  We study the important for the experiment features of the effect of the
electron shell on alpha decay in the adiabatic approach. The effect is of
tenths of a percent or less in magnitude, depending on the transition energy
and the atomic number. On the other hand, we show the predominant role of the
inner shells: more than 80% of the effect are due to the 1s electrons. This
fact is crucial for the experiment, allowing one to perform measurements in the
same storage rings, comparing for example, the probability of decay in the bare
nuclei and Helium-like ions. The analysis is presented concerning the reasons
for the relative success and the limits of applicability of the model of
"frozen" electron shell used to calculate the effect for more than half a
century.


  Maximising the information that can be extracted from weak lensing
measurements is a key goal for upcoming surveys such as LSST and Euclid. This
is typically achieved through statistics that are complementary to the cosmic
shear two-point correlation function, the most well established of which is the
weak lensing peak abundance. In this work, we study the clustering of weak
lensing peaks, and present parameter constraint forecasts for an LSST-like
survey. We use the cosmoslics $w$CDM simulations to measure the peak two-point
correlation function for a range of cosmological parameters, and use the
simulation data to train a Gaussian process regression emulator which is
applied to generate likelihood contours and provide parameter constraint
forecasts from mock observations. We investigate the dependence of the peak
two-point correlation function on the peak height, and find that the clustering
of low amplitude peaks is complementary to that of high amplitude peaks.
Consequently, their combination gives significantly tighter constraints than
the clustering of high peaks alone. The peak two-point correlation function is
significantly more sensitive to the cosmological parameters $h$ and $w_0$ than
the peak abundance, and when the probes are combined, constraints on
$\Omega_{\rm m}$, $S_8$, $h$ and $w_0$ improve by at least a factor of two,
relative to the peak abundance alone. Finally, we compare the forecasts for
weak lensing peaks and weak lensing voids, and show that the two are also
complementary; both probes can offer better constraints on $S_8$ and $w_0$ than
the shear correlation function by roughly a factor of two.


  Heavy quarks, i.e. charm and beauty, are considered calibrated probes for the
strongly interacting deconfined medium (Quark Gluon Plasma, QGP) formed in
heavy-ion collisions. Produced in hard scattering processes in the initial
stages of the collision, they interact with the medium, lose energy and,
depending on the coupling strength to the medium, take part in the collective
motion of the QCD matter. ALICE measured the production of ${\rm D^{0}}$, ${\rm
D^{*+}}$, ${\rm D^{+}}$ and ${\rm D_{s}}$ mesons at central rapidity in pp,
p-Pb and Pb-Pb collisions at the LHC. The study of the modification of the
transverse momentum differential yields of charm particles in Pb-Pb collisions
with respect to pp collisions, quantified by the nuclear modification factor
($R_{\rm AA}$), can unravel details of the energy loss mechanism, such as its
dependence on the quark mass and on the path length the parton travels through
the medium. A similar comparison between pp and p-Pb collision data ($R_{\rm
pPb}$) is fundamental to disentangle effects related to the presence of the hot
medium from cold nuclear matter effects. The degree of thermalization and
coupling to the medium is investigated in semi-peripheral Pb-Pb collisions by
measuring the elliptic flow coefficient ($v_{2}$) at low pt. At high pt,
$v_{2}$ is sensitive to the path-length dependence of the energy loss. Results
on the transverse momentum and centrality dependence of the D-meson elliptic
flow and $R_{AA}$ will be presented. The comparison with the $R_{\rm AA}$ of
non-prompt ${\rm J/}\psi$ from B-meson decays measured with CMS will be
discussed. The preliminary results on D-meson $R_{\rm pPb}$ and the dependence
of D-meson yields on rapidity in p-Pb collisions will be shown. As an outlook,
the analysis and the preliminary results on the azimuthal correlations of D
mesons and charged hadrons in pp collisions will be described.


  In this paper we introduce a bulk-surface reaction-diffusion (BSRD) model in
three space dimensions that extends the DIB morphochemical model to account for
the electrolyte contribution in the application, in order to study structure
formation during discharge-charge processes in batteries. Here we propose to
approximate the model by the Bulk-Surface Virtual Element Method on a
tailor-made mesh that proves to be competitive with fast bespoke methods for
PDEs on Cartesian grids. We present a selection of numerical simulations that
accurately match the classical morphologies found in experiments. Finally, we
compare the Turing patterns obtained by the coupled 3D BS-DIB model with those
obtained with the original 2D version.


  We introduce an analogue in hyperkahler geometry of the symplectic implosion,
in the case of SU(n) actions. Our space is a stratified hyperkahler space which
can be defined in terms of quiver diagrams. It also has a description as a
non-reductive geometric invariant theory quotient.


  We introduce squeezed vacua in loop quantum gravity, a new overcomplete basis
of states that contain prescribable correlations between geometric operators.
We study the behavior of long-range correlations and discuss the relevance of
these states for the reconstruction of a semiclassical spacetime from loop
quantum gravity.


  We consider multi-value expansion planning (MEP), a general bilevel
optimization model in which a planner optimizes arbitrary functions of the
dispatch outcome in the presence of a partially controllable, competitive
electricity market. The MEP problem can be used to jointly plan various grid
assets, such as transmission, generation, and battery storage capacities;
examples include identifying grid investments that minimize emissions in the
absence of a carbon tax, maximizing the profit of a portfolio of renewable
investments and long-term energy contracts, or reducing price inequities
between different grid stakeholders. The MEP problem, however, is in general
nonconvex, making it difficult to solve exactly for large real-world systems.
Therefore, we propose a fast stochastic implicit gradient-based heuristic
method that scales well to large networks with many scenarios. We use a strong
duality reformulation and the McCormick envelope to provide a lower bound on
the performance of our algorithm via convex relaxation. We test the performance
of our method on a large model of the U.S. Western Interconnect and demonstrate
that it scales linearly with network size and number of scenarios and can be
efficiently parallelized on large machines. We find that for medium-sized 16
hour cases, gradient descent on average finds a 5.3x lower objective value in
16.5x less time compared to a traditional reformulation-based approach solved
with an interior point method. We conclude with a large example in which we
jointly plan transmission, generation, and storage for a 768 hour case on 100
node system, showing that emissions penalization leads to additional 40.0%
reduction in carbon intensity at an additional cost of $17.1/MWh.


  A slab with relative permittivity $\epsilon = - 1 + i\delta$ and permeability
$\mu = - 1 + i\delta $ has a critical distance away from the slab where a small
particle will either be cloaked or imaged depending on whether it is located
inside or outside that critical distance. We find that the optical force acting
on a small cylinder under plane wave illumination reaches a maximum value at
this critical distance. Contrary to the usual observation that superlens
systems should be highly loss-sensitive, this maximum optical force remains a
constant when loss is changed within a certain range. For a fixed particle-slab
distance, increasing loss can even amplify the optical force acting on the
small cylinder, contrary to the usual belief that loss compromises the response
of supenlens.


  This paper proposes a robust method for semiparametric identification and
estimation in panel multinomial choice models, where we allow for
infinite-dimensional fixed effects that enter into consumer utilities in an
additively nonseparable way, thus incorporating rich forms of unobserved
heterogeneity. Our identification strategy exploits multivariate monotonicity
in parametric indexes, and uses the logical contraposition of an intertemporal
inequality on choice probabilities to obtain identifying restrictions. We
provide a consistent estimation procedure, and demonstrate the practical
advantages of our method with simulations and an empirical illustration with
the Nielsen data.


  Fisher's arrow of `time' in a cosmological phase space defined as in quantum
optics (i.e., whose points are coherent states) is introduced as follows.
Assuming that the phase space evolution of the universe starts from an initial
squeezed cosmological state towards a final thermal one, a Fokker-Planck
equation for the time-dependent, cosmological Q phase space probability
distribution can be written down. Next, using some recent results in the
literature, we derive an information arrow of time for the Fisher phase space
cosmological entropy based on the Q function. We also mention the application
of Fisher's arrow of time to stochastic inflation models


  In this communication the enhancement of low temperature magnetoresistance in
polycrystalline La1-xCaxMnO3 manganites is discussed. It is shown that
so-called grain boundary effects seem to be the simplest and natural
explanation of this phenomenon.


  We present an apparatus for terahertz fingerprint discrimination of materials
designed to be fast, simple, compact and economical in order to be suitable for
preliminary on-field analysis. The system working principles, bioinspired by
the human vision of colors, are based on the use of microfabricated
metamaterials selective filters and of a very compact optics based on metallic
ellipsoidal mirrors in air. We experimentally demonstrate the operation of the
apparatus in discriminating simple substances such as salt, staple foods and
grease in an accurate and reproducible manner. We present the system and the
obtained results and discuss issues and possible developments.


  We argue that the Scanning Tunneling Microscope (STM) images of resonant
states generated by doping Zn or Ni impurities into Cu-O planes of BSCCO are
the result of quantum interference of the impurity signal coming from several
distinct paths. The impurity image seen on the surface is greatly affected by
interlayer tunneling matrix elements. We find that the optimal tunneling path
between the STM tip and the metal (Cu, Zn, or Ni) $d_{x^2 - y^2}$ orbitals in
the Cu-O plane involves intermediate excited states. This tunneling path leads
to the four-fold nonlocal filter of the impurity state in Cu-O plane that
explains the experimental impurity spectra. Applications of the tunneling
filter to the Cu vacancy defects and ``direct'' tunneling into Cu-O planes are
also discussed.


  We discuss origin of equivalence between noncommutative and ordinary
Yang-Mills from point of view of string theory. Working in BRST/Hamiltonian
framework first we investigate string model in the decoupling limit and show
that change of variables and applying the conversion of constraints of
decoupled string theory gives commuting coordinates on the D-brane. Also, we
discuss algebra of constraints in general case and show the ways of having
commutative coordinates without going to decoupling limit. It could be argued
that noncommutative string in B-field is equivalent to the commutative model.
We investigate the case of the membrane ending on the M-5-brane in constant
C-field and discuss noncommutative/commutative equivalence in this case.


  This posting contains raw data used for extracting features of the phase
diagram and quantum criticality versus magnetic field $B$, temperature $T$ and
Rh-doping $x$ that will soon appear in Physical Review Letters, 2004. All of
the raw resistivity data is shown while only a selection of the magnetization
data is shown for which a sample-out background subtraction was made.


  In this paper, we propose a constrained linear data-feature mapping model as
an interpretable mathematical model for image classification using
convolutional neural network (CNN) such as the ResNet. From this viewpoint, we
establish the detailed connections in a technical level between the traditional
iterative schemes for constrained linear system and the architecture for the
basic blocks of ResNet. Under these connections, we propose some natural
modifications of ResNet type models which will have less parameters but still
maintain almost the same accuracy as these corresponding original models. Some
numerical experiments are shown to demonstrate the validity of this constrained
learning data-feature mapping assumption.


  The pricing of derivatives tied to baskets of assets demands a sophisticated
framework that aligns with the available market information to capture the
intricate non-linear dependency structure among the assets. We describe the
dynamics of the multivariate process of constituents with a copula model and
propose an efficient method to extract the dependency structure from the
market. The proposed method generates coherent sets of samples of the
constituents process through systematic sampling rearrangement. These samples
are then utilized to calibrate a local volatility model (LVM) of the basket
process, which is used to price basket derivatives. We show that the method is
capable of efficiently pricing basket options based on a large number of basket
constituents, accomplishing the calibration process within a matter of seconds,
and achieving near-perfect calibration to the index options of the market.


  We predict that the anti-ferromagnetic (AFM) magnetic structure of
delafossite PdCrO$_2$ has a staggered chirality with the double-layer
periodicity along the $z$-axis with intriguing magnetic anisotropy. We study
the electronic and magnetic structures of PdCrO$_2$ by carrying out density
functional theory (DFT) calculation. The calculated ground state turns out to
exhibit a 120$^\circ$ AFM ordering with staggered chirality. The result is
consistent with the previous neutron experiments, but our calculations
determine and provide more detailed information on the high symmetric
easy-plane and local-easy-axis structure. We investigate the origin of
staggered chirality as well as the easy-plane and local-easy-axis directions.
Based on the DFT and effective spin interaction models, we demonstrate the
complex magnetic ordering requires novel four-spin interactions, which cannot
be described by the usual exchange interaction. Also, we show Pd electronic
bands near the Fermi level pose a tiny degeneracy breaking, which arises from
the magnetic anisotropy with different easy-plane and local-easy-axis. We
expect that the twisting and rotating modes of easy-planes in the magnetic
double layers can be the critical factor to understand a hidden magnetic
property of PdCrO$_2$ and its related macroscopic property like the previously
reported anomalous Hall effect.


  By constructing successful couplings, the derivative formula, gradient
estimates and Harnack inequalities are established for the semigroup associated
with a class of degenerate functional stochastic differential equations.


  The hippocampus has the capacity for reactivating recently acquired memories
[1-3] and it is hypothesized that one of the functions of sleep reactivation is
the facilitation of consolidation of novel memory traces [4-11]. The dynamic
and network processes underlying such a reactivation remain, however, unknown.
We show that such a reactivation characterized by local, self-sustained
activity of a network region may be an inherent property of the recurrent
excitatory-inhibitory network with a heterogeneous structure. The entry into
the reactivation phase is mediated through a physiologically feasible
regulation of global excitability and external input sources, while the
reactivated component of the network is formed through induced network
heterogeneities during learning. We show that structural changes needed for
robust reactivation of a given network region are well within known
physiological parameters [12,13].


  We experimentally demonstrate quantum behavior of a macroscopic atomic spin
oscillator in the acoustic frequency range. Quantum back-action of the spin
measurement, ponderomotive squeezing of light, and oscillator spring softening
are observed at spin oscillation frequencies down to 6 kHz. Quantum noise
sources characteristic of spin oscillators operating in the near-DC frequency
range are identified and means for their mitigation are presented. These
results constitute an important step towards quantum noise reduction and
entanglement-enhanced sensing in the acoustic range using a negative-mass
reference frame. In particular, the results are relevant for broadband noise
reduction in gravitational wave detectors.


  The weak equivalence principle is one of the cornerstone of general
relativity. Its validity has been tested with impressive precision in the Solar
System, with experiments involving baryonic matter and light. However, on
cosmological scales and when dark matter is concerned, the validity of this
principle is still unknown. In this paper we construct a null test that probes
the validity of the equivalence principle for dark matter. Our test has the
strong advantage that it can be applied on data without relying on any
modelling of the theory of gravity. It involves a combination of redshift-space
distortions and relativistic effects in the galaxy number-count fluctuation,
that vanishes if and only if the equivalence principle holds. We show that the
null test is very insensitive to typical uncertainties in other cosmological
parameters, including the magnification bias parameter, and to non-linear
effects, making this a robust null test for modified gravity.


  We prove a new, universal gradient continuity estimate for solutions to
quasilinear equations with varying coefficients at points on its critical
singular set of degeneracy $S(u) := \{X : D u(X) = 0 \}$. Our main Theorem
reveals that along $S(u)$, $u$ is asymptotically as regular as solutions to
constant coefficient equations. In particular, along the critical set $S(u)$,
$Du$ enjoys a modulus of continuity much superior than the, possibly low,
continuity feature of the coefficients. Our main, leading result fosters a new
understanding on smoothness properties of solutions to degenerate or singular
equations, beyond typical elliptic regularity estimates, precisely where the
diffusion attributes of the equation collapse.


  Analogue gravitational systems are becoming an increasing popular way of
studying the behaviour of quantum systems in curved spacetime. Setups based on
ultracold quantum gases in particular, have been recently harnessed to explore
the thermal nature of Hawking's and Unruh's radiation that was theoretically
predicted almost 50 years ago. For solid state implementations, a promising
system is graphene, in which a link between the Dirac-like low-energy
electronic excitations and relativistic quantum field theories has been
unveiled soon after its discovery. Here we show that this link extends to the
case of curved quantum field theory when the graphene sheet is shaped in a
surface of constant negative curvature, known as Beltrami's pseudosphere.
Thanks to large-scale simulations, we provide numerical evidence that
energetically stable negative curvature graphene surfaces can be realized; the
ratio between the carbon-carbon bond length and the pseudosphere radius is
small enough to allow the formation of an horizon; and the associated Local
Density Of States evaluated at horizon's proximity has a thermal nature with a
characteristic temperature of few tens of Kelvin. Such findings pave the way to
the realization of a solid-state system in which the curved spacetime dynamics
of quantum many body systems can be investigated.


  Modern machine learning (ML) systems demand substantial training data, often
resorting to external sources. Nevertheless, this practice renders them
vulnerable to backdoor poisoning attacks. Prior backdoor defense strategies
have primarily focused on the identification of backdoored models or poisoned
data characteristics, typically operating under the assumption of access to
clean data. In this work, we delve into a relatively underexplored challenge:
the automatic identification of backdoor data within a poisoned dataset, all
under realistic conditions, i.e., without the need for additional clean data or
without manually defining a threshold for backdoor detection. We draw an
inspiration from the scaled prediction consistency (SPC) technique, which
exploits the prediction invariance of poisoned data to an input scaling factor.
Based on this, we pose the backdoor data identification problem as a
hierarchical data splitting optimization problem, leveraging a novel SPC-based
loss function as the primary optimization objective. Our innovation unfolds in
several key aspects. First, we revisit the vanilla SPC method, unveiling its
limitations in addressing the proposed backdoor identification problem.
Subsequently, we develop a bi-level optimization-based approach to precisely
identify backdoor data by minimizing the advanced SPC loss. Finally, we
demonstrate the efficacy of our proposal against a spectrum of backdoor
attacks, encompassing basic label-corrupted attacks as well as more
sophisticated clean-label attacks, evaluated across various benchmark datasets.
Experiment results show that our approach often surpasses the performance of
current baselines in identifying backdoor data points, resulting in about
4%-36% improvement in average AUROC. Codes are available at
https://github.com/OPTML-Group/BackdoorMSPC.


  Attention models are typically learned by optimizing one of three standard
loss functions that are variously called -- soft attention, hard attention, and
latent variable marginal likelihood (LVML) attention. All three paradigms are
motivated by the same goal of finding two models -- a `focus' model that
`selects' the right \textit{segment} of the input and a `classification' model
that processes the selected segment into the target label. However, they differ
significantly in the way the selected segments are aggregated, resulting in
distinct dynamics and final results. We observe a unique signature of models
learned using these paradigms and explain this as a consequence of the
evolution of the classification model under gradient descent when the focus
model is fixed. We also analyze these paradigms in a simple setting and derive
closed-form expressions for the parameter trajectory under gradient flow. With
the soft attention loss, the focus model improves quickly at initialization and
splutters later on. On the other hand, hard attention loss behaves in the
opposite fashion. Based on our observations, we propose a simple hybrid
approach that combines the advantages of the different loss functions and
demonstrates it on a collection of semi-synthetic and real-world datasets


  An ansatz, Det. $M_{\tilde H}=0,$ for the Higgsino mass matrix in string
orbifold trinification is suggested toward the minimal supersymmetric standard
model(MSSM). Small instanton solutions effective around the GUT scale can
fulfil this condition. An argument that the couplings contain a moduli field is
given for a dynamical realization of this Higgsino mass matrix ansatz.


  In this paper we present a method to obtain a possible self-adjoint
Hamiltonian operator so its energies satisfy Z(1/2+iE_n)=0, which is an
statement equivalent to Riemann Hypothesis, first we use the explicit formula
for the Chebyshev function Psi(x) and apply the change x=exp(u), after that we
consider an Statistical partition function involving the Chebyshev function and
its derivative so Z=Tr(exp(-BH), from the integral definition of the partition
function Z we try to obtain the Hamiltonian operator assuming that H=P^{2}+V(x)
by proposing a Non-linear integral equation involving Z(B=-iu) and V(x).


  This note presents two observations which have in common that they lie at the
boundary of toric geometry. The first one because it concerns the deformation
of affine toric varieties into non toric germs in order to understand how to
avoid some ramification problems arising in the study of local uniformization
in positive characteristic, and the second one because it uses limits of
projective systems of equivariant birational maps of toric varieties to study
the space of additive preorders on ${\mathbf Z}^r$ for $r\geq 2$.


  One of the central economic paradigms in multi-agent systems is that agents
should not be better off by acting dishonestly. In the context of collective
decision-making, this axiom is known as strategyproofness and turns out to be
rather prohibitive, even when allowing for randomization. In particular,
Gibbard's random dictatorship theorem shows that only rather unattractive
social decision schemes (SDSs) satisfy strategyproofness on the full domain of
preferences. In this paper, we obtain more positive results by investigating
strategyproof SDSs on the Condorcet domain, which consists of all preference
profiles that admit a Condorcet winner. In more detail, we show that, if the
number of voters $n$ is odd, every strategyproof and non-imposing SDS on the
Condorcet domain can be represented as a mixture of dictatorial SDSs and the
Condorcet rule (which chooses the Condorcet winner with probability $1$).
Moreover, we prove that the Condorcet domain is a maximal connected domain that
allows for attractive strategyproof SDSs if $n$ is odd as only random
dictatorships are strategyproof and non-imposing on any sufficiently connected
superset of it. We also derive analogous results for even $n$ by slightly
extending the Condorcet domain. Finally, we also characterize the set of
group-strategyproof and non-imposing SDSs on the Condorcet domain and its
supersets. These characterizations strengthen Gibbard's random dictatorship
theorem and establish that the Condorcet domain is essentially a maximal domain
that allows for attractive strategyproof SDSs.


  We study a class of phase-space distribution functions that is generated from
a Gaussian convolution of the Wigner distribution function. This class of
functions represents the joint count probability in simultaneous measurements
of position and momentum. We show that, using these functions, one can
determine the expectation value of a certain class of operators accurately,
even if measurement data performed only with imperfect detectors are available.
As an illustration, we consider the eight-port homodyne detection experiment
that performs simultaneous measurements of two quadrature amplitudes of a
radiation field.


  This article is the last of four that completely characterize a solution
space $\mathcal{S}_N$ for a homogeneous system of $2N+3$ linear partial
differential equations (PDEs) in $2N$ variables that arises in conformal field
theory (CFT) and multiple Schramm-Loewner evolution (SLE). The system comprises
$2N$ null-state equations and three conformal Ward identities that govern CFT
correlation functions of $2N$ one-leg boundary operators. In the first two
articles, we use methods of analysis and linear algebra to prove that
$\dim\mathcal{S}_N\leq C_N$, with $C_N$ the $N$th Catalan number. Building on
these results in the third article, we prove that $\dim\mathcal{S}_N=C_N$ and
$\mathcal{S}_N$ is spanned by (real-valued) solutions constructed with the
Coulomb gas (contour integral) formalism of CFT.
  In this article, we use these results to prove some facts concerning the
solution space $\mathcal{S}_N$. First, we show that each of its elements equals
a sum of at most two distinct Frobenius series in powers of the difference
between two adjacent points (unless $8/\kappa$ is odd, in which case a
logarithmic term may appear). This establishes an important element in the
operator product expansion (OPE) for one-leg boundary operators, assumed in
CFT. We also identify particular elements of $\mathcal{S}_N$, which we call
connectivity weights, and exploit their special properties to conjecture a
formula for the probability that the curves of a multiple-SLE$_\kappa$ process
join in a particular connectivity. Finally, we propose a reason for why the
"exceptional speeds" (certain $\kappa$ values that appeared in the analysis of
the Coulomb gas solutions in the third article) and the minimal models of CFT
are connected.


  Be abundances of old, low metallicity halo stars have major implications on
cosmic-ray origin, requiring acceleration out of fresh supernova ejecta. The
observed, essentially constant Be/Fe fixes the Be production per SNII, allowing
the determination of the energy supplied to cosmic rays per SNII. The results
rule out acceleration out of the metal-poor ISM, and favor Be production at all
epochs of Galactic evolution by cosmic rays having the same spectrum and source
composition as those at the current epoch. Individual supernova acceleration of
its own nucleosynthetic products and the collective acceleration by SN shocks
of ejecta-enriched matter in the interiors of superbubbles have been proposed
for such origin. The supernova acceleration efficiency is about 2% for the
refractory metals and 10% for all the cosmic rays.


  We give a brief introduction to the study of the algebraic structures -- and
their geometrical interpretations -- which arise in the BRST construction of a
conformal string background. Starting from the chiral algebra $\cA$ of a string
background, we consider a number of elementary but universal operations on the
chiral algebra. From these operations we deduce a certain fundamental odd
Poisson structure, known as a Gerstenhaber algebra, on the BRST cohomology of
$\cA$. For the 2D string background, the correponding G-algebra can be
partially described in term of a geometrical G-algebra of the affine plane
$\bC^2$. This paper will appear in the proceedings of {\it Strings 95}.


  This paper proposes machine-independent feature engineering for winding
inter-turn short circuit fault that uses electrical current signals. Electrical
current signal collected from permanent magnet synchronous motor (PMSM) is
subjected to different environmental and operational conditions. To solve these
problems, robust current signal imaging method and deep learning-based feature
extraction method are developed. The overall procedure includes the following
three key steps: (1) transformation of a time-series current signal to
two-dimensional image, (2) extracting features using convolutional neural
networks, and (3) calculating a health indicator using Mahalanobis distance.
Transformation of the time-series signal is based on recurrence plots (RP). The
proposed RP method develops from feature engineering that provides the dominant
fault feature representations in a robust way. The proposed RP is designed that
maximizes the features of inter-turn short fault and minimizes the effect of
noise from systems with various capacities. To demonstrate the validity of the
proposed method, two case studies are conducted using an artificial fault
seeded testbed with two different capacities of motor. By calculating the
feature using only the electrical current signal of the motor without the
parameters related to the capacity of the motor, the proposed feature can be
applied to motors with different capacities while maintaining the same
performance.


  AT-free graphs are characterized by vertex elimination orders. We show that
these AT-free orders of a graph can be generated in constant amortized time.


  Mixed-variable symplectic integrators are widely used in orbital dynamics.
However, they have been developed for Solar system-type architectures, and can
not handle evolving hierarchy, in particular in systems with two or more
stellar components. Such configuration may have occurred in the history of HD
106906, a tight pair of F-type stars surrounded by a debris disk and a
planetary-mass companion on a wide orbit. We present the new algorithm ODEA,
based on the symplectic algorithm SWIFT HJS, that can model any system
(binary,...) with unstable architecture. We study the peculiar system HD 106906
as a testcase for the code. We define and compute a criterion based on
acceleration ratios to indicate when the initial hierarchy is not relevant
anymore. A new hierarchy is then computed. The code is applied to study the two
fly-bys that occurred on system HD 106906, recently evidenced by De Rosa &
Kalas (2019), to determine if they could account for the wide orbit of the
planet. Thousands of simulations have been performed to account for the
uncertainty on the perturbers coordinates and velocities. The algorithm is able
to handle any change of hierarchy, temporary or not. We used it to fully model
HD 106906 encounters. The simulations confirm that the fly-bys could have
stabilized the planet orbit, and show that it can account for the planet
probable misalignment with respect to the disk plane as well as the disk
morphology. However, that requires a small distance at closest approach (< 0.05
pc), and this configuration is not guaranteed. ODEA is a very good choice for
the study of non-Solar type architecture. It can now adapt to an evolving
hierarchy, and is thus suitable to study capture of planets and dust. Further
observations of the perturbers, in particular their radial velocity, are
required to conclude on the effects of the fly-by on system HD 106906.


  The biomedical domain has sparked a significant interest in the field of
Natural Language Processing (NLP), which has seen substantial advancements with
pre-trained language models (PLMs). However, comparing these models has proven
challenging due to variations in evaluation protocols across different models.
A fair solution is to aggregate diverse downstream tasks into a benchmark,
allowing for the assessment of intrinsic PLMs qualities from various
perspectives. Although still limited to few languages, this initiative has been
undertaken in the biomedical field, notably English and Chinese. This
limitation hampers the evaluation of the latest French biomedical models, as
they are either assessed on a minimal number of tasks with non-standardized
protocols or evaluated using general downstream tasks. To bridge this research
gap and account for the unique sensitivities of French, we present the
first-ever publicly available French biomedical language understanding
benchmark called DrBenchmark. It encompasses 20 diversified tasks, including
named-entity recognition, part-of-speech tagging, question-answering, semantic
textual similarity, and classification. We evaluate 8 state-of-the-art
pre-trained masked language models (MLMs) on general and biomedical-specific
data, as well as English specific MLMs to assess their cross-lingual
capabilities. Our experiments reveal that no single model excels across all
tasks, while generalist models are sometimes still competitive.


  We open-source a state-of-the-art 4B-parameter generative model series for
Vietnamese, which includes the base pre-trained monolingual model PhoGPT-4B and
its chat variant, PhoGPT-4B-Chat. The base model, PhoGPT-4B, with exactly 3.7B
parameters, is pre-trained from scratch on a Vietnamese corpus of 102B tokens,
with an 8192 context length, employing a vocabulary of 20480 token types. The
chat variant, PhoGPT-4B-Chat, is the modeling output obtained by fine-tuning
PhoGPT-4B on a dataset of 70K instructional prompts and their responses, along
with an additional 290K conversations. In addition, we also demonstrate its
superior performance compared to previous open-source models. Our PhoGPT models
are available at: https://github.com/VinAIResearch/PhoGPT


  We report a measurement of $KLL$ dielectronic recombination in charge states
from Kr$^{+34}$ through Kr$^{+28}$, in order to investigate the contribution of
Breit interaction for a wide range of resonant states. Highly charged Kr ions
were produced in an electron beam ion trap, while the electron-ion collision
energy was scanned over a range of dielectronic recombination resonances. The
subsequent $K\alpha$ x rays were recorded both along and perpendicular to the
electron beam axis, which allowed the observation of the influence of Breit
interaction on the angular distribution of the x rays. Experimental results are
in good agreement with distorted-wave calculations. We demonstrate, both
theoretically and experimentally, that there is a strong state-selective
influence of the Breit interaction that can be traced back to the angular and
radial properties of the wavefunctions in the dielectronic capture.


  We observed two faint tidal dwarf galaxies (TDGs), NGC 5291N and NGC 5291 S
with the Infrared Spectrograph on the Spitzer Space Telescope. We detect strong
polycyclic aromatic hydrocarbon (PAH) emission, which match models of groups of
\~100 carbon atoms with an equal mixture of neutral and ionized PAHs. The TDGs
have a dominant warm ~140 K dust component in marked contrast to the cooler,
40-60 K dust found in starburst galaxies. For the first time we detect the
low-J rotational lines from molecular hydrogen. Adopting LTE there is ~10^5
solar masses of ~400 K gas, which is <0.1 % of the cold gas mass. The
combination of one-third solar metallicity with a recent, <5 million year,
epsiode of star formation is reflected in the S and Ne ratios. The excitation
is higher than typical values for starburst galaxies and similar to that found
in BCDs. Using the Infared Array Camera we identify an additional 13 PAH-rich
candidate TDGs. These sources occupy a distinct region of IRAC color space with
[3.6] - [4.5] < 0.4 and [4.5] - [8.0] > 3.2. NGC 5291 N and S have stellar
masses of (1.5 and 3.0) 10^8 solar masses, which is comparable to BCDs. This
system appears to be a remarkable TDG nursery.


  The Silicon photomultiplier-based Compton Telescope for Safety and Security
(SCoTSS) has been developed incorporating end-user requirements into the design
process. The end-user group includes those responsible for mobile survey in the
event of a radiological or nuclear accident, those responsible for radiation
survey support to security operations at major events and at Canadian borders,
as well as some of those responsible for Canadian defense applications. The
SCoTSS development program has reached a technology readiness level of eight,
and we are proceeding with field trials of the instrument in high-fidelity
operational environments. Prospective end users have been involved in trial set
up and execution, assuring applicability in their mission spaces. SCoTSS has
been subject to trials involving hidden sources, heavily shielded sources,
imager moving with respect to source, and complicated man-made surroundings.
Our operators value high sensitivity for anomaly geolocation and mapping. End
users also require an instrument which is capable of direction reconstruction
in motion, as well as rapid imaging of a field of view. We have developed a
"time to image" measure which allows for quantitative comparison of imagers of
fundamentally different technology, where one design may have an advantage in
terms of energy resolution and compactness and another design may have an
advantage in terms of efficiency and cost effectiveness. We present here the
performance of the SCoTSS imager in rapid direction finding. As well, we
compare the time to image quantity for the SCoTSS imager and the H3D Polaris-H
Quad imager where the data were taken under equivalent conditions. This
quantitative measure of imaging performance can allow operators to make an
informed choice of the design that meets their needs taking into consideration
also weight and size as well as budgetary constraints.


  We investigate the complexities of the McKean-Vlasov optimal control problem,
exploring its various formulations such as the strong and weak formulations, as
well as both Markovian and non-Markovian setups within financial markets.
Furthermore, we examine scenarios where the law governing the control process
impacts the dynamics of options. By conceptualizing controls as probability
measures on a fitting canonical space with filtrations, we unlock the potential
to devise classical measurable selection methods, conditioning strategies, and
concatenation arguments within this innovative framework. These tools enable us
to establish the dynamic programming principle under a wide range of
conditions.


  We present new broadband X-ray observations of the $z \sim 2.5$ lensed quasar
2MASS J1042+1641, combining $XMM$-$Newton$, $Chandra$ and $NuSTAR$ to provide
coverage of the X-ray spectrum over the 0.3$-$40 keV bandpass in the observed
frame, corresponding to the $\sim$1$-$140 keV band in the rest-frame of 2MASS
J1042+1641. The X-ray data show clear evidence for strong (but still
Compton-thin) X-ray absorption, $N_{\rm{H}} \sim 3-4 \times 10^{23}$ cm$^{-2}$,
in addition to significant reprocessing by Compton-thick material that must lie
away from our line-of-sight to the central X-ray source. We test two different
interpretations for the latter: first that the reprocessing occurs in a classic
AGN torus, as invoked in unification models, and second that the reprocessing
occurs in the accretion disc. Both models can successfully reproduce the
observed spectra, and both imply that the source is viewed at moderately low
inclinations ($i < 50^{\circ}$) despite the heavy line-of-sight absorption.
Combining the X-ray data with infrared data from $WISE$, the results seen from
2MASS J1042+1641 further support the recent suggestion that large X-ray and IR
surveys may together be able to identify good lensed quasar candidates in
advance of detailed imaging studies.


  We present a variation of the modular algorithm for computing the Hermite
normal form of an $\mathcal O_K$-module presented by Cohen, where $\mathcal
O_K$ is the ring of integers of a number field $K$. An approach presented in
(Cohen 1996) based on reductions modulo ideals was conjectured to run in
polynomial time by Cohen, but so far, no such proof was available in the
literature. In this paper, we present a modification of the approach of Cohen
to prevent the coefficient swell and we rigorously assess its complexity with
respect to the size of the input and the invariants of the field $K$.


  We study Strauss's model of a network with clustering and present an analytic
mean-field solution which is exact in the limit of large network size. Previous
computer simulations have revealed a degenerate region in the model's parameter
space in which triangles of adjacent edges clump together to form
unrealistically dense subgraphs, and perturbation calculations have been found
to break down in this region at all orders. Our analytic solution shows that
this region corresponds to a classic symmetry-broken phase and that the onset
of the degeneracy corresponds to a first-order phase transition in the density
of the network.


  Using the fusion principle of Bauer et al. we give explicit expressions for
some null vectors in the highest weight representations of the \bc algebra in
two different forms. These null vectors are the generalization of the Virasoro
ones described by Benoit and Saint-Aubin and analogues of the $W_3$ ones
constructed by Bowcock and Watts. We find connection between quantum Toda
models and the fusion method.


  Two unanswered questions in the heart of the theory of Leavitt path algebras
are whether Grothendieck group $K_0$ is a complete invariant for the class of
unital purely infinite simple algebras and, a weaker question, whether $L_2$
(the Leavitt path algebra associated to a vertex with two loops) and its Cuntz
splice algebra $L_{2-}$ are isomorphic. The positive answer to the first
question implies the latter. In this short paper, we raise and investigate
another question, the so-called Serre's conjecture, which sits in between of
the above two questions: The positive answer to the classification question
implies Serre's conjecture which in turn implies $L_2 \cong L_{2-}$. Along the
way, we give new easy to construct algebras having stable free but not free
modules.


  The particle-hole symmetry (equivalence) of the full shell-model Hilbert
space is straightforward and routinely used in practical calculations. In this
work we show that this symmetry is preserved in the subspace truncated at a
certain generalized seniority, and give the explicit transformation between the
states in the two types (particle and hole) of representations. Based on the
results, we study the particle-hole symmetry in popular theories that could be
regarded as further truncations on top of the generalized seniority, including
the microscopic interacting boson (fermion) model, the nucleon-pair
approximation, and others.


  We present the concept and the results of pilot measurements of tunneling in
a system {Al/$\delta_{Si}$-GaAs} under pressure up to 2 GPa at 4.2 K. The
obtained results may indicate the following: the barrier height for
{Al/$\delta$-GaAs} equals to 0.86 eV at P=0 and its pressure coefficient is $3
meV/kbar$; charged impurity density in the delta-layer starts to drop from
$4.5\times 10^{12} cm^{-2}$ down to $3.8\times 10^{12} cm^{-2}$ at about 1.5
GPa; metal-insulator transition may occur in 2DEG at about 2 GPa.


  We introduce an idea of producing an optical lattice relied on the Talbot
effect. Our alternative scheme is based on the interference of light behind a
diffraction grating in the near-field regime. We demonstrate 1-D and 2-D
optical lattices with the simulations and experiments. This Talbot optical
lattice can be broadly used from quantum simulations to quantum information.
The Talbot effect is usually used in lensless optical systems, therefore it
provides small aberrations.


  We compute the dimensions of all the secant varieties to the tangential
varieties of all Segre-Veronese surfaces. We exploit the typical approach of
computing the Hilbert function of special 0-dimensional schemes on projective
plane by using a new degeneration technique.


  There has been a recent resurgence of experimental efforts to quantitatively
determine the phase diagram of the Bose Hubbard model by carefully analyzing
experiments with ultracold bosonic atoms on an optical lattice. In many
realizations of these experiments, the hopping amplitudes are not homogeneous
throughout the lattice, but instead, the lattice has an anisotropy where
hopping along one direction is not exactly equal to hopping along a
perpendicular direction. In this contribution, we examine how an anisotropy in
the hopping matrix elements affects the Mott lobes of the Bose Hubbard model.
For weak anisotropy, we find the phase diagram is only slightly modified when
expressed in terms of the average hopping, while for strong anisotropy, one
expects to ultimately see dimensional crossover effects.


  These are lecture notes for a mini-course given at the Cornell Probability
Summer School in July 2013. Topics include lozenge tilings of polygons and
their representation theoretic interpretation, the (q,t)-deformation of those
leading to the Macdonald processes, nearest neighbor dynamics on Macdonald
processes, their limit to semi-discrete Brownian polymers, and large time
asymptotic analysis of polymer's partition function.


  We study Polish spaces for which a set of possible distances $A \subseteq
\mathbb{R}^+$ is fixed in advance. We determine, depending on the properties of
$A$, the complexity of the collection of all Polish metric spaces with
distances in $A$, obtaining also example of sets in some Wadge classes where
not many natural examples are known. Moreover we describe the properties that
$A$ must have in order that all Polish spaces with distances in that set belong
to a given class, such as zero-dimensional, locally compact, etc. These results
lead us to give a fairly complete description of the complexity, with respect
to Borel reducibility and again depending on the properties of $A$, of the
relations of isometry and isometric embeddability between these Polish spaces.


  In this note, we remark, with sufficient mathematical rigor, that many weak
generalizations of the usual minimum available in the literature are not true
generalizations. Motivated by the Ekeland Variational Principle, we provide,
first time, the criteria for weaker generalizations of the usual minimum.
Further, we show that the quasi efficiency, recently used in Bhatia et al.
(Optim. Lett. 7, 127-135 (2013)) and introduced in Gupta et al. ( Bull. Aust.
Math. Soc. 74, 207-218 (2006)) is not a true generalization of the usual
efficiency. Since the former paper relies heavily on the results of later one,
so we discuss the later paper. We show that the necessary optimality condition
is a consequence of the local Lipschitzness and sufficiency result is trivial
in the later paper. Consequently, the duality results of the same paper are
also inconsistent.


  The problem of the mean-square optimal linear estimation of the functional
$A\xi=\ \int\limits_{R^s}a(t)\xi(-t)dt,$ which depends on the unknown values of
stochastic stationary process $\xi(t)$ from observations of the process
$\xi(t)+\eta(t)$ at points $t\in\mathbb{R} ^{-} \backslash S $,
$S=\bigcup\limits_{l=1}^{s}[-M_{l}-N_{l}, \, \ldots, \, -M_{l} ],$
$R^s=[0,\infty) \backslash S^{+},$ $S^{+}=\bigcup\limits_{l=1}^{s}[ M_{l}, \,
\ldots, \, M_{l}+N_{l}]$ is considered. Formulas for calculating the
mean-square error and the spectral characteristic of the optimal linear
estimate of the functional are proposed under the condition of spectral
certainty, where spectral densities of the processes $\xi(t)$ and $\eta(t)$ are
exactly known. The minimax (robust) method of estimation is applied in the case
where spectral densities are not known exactly, but sets of admissible spectral
densities are given. Formulas that determine the least favorable spectral
densities and minimax spectral characteristics are proposed for some special
sets of admissible densities.


  A central problem of surveillance is to monitor multiple targets moving in a
large-scale, obstacle-ridden environment with occlusions. This paper presents a
novel principled Partially Observable Markov Decision Process-based approach to
coordinating and controlling a network of active cameras for tracking and
observing multiple mobile targets at high resolution in such surveillance
environments. Our proposed approach is capable of (a) maintaining a belief over
the targets' states (i.e., locations, directions, and velocities) to track
them, even when they may not be observed directly by the cameras at all times,
(b) coordinating the cameras' actions to simultaneously improve the belief over
the targets' states and maximize the expected number of targets observed with a
guaranteed resolution, and (c) exploiting the inherent structure of our
surveillance problem to improve its scalability (i.e., linear time) in the
number of targets to be observed. Quantitative comparisons with
state-of-the-art multi-camera coordination and control techniques show that our
approach can achieve higher surveillance quality in real time. The practical
feasibility of our approach is also demonstrated using real AXIS 214 PTZ
cameras


  We have performed large scale variational search for the best RVB ansatz for
the spin-$\frac{1}{2}$ kagome antiferromagnet with both nearest-neighboring(NN)
and next-nearest-neighboring(NNN) exchanges assuming only translational
symmetry. We find the best RVB state is always fully symmetric and has an mean
field ansatz that is gauge equivalent to a previous proposed Z$_{2}$ spin
liquid ansatz. The Z$_{2}$ state is found to be slightly more stable than the
extensively studied U(1) gapless Dirac spin liquid state in both the
$J_{2}\neq0$ and the $J_{2}=0$ case and to possess a small spinon gap for
$J_{2}<0.2$. The breaking of the U(1) gauge symmetry in the Z$_{2}$ state is
found to increase with $J_{2}$ and to be quite substantial around $J_{2}=0.15$.
However, we find the Z$_{2}$ state is always very close to the gapless U(1)
Dirac spin liquid state, although they have very different RVB parameters. We
argue the kagome antiferromagnet should be better understood as a near critical
system, rather than a system deep inside a gapped spin liquid phase with well
established Z$_{2}$ topological order.


  We consider two types of fluctuations in the mass-action equilibrium in
protein binding networks. The first type is driven by relatively slow changes
in total concentrations (copy numbers) of interacting proteins. The second
type, to which we refer to as spontaneous, is caused by quickly decaying
thermodynamic deviations away from the equilibrium of the system. As such they
are amenable to methods of equilibrium statistical mechanics used in our study.
We investigate the effects of network connectivity on these fluctuations and
compare them to their upper and lower bounds. The collective effects are shown
to sometimes lead to large power-law distributed amplification of spontaneous
fluctuations as compared to the expectation for isolated dimers. As a
consequence of this, the strength of both types of fluctuations is positively
correlated with the overall network connectivity of proteins forming the
complex. On the other hand, the relative amplitude of fluctuations is
negatively correlated with the abundance of the complex. Our general findings
are illustrated using a real network of protein-protein interactions in baker's
yeast with experimentally determined protein concentrations.


  We propose a simple and accurate method for computing analytically the mass
correlation function for cold dark matter and scale-free models that fits
N-body simulations over a range that extends from the linear to the strongly
non-linear regime. The method, based on the dynamical evolution of the pair
conservation equation, relies on a universal relation between the pair-wise
velocity and the smoothed correlation function valid for high and low density
models, as derived empirically from N-body simulations. An intriguing
alternative relation, based on the stable-clustering hypothesis, predicts a
power-law behavior of the mass correlation function that disagrees with N-body
simulations but conforms well to the observed galaxy correlation function if
negligible bias is assumed. The method is a useful tool for rapidly exploring a
wide span of models and, at the same time, raises new questions about large
scale structure formation.


  Compromising legitimate accounts is a way of disseminating malicious content
to a large user base in Online Social Networks (OSNs). Since the accounts cause
lots of damages to the user and consequently to other users on OSNs, early
detection is very important. This paper proposes a novel approach based on
authorship verification to identify compromised twitter accounts. As the
approach only uses the features extracted from the last user's post, it helps
to early detection to control the damage. As a result, the malicious message
without a user profile can be detected with satisfying accuracy. Experiments
were constructed using a real-world dataset of compromised accounts on Twitter.
The result showed that the model is suitable for detection due to achieving an
accuracy of 89%.


  In this paper, we discuss the significance and prospect for the newly
discovered a0(1710)[a0(1817)] resonance state at BESIII experiment, in which
they reported the observation of a scalar meson of spin-parity $J^P=0^+$ with
isospin $I=1$, branded as $a_0(1817)$. This state may be the same particle as
the $a_0(1710)$ observed by the BaBar experiment earlier. As early as 2008, we
found that f0(1710) can be regarded as a $K^* \bar{K}^*$ molecular state based
on the chiral unitary theory, and there is a partner state $a_0(1710)$ with an
isospin $I=1$. Our theoretical prediction based on this picture is in good
agreement with the latest BESIII data, which further supports the molecular
state picture of $a_0(1710)[a_0(1817)]$. If it is indeed the isospin partner
state of $f_0(1710)$, this would rule out $f_0(1710)$ as a glueball candidate.
This paper briefly reviews the relevant theoretical studies and suggests new
experiments to further examine the nature of $a_0(1710)[a_0(1817)]$.


  Let $\gamma(G)$ denote the domination number of graph $G$. Let $G$ and $H$ be
graphs and $G\Box H$ their Cartesian product. For $h\in V(H)$ define
$G_h=\{(g,h)\,|\,g\in V(G)\}$ and call this set a $G$-layer of $G\Box H$. We
prove the following special case of Vizing's conjecture. Let $D$ be a
dominating set of $G\Box H$. If there exist minimum dominating sets $D_1$ and
$D_2$ of $G$ such that for every $h\in V(H)$, the projection of $D\cap G_h$ to
$G$ is contained in $D_1$ or $D_2$, then $|D|\geq \gamma(G)\gamma(H)$.


  We present the experimental evidence of RF demodulation by a graphene
monolayer embedded in a coplanar structure. The demodulator was tested in the
frequency range from 100 MHz to 25 GHz using amplitude modulated input signals.
An input power of 0 dBm (1 mW) was used which is the typical power emitted for
short range wireless communication systems, such as Bluetooth. The graphene
demodulator exhibits good signal response in the frequency range associated to
industrial, scientific and medical (ISM) radio band (2.4 GHz).


  Distinguishing between classes of time series sampled from dynamic systems is
a common challenge in systems and control engineering, for example in the
context of health monitoring, fault detection, and quality control. The
challenge is increased when no underlying model of a system is known,
measurement noise is present, and long signals need to be interpreted. In this
paper we address these issues with a new non parametric classifier based on
topological signatures. Our model learns classes as weighted kernel density
estimates (KDEs) over persistent homology diagrams and predicts new trajectory
labels using Sinkhorn divergences on the space of diagram KDEs to quantify
proximity. We show that this approach accurately discriminates between states
of chaotic systems that are close in parameter space, and its performance is
robust to noise.


  We warn of the potential nuclear proliferation's consequences of military
applications of nano- or microgram amounts of antimatter, such as triggering of
high-yield thermonuclear explosions, laser pumping, compact sources of energy,
directed-energy beams, and portable sources of muons.


  The Grassmannian $\mathcal{G}_q(n,k)$ is the set of all $k$-dimensional
subspaces of the vector space $\mathbb{F}_q^n$. K\"{o}tter and Kschischang
showed that codes in Grassmannian space can be used for error-correction in
random network coding. On the other hand, these codes are $q$-analogs of codes
in the Johnson scheme, i.e., constant dimension codes. These codes of the
Grassmannian $\mathcal{G}_q(n,k)$ also form a family of $q$-analogs of block
designs and they are called subspace designs. In this paper, we examine one of
the last families of $q$-analogs of block designs which was not considered
before. This family, called subspace packings, is the $q$-analog of packings,
and was considered recently for network coding solution for a family of
multicast networks called the generalized combination networks. A subspace
packing $t$-$(n,k,\lambda)_q$ is a set $\mathcal{S}$ of $k$-subspaces from
$\mathcal{G}_q(n,k)$ such that each $t$-subspace of $\mathcal{G}_q(n,t)$ is
contained in at most $\lambda$ elements of $\mathcal{S}$. The goal of this work
is to consider the largest size of such subspace packings. We derive a sequence
of lower and upper bounds on the maximum size of such packings, analyse these
bounds, and identify the important problems for further research in this area.


  States of matter with a sharp Fermi-surface but no well-defined Landau
quasiparticles arise in a number of physical systems. Examples include: ${\it
(i)}$ quantum critical points associated with the onset of order in metals;
${\it (ii)}$ spinon Fermi-surface (U(1) spin-liquid) state of a Mott insulator;
${\it (iii)}$ Halperin-Lee-Read composite fermion charge liquid state of a
half-filled Landau level. In this work, we use renormalization group techniques
to investigate possible instabilities of such non-Fermi-liquids in two spatial
dimensions to Cooper pairing. We consider the Ising-nematic quantum critical
point as an example of a phase transition in a metal, and demonstrate that the
attractive interaction mediated by the order parameter fluctuations always
leads to a superconducting instability. Moreover, in the regime where our
calculation is controlled, superconductivity preempts the destruction of
electronic quasiparticles. On the other hand, the spinon Fermi-surface and the
Halperin-Lee-Read states are stable against Cooper pairing for a sufficiently
weak attractive short-range interaction; however, once the strength of
attraction exceeds a critical value, pairing sets in. We describe the ensuing
quantum phase transition between ${\it (i)}$ $U(1)$ and $Z_2$ spin-liquid
states; ${\it (ii)}$ Halperin-Lee-Read and Moore-Read states.


  Mean field theory is a device to analyze the collective behavior of a
dynamical system comprising many interacting particles. The theory allows to
reduce the behavior of the system to the properties of a handful of parameters.
In neural circuits, these parameters are typically the firing rates of
distinct, homogeneous subgroups of neurons. Knowledge of the firing rates under
conditions of interest can reveal essential information on both the dynamics of
neural circuits and the way they can subserve brain function. The goal of this
chapter is to provide an elementary introduction to the mean field approach for
populations of spiking neurons. We introduce the general idea in networks of
binary neurons, starting from the most basic results and then generalizing to
more relevant situations. This allows to derive the mean field equations in a
simplified setting. We then derive the mean field equations for populations of
integrate-and-fire neurons. An effort is made to derive the main equations of
the theory using only elementary methods from calculus and probability theory.
The chapter ends with a discussion of the assumptions of the theory and some of
the consequences of violating those assumptions. This discussion includes an
introduction to balanced and metastable networks, and a brief catalogue of
successful applications of the mean field approach to the study of neural
circuits.


  Despite the prominence of neural network approaches in the field of
recommender systems, simple methods such as matrix factorization with quadratic
loss are still used in industry for several reasons. These models can be
trained with alternating least squares, which makes them easy to implement in a
massively parallel manner, thus making it possible to utilize billions of
events from real-world datasets. Large-scale recommender systems need to
account for severe popularity skew in the distributions of users and items, so
a lot of research is focused on implementing sparse, mixed dimension or shared
embeddings to reduce both the number of parameters and overfitting on rare
users and items. In this paper we propose two matrix factorization models with
mixed dimension embeddings, which can be optimized in a massively parallel
fashion using the alternating least squares approach.


  We report on spin ratchet currents driven by terahertz radiation electric
fields in a Co/Pt magnetic metamaterial formed by triangle-shaped holes forming
an antidots lattice and subjected to an external magnetic field applied
perpendicularly to the metal film plane. We show that for a radiation
wavelength substantially larger than the period of the antidots array the
radiation causes a polarization-independent spin-polarized ratchet current. The
current is generated by the periodic asymmetric radiation intensity
distribution caused by the near-field diffraction at the edges of the antidots,
which induces spatially inhomogeneous periodic electron gas heating, and a
phase-shifted periodic asymmetric electrostatic force. The developed
microscopic theory shows that the magnetization of the Co/Pt film results in a
spin ratchet current caused by both the anomalous Hall and the anomalous Nernst
effects. Additionally, we observed a polarization-dependent trigonal spin
photocurrent, which is caused by the scattering of electrons at the antidot
boundaries resulting in a spin-polarized current due to the magnetization.
Microscopic theory of these effects reveals that the trigonal photocurrent is
generated at the boundaries of the triangle antidots, whereas the spin ratchet
is generated due to the spatially periodic temperature gradient over the whole
film. This difference causes substantially different hysteresis widths of these
two currents.


  We have measured the isotopic abundances of neon and a number of other
species in the galactic cosmic rays (GCRs) using the Cosmic Ray Isotope
Spectrometer (CRIS) aboard the ACE spacecraft. Our data are compared to recent
results from two-component Wolf-Rayet (WR) models. The three largest deviations
of galactic cosmic ray isotope ratios from solar-system ratios predicted by
these models, 12C/16O, 22Ne/20Ne, and 58Fe/56Fe, are very close to those
observed. All of the isotopic ratios that we have measured are consistent with
a GCR source consisting of ~20% of WR material mixed with ~80% material with
solar-system composition. Since WR stars are evolutionary products of OB stars,
and most OB stars exist in OB associations that form superbubbles, the good
agreement of our data with WR models suggests that OB associations within
superbubbles are the likely source of at least a substantial fraction of GCRs.
In previous work it has been shown that the primary 59Ni (which decays only by
electron-capture) in GCRs has decayed, indicating a time interval between
nucleosynthesis and acceleration of >10^5 yr.In this paper we suggest a
scenario that should allow much of the 59Ni to decay in the OB association
environment and conclude that the hypothesis of the OB association origin of
cosmic rays appears to be viable.


  Under MA_{omega_1} every uncountable almost disjoint family is either
anti-Luzin or has an uncountable Luzin subfamily. This fails under CH. Related
properties are also investigated.


  Large language models (LLMs) are becoming bigger to boost performance.
However, little is known about how explainability is affected by this trend.
This work explores LIME explanations for DeBERTaV3 models of four different
sizes on natural language inference (NLI) and zero-shot classification (ZSC)
tasks. We evaluate the explanations based on their faithfulness to the models'
internal decision processes and their plausibility, i.e. their agreement with
human explanations. The key finding is that increased model size does not
correlate with plausibility despite improved model performance, suggesting a
misalignment between the LIME explanations and the models' internal processes
as model size increases. Our results further suggest limitations regarding
faithfulness metrics in NLI contexts.


  This paper brings the construction of free medial quandles as well as free
$n$-symmetric medial quandles and free $m$-reductive medial quandles.


  We apply the Postprocessing Galerkin method to a recently introduced
continuous data assimilation (downscaling) algorithm for obtaining a numerical
approximation of the solution of the two-dimensional Navier-Stokes equations
corresponding to given measurements from a coarse spatial mesh. Under suitable
conditions on the relaxation (nudging) parameter, the resolution of the coarse
spatial mesh and the resolution of the numerical scheme, we obtain uniform in
time estimates for the error between the numerical approximation given by the
Postprocessing Galerkin method and the reference solution corresponding to the
measurements. Our results are valid for a large class of interpolant operators,
including low Fourier modes and local averages over finite volume elements.
Notably, we use here the 2D Navier-Stokes equations as a paradigm, but our
results apply equally to other evolution equations, such as the Boussinesq
system of Benard convection and other oceanic and atmospheric circulation
models.


  We study type IIB supergravity solutions with four supersymmetries that
interpolate between two types widely considered in the literature: the dual of
Becker and Becker's compactifications of M-theory to 3 dimensions and the dual
of Strominger's torsion compactifications of heterotic theory to 4 dimensions.
We find that for all intermediate solutions the internal manifold is not
Calabi-Yau, but has SU(3) holonomy in a connection with a torsion given by the
3-form flux. All 3-form and 5-form fluxes, as well as the dilaton, depend on
one function appearing in the supersymmetry spinor, which satisfies a nonlinear
differential equation. We check that the fields corresponding to a flat bound
state of D3/D5-branes lie in our class of solutions. The relations among
supergravity fields that we derive should be useful in studying new gravity
duals of gauge theories, as well as possibly compactifications.


  Miniature heaters are immersed in flows of quantum fluid and the efficiency
of heat transfer is monitored versus velocity, superfluid fraction and time.
The fluid is $^4$He helium with a superfluid fraction varied from 71% down to
0% and an imposed velocity up to 3 m/s, while the characteristic sizes of
heaters range from 1.3 $\mu$m up to few hundreds of microns. At low heat
fluxes, no velocity dependence is observed. In contrast, some velocity
dependence emerges at larger heat flux, as reported previously, and three
non-trivial properties of heat transfer are identified. First, at the largest
superfluid fraction (71%), a new heat transfer regime appears at non-null
velocities and it is typically 10% less conductive than at zero velocity.
Second, the velocity dependence of the mean heat transfer is compatible with
the square-root dependence observed in classical fluids. Surprisingly, the
prefactor to this dependence is maximum for an intermediate superfluid fraction
or temperature (around 2 K). Third, the heat transfer time series exhibit
highly conductive short-lived events. These \textit{cooling glitches} have a
velocity-dependent characteristic time, which manifest itself as a broad and
energetic peak in the spectrum of heat transfer time series, in the kHz range.
After showing that the velocity dependence can be attributed to the breaking of
superfluidity within a thin shell surrounding heaters, an analytical model of
forced heat transfer in a quantum flow is developed to account for the
properties reported above. We argue that large scale flow patterns must form
around the heater, having a size proportional to the heat flux (here two
decades larger than the heater diameter) and resulting in a turbulent wake. The
observed spectral peaking of heat transfer is quantitatively consistent with
the formation of a Von K\'arm\'an vortex street in the wake of a bluff body.


  To study discrete dynamical systems of different types --- deterministic,
statistical and quantum --- we develop various approaches. We introduce the
concept of a system of discrete relations on an abstract simplicial complex and
develop algorithms for analysis of compatibility and construction of canonical
decompositions of such systems. To illustrate these techniques we describe
their application to some cellular automata. Much attention is paid to study
symmetries of the systems. In the case of deterministic systems, we reveale
some important relations between symmetries and dynamics. We demonstrate that
moving soliton-like structures arise inevitably in deterministic dynamical
system whose symmetry group splits the set of states into a finite number of
group orbits. We develop algorithms and programs exploiting discrete symmetries
to study microcanonical ensembles and search phase transitions in mesoscopic
lattice models. We propose an approach to quantization of discrete systems
based on introduction of gauge connection with values in unitary
representations of finite groups --- the elements of the connection are
interpreted as amplitudes of quantum transitions. We discuss properties of a
quantum description of finite systems. In particular, we demonstrate that a
finite quantum system can be embedded into a larger classical system. Computer
algebra and computational group theory methods were useful tools in our study.


  Uniformity of the probability measure of phase space is considered in the
framework of classical equilibrium thermodynamics. For the canonical and the
grand canonical ensembles, relations are given between the phase space
uniformities and thermodynamic potentials, their fluctuations and correlations.
For the binary system in the vicinity of the critical point the uniformity is
interpreted in terms of temperature dependent rates of phases of well defined
uniformities. Examples of a liquid-gas system and the mass spectrum of nuclear
fragments are presented.


  This paper studies the one-phase Muskat problem driven by gravity and surface
tension. The regime considered here is unstable with the fluid on top of a dry
region. By a novel approach using a depth-averaged formulation, we derive two
asymptotic approximations for this scenario. The lower order approximation is
the classical thin film equation, while the higher order approximation provides
a new refined thin film equation. We prove the optimal order of convergence in
the shallowness parameter to the original Muskat solutions for both models with
low-regular initial data.


  Robust, or model-independent properties of the variance swap are well-known,
and date back to Dupire and Neuberger, who showed that, given the price of
co-terminal call options, the price of a variance swap was exactly specified
under the assumption that the price process is continuous. In Cox and Wang we
showed that a lower bound on the price of a variance call could be established
using a solution to the Skorokhod embedding problem due to Root. In this paper,
we provide a construction, and a proof of optimality of the upper bound, using
results of Rost and Chacon, and show how this proof can be used to determine a
super-hedging strategy which is model-independent. In addition, we outline how
the hedging strategy may be computed numerically. Using these methods, we also
show that the Heston-Nandi model is 'asymptotically extreme' in the sense that,
for large maturities, the Heston-Nandi model gives prices for variance call
options which are approximately the lowest values consistent with the same call
price data.


  Various attempts have been made in the literature at describing the origin
and the physical mechanisms behind flaring events in blazars with radiative
emission models, but detailed properties of multi-wavelength (MWL) light curves
still remain difficult to reproduce. We have developed a versatile radiative
code, based on a time-dependent treatment of particle acceleration, escape and
radiative cooling, allowing us to test different scenarios to connect the
continuous low-state emission self-consistently with that during flaring
states. We consider flares as weak perturbations of the quiescent state and
apply this description to the February 2010 MWL flare of Mrk 421, the brightest
Very High Energy (VHE) flare ever detected from this archetypal blazar,
focusing on interpretations with a minimum number of free parameters. A general
criterion is obtained, which disfavours a one-zone model connecting low and
high state under our assumptions. A two-zone model combining physically
connected acceleration and emission regions yields a satisfactory
interpretation of the available time-dependent MWL light curves and spectra of
Mrk 421, although certain details remain difficult to reproduce. The two-zone
scenario finally proposed for the complex quiescent and flaring VHE emitting
region involves both Fermi-I and Fermi-II acceleration mechanisms, respectively
at the origin of the quiescent and flaring emission.


  The topic of this paper is the design of a fully distributed and real-time
capable control scheme for the automation of road intersections. State of the
art Vehicle-to-Vehicle (V2V) communication technology is adopted. Vehicles
distributively negotiate crossing priorities by a Consensus-Based Auction
Algorithm (CBAA-M). Then, each agent solves a nonlinear Model Predictive
Control (MPC) problem that computes the optimal trajectory avoiding collisions
with higher priority vehicles and deciding the crossing order. The scheme is
shown to be real-time capable and able to respond to sudden priority changes,
e.g. if a vehicle gets an emergency call. Simulations reinforce theoretical
results.


  In this paper, we have used the QUICK scheme of the finite volume method to
investigate the problem of steady 2-D free convective incompressible flow with
heat and mass transfer in an inclined rectangular domain at different Rayleigh
numbers in the range of $10^4 \le Ra \le 10^6$, for Prandtl number $Pr=7.2$,
and Lewis number $Le=1$. We have used no-slip wall boundary conditions for the
components of velocity and Neumann boundary conditions for temperature and
concentration. We have used the QUICK scheme to discretize the governing
equations along with the boundary conditions chosen in the present problem. The
SIMPLE algorithm is adopted to compute the numerical solutions of flow
variables, $U$-velocity, $V$-velocity, pressure, temperature, and concentration
as well as the local and average Nusselt and Sherwood numbers at different
Rayleigh numbers in the range mentioned above. Our numerical solutions for
$U$-velocity along the vertical line through the geometric center has been
compared with benchmark solutions available in the literature for
$\lambda=15^{\circ},\, Ra=10^4,\, Pr=7.2$, and $Le=1$ and it has been found
that it is in the good agreement. Pressure increases with increasing the angles
of inclination. When the angles of inclination increase from
$\lambda=15^{\circ}$ to $\lambda=45^{\circ}$, the intensity of streamlines
decreases near the center and secondary cells are formed at the top and bottom
of the center of the domain. As the Rayleigh number is increased from $10^4$ to
$10^6$, the average Nusselt number is decreased for $\lambda=15^{\circ}$, and
decreases and then increases for $\lambda=45^{\circ}$, whereas, the average
Sherwood number increases for $\lambda=15^{\circ}$ and decreases for
$\lambda=45^{\circ}$.


  Nowadays, liquid rocket engines use closed-loop control at most near steady
operating conditions. The control of the transient phases is traditionally
performed in open-loop due to highly nonlinear system dynamics. This situation
is unsatisfactory, in particular for reusable engines. The open-loop control
system cannot provide optimal engine performance due to external disturbances
or the degeneration of engine components over time. In this paper, we study a
deep reinforcement learning approach for optimal control of a generic
gas-generator engine's continuous start-up phase. It is shown that the learned
policy can reach different steady-state operating points and convincingly adapt
to changing system parameters. A quantitative comparison with carefully tuned
open-loop sequences and PID controllers is included. The deep reinforcement
learning controller achieves the highest performance and requires only minimal
computational effort to calculate the control action, which is a big advantage
over approaches that require online optimization, such as model predictive
control. control.


  In this paper we study a mathematical model for an infectious disease such as
  Cholera without life-time immunity. Due to the different mobility for
susceptible, infected human and recovered human hosts, the diffusion
coefficients are assumed to be different. The resulting system is governed by a
strongly coupled reaction-diffusion system with different diffusion
coefficients. Global existence and uniqueness are established under certain
assumptions on known data. Moreover, global asymptotic behavior of the solution
is obtained when some parameters satisfy certain conditions. These results
extend the existing results in the literature. The main tool used in this paper
comes from the delicate theory of elliptic and parabolic equations. Moreover,
the energy method and Sobolev embedding are used in deriving {\em apriori}
estimates. The analysis developed in this paper can be employed to study other
epidemic models in biological and ecological systems.


  GGR News:
  The WYP speakers program, by Richard Price
  We hear that..., by Jorge Pullin
  100 Years ago, by Jorge Pullin
  Research Briefs:
  What's new in LIGO, by David Shoemaker
  Recent developments in the information loss paradox, by Eanna Flanagan
  Gravity Probe B mission ends, by Bob Kahn
  Conference reports:
  6th Edoardo Amaldi Meeting, by Matthew Benacquista
  Workshop on Numerical Relativity, BIRS, by Carsten Gundlach
  8th Capra Meeting on Radiation Reaction, by Leor Barack
  Theory and experiment in quantum gravity, by Elizabeth Winstanley


  Dust and ice mantles on dust grains play an important role in various
processes in protoplanetary disks (PPDs) around a young star, including
planetesimal formation, surface chemistry, and being the reservoir of water in
habitable zones. In this paper, we will perform two-dimensional modeling of
rotational disruption of dust grains and ice mantles due to centrifugal force
within suprathermally rotating grains spun-up by radiative torques for disks
around T-Tauri and Herbig Ae/Be stars. We first study rotational disruption of
large composite grains and find that large aggregates could be disrupted into
individual nanoparticles via the RAdiative Torque Disruption (RATD) mechanism.
We then study rotational desorption of ice mantles and ro-thermal desorption of
molecules from the ice mantle. We will show that ice mantles in the warm
surface layer and above of the disk can be disrupted into small icy fragments,
followed by rapid evaporation of molecules. We suggest that the rotational
disruption mechanism can replenish the ubiquitous presence of polycyclic
aromatic hydrogen (PAHs)/ nanoparticles in the hot surface layers of PPDs as
observed in mid-IR emission, which are presumably destroyed by extreme
ultraviolet (UV) stellar photons. We show that the water snowline is more
extended in the presence of rotational desorption, which would decrease the
number of comets but increase the number of asteroids formed in the solar
nebula. Finally, we suggest that the more efficient breakup of carbonaceous
grains than silicates by RATD might resolve the carbon deficit problem measured
on the Earth and rocky bodies.


  There is a group-theoretical connection between fermion mixing matrices and
minimal horizontal symmetry groups. Applying this connection to the
tri-bimaximal neutrino mixing matrix, we show that the minimal horizontal
symmetry group for leptons is uniquely $S_4$, the permutation group of four
objects.


  The spin contribution to the magnetic moment in SmMn2Ge2 has been measured by
magnetic Compton scattering in both the low and high temperature ferromagnetic
phases. At low temperature, the Sm site is shown to possess a large 4f spin
moment of 3.4 +/- 0.1 Bohr magnetons, aligned antiparallel to the total
magnetic moment. At high temperature, the data show conclusively that ordered
magnetic moments are present on the samarium site.


  We present a deep learning-based framework for portrait reenactment from a
single picture of a target (one-shot) and a video of a driving subject.
Existing facial reenactment methods suffer from identity mismatch and produce
inconsistent identities when a target and a driving subject are different
(cross-subject), especially in one-shot settings. In this work, we aim to
address identity preservation in cross-subject portrait reenactment from a
single picture. We introduce a novel technique that can disentangle identity
from expressions and poses, allowing identity preserving portrait reenactment
even when the driver's identity is very different from that of the target. This
is achieved by a novel landmark disentanglement network (LD-Net), which
predicts personalized facial landmarks that combine the identity of the target
with expressions and poses from a different subject. To handle portrait
reenactment from unseen subjects, we also introduce a feature dictionary-based
generative adversarial network (FD-GAN), which locally translates 2D landmarks
into a personalized portrait, enabling one-shot portrait reenactment under
large pose and expression variations. We validate the effectiveness of our
identity disentangling capabilities via an extensive ablation study, and our
method produces consistent identities for cross-subject portrait reenactment.
Our comprehensive experiments show that our method significantly outperforms
the state-of-the-art single-image facial reenactment methods. We will release
our code and models for academic use.


  We design a deterministic polynomial time $c^n$ approximation algorithm for
the permanent of positive semidefinite matrices where $c=e^{\gamma+1}\simeq
4.84$. We write a natural convex relaxation and show that its optimum solution
gives a $c^n$ approximation of the permanent. We further show that this factor
is asymptotically tight by constructing a family of positive semidefinite
matrices.


  We have developed a 3D computer model of polars which includes the accretion
stream, the accretion column, the secondary star, and the white dwarf. Each
component is represented by a fine grid of surface elements. With brightness
values attributed to each surface element, this model generates synthetic light
curves of the various components. As a first application, we present our
simulated light curves of the accretion stream, fitted to high-speed HST
spectroscopy of the eclipsing polar UZ Fornacis by the means of an evolution
strategy.


  Policy gradient methods in reinforcement learning update policy parameters by
taking steps in the direction of an estimated gradient of policy value. In this
paper, we consider the statistically efficient estimation of policy gradients
from off-policy data, where the estimation is particularly non-trivial. We
derive the asymptotic lower bound on the feasible mean-squared error in both
Markov and non-Markov decision processes and show that existing estimators fail
to achieve it in general settings. We propose a meta-algorithm that achieves
the lower bound without any parametric assumptions and exhibits a unique 3-way
double robustness property. We discuss how to estimate nuisances that the
algorithm relies on. Finally, we establish guarantees on the rate at which we
approach a stationary point when we take steps in the direction of our new
estimated policy gradient.


  Design of robots at the small scale is a trial-and-error based process, which
is costly and time-consuming. There are few dynamic simulation tools available
to accurately predict the motion or performance of untethered microrobots as
they move over a substrate. At smaller length scales, the influence of adhesion
and friction, which scales with surface area, becomes more pronounced. Thus,
rigid body dynamic simulators, which implicitly assume that contact between two
bodies can be modeled as point contact are not suitable. In this paper, we
present techniques for simulating the motion of microrobots where there can be
intermittent and non-point contact between the robot and the substrate. We use
these techniques to study the motion of tumbling microrobots of different
shapes and select shapes that are optimal for improving locomotion performance.
Simulation results are verified using experimental data on linear velocity,
maximum climbable incline angle, and microrobot trajectory. Microrobots with
improved geometry were fabricated, but limitations in the fabrication process
resulted in unexpected manufacturing errors and material/size scale
adjustments. The developed simulation model is able to incorporate these
limitations and emulate their effect on the microrobot's motion, reproducing
the experimental behavior of the tumbling microrobots, further showcasing the
effectiveness of having such a dynamic model.


  This self-contained paper is part of a series \cite{FF2,FF3} on actions by
diffeomorphisms of infinite groups on compact manifolds. The two main results
presented here are:
  1) Any homomorphism of (almost any) mapping class group or automorphism group
of a free group into $\Diff_+^r(S^1), r\geq 2$ is trivial. For r=0 Nielsen
showed that in many cases nontrivial (even faithful) representations exist.
Somewhat weaker results are proven for finite index subgroups.
  2) We construct a finitely-presented group of real-analytic diffeomorphisms
of $\R$ which is not residually finite.


  First we generalize the Thue-Morse sequence (the generalized Thue-Morse
sequences) by a cyclic permutations and p-adic system, and consider the
necessary-sufficient condition that it is non-periodic. Moreover if the
generalized Thue-Morse sequence is not periodic, then all equally spaced
subsequences of the generalized Thue-Morse sequences are not periodic. Finally
we apply recently combinatorial transcendence results to the generalized
non-periodic Thue-Morse sequence, we can found many transcendental numbers.


  We analyze the most general case of third-order Chern-Simons-like theories of
massive 3D gravity. Results show the conditions for finding the unitary regions
on the parameter space. There exists $(n-1)$th order theories on the boundary
of a unitary $n$th order model on parameter space under certain conditions, as
the first example recently demonstrated from the bimetric generalization of
exotic massive gravity. We investigated the mechanism that causes this type of
transition for third-order models. Hamiltonian analysis of the theory also
presents that ghost and no-ghost regions can be separated by Chern-Simons
theories.


  We consider mediated interactions in an array of floating transmons, where
each qubit capacitor consists of two superconducting pads galvanically isolated
from ground. Each such pair contributes two quantum degrees of freedom, one of
which is used as a qubit, while the other remains fixed. However, these
extraneous modes can generate coupling between the qubit modes that extends
beyond the nearest neighbor. We present a general formalism describing the
formation of this coupling and calculate it for a one-dimensional chain of
transmons. We show that the strength of coupling and its range (that is, the
exponential falloff) can be tuned independently via circuit design to realize a
continuum from nearest-neighbor-only interactions to interactions that extend
across the length of the chain. We present designs with capacitance and
microwave simulations showing that various interaction configurations can be
achieved in realistic circuits. Such coupling could be used in analog
simulation of different quantum regimes or to increase connectivity in digital
quantum systems. Thus mechanism must also be taken into account in other types
of qubits with extraneous modes.


  The observation that the 0-dimensional Geometric Invariant $\Sigma ^{0}(G;A)$
of Bieri-Neumann-Strebel-Renz can be interpreted as a horospherical limit set
opens a direct trail from Poincar\'e's limit set $\Lambda (\Gamma)$ of a
discrete group $\Gamma $ of M\"obius transformations (which contains the
horospherical limit set of $\Gamma $) to the roots of tropical geometry
(closely related to $\Sigma ^{0}(G;A)$ when G is abelian). We explore this
trail by introducing the horospherical limit set, $\Sigma (M;A)$, of a G-module
A when G acts by isometries on a proper CAT(0) metric space M. This is a subset
of the boundary at infinity of M. On the way we meet instances where $\Sigma
(M;A)$ is the set of all conical limit points, the complement of a spherical
building, the complement of the radial projection of a tropical variety, or
(via the Bieri-Neumann-Strebel invariant) where it is closely related to the
Thurston norm.


  Recent works reveal that adversarial augmentation benefits the generalization
of neural networks (NNs) if used in an appropriate manner. In this paper, we
introduce Temporal Adversarial Augmentation (TA), a novel video augmentation
technique that utilizes temporal attention. Unlike conventional adversarial
augmentation, TA is specifically designed to shift the attention distributions
of neural networks with respect to video clips by maximizing a temporal-related
loss function. We demonstrate that TA will obtain diverse temporal views, which
significantly affect the focus of neural networks. Training with these examples
remedies the flaw of unbalanced temporal information perception and enhances
the ability to defend against temporal shifts, ultimately leading to better
generalization. To leverage TA, we propose Temporal Video Adversarial
Fine-tuning (TAF) framework for improving video representations. TAF is a
model-agnostic, generic, and interpretability-friendly training strategy. We
evaluate TAF with four powerful models (TSM, GST, TAM, and TPN) over three
challenging temporal-related benchmarks (Something-something V1&V2 and
diving48). Experimental results demonstrate that TAF effectively improves the
test accuracy of these models with notable margins without introducing
additional parameters or computational costs. As a byproduct, TAF also improves
the robustness under out-of-distribution (OOD) settings. Code is available at
https://github.com/jinhaoduan/TAF.


  The Vela supernova remnant is the closest supernova remnant to Earth
containing an active pulsar, the Vela pulsar (PSR B0833-45). This pulsar is the
archetype of the middle-aged pulsar class and powers a bright pulsar wind
nebula (PWN), Vela-X, spanning a region of 2{\deg} x 3{\deg} south of the
pulsar and observed in the radio, X-ray and very high energy gamma-ray domains.
The detection of the Vela-X PWN by the Fermi Large Area Telescope (LAT) was
reported in the first year of the mission. Subsequently, we have
re-investigated this complex region and performed a detailed morphological and
spectral analysis of this source using 4 years of Fermi-LAT observations. This
study lowers the threshold for morphological analysis of the nebula from 0.8
GeV to 0.3 GeV, allowing inspection of distinct energy bands by the LAT for the
first time. We describe the recent results obtained on this PWN and discuss the
origin of the newly detected spatial features.


  Weakly-coupled models for the 750 GeV diphoton resonance often invoke new
particles carrying both color and/or electric charges to mediate loop-induced
couplings of the resonance to two gluons and two photons. The new colored
particles may not be stable and could decay into final states containing
standard model particles. We consider an electroweak doublet of vector-like
quarks (VLQs) carrying electric charges of 5/3 and 2/3, respectively, which
mediate the loop-induced couplings of the 750 GeV resonance. If the VLQ has a
mass at around 1 TeV, it naturally gives rise to the observed diphoton signal
strength while all couplings remain perturbative up to a high scale. At the
same time, if the charge-5/3 VLQ decays into final states containing top quark
and W boson, it would contribute to the multilepton excesses observed in both
Run 1 and Run 2 data. It is also possible to incorporate a dark matter
candidate in the decay final states to explain the observed relic density.


  Intermediate polars are members of the cataclysmic variable binary stars.
They are characterized by a moderately magnetized white dwarf accreting matter
from a cool main-sequence companion star. In many cases, this accretion gives
rise to a detectable $X$-ray emission. VZ Sex is an interesting $X$-ray source
whose nature needs a robust confirmation. Here, we used archive $XMM$-Newton
observation to assign the source to the intermediate polar class. We applied
the Lomb-Scargle periodogram method to detect any relevant periodic feature in
the $0.1$--$10$ keV light curve and performed a spectral fitting of the $X$-ray
spectrum in order to get information on the on-going accretion mechanism. By
inspecting the periodogram, we detected a clear periodic feature at $\simeq
20.3$ minutes that we interpret as the spin period of the white dwarf. We
additionally found the typical side bands expected as the consequence of the
beat between the spin and the orbital period of $\simeq 3.581$ hours. The
source is characterized by a unabsorbed flux of $\simeq 2.98\times 10^{-12}$
erg cm$^{-2}$ s$^{-1}$ corresponding to an intrinsic luminosity {of $\simeq 7
\times 10^{31}$ erg s$^{-1}$ } {for a distance of $\simeq 433$ pc}. The
existence of such features allow us to classify VZ Sex as a clear member of the
intermediate polar class. Furthermore, with the estimated WD spin, the ratio
$P_{spin}/P_{orb}$ is $\simeq 0.09$, i.e. consistent with that expected for a
typical IP system above the period gap. In addition, the estimated intrinsic
luminosity opens the possibility that a bridge linking the normally bright IPs
to the faint population of sources does exist.


  Liouville domains have become central objects in symplectic and contact
geometry. However, the auxiliary data they involve --- namely, Liouville forms
--- and the non-compactness of their completions generate some inconvenience.
The notion of ideal Liouville domains is designed to suppress these awkward
aspects and to let symplectic structures play the leading role. Ideal Liouville
domains are compact manifolds with boundary whose interior carries a symplectic
form satisfying some tameness condition along the boundary. Their definition
and their basic properties are presented in the first part of these notes,
while the second part discusses their relevance in contact geometry.


  Neural network models have been very successful at achieving high accuracy on
natural language inference (NLI) tasks. However, as demonstrated in recent
literature, when tested on some simple adversarial examples, most of the models
suffer a significant drop in performance. This raises the concern about the
robustness of NLI models. In this paper, we propose to make NLI models robust
by incorporating external knowledge to the attention mechanism using a simple
transformation. We apply the new attention to two popular types of NLI models:
one is Transformer encoder, and the other is a decomposable model, and show
that our method can significantly improve their robustness. Moreover, when
combined with BERT pretraining, our method achieves the human-level performance
on the adversarial SNLI data set.