  Most lip-to-speech (LTS) synthesis models are trained and evaluated under the
assumption that the audio-video pairs in the dataset are perfectly
synchronized. In this work, we show that the commonly used audio-visual
datasets, such as GRID, TCD-TIMIT, and Lip2Wav, can have data asynchrony
issues. Training lip-to-speech with such datasets may further cause the model
asynchrony issue -- that is, the generated speech and the input video are out
of sync. To address these asynchrony issues, we propose a synchronized
lip-to-speech (SLTS) model with an automatic synchronization mechanism (ASM) to
correct data asynchrony and penalize model asynchrony. We further demonstrate
the limitation of the commonly adopted evaluation metrics for LTS with
asynchronous test data and introduce an audio alignment frontend before the
metrics sensitive to time alignment for better evaluation. We compare our
method with state-of-the-art approaches on conventional and time-aligned
metrics to show the benefits of synchronization training.


  We numerically investigate and develop analytic models for both the DC and
pulsed spin-orbit-torque (SOT)-driven response of order parameter in
single-domain Mn$_3$Sn, which is a metallic antiferromagnet with an anti-chiral
120$^\circ$ spin structure. We show that DC currents above a critical threshold
can excite oscillatory dynamics of the order parameter in the gigahertz to
terahertz frequency spectrum. Detailed models of the oscillation frequency
versus input current are developed and found to be in excellent agreement with
the numerical simulations of the dynamics. In the case of pulsed excitation,
the magnetization can be switched from one stable state to any of the other
five stable states in the Kagome plane by tuning the duration or the amplitude
of the current pulse. Precise functional forms of the final switched state
versus the input current are derived, offering crucial insights into the
switching dynamics of Mn$_3$Sn. The readout of the magnetic state can be
carried out via either the anomalous Hall effect, or the recently demonstrated
tunneling magnetoresistance in an all-Mn$_3$Sn junction. We also discuss
possible disturbance of the magnetic order due to heating that may occur if the
sample is subject to large currents. Operating the device in pulsed mode or
using low DC currents reduces the peak temperature rise in the sample due to
Joule heating. Our predictive modeling and simulation results can be used by
both theorists and experimentalists to explore the interplay of SOT and the
order dynamics in Mn$_3$Sn, and to further benchmark the device performance.


  In this paper, a Bayesian semiparametric copula approach is used to model the
underlying multivariate distribution $F_{true}$. First, the Dirichlet process
is constructed on the unknown marginal distributions of $F_{true}$. Then a
Gaussian copula model is utilized to capture the dependence structure of
$F_{true}$. As a result, a Bayesian multivariate normality test is developed by
combining the relative belief ratio and the Energy distance. Several
interesting theoretical results of the approach are derived. Finally, through
several simulated examples and a real data set, the proposed approach reveals
excellent performance.


  In this work, we propose a novel implementation of Newton's method for
solving semi-discrete optimal transport (OT) problems for cost functions which
are a positive combination of $p$-norms, $1<p<\infty$. It is well understood
that the solution of a semi-discrete OT problem is equivalent to finding a
partition of a bounded region in Laguerre cells, and we prove that the Laguerre
cells are star-shaped with respect to the target points. By exploiting the
geometry of the Laguerre cells, we obtain an efficient and reliable
implementation of Newton's method to find the sought network structure. We
provide implementation details and extensive results in support of our
technique in 2-d problems, as well as comparison with other approaches used in
the literature.


  Frequency-dependent correlations, such as the spectral function and the
dynamical structure factor, help understand condensed matter experiments.
Within the density matrix renormalization group (DMRG) framework, an accurate
method for calculating spectral functions directly in frequency is the
correction-vector method. The correction-vector can be computed by solving a
linear equation or by minimizing a functional. This paper proposes an
alternative to calculate the correction vector: to use the Krylov-space
approach. This paper then studies the accuracy and performance of the
Krylov-space approach, when applied to the Heisenberg, the t-J, and the Hubbard
models. The cases studied indicate that Krylov-space approach can be more
accurate and efficient than conjugate gradient, and that the error of the
former integrates best when a Krylov-space decomposition is also used for
ground state DMRG.


  Let $\Bbbk$ be an algebraically closed field of characteristic 0. We study
some cohomological properties of Lie subalgebras of the Witt algebra $W =
\operatorname{Der}(\Bbbk[t,t^{-1}])$ and the one-sided Witt algebra $W_{\geq
-1} = \operatorname{Der}(\Bbbk[t])$. In the first part of the paper, we
consider finite codimension subalgebras of $W_{\geq -1}$. We compute
derivations and one-dimensional extensions of such subalgebras. These
correspond to $\operatorname{Ext}_{U(L)}^1(M,L)$, where $L$ is a subalgebra of
$W_{\geq -1}$ and $M$ is a one-dimensional representation of $L$. We find that
these subalgebras exhibit a kind of rigidity: their derivations and extensions
are controlled by the full one-sided Witt algebra. As an application of these
computations, we prove that any isomorphism between finite codimension
subalgebras of $W_{\geq -1}$ extends to an automorphism of $W_{\geq -1}$.
  The second part of the paper is devoted to explaining the observed rigidity.
We define a notion of "completely non-split extension" and prove that $W_{\geq
-1}$ is the universal completely non-split extension of any of its subalgebras
of finite codimension. In some sense, this means that even when studying
subalgebras of $W_{\geq -1}$ as abstract Lie algebras, they remember that they
are contained in $W_{\geq -1}$. We also consider subalgebras of infinite
codimension, explaining the similarities and differences between the finite and
infinite codimension situations.
  Almost all of the results above are also true for subalgebras of the Witt
algebra. We summarise results for $W$ at the end of the paper.


  The international community must collaborate to mitigate climate change and
sustain economic growth. However, collaboration is hard to achieve, partly
because no global authority can ensure compliance with international climate
agreements. Combining AI with climate-economic simulations offers a promising
solution to design international frameworks, including negotiation protocols
and climate agreements, that promote and incentivize collaboration. In
addition, these frameworks should also have policy goals fulfillment, and
sustained commitment, taking into account climate-economic dynamics and
strategic behaviors. These challenges require an interdisciplinary approach
across machine learning, economics, climate science, law, policy, ethics, and
other fields.
  Towards this objective, we organized AI for Global Climate Cooperation, a
Mila competition in which teams submitted proposals and analyses of
international frameworks, based on (modifications of) RICE-N, an AI-driven
integrated assessment model (IAM). In particular, RICE-N supports modeling
regional decision-making using AI agents. Furthermore, the IAM then models the
climate-economic impact of those decisions into the future.
  Whereas the first track focused only on performance metrics, the proposals
submitted to the second track were evaluated both quantitatively and
qualitatively. The quantitative evaluation focused on a combination of (i) the
degree of mitigation of global temperature rise and (ii) the increase in
economic productivity. On the other hand, an interdisciplinary panel of human
experts in law, policy, sociology, economics and environmental science,
evaluated the solutions qualitatively. In particular, the panel considered the
effectiveness, simplicity, feasibility, ethics, and notions of climate justice
of the protocols. In the third track, the participants were asked to critique
and improve RICE-N.


  I discuss three aspects of the notion of agency from the standpoint of
physics: (i) what makes a physical system an agent; (ii) the reason for
agency's time orientation; (iii) the source of the information generated in
choosing an action. I observe that agency is the breaking of an approximation
under which dynamics appears closed. I distinguish different notions of agency,
and observe that the answer to the questions above differ in different cases. I
notice a structural similarity between agency and memory, that allows us to
model agency, trace its time asymmetry to thermodynamical irreversibility, and
identify the source of the information generated by agency in the growth of
entropy. Agency is therefore a physical mechanism that transforms low entropy
into information. This may be the general mechanism at the source of the whole
information on which biology builds.


  Surface brightness profiles for 23 M31 star clusters were measured using
images from the Wide Field Planetary Camera 2 on the Hubble Space Telescope,
and fit to two types of models to determine the clusters' structural
properties. The clusters are primarily young (~10^8 yr) and massive (~10^4.5
solar masses), with median half-light radius 7 pc and dissolution times of a
few Gyr. The properties of the M31 clusters are comparable to those of clusters
of similar age in the Magellanic Clouds. Simulated star clusters are used to
derive a conversion from statistical measures of cluster size to half-light
radius so that the extragalactic clusters can be compared to young massive
clusters in the Milky Way. All three sets of star clusters fall approximately
on the same age-size relation. The young M31 clusters are expected to dissolve
within a few Gyr and will not survive to become old, globular clusters.
However, they do appear to follow the same fundamental plane relations as old
clusters; if confirmed with velocity dispersion measurements, this would be a
strong indication that the star cluster fundamental plane reflects universal
cluster formation conditions.


  A method to interpret probe spectra of driven degenerate atomic systems is
discussed. The dressed-atom multiphoton spectroscopy (DAMS) is based on a
dressing of the atomic system with the strong coupling field, followed by a
perturbative treatment of the probe field interaction. As example, we apply the
DAMS to provide a clear interpretation for anomalous electromagnetically
induced absorption (EIA), which cannot be explained by spontaneous transfer of
coherence. We show that anomalous EIA arises from quantum interference between
competing two-photon transitions, and explain the different dependences on the
coupling field strength observed for various angular momentum setups.


  We report on the cancellation of quantum back action noise in an
optomechanical cavity. We perform two measurements of the displacement of the
microresonator, one in reflection of the cavity, and one in transmission of the
cavity. We show that measuring the amplitude quadrature of the light in
transmission of the optomechanical cavity allows us to cancel the back action
noise between 1 kHz and 50 kHz, and obtain a more sensitive measurement of the
microresonator's position. To confirm that the back action is eliminated, we
measure the noise in the transmission signal as a function of circulating
power. By splitting the transmitted light onto two photodetectors and cross
correlating the two signals, we remove the contributon from shot noise and
measure a quantum noise free thermal noise spectrum. Eliminating the effects of
back action in this frequency regime is an important demonstration of a
technique that could be used to mitigate the effects of back action in
interferometric gravitational wave detectors such as Advanced LIGO.


  This paper analyses the various authentication systems implemented for
enhanced security and private re-position of an individual's log-in
credentials. The first part of the paper describes the multi-factor
authentication (MFA) systems, which, though not applicable to the field of
Internet of Things, provides great security to a user's credentials. MFA is
followed by a brief description of the working mechanism of interaction of
third party clients with private resources over the OAuth protocol framework
and a study of the delegation based authentication system in IP-based IoT.


  A search for partonic collective effects inside jets produced in
proton-proton collisions is performed via correlation measurements of charged
constituents using the CMS detector at the CERN LHC. The analysis uses data
collected at a center-of-mass energy of $\sqrt{s}$ = 13 TeV, corresponding to
an integrated luminosity of 138 fb$^{-1}$. Jets are reconstructed with the
anti-$k_\mathrm{T}$ algorithm with a distance parameter of 0.8 and are required
to have transverse momentum greater than 550 GeV and pseudorapidity
$\lvert\eta\rvert$ $\lt$ 1.6. Two-particle correlations among the charged
constituents within the jets are studied as functions of the particles'
azimuthal angle and pseudorapidity separations ($\Delta\phi^*$ and
$\Delta\eta^*$) in a jet coordinate basis, where constituents' $\eta^*$,
$\phi^*$ are defined relative to the direction of the jet. The correlation
functions are studied in classes of in-jet charged-particle multiplicity up to
$N_\text{ch}^\mathrm{j}$ $\approx$ 100. Fourier harmonics are extracted from
long-range azimuthal correlation functions to characterize azimuthal anisotropy
for $\lvert\Delta\eta^*\rvert$ $\gt$ 2. For low-multiplicity jets, the
long-range elliptic anisotropic harmonic, $v^*_2$, is observed to decrease with
$N_\text{ch}^\mathrm{j}$. This trend is well described by Monte Carlo event
generators. However, a rising trend for $v^*_2$ emerges at
$N_\text{ch}^\mathrm{j}$ $\gtrsim$ 80, hinting at a possible onset of
collective behavior, which is not reproduced by the models tested. This
observation yields new insights into the dynamics of parton fragmentation
processes in the vacuum.


  Let $f$ and $g$ be smooth multimodal maps with no periodic attractors and no
neutral points. If a topological conjugacy $h$ between $f$ and $g$ is $C^{1}$
at a point in the nearby expanding set of $f$, then $h$ is a smooth
diffeomorphism in the basin of attraction of a renormalization interval of $f$.
In particular, if $f:I \to I$ and $g:J \to J$ are $C^r$ unimodal maps and $h$
is $C^{1}$ at a boundary of $I$ then $h$ is $C^r$ in $I$.


  In this work we consider whether nonsymmorphic symmetries such as a glide
plane can protect the existence of topological crystalline insulators and
superconductors in three dimensions. In analogy to time-reversal symmetric
insulators, we show that the presence of a glide gives rise to a quantized
magnetoelectric polarizability, which we compute explicitly through the
Chern-Simons 3-form of the bulk wave functions for a glide symmetric model. Our
approach provides a measurable property for this insulator and naturally
explains the connection with mirror symmetry protected insulators and the
recently proposed $Z_2$ index for this phase. More generally, we prove that the
magnetoelectric polarizability becomes quantized with any orientation-reversing
space group symmetry. We also construct analogous examples of glide protected
topological crystalline superconductors in classes D and C and discuss how bulk
invariants are related to quantized surface thermal-Hall and spin-Hall
responses.


  This paper proposes a robust watermarking approach based on Discrete Cosine
Transform domain that combines Quick Response Code and chaotic system.


  Simplified models of transport in mesoscopic systems are often based on a
small sample connected to a finite number of leads. The leads are often
modelled using the Laplacian on the discrete half-line $\mathbb N$. Detailed
studies of the transport near thresholds require detailed information on the
resolvent of the Laplacian on the discrete half-line. This paper presents a
complete study of threshold resonance states and resolvent expansions at a
threshold for the Schr\"odinger operator on the discrete half-line $\mathbb N$
with a general boundary condition. A precise description of the expansion
coefficients reveals their exact correspondence to the generalized eigenspaces,
or the threshold types. The presentation of the paper is adapted from that of
Ito-Jensen [Rev.\ Math.\ Phys.\ {\bf 27} (2015), 1550002 (45 pages)],
implementing the expansion scheme of Jensen-Nenciu [Rev.\ Math.\ Phys.\
\textbf{13} (2001), 717--754, \textbf{16} (2004), 675--677] in its full
generality.


  It is well-known that with an appropriate combination of three Liouville-type
dilaton potentials, one can construct charged dilaton black holes in an
(anti)-de Sitter [(A)dS] spaces in the presence of linear Maxwell field.
However, asymptotically (A)dS dilaton black holes coupled to nonlinear gauge
field have not been found. In this paper, we construct, for the first time,
three new classes of dilaton black hole solutions in the presence of three
types of nonlinear electrodynamics, namely Born-Infeld, Logarithmic and
Exponential nonlinear electrodynamics. All these solutions are asymptotically
(A)dS and in the linear regime reduce to the Einstein-Maxwell-dilaton black
holes in AdS spaces. We investigate physical properties and the causal
structure, as well as asymptotic behavior of the obtained solutions, and show
that depending on the values of the metric parameters, the singularity can be
covered by various horizons. Interestingly enough, we find that the coupling of
dilaton field and nonlinear gauge field in the background of (A)dS spaces leads
to a strange behaviour for the electric field. We observe that the electric
field is zero at singularity and increases smoothly until reaches a maximum
value, then it decreases smoothly until goes to zero as $r\rightarrow\infty$.
The maximum value of the electric field increases with increasing the nonlinear
parameter $\beta$ or decreasing the dilaton coupling $\alpha$ and is shifted to
the singularity in the absence of either dilaton field ($\alpha=0$) or
nonlinear gauge field ($\beta\rightarrow\infty$).


  We study the thermodynamics of classical Heisenberg model using the multipath
approach to Metropolis algorithm Monte Carlo simulation. This simulation
approach produces uncorrelated results with known precision. Also, it can be
easily generalized to other classical models of magnetism. Comparing results
obtained from multipath and from single--path simulations we demonstrate that
these approaches produce equivalent results.


  I present chromospheric activity measurements of ~ 670 F, G, K and M main
sequence stars in the Southern Hemisphere, from ~8000 archival high-resolution
echelle spectra taken at Las Campanas Observatory since 2004. These stars were
targets from the Old Magellan Planet Search, and are now potential targets for
the New Magellan Planet Search that will look for rocky and habitable planets.
Activity indexes (S-values) are derived from Ca II H & K line cores and then
converted to the Mt. Wilson system. From these measurements, chromospheric
(logrhk) indexes are derived, which are then used as indicators of the level of
radial-velocity jitter, age and rotation periods these stars present.


  In this paper, we study unirational differential curves and the corresponding
differential rational parametrizations. We first investigate basic properties
of proper differential rational parametrizations for unirational differential
curves. Then we show that the implicitization problem of proper linear
differential rational parametric equations can be solved by means of
differential resultants. Furthermore, for linear differential curves, we give
an algorithm to determine whether an implicitly given linear differential curve
is unirational and, in the affirmative case, to compute a proper differential
rational parametrization for the differential curve.


  Very compelling deviations in the recently observed lepton nonuniversality
observables $\big (R_{D^{(*)}}, R_{K^{(*)}}, R_{J/\psi} \big )$ of semileptonic
$B$ meson decays from their Standard Model predictions hint towards the
presence of some kind of new physics beyond it. In this regard, we investigate
the effect of new physics in the semileptonic $\bar B_{d(s)}^* \to P \ell
\bar{\nu}_\ell$ decay processes, where $P=D,\pi (D_s,K$), in a model
independent way. We consider the presence of additional vector and scalar type
interactions and constrain the corresponding new couplings by fitting ${\rm
Br(B_{u}^+ \to \tau^+ \nu_\tau)}$, ${\rm Br(B \to \pi \tau \bar \nu_\tau)}$,
${\rm Br(B_{c}^+ \to \tau^+ \nu_\tau)}$, $R_\pi^l$, $R_{D^{(*)}}$ and
$R_{J/\psi}$ data. Using the constrained new parameters, we estimate the
branching ratios, forward-backward asymmetry, lepton-spin asymmetry and lepton
non-universality observables of $\bar B_{d,s}^{*} \to P \tau \bar \nu_\tau$
processes. We find that the branching ratios of these decay modes are sizeable
and deviate significantly (for vector-type couplings) from their corresponding
standard model values, which are expected to be within the reach of Run III of
Large Hadron Collider experiment.


  We propose the relation $M_\Lambda \sim (M_{Pl} M_U)^{1/2}$ where
$M_\Lambda$, $M_{Pl},$ and $M_U$ denote the mass scale associated with the
cosmological constant, the gravitational interaction, and the size of the
universe respectively.


  We propose ADOM - an accelerated method for smooth and strongly convex
decentralized optimization over time-varying networks. ADOM uses a dual oracle,
i.e., we assume access to the gradient of the Fenchel conjugate of the
individual loss functions. Up to a constant factor, which depends on the
network structure only, its communication complexity is the same as that of
accelerated Nesterov gradient method (Nesterov, 2003). To the best of our
knowledge, only the algorithm of Rogozin et al. (2019) has a convergence rate
with similar properties. However, their algorithm converges under the very
restrictive assumption that the number of network changes can not be greater
than a tiny percentage of the number of iterations. This assumption is hard to
satisfy in practice, as the network topology changes usually can not be
controlled. In contrast, ADOM merely requires the network to stay connected
throughout time.


  Strain engineering in Sn-rich group IV semiconductors is a key enabling
factor to exploit the direct band gap at mid-infrared wavelengths. Here, we
investigate the effect of strain on the growth of GeSn alloys in a Ge/GeSn
core/shell nanowire geometry. Incorporation of Sn content in the 10-20 at.%
range is achieved with Ge core diameters ranging from 50nm to 100nm. While the
smaller cores lead to the formation of a regular and homogeneous GeSn shell,
larger cores lead to the formation of multi-faceted sidewalls and broadened
segregation domains, inducing the nucleation of defects. This behavior is
rationalized in terms of the different residual strain, as obtained by
realistic finite element method simulations. The extended analysis of the
strain relaxation as a function of core and shell sizes, in comparison with the
conventional planar geometry, provides a deeper understanding of the role of
strain in the epitaxy of metastable GeSn semiconductors.


  We report experiments on gravity-capillary wave turbulence on the surface of
a fluid. The wave amplitudes are measured simultaneously in time and space
using an optical method. The full space-time power spectrum shows that the wave
energy is localized on several branches in the wave-vector-frequency space. The
number of branches depend on the power injected within the waves. The
measurement of the nonlinear dispersion relation is found to be well described
by a law suggesting that the energy transfer mechanisms involved in wave
turbulence are not only restricted to purely resonant interaction between
nonlinear waves. The power-law scaling of the spatial spectrum and the
probability distribution of the wave amplitudes at a given wave number are also
measured and compared to the theoretical predictions.


  The aim of the paper is to present numerical results supporting the presence
of conformal invariance in three dimensional statistical mechanics models at
criticality and to elucidate the geometric aspects of universality. As a case
study we study three dimensional percolation at criticality in bounded domains.
Both on discrete and continuous models of critical percolation, we test by
numerical experiments the invariance of quantities in finite domains under
conformal transformations focusing on crossing probabilities. Our results show
clear evidence of the onset of conformal invariance in finite realizations
especially for the continuum percolation models. Finally we propose a simple
analytical function approximating the crossing probability among two spherical
caps on the surface of a sphere and confront it with the numerical results.


  We have constructed an imaging device that capable to show a spatio-temporal
distribution of magnetic field intensity in real-time. The device employs a set
of AMR (Anisotropic Magneto Resistance) 3-axis magnetometers, which are
arranged into a two-dimensional sensor array. All of the magnetic field values
measured by the array are collected by a microcontroller, which pre-process and
send the data to a PDU (Processing and Display Unit) implemented on a
smartphone/tablets or a computer. An interpolation algorithm and display
software in the PDU present the field as a high-resolution video; hence, the
device works as a magnetic field camera. In the experiments, we employ the
camera to map the field distribution of distorted ambient magnetic field
induced by a hidden object. The obtained image of field shows both the position
and shape of the object. We also demonstrate the capability of the device to
image a loaded power-line cable carrying a 50~Hz alternating current.


  We study the crossover from the underdoped to the overdoped regime in the t-J
model.The underdoped regime is dominated by the superexchange interaction,
locking the spins into singlets which weakly perturbe coherent charge carriers.
In the overdoped, large carrier concentration regime, the Kondo effect
dominates resulting in spin-charge composite quasiparticles which are also
coherent. Separating these two Fermi liquid regimes, there is a critical doping
where superexchange and Kondo interaction balance each other, bringing the
system close to a local quantum critical point near the point of maximal
superconducting transition temperature. At this point, particle hole symmetry
is dynamically restored and physical quantities such as the optical
conductivity, exhibit power law behaviour at intermediate frequencies as
observed experimentally. Quantum criticality is avoided by the onset of
superconductivity.


  The Mamba layer offers an efficient selective state space model (SSM) that is
highly effective in modeling multiple domains, including NLP, long-range
sequence processing, and computer vision. Selective SSMs are viewed as dual
models, in which one trains in parallel on the entire sequence via an IO-aware
parallel scan, and deploys in an autoregressive manner. We add a third view and
show that such models can be viewed as attention-driven models. This new
perspective enables us to empirically and theoretically compare the underlying
mechanisms to that of the self-attention layers in transformers and allows us
to peer inside the inner workings of the Mamba model with explainability
methods. Our code is publicly available.


  Ultrafine particle behavior in electro-hydrodynamic (EHD) flow induced by
corona discharge is studied experimentally and numerically. The EHD flow serves
as a primary particle aspiration/sampling mechanism, the collector does not
require any additional flow generation. Multiphysics numerical model couples
the ion transport equation and the Navier-Stokes equations (NSE) to solve for
the spatiotemporal distribution of electric field, charge density, and flow
field, the results are compared with experimental velocity profiles at the
exit. The computed velocity and flow rate data are in good agreement with the
experimental data; the maximum velocity is located at the axis and ranges from
1 m/s to 4 m/s as a function of corona voltage. Experimentally evaluated
particle transmission trends for ambient and NaCl nanoparticles particles in
the 20 nm - 150 nm range are in good agreement with the theoretical models.
However, for particles in the 10 nm - 20 nm size range, the transmission is
lower due to the increased particle charging resulted from their exposure to
the high-intensity electric field and high charge density in the EHD driven
flow. These conditions yield a high probability of particles below 20 nm to
acquire and hold a unit charge. The transmission is lower for smaller particle
(10 nm) due to their high charge to mass ratio, and it increases as the
single-charged particles grow in mass up to 20 nm, resulting in their lower
electrical mobility. For particles larger than 20 nm, the electrical mobility
increases again as they can acquire multiple charges. The results shed insight
into interaction of nanoparticle and ions in high electrical field environment,
that occur in primary EHD driven flows and in the secondary flows generated by
corona discharge.


  The design of adaptive structures is one method to improve sustainability of
buildings. Adaptive structures are able to adapt to different loading and
environmental conditions or to changing requirements by either small or large
shape changes. In the latter case, also the mechanics and properties of the
deformation process play a role for the structure's energy efficiency. The
method of variational motion design, previously developed in the group of the
authors, allows to identify deformation paths between two given geometrical
configurations that are optimal with respect to a defined quality function. In
a preliminary, academic setting this method assumes that every single degree of
freedom is accessible to arbitrary external actuation forces that realize the
optimized motion. These (nodal) forces can be recovered a posteriori. The
present contribution deals with an extension of the method of motion design by
the constraint that the motion is to be realized by a predefined set of
actuation forces. These can be either external forces or prescribed length
chances of discrete, internal actuator elements. As an additional constraint,
static stability of each intermediate configuration during the motion is taken
into account. It can be accomplished by enforcing a positive determinant of the
stiffness matrix.


  We present a universal and rigorous approach to study difference frequency
generation in the terahertz domain, keeping the number of degrees of freedom to
a minimum, through the definition of a suitable figure of merit. The proposed
method relies on suitably normalized charts, that enable to predict the
optical-to-terahertz conversion efficiency of any system based on wave
propagation in quadratic nonlinear materials. The predictions of our approach
are found to be in good agreement with the best experimental results reported
to date, enabling also to estimate the d22 nonlinear coefficient of high
quality GaSe.


  In this note we have tried to determine how the existence of a local entropy
current with non-negative divergence constrains the second order transport
coefficients of an uncharged fluid, following the procedure described in
\cite{Romatschke:2009kr}. Just on symmetry ground the stress tensor of an
uncharged fluid can have 15 transport coefficients at second order in
derivative expansion. The condition of entropy-increase gives five relations
among these 15 coefficients. So finally the relativistic stress tensor of an
uncharged fluid can have 10 independent transport coefficients at second order.


  In this paper, we demonstrate the ability to discriminate between cultivated
maize plant and grass or grass-like weed image segments using the context
surrounding the image segments. While convolutional neural networks have
brought state of the art accuracies within object detection, errors arise when
objects in different classes share similar features. This scenario often occurs
when objects in images are viewed at too small of a scale to discern distinct
differences in features, causing images to be incorrectly classified or
localized. To solve this problem, we will explore using context when
classifying image segments. This technique involves feeding a convolutional
neural network a central square image along with a border of its direct
surroundings at train and test times. This means that although images are
labelled at a smaller scale to preserve accurate localization, the network
classifies the images and learns features that include the wider context. We
demonstrate the benefits of this context technique in the object detection task
through a case study of grass (foxtail) and grass-like (yellow nutsedge) weed
detection in maize fields. In this standard situation, adding context alone
nearly halved the error of the neural network from 7.1% to 4.3%. After only one
epoch with context, the network also achieved a higher accuracy than the
network without context did after 50 epochs. The benefits of using the context
technique are likely to particularly evident in agricultural contexts in which
parts (such as leaves) of several plants may appear similar when not taking
into account the context in which those parts appear.


  To establish the relationship between locomotory behavior and dynamics of
neural circuits in the nematode C. elegans we combined molecular and
theoretical approaches. In particular, we quantitatively analyzed the motion of
C. elegans with defective synaptic GABA and acetylcholine transmission,
defective muscle calcium signaling, and defective muscles and cuticle
structures, and compared the data with our systems level circuit model. The
major experimental findings are: (i) anterior-to-posterior gradients of body
bending flex for almost all strains both for forward and backward motion, and
for neuronal mutants, also analogous weak gradients of undulatory frequency,
(ii) existence of some form of neuromuscular (stretch receptor) feedback, (iii)
invariance of neuromuscular wavelength, (iv) biphasic dependence of frequency
on synaptic signaling, and (v) decrease of frequency with increase of the
muscle time constant. Based on (i) we hypothesize that the Central Pattern
Generator (CPG) is located in the head both for forward and backward motion.
Points (i) and (ii) are the starting assumptions for our theoretical model,
whose dynamical patterns are qualitatively insensitive to the details of the
CPG design if stretch receptor feedback is sufficiently strong and slow. The
model reveals that stretch receptor coupling in the body wall is critical for
generation of the neuromuscular wave. Our model agrees with our behavioral
data(iii), (iv), and (v), and with other pertinent published data, e.g., that
frequency is an increasing function of muscle gap-junction coupling.


  Recently, a hadronic state named $\eta_1(1855)$, about 1.86 GeV, was observed
in the BESIII experiment. This finding has a peculiar interest due to its
exotic quantum number $J^{PC}=1^{-+}$. In this paper, we examine the tetraquark
interpretation for the structure of $\eta_1(1855)$ in the configurations of
$[1_c]_{\bar{s}s}\otimes[1_c]_{\bar{q}q}$ and
$[1_c]_{\bar{s}q}\otimes[1_c]_{\bar{s}q}$, and perform a mass spectrum
calculation in the framework of QCD sum rules. The results show that the
observed $\eta_1(1855)$ could be embedded into the
$[1_c]_{\bar{s}s}\otimes[1_c]_{\bar{q}q}$ configuration. The possible
tetraquark and hybrid decay modes are analyzed, which are critical in decoding
its inner structure. In the same way, we evaluate as well the
$\bar{s}s\bar{s}s$ molecular state with $1^{-+}$ quantum number and find that
there might exist two such ground states.


  Motivated by the task of hyperparameter optimization, we introduce the
non-stochastic best-arm identification problem. Within the multi-armed bandit
literature, the cumulative regret objective enjoys algorithms and analyses for
both the non-stochastic and stochastic settings while to the best of our
knowledge, the best-arm identification framework has only been considered in
the stochastic setting. We introduce the non-stochastic setting under this
framework, identify a known algorithm that is well-suited for this setting, and
analyze its behavior. Next, by leveraging the iterative nature of standard
machine learning algorithms, we cast hyperparameter optimization as an instance
of non-stochastic best-arm identification, and empirically evaluate our
proposed algorithm on this task. Our empirical results show that, by allocating
more resources to promising hyperparameter settings, we typically achieve
comparable test accuracies an order of magnitude faster than baseline methods.


  We detect bright [CII]158$\mu$m line emission from the radio galaxy 3C 326N
at z=0.09, which shows weak star formation ($SFR<0.07$M$_{\odot}$~yr$^{-1}$)
despite having strong H$_2$ line emission and $2\times 10^9$M$_{\odot}$ of
molecular gas. The [CII] line is twice as strong as the 0-0S(1) 17$\mu$m H$_2$
line, and both lines are much in excess what is expected from UV heating. We
combine infrared Spitzer and Herschel data with gas and dust modeling to infer
the gas physical conditions. The [CII] line traces 30 to 50% of the molecular
gas mass, which is warm (70<T<100K) and at moderate densities
$700<n_{H}<3000$cm$^{-3}$. The [CII] line is broad with a blue-shifted wing,
and likely to be shaped by a combination of rotation, outflowing gas, and
turbulence. It matches the near-infrared H$_2$ and the Na D optical absorption
lines. If the wing is interpreted as an outflow, the mass loss rate would be
larger than 20M$_{\odot}$/yr, and the depletion timescale shorter than the
orbital timescale ($10^8$yr). These outflow rates may be over-estimated because
the stochastic injection of turbulence on galactic scales can contribute to the
skewness of the line profile and mimic outflowing gas. We argue that the
dissipation of turbulence is the main heating process of this gas. Cosmic rays
can also contribute to the heating but they require an average gas density
larger than the observational constraints. We show that strong turbulent
support maintains a high gas vertical scale height (0.3-4kpc) in the disk and
can inhibit the formation of gravitationally-bound structures at all scales,
offering a natural explanation for the weakness of star formation in 3C 326N.
To conclude, the bright [CII] line indicates that strong AGN jet-driven
turbulence may play a key role in enhancing the amount of molecular gas
(positive feedback) but yet can prevent star formation on galactic scales
(negative feedback).


  In this work, a novel approach for the construction and training of time
series models is presented that deals with the problem of learning on large
time series with non-equispaced observations, which at the same time may
possess features of interest that span multiple scales. The proposed method is
appropriate for constructing predictive models for non-stationary stochastic
time series.The efficacy of the method is demonstrated on a simulated
stochastic degradation dataset and on a real-world accelerated life testing
dataset for ball-bearings. The proposed method, which is based on GraphNets,
implicitly learns a model that describes the evolution of the system at the
level of a state-vector rather than of a raw observation. The proposed approach
is compared to a recurrent network with a temporal convolutional feature
extractor head (RNN-tCNN) which forms a known viable alternative for the
problem context considered. Finally, by taking advantage of recent advances in
the computation of reparametrization gradients for learning probability
distributions, a simple yet effective technique for representing prediction
uncertainty as a Gamma distribution over remaining useful life predictions is
employed.


  The Xuyi Schmidt Telescope Photometric Survey of the Galactic Anti-center
(XSTPS-GAC) is a photometric sky survey that covers nearly 6 000 deg^2 towards
Galactic anti-center in g r i bands. Half of its survey field locates on the
Galactic Anti-center disk, which makes XSTPS-GAC highly suitable for searching
new open clusters in the GAC region. In this paper, we report new open cluster
candidates discovered in this survey, as well as properties of these open
cluster candidates, such as age, distance and reddening, derived by isochrone
fitting in the color-magnitude diagram (CMD). These open cluster candidates are
stellar density peaks detected in the star density maps by applying the method
from Koposov et al. (2008). Each candidate is inspected on its true color image
composed from XSTPS-GAC three band images. Then its CMD is checked, in order to
identify whether the central region stars have a clear isochrone-like trend
differing from the background stars. The parameters derived from isochrone
fitting for these candidates are mainly based on three band photometry of
XSTPS-GAC. Meanwhile, when these new candidates are able to be seen clearly on
2MASS, their parameters are also derived based on 2MASS (J-H, J) CMD. Finally,
there are 320 known open clusters rediscovered and 24 new open cluster
candidates discovered in this work. Further more, the parameters of these new
candidates, as well as another 11 known recovered open clusters, are properly
determined for the first time.


  We quantify the importance of mass accretion during AGN phases in the growth
of supermassive black holes (BH) by comparing the mass function of black holes
in the local universe with that expected from AGN relics, which are black holes
grown entirely with mass accretion during AGN phases. The local BH mass
function (BHMF) is estimated by applying the well-known correlations between BH
mass, bulge luminosity and stellar velocity dispersion to galaxy luminosity and
velocity functions. The density of BH's in the local universe is 4.6 (-1.4;
+1.9) (h/0.7)^2 10^5 Msun Mpc^-3. The relic BHMF is derived from the continuity
equation with the only assumption that AGN activity is due to accretion onto
massive BH's and that merging is not important. We find that the relic BHMF at
z=0 is generated mainly at z<3. Moreover, the BH growth is anti-hierarchical in
the sense that smaller BH's (MBH< 10^7 Msun) grow at lower redshifts (z<1) with
respect to more massive one's (z~1-3). Unlike previous work, we find that the
BHMF of AGN relics is perfectly consistent with the local BHMF indicating the
local BH's were mainly grown during AGN activity. This agreement is obtained
while satisfying, at the same time, the constraints imposed from the X-ray
background. The comparison with the local BHMF also suggests that the merging
process is not important in shaping the relic BHMF, at least at low redshifts
(z<3). Our analysis thus suggests the following scenario: local black holes
grew during AGN phases in which accreting matter was converted into radiation
with efficiencies epsilon = 0.04-0.16 and emitted at a fraction lambda =
0.1-1.7 of the Eddington luminosity. The average total lifetime of these active
phases ranges from ~4.5 10^8 yr for MBH< 10^8 Msun to ~1.5 10^8 yr for MBH>
10^9 Msun. (abridged)


  In a differential approach elaborated, we study the evolution of the
parameters of Gaussian, mixed, continuous variable density matrices, whose
dynamics are given by Hermitian Hamiltonians expressed as quadratic forms of
the position and momentum operators or quadrature components. Specifically, we
obtain in generic form the differential equations for the covariance matrix,
the mean values, and the density matrix parameters of a multipartite Gaussian
state, unitarily evolving according to a Hamiltonian $\hat{H}$. We also present
the corresponding differential equations which describe the nonunitary
evolution of the subsystems. The resulting nonlinear equations are used to
solve the dynamics of the system instead of the Schr\"odinger equation. The
formalism elaborated allows us to define new specific invariant and
quasi-invariant states, as well as states with invariant covariance matrices,
i.e., states were only the mean values evolve according to the classical
Hamilton equations. By using density matrices in the position and in the
tomographic-probability representations, we study examples of these properties.
As examples, we present novel invariant states for the two-mode frequency
converter and quasi-invariant states for the bipartite parametric amplifier.


  We use S-duality and planarity to propose an argument for the
non-renormalization of the dispersion relation of giant magnon solutions in
type IIB string theory on AdS_5 x S^5. We compute the spectrum of giant magnons
for (p,q)-strings from field theory at strong coupling by using the central
charge properties of electrically and magnetically charged supersymmetric
states in the Coulomb branch of N=4 super Yang-Mills. We argue that the
coupling dependence of the giant magnon dispersion relation conjectured in the
literature using integrability assumptions is in fact the only functional
dependence compatible with S-duality.


  We consider a set system $(V, {\mathcal C}\subseteq 2^V)$ on a finite set $V$
of elements, where we call a set $C\in {\mathcal C}$ a component. We assume
that two oracles $\mathrm{L}_1$ and $\mathrm{L}_2$ are available, where given
two subsets $X,Y\subseteq V$, $\mathrm{L}_1$ returns a maximal component $C\in
{\mathcal C}$ with $X\subseteq C\subseteq Y$; and given a set $Y\subseteq V$,
$\mathrm{L}_2$ returns all maximal components $C\in {\mathcal C}$ with
$C\subseteq Y$. Given a set $I$ of attributes and a function $\sigma:V\to 2^I$
in a transitive system, a component $C\in {\mathcal C}$ is called a solution if
the set of common attributes in $C$ is inclusively maximal; i.e.,
$\bigcap_{v\in C}\sigma(v)\supsetneq \bigcap_{v\in X}\sigma(v)$ for any
component $X\in{\mathcal C}$ with $C\subsetneq X$. We prove that there exists
an algorithm of enumerating all solutions (or all components) in delay bounded
by a polynomial with respect to the input size and the running times of the
oracles.


  The total, orbital and spin moment of the Co2+ ion in CoO has been calculated
within the quasi-atomic approach with taking into account strong correlations,
crystal-field interactions and the intra-atomic spin-orbit coupling. The
orbital moment of 1.39 \mu B amounts at 0 K, in the magnetically-ordered state,
to more than 34% of the total moment (4.01 \mu B). The same calculations yield
for NiO the orbital and total moment of 0.46 \mu B and 2.45 \mu B,
respectively.
  PACS No: 71.70.E; 75.10.D
  Keywords: 3d magnetism, crystal field, spin-orbit coupling, orbital moment,
CoO, NiO


  A finite photonic lattice with two bands and a random gap is considered.
Using a two-dimensional Dirac equation, the effect of a random sign of the
Dirac mass is studied numerically. The edge state at the sample boundary has a
strong influence on the electromagnetic field and its polarization inside the
sample. The creation of edge states through a randomly fluctuating sign of the
Dirac mass defeats Anderson localization and allows the electromagnetic field
to distribute over the entire sample. The width of the distribution increases
with an increasing gap due to increasing sharpness of the edge states. These
results are compared with those of a random one-band Helmholtz equation. In
contrast to the Dirac model, the one-band model displays a clear signature of
Anderson localization.


  The duality between a $d$-dimensional conformal field theory with relevant
deformation and a gravity theory on an asymptotically AdS$_{d+1}$ geometry, has
become a suitable tool in the investigation of the emergence of gravity from
quantum entanglement in field theory. Recently, we have tested the duality
between the mass-deformed ABJM theory and asymptotically AdS$_4$ gravity
theory, which is obtained from the KK reduction of the 11-dimensional
supergravity on the LLM geometry. In this paper, we extend the KK reduction
procedure beyond the linear order and establish non-trivial KK maps between
4-dimensional fields and 11-dimensional fluctuations. We rely on this
gauge/gravity duality to calculate the entanglement entropy by using the
Ryu-Takayanagi holographic formula and the path integral method developed by
Faulkner. We show that the entanglement entropies obtained using these two
methods agree when the asymptotically AdS$_4$ metric satisfies the linearized
Einstein equation with nonvanishing energy-momentum tensor for two scalar
fields. These scalar fields encode the information of the relevant deformation
of the ABJM theory. This confirms that the asymptotic limit of LLM geometry is
the emergent gravity of the quantum entanglement in the mass-deformed ABJM
theory with a small mass parameter. We also comment on the issue of the
relative entropy and the Fisher information in our setup.


  We define the Hopf algebra structure on the Grothendieck group of
finite-dimensional polynomial representations of $U_q \hat{gl}_N$ in the limit
$N \to \infty$. The resulting Hopf algebra $Rep U_q \hat{gl}_\infty$ is a
tensor product of its Hopf subalgebras $Rep_a U_q \hat{gl}_\infty$,
$a\in\C^\times/q^{2\Z}$. When $q$ is generic (resp., $q^2$ is a primitive root
of unity of order $l$), we construct an isomorphism between the Hopf algebra
$Rep_a U_q \hat{gl}_\infty$ and the algebra of regular functions on the
prounipotent proalgebraic group $SL_\infty^-$ (resp., $\tilde{GL}_l^-$). When
$q$ is a root of unity, this isomorphism identifies the Hopf subalgebra of
$Rep_a U_q \hat{gl}_\infty$ spanned by the modules obtained by pullback with
respect to the Frobenius homomorphism with the algebra generated by the
coefficients of the determinant of an element of $\tilde{GL}_l^-$. This gives
us an explicit formula for the Frobenius pullbacks of the fundamental
representations. In addition, we construct a natural action of the Hall algebra
associated to the infinite linear quiver (resp., the cyclic quiver with $l$
vertices) on $Rep_a U_q \hat{gl}_infty$ and describe the span of the tensor
products of the evaluation representations taken at fixed points as a module
over this Hall algebra.


  Despite of various similar features, Functional Data Analysis and
High-Dimensional Data Analysis are two major fields in Statistics that grew up
recently almost independently one from each other. The aim of this paper is to
propose a survey on methodological advances for variable selection in
functional regression, which is typically a question for which both functional
and multivariate ideas are crossing. More than a simple survey, this paper aims
to promote even more new links between both areas.


  The celebrated Mackey-Glass model describes the dynamics of physiological
\textit{delayed} systems in which the actual evolution depends on the values of
the variables at some \textit{previous} times. This kind of systems are usually
expressed by delayed differential equations which turn out to be
infinite-dimensional. In this contribution, an electronic implementation
mimicking the Mackey-Glass model is proposed. New approaches for both the
nonlinear function and the delay block are made. Explicit equations for the
actual evolution of the implementation are derived. Simulations of the original
equation, the circuit equation, and experimental data show great concordance.


  Video Question Answering (VidQA) exhibits remarkable potential in
facilitating advanced machine reasoning capabilities within the domains of
Intelligent Traffic Monitoring and Intelligent Transportation Systems.
Nevertheless, the integration of urban traffic scene knowledge into VidQA
systems has received limited attention in previous research endeavors. In this
work, we present a novel approach termed Traffic-domain Video Question
Answering with Automatic Captioning (TRIVIA), which serves as a
weak-supervision technique for infusing traffic-domain knowledge into large
video-language models. Empirical findings obtained from the SUTD-TrafficQA task
highlight the substantial enhancements achieved by TRIVIA, elevating the
accuracy of representative video-language models by a remarkable 6.5 points
(19.88%) compared to baseline settings. This pioneering methodology holds great
promise for driving advancements in the field, inspiring researchers and
practitioners alike to unlock the full potential of emerging video-language
models in traffic-related applications.


  We formulate the generalized tunneling model for two level systems in
insulators that takes into account the interaction between them and a slow
power law dependence of their density of states. We show that the predictions
of this model are in a perfect agreement with the recent studies of the noise
in high quality superconducting resonators. The predictions also agree with the
temperature dependence of the TLS dephasing rates observed in phase qubits.
Both observations are impossible to explain in the framework of the standard
tunneling model of TLS. We discuss the origin of the universal dimensionless
parameter that controls the interaction between TLS in glasses and show that it
is consistent with the assumptions of the model.


  High-spin states in the odd-odd nucleus $^{168}$Ta have been populated in the
$^{120}$Sn($^{51}$V,3n) reaction. Two multi-quasiparticle structures have been
extended significantly from spin $\sim{20\hbar}$ to above ${40\hbar}$. As a
result, the first rotational alignment has been fully delineated and a second
band crossing has been observed for the first time in this nucleus.
Configurations for these strongly-coupled rotational bands are proposed based
on signature splitting, $B(M1)/B(E2)$ ratio information, and observed
rotation-alignment behavior. Properties of the observed bands in $^{168}$Ta are
compared to related structures in the neighboring odd-$Z$, odd-$N$, and odd-odd
nuclei and are discussed within the framework of the cranked shell model.


  Using recent results on higher order cumulants of conserved charge
fluctuations from lattice QCD, we construct mean, variance, skewness, kurtosis,
hyper-skewness and hyper-kurtosis of net-baryon number distributions for small
baryon chemical potentials $\mu_B$. For the strangeness neutral case
($\mu_S=0$) at fixed ratio of electric charge to baryon number density
($\frac{n_Q}{n_B}=0.4$), which is appropriate for a comparison with heavy ion
collisions, we present results for $\kappa_B \sigma_B^2$, $S_B \sigma_B^3/M_B$,
$\kappa^{H}_{B}\sigma_{B}^4$ and $S^{H}_{B}\sigma^5_{B}/M_{B}$ on the crossover
line for the chiral transition, $T_{pc}(\mu_B)$. Continuum extrapolations for
this pseudo-critical transition line have recently been reported by HotQCD up
to baryon chemical potentials $\mu_B\simeq 300$ MeV [arXiv:1812.08235]. These
cumulant ratios are of direct relevance for comparisons with corresponding
ratios measured by STAR in the BES-I and II runs at beam energies
$\sqrt{s_{NN}}\ge 20$ GeV. In particular, we point out that recent high
statistics results on skewness and kurtosis of net-baryon number distributions
obtained by STAR at $\sqrt{s_{NN}} = 54.4$ GeV put strong constraints on
freeze-out parameters and are consistent with predictions from thermal QCD.


  We present the next generation of MobileNets based on a combination of
complementary search techniques as well as a novel architecture design.
MobileNetV3 is tuned to mobile phone CPUs through a combination of
hardware-aware network architecture search (NAS) complemented by the NetAdapt
algorithm and then subsequently improved through novel architecture advances.
This paper starts the exploration of how automated search algorithms and
network design can work together to harness complementary approaches improving
the overall state of the art. Through this process we create two new MobileNet
models for release: MobileNetV3-Large and MobileNetV3-Small which are targeted
for high and low resource use cases. These models are then adapted and applied
to the tasks of object detection and semantic segmentation. For the task of
semantic segmentation (or any dense pixel prediction), we propose a new
efficient segmentation decoder Lite Reduced Atrous Spatial Pyramid Pooling
(LR-ASPP). We achieve new state of the art results for mobile classification,
detection and segmentation. MobileNetV3-Large is 3.2\% more accurate on
ImageNet classification while reducing latency by 15\% compared to MobileNetV2.
MobileNetV3-Small is 4.6\% more accurate while reducing latency by 5\% compared
to MobileNetV2. MobileNetV3-Large detection is 25\% faster at roughly the same
accuracy as MobileNetV2 on COCO detection. MobileNetV3-Large LR-ASPP is 30\%
faster than MobileNetV2 R-ASPP at similar accuracy for Cityscapes segmentation.


  We consider QED on a two-dimensional Euclidean torus with $f$ flavors of
massless fermions and flavor-dependent chemical potentials. The dependence of
the partition function on the chemical potentials is reduced to a
$(2f-2)$-dimensional theta function. At zero temperature, the system can exist
in an infinite number of phases characterized by certain values of traceless
number densities and separated by first-order phase transitions. Furthermore,
there exist many points in the $(f-1)$-dimensional space of traceless chemical
potentials where two or three phases can coexist for $f=3$ and two, three, four
or six phases can coexist for $f=4$. We conjecture that the maximal number of
coexisting phases grows exponentially with increasing $f$.


  The increasing amount of data exchange requires higher-capacity optical
communication links. Mode division multiplexing (MDM) is considered as a
promising technology to support the higher data throughput. In an MDM system,
the mode generator and sorter are the backbone. However, most of the current
schemes lack the programmability and universality, which makes the MDM link
susceptible to the mode crosstalk and environmental disturbances. In this
paper, we propose an intelligent multimode optical communication link using
universal mode processing (generation and sorting) chips. The mode processor
consists of a programmable 4*4 Mach Zehnder interferometer (MZI) network and
can be intelligently configured to generate or sort both quasi linearly
polarized (LP) modes and orbital angular momentum (OAM) modes in any desired
routing state. We experimentally establish a chip-to-chip MDM communication
system. The mode basis can be freely switched between four LP modes and four
OAM modes. We also demonstrate the multimode optical communication capability
at a data rate of 25 Gbit/s. The proposed scheme shows significant advantages
in terms of universality, intelligence, programmability and resistance to mode
crosstalk, environmental disturbances and fabrication errors, demonstrating
that the MZI-based reconfigurable mode processor chip has great potential in
long-distance chip-to-chip multimode optical communication systems.


  In this paper, we propose a method to build a sequence of generalized
empirical principal curves, with selected length, so that, in Hausdor distance,
the images of the estimating principal curves converge in probability to the
image of g.


  In Theorem 1 of Acta Arith. 99 (2001), 321-329, Cobeli and Zaharescu give a
result about the distribution of the ${\bf F}_p$-points on an affine curve. An
easy corollary to their theorem is that the set $\bigcup_p \lbrace
(\frac{x_1}{p}, ...,\frac{x_n}{p}), 1 \leq x_i < p \text{and} \prod_{1 \leq i
\leq n} x_i \equiv 1 \bmod{p} \rbrace$ is dense in $[ 0,1 ]^n$. In Integers 7
(2007), A7, Foo gives a elementary proof of that fact in dimension $2$.
Following Foo's ideas, we give a similar proof in dimension greater than or
equal to $3$.


  The momentum distribution for the $\eta'$ meson produced through the
inclusive decay $B\to \eta'X$ is investigated under two decay mechanisms,
$b\to\eta's$ and $b\to \eta' s g$. Although all these two mechanisms can
explain the recently observed decay rate of $B\to \eta'X$, the momentum
spectrums for $\eta'$ meson predicted by them are strongly different. Thus
detailed experiment is proposed to distinguish the two cases.


  Simulation studies allow us to explore the properties of statistical methods.
They provide a powerful tool with a multiplicity of aims; among others:
evaluating and comparing new or existing statistical methods, assessing
violations of modelling assumptions, helping with the understanding of
statistical concepts, and supporting the design of clinical trials. The
increased availability of powerful computational tools and usable software has
contributed to the rise of simulation studies in the current literature.
However, simulation studies involve increasingly complex designs, making it
difficult to provide all relevant results clearly. Dissemination of results
plays a focal role in simulation studies: it can drive applied analysts to use
methods that have been shown to perform well in their settings, guide
researchers to develop new methods in a promising direction, and provide
insights into less established methods. It is crucial that we can digest
relevant results of simulation studies. Therefore, we developed INTEREST: an
INteractive Tool for Exploring REsults from Simulation sTudies. The tool has
been developed using the Shiny framework in R and is available as a web app or
as a standalone package. It requires uploading a tidy format dataset with the
results of a simulation study in R, Stata, SAS, SPSS, or comma-separated
format. A variety of performance measures are estimated automatically along
with Monte Carlo standard errors; results and performance summaries are
displayed both in tabular and graphical fashion, with a wide variety of
available plots. Consequently, the reader can focus on simulation parameters
and estimands of most interest. In conclusion, INTEREST can facilitate the
investigation of results from simulation studies and supplement the reporting
of results, allowing researchers to share detailed results from their
simulations and readers to explore them freely.


  We study the magnetic-field-induced breakdown of superconductivity in
nm-scale metal grains having a mean electron level spacing $d \simeq
\tilde\Delta$ (bulk gap). Using a generalized variational BCS approach that
yields good qualitative agreement with measured spectra, we argue that Pauli
paramagnetism dominates orbital diamagnetism, as in the case of thin films in a
parallel magnetic field. However, the first-order transition observed for the
latter can be made continuous by finite size effects. The mean-field procedure
of describing the system by a single pairing parameter $\Delta$ breaks down for
$d \simeq \tilde\Delta$.


  Coagulation of particles occurs when two particles collide and stick
together. In the Martian atmosphere, dust coagulation would increase the
effective particle size, as small particles accrete to larger particles. Murphy
et al. (1990) showed that Brownian coagulation of dust in the Martian
atmosphere was not significant, due to the low dust particle mixing ratios,
while Montmessin et al. (2002) and Fedorova et al. (2014) showed that it mostly
involves particle radii smaller than 0.1 um. However, the effects of
coagulation have never been explored in 3D, during a global dust storm, i.e. in
presence of larger numbers of small particles. Here we revisit this issue by
using the NASA Ames Mars Global Climate Model (MGCM) to investigate the
temporal and spatial changes in dust particle sizes during the 2018 global
storm due to coagulation and the overall impact of these processes on Mars'
climate. Our parameterization for coagulation includes the effect of Brownian
motion, Brownian diffusion enhancement, and gravitational collection. We show
that Brownian motion and Brownian diffusion enhancement dominate gravitational
collection. The impact of coagulation is significant during the storm, with
coagulation rates increased by a factor of 10 compared to non-storm conditions.
The effective particle radius can be increased by a factor of 2 due to
coagulation, leading to a 20K colder atmosphere above 30 km altitude. Overall,
our parameterization improves the representation of the decay phase of the
storm relative to observations. The process remains significant outside the
storm period if large numbers of submicron-sized particles are involved. It may
be possible, in GCMs, to lift larger amounts of submicron-sized particles from
the surface without excess dust buildup in the atmosphere, thus improving the
agreement with some of the observations without diverging from the observed
column opacities.


  Auscher, McIntosh and Tchamitchian studied the heat kernels of second order
elliptic operators in divergence form with complex bounded measurable
coefficients on $\mathbb{R}^n$. In particular, in the case when $n=2$ they
obtained Gaussian upper bound estimates for the heat kernel without imposing
further assumption on the coefficients. We study the fundamental solutions of
the systems of second order parabolic equations in the divergence form with
bounded, measurable, time-independent coefficients, and extend their results to
the systems of parabolic equations.


  In this paper, we propose a novel graph kernel method for the wireless link
scheduling problem in device-to-device (D2D) networks on Riemannian manifold.
The link scheduling problem can be considered as a binary classification
problem since each D2D pair can only hold the state active or inactive. Our
goal is to learn a novel metric that facilitates the design of an efficient but
less computationally demanding machine learning (ML) solution for the binary
classification task of link scheduling problem that requires no channel state
information (CSI) and a fewer number of training samples as opposed to other
benchmark ML algorithms. To this aim, we first represent the wireless D2D
network as a graph and model the features of each D2D pair, including its
communication and interference links, as regularized (i.e., positively-shifted)
Laplacian matrices which are symmetric positive definite (SPD) one. By doing
so, we represent the feature information of each D2D pair as a point on the SPD
manifold, and we analyze the topology through Riemannian geometry. We compute
the Riemannian metric, e.g., Log-Euclidean metric (LEM), which are suitable
distance measures between the regularized Laplacian matrices. The LEM is then
utilized to define a positive definite graph kernel for the binary
classification of the link scheduling decisions. Simulation results demonstrate
that the proposed graph Kernel-based method is computationally less demanding
and achieves a sum rate of more than 95% of benchmark algorithm FPLinQ [1] for
10 D2D pairs without using CSI and less than a hundred training network
layouts.


  In the present paper, degeneration phenomena in conformal field theories are
studied. For this purpose, a notion of convergent sequences of CFTs is
introduced. Properties of the resulting limit structure are used to associate
geometric degenerations to degenerating sequences of CFTs, which, as familiar
from large volume limits of non-linear sigma models, can be regarded as
commutative degenerations of the corresponding ``quantum geometries''.
  As an application, the large level limit of the A-series of unitary Virasoro
minimal models is investigated in detail. In particular, its geometric
interpretation is determined.


  This paper addresses efficient hardware/software implementation approaches
for the AES (Advanced Encryption Standard) algorithm and describes the design
and performance testing algorithm for embedded system. Also, with the spread of
reconfigurable hardware such as FPGAs (Field Programmable Gate Array) embedded
cryptographic hardware became cost-effective. Nevertheless, it is worthy to
note that nowadays, even hardwired cryptographic algorithms are not so safe.
  From another side, the self-reconfiguring platform is reported that enables
an FPGA to dynamically reconfigure itself under the control of an embedded
microprocessor. Hardware acceleration significantly increases the performance
of embedded systems built on programmable logic. Allowing a FPGA-based
MicroBlaze processor to self-select the coprocessors uses can help reduce area
requirements and increase a system's versatility. The architecture proposed in
this paper is an optimal hardware implementation algorithm and takes dynamic
partially reconfigurable of FPGA. This implementation is good solution to
preserve confidentiality and accessibility to the information in the numeric
communication.


  Josephson plasma excitations in the high $T_c$ superconductor
Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$ have been investigated in a wide microwave
frequency region (9.8 -- 75 GHz), in particular, in magnetic field applied
parallel to the $ab$ plane of the single crystal. In sharp contrast to the case
for magnetic fields parallel to the c axis or tilted from the $ab$ plane, it
was found that there are two kinds of resonance modes, which are split in
energy and possess two distinctly different magnetic field dependences. One
always lies higher in energy than the other and has a shallow minimum at about
0.8 kOe, then increases linearly with magnetic field. On the other hand,
another mode begins to appear only in a magnetic field (from a few kOe and
higher) and has a weakly decreasing tendency with increasing magnetic field. By
comparing with a recent theoretical model the higher energy mode can naturally
be attributed to the Josephson plasma resonance mode propagating along the
primitive reciprocal lattice vector of the Josephson vortex lattice, whereas
the lower frequency mode is assigned to the novel phase collective mode of the
Josephson vortex lattice, which has never been observed before.


  We show that coupling the Standard Model to a Lorentz symmetry violating
sector may co-exist with viable phenomenology, provided that the interaction
between the two is mediated by higher-dimensional operators. In particular, if
the new sector acquires anisotropic scaling behavior above a "Horava-Lifshitz"
energy scale L_HL and couples to the Standard Model through interactions
suppressed by M_P, the transmission of the Lorentz violation into the Standard
Model is protected by the ratio L_HL^2/M_P^2. A wide scale separation,
L_HL<<M_P, can then make Lorentz-violating terms in the Standard Model sector
within experimental bounds without fine-tuning. We first illustrate our point
with a toy example of Lifshitz-type neutral fermion coupled to photon via the
magnetic moment operator, and then implement similar proposal for the
Ho\v{r}ava-Lifshitz gravity coupled to conventional Lorentz-symmetric matter
fields. We find that most radiatively induced Lorentz violation can be
controlled by a large scale separation, but the existence of instantaneously
propagating non-Lifshitz modes in gravity can cause a certain class of diagrams
to remain quadratically divergent above L_HL. Such problematic quadratic
divergence, however, can be removed by extending the action with terms of
higher Lifshitz dimension, resulting in a completely consistent setup that can
cope with the stringent tests of Lorentz invariance.


  Ecosystem services are the direct and indirect contributions of an ecosystem
to human well-being and survival. Ecosystem valuation is a method of assigning
a monetary value to an ecosystem with its goods and services,often referred to
as ecosystem service value (ESV). With the rapid expansion of cities, a
mismatch occurs between urban development and ecological development, and it is
increasingly urgent to establish a valid ecological assessment method. In this
study, we propose an ecological evaluation standard framework by designing an
ESV monitoring workflow based on the establishment of multi-level grids. The
proposed method is able to capture multi-scale features, facilitates
multi-level spatial expression, and can effectively reveal the spatial
heterogeneity of ESV. Taking Haian city in the Jiangsu province as the study
case, we implemented the proposed dynamic multi-level grids-based (DMLG) to
calculate its urban ESV in 2016 and 2019. We found that the ESV of Haian city
showed considerable growth (increased by 24.54 million RMB). Negative ESVs are
concentrated in the central city, which presented a rapid trend of outward
expansion. The results illustrated that the ongoing urban expanse does not
reduce the ecological value in the study area. The proposed unified grid
framework can be applied to other geographical regions and is expected to
benefit future studies in ecosystem service evaluation in terms of capture
multi-level spatial heterogeneity.


  In this paper we study the production of entanglement between two atoms which
are far from each other. We consider a system including eight two-level atoms
(1; 2;... ; 8) such that any atom with its adjacent atom is in atomic Bell
state, so that we have four separate pairs of maximally entangled states (i; i
+ 1) where i = 1; 3; 5; 7. Our purpose is to produce entanglement between the
atomic pair (1, 8), while these two distant atoms have no interaction. By
performing the interaction between adjacent nonentangled atomic pairs (2, 3) as
well as (6, 7), each pair with a two-mode quantized field, the entanglement is
produced between atoms (1, 4) and (5, 8), respectively. Finally, by applying an
appropriate Bell state measurement (BSM) on atoms (4, 5) or performing an
interaction between them with a single-mode field (quantum electrodynamic: QED
method), the qubit pair (1; 8) becomes entangled and so the quantum repeater is
successfully achieved. This swapped entanglement is then quantified via
concurrence measure and the effects of coupling coeficients and detuning on the
concurrence and success probability are numerically investigated. The maxima of
concurrence and success probability and the corresponding time periods have
been decreased by increasing the detuning in asymmetric condition in BSM
method. Also, the effects of detuning, initial interaction time and coupling
coeficient on the produced entanglement by QED method are considered.
Increasing (decreasing) of the detuning (interaction time) has destructive
effect on the swapped entanglement in asymmetric condition.


  The continuous inflow of bug reports is a considerable challenge in large
development projects. Inspired by contemporary work on mining software
repositories, we designed a prototype bug assignment solution based on machine
learning in 2011-2016. The prototype evolved into an internal Ericsson product,
TRR, in 2017-2018. TRR's first bug assignment without human intervention
happened in April 2019. Our study evaluates the adoption of TRR within its
industrial context at Ericsson. Moreover, we investigate 1) how TRR performs in
the field, 2) what value TRR provides to Ericsson, and 3) how TRR has
influenced the ways of working. We conduct an industrial case study combining
interviews with TRR stakeholders, minutes from sprint planning meetings, and
bug tracking data. The data analysis includes thematic analysis, descriptive
statistics, and Bayesian causal analysis. TRR is now an incorporated part of
the bug assignment process. Considering the abstraction levels of the
telecommunications stack, high-level modules are more positive while low-level
modules experienced some drawbacks. On average, TRR automatically assigns 30%
of the incoming bug reports with an accuracy of 75%. Auto-routed TRs are
resolved around 21% faster within Ericsson, and TRR has saved highly seasoned
engineers many hours of work. Indirect effects of adopting TRR include process
improvements, process awareness, increased communication, and higher job
satisfaction. TRR has saved time at Ericsson, but the adoption of automated bug
assignment was more intricate compared to similar endeavors reported from other
companies. We primarily attribute the difference to the very large size of the
organization and the complex products. Key facilitators in the successful
adoption include a gradual introduction, product champions, and careful
stakeholder analysis.


  In this paper, we calculate the size of a massive neutrino in the following
approach. We perform our calculation using its mass, spin, and magnetic moment
through the neutrino-electron interaction, $via$ the classical magnetic
dipole-dipole interaction. Thus, our estimate is obtained by mimicking the
low-energy electroweak scattering process $\nu_l$-$l^{\prime}$. This leads to
surprisingly accurate result which differs in less than one order of magnitude
of more detailed calculations with one-loop corrections based on the neutrino
charge radius and the $\nu_l$-$l^{\prime}$ scattering process. The resulting
estimates are flavour-blind and gauge independent by construction. We also find
that our lower bound is below the reported experimental upper bound on the
electron neutrino charged radius. So we obtained a constraining range for the
neutrino size.


  Finding the existence and the location of the QCD critical point is one of
the main goals of the RHIC beam energy scan program. To make theoretical
predictions and corroborate with the experimental data requires modeling the
space-time evolution of the matter created in heavy-ion collisions by dynamical
models such as the relativistic hydrodynamics with an appropriate Equation of
State (EoS). In the present exploratory study, we use a viscous 2+1 dimensional
event-by-event (e-by-e) hydrodynamic code at finite baryon densities with two
different EoSs (i) Lattice QCD + HRG with a crossover transition and (ii) EoS
with a first-order phase transition to studying the normalized symmetric
cumulants of charged pions $v_n$ $(n=2-4)$. We show that the normalized
symmetric cumulants can differentiate the two EoSs while all other conditions
remain the same. The conclusion does not change for various initial conditions
and shear viscosity. This indicates that these observables can be used to gain
information about the QCD EoS from experimental data and can be used as an EoS
meter.


  We revisit the anomalous chromomagnetic dipole moment in the Standard Model
and show that its triple gluon vertex contribution, with the on-shell gluon
($q^2=0$), generates an infrared divergent pole. Consequently, the
chromomagnetic dipole should not be perturbatively evaluated at $q^2=0$.
Focusing on this top quark anomaly, denoted as $\hat{\mu}_t(q^2)$, we compute
it with the off-shell gluon with a large momentum transfer, just as the
$\alpha_s(m_Z^2)$ convention scale, for both spacelike $q^2=-m_Z^2$ and
timelike $q^2=m_Z^2$ cases. We found that $\hat{\mu}_t(-m_Z^2)$ $=$ $-0.0224$
$-0.000925i$ and $\hat{\mu}_t(m_Z^2)$ $=$ $-0.0133$ $-0.0267i$. Our
$\mathrm{Re}\thinspace\hat{\mu}_t(-m_Z^2)$ matches well with the current
experimental value
$\hat{\mu}_t^\mathrm{Exp}=-0.024_{-0.009}^{+0.013}(\mathrm{stat})_{-0.011}^{+0.016}(\mathrm{syst})$,
and the $\mathrm{Im}\thinspace\hat{\mu}_t(-m_Z^2)$ part is induced by flavour
changing charged currents.


  Nonlinear Compton scattering is calculated for the collision of an electron
with a plane wave pulse. A mid infra-red (IR) peak arises in the photon
spectrum due to long-range interference associated with the pulse envelope. The
case of a flat-top pulse is studied as a toy model for pulse envelope effects
and reduced to two final-state momentum integrations; the case of a
sine-squared pulse is studied numerically. A perturbative expansion in
charge-field coupling reveals that already at intermediate intensities, many
orders are required to correctly capture the structure of the mid-IR peak. By
regularising the classical result, it is shown that the mid-IR peak is due to
plane-wave ponderomotive effects on the pulse envelope. Finally, it is shown
that the mid-IR peak can be isolated using energy, angle and polarisation
filters.


  We compute the variation of the Fokker-Wheeler-Feynman total linear and
angular momentum of a gravitationally interacting binary system under the
second post-Minkowskian retarded dynamics. The resulting $O(G^2)$
equations-of-motion-based, total change in the system's angular momentum is
found to agree with existing computations that assumed balance with angular
momentum fluxes in the radiation zone.


  Humans display a tendency to pay more attention to bad outcomes, often in a
disproportionate way relative to their statistical occurrence. They also
display euphorism, as well as a preference for the current state of affairs
(status quo bias). Based on the analysis of optimal solutions of infinite
horizon stationary optimization problems under imperfect state observation, we
show that such human perception and decision biases can be grounded in a form
of rationality. We also provide conditions (boundaries) for their possible
occurence and an analysis of their robustness.Thus, biases can be the product
of rational behavior.


  The diamond norm measures the distance between two quantum channels. From an
operational vewpoint, this norm measures how well we can distinguish between
two channels by applying them to input states of arbitrarily large dimensions.
In this paper, we show that the diamond norm can be conveniently and in a
physically transparent way computed by means of a Monte-Carlo algorithm based
on the Fano representation of quantum states and quantum operations. The
effectiveness of this algorithm is illustrated for several single-qubit quantum
channels.


  Corpus preparation for low-resource languages and for development of human
language technology to analyze or computationally process them is a laborious
task, primarily due to the unavailability of expert linguists who are native
speakers of these languages and also due to the time and resources required.
Bhojpuri, Magahi, and Maithili, languages of the Purvanchal region of India (in
the north-eastern parts), are low-resource languages belonging to the
Indo-Aryan (or Indic) family. They are closely related to Hindi, which is a
relatively high-resource language, which is why we compare with Hindi. We
collected corpora for these three languages from various sources and cleaned
them to the extent possible, without changing the data in them. The text
belongs to different domains and genres. We calculated some basic statistical
measures for these corpora at character, word, syllable, and morpheme levels.
These corpora were also annotated with parts-of-speech (POS) and chunk tags.
The basic statistical measures were both absolute and relative and were
exptected to indicate of linguistic properties such as morphological, lexical,
phonological, and syntactic complexities (or richness). The results were
compared with a standard Hindi corpus. For most of the measures, we tried to
the corpus size the same across the languages to avoid the effect of corpus
size, but in some cases it turned out that using the full corpus was better,
even if sizes were very different. Although the results are not very clear, we
try to draw some conclusions about the languages and the corpora. For POS
tagging and chunking, the BIS tagset was used to manually annotate the data.
The POS tagged data sizes are 16067, 14669 and 12310 sentences, respectively,
for Bhojpuri, Magahi and Maithili. The sizes for chunking are 9695 and 1954
sentences for Bhojpuri and Maithili, respectively.


  We consider the problem of learning useful robotic skills from previously
collected offline data without access to manually specified rewards or
additional online exploration, a setting that is becoming increasingly
important for scaling robot learning by reusing past robotic data. In
particular, we propose the objective of learning a functional understanding of
the environment by learning to reach any goal state in a given dataset. We
employ goal-conditioned Q-learning with hindsight relabeling and develop
several techniques that enable training in a particularly challenging offline
setting. We find that our method can operate on high-dimensional camera images
and learn a variety of skills on real robots that generalize to previously
unseen scenes and objects. We also show that our method can learn to reach
long-horizon goals across multiple episodes through goal chaining, and learn
rich representations that can help with downstream tasks through pre-training
or auxiliary objectives. The videos of our experiments can be found at
https://actionable-models.github.io


  We investigate the low-temperature thermodynamics of the unitary Fermi gas by
introducing a model based on the zero-temperature spectra of both bosonic
collective modes and fermonic single-particle excitations. We calculate the
Helmholtz free energy and from it we obtain the entropy, the internal energy
and the chemical potential as a function of the temperature. By using these
quantities and the Landau's expression for the superfluid density we determine
analytically the superfluid fraction, the critical temperature, the first sound
velocity and the second sound velocity. We compare our analytical results with
other theoretical predictions and experimental data of ultracold atoms and
dilute neutron matter.


  Abundancy index refers to the ratio of the sum of the divisors of a number to
the number itself. It is a concept of great importance in defining friendly and
perfect numbers. Here, we describe a suitable generalization of abundancy index
to the ring of Gaussian integers ($\mathbb{Z}[i]$). We first show that this
generalization possesses many of the useful properties of the traditional
abundancy index in $\mathbb{Z}$. We then investigate $k$-powerful
$\tau$-perfect numbers and prove results regarding their existence in
$\mathbb{Z}[i]$.


  An open quantum system consists of leads connected to a device of interest.
Within the nonequilibrium Green's function technique, we examine the
replacement of leads by self-energies in continuum calculations. Our starting
point is a formulation of the problem for continuum systems by T.E. Feuchtwang.
In this approach there is considerable flexibility in the choice of unperturbed
Green's functions. We examine the consequences of this freedom on the treatment
of leads. For any choice the leads can be replaced by coupling self-energies
which are simple functions of energy. We find that the retarded self-energy
depends on the details of the choice of unperturbed Green's function, and can
take any value. However, the nonequilibrum self-energy or scattering function
can be taken to be independent of this choice. Expressed in terms of these
self-energies, nonequilibrium transport calculations take a particularly simple
form.


  Reinforcement learning from human feedback (RLHF) is a recent technique to
improve the quality of the text generated by a language model, making it closer
to what humans would generate. A core ingredient in RLHF's success in aligning
and improving large language models (LLMs) is its reward model, trained using
human feedback on model outputs. In machine translation (MT), where metrics
trained from human annotations can readily be used as reward models, recent
methods using minimum Bayes risk decoding and reranking have succeeded in
improving the final quality of translation. In this study, we comprehensively
explore and compare techniques for integrating quality metrics as reward models
into the MT pipeline. This includes using the reward model for data filtering,
during the training phase through RL, and at inference time by employing
reranking techniques, and we assess the effects of combining these in a unified
approach. Our experimental results, conducted across multiple translation
tasks, underscore the crucial role of effective data filtering, based on
estimated quality, in harnessing the full potential of RL in enhancing MT
quality. Furthermore, our findings demonstrate the effectiveness of combining
RL training with reranking techniques, showcasing substantial improvements in
translation quality.


  We propose an improved version of the color evaporation model to describe
heavy quarkonium production. In contrast to the traditional color evaporation
model, we impose the constraint that the invariant mass of the intermediate
heavy quark-antiquark pair to be larger than the mass of produced quarkonium.
We also introduce a momentum shift between heavy quark-antiquark pair and the
quarkonium. Numerical calculations show that our model can describe the
charmonium yields as well as ratio of $\psi^\prime$ over $J/\psi$ better than
the traditional color evaporation model.


  We study the focusing stochastic nonlinear Schr\"odinger equation in 1D in
the $L^2$-critical and supercritical cases with an additive or multiplicative
perturbation driven by space-time white noise. Unlike the deterministic case,
the Hamiltonian (or energy) is not conserved in the stochastic setting, nor is
the mass (or the $L^2$-norm) conserved in the additive case. Therefore, we
investigate the time evolution of these quantities. After that we study the
influence of noise on the global behavior of solutions. In particular, we show
that the noise may induce blow-up, thus, ceasing the global existence of the
solution, which otherwise would be global in the deterministic setting.
Furthermore, we study the effect of the noise on the blow-up dynamics in both
multiplicative and additive noise settings and obtain profiles and rates of the
blow-up solutions. Our findings conclude that the blow-up parameters (rate and
profile) are insensitive to the type or strength of the noise: if blow-up
happens, it has the same dynamics as in the deterministic setting, however,
there is a (random) shift of the blow-up center, which can be described as a
random variable normally distributed.


  In the recent paper entitled "Explicit constructions of MDS self-dual codes"
accepted in { IEEE Transactions on Information Theory}, doi:
10.1109/TIT.2019.2954877, the author has constructed families of MDS self-dual
codes from genus zero algebraic geometry (AG) codes, where the AG codes of
length $n$ were defined using two divisors $G$ and $D=P_1+\cdots+P_n.$ In the
present correspondence, we explore more families of optimal self-dual codes
from AG codes. New families of MDS self-dual codes with odd characteristics and
those of almost MDS self-dual codes are constructed explicitly from genus zero
and genus one curves, respectively. More families of self-dual codes are
constructed from algebraic curves of higher genus.


  2-Dim quantum Poincare` Group E_q(1,1) at roots of unity, its dual
U_q(e(1,1)) and some of its homogeneous spaces are introduced. Invariant
integrals on E_q(1,1) and its invariant discrete subgroup E(1,1\mid p) are
constructed. *-Representations of the quantum algebra U_q(e(1,1)) constructed
in the homogeneous space SO(1,1\mid p) are integrated to the pseudo-unitary
representations of E_q(1,1) by means of the universal T-matrix. U_q(e(1,1)) is
realized on the quantum plane E_q^{(1,1)} and the eigenfunctions of the
complete set of observables are obtained in the angular momentum and momentum
basis. The matrix elements of the pseudo-unitary irreducible representations
are given in terms of the cut off q-exponential and q-Bessel functions whose
properties we also investigate.


  We explore the renormalization group (RG) properties of quantum gravity,
using the vielbein and the spin connection as the fundamental field variables.
We require the effective action to be invariant under the semidirect product of
spacetime diffeomorphisms and local frame rotations. Starting from the
corresponding functional integral we review the construction of an appropriate
theory space and an exact funtional RG equation operating on it. We then solve
this equation on a truncated space defined by a three parameter family of
Holst-type actions which involve a running Immirzi parameter. We find evidence
for the existence of an asymptotically safe fundamental theory. It is probably
inequivalent to metric quantum gravity constructed in the same way.


  This paper examines the export promotion of processed foods by a regional
economy and regional vitalisation policy. We employ Bertrand models that
contain a major home producer and a home producer in a local area. In our
model, growth in the profit of one producer does not result in an increase in
the profit of the other, despite strategic complements. We show that the profit
of the producer in the local area decreases because of the deterioration of a
location condition, and its profit increases through the reinforcement of the
administrative guidance. Furthermore, when the inefficiency of the location
worsens, the local government should optimally decrease the level of
administrative guidance. Hence, the local government should strategically
eliminate this inefficiency to maintain a sufficient effect of administrative
guidance.


  Deep representation learning on non-Euclidean data types, such as graphs, has
gained significant attention in recent years. Invent of graph neural networks
has improved the state-of-the-art for both node and the entire graph
representation in a vector space. However, for the entire graph representation,
most of the existing graph neural networks are trained on a graph
classification loss in a supervised way. But obtaining labels of a large number
of graphs is expensive for real world applications. Thus, we aim to propose an
unsupervised graph neural network to generate a vector representation of an
entire graph in this paper. For this purpose, we combine the idea of
hierarchical graph neural networks and mutual information maximization into a
single framework. We also propose and use the concept of periphery
representation of a graph and show its usefulness in the proposed algorithm
which is referred as GraPHmax. We conduct thorough experiments on several
real-world graph datasets and compare the performance of GraPHmax with a
diverse set of both supervised and unsupervised baseline algorithms.
Experimental results show that we are able to improve the state-of-the-art for
multiple graph level tasks on several real-world datasets, while remain
competitive on the others.


  We study a quantum information engine (QIE) modeled by a multi-qubit working
medium (WM) collectively coupled to a single thermal bath. We show that one can
harness the collective effects to significantly enhance the performance of the
QIE, as compared to equivalent engines lacking collective effects. We use one
bit of information about the WM magnetization to extract work from the thermal
bath. We analyze the work output, noise-to-signal ratio and thermodynamic
uncertainty relation, and contrast these performance metrics of a collective
QIE with that of an engine whose WM qubits are coupled independently to a
thermal bath. We show that in the limit of high temperatures of the thermal
bath, a collective QIE always outperforms its independent counterpart. In
contrast to quantum heat engines, where collective enhancement in specific heat
plays a direct role in improving the performance of the engines, here the
collective advantage stems from higher occupation probabilities for the higher
energy levels of the positive magnetization states, as compared to the
independent case.


  A systematic study of isotope chains in the rare--earth region is presented.
For the chains (144-154)Nd, (146-160)Sm, (148-162)Gd, and (150-166)Dy, energy
levels, E2 transition rates, and two--neutron separation energies are described
by using the most general (up to two--body terms) IBM Hamiltonian. For each
isotope chain a general fit is performed in such a way that all parameters but
one are kept fixed to describe the whole chain. In this region nuclei evolve
from spherical to deformed shapes and a method based on catastrophe theory, in
combination with a coherent state analysis to generate the IBM energy surfaces,
is used to identify critical phase transition points.


  The Traveling Salesperson problem asks for the shortest cyclic tour visiting
a set of cities given their pairwise distances and belongs to the NP-hard
complexity class, which means that with all known algorithms in the worst case
instances are not solveable in polynomial time, i.e., the problem is hard.
Though that does not mean, that there are not subsets of the problem which are
easy to solve. To examine numerically transitions from an easy to a hard phase,
a random ensemble of cities in the Euclidean plane given a parameter {\sigma},
which governs the hardness, is introduced. Here, a linear programming approach
together with suitable cutting planes is applied. Such algorithms operate
outside the space of feasible solutions and are often used in practical
application but rarely studied in physics so far. We observe several
transitions. To characterize these transitions, scaling assumptions from
continuous phase transitions are applied


  We present a systematic study of gas density perturbations in cool cores of
high-mass galaxy clusters. We select 12 relaxed clusters from the Cluster
Lensing And Supernova survey with Hubble (CLASH) sample and analyze their cool
core features observed with the Chandra X-ray Observatory. We focus on the
X-ray residual image characteristics after subtracting their global profile of
the X-ray surface brightness distribution. We find that all the galaxy clusters
in our sample have, at least, both one positive and one negative excess regions
in the X-ray residual image, indicating the presence of gas density
perturbations. We identify and characterize the locally perturbed regions using
our detection algorithm, and extract X-ray spectra of the intracluster medium
(ICM). The ICM temperature in the positive excess region is lower than that in
the negative excess region, whereas the ICM in both regions is in pressure
equilibrium in a systematic manner. These results indicate that gas sloshing in
cool cores takes place in more than 80% of relaxed clusters (95% CL). We
confirm this physical picture by analyzing synthetic X-ray observations of a
cool-core cluster from a hydrodynamic simulation, finding that our detection
algorithm can accurately extract both the positive and negative excess regions
and can reproduce the temperature difference between them. Our findings support
the picture that the gas density perturbations are induced by gas sloshing, and
a large fraction of cool-core clusters have undergone gas sloshing, indicating
that gas sloshing may be capable of suppressing runaway cooling of the ICM.