  This paper analyses the behaviour of a second order DPCM (Differential Pulse
Code Modulation) transmission system when the nonlinear characteristic of the
quantizer is taken into consideration. In this way, qualitatively new
properties of the DPCM system have been unravelled, which cannot be observed
and explained if the nonlinearity of the quantizer is neglected. For the
purposes of this study, a piece-wise linear nondifferentiable quantizer
characteristic is considered. The resulting model of the DPCM is of the form of
iteration equations (i.e. map), where the inverse iterate is not unique (i.e.
noninvertible map). Therefore the mathematical theory of noninvertible maps is
particularly suitable for this analysis, together with the more classic tools
of Non Linear Dynamics. This study allowed us in addition to show from a
theoretical point of view some new properties of nondifferentiable maps, in
comparison with differentiable ones. After a short review of noninvertible
maps, the presented methods and tools for noninvertible maps are applied to the
DPCM system. An original algorithm for calculation of bifurcation curves for
the DPCM map is proposed. Via the studies in the parameter and phase plane,
different nonlinear phenomena such as the overlapping of bifurcation curves
causing multistability, chaotic behaviour, or multiple basins with fractal
boundary are pointed out. All observed phenomena show a very complex dynamical
behaviour even in the constant input signal case, discussed here.


  We analyze the position and momentum uncertainties of the energy eigenstates
of the harmonic oscillator in the context of a deformed quantum mechanics,
namely, that in which the commutator between the position and momentum
operators is given by [x,p]=i\hbar(1+\beta p^2). This deformed commutation
relation leads to the minimal length uncertainty relation \Delta x >
(\hbar/2)(1/\Delta p +\beta\Delta p), which implies that \Delta x ~ 1/\Delta p
at small \Delta p while \Delta x ~ \Delta p at large \Delta p. We find that the
uncertainties of the energy eigenstates of the normal harmonic oscillator
(m>0), derived in Ref. [1], only populate the \Delta x ~ 1/\Delta p branch. The
other branch, \Delta x ~ \Delta p, is found to be populated by the energy
eigenstates of the `inverted' harmonic oscillator (m<0). The Hilbert space in
the 'inverted' case admits an infinite ladder of positive energy eigenstates
provided that \Delta x_{min} = \hbar\sqrt{\beta} > \sqrt{2}
[\hbar^2/k|m|]^{1/4}. Correspondence with the classical limit is also
discussed.


  A deep neural network for classification tasks is essentially consist of two
components: feature extractors and function approximators. They usually work as
an integrated whole, however, improvements on any components can promote the
performance of the whole algorithm. This paper focus on designing a new
function approximator. Conventionally, to build a function approximator, one
usually uses the method based on the nonlinear activation function or the
nonlinear kernel function and yields classical networks such as the
feed-forward neural network (MLP) and the radial basis function network (RBF).
In this paper, a new function approximator that is effective and efficient is
proposed. Instead of designing new activation functions or kernel functions,
the new proposed network uses the fractional form. For the sake of convenience,
we name the network the ratio net. We compare the effectiveness and efficiency
of the ratio net and that of the RBF and the MLP with various kinds of
activation functions in the classification task on the mnist database of
handwritten digits and the Internet Movie Database (IMDb) which is a binary
sentiment analysis dataset. It shows that, in most cases, the ratio net
converges faster and outperforms both the MLP and the RBF.


  Completing Loo-Keng Hua's approach to the real number system pioneered in
1962, this paper defines arithmetical operations directly on infinite decimals
without appealing to any ordering structure. Therefore, the widespread belief
that there exists an algorithm for determining the digits of the product of two
real numbers in terms of finite pieces of their decimal strings is essentially
confirmed.


  For a two-variable formula ψ(X,Y) of Monadic Logic of Order (MLO) the
Church Synthesis Problem concerns the existence and construction of an operator
Y=F(X) such that ψ(X,F(X)) is universally valid over Nat.
  B\"{u}chi and Landweber proved that the Church synthesis problem is
decidable; moreover, they showed that if there is an operator F that solves the
Church Synthesis Problem, then it can also be solved by an operator defined by
a finite state automaton or equivalently by an MLO formula. We investigate a
parameterized version of the Church synthesis problem. In this version ψ
might contain as a parameter a unary predicate P. We show that the Church
synthesis problem for P is computable if and only if the monadic theory of
<Nat,<,P> is decidable. We prove that the B\"{u}chi-Landweber theorem can be
extended only to ultimately periodic parameters. However, the MLO-definability
part of the B\"{u}chi-Landweber theorem holds for the parameterized version of
the Church synthesis problem.


  The exponential Papapetrou metric induced by scalar field conforms to
observational data not worse than the vacuum Schwarzschild solution. Here, we
analyze the origin of this metric as a peculiar space-time within a wide class
of scalar and antiscalar solutions of the Einstein equations parameterized by
scalar charge. Generalizing the three families of static solutions obtained by
Fisher (1948), Janis, Newman & Winicour (1968), and Xanthopoulos & Zannias
(1989), we prove that all three reduce to the same exponential metric provided
that scalar charge is equal to central mass, thereby suggesting the universal
character of such background scalar field.


  A spherically symmetric hydrodynamic stellar core collapse under gravity is
time-dependent and may become unstable once disturbed. Specifically for a
homologously collapse of stellar core characterized by a polytropic exponent
\Gamma=4/3, we examine oscillations and/or instabilities of three dimensional
(3D) general polytropic perturbations. For compressible 3D perturbations, the
polytropic index \gamma of perturbations can differ from \Gamma=4/3 of the
general polytropic hydrodynamic background flow. Our model formulation here is
more general and allows the existence of internal gravity g(-)-modes and/or
g(+)-modes. Eigenvalues and eigen-functions of various oscillatory and unstable
perturbation modes are computed. As studied in several specialized cases of
Goldreich & Weber and of Cao & Lou, we further confirm that acoustic p-modes
and surface f-modes remain stable in the current more general situations. In
comparison, g(-)-modes and sufficiently high radial order g(+)-modes are
unstable, leading to inevitable convective motions within the collapsing
stellar interior. Unstable growths of 3D g-mode disturbances are governed
dominantly by the angular momentum conservation and modified by the gas
pressure restoring force. We note in particular that unstable temporal growths
of 3D vortical perturbations exist even when the specific entropy distribution
becomes uniform and \gamma=\Gamma=4/3. Conceptually, unstable g-modes might
bear conceivable physical consequences on supernova explosions, the initial
kicks of nascent proto-neutron stars (PNSs) and break-ups of the collapsing
core, while unstable growths of vortical perturbations can lead to fast spins
of compact objects and other relevant results.


  We classify all linear division sequences in the integers, a problem going
back to at least the 1930s. As a corollary we also classify those linear
recurrence sequences in the integers for which $(x_m,x_n)=\pm x_{(m,n)}$. We
also show that if two linear division sequences have a large common factor
infinitely often then they are each divisible by a common linear division
sequence on some arithmetic progression. Moreover our proofs also work for
polynomials. The key to our proofs are Ritt's irreducibility theorem and the
subspace theorem (of Schmidt and Schlickewei), in a direction developed by
Bugeaud, Corvaja and Zannier.


  Certain quantum codes allow logic operations to be performed on the encoded
data, such that a multitude of errors introduced by faulty gates can be
corrected. An important class of such operations are {\em transversal}, acting
bitwise between corresponding qubits in each code block, thus allowing error
propagation to be carefully limited. If any quantum operation could be
implemented using a set of such gates, the set would be {\em universal}; codes
with such a universal, transversal gate set have been widely desired for
efficient fault-tolerant quantum computation. We study the structure of
GF(4)-additive quantum codes and prove that no universal set of transversal
logic operations exists for these codes. This result strongly supports the idea
that additional primitive operations, based for example on quantum
teleportation, are necessary to achieve universal fault-tolerant computation on
additive codes.


  Recently, deep neural networks (DNNs) have made great progress on automated
diagnosis with chest X-rays images. However, DNNs are vulnerable to adversarial
examples, which may cause misdiagnoses to patients when applying the DNN based
methods in disease detection. Recently, there is few comprehensive studies
exploring the influence of attack and defense methods on disease detection,
especially for the multi-label classification problem. In this paper, we aim to
review various adversarial attack and defense methods on chest X-rays. First,
the motivations and the mathematical representations of attack and defense
methods are introduced in details. Second, we evaluate the influence of several
state-of-the-art attack and defense methods for common thorax disease
classification in chest X-rays. We found that the attack and defense methods
have poor performance with excessive iterations and large perturbations. To
address this, we propose a new defense method that is robust to different
degrees of perturbations. This study could provide new insights into
methodological development for the community.


  The theory of stellar evolution can be more closely tested if we have the
opportunity to measure new quantities. Nowadays, observations of galactic RR
Lyr stars are available on a time baseline exceeding 100 years. Therefore, we
can exploit the possibility of investigating period changes, continuing the
pioneering work started by V. P. Tsesevich in 1969. We collected the available
times of maximum brightness of the galactic RR Lyr stars in the GEOS RR Lyr
database. Moreover, we also started new observational projects, including
surveys with automated telescopes, to characterise the O-C diagrams better. The
database we built has proved to be a very powerful tool for tracing the period
variations through the ages. We analyzed 123 stars showing a clear O-C pattern
(constant, parabolic or erratic) by means of different least-squares methods.
Clear evidence of period increases or decreases at constant rates has been
found, suggesting evolutionary effects. The median values are beta=+0.14
day/Myr for the 27 stars showing a period increase and beta=-0.20 day/Myr for
the 21 stars showing a period decrease. The large number of RR Lyr stars
showing a period decrease (i.e., blueward evolution) is a new and intriguing
result. There is an excess of RR Lyr stars showing large, positive $\beta$
values. Moreover, the observed beta values are slightly larger than those
predicted by theoretical models.


  In this paper, we demonstrate a new data-driven framework for real-time
neutral density estimation via model-data fusion in quasi-physical
ionosphere-thermosphere models. The framework has two main components: (i) the
development of a quasi-physical dynamic reduced order model (ROM) that uses a
linear approximation of the underlying dynamics and effect of the drivers, and
(ii) dynamic calibration of the ROM through estimation of the ROM coefficients
that represent the model parameters. We have previously demonstrated the
development of a quasi-physical ROM using simulation output from a physical
model and assimilation of non-operational density estimates derived from
accelerometer measurements along a single orbit. In this paper, we demonstrate
the potential of the framework for use with operational measurements. We use
simulated GPS-derived orbit ephemerides with 5 minute resolution as
measurements. The framework is a first of its kind, simple yet robust and
accurate method with high potential for providing real-time operational updates
to the state of the upper atmosphere using quasi-physical models with inherent
forecasting/predictive capabilities.


  Mannheim partner curves are studied by Liu and Wang [1,2]. Orbay and others
extended the theory of the Mannheim curves to the ruled surface in Euclidean
3-space[3]. We obtain the relationships between the curvatures and the torsions
of the dual Mannheim partner curves with respect to each other.


  We propose a type system to analyze the time consumed by multi-threaded
imperative programs with a shared global memory, which delineates a class of
safe multi-threaded programs. We demonstrate that a safe multi-threaded program
runs in polynomial time if (i) it is strongly terminating wrt a
non-deterministic scheduling policy or (ii) it terminates wrt a deterministic
and quiet scheduling policy. As a consequence, we also characterize the set of
polynomial time functions. The type system presented is based on the
fundamental notion of data tiering, which is central in implicit computational
complexity. It regulates the information flow in a computation. This aspect is
interesting in that the type system bears a resemblance to typed based
information flow analysis and notions of non-interference. As far as we know,
this is the first characterization by a type system of polynomial time
multi-threaded programs.


  A digital finite impulse response (FIR) filter design is fully synthesizable,
thanks to the mature CAD support of digital circuitry. On the contrary, analog
mixed-signal (AMS) filter design is mostly a manual process, including
architecture selection, schematic design, and layout. This work presents a
systematic design methodology to automate AMS FIR filter design using a time
approximation architecture without any tunable passive component, such as
switched capacitor or resistor. It not only enhances the flexibility of the
filter but also facilitates design automation with reduced analog complexity.
The proposed design flow features a hybrid approximation scheme that
automatically optimize the filter's impulse response in light of time
quantization effects, which shows significant performance improvement with
minimum designer's efforts in the loop. Additionally, a layout-aware regression
model based on an artificial neural network (ANN), in combination with
gradient-based search algorithm, is used to automate and expedite the filter
design. With the proposed framework, we demonstrate rapid synthesis of AMS FIR
filters in 65nm process from specification to layout.


  We consider the enumeration of states in the Brubaker-Bump-Friedberg
six-vertex model, whose boundary conditions are determined by an integer
partition. In general, we find the number of states is a polynomial in the
largest part of the partition. By explicating this technique, we also enumerate
the states completely for hook shapes and staircases.


  We report hot-wire measurements performed in two very different, co- and
counter-rotating flows, in normal and superfluid helium at 1.6 K, 2 K, and 2.3
K. As recently reported, the power spectrum of the hot-wire signal in
superfluid flows exhibits a significant bump at high frequency (Diribarne et
al. [1]). We confirm that the bump frequency does not depend significantly on
the temperature and further extend the previous analysis of the velocity
dependence of the bump, over more than one decade of velocity. The main result
is that the bump frequency depends on the turbulence intensity of the flow, and
that using the turbulent Reynolds number rather than the velocity as a control
parameter collapses results from both co- and counter-rotating flows. The
vortex shedding model previously proposed, in its current form, does not
account for this observation. This suggests that the physical origin of the
bump is related to the small scale turbulence properties of the flow. We
finally propose some qualitative physical mechanism by which the smallest
structures of the flow, at intervortex distance, could affect the heat flux of
the hot-wire.


  In this paper, we consider a system model in conjunction with two major
technologies in 5G communications, i.e., mobile edge computing and spectrum
sharing. An IoT network, which does not have access to any licensed spectrum,
carries its computational task offloading activities with help of spectrum
sharing. The IoT network cooperates with a licensed spectrum holding network by
relaying its data and in return gets access to the licensed spectrum. The
licensed spectrum holding network focuses on throughput maximization, whereas,
the IoT network tries to maximize task computation rate. We formulate an
optimization problem giving importance to both networks' interests. Typical IoT
nodes may be energy-constrained, which is considered along with task
computation time constraints. Parallel computation is considered while
computing IoT nodes' computational tasks at the mobile edge computing server,
where the processor is allocated based on IoT nodes' offloading capabilities.
The advantage of such processor allocation is shown in the result section.
Moreover, we also show how both IoT and licensed spectrum holding networks
benefit from the spectrum sharing by caring for each other requirements, which
echoes the fact, i.e., Sharing is Caring.


  We study SPDEs with two reflecting walls $\Lambda^1$, $\Lambda^2$ and two
singular drifts $\frac{c_1}{(X-\Lambda^1)^{\vartheta}}$,
$\frac{c_2}{(\Lambda^2-X)^{\vartheta}}$, driven by space-time white noise.
First, we establish the existence and uniqueness of the solutions $X$ for
$\vartheta\geq 0$. Second, we obtain the following pathwise properties of the
solutions $X$. If $\vartheta>3$, then a.s. $\Lambda^1<X<\Lambda^2$ for all
$t\geq0$; If $0<\vartheta<3$, then $X$ hits $\Lambda^1$ or $\Lambda^2$ with
positive probability in finite time. Thus $\vartheta=3$ is the critical
parameter for $X$ to hit reflecting walls.


  Automatic ICD coding is defined as assigning disease codes to electronic
medical records (EMRs). Existing methods usually apply label attention with
code representations to match related text snippets. Unlike these works that
model the label with the code hierarchy or description, we argue that the code
synonyms can provide more comprehensive knowledge based on the observation that
the code expressions in EMRs vary from their descriptions in ICD. By aligning
codes to concepts in UMLS, we collect synonyms of every code. Then, we propose
a multiple synonyms matching network to leverage synonyms for better code
representation learning, and finally help the code classification. Experiments
on the MIMIC-III dataset show that our proposed method outperforms previous
state-of-the-art methods.


  We introduce JointNet, a novel neural network architecture for modeling the
joint distribution of images and an additional dense modality (e.g., depth
maps). JointNet is extended from a pre-trained text-to-image diffusion model,
where a copy of the original network is created for the new dense modality
branch and is densely connected with the RGB branch. The RGB branch is locked
during network fine-tuning, which enables efficient learning of the new
modality distribution while maintaining the strong generalization ability of
the large-scale pre-trained diffusion model. We demonstrate the effectiveness
of JointNet by using RGBD diffusion as an example and through extensive
experiments, showcasing its applicability in a variety of applications,
including joint RGBD generation, dense depth prediction, depth-conditioned
image generation, and coherent tile-based 3D panorama generation.


  We build an SU(2)-Hopf bundle over a quantum toric four-sphere whose radius
is non central. The construction is carried out using local methods in terms of
sheaves of Hopf-Galois extensions. The associated instanton bundle is presented
and endowed with a connection with anti-selfdual curvature.


  By developing a new technique called the bi-coupling argument, we estimate
the relative entropy between different diffusion processes in terms of the
distances of initial distributions and drift-diffusion coefficients. As an
application, the entropy-cost inequality is established for nonlinear
Fokker-Planck equations, which has potential applications in optimal transport,
information theory and mean field particle systems.


  The advent of Neural-network Quantum States (NQS) has significantly advanced
wave function ansatz research, sparking a resurgence in orbital space
variational Monte Carlo (VMC) exploration. This work introduces three
algorithmic enhancements to reduce computational demands of VMC optimization
using NQS: an adaptive learning rate algorithm, constrained optimization, and
block optimization. We evaluate the refined algorithm on complex multireference
bond stretches of $\rm H_2O$ and $\rm N_2$ within the cc-pVDZ basis set and
calculate the ground-state energy of the strongly correlated chromium dimer
($\rm Cr_2$) in the Ahlrichs SV basis set. Our results achieve superior
accuracy compared to coupled cluster theory at a relatively modest CPU cost.
This work demonstrates how to enhance optimization efficiency and robustness
using these strategies, opening a new path to optimize large-scale Restricted
Boltzmann Machine (RBM)-based NQS more effectively and marking a substantial
advancement in NQS's practical quantum chemistry applications.


  We report on experimental results in a new regime of a relativistic
light-matter interaction employing mid-infrared (3.9-micrometer wavelength)
high-intensity femtosecond laser pulses. In the laser generated plasma, the
electrons reach relativistic energies already at rather low intensities due to
the fortunate lambda^2-scaling of the kinetic energy with the laser wavelength.
The lower intensity suppresses optical field ionization and creation of the
pre-plasma at the rising edge of the laser pulse efficiently, enabling an
enhanced efficient vacuum heating of the plasma. The lower critical plasma
density for long-wavelength radiation can be surmounted by using nanowires
instead of flat targets. In our experiments about 80% of the incident laser
energy has been absorbed resulting in a long living, keV-temperature,
high-charge state plasma with a density of more than three orders of magnitude
above the critical value. Our results pave the way to laser-driven experiments
on laboratory astrophysics and nuclear physics at a high repetition rate.


  CV/ITS (Connected Vehicle, Intelligent Transportation System) and AV/ADS
(Autonomous Vehicle, Automated Driving System) have been emerging for the sake
of saving people lives, improving traffic efficiency and helping the
environment for decades. There are separate efforts led respectively by USDOT
with state DOTs for CV, and private sectors through market driven approach from
start-ups and technology companies for AV. By CV/ITS effort there are 97
deployments of V2X communications utilizing the 5.9 GHz band, 18,877 vehicles
with aftermarket V2X communications devices, and 8,098 infrastructure V2X
devices installed at the roadsides. However, CV/ITS still cannot be massively
deployed in US markets due to lack of regulations, dedicated wireless spectrum
bands, sustainable financial & business models with mature supply chain, etc.
In the other side, technology-driven AV market has been much slower than
expected mainly because of immaturity of AI technology to handle different
complex driving scenarios in a cost effective way. In this paper, we first
present these two parallel journeys focusing on the deployments including
operating models, scenarios and applications, evaluations and lessons learning.
Then, come up with recommendations to a cooperative CAV approach driving a more
feasible, safer, affordable and cost effective transportation, but require a
great industry collaboration from Automotive, Transportation. ICT and Cloud.


  We study the interfacial thermal conductance of grain boundaries (GBs)
between monolayer graphene and hexagonal boron nitride (h-BN) sheets using a
combined atomistic approach. First, realistic samples containing graphene/h-BN
GBs with different tilt angles are generated using the phase-field crystal
(PFC) model developed recently [P. Hirvonen \textit{et al.}, Phys. Rev. B
\textbf{100}, 165412 (2019)] that captures slow diffusive relaxation
inaccessible to molecular dynamics (MD) simulations. Then, large-scale MD
simulations using the efficient GPUMD package are performed to assess heat
transport and rectification properties across the GBs. We find that lattice
mismatch between the graphene and h-BN sheets plays a less important role in
determining the interfacial thermal conductance as compared to the tilt angle.
In addition, we find no significant thermal rectification effects for these
GBs.


  We report the detection of 21-cm absorption from foreground galaxies towards
quasars, specifically z_gal = 0.3120 towards SDSS J084957.97+510829.0 (z_qso =
0.584; Pair-I) and z_gal = 0.3714 towards SDSS J144304.53+021419.3 (z_qso =
1.82; Pair-II). In both the cases, the integrated 21-cm optical depth is
consistent with the absorbing gas being a damped Lyman-\alpha (DLA) system. In
the case of Pair-I, strong Na I and Ca II absorption are also detected at z_gal
in the QSO spectrum. We identify an early-type galaxy at an impact parameter of
b ~ 14 kpc whose photometric redshift is consistent with that of the detected
metal and 21-cm absorption lines. This would be the first example of an
early-type galaxy associated with an intervening 21-cm absorber. The gas
detected in 21-cm and metal absorption lines in the outskirts of this luminous
red galaxy could be associated with the reservoir of cold H I gas with a low
level of star formation activity in the outer regions of the galaxy as reported
in the literature for z ~ 0.1 early-type galaxies. In the case of Pair-II, the
absorption is associated with a low surface brightness galaxy that, unlike most
other known quasar-galaxy pairs (QGPs) i.e. QSO sight lines passing through
disks/halos of foreground galaxies, is identified only via narrow optical
emission lines detected on top of the QSO spectra. Using SDSS spectra we infer
that the emission lines originate within ~ 5 kpc of the QSO sight line, and the
gas has metallicity [12+O/H] ~ 8.4 and star formation rate ~ 0.7-0.8 M_sun per
yr. The measured 21-cm optical depth can be reconciled with the N(H I) we
derive from the measured extinction (A_V=0.6) if either the H I gas is warm or
the extinction per hydrogen atom in this galaxy is much higher than the mean
value of the Small Magellanic Cloud. (Abridged)


  Signatures of soft supersymmetry breaking at the CERN LHC and in dark matter
experiments are discussed with focus drawn to light superparticles, and in
particular light gauginos and their discovery prospects. Connected to the above
is the recent PAMELA positron anomaly and its implications for signatures of
SUSY in early runs at the Large Hadron Collider. Other new possibilities for
physics beyond the Standard Model are also briefly discussed.


  An experimental method is developed for the robust frequency stabilization
using a high-finesse cavity when the laser exhibits large intermittent
frequency jumps. This is accomplished by applying an additional slow feedback
signal from Doppler-free fluorescence spectroscopy in an atomic beam with
increased frequency locking range. As a result, a stable and narrow-linewidth
556 nm laser maintains the frequency lock status for more than a week, and
contributes to more accurate evaluation of the Yb optical lattice clock. In
addition, the reference optical cavity is supported at vibration-insensitive
points without any vibration isolation table, making the laser setup more
simple and compact.


  We speed up existing decoding algorithms for three code classes in different
metrics: interleaved Gabidulin codes in the rank metric, lifted interleaved
Gabidulin codes in the subspace metric, and linearized Reed-Solomon codes in
the sum-rank metric. The speed-ups are achieved by new algorithms that reduce
the cores of the underlying computational problems of the decoders to one
common tool: computing left and right approximant bases of matrices over skew
polynomial rings. To accomplish this, we describe a skew-analogue of the
existing PM-Basis algorithm for matrices over ordinary polynomials. This
captures the bulk of the work in multiplication of skew polynomials, and the
complexity benefit comes from existing algorithms performing this faster than
in classical quadratic complexity. The new algorithms for the various
decoding-related computational problems are interesting in their own and have
further applications, in particular parts of decoders of several other codes
and foundational problems related to the remainder-evaluation of skew
polynomials.


  We discuss the extraction of the electromagnetic and spin polarisabilities of
nucleons from lattice QCD. We show that the external field method can be used
to measure all the electromagnetic and spin polarisabilities including those of
charged particles. We then turn to the extrapolations required to connect such
calculations to experiment in the context of finite volume chiral perturbation
theory. We derive results relevant for lattice simulations of QCD,
partially-quenched QCD and quenched QCD. Our results for the polarisabilities
show a strong dependence on the lattice volume and quark masses, typically
differing from the infinite volume limit by ~10% for current lattice volumes
and quark masses.


  We compare the performances of the templates defined by three different types
of approaches: traditional post-Newtonian templates (Taylor-approximants),
``resummed'' post-Newtonian templates assuming the adiabatic approximation and
stopping before the plunge (P-approximants), and further ``resummed''
post-Newtonian templates going beyond the adiabatic approximation and
incorporating the plunge with its transition from the inspiral
(Effective-one-body approximants). The signal to noise ratio is significantly
enhanced (mainly because of the inclusion of the plunge signal) by using these
new effective-one-body templates relative to the usual post-Newtonian ones for
binary masses greater than $ 30 M_\odot$, the most likely sources for initial
laser interferometers. Independently of the question of the plunge signal, the
comparison of the various templates confirms the usefulness of using
resummation methods. The paper also summarizes the key elements of the
construction of various templates and thus can serve as a resource for those
involved in writing inspiral search software.


  Precision medicine aims to create biomedical solutions tailored to specific
factors that affect disease risk and treatment responses within the population.
The success of the genomics era and recent widespread availability of
electronic health records (EHR) has ushered in a new wave of genomic biobanks
connected to EHR databases (EHR-linked biobanks). This perspective aims to
discuss how race, ethnicity, and genetic ancestry are currently utilized to
study common disease variation through genetic association studies. Although
genetic ancestry plays a significant role in shaping the genetic landscape
underlying disease risk in humans, the overall risk of a disease is caused by a
complex combination of environmental, sociocultural, and genetic factors. When
using EHR-linked biobanks to interrogate underlying disease etiology, it is
also important to be aware of how the biases associated with commonly used
descent-associated concepts such as race and ethnicity can propagate to
downstream analyses. We intend for this resource to support researchers who
perform or analyze genetic association studies in the EHR-linked biobank
setting such as those involved in consortium-wide biobanking efforts. We
provide background on how race, ethnicity, and genetic ancestry play a role in
current association studies, highlight considerations where there is no
consensus about best practices, and provide transparency about the current
shortcomings.


  We consider the well-posedness of a model for a flow-structure interaction.
This model describes the dynamics of an elastic flexible plate with clamped
boundary conditions immersed in a supersonic flow. A perturbed wave equation
describes the flow potential. The plate's out-of-plane displacement can be
modeled by various nonlinear plate equations (including von Karman and Berger).
We show that the linearized model is well-posed on the state space (as given by
finite energy considerations) and generates a strongly continuous semigroup. We
make use of these results to conclude global-in-time well-posedness for the
fully nonlinear model.
  The proof of generation has two novel features, namely: (1) we introduce a
new flow potential velocity-type variable which makes it possible to cover both
subsonic and supersonic cases, and to split the dynamics generating operator
into a skew-adjoint component and a perturbation acting outside of the state
space. Performing semigroup analysis also requires a nontrivial approximation
of the domain of the generator. And (2) we make critical use of hidden
regularity for the flow component of the model (in the abstract setup for the
semigroup problem) which allows us run a fixed point argument and eventually
conclude well-posedness. This well-posedness result for supersonic flows (in
the absence of rotational inertia) has been hereto open. The use of semigroup
methods to obtain well-posedness opens this model to long-time behavior
considerations.


  In recent years, deep learning has made remarkable strides, surpassing human
capabilities in tasks like strategy games, and it has found applications in
complex domains, including protein folding. In the realm of quantum chemistry,
machine learning methods have primarily served as predictive tools or design
aids using generative models, while reinforcement learning remains in its early
stages of exploration. This work introduces an actor-critic reinforcement
learning framework suitable for diverse optimization tasks, such as searching
for molecular structures with specific properties within conformational spaces.
As an example, we show an implementation of this scheme for calculating minimum
energy pathways of a Claisen rearrangement reaction and a number of SN2
reactions. Our results show that the algorithm is able to accurately predict
minimum energy pathways and thus, transition states, therefore providing the
first steps in using actor-critic methods to study chemical reactions.


  The appearance of linear spaces, describing physical quantities by vectors
and tensors, is ubiquitous in all of physics, from classical mechanics to the
modern notion of local Lorentz invariance. However, as natural as this seems to
the physicist, most computer scientists would argue that something like a
"local linear tangent space" is not very typical and in fact a quite surprising
property of any conceivable world or algorithm. In this paper, we take the
perspective of the computer scientist seriously, and ask whether there could be
any inherently information-theoretic reason to expect this notion of linearity
to appear in physics. We give a series of simple arguments, spanning quantum
information theory, group representation theory, and renormalization in quantum
gravity, that supports a surprising thesis: namely, that the local linearity of
space-time might ultimately be a consequence of the linearity of probabilities.
While our arguments involve a fair amount of speculation, they have the virtue
of being independent of any detailed assumptions on quantum gravity, and they
are in harmony with several independent recent ideas on emergent space-time in
high-energy physics.


  The notion of quantum matrix pairs is defined. These are pairs of matrices
with non-commuting entries, which have the same pattern of internal relations,
q-commute with each other under matrix multiplication, and are such that
products of powers of the matrices obey the same pattern of internal relations
as the original pair. Such matrices appear in an approach by the authors to
quantizing gravity in 2 space and 1 time dimensions with negative cosmological
constant on the torus. Explicit examples and transformations which generate new
pairs from a given pair are presented.


  We study a statistical mechanics model of two species of bosons with mutual
statistics $\theta=2\pi/n$ in (2+1) dimensions. This model realizes a
fractionalized topological phase of bosons, which is a fractionalized version
of the boson integer quantum Hall effect. The model can be studied with
sign-free Monte Carlo simulations. We study the phase transitions between the
fractionalized topological phase and a trivial insulator, and between different
topological phases. We find that these transitions are continuous, and we
measure their critical exponents.


  Gaussian processes are among the most useful tools in modeling continuous
processes in machine learning and statistics. If the value of a process is
known at a finite collection of points, one may use Gaussian processes to
construct a surface which interpolates these values to be used for prediction
and uncertainty quantification in other locations. However, it is not always
the case that the available information is in the form of a finite collection
of points. For example, boundary value problems contain information on the
boundary of a domain, which is an uncountable collection of points that cannot
be incorporated into typical Gaussian process techniques. In this paper we
construct a Gaussian process model which utilizes reproducing kernel Hilbert
spaces to unify the typical finite case with the case of having uncountable
information by exploiting the equivalence of conditional expectation and
orthogonal projections. We discuss this construction in statistical models,
including numerical considerations and a proof of concept.


  Network operators and system administrators are increasingly overwhelmed with
incessant cyber-security threats ranging from malicious network reconnaissance
to attacks such as distributed denial of service and data breaches. A large
number of these attacks could be prevented if the network operators were better
equipped with threat intelligence information that would allow them to block or
throttle nefarious scanning activities. Network telescopes or "darknets" offer
a unique window into observing Internet-wide scanners and other malicious
entities, and they could offer early warning signals to operators that would be
critical for infrastructure protection and/or attack mitigation. A network
telescope consists of unused or "dark" IP spaces that serve no users, and
solely passively observes any Internet traffic destined to the "telescope
sensor" in an attempt to record ubiquitous network scanners, malware that
forage for vulnerable devices, and other dubious activities. Hence, monitoring
network telescopes for timely detection of coordinated and heavy scanning
activities is an important, albeit challenging, task. The challenges mainly
arise due to the non-stationarity and the dynamic nature of Internet traffic
and, more importantly, the fact that one needs to monitor high-dimensional
signals (e.g., all TCP/UDP ports) to search for "sparse" anomalies. We propose
statistical methods to address both challenges in an efficient and "online"
manner; our work is validated both with synthetic data as well as real-world
data from a large network telescope.


  We report on the study of magneto-photogalvanic and magnetotransport
phenomena in 200 nm partially strained HgTe films. This thickness is slightly
larger than the estimated critical thickness of lattice relaxation leaving the
film partially relaxed with the value of the energy gap close to zero. We show
that illumination of HgTe films with monochromatic terahertz laser radiation
results in a giant resonant photocurrent caused by the cyclotron resonance in
the surface states. The resonant photocurrent is also detected in the reference
fully strained 80 nm HgTe films previously shown to be fully gapped 3D
topological insulators. We show that the resonance positions in both types of
films almost coincide demonstrating the existence of topologically protected
surface states in thick HgTe films. The conclusion is supported by
magnetotransport experiments.


  This paper proposes a method to compute crossfields based on the
Ginzburg-Landau theory. The Ginzburg-Landau functional has two terms: the
Dirichlet energy of the distribution and a term penalizing the mismatch between
the fixed and actual norm of the distribution. Directional fields on surfaces
are known to have a number of critical points, which are properly identified
with the Ginzburg-Landau approach: the asymptotic behavior of Ginzburg-Landau
problem provides well-distributed critical points over the 2-manifold, whose
indices are as low as possible. The central idea in this paper is to exploit
this theoretical background for crossfield computation on arbitrary surfaces.
Such crossfields are instrumental in the generation of meshes with quadrangular
elements. The relation between the topological properties of quadrangular
meshes and crossfields are hence first recalled. It is then shown that a
crossfield on a surface can be represented by a complex function of unit norm
with a number of critical points, i.e., a nearly everywhere smooth function
taking its values in the unit circle of the complex plane. As maximal
smoothness of the crossfield is equivalent with minimal energy, the crossfield
problem is equivalent to an optimization problem based on Ginzburg-Landau
functional. A discretization scheme with Crouzeix-Raviart elements is applied
and the correctness of the resulting finite element formulation is validated on
the unit disk by comparison with an analytical solution. The method is also
applied to the 2-sphere where, surprisingly but rightly, the computed critical
points are not located at the vertices of a cube, but at those of an anticube.


  High-multiplex and deep spectroscopic follow-up of upcoming panoramic
deep-imaging surveys like LSST, Euclid, and WFIRST is a widely recognized and
increasingly urgent necessity. No current or planned facility at a U.S.
observatory meets the sensitivity, multiplex, and rapid-response time needed to
exploit these future datasets. FOBOS, the Fiber-Optic Broadband Optical
Spectrograph, is a near-term fiber-based facility that addresses these
spectroscopic needs by optimizing depth over area and exploiting the aperture
advantage of the existing 10m Keck II Telescope. The result is an instrument
with a uniquely blue-sensitive wavelength range (0.31-1.0 um) at R~3500,
high-multiplex (1800 fibers), and a factor 1.7 greater survey speed and
order-of-magnitude greater sampling density than Subaru's Prime Focus
Spectrograph (PFS). In the era of panoramic deep imaging, FOBOS will excel at
building the deep, spectroscopic reference data sets needed to interpret vast
imaging data. At the same time, its flexible focal plane, including a mode with
25 deployable integral-field units (IFUs) across a 20 arcmin diameter field,
enables an expansive range of scientific investigations. Its key programmatic
areas include (1) nested stellar-parameter training sets that enable studies of
the Milky Way and M31 halo sub-structure, as well as local group dwarf
galaxies, (2) a comprehensive picture of galaxy formation thanks to detailed
mapping of the baryonic environment at z~2 and statistical linking of evolving
populations to the present day, and (3) dramatic enhancements in cosmological
constraints via precise photometric redshifts and determined redshift
distributions. In combination with Keck I instrumentation, FOBOS also provides
instant access to medium-resolution spectroscopy for transient sources with
full coverage from the UV to the K-band.


  Model Predictive Control (MPC) has been widely applied to the motion planning
of autonomous vehicles. An MPC-controlled vehicle is required to predict its
own trajectories in a finite prediction horizon according to its model. Beyond
this, the vehicle should also incorporate the prediction of the trajectory of
its nearby vehicles, or target vehicles (TVs) into its decision-making. The
conventional trajectory prediction methods, such as the constant-speed-based
ones, are too trivial to accurately capture the potential collision risks. In
this report, we propose a novel MPC-based motion planning method for an
autonomous vehicle with a set of risk-aware constraints. These constraints
incorporate the predicted trajectory of a TV learned using a
deep-learning-based method. A recurrent neural network (RNN) is used to predict
the TV's future trajectory based on its historical data. Then, the predicted TV
trajectory is incorporated into the optimization of the MPC of the ego vehicle
to generate collision-free motion. Simulation studies are conducted to showcase
the prediction accuracy of the RNN model and the collision-free trajectories
generated by the MPC.


  We consider families $u_p$ of solutions to the problem
\begin{equation}\label{problemAbstract} \left\{\begin{array}{lr}-\Delta u= u^p
& \mbox{ in }\Omega\\ u>0 & \mbox{ in }\Omega\\ u=0 & \mbox{ on }\partial
\Omega \end{array}\right.\tag{$\mathcal E_p$} \end{equation} where $p>1$ and
$\Omega$ is a smooth bounded domain of $\mathbb R^2$. We give a complete
description of the asymptotic behavior of $u_p$ as $p\rightarrow +\infty$,
under the condition \[p\int_{\Omega} |\nabla u_p|^2\,dx\rightarrow
\beta\in\mathbb R\qquad\mbox{ as $p\rightarrow +\infty$}.\]


  Let $\mathbb{K}$ be a field, and let $S=\mathbb{K}[X_1, ..., X_n]$ be the
polynomial ring. Let $I$ be a monomial ideal of $S$ with up to 5 generators. In
this paper, we present a computational experiment which allows us to prove that
$\mathrm{depth}_S S/I = \mathrm{sdepth}_S S/I < \mathrm{sdepth}_S I$. This
shows that the Stanley conjecture is true for $S/I$ and $I$, if $I$ can be
generated by at most 5 monomials. The result also brings additional
computational evidence for a conjecture made by Herzog.


  The parallel globe is an old, very simple and ingenious device that, when
systematically employed in astronomy classes, becomes a teaching tool with
great potential. Properly oriented according to the local meridian, this
instrument allows us to follow the shadows in any region of the Earth that is
illuminated by the Sun, as well as offering a clear view of the terminator, the
fast-moving grey line that divides the day from the night on our planet. With
knowledge of the shadows, it is possible to estimate the latitude of a site and
to infer local solar time anywhere in the planet's sunlit hemisphere.
Furthermore, by using the parallel globe we may understand simply the existence
of regions in which objects sometimes do not cast shadows, and also other
regions which, on the contrary, sometimes become "long-shadow" countries. In
this work, we first review the device and the basics of its assembly and
operation. In the second part, we describe in detail some activities targeted
to facilitate its use in the classroom, which our research group has been
developing during teacher training workshops.


  Following Aguil\'{o}-Su\~{n}er-Torrens (2008),
Koles\'{a}rov\'{a}-Mesiar-Mordelov\'{a}-Sempi (2006) and
Mayor-Su\~{n}er-Torrens (2005), we continue to develop a theory of matrix
representation for discrete copulas. To be more precise, we give
characterizations of meet-irreducible discrete copulas from an
order-theoretical aspect: we show that the set of all irreducible discrete
copulas is a lattice in analogy with Nelsen and \'{U}beda-Flores (2005).
Moreover, we clarify its lattice structure related to Kendall's $\tau$ and
Spearman's $\rho$ borrowing ideas from Coxeter groups.


  We consider the finite velocity of the ejecta of a type Ia supernova (SN Ia)
in the double detonation (DDet) scenario with a white dwarf (WD) mass-donor
companion, and find that the runaway velocity of the surviving (mass donor) WD
is lower than its pre-explosion orbital velocity by about 8-11%. This implies
that the fastest runaway WDs in the Galaxy, if come from the DDet scenario,
require even more massive WDs than what a simple calculation that neglects the
finite ejecta velocity gives. This extreme set of initial conditions makes such
binaries less common. We also tentatively find that the inner ejecta deviates
from spherical symmetry, but not to the degree that we can use observations to
make any claim. Our findings support the claim that the DDet scenario leads
mostly to peculiar SNe Ia but not to normal SNe Ia.


  We consider the translocation dynamics of a polymer chain forced through a
nanopore by an external force on its head monomer on the trans side. For a
proper theoretical treatment we generalize the iso-flux tension propagation
(IFTP) theory to include friction arising from the trans side subchain. The
theory reveals a complicated scenario of multiple scaling regimes depending on
the configurations of the cis and the trans side subchains. In the limit of
high driving forces $f$ such that the trans subchain is strongly stretched, the
theory is in excellent agreement with molecular dynamics simulations and allows
an exact analytic solution for the scaling of the translocation time ${\tau}$
as a function of the chain length $N_0$ and $f$. In this regime the asymptotic
scaling exponents for ${\tau} \sim N_0^{\alpha} f^{\beta}$ are $\alpha=2$, and
$\beta =-1$. The theory reveals significant correction-to-scaling terms arising
from the cis side subchain and pore friction, which lead to a very slow
approach to $\alpha =2$ from below as a function of increasing $N_0$.


  We use ultraviolet imaging taken with the XMM-Newton Optical Monitor
telescope (XMM-OM), covering 280 square arcminutes in the UVW1 band (effective
wavelength 2910 Angstroms) to measure rest-frame ultraviolet (1500 Angstrom)
luminosity functions of galaxies with redshifts z between 0.6 and 1.2. The
XMM-OM data are supplemented by a large body of optical and infrared imaging to
provide photometric redshifts. The XMM-OM data have a significantly narrower
point-spread-function (resulting in less source confusion) and simpler
K-correction than the GALEX data previously employed in this redshift range.
Ultraviolet-bright active galactic nuclei are excluded to ensure that the
luminosity functions relate directly to the star-forming galaxy population.
Binned luminosity functions and parametric Schechter-function fits are derived
in two redshift intervals: 0.6<z<0.8 and 0.8<z<1.2. We find that the luminosity
function evolves such that the characteristic absolute magnitude M* is brighter
for 0.8<z<1.2 than for 0.6<z<0.8.


  We present the results of the analysis of the hard band XMM-Newton spectra of
the luminous, L(2-10keV)~3.4E+45 erg/s, radio-quiet quasar, E1821+643. Two
emission features were observed in the 6-7 keV rest frame band, confirming
previous Chandra detection of these structures. We interpret these features as
two single emission lines, one consistent with the neutral Fe K-alpha line at
6.4 keV and the other most likely due to FeXXVI. If related to the quasar, the
high-energy emission line should originate in highly ionised matter, i.e. the
accretion disc or the clouds of the emission line regions. Alternatively, it
may be related to the intergalactic medium of the rich galaxy cluster in which
E1821+643 is embedded. A composite broad emission line in combination with an
absorption line model, however, also fits the data well. We discuss the
possible physical interpretations of the origin of these features.


  In this paper, we introduce a slight variation of the Dominated Coupling From
the Past algorithm (DCFTP) of Kendall, for bounded Markov chains. It is based
on the control of a (typically non-monotonic) stochastic recursion by a
(typically monotonic) one. We show that this algorithm is particularly suitable
for stochastic matching models with bounded patience, a class of models for
which the steady state distribution of the system is in general unknown in
closed form. We first show that the Markov chain of this model can be easily
controlled by an infinite-server queue. We then investigate the particular case
where patience times are deterministic, and this control argument may fail. in
that case we resort to an ad-hoc technique that can also be seen as a control
(this time, by the arrival sequence). We then compare this algorithm to the
classical CFTP one, and show how our perfect simulation results can be used to
estimate, and compare, the loss probabilities of various systems in
equilibrium.


  We present the results of near-infrared imaging and low-resolution near-
infrared spectroscopy of low mass objects in the NGC 1333 molecular cloud. A
JHK survey of an 11.4' x 11.7' area of the northern cluster was conducted to a
sensitivity of K < 16 mag. Using near-infrared magnitudes and colors from this
and previously published surveys, twenty-five brown dwarf candidates were
selected toward the high extinction cloud core. Spectra in the K band were
obtained and comparisons of the depths of water vapor absorption bands in our
candidate objects with a grid of dwarf,subgiant, and giant standards were made
to derive spectral types. These data were then used to derive effective
temperatures and stellar luminosities which, when combined with theoretical
tracks and isochrones for pre-main sequence objects, resulted in estimates for
their masses and ages. The models suggest a median age for the sample of < 1
Myr with substellar masses for at least 9 of the candidates including the x-ray
flare source ASR 24. Surface gravities have been estimated for the brown dwarf
candidates and, for a given spectral type,found to resemble more closely dwarfs
than giants. Using the near-infrared imaging data and age estimates from the
spectroscopic sample, an extinction-limited sample in the northern cluster was
defined. Consistent with recent studies of other young clusters, this sample
exhibits an accretion disk frequency of 0.75 +-0.20 and a mass spectrum slope
across the hydrogen-burning limit of alpha < 1.6 where dN/dM ~ M^-(alpha).


  Robust operation of power transmission grids is essential for most of today's
technical infrastructure and our daily life. Adding renewable generation to
power grids requires grid extensions and sophisticated control actions on
different time scales to cope with short-term fluctuations and long-term power
imbalance. Braess' paradox constitutes a counterintuitive collective phenomenon
that occurs if adding new transmission line capacity to a network increases
loads on other lines, effectively reducing the system's performance and
potentially even entirely removing its operating state. Combining simple
analytical considerations with numerical investigations on a small sample
network, we here study dynamical consequences of secondary control in AC power
grid models. We demonstrate that sufficiently strong control not only implies
dynamical stability of the system but may also cure Braess' paradox. Our
results highlight the importance of demand control in conjunction with grid
topology for stable operation and reveal a new functional benefit of secondary
control.


  For an s-wave superconductor/semiconductor/ferromagnetic-insulator structure,
the proximity effect can induce the energy gap in the semiconductor rather than
the superconducting pair potential of its microscope Hamiltonian. As a result,
it is questionable to realize topological superconducting states in that
structure.


  Generic quantum interference effects occuring in 1D-quasicrystals are
reviewed with emphasis on the joint effect of phason disorder on electronic
localization and propagation modes. In close conjunction with properties of
real materials, the contributions of quantum interferences in several regimes
close to the metal insulator transition are outlined.


  We investigate the spatial distribution of the physical and chemical
properties of the hot X-ray emitting plasma of the supernova remnant IC 443, in
order to get important constraints on its ionization stage, on the progenitor
supernova explosion, on the age of the remnant, and its physical association
with a close pulsar wind nebula.
  The hard X-ray thermal emission (1.4-5.0 keV) of IC 443 displays a
centrally-peaked morphology, its brightness peaks being associated with hot
(kT>1 keV) X-ray emitting plasma. A ring-shaped structure, characterized by
high values of equivalent widths and median photon energy, encloses the PWN.
Its hard X-ray emission is spectrally characterized by a collisional ionization
equilibrium model, and strong emission lines of Mg, Si, and S, requiring
oversolar metal abundances. Dynamically, the location of the ejecta ring
suggests an SNR age of ~4,000 yr.
  The presence of overionized plasma in the inner regions of IC 443, addressed
in previous works, is much less evident in our observations.


  [Abridged abstract] Large Language Models (LLMs) can solve some
undergraduate-level to graduate-level physics textbook problems and are
proficient at coding. Combining these two capabilities could one day enable AI
systems to simulate and predict the physical world.
  We present an evaluation of state-of-the-art (SOTA) LLMs on PhD-level to
research-level computational physics problems. We condition LLM generation on
the use of well-documented and widely-used packages to elicit coding
capabilities in the physics and astrophysics domains. We contribute $\sim 50$
original and challenging problems in celestial mechanics (with REBOUND),
stellar physics (with MESA), 1D fluid dynamics (with Dedalus) and non-linear
dynamics (with SciPy). Since our problems do not admit unique solutions, we
evaluate LLM performance on several soft metrics: counts of lines that contain
different types of errors (coding, physics, necessity and sufficiency) as well
as a more "educational" Pass-Fail metric focused on capturing the salient
physical ingredients of the problem at hand.
  As expected, today's SOTA LLM (GPT4) zero-shot fails most of our problems,
although about 40\% of the solutions could plausibly get a passing grade. About
$70-90 \%$ of the code lines produced are necessary, sufficient and correct
(coding \& physics). Physics and coding errors are the most common, with some
unnecessary or insufficient lines. We observe significant variations across
problem class and difficulty. We identify several failure modes of GPT4 in the
computational physics domain.
  Our reconnaissance work provides a snapshot of current computational
capabilities in classical physics and points to obvious improvement targets if
AI systems are ever to reach a basic level of autonomy in physics simulation
capabilities.


  Conceptual blending is a powerful tool for computational creativity where,
for example, the properties of two harmonic spaces may be combined in a
consistent manner to produce a novel harmonic space. However, deciding about
the importance of property features in the input spaces and evaluating the
results of conceptual blending is a nontrivial task. In the specific case of
musical harmony, defining the salient features of chord transitions and
evaluating invented harmonic spaces requires deep musicological background
knowledge. In this paper, we propose a creative tool that helps musicologists
to evaluate and to enhance harmonic innovation. This tool allows a music expert
to specify arguments over given transition properties. These arguments are then
considered by the system when defining combinations of features in an
idiom-blending process. A music expert can assess whether the new harmonic
idiom makes musicological sense and re-adjust the arguments (selection of
features) to explore alternative blends that can potentially produce better
harmonic spaces. We conclude with a discussion of future work that would
further automate the harmonisation process.


  State-of-the-art vision and vision-and-language models rely on large-scale
visio-linguistic pretraining for obtaining good performance on a variety of
downstream tasks. Generally, such models are often either cross-modal
(contrastive) or multi-modal (with earlier fusion) but not both; and they often
only target specific modalities or tasks. A promising direction would be to use
a single holistic universal model, as a "foundation", that targets all
modalities at once -- a true vision and language foundation model should be
good at vision tasks, language tasks, and cross- and multi-modal vision and
language tasks. We introduce FLAVA as such a model and demonstrate impressive
performance on a wide range of 35 tasks spanning these target modalities.


  We show that the subset of high energy neutrino events detected by IceCube
which correlate with the Galactic center (within uncertainties of their
reconstructed arrival directions) could originate in the collisions of protons
accelerated by the Sagittarius (Sgr) A* disk dynamo. Under very reasonable
assumptions on source parameters we demonstrate that the supermassive black
hole at the center of the Galaxy could launch protons and nuclei with multi PeV
energies. Acceleration of these particles in a period of seconds up to Lorentz
factors of \sim 10^7 is possible by means of the Blandford-Znajek mechanism,
which wires the spinning magnetosphere of Sgr A* as a Faraday unipolar
inductor. During the acceleration process the \sim PeV progenitors of \sim 50
TeV neutrinos radiate curvature photons in the keV energy range. We show that
IceCube neutrino astronomy with photon tagging on the Chandra X-ray Observatory
could provide a valuable probe for the Blandford-Znajek acceleration mechanism.
We also argue that EeV neutrinos, which may be produced in a similar fashion
during the merging of binary black holes, could become the smoking gun for
particle acceleration in a one-shot boost.


  This article describes the Laser calibration system of the Atlas hadronic
Tile Calorimeter that has been used during the run 1 of the LHC. First, the
stability of the system associated readout electronics is studied. It is found
to be stable with variations smaller than 0.6 %. Then, the method developed to
compute the calibration constants, to correct for the variations of the gain of
the calorimeter photomultipliers, is described. These constants were determined
with a statistical uncertainty of 0.3 % and a systematic uncertainty of 0.2 %
for the central part of the calorimeter and 0.5 % for the end-caps. Finally,
the detection and correction of timing mis-configuration of the Tile
Calorimeter using the Laser system are also presented.


  We show that every AF-algebra is generated by a single operator. This was
previously unclear, since the invariant that assigns to a C*-algebra its
minimal number of generators lacks natural permanence properties. In
particular, it may increase when passing to ideals or inductive limits.
  To obtain a better behaved theory, we not only ask if a C*-algebra is
generated by $n$ elements, but also if generating $n$-tuples are dense. This
defines the generator rank, which we show has many natural permanence
properties: it does not increase when passing to ideals, quotients or inductive
limits.


  Label information plays an important role in supervised hyperspectral image
classification problem. However, current classification methods all ignore an
important and inevitable problem---labels may be corrupted and collecting clean
labels for training samples is difficult, and often impractical. Therefore, how
to learn from the database with noisy labels is a problem of great practical
importance. In this paper, we study the influence of label noise on
hyperspectral image classification, and develop a random label propagation
algorithm (RLPA) to cleanse the label noise. The key idea of RLPA is to exploit
knowledge (e.g., the superpixel based spectral-spatial constraints) from the
observed hyperspectral images and apply it to the process of label propagation.
Specifically, RLPA first constructs a spectral-spatial probability transfer
matrix (SSPTM) that simultaneously considers the spectral similarity and
superpixel based spatial information. It then randomly chooses some training
samples as "clean" samples and sets the rest as unlabeled samples, and
propagates the label information from the "clean" samples to the rest unlabeled
samples with the SSPTM. By repeating the random assignment (of "clean" labeled
samples and unlabeled samples) and propagation, we can obtain multiple labels
for each training sample. Therefore, the final propagated label can be
calculated by a majority vote algorithm. Experimental studies show that RLPA
can reduce the level of noisy label and demonstrates the advantages of our
proposed method over four major classifiers with a significant margin---the
gains in terms of the average OA, AA, Kappa are impressive, e.g., 9.18%, 9.58%,
and 0.1043. The Matlab source code is available at
https://github.com/junjun-jiang/RLPA


  The goal of this paper is to address finite-horizon minimum variance and
covariance steering problems for discrete-time stochastic (Gaussian) linear
systems. On the one hand, the minimum variance problem seeks for a control
policy that will steer the state mean of an uncertain system to a prescribed
quantity while minimizing the trace of its terminal state covariance (or
variance). On the other hand, the covariance steering problem seeks for a
control policy that will steer the covariance of the terminal state to a
prescribed positive definite matrix. We propose a solution approach that relies
on the stochastic version of the affine disturbance feedback control
parametrization according to which the control input at each stage can be
expressed as an affine function of the history of disturbances that have acted
upon the system. Our analysis reveals that this particular parametrization
allows one to reduce the stochastic optimal control problems considered herein
into tractable convex programs with essentially the same decision variables.
This is in contrast with other control policy parametrizations, such as the
state feedback parametrization, in which the decision variables of the convex
program do not coincide with the controller's parameters of the stochastic
optimal control problem. In addition, we propose a variation of the control
parametrization which relies on truncated histories of past disturbances. We
show that by selecting the length of the truncated sequences appropriately, we
can design suboptimal controllers which can strike the desired balance between
performance and computational cost.


  Based on the electric vehicle (EV) arrival times and the duration of EV
connection to the charging station, we identify charging patterns and derive
groups of charging stations with similar charging patterns applying two
approaches. The ruled based approach derives the charging patterns by
specifying a set of time intervals and a threshold value. In the second
approach, we combine the modified l-p norm (as a matrix dissimilarity measure)
with hierarchical clustering and apply them to automatically identify charging
patterns and groups of charging stations associated with such patterns. A
dataset collected in a large network of public charging stations is used to
test both approaches. Using both methods, we derived charging patterns. The
first, rule-based approach, performed well at deriving predefined patterns and
the latter, hierarchical clustering, showed the capability of delivering
unexpected charging patterns.


  While a number of knowledge graph representation learning (KGRL) methods have
been proposed over the past decade, very few theoretical analyses have been
conducted on them. In this paper, we present the first PAC-Bayesian
generalization bounds for KGRL methods. To analyze a broad class of KGRL
models, we propose a generic framework named ReED (Relation-aware
Encoder-Decoder), which consists of a relation-aware message passing encoder
and a triplet classification decoder. Our ReED framework can express at least
15 different existing KGRL models, including not only graph neural
network-based models such as R-GCN and CompGCN but also shallow-architecture
models such as RotatE and ANALOGY. Our generalization bounds for the ReED
framework provide theoretical grounds for the commonly used tricks in KGRL,
e.g., parameter-sharing and weight normalization schemes, and guide desirable
design choices for practical KGRL methods. We empirically show that the
critical factors in our generalization bounds can explain actual generalization
errors on three real-world knowledge graphs.


  Aims The possible influence of solar superflares on the near-Earth space
radiation environment are assessed through the investigation of scaling laws
between the peak proton flux and fluence of Solar Energetic Particle (SEP)
events with the solar flare soft X-ray peak photon flux.
  Methods We compiled a catalog of 65 well-connected (W20-90) SEP events during
the last three solar cycles covering a period of $\sim$34 years (1984-2020)
that were associated with flares of class $\geq$C6.0 and investigated the
statistical relations between the recorded peak proton fluxes ($I_{P}$) and the
fluences ($F_{P}$) at a set of integral energies from E $>$10; $>$30; $>$60; to
$>$100 MeV versus the associated solar flare peak soft X-ray flux in the 1$-$8
A band ($F_{SXR}$). Based on the inferred relations, we calculate the
integrated energy dependence of the peak proton flux ($I_{P}$) and fluence
($F_{P}$) of the SEP events, assuming that they follow an inverse power-law
with respect to energy. Finally, we make use of simple physical assumptions,
combining our derived scaling laws, and estimate the upper limits for $I_{P}$
and $F_{P}$ focusing on the flare associated with the strongest GLE yet
directly observed (GLE 05 on 23 February 1956), and that inferred for the
cosmogenic radionuclide based SEP event of AD774/775.
  Results A scaling law relating $I_{P}$ and $F_{P}$ to the solar soft X-ray
peak intensity ($F_{SXR}$) as $\propto$~$F_{SXR}^{5/6}$ for a flare with a
$F_{SXR}$ = X600 (in the revised scale) is consistent with values of $F_{P}$
inferred for the cosmogenic nuclide event of AD774/775.


  Smart grids have received much attention in recent years in order to
optimally manage the resources, transmission and consumption of electric
power.In these grids, one of the most important communication services is the
multicast service. Providing multicast services in the smart communicative grid
poses several challenges, including the heterogeneity of different
communication media and the strict requirements of reliability, security and
latency. Wireless technologies and PLC connections are the two most important
media used in this grid, among which PLC connections are very unstable, which
makes it difficult to provide reliability. In this research, the problem of
geographically flooding of multicast data has been considered. First, this
problem has been modeled as an optimization problem which is used as a
reference model in evaluating the proposed approaches. Then, two MKMB and GCBT
multicast tree formation algorithms have been developed based on geographical
information according to the characteristics of smart grids. Comparison of
these two approaches shows the advantages and disadvantages of forming a
core-based tree compared to a source-based tree. Evaluation of these approaches
shows a relative improvement in tree cost and the amount of end-to-end delay
compared to basic algorithms. In the second part, providing security and
reliability in data transmission has been considered. Both Hybrid and Multiple
algorithms have been developed based on the idea of multiple transmission tree.
In the Hybrid algorithm, the aim is to provide higher security and reliability,
but in the Multiple algorithms, minimization of message transmission delay is
targeted. In the section of behavior evaluation, these two algorithms have been
studied in different working conditions, which indicates the achievement of the
desired goals.


  We give a more complete calculation of $b \to s e^+e^- $ decay including
leading log QCD corrections from $m_{top}$ to $M_W$ in addition to corrections
from $M_{W}$ to $m_b$. The differential decay rate is found to be slightly
suppressed for a large invariant mass of the $e^+e^- $ pair; while the
integrated width is slightly enhanced comparing with the results without the
QCD running from $m_{top}$ to $M_W$.


  We study the time evolution of a conformal field theory deformed by a
relevant operator under a smooth but fast quantum quench which brings it to the
conformal point. We argue that when the quench time scale $\delta t$ is small
compared to the scale set by the relevant coupling, the expectation value of
the quenched operator scales universally as $\delta g/ \delta t ^{2\Delta-d}$
where $\delta g$ is the quench amplitude. This growth is further enhanced by a
logarithmic factor in even dimensions. We present explicit results for free
scalar and fermionic field theories, supported by an analytic understanding of
the leading contribution for fast quenches. Results from this Letter suggest
that this scaling result, first found in holography, is in fact universal to
quantum quenches. Our considerations also show that this limit of fast smooth
quenches is quite different from an instantaneous quench from one
time-independent Hamiltonian to another, where the Schrodinger picture state at
the time of the quench simply serves as an initial condition for subsequent
evolution with the final Hamiltonian.


  Audio-driven one-shot talking face generation methods are usually trained on
video resources of various persons. However, their created videos often suffer
unnatural mouth shapes and asynchronous lips because those methods struggle to
learn a consistent speech style from different speakers. We observe that it
would be much easier to learn a consistent speech style from a specific
speaker, which leads to authentic mouth movements. Hence, we propose a novel
one-shot talking face generation framework by exploring consistent correlations
between audio and visual motions from a specific speaker and then transferring
audio-driven motion fields to a reference image. Specifically, we develop an
Audio-Visual Correlation Transformer (AVCT) that aims to infer talking motions
represented by keypoint based dense motion fields from an input audio. In
particular, considering audio may come from different identities in deployment,
we incorporate phonemes to represent audio signals. In this manner, our AVCT
can inherently generalize to audio spoken by other identities. Moreover, as
face keypoints are used to represent speakers, AVCT is agnostic against
appearances of the training speaker, and thus allows us to manipulate face
images of different identities readily. Considering different face shapes lead
to different motions, a motion field transfer module is exploited to reduce the
audio-driven dense motion field gap between the training identity and the
one-shot reference. Once we obtained the dense motion field of the reference
image, we employ an image renderer to generate its talking face videos from an
audio clip. Thanks to our learned consistent speaking style, our method
generates authentic mouth shapes and vivid movements. Extensive experiments
demonstrate that our synthesized videos outperform the state-of-the-art in
terms of visual quality and lip-sync.


  Topological quantum error correcting codes have emerged as leading candidates
towards the goal of achieving large-scale fault-tolerant quantum computers.
However, quantifying entanglement in these systems of large size in the
presence of noise is a challenging task. In this paper, we provide two
different prescriptions to characterize noisy stabilizer states, including the
surface and the color codes, in terms of localizable entanglement over a subset
of qubits. In one approach, we exploit appropriately constructed entanglement
witness operators to estimate a witness-based lower bound of localizable
entanglement, which is directly accessible in experiments. In the other recipe,
we use graph states that are local unitary equivalent to the stabilizer state
to determine a computable measurement-based lower bound of localizable
entanglement. If used experimentally, this translates to a lower bound of
localizable entanglement obtained from single-qubit measurements in specific
bases to be performed on the qubits outside the subsystem of interest. Towards
computing these lower bounds, we discuss in detail the methodology of obtaining
a local unitary equivalent graph state from a stabilizer state, which includes
a new and scalable geometric recipe as well as an algebraic method that applies
to general stabilizer states of arbitrary size. Moreover, as a crucial step of
the latter recipe, we develop a scalable graph-transformation algorithm that
creates a link between two specific nodes in a graph using a sequence of local
complementation operations. We develop open-source Python packages for these
transformations, and illustrate the methodology by applying it to a noisy
topological color code, and study how the witness and measurement-based lower
bounds of localizable entanglement varies with the distance between the chosen
qubits.


  We prove that the localizations of the categories of dg categories, of
cohomologically unital and strictly unital $A_\infty$ categories with respect
to the corresponding classes of quasi-equivalences are all equivalent. Moreover
we show that the last two localizations are equivalent to the corresponding
quotients by the relation of being isomorphic in the cohomology of the
$A_\infty$ category of $A_\infty$ functors. As an application we give a
complete proof of a claim by Kontsevich stating that the category of internal
Homs for two dg categories can be described as the category of strictly unital
$A_\infty$ functors between them.


  Modern quantum chemistry can make quantitative predictions on an immense
array of chemical systems. However, the interpretation of those predictions is
often complicated by the complex wave function expansions used. Here we show
that an exceptionally simple algebraic construction allows for defining atomic
core and valence orbitals, polarized by the molecular environment, which can
exactly represent self-consistent field wave functions. This construction
provides an unbiased and direct connection between quantum chemistry and
empirical chemical concepts, and can be used, for example, to calculate the
nature of bonding in molecules, in chemical terms, from first principles.


  The famous tree packing conjecture of Gy\'arf\'as from 1976 says that any
sequence of trees $T_1,\ldots,T_n$ such that $|T_i|=i$ for each $i\in [n]$
packs into the complete $n$-vertex graph $K_n$. Packing even just the largest
trees in such a sequence has proven difficult, with Bollob\'as drawing
attention to this in 1995 by conjecturing that, for each $k$, if $n$ is
sufficiently large then the largest $k$ trees in any such sequence can be
packed into $K_n$. This has only been shown for $k\leq 5$, by \.{Z}ak, despite
many partial results and much related work on the full tree packing conjecture.
We prove Bollob\'as's conjecture, by showing that, moreover, a linear number of
the largest trees can be packed in the tree packing conjecture.


  Chirality transfer from the level of molecular structure up to mesoscopic
lengthscales of supramolecular morphologies is a broad and persistent theme in
self-assembled soft materials, from biological to synthetic matter. Here, we
analyze the mechanism of chirality transfer in a prototypical self-assembly
system, block copolymers (BCPs), in particular, its impact on one of the most
complex and functionally vital phases: the cubic, triply-periodic, gyroid
network. Motivated by recent experimental studies, we consider a
self-consistent field model of ABC* triblock copolymers possessing an end-block
of chain chemistry and examine the interplay between chirality at the scale of
networks, in alternating double network phases, and the patterns of segmental
order within tubular network domains. We show that while segments in gyroids
exhibit twist in both polar and nematic segmental order parameters, the
magnitude of net nematic twist is generically much larger than polar twist, and
more surprising, {\it reverses handedness} relative to the sense of polar order
as well as the sense of dihedral twist of the network. Careful analysis of the
intra-domain nematic order reveals that this unique chirality transfer
mechanism relies on the strongly biaxial nature of segmental order in BCP
networks and relates the {\it biaxial twist} to complex patterns of frame
rotation of the principal directors in the intra-domain texture. Finally, we
show that this mechanism of twist reversal leads to chirality selection of
alternating gyroid networks in ABC* triblocks, in the limit of very weak
chirality .


  An iterative formula based on Newton Method alone is presented for the
iterative solutions of equations that ensures convergence in cases where the
traditional Newton Method may fail to converge to the desired root. In
addition, the method has super quadratic convergence of order 2.414. Newton
method is said to fail in certain cases leading to oscillation, divergence to
increasingly large number or off-shooting away to another root further from the
desired domain or off shooting to an invalid domain where the function may not
be defined. In addition when the derivative at the iteration point is zero,
Newton method stalls. In most of these cases, hybrids of several methods such
as Newton, bisection and secant methods are suggested as substitute methods and
Newton method is essentially blended with other methods or altogether
abandoned. This paper argues that a solution is still possible in most of these
cases by the application of Newton Method alone without resorting to other
methods and with the same computational effort, two functional evaluations per
iteration, like the traditional Newton method. In addition, the proposed
modified formula based on Newton method has better convergence characteristics
than the traditional Newton method.


  The radial thermal expansion {\alpha}r of bundles of single-walled carbon
nanotubes saturated with 3He up to the molar concentration 9.4% has been
investigated in the temperature interval 2.1-9.5 K by high-sensitivity
capacitance dilatometry. In the interval 2.1-7 K a negative {\alpha}r was
observed, with a magnitude which exceeded the largest negative {\alpha}r values
of pure and 4He-saturated nanotubes by three and two orders of magnitude,
respectively. The contributions of the two He isotope impurities to the
negative thermal expansion of the nanotube bundles are most likely connected
with the spatial redistribution of 4He and 3He atoms by tunneling at the
surface and inside nanotube bundles. The isotope effect turned out to be huge,
probably owing to the higher tunneling probability of 3He atoms.


  In ad-hoc human-robot collaboration (HRC), humans and robots work on a task
without pre-planning the robot's actions prior to execution; instead, task
allocation occurs in real-time. However, prior research has largely focused on
task allocations that are pre-planned - there has not been a comprehensive
exploration or evaluation of techniques where task allocation is adjusted in
real-time. Inspired by HCI research on territoriality and proxemics, we propose
a design space of novel task allocation techniques including both explicit
techniques, where the user maintains agency, and implicit techniques, where the
efficiency of automation can be leveraged. The techniques were implemented and
evaluated using a tabletop HRC simulation in VR. A 16-participant study, which
presented variations of a collaborative block stacking task, showed that
implicit techniques enable efficient task completion and task parallelization,
and should be augmented with explicit mechanisms to provide users with
fine-grained control.


  Superposition, arguably the most fundamental property of quantum mechanics,
lies at the heart of quantum information science. However, how to create the
superposition of any two unknown pure states remains as a daunting challenge.
Recently, it is proved that such a quantum protocol does not exist if the two
input states are completely unknown, whereas a probabilistic protocol is still
available with some prior knowledge about the input states [M. Oszmaniec
\emph{et al.}, Phys. Rev. Lett. 116, 110403 (2016)]. The knowledge is that both
of the two input states have nonzero overlaps with some given referential
state. In this work, we experimentally realize the probabilistic protocol of
superposing two pure states in a three-qubit nuclear magnetic resonance system.
We demonstrate the feasibility of the protocol by preparing a families of input
states, and the average fidelity between the prepared state and expected
superposition state is over 99%. Moreover, we experimentally illustrate the
limitation of the protocol that it is likely to fail or yields very low
fidelity, if the nonzero overlaps are approaching zero. Our experimental
implementation can be extended to more complex situations and other quantum
systems.


  In this paper, we compute the Joseph-Lundgren exponent for the quadharmonic
Lane-Emden equation, derive a monotonicity formula and classify the finite
Morse index solution to the following quadharmonic Lane-Emden equation:
\noindent \begin{equation}\nonumber \Delta^4
u=|u|^{p-1}u\;\;\;\;\hbox{in}\;\;\;\;\; \R^n. \end{equation} As a byproduct, we
also get a monotonicity formula for the quadharmonic maps $ \Delta^4 u=0$.


  Neutron-star (NS) - white-dwarf (WD) mergers may give rise to observable
explosive transients, but have been little explored. We use 2D coupled
hydrodynamical-thermonuclear FLASH-code simulations to study the evolution of
WD debris-disks formed following WD-disruptions by NSs. We use a 19-elements
nuclear-network and a detailed equation-of-state to follow the evolution,
complemented by a post-process analysis using a larger 125-isotopes
nuclear-network. We consider a wide range of initial conditions and study the
dependence of the results on the NS/WD masses ($1.4-2{\rm M_{\odot}}$;$\,{\rm
0.375-0.7\,M_{\odot}}$, respectively), WD-composition (CO/He/hybrid-He-CO) and
the accretion-disk structure. We find that viscous inflow in the disk gives
rise to continuous wind-outflow of mostly C/O material mixed with
nuclear-burning products arising from a weak detonation occurring in the
inner-region of the disk. We find that such transients are energetically weak
($10^{48}-10^{49}$ergs) compared with thermonuclear-supernovae (SNe), and are
dominated by the (gravitational) accretion-energy. Although
thermonuclear-detonations occur robustly in all of our simulations (besides the
He-WD) they produce only little energy $(1-10\%$ of the kinetic energy) and
$^{56}{\rm Ni}$ ejecta (few$\times10^{-4}-10^{-3}{\rm M_{\odot}})$, with
overall low ejecta masses of $\sim0.01-0.1{\rm M_{\odot}}$. Such explosions may
produce rapidly-evolving transients, much shorter and fainter than regular
type-Ia SNe. The composition and demographics of such SNe appear to be
inconsistent with those of Ca-rich type Ib SNe. Though they might be related to
the various classes of rapidly evolving SNe observed in recent years, they are
likely to be fainter than the typical ones, and may therefore give rise a
different class of potentially observable transients.


  We want to achieve efficiency for the exact computation of the dot product of
two vectors over word-size finite fields. We therefore compare the practical
behaviors of a wide range of implementation techniques using different
representations. The techniques used include oating point representations,
discrete logarithms, tabulations, Montgomery reduction, delayed modulus.


  Concepts of high precision studies of the one-way speed of light anisotropy
are discussed. The high energy particle beam allows measurement of a one-way
speed of light anisotropy (SOLA) via analysis of the beam momentum variation
with sidereal phase without the use of synchronized clocks. High precision beam
position monitors could provide accurate monitoring of the beam orbit and
determination of the particle beam momentum with relative accuracy on the level
of $10^{-10}$, which corresponds to a limit on SOLA of $10^{-18}$ with existing
storage rings. A few additional versions of the experiment are also presented.


  We report on the realization of a high-power, ultranarrow-linewidth, and
frequency-locked 532~nm laser system. The laser system consists of single-pass
and intra-cavity second harmonic generation of a continuous-wave Ytterbium
doped fiber laser at 1064~nm in the nonlinear crystal of periodically poled
lithium niobate and lithium triborate, respectively. With 47~W infrared input,
30~W green laser is generated through the type I critical phase matching in the
intracavity lithium triborate crystal. The laser linewidth is measured to be on
the order of sub-kHz, which is achieved by simultaneously locking the
single-pass frequency doubling output onto the iodine absorption line R69
(36-1) at 532~nm. Furthermore, the phase locking between the laser system and
another slave 1064~nm laser is demonstrated with relative frequency tunability
being up to 10~GHz. Our results completely satisfy the requirements of 532~nm
laser for quantum simulation with ultracold atoms.


  Lecture notes prepared for the 2021 SAGEX PhD School in Amplitudes hosted by
the University of Copenhagen August 10th through 13th. Topics covered include:
the manifestation of asymptotic symmetries via soft theorems, their
organization into currents in a celestial CFT, aspects of the holographic
dictionary, a literature guide, and accompanying exercises.


  The field of topological insulators (TI) was sparked by the prediction of the
quantum spin Hall effect (QSHE) in time reversal invariant systems, such as
spin-orbit coupled monolayer graphene. Ever since, a variety of monolayer
crystals have been proposed as two-dimensional (2D) TIs exhibiting the QSHE,
possibly even at high temperatures. However, conclusive evidence for a
monolayer QSHE is still lacking, and systems based on semiconductor
heterostructures operate at temperatures close to liquid helium. Here we report
the observation of the QSHE in monolayer WTe2 at temperatures up to 100 Kelvin.
The monolayer exhibits the hallmark quantized transport conductance, ~ e2/h per
edge, in the short edge limit. Moreover, a magnetic field suppresses the
conductance, and the observed Zeeman-type gap indicates the existence of a
Kramers degenerate point, demonstrating the importance of time reversal
symmetry for protection from elastic backscattering. Our results establish the
high-temperature QSHE and open a new realm for the discovery of topological
phases based on 2D crystals.


  For the lithium dimer we calculate cross sections for absorption of radiation
from the vibrational-rotational levels of the ground X [singlet Sigma g +]
electronic state to the vibrational levels and continua of the excited A
[singlet Sigma u +] and B [singlet Pi u] electronic states. Theoretical and
experimental data are used to characterize the molecular properties taking
advantage of knowledge recently obtained from photoassociation spectroscopy and
ultra-cold atom collision studies. The quantum-mechanical calculations are
carried out for temperatures in the range from 1000 to 2000 K and are compared
with previous calculations and measurements.


  We present a method for humanoid robot walking on partial footholds such as
small stepping stones and rocks with sharp surfaces. Our algorithm does not
rely on prior knowledge of the foothold, but information about an expected
foothold can be used to improve the stepping performance. After a step is
taken, the robot explores the new contact surface by attempting to shift the
center of pressure around the foot. The available foothold is inferred by the
way in which the foot rotates about contact edges and/or by the achieved center
of pressure locations on the foot during exploration. This estimated contact
area is then used by a whole body momentum-based control algorithm. To walk and
balance on partial footholds, we combine fast, dynamic stepping with the use of
upper body angular momentum to regain balance. We applied this method to the
Atlas humanoid designed by Boston Dynamics to walk over small contact surfaces,
such as line and point contacts. We present experimental results and discuss
performance limitations.


  By employing the gradient/Wilson flow, we derive a universal formula that
expresses a correctly normalized flavor non-singlet axial-vector current of
quarks. The formula is universal in the sense that it holds independently of
regularization and especially holds with lattice regularization. It is also
confirmed that, in the lowest non-trivial order of perturbation theory, the
triangle diagram containing the formula and two flavor non-singlet vector
currents possesses non-local structure that is compatible with the triangle
anomaly.


  Transformer, as one of the most advanced neural network models in Natural
Language Processing (NLP), exhibits diverse applications in the field of
anomaly detection. To inspire research on Transformer-based anomaly detection,
this review offers a fresh perspective on the concept of anomaly detection. We
explore the current challenges of anomaly detection and provide detailed
insights into the operating principles of Transformer and its variants in
anomaly detection tasks. Additionally, we delineate various application
scenarios for Transformer-based anomaly detection models and discuss the
datasets and evaluation metrics employed. Furthermore, this review highlights
the key challenges in Transformer-based anomaly detection research and conducts
a comprehensive analysis of future research trends in this domain. The review
includes an extensive compilation of over 100 core references related to
Transformer-based anomaly detection. To the best of our knowledge, this is the
first comprehensive review that focuses on the research related to Transformer
in the context of anomaly detection. We hope that this paper can provide
detailed technical information to researchers interested in Transformer-based
anomaly detection tasks.


  Large time-domain surveys provide a unique opportunity to detect and explore
variability of millions of sources on timescales from days to years. Broadband
photometric variability can be used as the key selection criteria for weak
type-I active galactic nuclei (AGN), when other "direct" confirmation criteria
like X-ray or radio emission are unavailable. However, to detect variability of
rather weak AGN powered by intermediate-mass black holes, typical sensitivity
provided by existing light curve databases is insufficient. Here we present an
algorithm for post-processing of light curves for sources with stochastic
variability, retrieved from the The Zwicky Transient Facility (ZTF) Forced
Photometry service. Using our approach, we can filter out spurious data points
related to data reduction artefacts and also eliminate long-term trends related
to imperfect photometric calibration. We can now confidently detect the
broad-band variability at the 1-3 $\%$ level which can potentially be used as a
substitute for expensive X-ray follow-up observations.


  High resolution spectra of stars in the ~200 Myr LMC globular cluster, NGC
1866, reveal rapidly rotating stars with variable H-alpha emission and
absorption, and signatures of outflowing material. The variable H-alpha line
can substanti ally affect photometric measurements obtained with HST/WFC3
narrow-band filters.


  Calculations are made of the $K^{+}+^{12}$C, $^{40}$Ca differential elastic
scattering cross sections at the beam momenta 0.635, 0.715, and 0.8 GeV/c. To
this end the microscopic optical potential derived in the high-energy
approximation was used where existing data on the kaon-nucleon amplitude and on
the point-like density distributions of target-nuclei were utilized. The effect
of different methods of relativization was studied and shown to play an
important role. A good agreement with the experimental data on differential
elastic cross sections was obtained.


  We have proposed a regularization technique and apply it to the Euler product
of zeta functions in the part one. In this paper that is the second part of the
trilogy, we give another evidence to demonstrate the Riemann hypotheses by
using the approximate functional equation. Some other results on the critical
line are also presented using the relations between the Euler product and the
deformed summation representions in the critical strip. In part three, we will
focus on physical applications using these outcomes.


  One can typically form a local robustness metric for a particular problem
quite directly, for Markov chain Monte Carlo applications as well as
optimization problems such as variational Bayes. However, we argue that simply
forming a local robustness metric is not enough: the hard work is showing that
it is useful. Computability, interpretability, and the ability of a local
robustness metric to extrapolate well, are more important -- and often more
difficult to establish -- than mere computation of derivatives.


  The Newton-Hooke algebras in d dimensions are constructed as contractions of
dS(AdS) algebras. Non-relativistic brane actions are WZ terms of these
Newton-Hooke algebras. The NH algebras appear also as subalgebras of
multi-temporal relativistic conformal algebras, SO(d+1, p+2). We construct
generalizations of pp-wave metrics from these algebras.


  In this paper, we give a form of refined Roth's theorem. As an application,
we prove a special case of the $abc$-conjecture.