  The study of molecular polaritons beyond simple quantum emitter ensemble
models (e.g., Tavis-Cummings) is challenging due to the large dimensionality of
these systems (the number of molecular emitters is $N\approx 10^{6}-10^{10}$)
and the complex interplay of molecular electronic and nuclear degrees of
freedom. This complexity constraints existing models to either coarse-grain the
rich physics and chemistry of the molecular degrees of freedom or artificially
limit the description to a small number of molecules. In this work, we exploit
permutational symmetries to drastically reduce the computational cost of
\textit{ab-initio} quantum dynamics simulations for large $N$. Furthermore, we
discover an emergent hierarchy of timescales present in these systems, that
justifies the use of an \textit{effective} single molecule to approximately
capture the dynamics of the entire ensemble, an approximation that becomes
exact as $N\rightarrow \infty$. We also systematically derive finite $N$
corrections to the dynamics, and show that addition of $k$ extra effective
molecules is enough to account for phenomena whose rates scale as
$\mathcal{O}(N^{-k})$. Based on this result, we discuss how to seamlessly
modify existing single-molecule strong coupling models to describe the dynamics
of the corresponding ensemble, as well as the crucial differences in phenomena
predicted by each model. We call this approach Collective dynamics Using
Truncated Equations (CUT-E), benchmark it against well-known results of
polariton relaxation rates, and apply it to describe a universal
cavity-assisted energy funneling mechanism between different molecular species.
Beyond being a computationally efficient tool, this formalism provides an
intuitive picture for understanding the role of bright and dark states in
chemical reactivity, necessary to generate robust strategies for polariton
chemistry.


  The equations of motion of nonspinning compact binary systems at the third
post-Newtonian (PN) order in massless scalar-tensor theories have recently been
obtained. In the present paper, we complete this work by computing at 3PN order
the ten integrals of motion together with the equations of motion in the
center-of-mass frame. We then perform the reduction of the center-of-mass
equations to quasi-circular orbits and determine the conserved energy and
angular momentum for circular orbits.


  Relativistically energetic, non-thermal population of electrons can give rise
to unique CMB spectral distortion signatures which can be significantly
different from thermal Sunyaev-Zeldovich signal or $y$-distortion. These
signatures depend upon the spectrum of non-thermal electrons, therefore, a
detection can inform us about the existence and abundance of non-thermal
electrons in our universe. Using public CMB maps and data, we derive upper
limits on non-thermal $y$-parameter for a relativistic, power-law electron
distribution. With future CMB experiments, we may be in a position to detect or
put significantly tighter constraints on these signals which can affect our
understanding of non-thermal electron distributions in our universe.


  String theory has been initially derived from motivations coming from strong
interaction phenomenology,but its application faced deep conceptual and
practical difficulties. The strong interactions found their theoretical
foundation elsewhere, namely on QCD, the quantum gauge field theory of quarks
and gluons. Recently, the Gauge/Gravity correspondence allowed to initiate a
reformulation of the connection between strings and gauge field theories,
avoiding some of the initial drawbacks and opening the way to new insights on
the gauge theory at strong coupling and eventually QCD. Among others, the
recent applications of the Gauge/Gravity correspondence to the formation of the
QGP, the quark-gluon plasma, in heavy-ion reactions seem to provide a
physically interesting insight on phenomenological features of the reactions.
In these lectures we will give a simplified introduction to those aspects of
string theory which, at the origin and in the recent developments, are
connected to strong interactions, for those students which are starting to
learn QCD and QGP physics from an experimental or phenomenological point of
view.


  Employing a 40-kW radio-frequency transmitter just west of Delta, UT, and
operating at 54.1 MHz, the TARA (Telescope Array RAdar) experiment seeks radar
detection of extensive air showers (EAS) initiated by ultra-high energy cosmic
rays (UHECR). For UHECR with energies in excess of $10^{19}$ eV, the
Doppler-shifted "chirps" resulting from EAS shower core radar reflections
should be observable above background (dominantly galactic) at distances of
tens of km from the TARA transmitter. In order to stereoscopically reconstruct
cosmic ray chirps, two remote, autonomous self-powered receiver stations have
been deployed. Each remote station (RS) combines both low power consumption as
well as low cost. Triggering logic, the powering and communication systems, and
some specific details of hardware components are discussed.


  We study the tensor consistency relation in models of axion inflation with an
SU(2) gauge field. In the tensor sector, we have two spin-2 modes, the standard
gravity waves and the tensor perturbations of the SU(2) gauge field which
sources the gravity waves at the linear level. Interestingly enough, we find
that the gravity waves are adiabatic and Maldacena's consistency relation
including a long wavelength gravity wave holds in this setup. However, since it
is partially polarized, there is a difference between the (n+1)-point functions
with different helicity states proportional to the ratio of the gauge field
density to the total density. These chiral n-point functions are the imprints
of the SU(2) gauge field on the primordial cosmological perturbations and a
robust observational feature of their contribution to the physics of inflation.


  This research was conducted to develop a method to identify voice utterance.
For voice utterance that encounters change caused by aging factor, with the
interval of 10 to 25 years. The change of voice utterance influenced by aging
factor might be extracted by MFCC (Mel Frequency Cepstrum Coefficient).
However, the level of the compatibility of the feature may be dropped down to
55%. While the ones which do not encounter it may reach 95%. To improve the
compatibility of the changing voice feature influenced by aging factor, then
the method of the more specific feature extraction is developed: which is by
separating the voice into several channels, suggested as MFCC multichannel,
consisting of multichannel 5 filterbank (M5FB), multichannel 2 filterbank
(M2FB) and multichannel 1 filterbank (M1FB). The result of the test shows that
for model M5FB and M2FB have the highest score in the level of compatibility
with 85% and 82% with 25 years interval. While model M5FB gets the highest
score of 86% for 10 years time interval.


  Terrestrial exoplanets orbiting within or near their host stars' habitable
zone are potentially apt for life. It has been proposed that time-series
measurements of reflected starlight from such planets will reveal their
rotational period, main surface features and some atmospheric information. From
imagery obtained with the Akatsuki spacecraft, here we show that Venus'
brightness at 283, 365, and 2020 nm is modulated by one or both of two periods
of 3.7 and 4.6 days, and typical amplitudes <10% but occasional events of
20-40%. The modulations are unrelated to the solid-body rotation; they are
caused by planetary-scale waves superimposed on the super-rotating winds. Here
we propose that two modulation periods whose ratio of large-to-small values is
not an integer number imply the existence of an atmosphere if detected at an
exoplanet, but it remains ambiguous whether the atmosphere is optically thin or
thick, as for Earth or Venus respectively. Multi-wavelength and long temporal
baseline observations may be required to decide between these scenarios.
Ultimately, Venus represents a false positive for interpretations of brightness
modulations of terrestrial exoplanets in terms of surface features.


  Reverse-mode automatic differentiation (AD) suffers from the issue of having
too much space overhead to trace back intermediate computational states for
back-propagation. The traditional method to trace back states is called
checkpointing that stores intermediate states into a global stack and restore
state through either stack pop or re-computing. The overhead of stack
manipulations and re-computing makes the general purposed (not tensor-based) AD
engines unable to meet many industrial needs. Instead of checkpointing, we
propose to use reverse computing to trace back states by designing and
implementing a reversible programming eDSL, where a program can be executed
bi-directionally without implicit stack operations. The absence of implicit
stack operations makes the program compatible with existing compiler features,
including utilizing existing optimization passes and compiling the code as GPU
kernels. We implement AD for sparse matrix operations and some machine learning
applications to show that our framework has the state-of-the-art performance.


  The propagation of polarization-entangled states of light through fluctuating
loss channels in the turbulent atmosphere is studied, including the situation
of strong losses. We consider violations of Bell inequalities by light, emitted
by a parametric down-conversion source, after transmission through the
turbulent atmosphere. It is shown by analytical calculations, that in the
presence of background radiation and dark counts, fluctuating loss channels may
preserve entanglement properties of light even better than standard loss
channels, when postselected measurements are applied.


  We introduce hydra (hyperbolic distance recovery and approximation), a new
method for embedding network- or distance-based data into hyperbolic space. We
show mathematically that hydra satisfies a certain optimality guarantee: It
minimizes the `hyperbolic strain' between original and embedded data points.
Moreover, it recovers points exactly, when they are located on a hyperbolic
submanifold of the feature space. Testing on real network data we show that the
embedding quality of hydra is competitive with existing hyperbolic embedding
methods, but achieved at substantially shorter computation time. An extended
method, termed hydra+, outperforms existing methods in both computation time
and embedding quality.


  We derive the equation for the quasi-normal modes corresponding to the scalar
excitation of a black hole moving away in the fifth dimension. This geometry is
the AdS/CFT dual of a boost-invariant expanding perfect fluid in N=4 SUSY
Yang-Mills theory at large proper-time. On the gauge-theory side, the dominant
solution of the equation describes the decay back to equilibrium of a scalar
excitation of the perfect fluid. Its characteristic proper-time can be
interpreted as a thermalization time of the perfect fluid, which is a universal
(and numerically small) constant in units of the unique scale of the problem.
This may provide a new insight on the short thermalization-time puzzle
encountered in heavy-ion collision phenomenology. A nontrivial scaling
behaviour in proper-time is obtained which can be interpreted in terms of a
slowly varying adiabatic approximation.


  We exhibit some new families of cyclotomic fields which have non-trivial plus
parts of their class numbers. We also prove the $3$ - divisibility of the plus
part of the class number of another family consisting of infinitely many
cyclotomic fields. At the end, we provide some numerical examples supporting
our results.


  Priors allow us to robustify inference and to incorporate expert knowledge in
Bayesian hierarchical models. This is particularly important when there are
random effects that are hard to identify based on observed data. The challenge
lies in understanding and controlling the joint influence of the priors for the
variance parameters, and makemyprior is an R package that guides the
formulation of joint prior distributions for variance parameters. A joint prior
distribution is constructed based on a hierarchical decomposition of the total
variance in the model along a tree, and takes the entire model structure into
account. Users input their prior beliefs or express ignorance at each level of
the tree. Prior beliefs can be general ideas about reasonable ranges of
variance values and need not be detailed expert knowledge. The constructed
priors lead to robust inference and guarantee proper posteriors. A graphical
user interface facilitates construction and assessment of different choices of
priors through visualization of the tree and joint prior. The package aims to
expand the toolbox of applied researchers and make priors an active component
in their Bayesian workflow.


  Hallucination detection in Large Language Models (LLMs) is crucial for
ensuring their reliability. This work presents our participation in the CLEF
ELOQUENT HalluciGen shared task, where the goal is to develop evaluators for
both generating and detecting hallucinated content. We explored the
capabilities of four LLMs: Llama 3, Gemma, GPT-3.5 Turbo, and GPT-4, for this
purpose. We also employed ensemble majority voting to incorporate all four
models for the detection task. The results provide valuable insights into the
strengths and weaknesses of these LLMs in handling hallucination generation and
detection tasks.


  In contrast to a widely held opinion, the three-body problem has an analytic
solution. This solution was found in 1909 by Sundman. The basic ideas behind it
and its history are presented.
  -----
  Contrairement \`a une opinion largement r\'epandue, le probl\`eme des trois
corps poss\`ede une solution analytique. Cette solution fut d\'ecouverte en
1909 par Sundman. Nous pr\'esentons dans cet article les id\'ees de base et
l'histoire de cette solution.
  -----
  Entgegen einer weitverbreiteten Meinung ist das Dreik\"orperproblem
analytisch l\"osbar. Diese L\"osung wurde 1909 von Sundman gefunden. Die ihr
zugrundeliegenden Ideen und ihre Geschichte werden in einfacher Form
dargestellt.


  It is known that any $n$-variable function on a finite prime field of
characteristic $p$ can be expressed as a polynomial over the same field with at
most $p^n$ monomials. However, it is not obvious to determine the polynomial
for a given concrete function. In this paper, we study the concrete polynomial
expressions of the carries in addition and multiplication of $p$-ary integers.
For the case of addition, our result gives a new family of symmetric
polynomials, which generalizes the known result for the binary case $p = 2$
where the carries are given by elementary symmetric polynomials. On the other
hand, for the case of multiplication of $n$ single-digit integers, we give a
simple formula of the polynomial expression for the carry to the next digit
using the Bernoulli numbers, and show that it has only $(n+1)(p-1)/2 + 1$
monomials, which is significantly fewer than the worst-case number $p^n$ of
monomials for general functions. We also discuss applications of our results to
cryptographic computation on encrypted data.


  In this paper, we will use a BIonic solution for analyzing the holographic
cosmology. A BIonic solution is a configuration of a D3-brane and an
anti-D3-brane connected by a wormhole, and holographic cosmology is a recent
proposal to explain cosmic expansion by using the holographic principle. In our
model, a BIonic configuration will be produced by the transition of fundamental
black strings. The formation of a BIonic configuration will cause inflation. As
the D3-brane moves away from the anti-D3-brane, The wormhole will get
annihilated, and the inflation will end with the annihilation of this wormhole.
However, it is possible for a D3-brane to collide with an anti-D3-brane. Such a
collision will occur if the distance between the D3-brane and the anti-D3-brane
reduces, and this will create tachyonic states. We will demonstrate that these
tachyonic states will lead to the formation of a new wormhole, and this will
cause acceleration of the universe before such a collision.


  The projected energy correlator measures the energy deposited in multiple
detectors as a function of the largest angular distance $x_L = (1 -
\cos\chi_L)/2$ between detectors. The collinear limit $x_L\to 0$ of the
projected energy correlator is particularly interesting for understanding the
jet-substructures, while the large logarithms of $x_L$ could potentially spoil
the perturbation theory and must be resummed. As a necessary ingredient for its
resummation at next-to-next-to-leading logarithmic (NNLL) accuracy, we
calculate the two-loop jet functions for the projected three-point energy
correlator (E3C), using direct integration method and the parameter space
Integration-by-Part (IBP) method. We then present the NNLL resummation for
$e^+e^-$ annihilation and an approximate NNLL resummation for $pp\rightarrow
jj$ process, where the two-loop hard constant is estimated in the latter case.
The convergence is improved and the hadronization effect in the collinear limit
is suppressed when considering the ratio of E3C distribution to two-point
energy-energy correlator (EEC). Our results show potential in precision
determination of strong coupling constant using energy correlators from both
$e^+e^-$ data and $pp$ data.


  In this article, we introduce the concept of samplets by transferring the
construction of Tausch-White wavelets to the realm of data. This way we obtain
a multilevel representation of discrete data which directly enables data
compression, detection of singularities and adaptivity. Applying samplets to
represent kernel matrices, as they arise in kernel based learning or Gaussian
process regression, we end up with quasi-sparse matrices. By thresholding small
entries, these matrices are compressible to O(N log N) relevant entries, where
N is the number of data points. This feature allows for the use of fill-in
reducing reorderings to obtain a sparse factorization of the compressed
matrices. Besides the comprehensive introduction to samplets and their
properties, we present extensive numerical studies to benchmark the approach.
Our results demonstrate that samplets mark a considerable step in the direction
of making large data sets accessible for analysis.


  We evaluate the extent to which newly detected exoplanetary systems
containing at least four planets adhere to a generalized Titius-Bode (TB)
relation. We find that the majority of exoplanet systems in our sample adhere
to the TB relation to a greater extent than the Solar System does, particularly
those detected by the Kepler mission. We use a generalized TB relation to make
a list of predictions for the existence of 141 additional exoplanets in 68
multiple-exoplanet systems: 73 candidates from interpolation, 68 candidates
from extrapolation. We predict the existence of a low-radius (R < 2.5 Earth
Radii) exoplanet within the habitable zone of KOI-812 and that the average
number of planets in the habitable zone of a star is 1-2. The usefulness of the
TB relation and its validation as a tool for predicting planets will be
partially tested by upcoming Kepler data releases.


  We prove that any finite collection of polygons of equal area has a common
hinged dissection. That is, for any such collection of polygons there exists a
chain of polygons hinged at vertices that can be folded in the plane
continuously without self-intersection to form any polygon in the collection.
This result settles the open problem about the existence of hinged dissections
between pairs of polygons that goes back implicitly to 1864 and has been
studied extensively in the past ten years. Our result generalizes and indeed
builds upon the result from 1814 that polygons have common dissections (without
hinges). We also extend our common dissection result to edge-hinged dissections
of solid 3D polyhedra that have a common (unhinged) dissection, as determined
by Dehn's 1900 solution to Hilbert's Third Problem. Our proofs are
constructive, giving explicit algorithms in all cases. For a constant number of
planar polygons, both the number of pieces and running time required by our
construction are pseudopolynomial. This bound is the best possible, even for
unhinged dissections. Hinged dissections have possible applications to
reconfigurable robotics, programmable matter, and nanomanufacturing.


  Parallel Global Optimization Algorithms (PGOA) provide an efficient way of
dealing with hard optimization problems. One method of parallelization of GOAs
that is frequently applied and commonly found in the contemporary literature is
the so-called Island Model (IM). In this paper we analyze the impact of the
migration topology on the performance of a PGOA which uses the Island Model. In
particular we consider parallel Differential Evolution and Simulated Annealing
with Adaptive Neighborhood and draw first conclusions that emerge from the
conducted experiments.


  We define and study the completely strongly porous at 0 subsets of R^{+}.
Several characterizations of these subsets are obtained, among them the
description via an universal property and structural one.


  In public roads, autonomous vehicles (AVs) face the challenge of frequent
interactions with human-driven vehicles (HDVs), which render uncertain driving
behavior due to varying social characteristics among humans. To effectively
assess the risks prevailing in the vicinity of AVs in social interactive
traffic scenarios and achieve safe autonomous driving, this article proposes a
social-suitable and safety-sensitive trajectory planning (S4TP) framework.
Specifically, S4TP integrates the Social-Aware Trajectory Prediction (SATP) and
Social-Aware Driving Risk Field (SADRF) modules. SATP utilizes Transformers to
effectively encode the driving scene and incorporates an AV's planned
trajectory during the prediction decoding process. SADRF assesses the expected
surrounding risk degrees during AVs-HDVs interactions, each with different
social characteristics, visualized as two-dimensional heat maps centered on the
AV. SADRF models the driving intentions of the surrounding HDVs and predicts
trajectories based on the representation of vehicular interactions. S4TP
employs an optimization-based approach for motion planning, utilizing the
predicted HDVs'trajectories as input. With the integration of SADRF, S4TP
executes real-time online optimization of the planned trajectory of AV within
lowrisk regions, thus improving the safety and the interpretability of the
planned trajectory. We have conducted comprehensive tests of the proposed
method using the SMARTS simulator. Experimental results in complex social
scenarios, such as unprotected left turn intersections, merging, cruising, and
overtaking, validate the superiority of our proposed S4TP in terms of safety
and rationality. S4TP achieves a pass rate of 100% across all scenarios,
surpassing the current state-of-the-art methods Fanta of 98.25% and
Predictive-Decision of 94.75%.


  We review the observational evidence for geodetic precession in PSR B1913+16
and present the latest observations and results from modelling the system
geometry and beam.


  Given a finite point set $P \subset \mathbb{R}^d$, a $k$-ary semi-algebraic
relation $E$ on $P$ is the set of $k$-tuples of points in $P$, which is
determined by a finite number of polynomial equations and inequalities in $kd$
real variables. The description complexity of such a relation is at most $t$ if
the number of polynomials and their degrees are all bounded by $t$. The Ramsey
number $R^{d,t}_k(s,n)$ is the minimum $N$ such that any $N$-element point set
$P$ in $\mathbb{R}^d$ equipped with a $k$-ary semi-algebraic relation $E$, such
that $E$ has complexity at most $t$, contains $s$ members such that every
$k$-tuple induced by them is in $E$, or $n$ members such that every $k$-tuple
induced by them is not in $E$.
  We give a new upper bound for $R^{d,t}_k(s,n)$ for $k\geq 3$ and $s$ fixed.
In particular, we show that for fixed integers $d,t,s$, $R^{d,t}_3(s,n) \leq
2^{n^{o(1)}},$ establishing a subexponential upper bound on $R^{d,t}_3(s,n)$.
This improves the previous bound of $2^{n^C}$ due to Conlon, Fox, Pach,
Sudakov, and Suk, where $C$ is a very large constant depending on $d,t,$ and
$s$. As an application, we give new estimates for a recently studied
Ramsey-type problem on hyperplane arrangements in $\mathbb{R}^d$. We also study
multi-color Ramsey numbers for triangles in our semi-algebraic setting,
achieving some partial results.


  In 1974 Orin Chein discovered a new family of Moufang loops which are now
called Chein loops. Such a loop can be created from any group $W$ together with
$\mathbb{Z}_2$ by a variation on a semi-direct product. We study these loops in
the case where $W$ is a Coxeter group and show that it has what we call a
Chein-Coxeter system, a small set of generators of order 2, together with a set
of relations closely related to the Coxeter relations and Chein relations. As a
result we are able to give amalgam presentations for Coxeter-Chein loops. This
is to our knowledge the first such presentation for a Moufang loop.


  Lensless imaging is an important and challenging problem. One notable
solution to lensless imaging is a single pixel camera which benefits from ideas
central to compressive sampling. However, traditional single pixel cameras
require many illumination patterns which result in a long acquisition process.
Here we present a method for lensless imaging based on compressive ultrafast
sensing. Each sensor acquisition is encoded with a different illumination
pattern and produces a time series where time is a function of the photon's
origin in the scene. Currently available hardware with picosecond time
resolution enables time tagging photons as they arrive to an omnidirectional
sensor. This allows lensless imaging with significantly fewer patterns compared
to regular single pixel imaging. To that end, we develop a framework for
designing lensless imaging systems that use ultrafast detectors. We provide an
algorithm for ideal sensor placement and an algorithm for optimized active
illumination patterns. We show that efficient lensless imaging is possible with
ultrafast measurement and compressive sensing. This paves the way for novel
imaging architectures and remote sensing in extreme situations where imaging
with a lens is not possible.


  Ground state diffusion Monte Carlo is used to investigate the binding
energies and carrier probability distributions of excitons, trions, and
biexcitons in a variety of two-dimensional transition metal dichalcogenide
materials. We compare these results to approximate variational calculations, as
well as to analogous Monte Carlo calculations performed with simplified carrier
interaction potentials. Our results highlight the successes and failures of
approximate approaches as well as the physical features that determine the
stability of small carrier complexes in monolayer transition metal
dichalcogenide materials. Lastly, we discuss points of agreement and
disagreement with recent experiments.


  In this paper we present a pilot study which investigates how non-verbal
behavior affects social influence in social robots. We also present a modular
system which is capable of controlling the non-verbal behavior based on the
interlocutor's facial gestures (head movements and facial expressions) in real
time, and a study investigating whether three different strategies for facial
gestures ("still", "natural movement", i.e. movements recorded from another
conversation, and "copy", i.e. mimicking the user with a four second delay) has
any affect on social influence and decision making in a "survival task". Our
preliminary results show there was no significant difference between the three
conditions, but this might be due to among other things a low number of study
participants (12).


  We present a method based on natural language processing (NLP), for studying
the influence of interest groups (lobbies) in the law-making process in the
European Parliament (EP). We collect and analyze novel datasets of lobbies'
position papers and speeches made by members of the EP (MEPs). By comparing
these texts on the basis of semantic similarity and entailment, we are able to
discover interpretable links between MEPs and lobbies. In the absence of a
ground-truth dataset of such links, we perform an indirect validation by
comparing the discovered links with a dataset, which we curate, of retweet
links between MEPs and lobbies, and with the publicly disclosed meetings of
MEPs. Our best method achieves an AUC score of 0.77 and performs significantly
better than several baselines. Moreover, an aggregate analysis of the
discovered links, between groups of related lobbies and political groups of
MEPs, correspond to the expectations from the ideology of the groups (e.g.,
center-left groups are associated with social causes). We believe that this
work, which encompasses the methodology, datasets, and results, is a step
towards enhancing the transparency of the intricate decision-making processes
within democratic institutions.


  We investigate charge transport of pn and npn junctions made from silicene,
Si analogue of graphene. The conductance shows the distinct gate-voltage
dependences peculiar to the topological and non-topological phases, where the
topological phase transition is caused by external electric field. Namely, the
conductance is suppressed in the np regime when the both sides are topological,
while in the nn regime when one side is topological and the other side is
non-topological. Furthermore, we find that the conductance is almost quantized
to be 0, 1 and 2. Our findings will open a new way to nanoelectronics based on
silicene.


  We study the possible spin-1 charmonium-like states by using QCD sum rule
approach. We calculate the two-point correlation functions for all the local
form tetraquark interpolating currents with $J^{PC}=1^{--}, 1^{-+}, 1^{++}$ and
$1^{+-}$ and extract the masses of the tetraquark charmonium-like states. The
mass of the $1^{--}$ $qc\bar q\bar c$ state is $4.6\sim4.7$ GeV, which implies
a possible tetraquark interpretation for Y(4660) meson. The masses for both the
$1^{++}$ $qc\bar q\bar c$ and $sc\bar s\bar c$ states are $4.0\sim 4.2$ GeV,
which is slightly above the mass of X(3872). For the $1^{-+}$ and $1^{+-}$
$qc\bar q\bar c$ states, the extracted masses are $4.5\sim4.7$ GeV and $4.0\sim
4.2$ GeV respectively.


  Given the collection of timestamped web documents related to the evolving
topic, timeline summarization (TS) highlights its most important events in the
form of relevant summaries to represent the development of a topic over time.
Most of the previous work focuses on fully-observable ranking models and
depends on hand-designed features or complex mechanisms that may not generalize
well. We present a novel dynamic framework for evolutionary timeline generation
leveraging distributed representations, which dynamically finds the most likely
sequence of evolutionary summaries in the timeline, called the Viterbi
timeline, and reduces the impact of events that irrelevant or repeated to the
topic. The assumptions of the coherence and the global view run through our
model. We explore adjacent relevance to constrain timeline coherence and make
sure the events evolve on the same topic with a global view. Experimental
results demonstrate that our framework is feasible to extract summaries for
timeline generation, outperforms various competitive baselines, and achieves
the state-of-the-art performance as an unsupervised approach.


  Novel View Synthesis (NVS), which tries to produce a realistic image at the
target view given source view images and their corresponding poses, is a
fundamental problem in 3D Vision. As this task is heavily under-constrained,
some recent work, like Zero123, tries to solve this problem with generative
modeling, specifically using pre-trained diffusion models. Although this
strategy generalizes well to new scenes, compared to neural radiance
field-based methods, it offers low levels of flexibility. For example, it can
only accept a single-view image as input, despite realistic applications often
offering multiple input images. This is because the source-view images and
corresponding poses are processed separately and injected into the model at
different stages. Thus it is not trivial to generalize the model into
multi-view source images, once they are available. To solve this issue, we try
to process each pose image pair separately and then fuse them as a unified
visual representation which will be injected into the model to guide image
synthesis at the target-views. However, inconsistency and computation costs
increase as the number of input source-view images increases. To solve these
issues, the Multi-view Cross Former module is proposed which maps
variable-length input data to fix-size output data. A two-stage training
strategy is introduced to further improve the efficiency during training time.
Qualitative and quantitative evaluation over multiple datasets demonstrates the
effectiveness of the proposed method against previous approaches. The code will
be released according to the acceptance.


  We introduce a new family of billiards which break time reversal symmetry in
spite of having piece-wise straight trajectories. We show that our billiards
preserve the ergodic and mixing properties of conventional billiards while they
may turn into exponential the power law decay of correlations characteristic of
Sinai type billiards. Such billiards can be implemented by squeezing the
transverse magnetic field along lines or along one-dimensional manifolds.


  We show in this Letter that relativistic dragging of inertial frames around
fast rotating collapsed stars is substantial and can give rise to observable
effects. We apply this to the kHz quasi periodic oscillations (QPOs) sources,
low mass X-ray binaries (LMXRBs) containing an accreting neutron star. Within
the beat frequency model, both the Keplerian frequency of the innermost region
of the accretion disk (~0.3-1.2 kHz) and the neutron star spin frequency
(~0.3-0.4 kHz) are directly observed. From these the Lense-Thirring precession
frequency (tens of Hz) of the same material in the innermost disk regions which
gives rise to the kHz QPOs is determined within a factor of ~4, depending on
the neutron star equation of state. The classical contribution from neutron
star oblateness decreases the precession frequency slightly. The broad peaks at
frequencies ~20-40 Hz in the power spectra of the Atoll-sources 4U1728-34,
4U0614+091 and KS1731-260 and their variations with the higher kHz QPO
frequency are well matched by Lense-Thirring precession of material in the
innermost disk region. We also suggest that the ~15-50 Hz horizontal branch
QPOs of GX5-1 and GX17+2 (and likewise other Z-type low mass X-ray binaries)
arise from the same mechanism.


  Moist-air norms and inner-products are currently used in atmospheric science
for computing dry or moist singular vectors and for determining forecast errors
or sensitivity to observations based on tangent linear and adjoint models. A
new moist-air norm is defined starting from old results published in Marquet
(QJRMS 1993) and based on the "Available Enthalpy" approach, namely one of the
Exergy function defined in general thermodynamics. Some interesting and
promising impacts of this new "Available Enthalpy" norm are described in this
brief version of a paper to be submitted to the QJRMS.


  In this paper, we propose a series of novel coordination schemes for
multi-cell downlink communication. Starting from full base station (BS)
coordination, we first propose a fully-coordinated scheme to exploit beneficial
effects of both inter-cell and intra-cell interference, based on sharing both
channel state information (CSI) and data among the BSs. To reduce the
coordination overhead, we then propose a partially-coordinated scheme where
only intra-cell interference is designed to be constructive while inter-cell is
jointly suppressed by the coordinated BSs. Accordingly, the coordination only
involves CSI exchange and the need for sharing data is eliminated. To further
reduce the coordination overhead, a third scheme is proposed, which only
requires the knowledge of statistical inter-cell channels, at the cost of a
slight increase on the transmission power. For all the proposed schemes,
imperfect CSI is considered. We minimize the total transmission power in terms
of probabilistic and deterministic optimizations. Explicitly, the former
statistically satisfies the users' signal-to-interference-plus-noise ratio
(SINR) while the latter guarantees the SINR requirements in the worst case CSI
uncertainties. Simulation verifies that our schemes consume much lower power
compared to the existing benchmarks, i.e., coordinated multi-point (CoMP) and
coordinated-beamforming (CBF) systems, opening a new dimension on multi-cell
coordination.


  In this paper, we discuss a decoupling of the Goldstone bosons from highly
excited hadrons in relation to the restoration of chiral symmetry in such
hadrons. We use a generalised Nambu-Jona-Lasinio model with the interaction
between quarks in the form of an instantaneous Lorentz-vector confining
potential. This model is known to provide spontaneous breaking of chiral
symmetry in the vacuum via the standard selfenergy loops for valence quarks.
For highly excited hadrons, where the typical momentum of valence quarks is
large, the loop contributions represent only a small correction to the
chiral-invariant classical contributions and asymptotically vanish.
Consequently the chiral symmetry violating Lorentz-scalar dynamical mass of
quarks vanishes. Then the conservation of the axial vector current in the
chiral limit requires, via the Goldberger-Treiman relation, that the valence
quarks decouple from the Goldstone boson. As a consequence, the whole hadron
decouples from the Goldstone boson as well, which implies that its axial
constant also vanishes.


  The reactions of electron-positron to nucleon-antinucleon pair at energy
threshold are studied in a non-perturbative quark model. The puzzling
experimental result that the ratio of the cross section of electron-positron to
proton-antiproton to the one of electron-positron to neutron-antineutron is
smaller than 1 can be understood in the framework of the phenomenological
nonrelativistic quark model and the theoretical predictions for the time-like
proton form factor at energy threshold are well consistent with the
experimental data. The work suggests that the two-step process, in which the
primary quark-antiquark pair forms first a vector meson which in turn decays
into a hadron pair, is dominant over the one-step process in which the primary
quark-antiquark pair is directly dressed by additional quark-antiquark pairs to
form a hadron pair. The experimental data on the reactions of electron-positron
to nucleon-antinucleon strongly suggest the reported vector meson omega(1930)
to be a 2D-wave particle, while the vector meson rho(2000) is preferred to be a
mixture of 3S and 2D states.


  The purpose of this short paper is to describe a project to manufacture a
3D-print of a pendant that includes a logo. The methods described in this paper
involve processing the image of the logo through a Mathematica script. These
methods can be applied to many logos and other images. With the Mathematica
script, a STereoLithography (.stl) file is created that can be used by a 3D
printer. Finally, the object is created on a 3D printer. We assume that the
reader is familiar with the basics of 3D printing.


  We consider the problem of power demand forecasting in residential
micro-grids. Several approaches using ARMA models, support vector machines, and
recurrent neural networks that perform one-step ahead predictions have been
proposed in the literature. Here, we extend them to perform multi-step ahead
forecasting and we compare their performance. Toward this end, we implement a
parallel and efficient training framework, using power demand traces from real
deployments to gauge the accuracy of the considered techniques. Our results
indicate that machine learning schemes achieve smaller prediction errors in the
mean and the variance with respect to ARMA, but there is no clear algorithm of
choice among them. Pros and cons of these approaches are discussed and the
solution of choice is found to depend on the specific use case requirements. A
hybrid approach, that is driven by the prediction interval, the target error,
and its uncertainty, is then recommended.


  We observed the double neutron star binary (DNSB) containing PSR J1537+1155
(also known as B1534+12) with the Chandra X-ray Observatory. This is one of the
two DNSBs detected in X-rays and the only one where a hint of variability with
orbital phase was found (in the previous Chandra observation). Our follow-up
observation supports the earlier result: the distribution of photon arrival
times with orbital phase again shows a deficit around apastron. The
significance of the deficit in the combined dataset exceeds 99%. Such an
orbital light-curve suggests that the X-ray emission is seen only when neutron
star B passes through the equatorial pulsar wind of neutron star A. We describe
statistical tests we used to determine the significance of the deficit, and
conclusions that can be drawn from its existence, such as interaction of the
pulsar wind with the neutron star companion. We also provide better constrained
spectral model parameters obtained from the joint spectral fits to the data
from both observations. A power-law successfully fits the data, with best-fit
photon index Gamma=3.1pm0.4 and unabsorbed flux f=(3.2pm0.8)x10^-15 erg s-1cm-2
(0.3-8 keV range).


  We study s-process element abundance ratios in stars by carrying out stellar
population synthesis, using a rapid synthetic stellar evolution code which
includes an up-to-date treatment of AGB nucleosynthesis and evolution. In
contrast to other studies, we find that a large spread in the 13C efficiency
parameter (13C_eff) is not needed to explain the observed spread in the ratios
of heavy s-process to light s-process elements ([hs/ls]), but this comes
naturally from the range of different initial stellar masses and their time
evolution. As a result, the 13C efficiency needed for fitting most stars in the
galactic disk is constrained to 1 < 13C_eff < 2.5. In the same fashion we also
study the [Pb/Ce] ratios of lead stars and find out that for low metallicities
13C_eff is approximately 0.5.


  We give a derivation of conductivities in certain classes of graphs based on
knowing certain subdeterminants of the response matrix, mainly utilizing the
boundary edge and boundary spike formulas given in Curtis' and Morrow's book.


  The relationship between the chemical picture of an isolated molecule and
that arising from the eiegenfunctions of the Schrodinger Coulomb Hamiltonian
ror the isolated molecule are examined and discussed.


  We analyse the Bose-Einstein condensation process and the
Berezinskii-Kosterlitz-Thouless phase transition within the Gross-Pitaevskii
model and their interplay with wave turbulence theory. By using numerical
experiments we study how the condensate fraction and the first order
correlation function behave with respect to the mass, the energy and the size
of the system. By relating the free-particle energy to the temperature we are
able to estimate the Berezinskii-Kousterlitz-Thouless transition temperature.
Below this transition we observe that for a fixed temperature the superfluid
fraction appears to be size-independent leading to a power-law dependence of
the condensate fraction with respect to the system size.


  The virial theorem for a system of interacting electrons in a crystal, which
is described within the framework of the tight-binding model, is derived. We
show that, in particular case of interacting massless electrons in graphene and
other Dirac materials, the conventional virial theorem is violated. Starting
from the tight-binding model, we derive the generalized virial theorem for
Dirac electron systems, which contains an additional term associated with a
momentum cutoff at the bottom of the energy band. Additionally, we derive the
generalized virial theorem within the Dirac model using the minimization of the
variational energy. The obtained theorem is illustrated by many-body
calculations of the ground state energy of an electron gas in graphene carried
out in Hartree-Fock and self-consistent random-phase approximations.
Experimental verification of the theorem in the case of graphene is discussed.


  The theory of photon drag of superconducting fluctuations in the
two-dimensional electron gas is developed. It is shown that the frequency
dependence of the induced current is qualitatively similar to the case of
photon drag of conventional two-dimensional degenerate electron gas. With the
decreasing temperature the magnitude of the effect increases dramatically and
the current of superconducting fluctuations carries an additional power of
reduced temperature in comparison with the Aslamazov-Larkin contribution. The
magnitude of the developed effect is expected sufficient to be visible against
the conventional photocurrent background.


  Using high-resolution spin-resolved photoemission spectroscopy, we observed a
thermal spin depolarization to which all spin-polarized electrons contribute.
Furthermore we observed a distinct minority spin state near the Fermi level and
a corresponding depolarization that seldom contributes to demagnetization. The
origin of this depolarization has been identified as the many-body effect
characteristics of half-metallic ferromagnets. Our investigation opens an
experimental field of itinerant ferromagnetic physics focusing on phenomena
with sub-meV energy scale.


  An isolated spin system that is in internal thermodynamic equilibrium and
that has an upper limit to its allowed energy states can possess a negative
temperature. We calculate the thermodynamic characteristics and the concurrence
in this system over the entire range of positive and negative temperatures. Our
calculation was performed for different real structures, which can be used in
experiments. It is found that the temperature dependence of the concurrence is
substantially asymmetrical similarly other thermodynamic characteristics. At a
negative temperature the maximum concurrence and the absolute temperature of
the entanglement appearance are sufficiently larger than those at a positive
temperature. The concurrence can be characterized by two dimensionless
parameters: by the ratio between the Zeeman and dipolar energies and by the
ratio of the thermal and dipolar energies. It was shown that for all considered
structures the dimensionless temperatures of the transition between
entanglement and separability of the first and second spins are independent of
spin structure and number of spins.


  In this paper, we shall discuss the family of biharmonic mappings for which
maximum principle holds. As a consequence of our study, we present Schwarz
Lemma for the family of biharmonic mappings. Also we discuss the univalency of
certain class of biharmonic mappings.


  We use a coherent fiber bundle to demonstrate the endoscopic absorption
imaging of quantum gases. We show that the fiber bundle introduces spurious
noise in the picture mainly due to the strong core-to-core coupling. By direct
comparison with free-space pictures, we observe that there is a maximum column
density that can be reliably measured using our fiber bundle, and we derive a
simple criterion to estimate it. We demonstrate that taking care of not
exceeding such maximum, we can retrieve exact quantitative information about
the atomic system, making this technique appealing for systems requiring
isolation form the environment.


  We describe a method to construct hypersurfaces of the complex affine
$n$-space with isomorphic $\mathbb{C}^*$-cylinders. Among these hypersurfaces,
we find new explicit counterexamples to the Laurent Cancellation Problem, i.e.
hypersurfaces that are non isomorphic, although their $\mathbb{C}^*$-cylinders
are isomorphic as abstract algebraic varieties. We also provide examples of non
isomorphic varieties $X$ and $Y$ with isomorphic cartesian squares $X\times X$
and $Y\times Y$.


  A machine learning model that generalizes well should obtain low errors on
unseen test examples. Thus, if we know how to optimally perturb training
examples to account for test examples, we may achieve better generalization
performance. However, obtaining such perturbation is not possible in standard
machine learning frameworks as the distribution of the test data is unknown. To
tackle this challenge, we propose a novel regularization method, meta-dropout,
which learns to perturb the latent features of training examples for
generalization in a meta-learning framework. Specifically, we meta-learn a
noise generator which outputs a multiplicative noise distribution for latent
features, to obtain low errors on the test instances in an input-dependent
manner. Then, the learned noise generator can perturb the training examples of
unseen tasks at the meta-test time for improved generalization. We validate our
method on few-shot classification datasets, whose results show that it
significantly improves the generalization performance of the base model, and
largely outperforms existing regularization methods such as information
bottleneck, manifold mixup, and information dropout.


  Electron spectrometry is traditionally challenging due to the difficulty of
correctly reconstructing the original energy of the detected electrons. Silicon
Drift Detectors, extensively used for X-ray spectrometry, are a promising
technology for the precise measurement of electrons energy. The ability to
correctly model the detector entrance window response to the energy deposited
by electrons is a critical aspect of this application. We hereby describe a
MonteCarlo-based approach to this problem, together with characterization and
validation measurements performed with electron beams from a Scanning Electron
Microscope.


  We compare Tetrad (Java) algorithms to the other public software packages BNT
(Bayes Net Toolbox, Matlab), pcalg (R), bnlearn (R) on the \vanilla" task of
recovering DAG structure to the extent possible from data generated recursively
from linear, Gaussian structure equation models (SEMs) with no latent
variables, for random graphs, with no additional knowledge of variable order or
adjacency structure, and without additional specification of intervention
information. Each one of the above packages offers at least one implementation
suitable to this purpose. We compare them on adjacency and orientation accuracy
as well as time performance, for fixed datasets. We vary the number of
variables, the number of samples, and the density of graph, for a total of 27
combinations, averaging all statistics over 10 runs, for a total of 270
datasets. All runs are carried out on the same machine and on their native
platforms. An interactive visualization tool is provided for the reader who
wishes to know more than can be documented explicitly in this report.


  The nonlinear rheological properties of dense suspensions are discussed
within simplified models, suggested by a recent first principles approach to
the model of Brownian particles in a constant-velocity-gradient solvent flow.
Shear thinning of colloidal fluids and dynamical yielding of colloidal glasses
arise from a competition between a slowing down of structural relaxation,
because of particle interactions, and enhanced decorrelation of fluctuations,
caused by the shear advection of density fluctuations. A mode coupling approach
is developed to explore the shear-induced suppression of particle caging and
the resulting speed-up of the structural relaxation.


  We study the semicrossed product of a finite dimensional C^*-algebra by two
types of commuting automorphisms, and identify them with matrix algebras of
analytic functions in two variables. We look at the connections with
semicrossed products by Z_+ actions.


  Strongly correlated systems with geometric frustrations can host the emergent
phases of matter with unconventional properties. Here, we study the spin $S =
1$ Heisenberg model on the honeycomb lattice with the antiferromagnetic first-
($J_1$) and second-neighbor ($J_2$) interactions ($0.0 \leq J_2/J_1 \leq 0.5$)
by means of density matrix renormalization group (DMRG). In the parameter
regime $J_2/J_1 \lesssim 0.27$, the system sustains a N\'{e}el
antiferromagnetic phase. At the large $J_2$ side $J_2/J_1 \gtrsim 0.32$, a
stripe antiferromagnetic phase is found. Between the two magnetic ordered
phases $0.27 \lesssim J_2/J_1 \lesssim 0.32$, we find a \textit{non-magnetic}
intermediate region with a plaquette valence-bond order. Although our
calculations are limited within $6$ unit-cell width on cylinder, we present
evidence that this plaquette state could be a strong candidate for this
non-magnetic region in the thermodynamic limit. We also briefly discuss the
nature of the quantum phase transitions in the system. We gain further insight
of the non-magnetic phases in the spin-$1$ system by comparing its phase
diagram with the spin-$1/2$ system.


  We present a selective review on probabilistic modeling of heterogeneity in
random graphs. We focus on latent space models and more particularly on
stochastic block models and their extensions that have undergone major
developments in the last five years.


  The accurate description of fluid flow and transport in fractured porous
media is of paramount importance to capture the macroscopic behaviour of an oil
reservoir, a geothermal system, or a CO2 sequestration site, to name few
applications. The construction of accurate simulation model for flow in
fractures is challenging due to the high ratios between a fracture's length and
width, which makes modeling by lower-dimensional manifolds a natural option. In
this paper we present a mixed-dimensional Darcy problem able to describe
pressure and Darcy velocity in all the dimensions, i.e. in the rock matrix, in
the fractures, and in their intersections. Moreover, we present a
mixed-dimensional transport problem which, given the Darcy velocity, describes
coupled advection and diffusion of a passive scalar into the fractured porous
media. The approach can handle both conducting and blocking fractures. Our
computational grids are created by coarsening of simplex tessellations that
conform to the fractures surfaces. An accurate choice of the discrete
approximation of the previous model, by virtual finite element and finite
volume, allows us to simulate complex problem with a good balance in term of
accuracy and computational cost. We illustrate the performance of our method by
comparing to benchmark studies for two-dimensional fractured porous media, as
well as a complex three-dimensional fracture geometry.


  In the context of deep learning with kernel machines, the deep Restricted
Kernel Machine (DRKM) framework allows multiple levels of kernel PCA (KPCA) and
Least-Squares Support Vector Machines (LSSVM) to be combined into a deep
architecture using visible and hidden units. We propose a new method for DRKM
classification coupling the objectives of KPCA and classification levels, with
the hidden feature matrix lying on the Stiefel manifold. The classification
level can be formulated as an LSSVM or as an MLP feature map, combining depth
in terms of levels and layers. The classification level is expressed in its
primal formulation, as the deep KPCA levels, in their dual formulation, can
embed the most informative components of the data in a much lower dimensional
space. The dual setting is independent of the dimension of the inputs and the
primal setting is parametric, which makes the proposed method computationally
efficient for both high-dimensional inputs and large datasets. In the
experiments, we show that our developed algorithm can effectively learn from
small datasets, while using less memory than the convolutional neural network
(CNN) with high-dimensional data. and that models with multiple KPCA levels can
outperform models with a single level. On the tested larger-scale datasets,
DRKM is more energy efficient than CNN while maintaining comparable
performance.


  It is pointed out that important contribution to neutrino masses and mixing
can come from flavour violating slepton exchange. For low and intermediate
$\tan\beta$ such effects can dominate over the usual tau Yukawa coupling
effects included in the renormalization group evolution. The mixing angles
satisfy then the relation different from the fixed point solution of the
renormalization group equation, and the desired neutrino mass splitting can be
generated.


  We establish a strong form of Littlewood's conjecture with inhomogeneous
shifts, for a full-dimensional set of pairs of badly approximable numbers on a
vertical line. We also prove a uniform assertion of this nature, generalising a
strong form of a result by Haynes, Jensen and Kristensen. Finally, we establish
a similar result involving inhomogeneously badly approximable numbers, making
progress towards a problem posed by Pollington, Velani, Zafeiropoulos and
Zorin.


  A remark on the proof that the Grothendieck constant satisfies $K_G <
\pi/(2\ln(1+\sqrt{2}))$.


  We consider the universal part of entanglement entropy across a plane in flat
space for a QFT, giving a non-perturbative expression in terms of a spectral
function. We study the change in entanglement entropy under a deformation by a
relevant operator, providing a pertrubative expansion where the terms are
correlation functions in the undeformed theory. The entanglement entropy for
free massive fermions and scalars easily follows. Finally, we study
entanglement entropy across a plane in a background geometry that is a
deformation of flat space, finding new universal terms arising from mixing of
geometry and couplings of the QFT.


  Solid deuterium (sD_2) is used as an efficient converter to produce ultracold
neutrons (UCN). It is known that the sD_2 must be sufficiently cold, of high
purity and mostly in its ortho-state in order to guarantee long lifetimes of
UCN in the solid from which they are extracted into vacuum. Also the UCN
transparency of the bulk sD_2 material must be high because crystal
inhomogeneities limit the mean free path for elastic scattering and reduce the
extraction efficiency. Observations at the UCN sources at Paul Scherrer
Institute and at Los Alamos National Laboratory consistently show a decrease of
the UCN yield with time of operation after initial preparation or later
treatment (`conditioning') of the sD_2. We show that, in addition to the
quality of the bulk sD_2, the quality of its surface is essential. Our
observations and simulations support the view that the surface is deteriorating
due to a build-up of D_2 frost-layers under pulsed operation which leads to
strong albedo reflections of UCN and subsequent loss. We report results of UCN
yield measurements, temperature and pressure behavior of deuterium during
source operation and conditioning, and UCN transport simulations. This,
together with optical observations of sD_2 frost formation on initially
transparent sD_2 in offline studies with pulsed heat input at the North
Carolina State University UCN source results in a consistent description of the
UCN yield decrease.


  The Einstein equations for an isotropic and homogeneous
Friedmann--Robertson--Walker Universe in the presence of a quintessence scalar
field are shown to be described in a unified way, formally identical to the
dynamics of a relativistic particle moving on a two--dimensional spacetime. The
correct Lagrangian for the system is presented and used to construct a spinor
quantum cosmology theory using Breit's prescription. The theory is
supersymmetric when written in Majorana representation. The spinor components
interact through a potential that unifies spacetime curvature and quintessence.
An exact supersymmetric solution for $k=0$ case is exhibited. This quantum
cosmology model may be interpreted as a theory of interacting universes.


  In this paper, we develop an algorithm called hierarchal online sequential
learning algorithm (H-OS-ELM) for single feed feedforward network with features
combined from hundreds of midlayers, the algorithm can learn chunk by chunk
with fixed or varying block size, we believe that the diverse selectivity of
neurons in top layers which consists of encoded distributed information
produced by the other neurons offers better computational advantage over
inference accuracy. Thus this paper proposes a Hierarchical model framework
combined with Online-Sequential learning algorithm, Firstly the model consists
of subspace feature extractor which consists of subnetwork neuron, using the
sub-features which is result of the feature extractor in first layer of the
hierarchy we get rid of irrelevant factors which are of no use for the learning
and iterate this process so that to recast the the subfeatures into the
hierarchical model to be processed into more acceptable cognition. Secondly by
using OS-Elm we are using non-iterative style for learning we are implementing
a network which is wider and shallow which plays a important role in
generalizing the overall performance which in turn boosts up the learning speed


  This paper analyses the application of no-reference metric NIQE to the task
of video-codec comparison. A number of issues in the metric behaviour on videos
was detected and described. The metric has outlying scores on black and
solid-coloured frames. The proposed averaging technique for metric quality
scores helped to improve the results in some cases. Also, NIQE has low-quality
scores for videos with detailed textures and higher scores for videos of lower
bitrates due to the blurring of these textures after compression. Although NIQE
showed natural results for many tested videos, it is not universal and
currently can not be used for video-codec comparisons.


  We propose a method to improve lattice operators composed of Wilson fermions
which allows the removal of all corrections of $O(a)$, including those
proportional to the quark mass. It requires off-shell improvement of quark
fields and composite operators, which is achieved by studying the behaviour of
quark and gluon correlation functions at large momenta.


  Shimura and Taniyama proved that if $A$ is a potentially CM abelian variety
over a number field $F$ with CM by a field $K$ linearly disjoint from F, then
there is an algebraic Hecke character $\lambda_A$ of $K$ such that
$L(A/F,s)=L(\lambda_A,s)$. We consider a certain converse to their result.
Namely, let $A$ be a potentially CM abelian variety appearing as a factor of
the Jacobian of a curve of the form $y^e=\gamma x^f+\delta$. Fix positive
integers $a$ and $n$ such that $n/2 < a \leq n$. Under mild conditions on $e,
f, \gamma, \delta$, we construct a Chow motive $M$, defined over
$F=\mathbb{Q}(\gamma,\delta)$, such that $L(M/F,s)$ and
$L(\lambda_A^a\bar{\lambda}_A^{n-a},s)$ have the same Euler factors outside
finitely many primes.


  Search space design is very critical to neural architecture search (NAS)
algorithms. We propose a fine-grained search space comprised of atomic blocks,
a minimal search unit that is much smaller than the ones used in recent NAS
algorithms. This search space allows a mix of operations by composing different
types of atomic blocks, while the search space in previous methods only allows
homogeneous operations. Based on this search space, we propose a resource-aware
architecture search framework which automatically assigns the computational
resources (e.g., output channel numbers) for each operation by jointly
considering the performance and the computational cost. In addition, to
accelerate the search process, we propose a dynamic network shrinkage technique
which prunes the atomic blocks with negligible influence on outputs on the fly.
Instead of a search-and-retrain two-stage paradigm, our method simultaneously
searches and trains the target architecture. Our method achieves
state-of-the-art performance under several FLOPs configurations on ImageNet
with a small searching cost. We open our entire codebase at:
https://github.com/meijieru/AtomNAS.


  We investigate a generalized stochastic model with the property known as mean
reversion, that is, the tendency to relax towards a historical reference level.
Besides this property, the dynamics is driven by multiplicative and additive
Wiener processes. While the former is modulated by the internal behavior of the
system, the latter is purely exogenous. We focus on the stochastic dynamics of
volatilities, but our model may also be suitable for other financial random
variables exhibiting the mean reversion property. The generalized model
contains, as particular cases, many early approaches in the literature of
volatilities or, more generally, of mean-reverting financial processes. We
analyze the long-time probability density function associated to the model
defined through a It\^o-Langevin equation. We obtain a rich spectrum of shapes
for the probability function according to the model parameters. We show that
additive-multiplicative processes provide realistic models to describe
empirical distributions, for the whole range of data.


  Light with light control of surface plasmon polaritons is theoretically
demonstrated. A barely simple and compact source of these waves consists in a
finite number of slits (evenly spaced) perforating a metal film. The system
scatters electromagnetic fields in one side of the metal film when it is
illuminated from the opposite side by a polarized light source. High intensity
light sources moreover efficiently generate light at second harmonic and higher
frequencies in the metal led by optical nonlinearities. It is shown how the
mixing of fields scattered by the slits from a weak beam at $\lambda$
wavelength, with the second harmonic fields generated by a high intensity $2
\lambda$ beam, creates a destructive interference of surface plasmons in one of
the two possible directions of emission from the slits, while these are
enhanced along the opposite direction. The unidirectional launching of surface
plasmons is due to the different properties of symmetry at $\lambda$ whether
they are linearly or nonlinearly generated. It is envisaged a nanodevice which
might allow sending digital information codified in the surface plasmon field
or be used to build ultra-narrow bandwidth surface plasmon frequency combs.


  Recently, an image scrambling encryption algorithm of pixel bit based on
chaos map was proposed. Considering the algorithm as a typical binary image
scrambling/permutation algorithm exerting on plaintext of size $M\times (8N)$,
this paper proposes a novel optimal method to break it with some
known/chosen-plaintexts. The spatial complexity and computational complexity of
the attack are only $O(32\cdot MN)$ and $O(16\cdot n_0\cdot MN)$ respectively,
where $n_0$ is the number of known/chosen-plaintexts used. The method can be
easily extended to break any permutation-only encryption scheme exerting on
plaintext of size $M\times N$ and with $L$ different levels of values. The
corresponding spatial complexity and computational complexity are only $O(MN)$
and $O(\lceil\log_L(MN)\rceil \cdot MN)$ respectively. In addition, some
specific remarks on the performance of the image scrambling encryption
algorithm are presented.


  We develop a general low-energy multiple-scattering partial-wave theory for
gapless topological insulator (TI) surfaces in the presence of magnetic
impurities. As applications, we discuss the differential cross section (CS)
$d\Lambda/d\varphi$, the total CS $\Lambda_{tot}$, the Hall component of
resistivity $\Omega$, and inverse momentum relaxation time $\Gamma_{M}$ for
single- and two-centered magnetic scattering. We show that differing from the
nonmagnetic impurity scattering, $s\mathtt{-}$wave approximation is not
advisable and convergent in the present case. The symmetry of CS is reduced and
the backscattering occurs and becomes stronger with increasing the effective
magnetic moment $M$ of single magnetic impurity. We show a non-zero
perpendicular resistivity component $\Omega$, which may be useful for tuning
the Hall voltage of the sample. Consistent with the analysis of $d\Lambda
/d\varphi$, by comparing $\Gamma_{M}$ with $\Lambda_{tot}$, we can determine
different weights of backscattering and forward scattering. Similar to CS,
$\Omega$ and $\Gamma_{M}$ also exhibit oscillating behavior for multiple
magnetic scattering centers due to interference effect.


  The dynamical encirclement around a second order exceptional point (EP) and
corresponding chirality driven nonadiabatic modal dynamics have attracted
enormous attention in the topological study of various non-Hermitian systems.
However, dynamical encirclement around multiple second-order EPs in a
multi-state system is yet to be explored. Here, exploiting an exclusive design
of a planar gain-loss assisted three-mode supported optical waveguide with
local Kerr-nonlinearity, we encounter multiple second-order EPs. Judiciously,
choosing a specific parameter space by varying the unbalanced gain-loss
profile, we encircle multiple EPs simultaneously, and explore the beam-dynamics
toward corresponding chiral or non-chiral aspects of the device. While
propagating through the designed waveguide, three coupled modes are collapsed
into a specific dominating mode, owing to corresponding nonadiabatic
corrections around multiple EPs. Even in the absence of chirality, here, the
same amount of focusing and de-focusing type nonlinearity gives different
dominating output, irrespective of the choice of inputs, for the same
topological structure of the waveguide. This exclusive topologically robust
compact scheme of nonlinearity induced asymmetric and non-chiral light dynamics
should provide a promising opportunity to switch or retrieve a selective mode
from a multi-mode signal in integrated devices.


  The Birkhoff polytope $B_n$ is the convex hull of all $n\times n$ permutation
matrices in $\mathbb{R}^{n\times n}$. We compute the combinatorial symmetry
group of the Birkhoff polytope.
  A representation polytope is the convex hull of some finite matrix group
$G\leq \operatorname{GL}(d,\mathbb{R})$. We show that the group of permutation
matrices is essentially the only finite matrix group which yields a
representation polytope with the same face lattice as the Birkhoff polytope.


  The surface brightness distribution of $\sim$30-40$\%$ of the early-type
dwarf galaxies with $-18 \leq M_{B} \leq -15$ in the Virgo and the Coma
clusters is fitted by models that include two structural components (S\`ersic +
exponential) as for bright disc galaxies.The goal of the present study is to
determine whether early-type dwarf galaxies with a two-component stellar
structure in the Virgo and the Coma clusters are low-luminosity copies of
bright disc galaxies or are the remnants of bright galaxies strongly
transformed by cluster environmental effects.I analysed the location of bright
disc galaxies and early-type dwarfs in the $r_{b,e}/h$- $n$ plane. The location
in this plane of the two-component dwarf galaxies was compared with the
remnants of tidally disrupted disc galaxies reported by numerical simulations.
Bright unbarred disc galaxies show a strong correlation in the $r_{b,e}/h$-$n$
plane. Galaxies with larger S\`ersic shape parameters show a higher $r_{b,e}/h$
ratio. In contrast, two-component early-type dwarf galaxies do not follow the
same correlation. A fraction ($\sim$55%) of them are located outside the locus
defined in this plane by having 95$\%$ of bright disc galaxies. This
distribution indicates that they are not a low-mass replica of bright disc
galaxies. The different location in the $r_{b,e}/h$- $n$ plane of two-component
early-type dwarfs and bright galaxies can be qualitatively explain whether the
former are remnants of disc galaxies strongly transformed by tidal
processes.The progenitors of $\sim$20-25% of early-type dwarf galaxies with
$-18 \leq M_{B} \leq -15$ in the Virgo and Coma clusters could be bright disc
galaxies transformed by effects of the environment. These tidally transformed
galaxies can be selected according to their location in the $r_{b,e}/h$-$n$
plane.


  Trapped ultracold Fermi gases provide a system that can be tuned between the
BCS and BEC regimes by means of a magnetic-field Feshbach resonance.
Condensation of fermionic atom pairs in a $^{40}$K gas was demonstrated
experimentally by a sweep technique that pairwise projects fermionic atoms onto
molecules. In this paper we examine previous data obtained with this technique
that probed the phase boundary in the temperature-magnetic field plane.
Comparison of the $^{40}$K data to a theoretically computed phase diagram
demonstrates good agreement between the two.


  In this paper, we study the maximal edge-traversal time (simply we call
maximal weight hereafter) on the optimal paths in the first passage percolation
for several edge distributions, including the Pareto and Weibull distributions.
It is known to be unbounded when the edge distribution has unbounded support
[J. van den Berg and H. Kesten. Inequalities for the time constant in
first-passage percolation. Ann. Appl. Probab. 56-80, 1993]. We determine the
order of the growth up to a multiplicative constant.


  It is proved that any function of a Lusin-type class, the class of
$ACG_r$-functions, is differentiable almost everywhere in the sense of a
derivative defined in the space~$L^r$, $1\le r<\infty$. This leads to obtaining
a full descriptive characterization of a Henstock-Kurzweil-type integral, the
$HK_r$-integral, which serves to recover functions from their
$L^r$-derivatives. The class $ACG_r$ is compared with the classical Lusin class
$ACG$ and it is shown that a continuous $ACG$-function can fail to be
$L^r$-differentiable almost everywhere.


  Balancing common disease treatment and epidemic control is a key objective of
medical supplies procurement in hospitals during a pandemic such as COVID-19.
This problem can be formulated as a bi-objective optimization problem for
simultaneously optimizing the effects of common disease treatment and epidemic
control. However, due to the large number of supplies, difficulties in
evaluating the effects, and the strict budget constraint, it is difficult for
existing evolutionary multiobjective algorithms to efficiently approximate the
Pareto front of the problem. In this paper, we present an approach that first
transforms the original high-dimensional, constrained multiobjective
optimization problem to a low-dimensional, unconstrained multiobjective
optimization problem, and then evaluates each solution to the transformed
problem by solving a set of simple single-objective optimization subproblems,
such that the problem can be efficiently solved by existing evolutionary
multiobjective algorithms. We applied the transform-and-divide evolutionary
optimization approach to six hospitals in Zhejiang Province, China, during the
peak of COVID-19. Results showed that the proposed approach exhibits
significantly better performance than that of directly solving the original
problem. Our study has also shown that transform-and-divide evolutionary
optimization based on problem-specific knowledge can be an efficient solution
approach to many other complex problems and, therefore, enlarge the application
field of evolutionary algorithms.


  We give new improvements to the Chudnovsky-Chudnovsky method that provides
upper bounds on the bilinear complexity of multiplication in extensions of
finite fields through interpolation on algebraic curves. Our approach features
three independent key ingredients:
  (1) We allow asymmetry in the interpolation procedure. This allows to prove,
via the usual cardinality argument, the existence of auxiliary divisors needed
for the bounds, up to optimal degree.
  (2) We give an alternative proof for the existence of these auxiliary
divisors, which is constructive, and works also in the symmetric case, although
it requires the curves to have sufficiently many points.
  (3) We allow the method to deal not only with extensions of finite fields,
but more generally with monogenous algebras over finite fields. This leads to
sharper bounds, and is designed also to combine well with base field descent
arguments in case the curves do not have sufficiently many points.
  As a main application of these techniques, we fix errors in, improve, and
generalize, previous works of Shparlinski-Tsfasman-Vladut, Ballet, and
Cenk-Ozbudak. Besides, generalities on interpolation systems, as well as on
symmetric and asymmetric bilinear complexity, are also discussed.


  We present the first observation of exclusive $e^+e^-$ production in
hadron-hadron collisions, using $p\bar{p}$ collision data at
\mbox{$\sqrt{s}=1.96$ TeV} taken by the Run II Collider Detector at Fermilab,
and corresponding to an integrated luminosity of \mbox{532 pb$^{-1}$}. We
require the absence of any particle signatures in the detector except for an
electron and a positron candidate, each with transverse energy {$E_T>5$ GeV}
and pseudorapidity {$|\eta|<2$}. With these criteria, 16 events are observed
compared to a background expectation of {$1.9\pm0.3$} events. These events are
consistent in cross section and properties with the QED process \mbox{$p\bar{p}
\to p + e^+e^- + \bar{p}$} through two-photon exchange. The measured cross
section is \mbox{$1.6^{+0.5}_{-0.3}\mathrm{(stat)}\pm0.3\mathrm{(syst)}$ pb}.
This agrees with the theoretical prediction of {$1.71 \pm 0.01$ pb}.


  Applying Discretized Light Cone Quantization, we perform the first
calculation of the spectrum of true muonium, the $\mu^+ \mu^-$ atom, as
modified by the inclusion of an $|e\bar e >$ Fock component. The shift in the
mass eigenvalue is found to be largest for triplet states. If $m_e$ is taken to
be a substantial fraction of $m_\mu$, the integrated probability of the
electronic component of the $1 \, {}^3 /! S_1$ state is found to be as large as
$O(10^{-2})$. Initial studies of the Lamb shift for the atom are performed.
Directions for making the simulations fully realistic are discussed.


  Commonly, the comparisons of treatment groups versus a control is performed
for location effects only where possible scale effects are considered as
disturbing. Sometimes scale effects are also relevant, as a kind of early
indicator for changes. Here several approaches for Dunnett-type tests for
location or scale effects are proposed and compared by a simulation study. Two
real data examples are analysed accordingly and the related R-code is available
in the Appendix.


  In this lecture notes we present the equations and the physics involved in
the dynamic of incompressible fluids. We present the mathematical techniques
needed in order to prove the existence and uniqueness result for the case where
we consider Burgers equation. We also explain an useful numerical method when
dealing with this kind of equations. These lecture notes were written for the
2010 JAE-Intro Summer School. This Summer School was organized by ICMAT-CSIC
and takes place in Madrid.


  Coupling between spatially separated magnets can be mediated by excitations
such as photons and phonons, which can be characterized as coherent coupling
and dissipative coupling with real and imaginary coupling rate. We
theoretically predict the existence of dynamic exchange coupling in a closed
magneto-elastic system mediated by attenuating elastic waves and whose coupling
rate is complex in general, leading to alternating repulsive or attractive
spectrum depending on thickness of the elastic media. The presence of dynamic
exchange coupling and its competition with coherent coupling are numerically
verified according to the generalized Hooke's law in magneto-elastic systems.
The predicted mechanism provides a new strategy to synchronize precessing
magnets as well as other excitations over long distance and pave the way for
non-Hermitian engineering of collective modes in hybrid magnonics, phononics
and photonics.


  We develop a theory of the spin Seebeck effect (SSE) in paramagnets as well
as in antiferromagnets at elevated temperatures where the classical limit of
the fluctuation-dissipation theorem is applicable. Employing dissipative
stochastic models that are valid at these temperatures, we calculate the SSE
signal, and we find that both the paramagnetic SSE and the antiferromagnetic
SSE are expressed by a single equation that is proportional to the external
magnetic field times the spin susceptibility of the magnet. The present result
suggests the appearance of a cusp structure at the Neel temperature in the
antiferromagnetic SSE signal.


  Using numerical simulations, we study the non-equilibrium coarsening dynamics
of a binary solvent around spherical colloids in the presence of a temperature
gradient. The coarsening dynamics following a temperature quench is studied by
solving the coupled modified Cahn-Hilliard-Cook equation and the heat diffusion
equation, which describe the concentration profile and the temperature field,
respectively. For the temperature field we apply a suitable boundary condition.
We observe the formation of circular layers of different phases around the
colloid whereas away from the colloid patterns of spinodal decomposition
persist. Additionally, we investigate the dependence of the pattern formation
on the quench temperature. Our simulation mimics an experimental system where
the colloid is heated by laser illumination. Note that we look at the cooling
of a solvent with an upper critical temperature, whereas the experimental
analogue is the laser-heating of a solvent with a lower critical temperature.
We also study a two colloid system. Here, we observe that a bridge of one phase
forms connecting the two colloids. Also, we study the force acting on the
colloids that is generated by the chemical potential gradient.


  We present a study of the morphological fractions and color-magnitude
relation in the most distant X-ray selected galaxy cluster currently known,
XMMXCS J2215.9-1738 at z=1.46, using a combination of optical imaging data
obtained with the Hubble Space Telescope Advanced Camera for Surveys, and
infrared data from the Multi-Object Infrared Camera and Spectrograph, mounted
on the 8.2m Subaru telescope. We find that the morphological mix of the cluster
galaxy population is similar to clusters at z~1: approximately ~62% of the
galaxies identified as likely cluster members are ellipticals or S0s; and ~38%
are spirals or irregulars. We measure the color-magnitude relations for the
early type galaxies, finding that the slope in the z_850-J relation is
consistent with that measured in the Coma cluster, some ~9 Gyr earlier,
although the uncertainty is large. In contrast, the measured intrinsic scatter
about the color-magnitude relation is more than three times the value measured
in Coma, after conversion to rest frame U-V. From comparison with stellar
population synthesis models, the intrinsic scatter measurements imply mean
luminosity weighted ages for the early type galaxies in J2215.9-1738 of ~3 Gyr,
corresponding to the major epoch of star formation coming to an end at z_f =
3-5. We find that the cluster exhibits evidence of the `downsizing' phenomenon:
the fraction of faint cluster members on the red sequence expressed using the
Dwarf-to-Giant Ratio (DGR) is 0.32+/-0.18. This is consistent with
extrapolation of the redshift evolution of the DGR seen in cluster samples at z
< 1. In contrast to observations of some other z > 1 clusters, we find a lack
of very bright galaxies within the cluster.


  This paper considers a multiuser full-duplex (FD) wireless communication
system, where a FD radio base station (BS) serves multiple single-antenna
half-duplex (HD) uplink and downlink users simultaneously. Unlike conventional
interference mitigation approaches, we propose to use the knowledge of the data
symbols and the channel state information (CSI) at the FD radio BS to exploit
the multi-user interference constructively rather than to suppress it. We
propose a multi-objective optimisation problem (MOOP) via the weighted
Tchebycheff method to study the trade-off between the two desirable system
design objectives namely the total downlink transmit power minimisation and the
total uplink transmit power minimisation problems at the same time ensuring the
required quality-of-service (QoS) for all users. In the proposed MOOP, we adapt
the QoS constraints for the downlink users to accommodate constructive
interference (CI) for both generic phase shift keying (PSK) modulated signals
as well as for quadrature amplitude modulated (QAM) signals. We also extended
our work to a robust design to study the system with imperfect uplink, downlink
and self-interference CSI. Simulation results and analysis show that,
significant power savings can be obtained. More importantly, however, the MOOP
approach here allows for the power saved to be traded off for both uplink and
downlink power savings, leading to an overall energy efficiency improvement in
the wireless link.


  Open clusters can be the key to deepen our knowledge on various issues
involving the structure and evolution of the Galactic disk and details of
stellar evolution because a cluster's properties are applicable to all its
members. However the number of open clusters with detailed analysis from high
resolution spectroscopy and/or precision photometry imposes severe limitation
on studies of these objects. To expand the number of open clusters with
well-defined chemical abundances and fundamental parameters, we investigate the
poorly studied, anticenter open cluster Tombaugh 1. Using precision
uvbyCaH$\beta$ photometry and high resolution spectroscopy, we derive the
cluster's properties and, for the first time, present detailed abundance
analysis of 10 potential cluster stars. Using radial position from the cluster
center and multiple color indices, we have isolated a sample of unevolved
probable, single-star members of Tombaugh 1. The weighted photometric
metallicity from $m_1$ and $hk$ is [Fe/H] = -0.10 $\pm$ 0.02, while a match to
the Victoria-Regina Str\"{o}mgren isochrones leads to an age of 0.95 $\pm$ 0.10
Gyr and an apparent modulus of $(m-M)$ = 13.10 $\pm$ 0.10. Radial velocities
identify 6 giants as probable cluster members and the elemental abundances of
Fe, Na, Mg, Al, Si, Ca, Ti, Cr, Ni, Y,Ba, Ce, and Nd have been derived for both
the cluster and the field stars. Tombaugh 1 appears to be a typical inner thin
disk, intermediate-age open cluster of slightly subsolar metallicity, located
just beyond the solar circle, with solar elemental abundance ratios except for
the heavy s-process elements, which are a factor of two above solar. Its
metallicity is consistent with a steep metallicity gradient in the
galactocentric region between 9.5 and 12 kpc. Our study also shows that Cepheid
XZ CMa is not a member of Tombaugh 1, and reveals that this Cepheid presents
signs of barium enrichment.


  Convective drying of biomass is an important technological solution required
to increase the quality of biomass for efficient biomass conversion in heat and
power generation sector. We propose a fully predictive method based on
iteratively solving heat power conservation equation, which evaluates the
convective drying rate for deep fixed porous material bed containing any type
of evaporating liquid during a constant-rate drying period with given inlet air
parameters. The analysis of the heat power conservation equation during the
constant-rate period showed that the drying rate of deep fixed moist porous
material bed is a linear function of the inlet air mass flow rate and is
independent of the initial masses of water and dry material inside the bed when
inlet air absolute humidity is constant. Furthermore, the proposed method
estimates the theoretical maximum possible drying rate for a drying system with
given inlet air conditions and; therefore, it can be used as an important tool
for designing industrial equipment and verifying the correctness of drying
experiments.


  The cybersecurity threat landscape has lately become overly complex. Threat
actors leverage weaknesses in the network and endpoint security in a very
coordinated manner to perpetuate sophisticated attacks that could bring down
the entire network and many critical hosts in the network. Increasingly
advanced deep and machine learning-based solutions have been used in threat
detection and protection. The application of these techniques has been reviewed
well in the scientific literature. Deep Reinforcement Learning has shown great
promise in developing AI-based solutions for areas that had earlier required
advanced human cognizance. Different techniques and algorithms under deep
reinforcement learning have shown great promise in applications ranging from
games to industrial processes, where it is claimed to augment systems with
general AI capabilities. These algorithms have recently also been used in
cybersecurity, especially in threat detection and endpoint protection, where
these are showing state-of-the-art results. Unlike supervised machines and deep
learning, deep reinforcement learning is used in more diverse ways and is
empowering many innovative applications in the threat defense landscape.
However, there does not exist any comprehensive review of these unique
applications and accomplishments. Therefore, in this paper, we intend to fill
this gap and provide a comprehensive review of the different applications of
deep reinforcement learning in cybersecurity threat detection and protection.


  We prove a conjecture of J. Palis: any diffeomorphism of a compact manifold
can be C1-approximated by a Morse-Smale diffeomorphism or by a diffeomorphism
having a transverse homoclinic intersection.
  -----
  Cr'eation d'intersection homoclines : un mod`ele pour la dynamique centrale
des syst`emes partiellement hyperboliques.
  Nous montrons une conjecture de J. Palis : tout diff'eomorphisme d'une
vari'et'e compacte peut ^etre approch'e en topologie C1 par un diff'eomorphisme
Morse-Smale ou par un diff'eomorphisme ayant une intersection homocline
transverse.


  In the problem of domain generalization (DG), there are labeled training data
sets from several related prediction problems, and the goal is to make accurate
predictions on future unlabeled data sets that are not known to the learner.
This problem arises in several applications where data distributions fluctuate
because of environmental, technical, or other sources of variation. We
introduce a formal framework for DG, and argue that it can be viewed as a kind
of supervised learning problem by augmenting the original feature space with
the marginal distribution of feature vectors. While our framework has several
connections to conventional analysis of supervised learning algorithms, several
unique aspects of DG require new methods of analysis.
  This work lays the learning theoretic foundations of domain generalization,
building on our earlier conference paper where the problem of DG was introduced
(Blanchard et al., 2011). We present two formal models of data generation,
corresponding notions of risk, and distribution-free generalization error
analysis. By focusing our attention on kernel methods, we also provide more
quantitative results and a universally consistent algorithm. An efficient
implementation is provided for this algorithm, which is experimentally compared
to a pooling strategy on one synthetic and three real-world data sets.


  In order to derive the equivalent partial differential equations of a lattice
Boltzmann scheme,the Chapman Enskog expansion is very popular in the lattive
Boltzmann community. A maindrawback of this approach is the fact that
multiscale expansions are used without any clearmathematical signification of
the various variables and operators. Independently of thisframework, the Taylor
expansion method allows to obtain formally the equivalent partialdifferential
equations. In this contribution, we prove that both approaches give
identicalresults with acoustic scaling for a very general family of lattice
Boltzmann schemes and upto fourth order accuracy. Examples with a single scalar
conservation illustrate our purpose.


  Solar-cycle related variation of differential rotation is investigated
through analyzing the rotation rates of magnetic fields, distributed along
latitudes and varying with time at the time interval of August 1976 to April
2008. More pronounced differentiation of rotation rates is found to appear at
the ascending part of a Schwabe cycle than at the descending part on an
average. The coefficient $B$ in the standard form of differential rotation,
which represents the latitudinal gradient of rotation, may be divided into
three parts within a Schwabe cycle. Part one spans from the start to the
$4^{th}$ year of a Schwabe cycle, within which the absolute $B$ is
approximately a constant or slightly fluctuates. Part two spans from the
$4^{th}$ to the $7^{th}$ year, within which the absolute $B$ decreases. Part
three spans from the $7^{th}$ year to the end, within which the absolute $B$
increases. Strong magnetic fields repress differentiation of rotation rates, so
that rotation rates show less pronounced differentiation, but weak magnetic
fields seem to just reflect differentiation of rotation rates. The solar-cycle
related variation of solar differential rotation is inferred to the result of
both the latitudinal migration of the surface torsional pattern and the
repression of strong magnetic activity to differentiation of rotation rates.


  We realize experimentally a cold atom system equivalent to the 3D Anderson
model of disordered solids where the anisotropy can be controlled by adjusting
an experimentally accessible parameter. This allows us to study experimentally
the disorder vs anisotropy phase diagram of the Anderson metal-insulator
transition. Numerical and experimental data compare very well with each other
and a theoretical analysis based on the self-consistent theory of localization
correctly discribes the observed behavior, illustrating the flexibility of cold
atom experiments for the study of transport phenomena in complex quantum
systems.


  The microscopic approach quantum dissipation process presented by Yu and Sun
[Phys. Rev., A49(1994)592, A51(1995)1845] is developed to analyze the wave
function structure of dynamic evolution of a typical dissipative system, a
single mode boson soaked in a bath of many bosons. In this paper, the wave
function of total system is explicitly obtained as a product of two components
of the system and the bath in the coherent state representation. It not only
describes the influence of the bath on the variable of the system through the
Brownian motion, but also manifests the back- action of the system on the bath
and the effects of the mutual interaction among the bosons of the bath. Due to
the back-action, the total wave function can only be partially factorizable
even for the Brownian motion can be ignored in certain senses, such as the
cases with weak coupling and large detuning


  Problems involving approximation from scattered data where data is arranged
quasi-uniformly have been treated by RBF methods for decades. Treating data
with spatially varying density has not been investigated with the same
intensity, and is far less well understood. In this article we consider the
stability of surface spline interpolation (a popular type of RBF interpolation)
for data with nonuniform arrangements. Using techniques similar to those
recently employed by Hangelbroek, Narcowich and Ward to demonstrate the
stability of interpolation from quasi-uniform data on manifolds, we show that
surface spline interpolation on R^d is stable, but in a stronger, local sense.
We also obtain pointwise estimates showing that the Lagrange function decays
very rapidly, and at a rate determined by the local spacing of datasites. These
results, in conjunction with a Lebesgue lemma, show that surface spline
interpolation enjoys the same rates of convergence as those of the local
approximation schemes recently developed by DeVore and Ron.


  Recent approaches to cross-lingual word embedding have generally been based
on linear transformations between the sets of embedding vectors in the two
languages. In this paper, we propose an approach that instead expresses the two
monolingual embedding spaces as probability densities defined by a Gaussian
mixture model, and matches the two densities using a method called normalizing
flow. The method requires no explicit supervision, and can be learned with only
a seed dictionary of words that have identical strings. We argue that this
formulation has several intuitively attractive properties, particularly with
the respect to improving robustness and generalization to mappings between
difficult language pairs or word pairs. On a benchmark data set of bilingual
lexicon induction and cross-lingual word similarity, our approach can achieve
competitive or superior performance compared to state-of-the-art published
results, with particularly strong results being found on etymologically distant
and/or morphologically rich languages.


  In this study, we aim to improve our understanding of the doping mechanism
involved in the polymer PBDTTT-c doped with(Mo(tfd-COCF3)3. We follow the
evolution of the hole density with dopant concentration to highlight the limits
of organic semiconductor doping. To enable the use of doping to enhance the
performance of organic electronic devices, doping efficiency must be understood
and improved. We report here a study using complementary optical and electrical
characterization techniques, which sheds some light on the origin of this
limited doping efficiency at high dopant concentration. Two doping mechanisms
are considered, the direct charge transfer (DCT) and the charge transfer
complex (CTC). We discuss the validity of the model involved as well as its
impact on the doping efficiency.


  Graph embedding technics are studied with interest on public datasets, such
as BlogCatalog, with the common practice of maximizing scoring on graph
reconstruction, link prediction metrics etc. However, in the financial sector
the important metrics are often more business related, for example fraud
detection rates. With our privileged position of having large amount of
real-world non-public P2P-lending social data, we aim to study empirically
whether recent advances in graph embedding technics provide a useful signal for
metrics more closely related to business interests, such as fraud detection
rate.