem called the
qualitative dueling bandit (QDB) problem, where an agent observes not numeric
but qualitative feedback by pulling each arm. We employ the same regret as the
dueling bandit (DB) problem where the duel is carried out by comparing the
qualitative feedback. Although we can naively use classic DB algorithms for
solving the QDB problem, this reduction significantly worsens the
performance---actually, in the QDB problem, the probability that one arm wins
the duel over another arm can be directly estimated without carrying out actual
duels. In this paper, we propose such direct algorithms for the QDB problem.
Our theoretical analysis shows that the proposed algorithms significantly
outperform DB algorithms by incorporating the qualitative feedback, and
experimental results also demonstrate vast improvement over the existing DB
algorithms.


  While various knowledge distillation (KD) methods in CNN-based detectors show
their effectiveness in improving small students, the baselines and recipes for
DETR-based detectors are yet to be built. In this paper, we focus on the
transformer decoder of DETR-based detectors and explore KD methods for them.
The outputs of the transformer decoder lie in random order, which gives no
direct correspondence between the predictions of the teacher and the student,
thus posing a challenge for knowledge distillation. To this end, we propose
MixMatcher to align the decoder outputs of DETR-based teachers and students,
which mixes two teacher-student matching strategies, i.e., Adaptive Matching
and Fixed Matching. Specifically, Adaptive Matching applies bipartite matching
to adaptively match the outputs of the teacher and the student in each decoder
layer, while Fixed Matching fixes the correspondence between the outputs of the
teacher and the student with the same object queries, with the teacher's fixed
object queries fed to the decoder of the student as an auxiliary group.
  Based on MixMatcher, we build \textbf{D}ecoder \textbf{D}istillation for
\textbf{DE}tection \textbf{TR}ansformer (D$^3$ETR), which distills knowledge in
decoder predictions and attention maps from the teachers to students. D$^3$ETR
shows superior performance on various DETR-based detectors with different
backbones. For example, D$^3$ETR improves Conditional DETR-R50-C5 by
$\textbf{7.8}/\textbf{2.4}$ mAP under $12/50$ epochs training settings with
Conditional DETR-R101-C5 as the teacher.


  The advent of Moir\'e materials has galvanized interest in the nature of
charge carriers in topological bands. In contrast to conventional materials
where charge carriers are electron-like quasiparticles, topological bands allow
for more exotic possibilities where charge is carried by nontrivial topological
textures, such as skyrmions. However, the real space description of skyrmions
is ill-suited to address the limit of small or `baby' skyrmions which consist
of an electron and a few spin flips. Here, we study the formation of the
smallest skyrmions -- spin polarons, formed as bound states of an electron and
a spin flip -- in Chern ferromagnets. We show that, quite generally, there is
an attraction between an electron and a spin flip that is purely topological in
origin and of $p$-wave symmetry, which promotes the formation of spin polarons.
Applying our results to the topological bands of twisted bilayer graphene, we
identify a range of parameters where spin polarons are formed and are lower in
energy than electrons. In particular, spin polarons are found to be
energetically cheaper on doping correlated insulators at integer fillings
towards charge neutrality, consistent with the absence of quantum oscillations
and the rapid onset of flavor polarization (cascade) transition in this regime.
Our study sets the stage for pairing of spin polarons, helping bridge skyrmion
pairing scenarios and momentum space approaches to superconductivity.


  High-energy particle physics experiments allow for the possible existence of
a new light, very weakly coupled, neutral gauge boson (the U boson). This one
permits for light (spin-1/2 or spin-0) particles to be acceptable Dark Matter
candidates, by inducing sufficient (stronger than weak) annihilation cross
sections into e+e-. They could be responsible for the bright 511 keV gamma ray
line observed by INTEGRAL from the galactic bulge.
  Such a new interaction may have important consequences, especially at lower
energies. Parity-violation atomic-physics experiments provide strong
constraints on such a U boson, if its couplings to quarks and electrons violate
parity. With the constraints coming from an unobserved axionlike behaviour of
this particle, they privilegiate a pure vector coupling of the U boson to
quarks and leptons, unless the corresponding symmetry is broken sufficiently
above the electroweak scale.


  Consider a diffusion-free passive scalar $\theta$ being mixed by an
incompressible flow $u$ on the torus $\mathbb{T}^d$. Our aim is to study how
well this scalar can be mixed under an enstrophy constraint on the advecting
velocity field.Our main result shows that the mix-norm
($||\theta(t)||_{H^{-1}}$) is bounded below by an exponential function of time.
The exponential decay rate we obtain is not universal and depends on the size
of the support of the initial data. We also perform numerical simulations and
confirm that the numerically observed decay rate scales similarly to the
rigorous lower bound, at least for a significant initial period of time. The
main idea behind our proof is to use recent work of Crippa and DeLellis ('08)
making progress towards the resolution of Bressan's rearrangement cost
conjecture.


  The Microsoft TerraServer stores aerial and satellite images of the earth in
a SQL Server Database served to the public via the Internet. It is the world's
largest atlas, combining five terabytes of image data from the United States
Geodetic Survey, Sovinformsputnik, and Encarta Virtual Globe. Internet browsers
provide intuitive spatial and gazetteer interfaces to the data. The TerraServer
is also an E-Commerce application. Users can buy the right to use the imagery
using Microsoft Site Servers managed by the USGS and Aerial Images. This paper
describes the TerraServer's design and implementation.


  This work, dealt with the classical mean value theorem and took advantage of
it in the fractional calculus. The concept of a fractional critical point is
introduced. Some sufficient conditions for the existence of a critical point is
studied and an illustrative example rele- vant to the concept of the time
dilation effect is given. The present paper also includes, some connections
between convexity (and monotonicity) with fractional derivative in the
Riemann-Liouville sense.


  The structure of the 4-point N=1 super-conformal blocks in the Ramond sector
is analyzed. The elliptic recursion relations for these blocks are derived.


  Electron-neutrino charged-current interactions with xenon nuclei were modeled
in the nEXO neutrinoless double-beta decay detector (~5-tonne, 90%
${}^{136}$Xe, 10% ${}^{134}$Xe) to evaluate its sensitivity to supernova
neutrinos. Predictions for event rates and detectable signatures were modeled
using the MARLEY event generator. We find good agreement between MARLEY's
predictions and existing theoretical calculations of the inclusive cross
sections at supernova neutrino energies. The interactions modeled by MARLEY
were simulated within the nEXO simulation framework and were run through an
example reconstruction algorithm to determine the detector's efficiency for
reconstructing these events. The simulated data, incorporating the detector
response, were used to study the ability of nEXO to reconstruct the incident
electron-neutrino spectrum and these results were extended to a larger xenon
detector of the same isotope enrichment. We estimate that nEXO will be able to
observe electron-neutrino interactions with xenon from supernovae as far as 5
to 8 kpc from earth, while the ability to reconstruct incident
electron-neutrino spectrum parameters from observed interactions in nEXO is
limited to closer supernovae.