  When trained on language data, do transformers learn some arbitrary
computation that utilizes the full capacity of the architecture or do they
learn a simpler, tree-like computation, hypothesized to underlie compositional
meaning systems like human languages? There is an apparent tension between
compositional accounts of human language understanding, which are based on a
restricted bottom-up computational process, and the enormous success of neural
models like transformers, which can route information arbitrarily between
different parts of their input. One possibility is that these models, while
extremely flexible in principle, in practice learn to interpret language
hierarchically, ultimately building sentence representations close to those
predictable by a bottom-up, tree-structured model. To evaluate this
possibility, we describe an unsupervised and parameter-free method to
\emph{functionally project} the behavior of any transformer into the space of
tree-structured networks. Given an input sentence, we produce a binary tree
that approximates the transformer's representation-building process and a score
that captures how "tree-like" the transformer's behavior is on the input. While
calculation of this score does not require training any additional models, it
provably upper-bounds the fit between a transformer and any tree-structured
approximation. Using this method, we show that transformers for three different
tasks become more tree-like over the course of training, in some cases
unsupervisedly recovering the same trees as supervised parsers. These trees, in
turn, are predictive of model behavior, with more tree-like models generalizing
better on tests of compositional generalization.


  We present a deep metric variational autoencoder for multi-modal data
generation. The variational autoencoder employs triplet loss in the latent
space, which allows for conditional data generation by sampling in the latent
space within each class cluster. The approach is evaluated on a multi-modal
dataset consisting of otoscopy images of the tympanic membrane with
corresponding wideband tympanometry measurements. The modalities in this
dataset are correlated, as they represent different aspects of the state of the
middle ear, but they do not present a direct pixel-to-pixel correlation. The
approach shows promising results for the conditional generation of pairs of
images and tympanograms, and will allow for efficient data augmentation of data
from multi-modal sources.


  An upper bound on degrees of elements of a minimal generating system for
invariants of quivers of dimension (2,...,2) is established over a field of
arbitrary characteristic and its precision is estimated. The proof is based on
the reduction to the problem of description of maximal paths satisfying certain
condition.


  Increasing the number of parameters in large language models (LLMs) usually
improves performance in downstream tasks but raises compute and memory costs,
making deployment difficult in resource-limited settings. Quantization
techniques, which reduce the bits needed for model weights or activations with
minimal performance loss, have become popular due to the rise of LLMs. However,
most quantization studies use pre-trained LLMs, and the impact of quantization
on instruction-tuned LLMs and the relationship between perplexity and benchmark
performance of quantized LLMs are not well understood. Evaluation of quantized
LLMs is often limited to language modeling and a few classification tasks,
leaving their performance on other benchmarks unclear. To address these gaps,
we propose a structured evaluation framework consisting of three critical
dimensions: (1) knowledge \& capacity, (2) alignment, and (3) efficiency, and
conduct extensive experiments across ten diverse benchmarks. Our experimental
results indicate that LLMs with 4-bit quantization can retain performance
comparable to their non-quantized counterparts, and perplexity can serve as a
proxy metric for quantized LLMs on most benchmarks. Furthermore, quantized LLMs
with larger parameter scales can outperform smaller LLMs. Despite the memory
savings achieved through quantization, it can also slow down the inference
speed of LLMs. Consequently, substantial engineering efforts and hardware
support are imperative to achieve a balanced optimization of decoding speed and
memory consumption in the context of quantized LLMs.


  The notion of quantum hashing formalized by F. Ablayev and A. Vasiliev in
2013. F. Ablayev and M. Ablayev in 2014 introduced the notion of quantum hash
generator which is convenient technical tool for constructing quantum hash
func- tions. M. Ziatdinov in 2014 presented group approach for constructing
quantum hash functions. All these mentioned above results present constructions
of quan- tum hash functions based on abelian groups. This paper continue the
research on quantum hashing. Our approach allows us to construct quantum hash
function working on any (finite) group. Also our approach allows us to
construct quantum hash functions based on classical hash function from $NC^1$.


  Majorana modes are zero-energy excitations of a topological superconductor
that exhibit non-Abelian statistics. Following proposals for their detection in
a semiconductor nanowire coupled to an s-wave superconductor, several tunneling
experiments reported characteristic Majorana signatures. Reducing disorder has
been a prime challenge for these experiments because disorder can mimic the
zero-energy signatures of Majoranas, and renders the topological properties
inaccessible. Here, we show characteristic Majorana signatures in InSb nanowire
devices exhibiting clear ballistic transport properties. Application of a
magnetic field and spatial control of carrier density using local gates
generates a zero bias peak that is rigid over a large region in the parameter
space of chemical potential, Zeeman energy, and tunnel barrier potential. The
reduction of disorder allows us to resolve separate regions in the parameter
space with and without a zero bias peak, indicating topologically distinct
phases. These observations are consistent with the Majorana theory in a
ballistic system, and exclude for the first time the known alternative
explanations that invoke disorder or a nonuniform chemical potential.


  Almost forty years ago, Connes, Feldman and Weiss proved that for measurable
equivalence relations the notions of amenability and hyperfiniteness coincide.
In this paper we define the uniform version of amenability and hyperfiniteness
for measurable graphed equivalence relations of bounded vertex degrees and
prove that these two notions coincide as well. Roughly speaking, a measured
graph $\cG$ is uniformly hyperfinite if for any $\eps>0$ there exists $K\geq 1$
such that not only $\cG$, but all of its subgraphs of positive measure are
$(\eps,K)$-hyperfinite. We also show that this condition is equivalent to
weighted hyperfiniteness and a strong version of fractional hyperfiniteness, a
notion recently introduced by Lov\'asz.
  As a corollary, we obtain a characterization of exactness of finitely
generated groups via uniform hyperfiniteness.


  We study learning problems in which the conditional distribution of the
output given the input varies as a function of additional task variables. In
varying-coefficient models with Gaussian process priors, a Gaussian process
generates the functional relationship between the task variables and the
parameters of this conditional. Varying-coefficient models subsume hierarchical
Bayesian multitask models, but also generalizations in which the conditional
varies continuously, for instance, in time or space. However, Bayesian
inference in varying-coefficient models is generally intractable. We show that
inference for varying-coefficient models with isotropic Gaussian process priors
resolves to standard inference for a Gaussian process that can be solved
efficiently. MAP inference in this model resolves to multitask learning using
task and instance kernels, and inference for hierarchical Bayesian multitask
models can be carried out efficiently using graph-Laplacian kernels. We report
on experiments for geospatial prediction.


  This is an overview about a method of constructing ccc forcings: Suppose
first that a continuous, commutative system of complete embeddings between
countable forcings indexed along $\omega_1$ is given. Then its direct limit
satisfies ccc by a well-known theorem on finite support iterations. However,
this limit has size at most $\omega_1$. To get larger forcings, we do not
consider linear systems but higher-dimensional systems which are indexed along
simplified morasses.


  We derive a microscopic equation of motion for the dynamical orientational
correlators of molecular crystals. Our approach is based upon mode coupling
theory. Compared to liquids we find four main differences: (i) the memory
kernel contains Umklapp processes, (ii) besides the static two-molecule
orientational correlators one also needs the static one-molecule orientational
density as an input, where the latter is nontrivial, (iii) the static
orientational current density correlator does contribute an anisotropic,
inertia-independent part to the memory kernel, (iv) if the molecules are
assumed to be fixed on a rigid lattice, the tensorial orientational correlators
and the memory kernel have vanishing l,l'=0 components. The resulting mode
coupling equations are solved for hard ellipsoids of revolution on a rigid
sc-lattice. Using the static orientational correlators from Percus-Yevick
theory we find an ideal glass transition generated due to precursors of
orientational order which depend on X and p, the aspect ratio and packing
fraction of the ellipsoids. The glass formation of oblate ellipsoids is
enhanced compared to that for prolate ones. For oblate ellipsoids with X <~ 0.7
and prolate ellipsoids with X >~ 4, the critical diagonal nonergodicity
parameters in reciprocal space exhibit more or less sharp maxima at the zone
center with very small values elsewhere, while for prolate ellipsoids with 2 <~
X <~ 2.5 we have maxima at the zone edge. The off-diagonal nonergodicity
parameters are not restricted to positive values and show similar behavior. For
0.7 <~ X <~ 2, no glass transition is found. In the glass phase, the
nonergodicity parameters show a pronounced q-dependence.


  To complement the 2MASS Redshift Survey (2MRS) and the 2MASS Tully-Fisher
survey (2MTF) a search for 21cm HI line emission of 2MASS bright galaxy
candidates has been pursued along the dust-obscured plane of the Milky Way with
the 100m Nancay Radio Telescope. For our sample selection we adopted an
isophotal extinction-corrected K-band magnitude limit of $K_s^o = 11.25$mag,
corresponding to the first 2MRS data release and 2MTF, for which the 2MASX
completeness level remains fairly constant deep into the Zone of Avoidance
(ZoA). About one thousand galaxies without prior redshift measurement
accessible from Nancay (Dec > -40\deg) were observed to an rms noise level of
~3 mJy for the velocity range -250 to 10'600 km/s. This resulted in 220 clear
and 12 marginal detections of the target sample. Only few detections have
redshifts above 8000 km/s due to recurring radio frequency interference (RFI).
A further 29 detections and 6 marginals have their origin in non-target
galaxies in the telescope beam. The newly detected galaxies are on average
considerably more \HI-rich (mostly $10^9 - 10^{10}$M$_\odot$) compared to
systematic (blind) HI surveys. The HI detections reveal various new filaments
crossing the mostly uncharted northern ZoA (e.g. at $\ell \sim 90\deg, 130\deg,
160\deg$), whilst consolidating galaxy agglomerations in Monoceros and Puppis
($\ell \sim 220\deg, 240\deg$). Considerably new insight has been gained about
the extent of the Perseus-Pisces Supercluster through the confirmation of a
ridge ($\ell \sim 160\deg$) encompassing the 3C129 cluster that links
Perseus-Pisces to Lynx, and the continuation of the second Perseus-Pisces arm
($\ell \sim 90\deg$) across the ZoA.


  Extensive numerical analysis of the eigenspectra of the $SU_q(N)$ invariant
Perk-Schultz Hamiltonian shows some simple regularities for a significant part
of the eigenspectrum. Inspired by those results we have found two set of
solutions of the associated nested Bethe-ansatz equations. The first set is
obtained at a special value of the anisotropy ($q = \exp(i2\pi (N-1)/N)$) and
describes in particular the ground state and nearby excitations as a sum of
free-fermion quasienergies. The second set of solutions provides the energies
in the sectors whose number $n_i$ of particles of distinct species ($i =0,
>..., N-1$) are less or equal to the unity except for one of the species. For
this last set we obtain the eigenspectra of a free fermion model for arbitrary
values of the anisotropy.


  We prove that for every positive integer $k$ there exist an
inclusion-exclusion polynomial $Q_{\{q_1,q_2,...,q_k\}}$ with the height at
least $c^{2^k}\prod_{j=1}^{k-2}q_j^{2^{k-j-1}-1}$, where $c$ is a positive
constant and $q_1<q_2<...<q_k$ are pairwise coprime and arbitrary large.


  In this paper, we study existence of isometric embedding of $S_q^m$ into
$S_p^n,$ where $1\leq p\neq q\leq \infty$ and $n\geq m\geq 2.$ We show that for
all $n\geq m\geq 2$ if there exists a linear isometry from $S_q^m$ into
$S_p^n$, where $(q,p)\in(1,\infty]\times(1,\infty)
\cup(1,\infty)\setminus\{3\}\times\{1,\infty\}$ and $p\neq q,$ then we must
have $q=2.$ This mostly generalizes a classical result of Lyubich and
Vaserstein. We also show that whenever $S_q$ embeds isometrically into $S_p$
for $(q,p)\in \left(1,\infty\right)\times\left[2,\infty
\right)\cup[4,\infty)\times\{1\} \cup\{\infty\}\times\left(
1,\infty\right)\cup[2,\infty)\times\{\infty\}$ with $p\neq q,$ we must have
$q=2.$ Thus, our work complements work of Junge, Parcet, Xu and others on
isometric and almost isometric embedding theory on non-commutative
$L_p$-spaces. Our methods rely on several new ingredients related to
perturbation theory of linear operators, namely Kato-Rellich theorem, theory of
multiple operator integrals and Birkhoff-James orthogonality, followed by
thorough and careful case by case analysis. The question whether for $m\geq 2$
and $1<q<2,$ $S_q^m$ embeds isometrically into $S_\infty^n$, was left open in
\textit{Bull. London Math. Soc.} 52 (2020) 437-447.


  Existing approaches to solving combinatorial optimization problems on graphs
suffer from the need to engineer each problem algorithmically, with practical
problems recurring in many instances. The practical side of theoretical
computer science, such as computational complexity, then needs to be addressed.
Relevant developments in machine learning research on graphs are surveyed for
this purpose. We organize and compare the structures involved with learning to
solve combinatorial optimization problems, with a special eye on the
telecommunications domain and its continuous development of live and research
networks.


  Entity resolution is the task of disambiguating records that refer to the
same entity in the real world. In this work, we explore adapting one of the
most efficient and accurate Jaccard-based entity resolution algorithms -
PPJoin, to the private domain via homomorphic encryption. Towards this, we
present our precise adaptation of PPJoin (HE-PPJoin) that details certain
subtle data structure modifications and algorithmic additions needed for
correctness and privacy. We implement HE-PPJoin by extending the PALISADE
homomorphic encryption library and evaluate over it for accuracy and incurred
overhead. Furthermore, we directly compare HE-PPJoin against P4Join, an
existing privacy-preserving variant of PPJoin which uses fingerprinting for raw
content obfuscation, by demonstrating a rigorous analysis of the efficiency,
accuracy, and privacy properties achieved by our adaptation as well as a
characterization of those same attributes in P4Join.


  This paper develops a risk-aware net demand forecasting product for virtual
power plants, which helps reduce the risk of high operation costs. At the
training phase, a bilevel program for parameter estimation is formulated, where
the upper level optimizes over the forecast model parameter to minimize the
conditional value-at-risk (a risk metric) of operation costs. The lower level
solves the operation problems given the forecast. Leveraging the specific
structure of the operation problem, we show that the bilevel program is
equivalent to a convex program when the forecast model is linear. Numerical
results show that our approach effectively reduces the risk of high costs
compared to the forecasting approach developed for risk-neutral decision
makers.


  The trace anomaly of gluodynamics on the lattice shows clear fingerprints of
a dimension two condensate above the phase transition. The condensate manifests
itself through even powers of the inverse temperature while the total
perturbative contribution corresponds to a mild temperature dependence and
turns out to be compatible with zero within errors. We try several resummation
methods based on a renormalization group improvement. The trace anomaly data
are analyzed and compared with other determinations of the dimension two
condensate based on the Polyakov loop and the heavy qq free energy, yielding
roughly similar numerical values. The role of glueballs near the transition is
also discussed.


  We describe the solution of an optimal stopping problem for a stable L\'evy
process killed at state-dependent rate, which can be seen as a model for
bankruptcy. The killing rate is chosen in such a way that the killed process
remains self-similar, and the solution to the optimal stopping problem is
obtained by characterising a self-similar Markov process associated with the
stable process. The optimal stopping strategy is to stop upon first passage
into an interval, found explicitly in terms of the parameters of the model.


  We introduce Kapre, Keras layers for audio and music signal preprocessing.
Music research using deep neural networks requires a heavy and tedious
preprocessing stage, for which audio processing parameters are often ignored in
parameter optimisation. To solve this problem, Kapre implements time-frequency
conversions, normalisation, and data augmentation as Keras layers. We report
simple benchmark results, showing real-time on-GPU preprocessing adds a
reasonable amount of computation.


  We analyze the storage and retrieval of intense-broadband pulses with the
added effects of Doppler broadening and detuning in a $\Lambda$ configuration.
We compute analytical solutions via the inverse scattering technique and show
how the signal field is transferred to a spin-wave in the atomic medium and
later retrieved by the interaction of a control pulse. Due to the intensity of
the pulses, the pulse area (as defined for self-induced transparency) plays a
key role in the interaction, as it determines the location of the spin wave
within the medium. Additionally, we compare our results to non-ideal conditions
by considering pulses of finite length and the effect of spontaneous emission.


  Online continual learning, especially when task identities and task
boundaries are unavailable, is a challenging continual learning setting. One
representative kind of methods for online continual learning is replay-based
methods, in which a replay buffer called memory is maintained to keep a small
part of past samples for overcoming catastrophic forgetting. When tackling with
online continual learning, most existing replay-based methods focus on
single-label problems in which each sample in the data stream has only one
label. But multi-label problems may also happen in the online continual
learning setting in which each sample may have more than one label. In the
online setting with multi-label samples, the class distribution in data stream
is typically highly imbalanced, and it is challenging to control class
distribution in memory since changing the number of samples belonging to one
class may affect the number of samples belonging to other classes. But class
distribution in memory is critical for replay-based memory to get good
performance, especially when the class distribution in data stream is highly
imbalanced. In this paper, we propose a simple but effective method, called
optimizing class distribution in memory (OCDM), for multi-label online
continual learning. OCDM formulates the memory update mechanism as an
optimization problem and updates the memory by solving this problem.
Experiments on two widely used multi-label datasets show that OCDM can control
the class distribution in memory well and can outperform other state-of-the-art
methods.


  Using archival BATSE (Burst and Transient Source Experiment) 20-60 keV band
X-ray flux and pulse frequency time series, we look for correlations between
torque, luminosity and specific angular momentum for three high mass X-ray
binary pulsars Vela X-1, GX 301-2 and OAO 1657-415. Our results show that there
is no correlation between pulse frequency derivative and flux which may be an
indication of the absence of stable prograde accretion disk. From the strong
correlation of specific angular momentum and torque, we conclude that the
accretion geometry changes continuously as suggested by the hydrodynamic
simulations(Blondin et al. 1990).


  Education in statistics, the application of statistics in scientific
research, and statistics itself as a scientific discipline are in crisis.
Within science, the main cause of the crisis is the insufficiently clarified
concept of probability. This article aims to separate the concept of
probability which is scientifically based from other concepts that do not have
this characteristic. The scientifically based concept of probability is
Kolmogorovs concept of probability models together with the conditions of their
applicability. Bayesian statistics is based on the subjective concept of
probability, and as such can only have a heuristic value in searching for the
truth, but it cannot and must not replace the truth. The way out of the crisis
should take Kolmogorov and Bayesian analysis as elements, each of which has a
well-defined and limited use. Only together with qualitative analysis and other
types of quantitative analysis, and combined with experiments, they can
contribute to reaching correct conclusions.


  Over the past decade, the importance of the 1D signature which can be seen as
a functional defined along a path, has been pivotal in both path-wise
stochastic calculus and the analysis of time series data. By considering an
image as a two-parameter function that takes values in a $d$-dimensional space,
we introduce an extension of the path signature to images. We address numerous
challenges associated with this extension and demonstrate that the 2D signature
satisfies a version of Chen's relation in addition to a shuffle-type product.
Furthermore, we show that specific variations of the 2D signature can be
recursively defined, thereby satisfying an integral-type equation. We analyze
the properties of the proposed signature, such as continuity, invariance to
stretching, translation and rotation of the underlying image. Additionally, we
establish that the proposed 2D signature over an image satisfies a universal
approximation property.


  We calculate the ratio $f_{B_s}/f_{B_d}$ by following the Oakes' method which
is based on chiral symmetry breaking, but we improve his calculation by
performing the calculation of the factor
$<0|{\bar{b}}{\gamma}_5s|B_s>$/$<0|{\bar{b}}{\gamma}_5d|B_d>$ in the mock meson
model. In this calculation we improved the mock meson model by using the value
of the parameter $\beta$ which is obtained by the variational method in the
relativistic quark model. We also calculate $f_{D_s}/f_{D_d}$, and then
$(f_{B_s}/f_{B_d})\, /\, (f_{D_s}/f_{D_d})$. In this method we also obtain the
ratio $f_{B_s}/f_{D_s}$ and $f_{B_d}/f_{D_d}$ which are important for the
knowledge of CP violation and $B$-$\bar{B}$ mixing.


  We present a comprehensive review of the theoretical and experimental
progress in the investigation of novel high-temperature quantum chromodynamics
phenomena in small systems at both the Relativistic Heavy Ion Collider and the
Large Hadron Collider. We highlight the challenges and opportunities associated
with studying small systems, by which we generally mean collision systems that
involve at least one light ion or even a photon projectile. We discuss
perspectives on possible future research directions to better understand the
underlying physics at work in the collisions of small systems.


  We study graph spanners for point-set in the high-dimensional Euclidean
space. On the one hand, we prove that spanners with stretch <\sqrt{2} and
subquadratic size are not possible, even if we add Steiner points. On the other
hand, if we add extra nodes to the graph (non-metric Steiner points), then we
can obtain (1+\eps)-approximate spanners of subquadratic size. We show how to
construct a spanner of size n^{2-\Omega(\eps^3)}, as well as a directed version
of the spanner of size n^{2-\Omega(\eps^2)}.
  We use our directed spanner to obtain an algorithm for computing
(1+\eps)-approximation to Earth-Mover Distance (optimal transport) between two
sets of size n in time n^{2-\Omega(\eps^2)}.


  For every NAND formula of size N, there is a bounded-error N^{1/2+o(1)}-time
quantum algorithm, based on a coined quantum walk, that evaluates this formula
on a black-box input. Balanced, or ``approximately balanced,'' NAND formulas
can be evaluated in O(sqrt{N}) queries, which is optimal. It follows that the
(2-o(1))-th power of the quantum query complexity is a lower bound on the
formula size, almost solving in the positive an open problem posed by Laplante,
Lee and Szegedy.


  It has been shown that there are not only transverse but also longitudinal
couplings between microwave fields and a superconducting qubit with broken
inversion symmetry of the potential energy. Using multiphoton processes induced
by longitudinal coupling fields and frequency matching conditions, we design a
universal algorithm to produce arbitrary superpositions of two-mode photon
states of microwave fields in two separated transmission line resonators, which
are coupled to a superconducting qubit. Based on our algorithm, we analyze the
generation of evenly-populated states and NOON states. Compared to other
proposals with only single-photon process, we provide an efficient way to
produce entangled microwave states when the interactions between
superconducting qubits and microwave fields are in the ultrastrong regime.


  We describe rules for building 2d theories labeled by 4-manifolds. Using the
proposed dictionary between building blocks of 4-manifolds and 2d N=(0,2)
theories, we obtain a number of results, which include new 3d N=2 theories
T[M_3] associated with rational homology spheres and new results for
Vafa-Witten partition functions on 4-manifolds. In particular, we point out
that the gluing measure for the latter is precisely the superconformal index of
2d (0,2) vector multiplet and relate the basic building blocks with coset
branching functions. We also offer a new look at the fusion of defect lines /
walls, and a physical interpretation of the 4d and 3d Kirby calculus as
dualities of 2d N=(0,2) theories and 3d N=2 theories, respectively


  Cooperative utilization of Unmanned Aerial Vehicles (UAVs) in public and
military surveillance applications has attracted significant attention in
recent years. Most UAVs are equipped with sensors that have bounded coverage
and wireless communication equipment with limited range. Such limitations pose
challenging problems to monitor mobile targets. This paper examines fulfilling
surveillance objectives to achieve better coverage while building a resilient
network between UAVs with an extended lifetime. The multiple target tracking
problem is studied by including a relay UAV within the fleet whose trajectory
is autonomously calculated in order to achieve a reliable connected network
among all UAVs. Optimization problems are formulated for single-hop and
multi-hop communications among UAVs. Three heuristic algorithms are proposed
for multi-hop communications and their performances are evaluated. A hybrid
algorithm, which dynamically switches between single-hop and multi-hop
communications is also proposed. The effect of the time horizon considered in
the optimization problem is studied. Performance evaluation results show that
the trajectories generated for the relay UAV by the hybrid algorithm can
achieve network lifetimes that are within 5% of the maximum possible network
lifetime which can be obtained if the entire trajectories of all targets were
known a priori.


  This work employs some techniques in order to filter random noise from the
information provided by minimum spanning trees obtained from the correlation
matrices of international stock market indices prior to and during times of
crisis. The first technique establishes a threshold above which connections are
considered affected by noise, based on the study of random networks with the
same probability density distribution of the original data. The second
technique is to judge the strengh of a connection by its survival rate, which
is the amount of time a connection between two stock market indices endure. The
idea is that true connections will survive for longer periods of time, and that
random connections will not. That information is then combined with the
information obtained from the first technique in order to create a smaller
network, where most of the connections are either strong or enduring in time.


  Skeleton-based Motion Capture (MoCap) systems have been widely used in the
game and film industry for mimicking complex human actions for a long time.
MoCap data has also proved its effectiveness in human activity recognition
tasks. However, it is a quite challenging task for smaller datasets. The lack
of such data for industrial activities further adds to the difficulties. In
this work, we have proposed an ensemble-based machine learning methodology that
is targeted to work better on MoCap datasets. The experiments have been
performed on the MoCap data given in the Bento Packaging Activity Recognition
Challenge 2021. Bento is a Japanese word that resembles lunch-box. Upon
processing the raw MoCap data at first, we have achieved an astonishing
accuracy of 98% on 10-fold Cross-Validation and 82% on
Leave-One-Out-Cross-Validation by using the proposed ensemble model.


  This work develops a cross correlation maximization technique, based on
statistical concepts, for pattern matching purposes in time series. The
technique analytically quantifies the extent of similitude between a known
signal within a group of data, by means of a single parameter. Specifically,
the method was applied to voice recognition problem, by selecting samples from
a given individual recordings of the 5 vowels, in Spanish. The frequency of
acquisition of the data was 11.250 Hz. A certain distinctive interval was
established from each vowel time series as a representative test function and
it was compared both to itself and to the rest of the vowels by means of an
algorithm, for a subsequent graphic illustration of the results.
  We conclude that for a minimum distinctive length, the method meets
resemblance between every vowel with itself, and also an irrefutable difference
with the rest of the vowels for an estimate length of 30 points (~2 10-3 s).


  Early matter-dominated eras (EMDEs) are a natural feature arising in many
models of the early universe and can generate a stochastic gravitational wave
background (SGWB) during the transition from an EMDE to the radiation-dominated
universe required by the time of Big Bang Nucleosynthesis. While there are
calculations of the SGWB generated in the linear regime, no detailed study has
been made of the nonlinear regime. We perform the first comprehensive
calculation of GW production in the nonlinear regime, using a hybrid $N$-body
and lattice simulation to study GW production from both a metastable matter
species and the radiation produced in its decay. We find that nonlinearities
significantly enhance GW production up to frequencies at least as large as the
inverse light-crossing time of the largest halos that form prior to reheating.
The resulting SGWB is within future observational reach for curvature
perturbations as small as those probed in the cosmic microwave background,
depending on the reheating temperature. Out-of-equilibrium dynamics could
further boost the induced SGWB, while a fully relativistic gravitational
treatment is required to resolve the spectrum at even higher frequencies.


  The K2K experiment, using a fine-grained detector in a neutrino beam of
energy $<E> \sim 1.3 \mathrm{GeV}$ has observed two-track events that can be
interpreted as a coherent reaction $\nu_\mu + \N \to \mu^- + \N + \pi^+
  (\N = \rm{C}^{12})$ or an incoherent process $\nu_\mu + (p,n) \to \mu^- +
\pi^+ + (p,n)$, the final nucleon being unobserved. The data show a significant
deficit of forward-going muons in the interval $Q^2 \lesssim 0.1 \rm{GeV}^2$,
where a sizeable coherent signal is expected. We attempt an explanantion of
this effect, using a PCAC formula that includes the effect of the non-vanishing
muon mass. A suppression of about 25 % is caused by a destructive interference
of the axial vector and pseudoscalar (pion-exchange) amplitudes. The incoherent
background is also reduced by 10 - 15 %. As a consequence the discrepancy
between theory and observation is significantly reduced.


  Confidential Content-Based Publish/Subscribe (C-CBPS) is an interaction
(pub/sub) model that allows parties to exchange data while still protecting
their security and privacy interests. In this paper we advance the state of the
art in C-CBPS by showing how all predicate circuits in NC1 (logarithmic-depth,
bounded fan-in) can be securely computed by a broker while guaranteeing perfect
information-theoretic security. Previous work could handle only strictly
shallower circuits (e.g. those with depth O(\sqrt{\lg n}) [SYY99, V76]. We
present three protocols -- UGP-Match, FSGP-Match and OFSGP-Match -- all three
are based on (2-decomposable randomized encodings of) group programs and handle
circuits in NC1. UGP-Match is conceptually simple and has a clean proof of
correctness but it is inefficient and impractical. FSGP-Match uses a "fixed
structure" trick to achieve efficiency and scalability. And, finally,
OFSGP-Match uses hand-optimized group programs to wring greater efficiencies.
We complete our investigation with an experimental evaluation of a prototype
implementation.


  It is proposed the new microscopic theory of Vavilov-Cherenkov radiation
(VCR), emitted directly by medium in non-equilibrium state, arising due to the
interaction of medium with a sufficiently fast charged particle. Contrary to
the macroscopic VCR theory of Tamm-Frank and quantum VCR theory of Ginzburg, we
establish the new VCR parametric resonance mechanism and the new threshold of
VCR effect, which is better corresponding to the VCR observations. We show that
counting of the, known from Abraham's electrodynamics, force density
F_A=0.5rot[PE] (P is the polarization vector of the medium in locally
non-equilibrium anisotropic state, arising due to the non-stationary electric
field E of particle, moving with the constant speed v) defines the possibility
of parametric resonance excitation of the transversal to E polarization waves
P. We get that the condition of exponential growth with time of the amplitude
of the wave P, providing the realization of VCR effect, is |v|>v_th=c/n_*,
where c is the light speed in vacuum, (n_*)>n>1, and n_* is the refraction
index of the isotropic medium in the equilibrium state.


  We construct qualitatively new examples of superabundant tropical curves
which are non-realizable in genus $3$ and $4$. These curves are in
$\mathbb{R}^3$ and $\mathbb{R}^4$ respectively, and have properties resembling
canonical embeddings of genus $3$ and $4$ algebraic curves. In particular, the
genus $3$ example is a degree $4$ planar tropical curve, and the genus $4$
example is contained in the product of a tropical line and a tropical conic.
They have excess dimension of deformation space equal to $1$. Non-realizability
follows by combining this with a dimension calculation for the corresponding
space of logarithmic curves.


  We explore the unconventional wave scattering properties of non-Hermitian
systems in which amplification or damping are induced by time-periodic
modulation. These non- Hermitian time-Floquet systems are capable of
non-reciprocal operations in the frequency domain, which can be exploited to
induce novel physical phenomena such as unidirectional wave amplification and
perfect non-reciprocal response with zero or even negative insertion losses.
This unique behavior is obtained by imparting a specific low-frequency
time-periodic modulation to the coupling between lossless resonators, promoting
only upward frequency conversion, and leading to non-reciprocal parametric
gain. We provide a full-wave demonstration of our findings in a one-way
microwave amplifier, and establish the potential of non-Hermitian time-Floquet
devices for insertion-loss free microwave isolation and unidirectional
parametric amplification.


  We present observations of the BL Lac object 1ES 0414+009 in the >200 GeV
gamma-ray band by the VERITAS array of Cherenkov telescopes. 1ES 0414+009 was
observed by VERITAS between January 2008 and February 2011, resulting in 56.2
hours of good quality pointed observations. These observations resulted in a
detection of 822 events from the source corresponding to a statistical
significance of 6.4 standard deviations (6.4 sigma) above the background. The
source flux, showing no evidence for variability, is measured as 5.2 +/-
1.1_stat +/- 2.6_sys * 10^-12 photons cm^-2 s^-1 above 200 GeV, equivalent to
approximately 2% of the Crab Nebula flux above this energy. The differential
photon spectrum from 230 GeV to 850 GeV is well fit by a power law with an
photon index of Gamma 3.4 +/- 0.5_stat +/- 0.3_sys and a flux normalization of
1.6 +/- 0.3_stat +/- 0.8_sys * 10^-11 photons cm^-2 s^-1 at 300 GeV. We also
present multiwavelength results taken in the optical (MDM), X-ray (Swift-XRT),
and GeV (Fermi-LAT) bands and use these results to construct a broadband
spectral energy distribution (SED). Modeling of this SED indicates that
homogenous one-zone leptonic scenarios are not adequate to describe emission
from the system, with a lepto-hadronic model providing a better fit to the
data.


  In this work the effects of impurity in various insulating phases of the
twisted bilayer graphene (TBG) are studied. The well-accepted continuum
model\cite{b} is employed and the local density of states (DOS) is calculated.
It is found that insulating phases breaking different symmetries proposed in
previous theories\cite{pa,op1,Lee_2019} are distinguishable via the number and
properties of in-gap bound state peaks induced by impurities in local DOS.
Insulating phases breaking the same previously proposed symmetries can be
further classified by the remaining anti-unitary symmetries and distinguished
by the corresponding remaining Kramers degeneracy of bound states. The in-gap
bound state peaks in local DOS and the degeneracy of the bound states can in
principle be detected in scanning tunnelling microscopy (STM) experiments, and
thus can help to the distinction of various insulating phases.


  We discuss the one-loop quantum corrections to the top quark width and to the
hadronic widths of the Higgs bosons of the MSSM, and emphasize the results
obtained in particular regions of the MSSM parameter space which have been
proposed to alleviate the anomalies observed in the decay modes of the $Z$ into
$b\bar{b}$ and $c\bar{c}$. We find that the corrections can be large and should
be visible through the measurement of the top quark production cross-sections
in future experiments at the Tevatron and at the LHC.


  The protonation of N2 bound to the active center of nitrogenase has been
investigated using state-of-the-art DFT calculations. Dinitrogen in the
bridging mode is activated by forming two bonds to Fe sites, which results in a
reduction of the energy for the first hydrogen transfer by 123 kJ/mol. The
axial binding mode with open sulfur bridge is less reactive by 30 kJ/mol and
the energetic ordering of the axial and bridged binding mode is reversed in
favor of the bridging dinitrogen during the first protonation. Protonation of
the central ligand is thermodynamically favorable but kinetically hindered. If
the central ligand is protonated, the proton is transferred to dinitrogen
following the second protonation. Protonation of dinitrogen at the Mo site does
not lead to low-energy intermediates.


  We study systems interpolating between the 3D incompressible Euler and
electron--MHD equations, given by \begin{equation*}
  \partial_t B + V \cdot \nabla B = B\cdot \nabla V, \qquad V = -\nabla\times
(-\Delta)^{-a} B, \qquad \nabla\cdot B = 0,
  \end{equation*} where $B$ is a time-dependent vector field in $\mathbb{R}^3$.
Under the assumption that the initial data is axi-symmetric without swirl, we
prove local well-posedness of Lipschitz continuous solutions and existence of
traveling waves in the range $1/2<a<1$. These generalize the corresponding
results for the 3D axisymmetric Euler equations and should be useful in the
study of stability and instability for axisymmetric solutions.


  We propose a spin field-effect transistor based on spin-orbit (s-o) coupling
of both the Rashba and the Dresselhaus types. Differently from earlier
proposals, spin transport through our device is tolerant against
spin-independent scattering processes. Hence the requirement of strictly
ballistic transport can be relaxed. This follows from a unique interplay
between the Dresselhaus and the (gate-controlled) Rashba interactions; these
can be tuned to have equal strengths thus yielding k-independent eigenspinors
even in two dimensions. We discuss implementations with two-dimensional devices
and quantum wires. In the latter, our setup presents strictly parabolic
dispersions which avoids complications arising from anticrossings of different
bands.


  We consider the effects of disorder in a Dirac-like Hamiltonian. In order to
use conformal perturbation theory, we argue that one should consider disorder
in an imaginary vector potential. This affects significantly the signs of the
lowest order $\beta$eta functions. We present evidence for the existence of two
distinct universality classes, depending on the relative strengths of the gauge
field verses impurity disorder strengths. In one class all disorder is driven
irrelevant by the gauge field disorder.


  We study the four-dimensional N=2 superconformal field theories that describe
D3-branes probing the recently constructed N=2 S-folds in F-theory. We
introduce a novel, infinite class of superconformal field theories related to
S-fold theories via partial Higgsing. We determine several properties of both
the S-fold models and this new class of theories, including their central
charges, Coulomb branch spectrum, and moduli spaces of vacua, by bringing to
bear an array of field-theoretical techniques, to wit, torus-compactifications
of six-dimensional N=(1,0) theories, class S technology, and the SCFT/VOA
correspondence.


  Bimetallic nanoreactors in which a plasmonic metal is used to funnel solar
energy towards a catalytic metal have recently been studied experimentally, but
a detailed theoretical understanding of these systems is lacking. Here, we
present theoretical results of hot-carrier generation rates of different Au-Pd
nanoarchitectures. In particular, we study spherical core-shell nanoparticles
with a Au core and a Pd shell as well as antenna-reactor systems consisting of
a large Au nanoparticle with acts as antenna and a smaller Pd satellite
nanoparticle separated by a gap. In addition, we investigate an antenna-reactor
system in which the satellite is a core-shell nanoparticle. Hot-carrier
generation rates are obtained from an atomistic quantum-mechanical modelling
technique which combines a solution of Maxwell's equation with a tight-binding
description of the nanoparticle electronic structure. We find that
antenna-reactor systems exhibit significantly higher hot-carrier generation
rates in the catalytic material than the core-shell system as a result of
strong electric field enhancements associated with the gap between the antenna
and the satellite. For these systems, we also study the dependence of
hot-carrier generation rate on the size of the gap, the radius of the antenna
nanoparticle and the direction of light polarization. Our insights pave the way
towards a mechanistic understanding of hot-carrier generation in heterogeneous
nanostructures for photocatalysis and other energy conversion applications.


  In this article, we prove linear stability, scattering and inviscid damping
with optimal decay rates for the linearized 2D Euler equations around a large
class of strictly monotone shear flows, $(U(y),0)$, in a periodic channel under
Sobolev perturbations. Here, we consider the settings of both an infinite
periodic channel of period $L$, $\mathbb{T}_{L}\times \mathbb{R}$, as well as a
finite periodic channel, $\mathbb{T}_{L} \times [0,1]$, with impermeable walls.
The latter setting is shown to not only be technically more challenging, but to
exhibit qualitatively different behavior due to boundary effects.


  We study a localization of functions defined on Vilenkin groups. To measure
the localization we introduce two uncertainty products $UP_{\lambda}$ and
$UP_{G}$ that are similar to the Heisenberg uncertainty product. $UP_{\lambda}$
and $UP_{G}$ differ from each other by the metric used for the Vilenkin group
$G$. We discuss analogs of a quantitative uncertainty principle.
Representations for $UP_{\lambda}$ and $UP_{G}$ in terms of Walsh and Haar
basis are given.


  This paper reports the results of a Berkeley-Illinois-Maryland array
interferometric observation of EP Aqr, a semiregular pulsating star with a
double component line profile in the CO J=1-0 line. The broad component shows a
flat-top profile, and the narrow component shows a spiky strong peak. Though
the previous single dish observations suggested that the CO J=2-1 line exhibits
a Gaussian-like profile, the CO J=1-0 line does not. The spatial distributions
of both the narrow and broad components appears to be roughly round with the
same peak positions. No significant velocity gradient is seen. The
spatial-kinetic properties of the molecular envelope of EP Aqr are reminiscent
of a multiple shell structure model rather than a bipolar flow and disk model.
A problem of this interpretation is that no evidence of interaction between the
narrow and broad component regions is seen. A Gaussian-like feature seen in the
CO J=2-1 line might play a key role to understand the spatio-kinetic properties
of the molecular envelope of EP Aqr.


  For a scheme X, we construct a sheaf C of complexes on X such that for every
quasi-compact open subset U of X, C(U) is quasi-isomorphic to the Hochschild
complex of the scheme U. Since C is moreover acyclic for taking sections on
quasi-compact opens, we obtain a local to global spectral sequence for
Hochschild cohomology if X is quasi-compact.


  In this paper, we show that every D3-directing CNFA can be mapped uniquely to
a DFA with the same synchronizing word length. This implies that \v{C}ern\'y's
conjecture generalizes to CNFAs and that the general upper bound for the length
of a shortest D3-directing word is equal to the Pin-Frankl bound for DFAs. As a
second consequence, for several classes of CNFAs sharper bounds are
established. Finally, our results allow us to detect all critical CNFAs on at
most 6 states. It turns out that only very few critical CNFAs exist.


  The interaction of CO with the Fe3O4(001)-(rt2xrt2)R45{\deg} surface was
studied using temperature programmed desorption (TPD), scanning tunneling
microscopy (STM) and x-ray photoelectron spectroscopy (XPS), the latter both
under ultrahigh vacuum (UHV) conditions and in CO pressures up to 1 mbar. In
general, the CO-Fe3O4 interaction is found to be weak. The strongest adsorption
occurs at surface defects, leading to small TPD peaks at 115 K, 130 K and 190
K. Desorption from the regular surface occurs in two distinct regimes. For
coverages up to 2 CO molecules per (rt2xrt2)R45{\deg} unit cell, the desorption
maximum shows a large shift with increasing coverage, from initially 105 K to
70 K. For coverages between 2 and 4 molecules per (rt2xrt2)R45{\deg} unit cell,
a much sharper desorption feature emerges at 50 K. Thermodynamic analysis of
the TPD data suggests a phase transition from a dilute 2D gas into an ordered
overlayer with CO molecules bound to surface Fe3+ sites. XPS data acquired at
45 K in UHV are consistent with physisorption. Some carbon-containing species
are observed in the near-ambient-pressure XPS experiments at room temperature,
but are attributed to contamination and/or reaction with CO with water from the
residual gas. No evidence was found for surface reduction or carburization by
CO molecules.


  Earlier it has been supposed that the law of conservation of energy in
chemical reactions has the following form: DU=DQ-PDV+SUM(muiDN) In the present
paper it has been proved by means of the theory of ordinary differential
equations that in the biggest part of the chemical reactions it must have the
following form: DU=DQ+PDV+SUM(muiDN) The result obtained allows to explain a
paradox in chemical thermodynamics: the heat of chemical processes measured by
calorimetry and by the Vant-Hoff equation differs very much from each other.
The result is confirmed by many experiments.


  We report Coulomb drag measurements on GaAs-AlGaAs electron-hole bilayers.
The two layers are separated by a 10 or 25nm barrier. Below T$\approx$1K we
find two features that a Fermi-liquid picture cannot explain. First, the drag
on the hole layer shows an upturn, which may be followed by a downturn. Second,
the effect is either absent or much weaker in the electron layer, even though
the measurements are within the linear response regime. Correlated phases have
been anticipated in these, but surprisingly, the experimental results appear to
contradict Onsager's reciprocity theorem.


  The accuracy and efficiency of ab-initio quantum Monte Carlo (QMC) algorithms
benefits greatly from compact variational trial wave functions that accurately
reproduce ground state properties of a system. We investigate the possibility
of using multi-Slater-Jastrow trial wave functions with non-orthogonal
determinants by optimizing identical single particle orbitals independently in
separate determinants. As a test case, we compute variational and fixed-node
diffusion Monte Carlo (FN-DMC) energies of a C$_2$ molecule. For a given
multi-determinant expansion, we find that this non-orthogonal orbital
optimization results in a consistent improvement in the variational energy and
the FN-DMC energy on the order of a few tenths of an eV. Our calculations
indicate that trial wave functions with non-orthogonal determinants can improve
computed energies in a QMC calculation when compared to their orthogonal
counterparts.


  We consider the problem of reinforcement learning under safety requirements,
in which an agent is trained to complete a given task, typically formalized as
the maximization of a reward signal over time, while concurrently avoiding
undesirable actions or states, associated to lower rewards, or penalties. The
construction and balancing of different reward components can be difficult in
the presence of multiple objectives, yet is crucial for producing a satisfying
policy. For example, in reaching a target while avoiding obstacles, low
collision penalties can lead to reckless movements while high penalties can
discourage exploration. To circumvent this limitation, we examine the effect of
past actions in terms of safety to estimate which are acceptable or should be
avoided in the future. We then actively reshape the action space of the agent
during reinforcement learning, so that reward-driven exploration is constrained
within safety limits. We propose an algorithm enabling the learning of such
safety constraints in parallel with reinforcement learning and demonstrate its
effectiveness in terms of both task completion and training time.


  We consider an energy harvesting source that is collecting measurements from
a physical phenomenon and sending updates to a destination within a
communication session time. Updates incur transmission delays that are function
of the energy used in their transmission. The more transmission energy used per
update, the faster it reaches the destination. The goal is to transmit updates
in a timely manner, namely, such that the total age of information is minimized
by the end of the communication session, subject to energy causality
constraints. We consider two variations of this problem. In the first setting,
the source controls the number of measurement updates, their transmission
times, and the amounts of energy used in their transmission (which govern their
delays, or service times, incurred). In the second setting, measurement updates
externally arrive over time, and therefore the number of updates becomes fixed,
at the expense of adding data causality constraints to the problem. We
characterize age-minimal policies in the two settings, and discuss the
relationship of the age of information metric to other metrics used in the
energy harvesting literature.


  It is shown that in an inhomogeneous neutron matter the pairing field bounds
neutrons around the Fermi level leading to the formation of localized Andreev
states. In the case of the inner crust of neutron stars the localization length
has been determined as a function of the nuclear density.


  As research and practice in artificial intelligence (A.I.) grow in leaps and
bounds, the resources necessary to sustain and support their operations also
grow at an increasing pace. While innovations and applications from A.I. have
brought significant advances, from applications to vision and natural language
to improvements to fields like medical imaging and materials engineering, their
costs should not be neglected. As we embrace a world with ever-increasing
amounts of data as well as research and development of A.I. applications, we
are sure to face an ever-mounting energy footprint to sustain these
computational budgets, data storage needs, and more. But, is this sustainable
and, more importantly, what kind of setting is best positioned to nurture such
sustainable A.I. in both research and practice? In this paper, we outline our
outlook for Green A.I. -- a more sustainable, energy-efficient and energy-aware
ecosystem for developing A.I. across the research, computing, and practitioner
communities alike -- and the steps required to arrive there. We present a
bird's eye view of various areas for potential changes and improvements from
the ground floor of AI's operational and hardware optimizations for
datacenters/HPCs to the current incentive structures in the world of A.I.
research and practice, and more. We hope these points will spur further
discussion, and action, on some of these issues and their potential solutions.


  The new advances of the Internet of Things (IoT) technology can be utilized
to promote service delivery in several real-life applications such as
healthcare systems. The Routing Protocol for Low Power and Loss Network (RPL)
is a routing protocol designed to serve as a proper routing protocol for
packets in Wireless Sensor Networks (WSN). Among the most prominent issues
exist in the RPL protocol are packet loss within the WSN and sensors power
consumption especially in healthcare WSNs. Multiple Objective Functions (OF) in
RPL intended to find the routes from source nodes to a destination node. This
paper presents an evaluation to discover which OF is more efficient for a WSN
in a healthcare scenario where the Packet Delivery Ratio (PDR) of WSN and the
sensors' power consumption are prominent concerns. Expected transmission Count
(ETX) and Objective Function Zero (OF0) of RPL were examined in various network
densities and network topologies such as the grid and random topology. The
simulation outcomes revealed that the OF0 is more efficient regarding the PDR
and power consumption compared to the ETX in random


  We evaluate explicitly, in terms of the asymptotic data, the ratio of the
constant pre-factors in the large and small $x$ asymptotics of the tau
functions for global solutions of the tt{*}-Toda equations. This constant
problem for the sinh-Gordon equation, which is the case $n=1$ of the tt{*}-Toda
equations, was solved by C. A. Tracy. We also introduce natural symplectic
structures on the space of asymptotic data and on the space of monodromy data
for a wider class of solutions, and show that these symplectic structures are
preserved by the Riemann-Hilbert correspondence.


  We consider the one-bit quantizer that minimizes the mean squared error for a
source living in a real Hilbert space. The optimal quantizer is a projection
followed by a thresholding operation, and we provide methods for identifying
the optimal direction along which to project. As an application of our methods,
we characterize the optimal one-bit quantizer for a continuous-time random
process that exhibits low-dimensional structure. We numerically show that this
optimal quantizer is found by a neural-network-based compressor trained via
stochastic gradient descent.


  Superoscillations can explain the arbitrarily high frequencies' paradox in
black hole radiation


  We consider a class of pursuit-evasion differential games in which the evader
has continuous access to the pursuer's location, but not vice-versa. There is a
remote sensor (e.g., a radar station) that can sense the evader's location upon
a request from the pursuer and communicate that sensed location to the pursuer.
The pursuer has a budget on the total number of sensing requests. The outcome
of the game is determined by the sensing and motion strategies of the players.
We obtain an equilibrium sensing strategy for the pursuer and an equilibrium
motion strategy for the evader. We quantify the degradation in the pursuer's
pay-off due to its sensing limitations.


  Long-range $(n+2)D_{5/2} \, nF_J$ Rydberg macro-dimers are observed in an
ultracold cesium Rydberg gas for $39\leq n\leq48$. Strong dipolar "flip"
($\langle D_{5/2} F_{5/2} \vert \hat{V}_{dd} \vert F_{5/2} D_{5/2} \rangle$,
$\langle D_{5/2} F_{7/2} \vert \hat{V}_{dd} \vert F_{7/2} D_{5/2} \rangle$) and
"cross" ($\langle D_{5/2} F_{7/2} \vert \hat{V}_{dd} \vert F_{5/2} D_{5/2}
\rangle$) couplings lead to bound, fine-structure-mixed $(n+2)D_{5/2}nF_J$
macro-dimers at energies between the $F_J$ fine-structure levels. The $DF$
macro-dimers are measured by microwave photo-association from optically
prepared $[(n+2)D_{5/2}]_2$ Rydberg pair states. Calculated adiabatic potential
curves are used to elucidate the underlying physics and to model the $DF$
macro-dimer spectra, with good overall agreement. Microwave photo-association
allows Franck-Condon tuning, which we have studied by varying the detuning of a
Rydberg-atom excitation laser. Further, in Stark spectroscopy we have measured
molecular DC electric polarizabilities that are considerably larger than those
of the atomic states. The large molecular polarizabilities may be caused by
high-$\ell$ mixing. The observed linewidths of the Stark-shifted molecular
lines provide initial evidence for intra-molecular induced-dipole-dipole
interaction.


  Inspired by the event accumulation around 2.6 GeV in the
$\eta^\prime\pi^+\pi^-$ invariant mass spectrum of $J/\psi\to \gamma
\eta^\prime\pi^+\pi^-$, which was reported by the BESIII Collaboration, we
carry out the study of the mass spectrum and decay behavior of four radial
excitations in the pseudoscalar meson family, which include
$\eta^{(\prime)}(6S)$ and $\eta^{(\prime)}(7S)$. Combining with these analysis,
we present the calculation of the reactions induced by a pion or kaon on the
proton target which are relevant to these four discussed states. According to
this information, we give concrete experimental suggestion of searching for
them, which will become a new task for future experiments.


  Recent progress in matter-wave interferometry aims to directly probe the
quantum properties of matter on ever increasing scales. However, in order to
perform interferometric experiments with massive mesoscopic objects, taking
into account the constraints on the experimental set-ups, the point-like
particle approximation needs to be cast aside. In this work, we consider
near-field interferometry based on the Talbot effects with a single optical
grating for large spherical particles beyond the point-particle approximation.
We account for the suppression of the coherent grating effect and, at the same
time, the enhancement of the decoherence effects due to scattering and
absorption of grating photons.


  Deep neural networks (DNN) have been studied in various machine learning
areas. For example, event-related potential (ERP) signal classification is a
highly complex task potentially suitable for DNN as signal-to-noise ratio is
low, and underlying spatial and temporal patterns display a large intra- and
intersubject variability. Convolutional neural networks (CNN) have been
compared with baseline traditional models, i.e. linear discriminant analysis
(LDA) and support vector machines (SVM) for single trial classification using a
large multi-subject publicly available P300 dataset of school-age children (138
males and 112 females). For single trial classification, classification
accuracy stayed between 62% and 64% for all tested classification models. When
applying the trained classification models to averaged trials, accuracy
increased to 76-79% without significant differences among classification
models. CNN did not prove superior to baseline for the tested dataset.
Comparison with related literature, limitations and future directions are
discussed.


  We examine the possibility of the flavor symmetry being $SU_f(3)$ in which
the phenomenologically successful discreet symmetry $A_4$ is embedded. The
allowed quadratic and quartic potentials are constructed exploiting the full
symmetry chain $SU(3)\supset SO(4)\supset A_4$. The spontaneous symmetry
breaking involving the $SU(3)$ octet scalar fields is analyzed.


  Using our solution for the open spin-1/2 XXZ quantum spin chain with N spins
and two arbitrary boundary parameters at roots of unity, the central charge and
the conformal dimensions for bulk hole excitations are derived from the 1/N
correction to the energy (Casimir energy).


  The Debye mass sets a scale for the screening of static charges and the
scattering of fast charges within a gauge plasma. Inspired by its potential
cosmological applications, we determine a QCD Debye mass at 2-loop order in a
broad temperature range (1 GeV ... 10 TeV), demonstrating how quark mass
thresholds get smoothly crossed. Along the way, integration-by-parts identities
pertinent to massive loops at finite temperature are illuminated.


  The cross section of the process $e^+e^-\to\pi^+\pi^-$ has been measured in
the center-of-mass energy range from 0.32 to 1.2 GeV with the CMD-3 detector at
the electron-positron collider VEPP-2000. The measurement is based on an
integrated luminosity of about 88 pb$^{-1}$, of which 62 pb$^{-1}$ represent a
complete dataset collected by CMD-3 at center-of-mass energies below 1 GeV. In
the dominant region near the $\rho$ resonance a systematic uncertainty of 0.7%
was achieved. The implications of the presented results for the evaluation of
the hadronic contribution to the anomalous magnetic moment of the muon are
discussed.


  In this paper, we consider the problem of optimal scalable video delivery to
mobile users in wireless networks given arbitrary Quality Adaptation (QA)
mechanisms. In current practical systems, QA and scheduling are performed
independently by the content provider and network operator, respectively. While
most research has been focused on jointly optimizing these two tasks, the high
complexity that comes with a joint approach makes the implementation
impractical. Therefore, we present a scheduling mechanism that takes the QA
logic of each user as input and optimizes the scheduling accordingly. Hence,
there is no need for centralized QA and cross-layer interactions are minimized.
We model the QA-adaptive scheduling and the jointly optimal problem as a
Restless Bandit and a Multi-user Semi Markov Decision Process, respectively in
order to compare the loss incurred by not employing a jointly optimal scheme.
We then present heuristic algorithms in order to achieve the optimal outcome of
the Restless Bandit solution assuming the base station has knowledge of the
underlying quality adaptation of each user (QA-Aware). We also present a
simplified heuristic without the need for any higher layer knowledge at the
base station (QA-Blind). We show that our QA-Aware strategy can achieve up to
two times improvement in user network utilization compared to popular baseline
algorithms such as Proportional Fairness. We also provide a testbed
implementation of the QA-Blind scheme in order to compare it with baseline
algorithms in a real network setting.


  For every smooth and separated Deligne-Mumford stack $F$, we associate a
motive $M(F)$ in Voevodsky's category of mixed motives with rational
coefficients $\mathbf{DM}^{\eff}(k,\mathbb{Q})$. When $F$ is proper over a
field of characteristic 0, we compare $M(F)$ with the Chow motive associated to
$F$ by Toen (\cite{t}). Without the properness condition we show that $M(F)$ is
a direct summand of the motive of a smooth quasi-projective variety.


  Generative Adversarial Imitation Learning suffers from the fundamental
problem of reward bias stemming from the choice of reward functions used in the
algorithm. Different types of biases also affect different types of
environments - which are broadly divided into survival and task-based
environments. We provide a theoretical sketch of why existing reward functions
would fail in imitation learning scenarios in task based environments with
multiple terminal states. We also propose a new reward function for GAIL which
outperforms existing GAIL methods on task based environments with single and
multiple terminal states and effectively overcomes both survival and
termination bias.


  Let p and n be positive integers with p>1, and let E(p,n) be the oriented
3-manifold obtained by performing pn(p-1)-1 surgery on a positive torus knot of
type (p, pn+1). We prove that E(2,n) does not carry tight contact structures
for any n, while E(p,n) carries tight contact structures for any n and any odd
p. In particular, we exhibit the first infinite family of closed, oriented,
irreducible 3-manifolds which do not support tight contact structures. We
obtain the nonexistence results via standard methods of contact topology, and
the existence results by using a quite delicate computation of contact
Ozsvath-Szabo invariants.


  We consider the problem of inference for non-stationary time series with
heavy-tailed error distribution. Under a time-varying linear process framework
we show that there exists a suitable local approximation by a stationary
process with heavy-tails. This enable us to introduce a local
approximation-based estimator which estimates consistently time-varying
parameters of the model at hand. To develop a robust method, we also suggest a
self-weighing scheme which is shown to recover the asymptotic normality of the
estimator regardless of whether the finite variance of the underlying process
exists. Empirical evidence favoring this approach is provided.


  We apply a pulsed-light interferometer to measure both the intensity and the
phase of light that is transmitted through a strongly scattering disordered
material. From a single set of measurements we obtain the time-resolved
intensity, frequency correlations and statistical phase information
simultaneously. We compare several independent techniques of measuring the
diffusion constant for diffuse propagation of light. By comparing these
independent measurements, we obtain experimental proof of the consistency of
the diffusion model and corroborate phase statistics theory.


  LISA might detect gravitational waves from mergers of massive black hole
binaries strongly lensed by intervening galaxies (Sereno et al. 2010). The
detection of multiple gravitational lensing events would provide a new tool for
cosmography. Constraints on cosmological parameters could be placed by
exploiting either lensing statistics of strongly lensed sources or time delay
measurements of lensed gravitational wave signals. These lensing methods do not
need the measurement of the redshifts of the sources and the identification of
their electromagnetic counterparts. They would extend cosmological probes to
redshift z <= 10 and are then complementary to other lower or higher redshift
tests, such as type Ia supernovae or cosmic microwave background. The accuracy
of lensing tests strongly depends on the formation history of the merging
binaries, and the related number of total detectable multiple images. Lensing
amplification might also help to find the host galaxies. Any measurement of the
source redshifts would allow to exploit the distance-redshift test in
combination with lensing methods. Time-delay analyses might measure the Hubble
parameter H_0 with accuracy of >= 10 km s^{-1}Mpc^{-1}. With prior knowledge of
H_0, lensing statistics and time delays might constrain the dark matter density
(delta Omega_M >= 0.08, due to parameter degeneracy). Inclusion of our methods
with other available orthogonal techniques might significantly reduce the
uncertainty contours for Omega_M and the dark energy equation of state.


  In many settings it is important for one to be able to understand why a model
made a particular prediction. In NLP this often entails extracting snippets of
an input text `responsible for' corresponding model output; when such a snippet
comprises tokens that indeed informed the model's prediction, it is a faithful
explanation. In some settings, faithfulness may be critical to ensure
transparency. Lei et al. (2016) proposed a model to produce faithful rationales
for neural text classification by defining independent snippet extraction and
prediction modules. However, the discrete selection over input tokens performed
by this method complicates training, leading to high variance and requiring
careful hyperparameter tuning. We propose a simpler variant of this approach
that provides faithful explanations by construction. In our scheme, named
FRESH, arbitrary feature importance scores (e.g., gradients from a trained
model) are used to induce binary labels over token inputs, which an extractor
can be trained to predict. An independent classifier module is then trained
exclusively on snippets provided by the extractor; these snippets thus
constitute faithful explanations, even if the classifier is arbitrarily
complex. In both automatic and manual evaluations we find that variants of this
simple framework yield predictive performance superior to `end-to-end'
approaches, while being more general and easier to train. Code is available at
https://github.com/successar/FRESH


  In this paper, we propose to employ a bank of modality-dedicated
Convolutional Neural Networks (CNNs), fuse, train, and optimize them together
for person classification tasks. A modality-dedicated CNN is used for each
modality to extract modality-specific features. We demonstrate that, rather
than spatial fusion at the convolutional layers, the fusion can be performed on
the outputs of the fully-connected layers of the modality-specific CNNs without
any loss of performance and with significant reduction in the number of
parameters. We show that, using multiple CNNs with multimodal fusion at the
feature-level, we significantly outperform systems that use unimodal
representation. We study weighted feature, bilinear, and compact bilinear
feature-level fusion algorithms for multimodal biometric person identification.
Finally, We propose generalized compact bilinear fusion algorithm to deploy
both the weighted feature fusion and compact bilinear schemes. We provide the
results for the proposed algorithms on three challenging databases: CMU
Multi-PIE, BioCop, and BIOMDATA.


  We present a deterministic algorithm for computing all irreducible factors of
degree $\le d$ of a given bivariate polynomial $f\in K[x,y]$ over an algebraic
number field $K$ and their multiplicities, whose running time is polynomial in
the bit length of the sparse encoding of the input and in $d$. Moreover, we
show that the factors over $\Qbarra$ of degree $\le d$ which are not binomials
can also be computed in time polynomial in the sparse length of the input and
in $d$.


  We have calculated the dispersion curves of H vibrational modes on Pt(111),
using first-principles, total energy calculations based on a mixed-basis set
and norm-conserving pseudopotentials. Linear response theory and the harmonic
approximation are invoked. For 1 ML coverage, H atoms are assumed to occupy the
fcc hollow sites. At the Gamma point of the surface Brillouin zone, we find
modes, respectively, polarized parallel and perpendicular to the surface at
73.5 meV and 142.6 meV. The degeneracy of the parallel mode is lifted at the
zone boundaries, yielding modes at 69.6 meV and 86.3 meV, at the M point, and
at 79.4 meV and 80.8 meV, at the K point. The substrate surface modes are also
found to shift in frequencies from their calculated values for clean Pt(111).
We discuss the details of the changes in surface force constant on H adsorption
on Pt(111). We also consider the case of subsurface adsorption for 2 ML of H
and present vibrational frequencies of H atoms adsorbed in several subsurface
sites. The appearance of new vertically polarized modes in the range of 98 .
106 meV (octahedral site) and 124 . 162 meV (tetrahedral site) is discussed in
the context of experimental data.


  Relation extraction systems require large amounts of labeled examples which
are costly to annotate. In this work we reformulate relation extraction as an
entailment task, with simple, hand-made, verbalizations of relations produced
in less than 15 min per relation. The system relies on a pretrained textual
entailment engine which is run as-is (no training examples, zero-shot) or
further fine-tuned on labeled examples (few-shot or fully trained). In our
experiments on TACRED we attain 63% F1 zero-shot, 69% with 16 examples per
relation (17% points better than the best supervised system on the same
conditions), and only 4 points short to the state-of-the-art (which uses 20
times more training data). We also show that the performance can be improved
significantly with larger entailment models, up to 12 points in zero-shot,
allowing to report the best results to date on TACRED when fully trained. The
analysis shows that our few-shot systems are specially effective when
discriminating between relations, and that the performance difference in low
data regimes comes mainly from identifying no-relation cases.


  The use of key-dependent shiftRows can be considered as one of the applied
methods for altering the quality of a cryptographic algorithm. This article
describes one approach for changing the ShiftRows transformation employed in
the algorithm AES. The approach employs methods inspired from DNA processes and
structure which depended on the key while the parameters of the created new
ShiftRows have characteristics identical to those of the original algorithm AES
in addition to increase its resistance against attacks. The proposed new
ShiftRows were tested for coefficient correlation for dynamic and static
independence between the input and output. The NIST Test Suite tests were used
to test the randomness for the block cipher that used the new transformation.


  The climate of early Mars remains a topic of intense debate. Ancient terrains
preserve landscapes consistent with stream channels, lake basins, and possibly
even oceans, and thus the presence of liquid water flowing on the Martian
surface 4 billion years ago. However, despite the geological evidence,
determining how long climatic conditions supporting liquid water lasted remains
uncertain. Climate models have struggled to generate sufficiently warm surface
conditions given the faint young Sun - even assuming a denser early atmosphere.
A warm climate could have potentially been sustained by supplementing
atmospheric CO2 and H2O warming with either secondary greenhouse gases or
clouds. Alternatively, the Martian climate could have been predominantly cold
and icy, with transient warming episodes triggered by meteoritic impacts,
volcanic eruptions, methane bursts, or limit cycles. Here, we argue that a warm
and semi-arid climate capable of producing rain is most consistent with the
geological and climatological evidence.


  We investigate an extension of the Minimal Supersymmetric Standard Model
(MSSM) containing a $SU(2)$ Higgs triplet of zero hypercharge and a gauge
singlet. We focus on a scenario of this model which allows a light pseudoscalar
and/or a scalar below $100$ GeV in the spectrum, consistent with the most
recent data from the LHC and the earlier data from the LEP experiments. We
analyze the exotic decay of the discovered Higgs $(h_{125})$ into two light
(hidden) Higgs bosons present in the extension. The latter are allowed by the
uncertainties in the Higgs decay $h_{125}\to WW^*$, $h_{125}\to ZZ^*$ and
$h_{125}\to \gamma\gamma$. We have searched for such light Higgs bosons in the
$2b+2\tau$, $\geq 3\tau$, $2b+2\mu$ and $2\tau+2\mu$ final states at the LHC
with 13 and 14 TeV. A region of such parameter space can be explored with an
integrated luminosity of 25 fb$^{-1}$ at the LHC.


  We present a search for the lepton-flavour-violating decays $B^+ \to K^+
\tau^\pm \ell^\mp$, with $\ell = (e, \mu)$, using the full data sample of $772
\times 10^6$ $B\overline{B}$ pairs recorded by the Belle detector at the KEKB
asymmetric-energy $e^+ e^-$ collider. We use events in which one $B$ meson is
fully reconstructed in a hadronic decay mode. We find no evidence for $B^\pm
\to K^\pm \tau \ell$ decays and set upper limits on their branching fractions
at the 90% confidence level in the $(1$-$3) \times 10^{-5}$ range. The obtained
limits are the world's best results.


  First ideas of neutrino masses, mixing and oscillations proposed by Bruno
Pontecorvo in 1957 and later development of these ideas are considered in some
details. Original ideas of the two-neutrino mixing proposed by Maki, Nakagawa
and Sakata in 1962 are also discussed.


  The asymptotic tail behaviour of sums of independent subexponential random
variables is well understood, one of the main characteristics being the
principle of the single big jump. We study the case of dependent subexponential
random variables, for both deterministic and random sums, using a fresh
approach, by considering conditional independence structures on the random
variables. We seek sufficient conditions for the results of the theory with
independent random variables still to hold. For a subexponential distribution,
we introduce the concept of a boundary class of functions, which we hope will
be a useful tool in studying many aspects of subexponential random variables.
The examples we give in the paper demonstrate a variety of effects owing to the
dependence, and are also interesting in their own right.


  The study of the chemical composition of Planetary Nebulae in external
galaxies is of paramount importance in the fields of stellar evolution and of
the chemical enrichment history of galaxies. In the last years a number of
spectroscopic studies with 6-8m-class telescopes have been devoted to this
subject improving our knowledge of, among other, the time-evolution of the
radial metallicity gradient in disk galaxies, the chemical evolution of dwarf
galaxies, and the stellar evolution at low metallicity.


  Recent years have seen advances in generalization bounds for noisy stochastic
algorithms, especially stochastic gradient Langevin dynamics (SGLD) based on
stability (Mou et al., 2018; Li et al., 2020) and information theoretic
approaches (Xu and Raginsky, 2017; Negrea et al., 2019; Steinke and
Zakynthinou, 2020). In this paper, we unify and substantially generalize
stability based generalization bounds and make three technical contributions.
First, we bound the generalization error in terms of expected (not uniform)
stability which arguably leads to quantitatively sharper bounds. Second, as our
main contribution, we introduce Exponential Family Langevin Dynamics (EFLD), a
substantial generalization of SGLD, which includes noisy versions of Sign-SGD
and quantized SGD as special cases. We establish data-dependent expected
stability based generalization bounds for any EFLD algorithm with a O(1/n)
sample dependence and dependence on gradient discrepancy rather than the norm
of gradients, yielding significantly sharper bounds. Third, we establish
optimization guarantees for special cases of EFLD. Further, empirical results
on benchmarks illustrate that our bounds are non-vacuous, quantitatively
sharper than existing bounds, and behave correctly under noisy labels.


  The distribution of fake news is not a new but a rapidly growing problem. The
shift to news consumption via social media has been one of the drivers for the
spread of misleading and deliberately wrong information, as in addition to it
of easy use there is rarely any veracity monitoring. Due to the harmful effects
of such fake news on society, the detection of these has become increasingly
important. We present an approach to the problem that combines the power of
transformer-based language models while simultaneously addressing one of their
inherent problems. Our framework, CMTR-BERT, combines multiple text
representations, with the goal of circumventing sequential limits and related
loss of information the underlying transformer architecture typically suffers
from. Additionally, it enables the incorporation of contextual information.
Extensive experiments on two very different, publicly available datasets
demonstrates that our approach is able to set new state-of-the-art performance
benchmarks. Apart from the benefit of using automatic text summarization
techniques we also find that the incorporation of contextual information
contributes to performance gains.


  We study thermodynamical properties of a fuzzy sphere in matrix quantum
mechanics of the BFSS type including the Chern-Simons term. Various quantities
are calculated to all orders in perturbation theory exploiting the one-loop
saturation of the effective action in the large-N limit. The fuzzy sphere
becomes unstable at sufficiently strong coupling, and the critical point is
obtained explicitly as a function of the temperature. The whole phase diagram
is investigated by Monte Carlo simulation. Above the critical point, we obtain
perfect agreement with the all order results. In the region below the critical
point, which is not accessible by perturbation theory, we observe the Hagedorn
transition. In the high temperature limit our model is equivalent to a totally
reduced model, and the relationship to previously known results is clarified.


  We present a simple, general energy functional for ferromagnetic materials
based upon a local spin density extension to the Stoner theory of itinerant
ferromagnetism. The functional reproduces well available ab initio results and
experimental interfacial energies for grain boundaries in iron. The model shows
that inter-granular cohesion along symmetric tilt boundaries in iron is
dependent upon strong magnetic structure at the interface, illuminates the
mechanisms underlying this structure, and provides a simple explanation for
relaxation of the atomic structure at these boundaries.


  In recent work we have shown that a black hole stacked on a brane escapes
once it acquires a recoil velocity. This result was obtained in the {\it
probe-brane} approximation, {\it i.e.}, when the tension of the brane is
negligibly small. Therefore, it is not clear whether the effect of the brane
tension may prevent the black hole from escaping for small recoil velocities.
The question is whether a critical escape velocity exists. Here, we analyze
this problem by studying the interaction between a Dirac-Nambu-Goto brane and a
black hole assuming adiabatic (quasi-static) evolution. By describing the brane
in a fixed black hole spacetime, which restricts our conclusions to lowest
order effects in the tension, we find that the critical escape velocity does
not exist for co-dimension one branes, while it does for higher co-dimension
branes.


  This is an idiosyncratic account of the main results presented at the 31st
Rencontres de Blois, which took place from June 2nd to June 7th, 2019 in the
Castle of Blois, France.


  Some dynamical properties present in a problem concerning the acceleration of
particles in a wave packet are studied. The dynamics of the model is described
in terms of a two-dimensional area preserving map. We show that the phase space
is mixed in the sense that there are regular and chaotic regions coexisting. We
use a connection with the standard map in order to find the position of the
first invariant spanning curve which borders the chaotic sea. We find that the
position of the first invariant spanning curve increases as a power of the
control parameter with the exponent 2/3. The standard deviation of the kinetic
energy of an ensemble of initial conditions obeys a power law as a function of
time, and saturates after some crossover. Scaling formalism is used in order to
characterize the chaotic region close to the transition from integrability to
nonintegrability and a relationship between the power law exponents is derived.
The formalism can be applied in many different systems with mixed phase space.
Then, dissipation is introduced into the model and therefore the property of
area preservation is broken, and consequently attractors are observed. We show
that after a small change of the dissipation, the chaotic attractor as well as
its basin of attraction are destroyed, thus leading the system to experience a
boundary crisis. The transient after the crisis follows a power law with
exponent -2.


  Type Ia supernovae (SNe Ia) originate from the thermonuclear explosion of
carbon-oxygen white dwarfs (CO WDs), giving rise to luminous optical
transients. A relatively common variety of subluminous SNe Ia events, referred
to as SNe Iax, are believed to arise from the failed detonation of a CO WD. In
this paper, we explore failed detonation SNe Ia in the context of the
double-degenerate channel of merging white dwarfs. In particular, we have
carried out the first fully three-dimensional simulation of the merger of a ONe
WD with a CO WD. While the hot, tidally-disrupted carbon-rich disk material
originating from the CO WD secondary is readily susceptible to detonation in
such a merger, the ONe WD primary core is not. This merger yields a failed
detonation, resulting in the ejection of a small amount of mass, and leaving
behind a kicked, super-Chandrasekhar ONe WD remnant enriched by the fallback of
the products of nuclear burning. The resulting outburst is a rapidly-fading
optical transient with a small amount of radioactive $^{56}$Ni powering the
light curve. Consequently, the ONe-CO WD merger naturally produces a very faint
and rapidly-fading transient, fainter even than the faintest Type Iax events
observed to date, such as SN $2008$ha and SN 2010ae. More massive ONe primaries
than considered here may produce brighter and longer-duration transients.


  It has been observed in B->phiK* and B^{0(+)}->rho^{0(+)}K^{*0} that the
fraction of transverse decays, fT, and the fraction of longitudinal decays, fL,
are roughly equal, in opposition to the naive expectation, fT/fL << 1. If one
requires a single explanation of all polarization puzzles, two possibilities
remain within the standard model (SM): penguin annihilation and rescattering.
We examine the predictions of these two explanations for fT/fL in b -> d
decays. We also study polarization observables in B -> V T decays (V is a
vector and T is a tensor meson) to probe whether the two SM explanations
account for the fT/fL ratio in this type of decays and to further investigate
the two new-physics scenarios which explain the data in B -> pi K and the
phi(rho) K* polarization measurements.


  We recall fundamental aspects of the pluriclosed flow equation and survey
various existence and convergence results, and the various analytic techniques
used to establish them. Building on this, we formulate a precise conjectural
description of the long time behavior of the flow on complex surfaces. This
suggests an attendant geometrization conjecture which has implications for the
topology of complex surfaces and the classification of generalized K\"ahler
structures.


  For the gluon propagator of pure SU(2) lattice gauge theory in the Landau
gauge we investigate the effect of Gribov copies and finite-volume effects.
Concerning gauge fixing, we enlarge the accessible gauge orbits by adding
non-periodic Z(2) gauge transformations and systematically employ the simulated
annealing algorithm. Strategies to keep all Z(2) sectors under control within
reasonable CPU time are discussed. We demonstrate that the finite-volume
effects in the infrared regime become ameliorated. Reaching a physical volume
of about (6.5 fm)^4, we find that the propagator, calculated with the indicated
improvements, becomes flat in the region of smallest momenta. First signs in 4d
of a final decrease towards vanishing momentum are discussed.


  Dense high-precision photometry of microlensed stars during a fold-caustic
passage can be used to reveal their intensity profiles from which the
temperature of the stellar atmosphere as function of fractional radius can be
derived. While the capabilities of current microlensing follow-up campaigns
such as PLANET allow a precise measurement of linear limb-darkening
coefficients, the residual signal of a second coefficient characterizing
square-root limb darkening is ~ 25 times smaller which prevents a proper
determination except for unlikely cases of very high caustic-peak-to-outside
relative magnifications with no adequate event being observed so far or for
source stars passing over a cusp singularity. Although the presence of limb
darkening can be well established from the data, a reliable measurement of the
index of an underlying power-law cannot be obtained.


  We have measured the chlorine isotope ratio in six M giant stars using HCl
1-0 P8 features at 3.7 microns with R $\sim$ 50,000 spectra from Phoenix on
Gemini South. The average Cl isotope ratio for our sample of stars is 2.66
$\pm$ 0.58 and the range of measured Cl isotope ratios is 1.76 $<$
$^{35}$Cl/$^{37}$Cl $<$ 3.42. The solar system meteoric Cl isotope ratio of
3.13 is consistent with the range seen in the six stars. We suspect the large
variations in Cl isotope ratio are intrinsic to the stars in our sample given
the uncertainties. Our average isotopic ratio is higher than the value of 1.80
for the solar neighborhood at solar metallicity predicted by galactic chemical
evolution models. Finally the stellar isotope ratios in our sample are similar
to those measured in the interstellar medium.


  In this paper, we propose BANG, a new pretraining model to Bridge the gap
between Autoregressive (AR) and Non-autoregressive (NAR) Generation. AR and NAR
generation can be uniformly regarded as to what extent previous tokens can be
attended, and BANG bridges AR and NAR generation by designing a novel model
structure for large-scale pretraining. The pretrained BANG model can
simultaneously support AR, NAR and semi-NAR generation to meet different
requirements. Experiments on question generation (SQuAD 1.1), summarization
(XSum) and dialogue generation (PersonaChat) show that BANG improves NAR and
semi-NAR performance significantly as well as attaining comparable performance
with strong AR pretrained models. Compared with the semi-NAR strong baselines,
BANG achieves absolute improvements of 14.01 and 5.24 in the overall scores of
SQuAD 1.1 and XSum, respectively. In addition, BANG achieves absolute
improvements of 10.73, 6.39 and 5.90 in the overall scores of SQuAD, XSUM and
PersonaChat respectively compared with the strong NAR baselines.


  The phase behavior of charge-stabilized colloidal suspensions is modeled by a
combination of response theory for electrostatic interparticle interactions and
variational theory for free energies. Integrating out degrees of freedom of the
microions (counterions, salt ions), the macroion-microion mixture is mapped
onto a one-component system governed by effective macroion interactions. Linear
response of microions to the electrostatic potential of the macroions results
in a screened-Coulomb (Yukawa) effective pair potential and a one-body volume
energy, while nonlinear response modifies the effective interactions [A. R.
Denton, \PR E {\bf 70}, 031404 (2004)]. The volume energy and effective pair
potential are taken as input to a variational free energy, based on
thermodynamic perturbation theory. For both linear and first-order nonlinear
effective interactions, a coexistence analysis applied to aqueous suspensions
of highly charged macroions and monovalent microions yields bulk separation of
macroion-rich and macroion-poor phases below a critical salt concentration, in
qualitative agreement with predictions of related linearized theories [R. van
Roij, M. Dijkstra, and J.-P. Hansen, \PR E {\bf 59}, 2010 (1999); P. B. Warren,
\JCP {\bf 112}, 4683 (2000)]. It is concluded that nonlinear screening can
modify phase behavior but does not necessarily suppress bulk phase separation
of deionized suspensions.


  Reaction-diffusion equations coupled to ordinary differential equations
(ODEs) may exhibit spatially low-regular stationary solutions. This work
provides a comprehensive theory of asymptotic stability of bounded,
discontinuous or continuous, stationary solutions of reaction-diffusion-ODE
systems. We characterize the spectrum of the linearized operator and relate its
spectral properties to the corresponding semigroup properties. Considering the
function spaces $L^\infty(\Omega)^{m+k}, L^\infty(\Omega)^m \times
C(\overline{\Omega})^k$ and $C(\overline{\Omega})^{m+k}$, we establish a sign
condition on the spectral bound of the linearized operator, which implies
nonlinear stability or instability of the stationary pattern.


  The determination of the masses of Supersymmetric particles such as the
Selectron for energies above threshold using the energy end-points method is
subject to signal deconvolution difficulties and to Standard Model and
Supersymmetric backgrounds. The important features of Right and Left Selectron
production are used to design an experimentally robust method both for
determining the Left and Right Selectron masses, the Neutralino mass and for
suppresing backgrounds. The mass resolution is an order of magnitude better
than in previous methods. Additional features, such as the determination of the
relative leptonic branching ratios of the selectron decay are present in the
method.


  Generative modeling of crystal structures is significantly challenged by the
complexity of input data, which constrains the ability of these models to
explore and discover novel crystals. This complexity often confines de novo
design methodologies to merely small perturbations of known crystals and
hampers the effective application of advanced optimization techniques. One such
optimization technique, Latent Space Bayesian Optimization (LSBO) has
demonstrated promising results in uncovering novel objects across various
domains, especially when combined with Variational Autoencoders (VAEs).
Recognizing LSBO's potential and the critical need for innovative crystal
discovery, we introduce Crystal-LSBO, a de novo design framework for crystals
specifically tailored to enhance explorability within LSBO frameworks.
Crystal-LSBO employs multiple VAEs, each dedicated to a distinct aspect of
crystal structure: lattice, coordinates, and chemical elements, orchestrated by
an integrative model that synthesizes these components into a cohesive output.
This setup not only streamlines the learning process but also produces
explorable latent spaces thanks to the decreased complexity of the learning
task for each model, enabling LSBO approaches to operate. Our study pioneers
the use of LSBO for de novo crystal design, demonstrating its efficacy through
optimization tasks focused mainly on formation energy values. Our results
highlight the effectiveness of our methodology, offering a new perspective for
de novo crystal discovery.


  Recent developments in two-dimensional (2D) magnetism have motivated the
search for novel van-der Waals (vdWs) magnetic materials to explore new
magnetic phenomenon in the 2D limit. Metal thiophosphates, MPX3, is a class of
magnetic vdWs materials with antiferromagnetic (AFM) ordering persisting down
to the atomically thin limit. The magnetism in this material family has been
found to be highly dependent on the choice of transition metal M. In this work,
we have synthesized the intermediate compounds Ni1-xMnxPS3 (0 < x < 1) and
investigated their magnetic properties. Our study reveals that the variation of
Ni and Mn content in Ni1-xMnxPS3 can efficiently tune the spin-flop transition,
likely due to the modulation of the magnetic anisotropy. Such effective tunning
offers a promising candidate to engineer 2D magnetism for future device
applications.


  Exceptional points (EPs) are singularities that arise in non-Hermitian
physics. Current research efforts focus only on systems supporting isolated EPs
characterized by increased sensitivity to external perturbations, which makes
them potential candidates for building next generation optical sensors. On the
downside, this feature is also the Achilles heel of these devices: they are
very sensitive to fabrication errors and experimental uncertainties. To
overcome this problem, we introduce a new design concept for implementing
photonic EPs that combine the robustness required for practical use together
with their hallmark sensitivity. Particularly, our proposed structure exhibits
a hypersurface of Jordan EPs (JEPs) embedded in a larger space, and having the
following peculiar features: (1) A large class of undesired perturbations shift
the operating point along the exceptional surface (ES), thus leaving the system
at another EP which explains the robustness; (2) Perturbations due to back
reflection/scattering force the operating point out of the ES, leading to
enhanced sensitivity. Importantly, our proposed geometry is relatively easy to
implement using standard photonics components and the design concept can be
extended to other physical platforms such as microwave or acoustics.