  We give a mathematical formalization of `generalized data parallel'
operations, a concept that covers such common scientific kernels as
matrix-vector multiplication, multi-grid coarsening, load distribution, and
many more. We show that from a compact specification such computational aspects
as MPI messages or task dependencies can be automatically derived.


  Stochastic modelling is an essential component of the quantitative sciences,
with hidden Markov models (HMMs) often playing a central role. Concurrently,
the rise of quantum technologies promises a host of advantages in computational
problems, typically in terms of the scaling of requisite resources such as time
and memory. HMMs are no exception to this, with recent results highlighting
quantum implementations of deterministic HMMs exhibiting superior memory and
thermal efficiency relative to their classical counterparts. In many contexts
however, non-deterministic HMMs are viable alternatives; compared to them the
advantages of current quantum implementations do not always hold. Here, we
provide a systematic prescription for constructing quantum implementations of
non-deterministic HMMs that re-establish the quantum advantages against this
broader class. Crucially, we show that whenever the classical implementation
suffers from thermal dissipation due to its need to process information in a
time-local manner, our quantum implementations will both mitigate some of this
dissipation, and achieve an advantage in memory compression.


  In this paper, we will present p roposed enhance process of image compression
by using RLE algorithm. This proposed yield to decrease the size of compressing
image, but the original method used primarily for compressing a binary images
[1].Which will yield increasing the size of an original image mostly when used
for color images. The test of an enhanced algorithm is performed on sample
consists of ten BMP 24-bit true color images, building an application by using
visual basic 6.0 to show the size after and before compression process and
computing the compression ratio for RLE and for the enhanced RLE algorithm.


  Low rank tensor completion is a highly ill-posed inverse problem,
particularly when the data model is not accurate, and some sort of
regularization is required in order to solve it. In this article we focus on
the calibration of the data model. For alternating optimization, we observe
that existing rank adaption methods do not enable a continuous transition
between manifolds of different ranks. We denote this characteristic as
$\textit{instability (under truncation)}$. As a consequence of this property,
arbitrarily small changes in the iterate can have arbitrarily large influence
on the further reconstruction. We therefore introduce a singular value based
regularization to the standard alternating least squares (ALS), which is
motivated by averaging in microsteps. We prove its $\textit{stability}$ and
derive a natural semi-implicit rank adaption strategy. We further prove that
the standard ALS microsteps for completion problems are only stable on
manifolds of fixed ranks, and only around points that have what we define as
$\textit{internal tensor restricted isometry property, iTRIP}$. In conclusion,
numerical experiments are provided that show improvements of the reconstruction
quality up to orders of magnitude in the new Stable ALS Approximation (SALSA)
compared to standard ALS and the well known Riemannian optimization RTTC.


  The potential harms of the under-representation of minorities in training
data, particularly in multi-modal settings, is a well-recognized concern. While
there has been extensive effort in detecting such under-representation,
resolution has remained a challenge. With recent advancements in generative AI,
large language models and foundation models have emerged as versatile tools
across various domains. In this paper, we propose Chameleon, a system that
efficiently utilizes these tools to augment a data set with a minimal addition
of synthetically generated tuples, in order to enhance the coverage of the
under-represented groups. Our system follows a rejection sampling approach to
ensure the generated tuples have a high quality and follow the underlying
distribution. In order to minimize the rejection chance of the generated
tuples, we propose multiple strategies for providing a guide for the foundation
model. Our experiment results, in addition to confirming the efficiency of our
proposed algorithms, illustrate the effectiveness of our approach, as the
unfairness of the model in a downstream task significantly dropped after data
repair using Chameleon.


  Gene/protein interactions provide critical information for a thorough
understanding of cellular processes. Recently, considerable interest and effort
has been focused on the construction and analysis of genome-wide gene networks.
The large body of biomedical literature is an important source of gene/protein
interaction information. Recent advances in text mining tools have made it
possible to automatically extract such documented interactions from free-text
literature. In this paper, we propose a comprehensive framework for
constructing and analyzing large-scale gene functional networks based on the
gene/protein interactions extracted from biomedical literature repositories
using text mining tools. Our proposed framework consists of analyses of the
network topology, network topology-gene function relationship, and temporal
network evolution to distill valuable information embedded in the gene
functional interactions in literature. We demonstrate the application of the
proposed framework using a testbed of P53-related PubMed abstracts, which shows
that literature-based P53 networks exhibit small-world and scale-free
properties. We also found that high degree genes in the literature-based
networks have a high probability of appearing in the manually curated database
and genes in the same pathway tend to form local clusters in our
literature-based networks. Temporal analysis showed that genes interacting with
many other genes tend to be involved in a large number of newly discovered
interactions.


  Online (also called "recursive" or "adaptive") estimation of fixed model
parameters in hidden Markov models is a topic of much interest in times series
modelling. In this work, we propose an online parameter estimation algorithm
that combines two key ideas. The first one, which is deeply rooted in the
Expectation-Maximization (EM) methodology consists in reparameterizing the
problem using complete-data sufficient statistics. The second ingredient
consists in exploiting a purely recursive form of smoothing in HMMs based on an
auxiliary recursion. Although the proposed online EM algorithm resembles a
classical stochastic approximation (or Robbins-Monro) algorithm, it is
sufficiently different to resist conventional analysis of convergence. We thus
provide limited results which identify the potential limiting points of the
recursion as well as the large-sample behavior of the quantities involved in
the algorithm. The performance of the proposed algorithm is numerically
evaluated through simulations in the case of a noisily observed Markov chain.
In this case, the algorithm reaches estimation results that are comparable to
that of the maximum likelihood estimator for large sample sizes.


  The motility-induced phase separation (MIPS) phenomenon in active matter has
been of great interest for the past decade or so. A central conceptual puzzle
is that this behavior, which is generally characterized as a nonequilibrium
phenomenon, can yet be explained using simple equilibrium models of
thermodynamics. Here, we address this problem using a new theory, statistical
teleodynamics, which is a conceptual synthesis of game theory and statistical
mechanics. In this framework, active agents compete in their pursuit of maximum
effective utility, and this self-organizing dynamics results in an arbitrage
equilibrium in which all agents have the same effective utility. We show that
MIPS is an example of arbitrage equilibrium and that it is mathematically
equivalent to other phase-separation phenomena in entirely different domains,
such as sociology and economics. As examples, we present the behavior of Janus
particles in a potential trap and the effect of chemotaxis on MIPS.


  The generalization mystery of overparametrized deep nets has motivated
efforts to understand how gradient descent (GD) converges to low-loss solutions
that generalize well. Real-life neural networks are initialized from small
random values and trained with cross-entropy loss for classification (unlike
the "lazy" or "NTK" regime of training where analysis was more successful), and
a recent sequence of results (Lyu and Li, 2020; Chizat and Bach, 2020; Ji and
Telgarsky, 2020) provide theoretical evidence that GD may converge to the
"max-margin" solution with zero loss, which presumably generalizes well.
However, the global optimality of margin is proved only in some settings where
neural nets are infinitely or exponentially wide. The current paper is able to
establish this global optimality for two-layer Leaky ReLU nets trained with
gradient flow on linearly separable and symmetric data, regardless of the
width. The analysis also gives some theoretical justification for recent
empirical findings (Kalimeris et al., 2019) on the so-called simplicity bias of
GD towards linear or other "simple" classes of solutions, especially early in
training. On the pessimistic side, the paper suggests that such results are
fragile. A simple data manipulation can make gradient flow converge to a linear
classifier with suboptimal margin.


  Two-dimensional Dirac semimetals have attracted much attention because of
their linear energy dispersion and non-trivial Berry phase. Graphene-like 2D
Dirac materials are gapless only within certain approximations, e.g., if
spin-orbit coupling (SOC) is neglected. It has recently been reported that
materials with nonsymmorphic crystal lattice possess symmetry-enforced
Dirac-like band dispersion around certain high-symmetry momenta even in the
presence of SOC. Here we calculate the optical absorption coefficient of
nonsymmorphic semimetals, such as $\alpha$-bismuthene, which hosts two
anisotropic Dirac cones with different Fermi velocities along $x$ and $y$
directions.We find that the optical absorption coefficient depends strongly on
the anisotropy factor and the photon polarization. When a magnetic field is
applied perpendicular to the plane of the material, the absorption coefficient
also depends on an internal parameter we termed the mixing angle of the band
structure. We further find that an in-plane magnetic field, while leaving the
system gapless, can induce a Van-Hove singularity in the joint density of
states: this causes a significant enhancement of the optical absorption at the
frequency of the singularity for one direction of polarization but not for the
orthogonal one, making the optical properties even more strongly dependent on
polarization. Due to the anisotropy present in our model, the Dirac cones at
two high-symmetry momenta in the Brillouin zone contribute very differently to
the optical absorbance. Consequently, it might be possible to preferentially
populate one valley or the other by varying photon polarization and frequency.
These results suggest that nonsymmorphic 2D Dirac semimetals are excellent
candidate materials for tunable magneto-optic devices.


  With unprecedented angular resolution, the Event Horizon Telescope (EHT) has
opened a new era of black holes. We have previously calculated the expected
polarization images of M87* with the EHT observations in mind. There, we
demonstrated that circular polarization (CP) images, as well as the linear
polarization (LP) maps, can convey quite useful information to us, such as the
flow structure and magnetic field configuration around the black hole. In this
paper, we make new predictions for the cases in which disk emission dominates
over jet emission, bearing Sgr A* in mind. Here we set the proton-to-electron
temperature ratio of the disk component to be Tp/Te $\sim$ 2 so as to suppress
jet emission relative to emission from accretion flow. As a result, we obtain
ring-like images and triple-forked images around the black hole for face-on and
edge-on cases, respectively. We also find significant CP components in the
images ($\gtrsim 10\%$ in fraction), both with positive and negative signs,
amplified through the Faraday conversion, not sensitively depending on the
inclination angles. Furthermore, we find a "separatrix" in the CP images,
across which the sign of CP is reversed and on which the LP flux is brightest,
that can be attributed to the helical magnetic field structure in the disk.
These results indicate that future full polarization EHT images are a quite
useful tracer of the magnetic field structure. We also discuss to what extent
we will be able to extract information regarding the magnetic field
configurations, under the scattering in the interstellar plasma, in future EHT
polarimetric observations of Sgr A*.


  A theoretical study is presented on the scattering of graphene surface
plasmons by defects in the graphene sheet they propagate in. These defects can
be either natural (as domain boundaries, ripples and cracks, among others) or
induced by an external gate. The scattering is shown to be governed by an
integral equation, derived from a plane wave expansion of the fields, which in
general must be solved numerically but it provides useful analytical results
for small defects. Two main cases are considered: smooth variations of the
graphene conductivity (characterized by a Gaussian conductivity profile) and
sharp variations (represented by islands with different conductivity). In
general, reflection largely dominates over radiation out of the graphene sheet.
However, in the case of sharply defined conductivity islands there are some
values of island size and frequency where the reflectance vanishes and,
correspondingly, the radiation out of plane is the main scattering process. For
smooth defects, the reflectance spectra present a single maximum at the
condition $k_p a \approx \sqrt{2}$, where $k_p$ is the GSP wavevector and $a$
the spatial width of the defect. In contrast, the reflectance spectra of sharp
defects present periodic oscillations with period $k_p' a$, where $k_p'$ is the
GSP wavelength inside the defect. Finally, the case of cracks (gaps in the
graphene conductivity) is considered, showing that the reflectance is
practically unity for gap widths larger than one tenth of the GSP wavelength.


  The properties of a two-dimensional (2D) electron system can be drastically
altered by a magnetic field applied perpendicular to the 2D plane. In
particular, the frequency of its bulk collective excitations becomes gaped at
the cyclotron frequency, while the low-frequency localized excitations, the
edge magnetoplasmon (EMP), appear near the system's edge. A new type of the
delocalized low-frequency excitations, the gradient magnetoplasmon (GMP), was
recently shown to exist in a 2D electron system with a linear density gradient
that breaks the system's cylindrical symmetry [Phys. Rev. B \textbf{103},
075420 (2021)]. Like EMP, these new excitations are gapless and chiral, and
originate from the classical Hall effect. Here we show that a similar
magnetoplasmon mode can exist in a system with strongly-inhomogeneous radial
distribution of the electron density that preserves the cylindrical symmetry.
This is experimentally demonstrated in a pristine system of surface electrons
on liquid helium and is confirmed by a numerical simulation. This result
extends the variety of known collective excitations in a 2D charge system and
presents electrons on helium as a promising model system for their study.


  We discuss the possibility to extend the spectral action up to energy close
to the Planck scale, taking also into account the gravitational effects given
by graviton exchange. Including this contribution in the theory, the coupling
constant unification is not compromised, but is shifted to the Planck scale
rendering all gauge couplings asymptotically free. In the scheme of
noncommutative geometry, the gravitational effects change the main standard
model coupling constants, leading to a restriction of the free parameters of
the theory compatible with the Higgs and top mass prediction. We also discuss
consequences for the neutrino mass and the see-saw mechanism.


  In this article, we derive the fermionic formalism of Hamiltonians as well as
corresponding excitation spectrums and states of Calogero-Sutherland(CS),
Laughlin and Halperin systems, respectively. In addition, we study the
triangular property of these Hamiltonians and prove the integrability in these
three cases.


  This paper gives a new, simple proof of the known fact that for contact
processes on general lattices, in the subcritical regime the expected number of
infected sites decays exponentially fast as time tends to infinity. The proof
also yields an explicit bound on the survival probability below the critical
recovery rate, which shows that the critical exponent associated with this
function is bounded from below by its mean-field value. The main idea of the
proof is that if the expected number of infected sites decays slower than
exponentially, then this implies the existence of a harmonic function that can
be used to show that the process survives for any lower value of the recovery
rate.


  In this Letter, we investigate the long-duration quasi-static evolution of 12
pre-eruptive filaments (4 active region and 8 quiescent filaments), mainly
focusing on the evolution of the filament height in three dimension (3D) and
the decay index of the background magnetic field. The filament height in 3D is
derived through two-perspective observations of \textit{Solar Dynamics
Observatory} and \textit{Solar TErrestrial RElations Observatory}. The coronal
magnetic field is reconstructed using the potential field source surface model.
A new finding is that the filaments we studied show two types of long-duration
evolution: one type is comprised of a long-duration static phase and a short
slow rise phase with a duration of less than 12 hours and a speed of 0.1--0.7
km s$^{-1}$, while the other one only presents a slow rise phase but with an
extremely long duration of more than 60 hours and a smaller speed of 0.01--0.2
km s$^{-1}$. At the moment approaching the eruption, the decay index of the
background magnetic field at the filament height is similar for both active
region and quiescent filaments. The average value and upper limit are $\sim$0.9
and $\sim$1.4, close to the critical index of torus instability. Moreover, the
filament height and background magnetic field strength are also found to be
linearly and exponentially related with the filament length, respectively.


  These notes are an expanded version of the author's lectures at the graduate
workshop "Noncommutative Algebraic Geometry" at the Mathematical Sciences
Research Institute in June 2012. The main topics discussed are Artin-Schelter
regular algebras, point modules, and the noncommutative projective scheme
associated to a graded algebra.


  While physiological sensors enter the mass market and reach the general
public, they are still mainly employed to monitor health -- whether it is for
medical purpose or sports. We describe an application that uses heart rate
feedback as an incentive for social interactions. A traditional board game has
been "augmented" through remote physiological sensing, using webcams.
Projection helped to conceal the technological aspects from users. We detail
how players reacted -- stressful situations could emerge when users are
deprived from their own signals -- and we give directions for game designers to
integrate physiological sensors.


  Using molecular dynamics we study the dependence of the friction force on the
sliding speed when an elastic slab (block) is sliding on a rigid substrate with
a ${\rm sin} (q_0 x)$ surface height profile. The friction force is nearly
velocity independent due to phonon emission at the closing and opening crack
tips, where rapid atomic snap-in and -out events occur during sliding. The
rapid events result from lattice trapping and are closely related to the
velocity gap and hysteresis effects observed in model studies of crack
propagation in solids. This indicates that the friction force is dominated by
processes occurring at the edges of the contact area, which is confirmed by
calculations showing that the friction force is independent of the normal
force. The friction force increases drastically when the sliding velocity
approaches the solid transverse sound velocity, as expected from the theory of
cracks.


  We consider the problem of how to regulate an oligopoly when firms have
private information about their costs. In the environment, consumers make
discrete choices over goods, and minimal structure is placed on the manner in
which firms compete. In the optimal regulatory policy, the regulator need only
solicit prices from firms, and based on those prices, charge them taxes or give
them subsidies, and impose on each firm a ``yardstick'' price cap that depends
on the posted prices of competing firms.


  In this paper we establish the uniformity property of a simplified
Ericksen-Leslie system modelling the hydrodynamics of nematic liquid crystals
on the two dimensional unit sphere $S^2$, namely the uniform convergence in
$L^2$ to a steady state exponentially as t tends to infinity. The main
assumption, similar to Topping [15], concerns the equation of liquid crystal
director $d$ and states that at infinity time, a weak limit $d_\infty$ and any
bubble $\omega_i$($1\le i\le l$) share a common orientation. As consequences,
the uniformity property holds under various types of small initial data.


  Under the standard perturbation theory (SPT), we obtain the fully consistent
third-order density fluctuation and kernels for the general dark energy models
without using the Einstein-de Sitter (EdS) universe assumption for the first
time. We also show that even though the temporal and spatial components of the
SPT solutions can not be separable, one can find the exact solutions to any
order in general dark energy models. With these exact solutions, we obtain the
less than \% error correction of one-loop matter power spectrum compared to
that obtained from the EdS assumption for $k = 0.1 {\rm h\, Mpc}^{-1}$ mode at
$z = 0$ (1, 1.5). Thus, the EdS assumption works very well at this scale.
However, if one considers the correction for $P_{13}$, the error is about 6 (9,
11) \% for the same mode at $z = 0$ (1, 1.5). One absorbs $P_{13}$ into the
linear power spectrum in the renormalized perturbation theory (RPT) and thus
one should use the exact solution instead of the approximation one. The error
on the resummed propagator $N$ of RPT is about 14 (8, 6) \% at $z =0$ (1, 1.5)
for $k = 0.4 {\rm h\, Mpc}^{-1}$. For $k = 1 {\rm h\, Mpc}^{-1}$, the error
correction of the total matter power spectrum is about 3.6 (4.6, 4.5) \% at $z
= 0$ (1, 1.5). Upcoming observation is required to archive the sub-percent
accuracy to provide the strong constraint on the dark energy and this
consistent solution is prerequisite for the model comparison.


  Translation of proteins is a fundamental part of gene expression that is
mediated by ribosomes. As ribosomes significantly contribute to both cellular
mass and energy consumption, achieving efficient management of the ribosome
population is also crucial to metabolism and growth. Inspired by biological
evidence for nutrient-dependent mechanisms that control both ribosome active
degradation and genesis, we introduce a dynamical model of protein production,
that includes the dynamics of resources and control over the ribosome
population. Under the hypothesis that active degradation and biogenesis are
optimal for maximizing and maintaining protein production, we aim to
qualitatively reproduce empirical observations of the ribosome population
dynamics. Upon formulating the associated optimization problem, we first
analytically study the stability and global behaviour of solutions under
constant resource input, and characterize the extent of oscillations and
convergence rate to a global equilibrium. We further use these results to
simplify and solve the problem under a quasi-static approximation. Using
biophysical parameter values, we find that optimal control solutions lead to
both control mechanisms and the ribosome population switching between periods
of feeding and fasting, suggesting that the intense regulation of ribosome
population observed in experiments allows to maximize and maintain protein
production. Finally, we find some range for the control values over which such
a regime can be observed, depending on the intensity of fasting.


  The $\Pi$-operator (Ahlfors-Beurling transform) plays an important role in
solving the Beltrami equation. In this paper we define two $\Pi$-operators on
the n-sphere. The first spherical $\Pi$-operator is shown to be an $L^2$
isometry up to isomorphism. To improve this, with the help of the spectrum of
the spherical Dirac operator, the second spherical $\Pi$ operator is
constructed as an isometric $L^2$ operator over the sphere. Some analogous
properties for both $\Pi$-operators are also developed. We also study the
applications of both spherical $\Pi$-operators to the solution of the spherical
Beltrami equations.


  Colloidal gels are elasto-plastic materials composed of an
out-of-equilibrium, self-assembled network of micron-sized (solid) particles
suspended in a fluid. Recent work has shown that far-field hydrodynamic
interactions do not change gel structure, only the rate at which the network
forms and ages. However, during gel formation, the interplay between
short-ranged attractions leading to gelation and equally short-ranged
hydrodynamic lubrication interactions remains poorly understood. Here, we
therefore study gelation using a range of hydrodynamic descriptions: from
single-body (Brownian Dynamics), to pairwise (Rotne-Prager-Yamakawa), to
(non-)lubrication-corrected many-body (Stokesian Dynamics). We confirm the
current understanding informed by simulations accurate in the far-field. Yet,
we find that accounting for lubrication can strongly impact structure at low
colloid volume fraction. Counterintuitively, strongly dissipative lubrication
interactions also accelerate the aging of a gel, irrespective of colloid volume
fraction. Both elements can be explained by lubrication forces facilitating
collective dynamics and therefore phase-separation. Our findings indicate that
despite the computational cost, lubricated hydrodynamic modeling with many-body
far-field interactions is needed to accurately capture the evolution of the gel
structure.


  The dynamics and stability of a thin gas layer moving between two fluid
layers moving in the same or opposite direction is studied. The linear
evolutionary equations describing the spatial-temporal dynamics of the
interface perturbations between gas and two fluid layers are derived for the
flat two-dimensional case. Integral correlations across the layer are obtained,
and the various kinds of time dependent base states are found. A linear
stability is considered for the system using non-stationary equation array
derived. The equation array consists of the two one-dimensional non-stationary
equations of a seventh and fourth order. The results of the numerical study of
the governing evolution equations support the results of the analysis for more
simple limit cases. It is found that the thin sheet gas flow in-between two
liquid layers is unstable and the peculiarities are found and discussed
together with some applications available.


  Faraday rotation is a fundamental property present in all non-reciprocal
optical elements. In the THz range, graphene displays strong Faraday rotation;
unfortunately, it is limited to frequencies below the cyclotron resonance. Here
we show experimentally that in specifically design metasurfaces,
magneto-plasmons can be used to circumvent this limitation. We find excellent
agreement between theory and experiment and provide new physical insights and
predictions on these phenomena. Finally, we demonstrate strong tuneability in
these metasurfaces using electric and magnetic field biasing.


  Large language models are powerful text processors and reasoners, but are
still subject to limitations including outdated knowledge and hallucinations,
which necessitates connecting them to the world. Retrieval-augmented large
language models have raised extensive attention for grounding model generation
on external knowledge. However, retrievers struggle to capture relevance,
especially for queries with complex information needs. Recent work has proposed
to improve relevance modeling by having large language models actively involved
in retrieval, i.e., to improve retrieval with generation. In this paper, we
show that strong performance can be achieved by a method we call Iter-RetGen,
which synergizes retrieval and generation in an iterative manner. A model
output shows what might be needed to finish a task, and thus provides an
informative context for retrieving more relevant knowledge which in turn helps
generate a better output in the next iteration. Compared with recent work which
interleaves retrieval with generation when producing an output, Iter-RetGen
processes all retrieved knowledge as a whole and largely preserves the
flexibility in generation without structural constraints. We evaluate
Iter-RetGen on multi-hop question answering, fact verification, and commonsense
reasoning, and show that it can flexibly leverage parametric knowledge and
non-parametric knowledge, and is superior to or competitive with
state-of-the-art retrieval-augmented baselines while causing fewer overheads of
retrieval and generation. We can further improve performance via
generation-augmented retrieval adaptation.


  The behavior of general nonclassical two-mode Gaussian states at a beam
splitter is investigated. Single-mode nonclassicality as well as two-mode
entanglement of both input and output states are analyzed suggesting their
suitable quantifiers. These quantifiers are derived from local and global
invariants of linear unitary two-mode transformations such that the sum of
input (or output) local nonclassicality measures and entanglement measure gives
a global invariant. This invariant quantifies the global nonclassicality
resource. Mutual transformations of local nonclassicalities and entanglement
induced by the beam splitter are analyzed considering incident noisy twin
beams, single-mode noisy squeezed vacuum states, and states encompassing both
squeezed states and twin beams. A rich tapestry of interesting nonclassical
output states is predicted.


  In this paper we introduce some new copulas emerging from shock models. It
was shown earlier that reflected maxmin copulas (RMM for short) are not just
some specific singular copulas; they contain many important absolutely
continuous copulas including the negative quadrant dependent part of the
Eyraud-Farlie-Gumbel-Morgenstern class. The main goal of this paper is to
develop the RMM copulas with dependent endogenous shocks and give evidence that
RMM copulas may exhibit some characteristics better than the original maxmin
copulas (MM for short): (1) An important evidence for that is the iteration
procedure of the RMM transformation which we prove to be always convergent and
we give many properties of it that are useful in applications. (2) Using this
result we find also the limit of the iteration procedure of the MM
transformation thus answering a question proposed earlier by Durante,
Omladi\v{c}, Ora\v{z}em, and Ru\v{z}i\'{c}. (3) We give the multivariate
dependent RMM copula that compares to the MM version given by Durante,
Omladi\v{c}, Ora\v{z}em, and Ru\v{z}i\'{c}. In all our copulas the
idiosyncratic and systemic shocks are combined via asymmetric linking functions
as opposed to Marshall copulas where symmetric linking functions are used.


  In this paper, we derive the joint Laplace transforms of occupation times
until its last passage times as well as its positions. Motivated by Baurdoux
[2], the last times before an independent exponential variable are studied. By
applying dual arguments, explicit formulas are derived in terms of new
analytical identities from Loeffen et al. [12].


  We study the problem of assigning $K$ identical servers to a set of $N$
parallel queues in a time-slotted queueing system. The connectivity of each
queue to each server is randomly changing with time; each server can serve at
most one queue and each queue can be served by at most one server during each
time slot. Such a queueing model has been used in addressing resource
allocation problems in wireless networks. It has been previously proven that
Maximum Weighted Matching (MWM) is a throughput-optimal server assignment
policy for such a queueing system. In this paper, we prove that for a system
with i.i.d. Bernoulli packet arrivals and connectivities, MWM minimizes, in
stochastic ordering sense, a broad range of cost functions of the queue lengths
such as total queue occupancy (which implies minimization of average queueing
delays). Then, we extend the model by considering imperfect services where it
is assumed that the service of a scheduled packet fails randomly with a certain
probability. We prove that the same policy is still optimal for the extended
model. We finally show that the results are still valid for more general
connectivity and arrival processes which follow conditional permutation
invariant distributions.


  Neural sequence-to-sequence automatic speech recognition (ASR) systems are in
principle open vocabulary systems, when using appropriate modeling units. In
practice, however, they often fail to recognize words not seen during training,
e.g., named entities, numbers or technical terms. To alleviate this problem,
Huber et al. proposed to supplement an end-to-end ASR system with a word/phrase
memory and a mechanism to access this memory to recognize the words and phrases
correctly. In this paper we study, a) methods to acquire important words for
this memory dynamically and, b) the trade-off between improvement in
recognition accuracy of new words and the potential danger of false alarms for
those added words. We demonstrate significant improvements in the detection
rate of new words with only a minor increase in false alarms (F1 score 0.30
$\rightarrow$ 0.80), when using an appropriate number of new words. In
addition, we show that important keywords can be extracted from supporting
documents and used effectively.


  The phonon-mode decomposition of the electron-phonon coupling in the
MgB2-like system Li_{1-x}BC is explored using first principles calculations. It
is found that the high temperature superconductivity of such systems results
from extremely strong coupling to only ~2% of the phonon modes. Novel
characteristics of E_2g branches include (1) ``mode lambda'' values of 25 and
greater compared to a mean of $\sim 0.4$ for other modes, (2) a precipitous
Kohn anomaly, and (3) E_2g phonon linewidths within a factor of ~2 of the
frequency itself, indicating impending breakdown of linear electron-phonon
theory. This behavior in borne out by recent inelastic x-ray scattering studies
of MgB2 by Shukla et al.


  We compute the leading-order inertial corrections to the instantaneous force
acting on a rigid body moving with a time-dependent slip velocity in a linear
flow field, assuming that the variation of the undisturbed flow at the body
scale is much larger than the slip velocity between the body and the fluid.
Motivated by applications to turbulent particle-laden flows, we seek a
formulation allowing this force to be determined for an arbitrarily-shaped body
moving in a general linear flow. We express the equations governing the flow
disturbance in a non-orthogonal coordinate system moving with the undisturbed
flow and solve the problem using matched asymptotic expansions. The use of the
co-moving coordinates enables the leading-order inertial corrections to the
force to be obtained at any time in an arbitrary linear flow field. We then
specialize this approach to compute the time-dependent force components for a
sphere moving in three canonical flows: solid body rotation, planar elongation,
and uniform shear. We discuss the behaviour and physical origin of the
different force components in the short-time and quasi-steady limits. Last, we
illustrate the influence of time-dependent and quasi-steady inertial effects by
examining the sedimentation of prolate and oblate spheroids in a pure shear
flow.


  Single-cell RNA-sequencing (scRNA-seq) stands as a powerful tool for
deciphering cellular heterogeneity and exploring gene expression profiles at
high resolution. However, its high cost renders it impractical for extensive
sample cohorts within routine clinical care, hindering its broader
applicability. Hence, many methodologies have recently arised to estimate cell
type proportions from bulk RNA-seq samples (known as deconvolution methods).
However, they have several limitations: Many depend on selecting a robust
scRNA-seq reference dataset, which is often challenging. Secondly, building
reliable pseudobulk samples requires determining the optimal number of genes or
cells involved in the simulated data generation process, which has not been
studied in depth. Moreover, pseudobulk and bulk RNA-seq samples often exhibit
distribution shifts. Finally, most modern deconvolution approaches behave as a
black box, and the underlying mechanisms of the deconvolution task are still
unknown, which can compromise the reliability of the results. In this work, we
present Sweetwater, an adaptive and interpretable autoencoder able to
efficiently deconvolve bulk RNA-seq and microarray samples leveraging multiple
classes of reference data, such as scRNA-seq and single-nuclei RNA-seq.
Moreover, it can be trained on a mixture of FACS-sorted FASTQ files, which we
newly propose to use as this reduces platform-specific biases and may
potentially outperform single-cell-based references. Also, we demonstrate that
Sweetwater effectively uncovers biologically meaningful patterns during the
training process, increasing the reliability of the results. Sweetwater is
available at https://github.com/ubioinformat/Sweetwater, and we anticipate will
facilitate and expedite the accurate examination of high-throughput clinical
data across diverse applications.


A sketch based 3D shape retrieval


  Experimental and numerical studies of spatiotemporal femtosecond soliton
propagation over up to 1 km spans of parabolic graded-index (GRIN) fibers
reveal that initial multimode soliton pulses naturally and irreversibly evolve
into a singlemode soliton. This is carried by the fundamental mode of the
fiber, which acts as a dynamical attractor of the multimode system for up to
the record value (for multimode fibers) of 5600 chromatic dispersion distances.
This experimental evidence invalidates the use of variational approaches, which
intrinsically require that the initial multimode propagation of a self-imaging
soliton is indefinitely maintained.


  One can simplify the triad formulations of canonical gravity by abandoning
any relation to a fixed coordinate system. That means in case of the \ADM
formalism that one can determine the momentum by direct derivation of the
Lagrange-3-form w.r.t the time-derivative of the triad-1-forms, thus the
momentum is most naturally a 2-form. We apply this concept to the Palatini
formulation where we can closely follow Dirac's concept to find and eliminate
the second class constraints. Following the same way for the Ashtekar theory it
will turn out to be equivalent to two successive canonical transformations
where the first makes explicit use of the spatial dimension being 3 and the
second is usually hidden in the use of densities. At the end we can give a
simple version of the reality constraints.


  We report a study of the photoconductivity (PC) induced in different types of
diamonds (type IIa single crystals and CVD) by femtosecond XUV pulses (high
order harmonics - up to 19th - of a titanium doped laser). We also reprot UPS
spectras obtained with harmonics 13 to 29. Depending on the harmonic's order,
the PC signal first increases (orders 9 to 13) and then decreases. If the
increase is easily interpreted as resulting from a carrier multiplication
process, the further decrease has not yet received an explanation. The UPS
measurements also suggest a strong effect of the plasmon relaxation on the
carrier multiplication process. Finally, we performed a preliminary GW
ab-initio calculation of the carriers lifetime, acounting for electron-electron
interactions. In the near-bandgap region, it behaves approximatively according
to the Fermi-liquid model, from which it strongly departs at higher energies,
which is attributed to band-structure effects and to plasmon excitations.


  An extensive study of population control techniques (PCTs) for time-dependent
and eigenvalue Monte Carlo (MC) neutron transport calculations is presented. We
define PCT as a technique that takes a censused population and returns a
controlled, unbiased population. A new perspective based on an abstraction of
particle census and population control is explored, paving the way to improved
understanding and application of the concepts. Five distinct PCTs identified
from the literature are reviewed: Simple Sampling (SS), Splitting-Roulette
(SR), Combing (CO), modified Combing (COX), and Duplicate-Discard (DD). A
theoretical analysis of how much uncertainty is introduced to a population by
each PCT is presented. Parallel algorithms for the PCTs applicable for both
time-dependent and eigenvalue MC simulations are proposed. The relative
performances of the PCTs based on runtime and tally mean error or standard
deviation are assessed by solving time-dependent and eigenvalue test problems.
It is found that SR and CO are equally the most performant techniques, closely
followed by DD.


  An overview of jet production, measurement techniques, and recent physics
results from colliders is presented. Analyses utilizing jets and boson plus
jets final states are included and implications of the data are discussed. The
results presented here are a snapshot of those available at the time of the PIC
2012 conference in September 2012.


  We study the possibility that the approximate time shift symmetry during
inflation is promoted to the full invariance under time reparametrization t \to
\tilde t(t), or equivalently under field redefinition of the inflaton \phi \to
\tilde\phi(\phi). The symmetry allows only two operators at leading order in
derivatives, so that all n-point functions of scalar perturbations are fixed in
terms of the power spectrum normalization and the speed of sound. During
inflation the decaying mode only decays as 1/a and this opens up the
possibility to violate some of the consistency relations in the squeezed limit,
although this violation is suppressed by the (small) breaking of the field
reparametrization symmetry. In particular one can get terms in the 3-point
function that are only suppressed by 1/k_L in the squeezed limit k_L \to 0
compared to the local shape.


  Let G be a linear algebraic group over the field of real numbers R, and let Y
be a right homogeneous space of G. We wish to find a real point of Y or to
prove that Y has no real points. We describe a method to do that, implicitly
using second nonabelian Galois cohomology. Our method is suitable for
computer-assisted calculations.


  In this paper, we complement Verd\'{u}'s work on spectral efficiency in the
wideband regime by investigating the fundamental tradeoff between rate and
bandwidth when a constraint is imposed on the error exponent. Specifically, we
consider both AWGN and Rayleigh-fading channels. For the AWGN channel model,
the optimal values of $R_z(0)$ and $\dot{R_z}(0)$ are calculated, where
$R_z(1/B)$ is the maximum rate at which information can be transmitted over a
channel with bandwidth $B/2$ when the error-exponent is constrained to be
greater than or equal to $z.$ Based on this calculation, we say that a sequence
of input distributions is near optimal if both $R_z(0)$ and $\dot{R_z}(0)$ are
achieved. We show that QPSK, a widely-used signaling scheme, is near-optimal
within a large class of input distributions for the AWGN channel. Similar
results are also established for a fading channel where full CSI is available
at the receiver.


  A framework for unsupervised group activity analysis from a single video is
here presented. Our working hypothesis is that human actions lie on a union of
low-dimensional subspaces, and thus can be efficiently modeled as sparse linear
combinations of atoms from a learned dictionary representing the action's
primitives. Contrary to prior art, and with the primary goal of spatio-temporal
action grouping, in this work only one single video segment is available for
both unsupervised learning and analysis without any prior training information.
After extracting simple features at a single spatio-temporal scale, we learn a
dictionary for each individual in the video during each short time lapse. These
dictionaries allow us to compare the individuals' actions by producing an
affinity matrix which contains sufficient discriminative information about the
actions in the scene leading to grouping with simple and efficient tools. With
diverse publicly available real videos, we demonstrate the effectiveness of the
proposed framework and its robustness to cluttered backgrounds, changes of
human appearance, and action variability.


  We prove that there exists a nonprincipal ultrafilter $\mathcal U$ on
$\mathbb N$ such that for every countable (or separable) structure $B$ in a
countable language the quotient map from the reduced product associated with
the Fr\'echet filter onto the ultrapower has a right inverse. The proof uses
the Continuum Hypothesis. We characterize the ultrafilters $\mathcal U$ with
this property, and show that consistently with ZFC such ultrafilters need not
exist. We also prove a similar ZFC result sufficiently strong to obtain all
concrete applications of the existence of a right inverse to the quotient map.
Among applications, we prove a transfer theorem, answering a question of
Schafhauser and Tikuisis, motivated by the Elliott classification programme. We
also show that, in the category of C*-algebras, tensoring with the C*-algebra
of all continuous functions on the Cantor space preserves elementarity. We also
prove that tensoring with the Jiang--Su algebra or a UHF algebra does not
preserve elementarity in general.


  Recent computational efforts have shown that the current potential energy
models used in molecular dynamics are not accurate enough to describe the
conformational ensemble of RNA oligomers and suggest that molecular dynamics
should be complemented with experimental data. We here propose a scheme based
on the maximum entropy principle to combine simulations with bulk experiments.
In the proposed scheme the noise arising from both the measurements and the
forward models used to back calculate the experimental observables is
explicitly taken into account. The method is tested on RNA nucleosides and is
then used to construct chemically consistent corrections to the Amber RNA force
field that allow a large set of experimental data on nucleosides and
dinucleosides to be correctly reproduced. The transferability of these
corrections is assessed against independent data on tetranucleotides and
displays a previously unreported agreement with experiments. This procedure can
be applied to enforce multiple experimental data on multiple systems in a
self-consistent framework thus suggesting a new paradigm for force field
refinement.


  A system of electrons in two dimensions and strong magnetic fields can be
tuned to create a gapped 2D system with one dimensional channels along the
edge. Interactions among these edge modes can lead to independent transport of
charge and heat, even in opposite directions. Measuring the chirality and
transport properties of these charge and heat modes can reveal otherwise hidden
structure in the edge. Here, we heat the outer edge of such a quantum Hall
system using a quantum point contact. By placing quantum dots upstream and
downstream along the edge of the heater, we can measure both the chemical
potential and temperature of that edge to study charge and heat transport,
respectively. We find that charge is transported exclusively downstream, but
heat can be transported upstream when the edge has additional structure related
to fractional quantum Hall physics.


  The 'optical spring' results from dynamical back-action and can be used to
improve the sensitivity of cavity-enhanced gravitational-wave detectors. The
effect occurs if an oscillation of the cavity length results in an oscillation
of the intra-cavity light power having such a phase relation that the light's
radiation pressure force amplifies the oscillation of the cavity length. Here,
we analyse a Michelson interferometer whose optical-spring cavity includes an
additional optical-parametric amplifier with adjustable phase. We find that the
phase of the parametric pump field is a versatile parameter for shaping the
interferometer's spectral density.


  Let $\Gamma$ be a finite group. Consider the wreath product $G_n := \Gamma^n
\rtimes S_n$ and the subgroup $K_n := \Delta_n \times S_n\subseteq G_n$, where
$S_n$ is the symmetric group and $\Delta_n$ is the diagonal subgroup of
$\Gamma^n$. For certain values of $n$ (which depend on the group $\Gamma$), the
pair $(G_n, K_n)$ is a Gelfand pair. It is not known for all finite groups
which values of $n$ result in Gelfand pairs. Building off the work of
Benson--Ratcliff, we obtain a result which simplifies the computation of
multiplicities of irreducible representations in certain tensor product
representations, then apply this result to show that for $\Gamma = S_k, \ k
\geq 5$, $(G_n,K_n)$ is a Gelfand pair exactly when $n = 1,2$.


  We discuss the two-dimensional (2D), $\epsilon<2$ extremal ground states of
charged black hole. Here $\epsilon$ is the dilaton coupling parameter for the
Maxwell term. The complete analysis of stability is carried out for all these
extremal black holes. It is found that they are all unstable. To understand
this instability, we study the non-extremal charged black hole with two (inner
and outer) horizons. The extremal black holes appear when two horizons
coalesce. It conjectures that the instability originates from the inner
horizon.


  Let $A$ be a quasi-hereditary algebra. We prove that in many cases, a tilting
module is rigid (i.e. has identical radical and socle series) if it does not
have certain subquotients whose composition factors extend more than one layer
in the radical series or the socle series. We apply this theorem to give new
results about the radical series of some tilting modules for $SL_4(K)$, where
$K$ is a field of positive characteristic.


  Two-particle (2-p) excitations such as spin and charge excitations play a key
role in high-Tc cuprate superconductors (HTSC). On the basis of a
parameter-free theory, which extends the Variational Cluster Approach (a
recently developed embedded cluster method) to 2-p excitations, the magnetic
excitations of HTSC are shown to be reproduced for a Hubbard model within the
relevant strong-coupling regime. In particular, the resonance mode in the
underdoped regime, its intensity and "hour-glass" dispersion are in good
overall agreement with experiments.


  It is shown that the before-before (or Suarez-Scarani) experiment refutes
hidden variable models with a deterministic ("realistic") nonlocal part, and
the experimental violation of Leggett-type inequalities models with a random
nonlocal part and a biased random local one. Therefore the claim that
Groeblacher et al. present "an experimental test of nonlocal realism" [Nature,
446, 871-875 (2007)] is misleading, and Marek Zukowski's comment
[arXiv:0809.0072v1] misses the point. A new experiment is proposed.


  The aim of this paper is to give an alternative construction of Street's
cosimplicial object of orientals, based on an idea of Burroni that orientals
are free algebras for some algebraic structure on strict $\omega$-categories.
More precisely, following Burroni, we define the notion of an expansion on an
$\omega$-category and we show that the forgetful functor from strict
$\omega$-categories endowed with an expansion to strict $\omega$-categories is
monadic. By iterating this monad starting from the empty $\omega$-category, we
get a cosimplicial object in strict $\omega$-categories. Our main contribution
is to show that this cosimplicial object is the cosimplicial objects of
orientals. To do so, we prove, using Steiner's theory of augmented directed
chain complexes, a general result for comparing polygraphs having same
generators and same linearized sources and targets.


  In a recent article, Kiukas and Werner claim to have shown that Bohmian
Mechanics does not make the same empirical predictions as ordinary Quantum
Mechanics. More precisely, they have shown that ordinary Quantum Mechanics
predicts maximal violations of the CHSH-Bell inequality for a certain
experiment in which only position measurements are performed on two
noninteracting entangled free non-relativistic particles. Kiukas and Werner
claim that Bohmian Mechanics doesn't predict a violation of the CHSH-Bell
inequality for that experiment. We explain that such claim is wrong and that
the argument supporting their claim neglects the fact that Bohmian Mechanics
does not satisfy all the assumptions needed to prove the CHSH-Bell inequality.
We also clear up another few misconceptions about Bohmian Mechanics appearing
in their article.


  We introduce a novel property of bipartite quantum states, which we call
"faithfulness", and we say that a state is faithful when acting with a channel
on one of the two quantum systems, the output state carries a complete
information about the channel. The concept of faithfulness can also be extended
to sets of states, when the output states patched together carry a complete
imprinting of the channel.


  We compare the potential of neural network (NN)-based channel estimation with
classical linear minimum mean square error (LMMSE)-based estimators, also known
as Wiener filtering. For this, we propose a low-complexity recurrent neural
network (RNN)-based estimator that allows channel equalization of a sequence of
channel observations based on independent time- and frequency-domain long
short-term memory (LSTM) cells. Motivated by Vehicle-to-Everything (V2X)
applications, we simulate time- and frequency-selective channels with
orthogonal frequency division multiplex (OFDM) and extend our channel models in
such a way that a continuous degradation from line-of-sight (LoS) to
non-line-of-sight (NLoS) conditions can be emulated. It turns out that the
NN-based system cannot just compete with the LMMSE equalizer, but it also can
be trained w.r.t. resilience against system parameter mismatch. We thereby
showcase the conceptual simplicity of such a data-driven system design, as this
not only enables more robustness against, e.g., signal-to-noise-ratio (SNR) or
Doppler spread estimation mismatches, but also allows to use the same equalizer
over a wider range of input parameters without the need of re-building (or
re-estimating) the filter coefficients. Particular attention has been paid to
ensure compatibility with the existing IEEE 802.11p piloting scheme for V2X
communications. Finally, feeding the payload data symbols as additional
equalizer input unleashes further performance gains. We show significant gains
over the conventional LMMSE equalization for highly dynamic channel conditions
if such a data-augmented equalization scheme is used.


  In this article I discuss Zermelo's navigation problem in spacetime as a
geometrization of the frame dragging effect, and recast various examples
involving the latter into Zermelo form. I start by describing a stationary
spacetime in Zermelo's form and show that the Zermelo wind is the drift
velocity under frame dragging effect. Then we discuss various problems in this
context, such as Hubble expansion of the universe and accelerated frames in
special relativity. Another example I will discuss is the self-gravitating disk
around a black hole in post-Newtonian (PN1) approximation to describe the
anti-dragging effect in terms of a Zermelo wind.


  We propose a randomized algorithm for training Support vector machines(SVMs)
on large datasets. By using ideas from Random projections we show that the
combinatorial dimension of SVMs is $O({log} n)$ with high probability. This
estimate of combinatorial dimension is used to derive an iterative algorithm,
called RandSVM, which at each step calls an existing solver to train SVMs on a
randomly chosen subset of size $O({log} n)$. The algorithm has probabilistic
guarantees and is capable of training SVMs with Kernels for both classification
and regression problems. Experiments done on synthetic and real life data sets
demonstrate that the algorithm scales up existing SVM learners, without loss of
accuracy.


  A rank one local system $\LL$ on a smooth complex algebraic variety $M$ is
1-admissible if the dimension of the first cohomology group $H^1(M,\LL)$ can be
computed from the cohomology algebra $H^*(M,\C)$ in degrees $\leq 2$. Under the
assumption that $M$ is 1-formal, we show that all local systems, except
finitely many, on a non-translated irreducible component $W$ of the first
characteristic variety $\V_1(M)$ are 1-admissible, see Proposition 3.1. The
same result holds for local systems on a translated component $W$, but now
$H^*(M,\C)$ should be replaced by $H^*(M_0,\C)$, where $M_0$ is a Zariski open
subset obtained from $M$ by deleting some hypersurfaces determined by the
translated component $W$, see Theorem 4.3.


  We discuss a mass-lumped midpoint scheme for the numerical approximation of
the Landau-Lifshitz-Gilbert equation, which models the dynamics of the
magnetization in ferromagnetic materials. In addition to the classical
micromagnetic field contributions, our setting covers the non-standard
Dzyaloshinskii-Moriya interaction, which is the essential ingredient for the
enucleation and stabilization of magnetic skyrmions. Our analysis also includes
the inexact solution of the arising nonlinear systems, for which we discuss
both a constraint preserving fixed-point solver from the literature and a novel
approach based on the Newton method. We numerically compare the two
linearization techniques and show that the Newton solver leads to a
considerably lower number of nonlinear iterations. Moreover, in a numerical
study on magnetic skyrmions, we demonstrate that, for magnetization dynamics
that are very sensitive to energy perturbations, the midpoint scheme, due to
its conservation properties, is superior to the dissipative tangent plane
schemes from the literature.


  The novel concept of a Cyber-Human Social System (CHSS) and a diverse and
pluralistic 'mixed-life society' is proposed, wherein cyber and human societies
commit to each other. This concept enhances the Cyber-Physical System (CPS),
which is associated with the current Society 5.0, a social vision realised
through the fusion of cyber (virtual) and physical (real) spaces following
information society (Society 4.0 and Industry 4.0). Moreover, the CHSS enhances
the Human-CPS, the Human-in-the-Loop CPS (HiLCPS), and the Cyber-Human System
by intervening in individual behaviour pro-socially and supporting consensus
building. As a form of architecture that embodies the CHSS concept, the
Cyber-Human Social Co-Operating System (Social Co-OS) that combines cyber and
human societies is shown. In this architecture, the cyber and human systems
cooperate through the fast loop (operation and administration) and slow loop
(consensus and politics). Furthermore, the technical content and current
implementation of the basic functions of the Social Co-OS are described. These
functions consist of individual behavioural diagnostics, interventions in the
fast loop, group decision diagnostics and consensus building in the slow loop.
Subsequently, this system will contribute to mutual aid communities and
platform cooperatives.


  The CMS experiment recorded 177.75 /fb of proton-proton collision data during
the RUN-1 and RUN-2 data taking period. Successful data taking at increasing
instantaneous luminosities with the evolving detector configuration was a big
achievement of the collaboration. The CMS RPC system provided redundant
information for the robust muon triggering, reconstruction, and identification.
To ensure stable data taking, the CMS RPC collaboration has performed detector
operation, calibration, and performance studies. Various software and related
tools are developed and maintained accordingly. In this paper, the overall
performance of the CMS RPC system and experiences of the data taking during the
RUN-2 period are summarised.


  If the AdS/CFT correspondence is valid in the Coulomb branch, the potential
between waves on a pair of test branes in the bulk should be reproduced by the
relevant Yang-Mills theory effective action on the boundary. Earlier work has
provided evidence for this in the case of constant gauge field brane waves. In
this paper we provide concrete evidence for an earlier proposal that the
effects of exchange of supergravity modes with nonzero momentum in the brane
directions are encoded in certain terms involving derivatives of the field
strength in the gauge theory effective action. We explicitly calculate the
force quadratic in the field strengths coming from the exchange of non-zero
momentum two form fields between two 3-branes in $AdS_5 \times S^5$ to lowest
nontrivial order in the momentum. We show that this is exactly the same as that
between the branes living in flat space. The result is in agreement with the
gauge theory effective action and consistent with the non-renormalization
property of this term. We comment on the relationship of other ``acceleration''
terms in the SYM effective action with quantities in supergravity.


  The experimental achievements and the results obtained so far with the
LPCTrap device installed at GANIL are presented. The apparatus is dedicated to
the study of the weak interaction at low energy by means of precise
measurements of the BETA-NU angular correlation parameter in nuclear BETA
decays. So far, the data collected with three isotopes have enabled to
determine, for the first time, the charge state distributions of the recoiling
ions, induced by shakeoff process. The analysis is presently refined to deduce
the correlation parameters, with the potential of improving both the constraint
deduced at low energy on exotic tensor currents (6He1+) and the precision on
the V u d element of the quark-mixing matrix (35Ar1+ and 19Ne1+) deduced from
the mirror transitions dataset.


  Recently, formulas for the mixing matrices of quarks and leptons have been
put forward. My contribution here describes the relevant foundational and
technical aspects which have led to those results. The work has been carried
out in the framework of the microscopic model. The most general ansatz for the
interactions among tetrons leads to a Hamiltonian H involving
Dzyaloshinskii-Moriya (DM), Heisenberg and torsional isospin forces.
Diagonalization of the Hamiltonian provides for 24 eigenvalues which are
identified as the quark and lepton masses. While the masses of the third and
second family arise from DM and Heisenberg type of isospin interactions, light
family masses are related to torsional interactions among tetrons. Neutrino
masses turn out to be special in that they are given in terms of tiny isospin
non-conserving DM, Heisenberg and torsional couplings. The approach not only
leads to masses, but also allows to calculate the quark and lepton eigenstates,
an issue, which is important for the determination of the CKM and PMNS mixing
matrices. The almost exact isospin conservation of the system dictates the form
of the lepton states and makes them independent of all the couplings in H. Much
in contrast, there is a strong dependence of the quark states on the coupling
strengths, and a promising hierarchy between the quark family mixings shows up.


  We present angle resolved photoemission experiments and scanning tunneling
spectroscopy results on the doped topological insulator Cu0.2Bi2Te3.
Quasi-particle interference (QPI) measurements, based on high resolution
conductance maps of the local density of states show that there are three
distinct energy windows for quasi-particle scattering. Using a model
Hamiltonian for this system two new scattering channels are identified: the
first between the surface states and the conduction band and the second between
conduction band states. We also observe that the real space density modulation
has a predominant three-fold symmetry, which rules out a simple, isotropic
impurity potential. We obtain agreement between experiment and theory by
considering a modified scattering potential that is consistent with having
mostly Bi-Te anti-site defects as scatterers.


  It is shown that the interactions between the fermion and the gravitational
fields are due to the torsion field. The torsion field is considered to be a
potential one, like the electromagnetic and gravitational fields. The field
equations are obtained, which describe the interactions of the torsion field
with the conventional physical fields. The general covariant Lagrangian of the
gravitational field, based on the torsion field, is derived. Experiment is
proposed to test the theory.


  We study the impact of the wetting properties on the immiscible displacement
of a viscous fluid in disordered porous media. We present a novel pore-scale
model that captures wettability and dynamic effects, including the
spatiotemporal nonlocality associated with interface readjustments. Our
simulations show that increasing the wettability of the invading fluid (the
contact angle) promotes cooperative pore filling that stabilizes the invasion,
and that this effect is suppressed as the flow rate increases, due to viscous
instabilities. We use scaling analysis to derive two dimensionless numbers that
predict the mode of displacement. By elucidating the underlying mechanisms, we
explain classical yet intriguing experimental observations. These insights
could be used to improve technologies such as hydraulic fracturing, CO$_{2}$
geo-sequestration, and microfluidics.


  Automatic failure diagnosis is crucial for large microservice systems.
Currently, most failure diagnosis methods rely solely on single-modal data
(i.e., using either metrics, logs, or traces). In this study, we conduct an
empirical study using real-world failure cases to show that combining these
sources of data (multimodal data) leads to a more accurate diagnosis. However,
effectively representing these data and addressing imbalanced failures remain
challenging. To tackle these issues, we propose DiagFusion, a robust failure
diagnosis approach that uses multimodal data. It leverages embedding techniques
and data augmentation to represent the multimodal data of service instances,
combines deployment data and traces to build a dependency graph, and uses a
graph neural network to localize the root cause instance and determine the
failure type. Our evaluations using real-world datasets show that DiagFusion
outperforms existing methods in terms of root cause instance localization
(improving by 20.9% to 368%) and failure type determination (improving by 11.0%
to 169%).


  Quantum Chromo Dynamics (QCD), the theory of strong interactions, predicts a
transition of the usual matter to a new phase of matter, called Quark-Gluon
Plasma (QGP), at sufficiently high temperatures. The non-perturbative technique
of defining a theory on a space-time lattice has been used to obtain this and
other predictions about the nature of QGP. Heavy ion collisions at the Large
Hadron Collider in CERN can potentially test these predictions and thereby test
our theoretical understanding of confinement. This brief review aims at
providing a glimpse of both these aspects of QGP.


  We introduce a method for high-fidelity quantum state transduction between a
superconducting microwave qubit and the ground state spin system of a
solid-state artificial atom, mediated via an acoustic bus connected by
piezoelectric transducers. Applied to present-day experimental parameters for
superconducting circuit qubits and diamond silicon vacancy centers in an
optimized phononic cavity, we estimate quantum state transduction with fidelity
exceeding 99\% at a MHz-scale bandwidth. By combining the complementary
strengths of superconducting circuit quantum computing and artificial atoms,
the hybrid architecture provides high-fidelity qubit gates with long-lived
quantum memory, high-fidelity measurement, large qubit number, reconfigurable
qubit connectivity, and high-fidelity state and gate teleportation through
optical quantum networks.


  Image research has shown substantial attention in deblurring networks in
recent years. Yet, their practical usage in real-world deblurring, especially
motion blur, remains limited due to the lack of pixel-aligned training triplets
(background, blurred image, and blur heat map) and restricted information
inherent in blurred images. This paper presents a simple yet efficient
framework to synthetic and restore motion blur images using Inertial
Measurement Unit (IMU) data. Notably, the framework includes a strategy for
training triplet generation, and a Gyroscope-Aided Motion Deblurring (GAMD)
network for blurred image restoration. The rationale is that through harnessing
IMU data, we can determine the transformation of the camera pose during the
image exposure phase, facilitating the deduction of the motion trajectory (aka.
blur trajectory) for each point inside the three-dimensional space. Thus, the
synthetic triplets using our strategy are inherently close to natural motion
blur, strictly pixel-aligned, and mass-producible. Through comprehensive
experiments, we demonstrate the advantages of the proposed framework: only
two-pixel errors between our synthetic and real-world blur trajectories, a
marked improvement (around 33.17%) of the state-of-the-art deblurring method
MIMO on Peak Signal-to-Noise Ratio (PSNR).


  The emergence of quantum sensor networks has presented opportunities for
enhancing complex sensing tasks, while simultaneously introducing significant
challenges in designing and analyzing quantum sensing protocols due to the
intricate nature of entanglement and physical processes. Supervised learning
assisted by an entangled sensor network (SLAEN) [Phys. Rev. X 9, 041023 (2019)]
represents a promising paradigm for automating sensor-network design through
variational quantum machine learning. However, the original SLAEN, constrained
by the Gaussian nature of quantum circuits, is limited to learning linearly
separable data. Leveraging the universal quantum control available in
cavity-QED experiments, we propose a generalized SLAEN capable of handling
nonlinear data classification tasks. We establish a theoretical framework for
physical-layer data classification to underpin our approach. Through training
quantum probes and measurements, we uncover a threshold phenomenon in
classification error across various tasks -- when the energy of probes exceeds
a certain threshold, the error drastically diminishes to zero, providing a
significant improvement over the Gaussian SLAEN. Despite the non-Gaussian
nature of the problem, we offer analytical insights into determining the
threshold and residual error in the presence of noise. Our findings carry
implications for radio-frequency photonic sensors and microwave dark matter
haloscopes.


  While dealing with the constant-strength magnetic Laplacian on the annulus,
we complete J. Peetre's work. In particular, the eigenspaces associated with
its discrete spectrum are true-polyanalytic spaces with respect to the
invariant Cauchy-Riemann operator, and we write down explicit formulas for
their reproducing kernels. The latter are expressed by means of the fourth
Jacobi theta function and of its logarithmic derivatives when the magnetic
field strength is an integer. Under this quantization condition, we also derive
the transformation rule satisfied by the reproducing kernel under the
automorphism group of the annulus.


  Non-Abelian topological phases (NATPs) are highly sought-after candidate
states for quantum computing and communication while lacking straightforward
configuration and manipulation, especially for classical waves. In this work,
we exploit novel braid-type couplings among a pair of triple-component acoustic
dipoles, which act as functional elements with effective imaginary couplings.
Sequencing them in one dimension allows us to generate acoustic NATPs in a
compact yet reciprocal Hermitian system. We further provide the whole phase
diagram that encompasses all i, j, and k non-Abelian phases, and directly
demonstrate their unique quotient relations via different endpoint states. Our
NATPs based on real-space braiding may inspire the exploration of acoustic
devices with non-commutative characters.


  On the predual of a von Neumann algebra, we define a differentiable manifold
structure and affine connections by embeddings into non-commutative L_p-spaces.
Using the geometry of uniformly convex Banach spaces and duality of the L_p and
L_q spaces for 1/p+1/q=1, we show that we can introduce the \alpha-divergence,
for \alpha in (-1,1), in a similar manner as Amari in the classical case. If
restricted to the positive cone, the \alpha-divergence belongs to the class of
quasi-entropies, defined by Petz.


  In recent years, deep learning algorithms have become increasingly more
prominent for their unparalleled ability to automatically learn discriminant
features from large amounts of data. However, within the field of
electromyography-based gesture recognition, deep learning algorithms are seldom
employed as they require an unreasonable amount of effort from a single person,
to generate tens of thousands of examples.
  This work's hypothesis is that general, informative features can be learned
from the large amounts of data generated by aggregating the signals of multiple
users, thus reducing the recording burden while enhancing gesture recognition.
Consequently, this paper proposes applying transfer learning on aggregated data
from multiple users, while leveraging the capacity of deep learning algorithms
to learn discriminant features from large datasets. Two datasets comprised of
19 and 17 able-bodied participants respectively (the first one is employed for
pre-training) were recorded for this work, using the Myo Armband. A third Myo
Armband dataset was taken from the NinaPro database and is comprised of 10
able-bodied participants. Three different deep learning networks employing
three different modalities as input (raw EMG, Spectrograms and Continuous
Wavelet Transform (CWT)) are tested on the second and third dataset. The
proposed transfer learning scheme is shown to systematically and significantly
enhance the performance for all three networks on the two datasets, achieving
an offline accuracy of 98.31% for 7 gestures over 17 participants for the
CWT-based ConvNet and 68.98% for 18 gestures over 10 participants for the raw
EMG-based ConvNet. Finally, a use-case study employing eight able-bodied
participants suggests that real-time feedback allows users to adapt their
muscle activation strategy which reduces the degradation in accuracy normally
experienced over time.


  Quantum annealers, such as the device built by D-Wave Systems, Inc., offer a
way to compute solutions of NP-hard problems that can be expressed in Ising or
QUBO (quadratic unconstrained binary optimization) form. Although such
solutions are typically of very high quality, problem instances are usually not
solved to optimality due to imperfections of the current generations quantum
annealers. In this contribution, we aim to understand some of the factors
contributing to the hardness of a problem instance, and to use machine learning
models to predict the accuracy of the D-Wave 2000Q annealer for solving
specific problems. We focus on the Maximum Clique problem, a classic NP-hard
problem with important applications in network analysis, bioinformatics, and
computational chemistry. By training a machine learning classification model on
basic problem characteristics such as the number of edges in the graph, or
annealing parameters such as D-Wave's chain strength, we are able to rank
certain features in the order of their contribution to the solution hardness,
and present a simple decision tree which allows to predict whether a problem
will be solvable to optimality with the D-Wave 2000Q. We extend these results
by training a machine learning regression model that predicts the clique size
found by D-Wave.


  We present a scheme for simulating conditioned semimartingales taking values
in Riemannian manifolds. Extending the guided bridge proposal approach used for
simulating Euclidean bridges, the scheme replaces the drift of the conditioned
process with an approximation in terms of a scaled radial vector field. This
handles the fact that transition densities are generally intractable on
geometric spaces. We prove the validity of the scheme by a change of measure
argument, and we show how the resulting guided processes can be used in
importance sampling and for approximating the density of the unconditioned
process. The scheme is used for numerically simulating bridges on two- and
three-dimensional manifolds, for approximating otherwise intractable transition
densities, and for estimating the diffusion mean of sampled geometric data.


  By stacking various two-dimensional (2D) atomic crystals [1] on top of each
other, it is possible to create multilayer heterostructures and devices with
designed electronic properties [2-5]. However, various adsorbates become
trapped between layers during their assembly, and this not only affects the
resulting quality but also prevents the formation of a true artificial layered
crystal upheld by van der Waals interaction, creating instead a laminate glued
together by contamination. Transmission electron microscopy (TEM) has shown
that graphene and boron nitride monolayers, the two best characterized 2D
crystals, are densely covered with hydrocarbons (even after thermal annealing
in high vacuum) and exhibit only small clean patches suitable for atomic
resolution imaging [6-10]. This observation seems detrimental for any realistic
prospect of creating van der Waals materials and heterostructures with
atomically sharp interfaces. Here we employ cross sectional TEM to take a side
view of several graphene-boron nitride heterostructures. We find that the
trapped hydrocarbons segregate into isolated pockets, leaving the interfaces
atomically clean. Moreover, we observe a clear correlation between interface
roughness and the electronic quality of encapsulated graphene. This work proves
the concept of heterostructures assembled with atomic layer precision and
provides their first TEM images.


  Recent theoretical and experimental work has demonstrated how the
superconducting critical temperature ($T_c$) can be modified by rotating the
magnetization of a single homogeneous ferromagnet proximity-coupled to the
superconducting layer. This occurs when the superconductor and ferromagnet are
separated by a thin heavy normal metal that provides an enhanced interfacial
Rashba spin-orbit interaction. We consider the reciprocal effect: magnetization
reorientation driven by the superconducting phase transition. We solve the
tight-binding Bogoliubov-de Gennes equations on a lattice self-consistently and
find that the relative angle between the spin-orbit field and the magnetization
gives rise to a contribution in the free energy even in the normal state due to
band-structure effects. For temperatures below $T_c$, superconductivity gives
rise to a competing contribution. By lowering the temperature, in addition to
reorientation of the favored magnetization direction from in-plane to
out-of-plane, a $\pi/4$ in-plane rotation for thicker ferromagnetic layers is
possible. Furthermore, computation of $T_c$ of the structure in the ballistic
limit shows a dependence on the in-plane orientation of the magnetization, in
contrast to our previous result on the diffusive limit. This finding is
relevant with respect to thin-film heterostructures since these are likely to
be in the ballistic regime of transport. Finally, we discuss the experimental
feasibility of observing the magnetic anisotropy induced by the superconducting
transition when other magnetic anisotropies, such as the shape anisotropy for a
ferromagnetic film, are taken into account. Our work suggests that the
superconducting condensation energy in principle can trigger a reorientation of
the magnetization of a thin-film ferromagnet upon lowering the temperature
below $T_c$, in particular for ferromagnets with weak magnetic anisotropies.


  We report the discovery of a highly eccentric long-period Jovian planet
orbiting the hot-Jupiter host HD\,83443. By combining radial velocity data from
four instruments (AAT/UCLES, Keck/HIRES, HARPS, Minerva-Australis) spanning
more than two decades, we find evidence for a planet with
m~sin~$i=1.35^{+0.07}_{-0.06}$\,\mj, moving on an orbit with $a=8.0\pm$0.8\,au
and eccentricity $e=0.76\pm$0.05. We combine our radial velocity analysis with
\textit{Gaia} eDR3 /\textit{Hipparcos} proper motion anomalies and derive a
dynamical mass of $1.5^{+0.5}_{-0.2} M_{\rm Jup}$. We perform a detailed
dynamical simulation that reveals locations of stability within the system that
may harbor additional planets, including stable regions within the habitable
zone of the host star. HD\,83443 is a rare example of a system hosting a hot
Jupiter and an exterior planetary companion. The high eccentricity of
HD\,83443c suggests that a scattering event may have sent the hot Jupiter to
its close orbit while leaving the outer planet on a wide and eccentric path.


  We model the evolution of a Jupiter-mass protoplanet formed by the disk
instability mechanism at various radial distances accounting for the presence
of the disk. Using three different disk models, it is found that a newly-formed
Jupiter-mass protoplanet at radial distance of $\lesssim$ 5-10 AU cannot
undergo a dynamical collapse and evolve further to become a gravitational bound
planet. We therefore conclude that {\it giant planets, if formed by the
gravitational instability mechanism, must form and remain at large radial
distances during the first $\sim$ 10$^5-10^6$ years of their evolution}. The
minimum radial distances in which protoplanets of 1 Saturn-mass, 3 and 5
Jupiter-mass protoplanets can evolve using a disk model with $\dot{M}=10^{-6}
M_{Sun}/yr$ and $\alpha=10^{-2}$ are found to be 12, 9, and 7 AU, respectively.
The effect of gas accretion on the planetary evolution of a Jupiter-mass
protoplanet is also investigated. It is shown that gas accretion can shorten
the pre-collapse timescale substantially. Our study suggests that the timescale
of the pre-collapse stage does not only depend on the planetary mass, but is
greatly affected by the presence of the disk and efficient gas accretion.


  Generating musical audio directly with neural networks is notoriously
difficult because it requires coherently modeling structure at many different
timescales. Fortunately, most music is also highly structured and can be
represented as discrete note events played on musical instruments. Herein, we
show that by using notes as an intermediate representation, we can train a
suite of models capable of transcribing, composing, and synthesizing audio
waveforms with coherent musical structure on timescales spanning six orders of
magnitude (~0.1 ms to ~100 s), a process we call Wave2Midi2Wave. This large
advance in the state of the art is enabled by our release of the new MAESTRO
(MIDI and Audio Edited for Synchronous TRacks and Organization) dataset,
composed of over 172 hours of virtuosic piano performances captured with fine
alignment (~3 ms) between note labels and audio waveforms. The networks and the
dataset together present a promising approach toward creating new expressive
and interpretable neural models of music.


  In recent years there has been considerable interest in developing photonic
temperature sensors such as the Fiber Bragg gratings (FBG) as an alternative to
resistance thermometry. In this study we examine the thermal response of FBGs
over the temperature range of 233 K to 393 K. We demonstrate, in a hermetically
sealed dry Argon environment, that FBG devices show a quadratic dependence on
temperature with expanded uncertainties (k = 2) of ~500 mK. Our measurements
indicate that the combined measurement uncertainty is dominated by uncertainty
in determining the peak center fitting and by thermal aging of polyimide coated
fibers.


  The study of grain boundary phase transitions is an emerging field until
recently dominated by experiments. The major bottleneck in exploration of this
phenomenon with atomistic modeling has been the lack of a robust computational
tool that can predict interface structure. Here we develop a new computational
tool based on evolutionary algorithms that performs efficient grand-canonical
grain boundary structure search and we design a clustering analysis that
automatically identifies different grain boundary phases. Its application to a
model system of symmetric tilt boundaries in Cu uncovers an unexpected rich
polymorphism in the grain boundary structures. We find new ground and
metastable states by exploring structures with different atomic densities. Our
results demonstrate that the grain boundaries within the entire misorientation
range have multiple phases and exhibit structural transitions, suggesting that
phase behavior of interfaces is likely a general phenomenon.


  We present a sampling-based kinodynamic planning framework for a bipedal
robot in complex environments. Unlike other footstep planner which typically
plan footstep locations and the biped dynamics in separate steps, we handle
both simultaneously. Three advantages of this approach are (1) the ability to
differentiate alternate routes while selecting footstep locations based on the
temporal duration of the route as determined by the Linear Inverted Pendulum
Model dynamics, (2) the ability to perform collision checking through time so
that collisions with moving obstacles are prevented without avoiding their
entire trajectory, and (3) the ability to specify a minimum forward velocity
for the biped. To generate a dynamically consistent description of the walking
behavior, we exploit the Phase Space Planner. To plan a collision free route
toward the goal, we adapt planning strategies from non-holonomic wheeled robots
to gather a sequence of inputs for the PSP. This allows us to efficiently
approximate dynamic and kinematic constraints on bipedal motion, to apply a
sampling based planning algorithms, and to use the Dubin's path as the steering
method to connect two points in the configuration space. The results of the
algorithm are sent to a Whole Body Controller to generate full body dynamic
walking behavior.


  This paper presents a novel feature selection method based on the conditional
mutual information (CMI). The proposed High Order Conditional Mutual
Information Maximization (HOCMIM) incorporates high order dependencies into the
feature selection procedure and has a straightforward interpretation due to its
bottom-up derivation. The HOCMIM is derived from the CMI's chain expansion and
expressed as a maximization optimization problem. The maximization problem is
solved using a greedy search procedure, which speeds up the entire feature
selection process. The experiments are run on a set of benchmark datasets (20
in total). The HOCMIM is compared with eighteen state-of-the-art feature
selection algorithms, from the results of two supervised learning classifiers
(Support Vector Machine and K-Nearest Neighbor). The HOCMIM achieves the best
results in terms of accuracy and shows to be faster than high order feature
selection counterparts.


  Let $K/\mathbf{Q}$ be a finite Galois extension. The P\'olya group of $K$ is
the subgroup of the class group $Cl(K)$, generated by the classes of ambiguous
ideals of $K$. In this note, among other results, we prove that every finite
abelian group is isomorphic to the P\'olya group of a number field.


  We study the stability of static spherically symmetric charged black holes
under tensor type perturbations in Lovelock theory which is a natural higher
dimensional generalization of Einstein theory. We derive the master equation
for tensor type perturbations and present the criterions for the stability.
Examining these criterions numerically, we show that a black hole with small
charge has the instability if its mass is as small as extreme mass. Combined
with our previous result that neutral black hole has no dynamical instability
in odd dimensions, this result suggests that charges have fatal effects on
black holes in Lovelock theory.


  Plug-and-play (PnP) method is a recent paradigm for image regularization,
where the proximal operator (associated with some given regularizer) in an
iterative algorithm is replaced with a powerful denoiser. Algorithmically, this
involves repeated inversion (of the forward model) and denoising until
convergence. Remarkably, PnP regularization produces promising results for
several restoration applications. However, a fundamental question in this
regard is the theoretical convergence of the PnP iterations, since the
algorithm is not strictly derived from an optimization framework. This question
has been investigated in recent works, but there are still many unresolved
problems. For example, it is not known if convergence can be guaranteed if we
use generic kernel denoisers (e.g. nonlocal means) within the ISTA framework
(PnP-ISTA). We prove that, under reasonable assumptions, fixed-point
convergence of PnP-ISTA is indeed guaranteed for linear inverse problems such
as deblurring, inpainting and superresolution (the assumptions are verifiable
for inpainting). We compare our theoretical findings with existing results,
validate them numerically, and explain their practical relevance.


  Phylogenetic trees canonically arise as embeddings of phylogenetic networks.
We recently showed that the problem of deciding if two phylogenetic networks
embed the same sets of phylogenetic trees is computationally hard, \blue{in
particular, we showed it to be $\Pi^P_2$-complete}. In this paper, we establish
a polynomial-time algorithm for this decision problem if the initial two
networks consists of a normal network and a tree-child network. The running
time of the algorithm is quadratic in the size of the leaf sets.


  When global continuous symmetries are spontaneously broken, there appear
gapless collective excitations called Nambu-Goldstone modes (NGMs) that govern
the low-energy property of the system. The application of this famous theorem
ranges from high-energy, particle physics to condensed matter and atomic
physics. When a symmetry breaking occurs in systems that lack the Lorentz
invariance to start with, as is usually the case in condensed matter systems,
the number of resulting NGMs can be fewer than that of broken symmetry
generators, and the dispersion of NGMs is not necessarily linear. In this
article, we review recently established formulas for NGMs associated with
broken internal symmetries that work equally for relativistic and
nonrelativistic systems. We also discuss complexities of NGMs originating from
space-time symmetry breaking. In the process we cover many illuminating
examples from various context. We also present a complementary point of view
from the Lieb-Schultz-Mattis theorem.


  In the Cauchy problem of general relativity one considers initial data that
satisfies certain constraints. The evolution equations guarantee that the
evolved variables will satisfy the constraints at later instants of time. This
is only true within the domain of dependence of the initial data. If one wishes
to consider situations where the evolutions are studied for longer intervals
than the size of the domain of dependence, as is usually the case in three
dimensional numerical relativity, one needs to give boundary data. The boundary
data should be specified in such a way that the constraints are satisfied
everywhere, at all times. In this paper we address this problem for the case of
general relativity linearized around Minkowski space using the generalized
Einstein-Christoffel symmetric hyperbolic system of evolution equations. We
study the evolution equations for the constraints, specify boundary conditions
for them that make them well posed and further choose these boundary conditions
in such a way that the evolution equations for the metric variables are also
well posed. We also consider the case of a manifold with a non-smooth boundary,
as is the usual case of the cubic boxes commonly used in numerical relativity.
The techniques discussed should be applicable to more general cases, as
linearizations around more complicated backgrounds, and may be used to
establish well posedness in the full non-linear case.


  New methods of flow visualization near absolute zero have opened the way to
directly compare quantum turbulence (in superfluid helium) to classical
turbulence (in ordinary fluids such as air or water) and explore analogies and
differences. We present results of numerical simulations in which we examine
the statistics of the superfluid acceleration in thermal counterflow. We find
that, unlike the velocity, the acceleration obeys scaling laws similar to
classical turbulence, in agreement with a recent quantum turbulence experiment
of La Mantia et al.


  We revisit the Polyakov Loop coupled Nambu-Jona-Lasinio model that maintains
the Polyakov loop dynamics in the limit of zero temperature. This is of
interest for astrophysical applications in the interior of neutron stars. For
this purpose we re-examine the form of the potential for the deconfinement
order parameter at finite baryonic densities. Since the modification of this
potential at any temperature is formally equivalent to assigning a baryonic
charge to gluons, we develop a more general formulation of the present model
that cures this spurious effect and is normalized to match the asymptotic
behaviour of the QCD equation of state given by $\mathcal{O}(\alpha_s^2)$ and
partial $\mathcal{O}(\alpha_s^3\ln^2\alpha_s)$ perturbative results.


  Motivated by the operational problems in click and collect systems, such as
curbside pickup programs, we study a joint admission control and capacity
allocation problem. We consider a system where arriving customers have
preferred service delivery times and gauge the service quality based on the
service provider's ability to complete the service as close as possible to the
preferred time. Customers can be of different priority classes, and their
priority may increase as they wait longer in the queue. The service provider
can reject customers upon their arrival if the system is overloaded or
outsource the service (alternatively work overtime) when the capacity is not
enough. The service provider's goal is to find the minimum-cost admission and
capacity allocation policy to dynamically decide when to serve and whom to
serve. We model this problem as a Markov Decision Process. Our structural
results partially characterize a set of suboptimal solutions, and we develop
solution methods using these results. We also develop a problem-specific
approximation method that is based on state aggregation to overcome the
computational challenges. We present extensive computational results and
discuss the impact of problem parameters on the optimal policy.


  We show that a convolution semigroup of measures has Jacobi parameters
polynomial in the convolution parameter $t$ if and only if the measures come
from the Meixner class. Moreover, we prove the parallel result, in a more
explicit way, for the free convolution and the free Meixner class. We then
construct the class of measures satisfying the same property for the two-state
free convolution. This class of two-state free convolution semigroups has not
been considered explicitly before. We show that it also has Meixner-type
properties. Specifically, it contains the analogs of the normal, Poisson, and
binomial distributions, has a Laha-Lukacs-type characterization, and is related
to the $q=0$ case of quadratic harnesses.


  Quantum addition based on the quantum Fourier transform can be an integral
part of a quantum circuit and proved to be more efficient than the existing
classical ripple carry adder. Our study includes identifying the quantum
resource required in a quantum adder in any arbitrary dimension and its
relationship with the performance indicator in the presence of local noise
acting on the circuit and when a limited number of controlled rotation
operations is permitted, a procedure known as banding. We analytically prove an
upper bound on the number of the controlled rotation gates required to
accomplish the quantum addition up to an arbitrary defect in the fidelity
between the desired and imperfect output. When the environment interacts with
individual qudits, we establish a connection between quantum coherence and
fidelity of the output. Interestingly, we demonstrate that when banding is
employed in the presence of noise, approximate circuits of constant depth
outperform circuits with a higher number of controlled rotations, establishing
a complementary relationship between the approximate quantum adder and the
strength of the noise. We exhibit that utilizing magnetic fields to prepare an
initial state that evolves according to a one-dimensional spin chain for a
specific amount of time can be a potential technique to implement quantum
addition circuits in many-body systems.


  This paper will propose a novel star schema attribute induction as a new
attribute induction paradigm and as improving from current attribute oriented
induction. A novel star schema attribute induction will be examined with
current attribute oriented induction based on characteristic rule and using non
rule based concept hierarchy by implementing both of approaches. In novel star
schema attribute induction some improvements have been implemented like
elimination threshold number as maximum tuples control for generalization
result, there is no ANY as the most general concept, replacement the role
concept hierarchy with concept tree, simplification for the generalization
strategy steps and elimination attribute oriented induction algorithm. Novel
star schema attribute induction is more powerful than the current attribute
oriented induction since can produce small number final generalization tuples
and there is no ANY in the results.