  Double-lined spectroscopic binaries (SB2) allow us to determine a lower limit
of the masses of their components directly to test stellar models. In this
work, our aim is to derive the orbital and physical parameters of GJ1284, a
young SB2. We also revise the membership of this system and its two wide
co-moving companions, GJ898 and GJ897AB, to a young moving group to assess,
along with other youth indicators, their age. Afterwards, we compare the
results from these analyses and the photometry of these systems with several
pre-main-sequence evolutionary models. We determine the orbit of the GJ1284
system alongside its systemic velocity from high resolution spectra.
Additionally, we use TESS photometry to derive the rotational period of the
GJ1284 and its two wide companions. GJ1284 is a binary system located at
approximately 16 pc with an eccentric orbit ($ e = 0.505 $) of 11.83 d period
made up of an M2-M2.5 + M3-M3.5. The revised systemic velocity of $ \gamma =
0.84 \pm 0.14\,\mathrm{km\,s}^{-1} $ suggests that it is a member of the Local
Association. The kinematics together with other activity and youth indicators
imply an age of 110-800 Myr for this system and its two companions. The
isochronal ages derived from the comparison of the photometry with several
evolutionary models are younger than the age estimated from the activity
indicators for the three co-moving systems. The masses for the components of
GJ1284, derived from their luminosity and age using the different models, are
not consistent with the masses derived from the photometry, except for the
PARSEC models, but are compatible with dynamical masses of double-lined
eclipsing binaries with similar ages and spectral types. The effect of magnetic
activity in the form of spots can reconcile to some extent the photometric and
dynamical masses, but is not considered in most of the evolutionary models.


  Let $\mathfrak{o}$ be a complete discrete valuation ring with finide residue
field $\mathsf{k}$ of odd characteristic, and let $\mathbf{G}$ be a symplectic
or special orthogonal group scheme over $\mathfrak{o}$. For any
$\ell\in\mathbb{N}$ let $G^\ell$ denote the $\ell$-th principal congruence
subgroup of $\mathbf{G}(\mathfrak{o})$. An irreducible character of the group
$\mathbf{G}(\mathfrak{o})$ is said to be regular if it is trivial on a subgroup
$G^{\ell+1}$ for some $\ell$, and if its restriction to
$G^\ell/G^{\ell+1}\simeq \mathrm{Lie}(\mathbf{G})(\mathsf{k})$ consists of
characters of minimal $\mathbf{G}(\mathsf{k}^{\rm alg})$ stabilizer dimension.
In the present paper we consider the regular characters of such classical
groups over $\mathfrak{o}$, and construct and enumerate all regular characters
of $\mathbf{G}(\mathfrak{o})$, when the characteristic of $\mathsf{k}$ is
greater than two. As a result, we compute the regular part of their
representation zeta function.


  We define an obstruction to the formality of a differential graded algebra
over a graded operad defined over a commutative ground ring. This obstruction
lives in the derived operadic cohomology of the algebra. Moreover, it
determines all operadic Massey products induced on the homology algebra, hence
the name of derived universal Massey product.


  Based on the deformed nucleon distributions obtained from the constrained
Skyrme-Hartree-Fock-Bogolyubov calculation using different nuclear symmetry
energies, we have investigated the effects of the neutron skin and the
collision geometry on the yield of free spectator nucleons as well as the yield
ratio $N_n/N_p$ of free spectator neutrons to protons in collisions of deformed
nuclei at RHIC energies. We found that tip-tip (body-body) collisions with
prolate (oblate) nuclei lead to fewest free spectator nucleons, compared to
other collision configurations. While the $N_n/N_p$ ratio is sensitive to the
average neutron-skin thickness of colliding nuclei and the symmetry energy, it
is affected by the polar angular distribution of the neutron skin in different
collision configurations. We also found that the collision geometry effect can
be as large as 50% the symmetry energy effect in some collision systems. Due to
the particular deformed neutron skin in $^{238}$U and $^{96}$Zr, the symmetry
energy effect on the $N_n/N_p$ ratio is enhanced in tip-tip $^{238}$U+$^{238}$U
collisions and body-body $^{96}$Zr+$^{96}$Zr collisions compared to other
collision orientations in the same collision system. Our study may shed light
on probing deformed neutron skin by selecting desired configurations in
high-energy collisions with deformed nuclei.


  We consider models of light super-weakly interacting cold dark matter, with
O(10-100) keV mass, focusing on bosonic candidates such as pseudoscalars and
vectors. We analyze the cosmological abundance, the gamma-background created by
particle decays, the impact on stellar processes due to cooling, and the direct
detection capabilities in order to identify classes of models that pass all the
constraints. In certain models, variants of photoelectric (or axioelectric)
absorption of dark matter in direct-detection experiments can provide a
sensitivity to the superweak couplings to the Standard Model which is superior
to all existing indirect constraints. In all models studied, the annual
modulation of the direct-detection signal is at the currently unobservable
level of O(10^{-5}).


  The increasing availability of structured datasets, from Web tables and
open-data portals to enterprise data, opens up opportunities~to enrich
analytics and improve machine learning models through relational data
augmentation. In this paper, we introduce a new class of data augmentation
queries: join-correlation queries. Given a column $Q$ and a join column $K_Q$
from a query table $\mathcal{T}_Q$, retrieve tables $\mathcal{T}_X$ in a
dataset collection such that $\mathcal{T}_X$ is joinable with $\mathcal{T}_Q$
on $K_Q$ and there is a column $C \in \mathcal{T}_X$ such that $Q$ is
correlated with $C$. A na\"ive approach to evaluate these queries, which first
finds joinable tables and then explicitly joins and computes correlations
between $Q$ and all columns of the discovered tables, is prohibitively
expensive. To efficiently support correlated column discovery, we 1) propose a
sketching method that enables the construction of an index for a large number
of tables and that provides accurate estimates for join-correlation queries,
and 2) explore different scoring strategies that effectively rank the query
results based on how well the columns are correlated with the query. We carry
out a detailed experimental evaluation, using both synthetic and real data,
which shows that our sketches attain high accuracy and the scoring strategies
lead to high-quality rankings.


  Epigenetics is most often reduced to chromatin marking in the current
literature, whereas this notion was initially defined in a more general
context. This restricted view ignores that epigenetic memories are in fact more
robustly ensured in living systems by steady state mechanisms with permanent
molecule renewal. This misconception is likely to result from misleading
intuitions and insufficient dialogues between traditional and quantitative
biologists. To demystify dynamic epigenetics, its most famous image, a
Waddington landscape and its attractors, are explicitly drawn. The simple
example provided is sufficient to highlight the main requirements and
characteristics of dynamic gene networks, underlying cellular differentiation,
de-differentiation and trans-differentiation.


  We examine the issue of renormalizability of asymptotically free field
theories on non-commutative spaces. As an example, we solve the non-commutative
O(N) invariant Gross-Neveu model at large N. On commutative space this is a
renormalizable model with non-trivial interactions. On the noncommutative
space, if we take the translation invariant ground state, we find that the
model is non-renormalizable. Removing the ultraviolet cutoff yields a trivial
non-interacting theory.


  XDAQ is a generic data acquisition software environment that emerged from a
rich set of of use-cases encountered in the CMS experiment. They cover not the
deployment for multiple sub-detectors and the operation of different processing
and networking equipment as well as a distributed collaboration of users with
different needs. The use of the software in various application scenarios
demonstrated the viability of the approach. We discuss two applications, the
tracker local DAQ system for front-end commissioning and the muon chamber
validation system. The description is completed by a brief overview of XDAQ.


  We perform a detailed analysis of electronic polarizability of graphene with
different theoretical approaches. From Kubo's linear response formalism, we
give a general expression of frequency and wave-vector dependent polarizability
within the random phase approximation. Four theoretical approaches have been
applied to the single-layer graphene and their differences are on the
band-overlap of wavefunctions. By comparing with the \textit{ab initio}
calculation, we discuss the validity of methods used in literature. Our results
show that the tight-binding method is as good as the time-demanding \textit{ab
initio} approach in calculating the polarizability of graphene. Moreover, due
to the special Dirac-cone band structure of graphene, the Dirac model
reproduces results of the tight-binding method for energy smaller than
\SI{3}{\electronvolt}. For doped graphene, the intra-band transitions dominate
at low energies and can be described by the Lindhard formula for
two-dimensional electron gases. At zero temperature and long-wavelength limit,
with the relaxation time approximation, all theoretical methods reduce to a
long-wave analytical formula and the intra-band contributions agree to the
Drude polarizability of graphene. Effects of electrical doping and temperature
are also discussed. This work may provide a solid reference for researches and
applications of the screening effect of graphene.


  The deployment of robots within realistic environments requires the
capability to plan and refine the loco-manipulation trajectories on the fly to
avoid unexpected interactions with a dynamic environment. This extended
abstract provides a pipeline to offline plan a configuration space global
trajectory based on a randomized strategy, and to online locally refine it
depending on any change of the dynamic environment and the robot state. The
offline planner directly plans in the contact space, and additionally seeks for
whole-body feasible configurations compliant with the sampled contact states.
The planned trajectory, made by a discrete set of contacts and configurations,
can be seen as a graph and it can be online refined during the execution of the
global trajectory. The online refinement is carried out by a graph optimization
planner exploiting visual information. It locally acts on the global initial
plan to account for possible changes in the environment. While the offline
planner is a concluded work, tested on the humanoid COMAN+, the online local
planner is still a work-in-progress which has been tested on a reduced model of
the CENTAURO robot to avoid dynamic and static obstacles interfering with a
wheeled motion task. Both the COMAN+ and the CENTAURO robots have been designed
at the Italian Institute of Technology (IIT).


  We obtain asymptotic results on the average numbers of Goldbach
representations of an interger as the sum of two primes in different arithmetic
progressions. We also prove an omega-result showing that the asymptotic result
is essentially the best possible.


  Yang-Mills theory and QCD are well-defined for any Lie group as gauge group.
The choice G2 is of great interest, as it is the smallest group with trivial
center and being at the same time accessible to simulations. This theory has
been found to have many properties in common with SU(3) Yang-Mills theory and
QCD, permitting to study the role of the center. Herein, these investigations
are extended to topological properties of G2 Yang-Mills theory. After giving
the instanton construction for G2, topological lumps with instanton topological
charge are identified in cooled lattice configurations. The corresponding
topological susceptibility is determined in the vacuum and at low and high
temperatures, showing a significant response to the phase structure of the
theory.


  We compute the expansion of the 3-d Lattice QCD free energy to four loop
order by means of Numerical Stochastic Perturbation Theory. The first and
second order are already known and are correctly reproduced. The third and
fourth order coefficients are new results. The known logarithmic divergence in
the fourth order is correctly identified. We comment on the relevance of our
computation in the context of dimensionally reduced finite temperature QCD.


  We focus on the online-based active learning (OAL) setting where an agent
operates over a stream of observations and trades-off between the costly
acquisition of information (labelled observations) and the cost of prediction
errors. We propose a novel foundation for OAL tasks based on partial
monitoring, a theoretical framework specialized in online learning from
partially informative actions. We show that previously studied binary and
multi-class OAL tasks are instances of partial monitoring. We expand the
real-world potential of OAL by introducing a new class of cost-sensitive OAL
tasks. We propose NeuralCBP, the first PM strategy that accounts for predictive
uncertainty with deep neural networks. Our extensive empirical evaluation on
open source datasets shows that NeuralCBP has favorable performance against
state-of-the-art baselines on multiple binary, multi-class and cost-sensitive
OAL tasks.


  We provide a definition of a $\prec$-asymptotic pair in a topological action
of a countable group $G$, where $\prec$ is an order on $G$ of type $\mathbb Z$.
We then prove that if $G$ is a countable amenable group and $(X,G)$ is a
topological $G$-action of positive entropy, then for every multiorder
$(\tilde{\mathcal O},\nu,G)$ and $\nu$-almost every order
$\prec\,\in\tilde{\mathcal O}$ there exists a $\prec$-asympotic pair in $X$.
This result is a generalization of the Blanchard-Host-Ruette Theorem for
classical topological dynamical systems (actions of~$\mathbb Z$). We also prove
that for every countable amenable group $G$, and every multiorder on $G$
arising from a tiling system, every topological $G$-action of entropy zero has
an extension which has no $\prec$-asymptotic pairs for any $\prec$ belonging to
this multiorder. Together, these two theorems give a characterization of
topological $G$-actions of entropy zero: $(X,G)$ has topological entropy zero
if and only if, for any multiorder $\tilde{\mathcal O}_{\boldsymbol{\mathsf
T}}$ on $G$ arising from a tiling system of entropy zero, there exists an
extension $(Y,G)$ of $(X,G)$, which has no $\prec$-asymptotic pairs for any
$\prec\,\in\tilde{\mathcal O}_{\boldsymbol{\mathsf T}}$, equivalently, there
exists a multiorder $(\tilde{\mathcal O},\nu,G)$ on $G$, such that for
$\nu$-almost any $\prec\,\in\tilde{\mathcal O}$, there are no
$\prec$-asymptotic pairs in $(Y,G)$.


  Computational determination of the equilibrium state of heterogeneous
phospholipid mem-branes is a significant challenge. We wish to explore the rich
phase diagram of these multi-component systems. However, the diffusion and
mixing times in membranes are long com-pared to typical times of computer
simulations. To speed up the relaxation times, advanced simulation methods are
used. We evaluate the combination of enhanced sampling tech-niques such as MDAS
(Molecular Dynamics with Alchemical Steps) and MC-MD (Monte Carlo with
Molecular Dynamics) with a coarse-grained model of membranes (Martini) to
re-duce the number of steps and force evaluations that are needed to reach
equilibrium. We illustrate a significant gain compared to straightforward
Molecular Dynamics of the Martini model by factors between three to ten. The
combination is a useful tool to enhance the study of phase separation and the
formation of domains in biological membranes.


  We investigate the dynamics following sudden quenches across quantum critical
points belonging to different universality classes. Specifically, we use matrix
product state methods to study the quantum Ising chain in the presence of two
additional terms which break integrability. We find that in all models the rate
function for the return probability to the initial state becomes a non-analytic
function of time in the thermodynamic limit. This so-called `dynamical phase
transition' was first observed in a recent work by Heyl, Polkovnikov, and
Kehrein [Phys. Rev. Lett. 110, 135704 (2013)] for the exactly-solvable quantum
Ising chain, which can be mapped to free fermions. Our results for `interacting
theories' indicate that non-analytic dynamics is a generic feature of sudden
quenches across quantum critical points. We discuss potential connections to
the dynamics of the order parameter.


  Gait recognition is widely used in social security applications due to its
advantages in long-distance human identification. Recently, sequence-based
methods have achieved high accuracy by learning abundant temporal and spatial
information. However, their robustness under adversarial attacks has not been
clearly explored. In this paper, we demonstrate that the state-of-the-art gait
recognition model is vulnerable to such attacks. To this end, we propose a
novel temporal sparse adversarial attack method. Different from previous
additive noise models which add perturbations on original samples, we employ a
generative adversarial network based architecture to semantically generate
adversarial high-quality gait silhouettes or video frames. Moreover, by
sparsely substituting or inserting a few adversarial gait silhouettes, the
proposed method ensures its imperceptibility and achieves a high attack success
rate. The experimental results show that if only one-fortieth of the frames are
attacked, the accuracy of the target model drops dramatically.


  The space $D'_\Gamma$ of distributions having their wavefront sets in a
closed cone $\Gamma$ has become important in physics because of its role in the
formulation of quantum field theory in curved space time. In this paper, the
topological and bornological properties of $D'_\Gamma$ and its dual
$E'_\Lambda$ are investigated. It is found that $D'_\Gamma$ is a nuclear,
semi-reflexive and semi-Montel complete normal space of distributions. Its
strong dual $E'_\Lambda$ is a nuclear, barrelled and bornological normal space
of distributions which, however, is not even sequentially complete. Concrete
rules are given to determine whether a distribution belongs to $D'_\Gamma$,
whether a sequence converges in $D'_\Gamma$ and whether a set of distributions
is bounded in $D'_\Gamma$.


  We consider the verification of multiple expected reward objectives at once
on Markov decision processes (MDPs). This enables a trade-off analysis among
multiple objectives by obtaining the Pareto front. We focus on strategies that
are easy to employ and implement. That is, strategies that are pure (no
randomization) and have bounded memory. We show that checking whether a point
is achievable by a pure stationary strategy is NP-complete, even for two
objectives, and we provide an MILP encoding to solve the corresponding problem.
The bounded memory case can be reduced to the stationary one by a product
construction. Experimental results using \Storm and Gurobi show the feasibility
of our algorithms.


  We present a detailed investigation of the magnetic and magnetotransport
properties of thin films of ferromagnetic Ga1-xMnxAs synthesized using ion
implantation and pulsed-laser melting (II-PLM). The field and
temperature-dependent magnetization, magnetic anisotropy, temperature-dependent
resistivity, magnetoresistance, and Hall effect of II-PLM Ga1-xMnxAs films have
all of the characteristic signatures of the strong p-d interaction of holes and
Mn ions observed in the dilute hole-mediated ferromagnetic phase. The
ferromagnetic and electrical transport properties of II-PLM films correspond to
the peak substitutional Mn concentration meaning that the non-uniform Mn depth
distribution is unimportant in determining the film properties. Good
quantitative agreement is found with films grown by low temperature molecular
beam epitaxy (LT-MBE) and having the similar substitutional Mn_Ga composition.
Additionally, we demonstrate that II-PLM Ga1-xMnxAs films are free from
interstitial Mn_I because of the high temperature processing. At high Mn
implantation doses the kinetics of solute redistribution during solidification
alone determine the maximum resulting Mn_Ga concentration. Uniaxial anisotropy
between in-plane [-110]and [110] directions is present in II-PLM Ga1-xMnxAs
giving evidence for this being an intrinsic property of the carrier-mediated
ferromagnetic phase.


  The explosion in the e-commerce industry which has been necessitated by the
growth and advance expansion of Information technology and its related
facilities in recent years have been met with adverse security issues
consequently affecting the industry and the entire online activities. This
paper exams the prevailing security threats e-commerce is facing which is
predominantly known as cyber-crime and how computer related technology and
facilities such as digital forensics tools can be adopted extensively to ensure
security in online related business activities. This paper investigated the
risk, damage and the cost cyber-crime poses to individuals and organizations
when they become victims. As it is obvious transacting business online as well
as all related online activities has become inherent in our everyday life. The
paper also comprehensively elucidate on some of the cyber-crime activities that
are posing serious threat to the security of E-commerce. Amazon and eBay were
used as the case of study in relation to respondents who patronizes these
renowned e-commerce sites for various transactions.
  Keywords: E-commerce Security,Cyber-Crime,digital forensics, Network
forensics, Network security, Online transactions, Identity theft, hacking.


  The non-perturbation and perturbation structures of the q-deformed
probability currents are studied. According to two ways of realizing the
q-deformed Heisenberg algebra by the undeformed operators, the perturbation
structures of two q-deformed probability currents are explored in detail.
Locally the structures of two perturbation q-deformed probability currents are
different, one is explicitly potential dependent; the other is not. But their
total contributions to the whole space are the same.


  We present laboratory experiments that investigate the structure and flow
characteristics of gravity currents travelling through an array of roughness
elements. The roughness elements are of comparable height to the gravity
current such that the current flows through the roughness array rather than
over it. The frontal velocity and density structure are measured as the current
transitions from flowing along a smooth bed to flowing through the roughness
array, and then back to a smooth bed. We find that, upon entering the roughness
array, the gravity current decelerates and the density structure changes from
the head and tail structure typical of smooth bed gravity currents, to a wedge
shape. A model is presented that explains the deceleration and change in shape
based on a dynamic balance between a pressure gradient within the current tail
and a drag force associated with individual roughness elements. This model
accurately predicts the deceleration of the gravity current, supporting the
proposed dynamic balance.


  We deal with two forms of the "uniqueness cases" in the classification of
large simple $K^*$-groups of finite Morley rank of odd type, where large means
the $m_2(G)$ at least three. This substantially extends results known for even
larger groups having \Prufer 2-rank at least three, to cover the two groups
$\PSp_4$ and $\G_2$. With an eye towards distant developments, we carry out
this analysis for $L^*$-groups which is substantially broader than the $K^*$
setting.


  Recent research on robustness has revealed significant performance gaps
between neural image classifiers trained on datasets that are similar to the
test set, and those that are from a naturally shifted distribution, such as
sketches, paintings, and animations of the object categories observed during
training. Prior work focuses on reducing this gap by designing engineered
augmentations of training data or through unsupervised pretraining of a single
large model on massive in-the-wild training datasets scraped from the Internet.
However, the notion of a dataset is also undergoing a paradigm shift in recent
years. With drastic improvements in the quality, ease-of-use, and access to
modern generative models, generated data is pervading the web. In this light,
we study the question: How do these generated datasets influence the natural
robustness of image classifiers? We find that Imagenet classifiers trained on
real data augmented with generated data achieve higher accuracy and effective
robustness than standard training and popular augmentation strategies in the
presence of natural distribution shifts. We analyze various factors influencing
these results, including the choice of conditioning strategies and the amount
of generated data. Additionally, we find that the standard ImageNet classifiers
suffer a performance degradation of upto 20\% on the generated data, indicating
their fragility at accurately classifying the objects under novel variations.
Lastly, we demonstrate that the image classifiers, which have been trained on
real data augmented with generated data from the base generative model, exhibit
greater resilience to natural distribution shifts compared to the classifiers
trained on real data augmented with generated data from the finetuned
generative model on the real data. The code, models, and datasets are available
at https://github.com/Hritikbansal/generative-robustness.


  We introduce a network growth model based on complete redirection: a new node
randomly selects an existing target node, but attaches to a random neighbor of
this target. For undirected networks, this simple growth rule generates
unusual, highly modular networks. Individual network realizations typically
contain multiple macrohubs---nodes whose degree scales linearly with the number
of nodes $N$. The size of the network "nucleus"---the set of nodes of degree
greater than one---grows sublinearly with $N$ and thus constitutes a
vanishingly small fraction of the network. The network therefore consists
almost entirely of leaves (nodes of degree one) as $N\to\infty$.


  We show that $p$-forms on $AdS_{2p+1}$ describe both singletons and massless
particles. On the $2p$-dimensional boundary the singleton $p$-form Lagrangian
reduces to the conformally invariant functional $\int F^2$. All the
representations, singletons as well as massless, are zero center modules and
involve a vacuum mode. Two- and three-form singleton fields are required by
supersymmetry in AdS$_5$ and AdS$_7$ supergravity respectively.


  We adopt the notion of the farsighted stable set to determine which matchings
are stable when agents are farsighted in matching markets with couples. We show
that a singleton matching is a farsighted stable set if and only if the
matching is stable. Thus, matchings that are stable with myopic agents remain
stable when agents become farsighted. Examples of farsighted stable sets
containing multiple non-stable matchings are provided for markets with and
without stable matchings. For couples markets where the farsighted stable set
does not exist, we propose the DEM farsighted stable set to predict the
matchings that are stable when agents are farsighted.


  In this work, we report on hot carrier diffusion in graphene across large
enough length scales that the carriers are not thermalized across the crystal.
The carriers are injected into graphene at one site and their thermal transport
is studied as a function of applied power and distance from the heating source,
up to tens of micrometers away. Superconducting contacts prevent out-diffusion
of hot carriers to isolate the electron-phonon coupling as the sole channel for
thermal relaxation. As local thermometers, we use the amplitude of the
Universal Conductance Fluctuations, which varies monotonically as a function of
temperature. By measuring the electron temperature simultaneously along the
length we observe a thermal gradient which results from the competition between
electron-phonon cooling and lateral heat flow.


  We examine several recently suggested methods for the detection of long-range
correlations in data series based on similar ideas as the well-established
Detrended Fluctuation Analysis (DFA). In particular, we present a detailed
comparison between the regular DFA and two recently suggested methods: the
Centered Moving Average (CMA) Method and a Modified Detrended Fluctuation
Analysis (MDFA). We find that CMA is performing equivalently as DFA in long
data with weak trends and slightly superior to DFA in short data with weak
trends. When comparing standard DFA to MDFA we observe that DFA performs
slightly better in almost all examples we studied. We also discuss how several
types of trends affect the different types of DFA. For weak trends in the data,
the new methods are comparable with DFA in these respects. However, if the
functional form of the trend in data is not a-priori known, DFA remains the
method of choice. Only a comparison of DFA results, using different detrending
polynomials, yields full recognition of the trends. A comparison with
independent methods is recommended for proving long-range correlations.


  Evolutionary robot systems are usually affected by the properties of the
environment indirectly through selection. In this paper, we present and
investigate a system where the environment also has a direct effect: through
regulation. We propose a novel robot encoding method where a genotype encodes
multiple possible phenotypes, and the incarnation of a robot depends on the
environmental conditions taking place in a determined moment of its life. This
means that the morphology, controller, and behavior of a robot can change
according to the environment. Importantly, this process of development can
happen at any moment of a robot lifetime, according to its experienced
environmental stimuli. We provide an empirical proof-of-concept, and the
analysis of the experimental results shows that Plasticoding improves
adaptation (task performance) while leading to different evolved morphologies,
controllers, and behaviour.


  Interpolation error estimates in terms of geometric quality measures are
established for harmonic coordinates on polytopes in two and three dimensions.
First we derive interpolation error estimates over convex polygons that depend
on the geometric quality of the triangles in the constrained Delaunay
triangulation of the polygon. This characterization is sharp in the sense that
families of polygons with poor quality triangles in their constrained Delaunay
triangulations are shown to produce large error when interpolating a basic
quadratic function. Non-convex polygons exhibit a similar limitation: large
constrained Delaunay triangles caused by vertices approaching a non-adjacent
edge also lead to large interpolation error. While this relationship is
generalized to convex polyhedra in three dimensions, the possibility of sliver
tetrahedra in the constrained Delaunay triangulation prevent the analogous
estimate from sharply reflecting the actual interpolation error. Non-convex
polyhedra are shown to be fundamentally different through an example of a
family of polyhedra containing vertices which are arbitrarily close to
non-adjacent faces yet the interpolation error remains bounded.


  Excitations of colliding nuclei during a nuclear reaction considerably affect
fusion cross sections at energies around the Coulomb barrier. It has been
demonstrated that such channel coupling effects can be represented in terms of
a distribution of multiple fusion barriers. We here apply a Bayesian approach
to analyze the so called fusion barrier distributions. This method determines
simultaneously the barrier parameters and the number of barriers. We
particularly investigate the $^{16}$O+$^{144}$Sm and $^{16}$O+$^{154}$Sm
systems in order to demonstrate the effectiveness of the method. The present
analysis indicates that the fusion barrier distribution for the former system
is most consistent with three fusion barriers, even though the experimental
data show only two distinct peaks.


  This paper concerns about the limiting distributions of change point
estimators, in a high-dimensional linear regression time series context, where
a regression object $(y_t, X_t) \in \mathbb{R} \times \mathbb{R}^p$ is observed
at every time point $t \in \{1, \ldots, n\}$. At unknown time points, called
change points, the regression coefficients change, with the jump sizes measured
in $\ell_2$-norm. We provide limiting distributions of the change point
estimators in the regimes where the minimal jump size vanishes and where it
remains a constant. We allow for both the covariate and noise sequences to be
temporally dependent, in the functional dependence framework, which is the
first time seen in the change point inference literature. We show that a
block-type long-run variance estimator is consistent under the functional
dependence, which facilitates the practical implementation of our derived
limiting distributions. We also present a few important byproducts of our
analysis, which are of their own interest. These include a novel variant of the
dynamic programming algorithm to boost the computational efficiency, consistent
change point localisation rates under temporal dependence and a new Bernstein
inequality for data possessing functional dependence. Extensive numerical
results are provided to support our theoretical results. The proposed methods
are implemented in the R package \texttt{changepoints} \citep{changepoints_R}.


  We study the possibility of using guided photons to generate, control, and
measure the entanglement of two qubits that is mediated by a one-dimensional
waveguide. We show how entanglement can be generated both with single photon
and with two-photon wavepackets. The introduction of a second photon allows for
a manipulation of the entanglement between the qubits, and phenomena such as
sudden death and revival of entanglement appear. Finally, we propose a
procedure for entanglement detection via the scattering output of a
single-photon over a qubit state.


Recent lattice QCD results on charmonium spectroscopy are reviewed.


  A secure quantum identification system combining a classical identification
procedure and quantum key distribution is proposed. Each identification
sequence is always used just once and new sequences are ``refuelled'' from a
shared provably secret key transferred through the quantum channel. Two
identification protocols are devised. The first protocol can be applied when
legitimate users have an unjammable public channel at their disposal. The
deception probability is derived for the case of a noisy quantum channel. The
second protocol employs unconditionally secure authentication of information
sent over the public channel, and thus it can be applied even in the case when
an adversary is allowed to modify public communications. An experimental
realization of a quantum identification system is described.


  Depth estimation has been widely studied and serves as the fundamental step
of 3D perception for intelligent vehicles. Though significant progress has been
made in monocular depth estimation in the past decades, these attempts are
mainly conducted on the KITTI benchmark with only front-view cameras, which
ignores the correlations across surround-view cameras. In this paper, we
propose S3Depth, a Simple Baseline for Supervised Surround-view Depth
Estimation, to jointly predict the depth maps across multiple surrounding
cameras. Specifically, we employ a global-to-local feature extraction module
which combines CNN with transformer layers for enriched representations.
Further, the Adjacent-view Attention mechanism is proposed to enable the
intra-view and inter-view feature propagation. The former is achieved by the
self-attention module within each view, while the latter is realized by the
adjacent attention module, which computes the attention across multi-cameras to
exchange the multi-scale representations across surround-view feature maps.
Extensive experiments show that our method achieves superior performance over
existing state-of-the-art methods on both DDAD and nuScenes datasets.


  The paper provided a description of a new model of information retrieval,
which is an extension of vector-space model and is based on the principles of
the theory of hypercomplex numerical systems. The model allows to some extent
realize the idea of fuzzy search and allows you to apply in practice the model
of information retrieval practical developments in the field of hypercomplex
numerical systems.


  Let $\mathcal{A}'$ be the set of integers missing any three fixed digits from
their decimal expansion. We produce primes in a thin sequence by proving an
asymptotic formula for counting primes of the form $p = m^2 + \ell^2$, with
$\ell \in \mathcal{A}'$.
  The proof draws on ideas from the work of Friedlander-Iwaniec on primes of
the form $p = x^2+y^4$, as well as ideas from the work of Maynard on primes
with restricted digits.


  We study the thin torus limit of the Haldane-Rezayi state. Eight of the ten
ground states are found to assume a simple product form in this limit, as is
known to be the case for many other quantum Hall trial wave functions. The two
remaining states have a somewhat unusual thin torus limit, where a "broken"
pair of defects forming a singlet is completely delocalized. We derive these
limits from the wave functions on the cylinder, and deduce the dominant matrix
elements of the thin torus hollow-core Hamiltonians. We find that there are
gapless excitations in the thin torus limit. This is in agreement with the
expectation that local Hamiltonians stabilizing wave functions associated with
non-unitary conformal field theories are gapless. We also use the thin torus
analysis to obtain explicit counting formulas for the zero modes of the
hollow-core Hamiltonian on the torus, as well as for the parent Hamiltonians of
several other paired and related quantum Hall states.


  We compare the recent measurements of gap between jets at the Tevatron and
the LHC with the Balitski Fadin Kuraev Lipatov framework. While a good
agreement is obtained with Tevatron data, some discrepancies especially for the
rapidity separation between jets are found that can be explained by an excess
of initial state radiation in PYTHIA.


  Using multihadronic Z0 decays recorded in 1991-1995 by the OPAL detector in
e+e- collisions at LEP1, experimental analyses were made of the following
subjects: (a) Bose-Einstein correlations; (b) Intermittency and correlations;
(c) rho and omega spin alignments; (d) A search for the tensor glueball
candidate fj(2200).


  In this paper, we address a recent trend in robotic home appliances to
include vision systems on personal devices, capable of personalizing the
appliances on the fly. In particular, we formulate and address an important
technical task of personal object search, which involves localization and
identification of personal items of interest on images captured by robotic
appliances, with each item referenced only by a few annotated images. The task
is crucial for robotic home appliances and mobile systems, which need to
process personal visual scenes or to operate with particular personal objects
(e.g., for grasping or navigation). In practice, personal object search
presents two main technical challenges. First, a robot vision system needs to
be able to distinguish between many fine-grained classes, in the presence of
occlusions and clutter. Second, the strict resource requirements for the
on-device system restrict the usage of most state-of-the-art methods for
few-shot learning and often prevent on-device adaptation. In this work, we
propose Swiss DINO: a simple yet effective framework for one-shot personal
object search based on the recent DINOv2 transformer model, which was shown to
have strong zero-shot generalization properties. Swiss DINO handles challenging
on-device personalized scene understanding requirements and does not require
any adaptation training. We show significant improvement (up to 55%) in
segmentation and recognition accuracy compared to the common lightweight
solutions, and significant footprint reduction of backbone inference time (up
to 100x) and GPU consumption (up to 10x) compared to the heavy
transformer-based solutions.


  The angular dependence of the nonlinear transverse magnetic moment of
untwinned high-quality single crystals of optimally doped YBCO have been
studied at a temperature of 2.5K using a low frequency AC technique. The
absence of any signature at angular period 2\pi/4is analyzed in light of the
numerical predictions of such a signal for a pure d-wave order parameter with
line nodes. Implications of this null result for the existence of a non-zero
gap at all angles on the Fermi surface are discussed.


  Machine learning models of music typically break up the task of composition
into a chronological process, composing a piece of music in a single pass from
beginning to end. On the contrary, human composers write music in a nonlinear
fashion, scribbling motifs here and there, often revisiting choices previously
made. In order to better approximate this process, we train a convolutional
neural network to complete partial musical scores, and explore the use of
blocked Gibbs sampling as an analogue to rewriting. Neither the model nor the
generative procedure are tied to a particular causal direction of composition.
Our model is an instance of orderless NADE (Uria et al., 2014), which allows
more direct ancestral sampling. However, we find that Gibbs sampling greatly
improves sample quality, which we demonstrate to be due to some conditional
distributions being poorly modeled. Moreover, we show that even the cheap
approximate blocked Gibbs procedure from Yao et al. (2014) yields better
samples than ancestral sampling, based on both log-likelihood and human
evaluation.


  (Abridged) We present an analysis of a 10-day continuous ASCA observation of
the narrow-line Seyfert 1 galaxy IRAS 13224-3809. The soft (0.7-1.3 keV) and
hard (1.3-10 keV) X-ray band light curves binned to 5000s reveal trough-to-peak
variations by a factor >25 and 20, respectively. The light curves in the soft
and hard bands are strongly correlated without any significant delay. However,
this correlation is not entirely due to changes in the power-law flux alone but
also due to changes in the soft X-ray hump emission above the power law. The
presence of a soft X-ray hump below 2 keV, previously detected in ROSAT and
ASCA data, is confirmed. Time resolved spectroscopy using daily sampling
reveals changes in the power-law slope, with Gamma in the range 1.74-2.47,
however, day-to-day variations in Gamma are not significant. The Soft hump
emission is found to dominate the observed variability on a timescale of a
week, but on shorter timescales (20000s) the power-law component appears to
dominate the observed variability. Flux resolved spectroscopy reveals that at
high flux levels the power law becomes steeper and the soft hump more
pronounced. The steepening of the photon index with the fluxes in the soft and
hard bands can be understood in the framework of disk/corona models in which
accretion disk is heated by viscous dissipation as well as by reprocessing of
hard X-rays following an X-ray flare resulting from coronal dissipation through
magnetic reconnection events.


  Let $\chi$ denote a primitive, non-quadratic Dirichlet character with
conductor $q$, and let $L(s, \chi)$ denote its associated Dirichlet
$L$-function. We show that $|L(1, \chi)| \geq 1/(9.12255 \log(q/\pi))$ for
sufficiently large $q$, and that $|L(1, \chi)| \geq 1/(9.69030 \log(q/\pi))$
for all $q\geq2$, improving some results of Louboutin. The improvements stem
principally from the construction, via simulated annealing, of some real
trigonometric polynomials having particularly favorable properties.


  An initial state for the observable universe consisting of a finite region
with a large vacuum energy will break-up due to near horizon quantum critical
fluctuations. This will lead to a Friedmann-like early universe consisting of
an expanding cloud of dark energy stars and radiation. In this note we point
out that this scenario provides a simple explanation for the present day
density of dark matter as well as the level of CMB temperature flucuations. It
is also predicted that all dark matter will be clumped on mass scales ~ 10E3
solar masses.


  This is a first version of a paper concerning abstract evolution equation
with fractional time derivatives. Maximal regularity results in spaces of
continuous and Hoelder continuous functions are described.


  We use a combination of Planck cosmic microwave background (CMB) anisotropy
data and non-CMB data that include Pantheon+ type Ia supernovae, Hubble
parameter [$H(z)$], growth factor ($f\sigma_8$) measurements, and a collection
of baryon acoustic oscillation (BAO) data, but not recent DESI 2024 BAO
measurements, to confirm the DESI 2024 (DESI+CMB+PantheonPlus) data compilation
support for dynamical dark energy with an evolving equation of state parameter
$w(z) = w_0 + w_a z/(1+z)$. From our joint compilation of CMB and non-CMB data,
in a spatially-flat cosmological model, we obtain $w_0 = -0.850 \pm 0.059$ and
$w_a = -0.59^{+0.26}_{-0.22}$ and find that this dynamical dark energy is
favored over a cosmological constant by $\sim 2\sigma$. Our data constraints on
the flat $w_0w_a$CDM model are slightly more restrictive than the DESI 2024
constraints, with the DESI 2024 and our values of $w_0$ and $w_a$ differing by
$-0.27\sigma$ and $0.44\sigma$, respectively. Our data compilation slightly
more strongly favors the flat $w_0w_a$CDM model over the flat $\Lambda$CDM
model than does the DESI 2024 data compilation.


  Spectroscopic observations with the EUV Imaging Spectrometer (EIS) on Hinode
have revealed large areas of high speed outflows at the periphery of many solar
active regions. These outflows are of interest because they may connect to the
heliosphere and contribute to the solar wind. In this Letter we use slit
rasters from EIS in combination with narrow band slot imaging to study the
temperature dependence of an active region outflow and show that it is more
complicated than previously thought. Outflows are observed primarily in
emission lines from Fe XI - Fe XV. Observations at lower temperatures (Si VII),
in contrast, show bright fan-like structures that are dominated by downflows.
The morphology of the outflows is also different than that of the fans. This
suggests that the fan loops, which often show apparent outflows in imaging
data, are contained on closed field lines and are not directly related to the
active region outflows.


  Speech enhancement (SE) is usually required as a front end to improve the
speech quality in noisy environments, while the enhanced speech might not be
optimal for automatic speech recognition (ASR) systems due to speech
distortion. On the other hand, it was shown that self-supervised pre-training
enables the utilization of a large amount of unlabeled noisy data, which is
rather beneficial for the noise robustness of ASR. However, the potential of
the (optimal) integration of SE and self-supervised pre-training still remains
unclear. In order to find an appropriate combination and reduce the impact of
speech distortion caused by SE, in this paper we therefore propose a joint
pre-training approach for the SE module and the self-supervised model. First,
in the pre-training phase the original noisy waveform or the waveform obtained
by SE is fed into the self-supervised model to learn the contextual
representation, where the quantified clean speech acts as the target. Second,
we propose a dual-attention fusion method to fuse the features of noisy and
enhanced speeches, which can compensate the information loss caused by
separately using individual modules. Due to the flexible exploitation of
clean/noisy/enhanced branches, the proposed method turns out to be a
generalization of some existing noise-robust ASR models, e.g., enhanced
wav2vec2.0. Finally, experimental results on both synthetic and real noisy
datasets show that the proposed joint training approach can improve the ASR
performance under various noisy settings, leading to a stronger noise
robustness.


  Let A be an n by n doubly substochastic matrix and denote {\sigma}(A) the sum
of all elements of A. In this paper we give the upper bound of the permanent of
(I-A) with respect to n and {\sigma}(A).


  Machine learning algorithms can perform well when trained on large datasets.
While large organisations often have considerable data assets, it can be
difficult for these assets to be unified in a manner that makes training
possible. Data is very often 'siloed' in different parts of the organisation,
with little to no access between silos. This fragmentation of data assets is
especially prevalent in heavily regulated industries like financial services or
healthcare. In this paper we propose a framework to enable asynchronous
collaborative training of machine learning models across data silos. This
allows data science teams to collaboratively train a machine learning model,
without sharing data with one another. Our proposed approach enhances
conventional federated learning techniques to make them suitable for this
asynchronous training in this intra-organisation, cross-silo setting. We
validate our proposed approach via extensive experiments.


  We show in detail the general relationship between the Schr\"{o}dinger
equation approach to calculating the MSW effect and the quantum field
theoretical S-matrix approach. We show the precise form a generic neutrino
propagator must have to allow a physically meaningful ``oscillation
probability'' to be decoupled from neutrino production fluxes and detection
cross-sections, and explicitly list the conditions---not realized in cases of
current experimental interest---in which the field theory approach would be
useful.


  Visualization of three-dimensional morphological changes in the subcellular
structures of a biological specimen is one of the greatest challenges in life
science. Despite conspicuous refinements in optical nanoscopy, determination of
quantitative changes in subcellular structure, i.e., size and thickness,
remains elusive. We present an integrated chip-based optical nanoscopy set-up
that provides a lateral optical resolution of 61 nm combined with a highly
sensitive quantitative phase microscopy (QPM) system with a spatial phase
sensitivity of $\pm$20 mrad. We use the system to obtain the 3D morphology of
liver sinusoidal endothelial cells (LSECs) combined with super-resolved spatial
information. LSECs have a unique morphology with nanopores that are present in
the plasma membrane, called fenestration. The fenestrations are grouped in
clusters called sieve plates, which are around 100 nm thick. Thus, imaging and
quantification of fenestration and sieve plate thickness requires resolution
and sensitivity of sub-100 nm along both lateral and axial directions. In the
chip-based nanoscope, the optical waveguides are used both for hosting and
illuminating the sample. A strong evanescent field is generated on top of the
waveguide surface for single molecule fluorescence excitation. The fluorescence
signal is captured by an upright microscope, which is converted into a
Linnik-type interferometer to sequentially acquire both super-resolved images
and quantitative phase information of the sample. The multi-modal microscope
provided an estimate of the fenestration diameter of 124$\pm$41 nm and revealed
the average estimated thickness of the sieve plates in the range of
91.2$\pm$43.5 nm for two different cells. The combination of these techniques
offers visualization of both the lateral size (using nanoscopy) and the
thickness map of sieve plates, i.e. discrete clusters fenestrations in QPM
mode.


  While the splinter property is a local property for Noetherian schemes in
characteristic zero, Bhatt observed that it imposes strong conditions on the
global geometry of proper schemes in positive characteristic. We show that if a
proper scheme over a field of positive characteristic is a splinter, then its
Nori fundamental group is trivial and its Kodaira dimension is negative. In
another direction, Bhatt also showed that any splinter in positive
characteristic is a derived splinter. We ask whether the splinter property is a
derived-invariant for projective varieties in positive characteristic and give
a positive answer for Gorenstein projective varieties with big anticanonical
divisor. For that purpose, we introduce the notion of O-equivalence and show
that the derived splinter property for schemes of finite type and separated
over a fixed Noetherian base is preserved under O-equivalence. Finally, we show
that global F-regularity is a derived-invariant for normal Gorenstein
projective varieties in positive characteristic.


  It has been widely observed that there exists no universal best
Multi-objective Evolutionary Algorithm (MOEA) dominating all other MOEAs on all
possible Multi-objective Optimization Problems (MOPs). In this work, we
advocate using the Parallel Algorithm Portfolio (PAP), which runs multiple
MOEAs independently in parallel and gets the best out of them, to combine the
advantages of different MOEAs. Since the manual construction of PAPs is
non-trivial and tedious, we propose to automatically construct high-performance
PAPs for solving MOPs. Specifically, we first propose a variant of PAPs, namely
MOEAs/PAP, which can better determine the output solution set for MOPs than
conventional PAPs. Then, we present an automatic construction approach for
MOEAs/PAP with a novel performance metric for evaluating the performance of
MOEAs across multiple MOPs. Finally, we use the proposed approach to construct
a MOEAs/PAP based on a training set of MOPs and an algorithm configuration
space defined by several variants of NSGA-II. Experimental results show that
the automatically constructed MOEAs/PAP can even rival the state-of-the-art
ensemble MOEAs designed by human experts, demonstrating the huge potential of
automatic construction of PAPs in multi-objective optimization.


  We describe the Koszul dual of two quadratic operads on planar forests
introduced to study the infinitesimal Hopf algebra of planar rooted trees and
prove that these operads are Koszul.


  We give a characterization of the extremal sequences for the Bellman function
of three variables of the dyadic maximal operator in relation to Kolmogorov's
inequality. In fact we prove that they behave approximately like eigenfunctions
of this operator for a specific eigenvalue. For this approach we use the one
introduced in [4], where the respective Bellman function has been precisely
evaluated.


  The l1-norm minimization problem plays an important role in the compressed
sensing (CS) theory. We present in this letter an algorithm for solving the
problem of l1-norm minimization for quaternion signals by converting it to
second-order cone programming. An application example of the proposed algorithm
is also given for practical guidelines of perfect recovery of quaternion
signals. The proposed algorithm may find its potential application when CS
theory meets the quaternion signal processing.


  In this work, we introduce PokeRRT, a novel motion planning algorithm that
demonstrates poking as an effective non-prehensile manipulation skill to enable
fast manipulation of objects and increase the size of a robot's reachable
workspace. We showcase poking as a failure recovery tactic used synergistically
with pick-and-place for resiliency in cases where pick-and-place initially
fails or is unachievable. Our experiments demonstrate the efficiency of the
proposed framework in planning object trajectories using poking manipulation in
uncluttered and cluttered environments. In addition to quantitatively and
qualitatively demonstrating the adaptability of PokeRRT to different scenarios
in both simulation and real-world settings, our results show the advantages of
poking over pushing and grasping in terms of success rate and task time.


  Electrical current can be completely spin polarized in a class of materials
known as half-metals, as a result of the coexistence of metallic nature for
electrons with one spin orientation and insulating for electrons with the
other. Such asymmetric electronic states for the different spins have been
predicted for some ferromagnetic metals - for example, the Heusler compounds-
and were first observed in a manganese perovskite. In view of the potential for
use of this property in realizing spin-based electronics, substantial efforts
have been made to search for half-metallic materials. However, organic
materials have hardly been investigated in this context even though
carbon-based nanostructures hold significant promise for future electronic
device. Here we predict half-metallicity in nanometre-scale graphene ribbons by
using first-principles calculations. We show that this phenomenon is realizable
if in-plane homogeneous electric fields are applied across the zigzag-shaped
edges of the graphene nanoribbons, and that their magnetic property can be
controlled by the external electric fields. The results are not only of
scientific interests in the interplay between electric fields and electronic
spin degree of freedom in solids but may also open a new path to explore
spintronics at nanometre scale, based on graphene.


  We outline a practical scheme for measuring the thermodynamic properties of a
Bose-Einstein condensate as a function of internal energy. We propose using
Bragg scattering and controlled trap manipulations to impart a precise amount
of energy to a near zero temperature condensate. After thermalisation the
temperature can be measured using standard techniques to determine the state
equation $T(U,N,\omega)$. Our analysis accounts for interaction effects and the
excitation of constants of motion which restrict the energy available for
thermalisation.


  We have refined the census of stars and brown dwarfs in the Upper Sco
association (~10 Myr, ~145 pc) by 1) updating the selection of candidate
members from our previous survey to include the high-precision astrometry from
the second data release of Gaia, 2) obtaining spectra of a few hundred
candidate members to measure their spectral types and verify their youth, and
3) assessing the membership (largely with Gaia astrometry) of 2020 stars toward
Upper Sco that show evidence of youth in this work and previous studies. We
arrive at a catalog of 1761 objects that are adopted as members of Upper Sco.
The distribution of spectral types among the adopted members is similar to
those in other nearby star-forming regions, indicating a similar initial mass
function. In previous studies, we have compiled mid-infrared photometry from
WISE and the Spitzer Space Telescope for members of Upper Sco and used those
data to identify the stars that show evidence of circumstellar disks; we
present the same analysis for our new catalog of members. As in earlier work,
we find that the fraction of members with disks increases with lower stellar
masses, ranging from <=10% for >1 Msun to ~22% for 0.01-0.3 Msun. Finally, we
have estimated the relative ages of Upper Sco and other young associations
using their sequences of low-mass stars in M(G_RP) versus G_BP-G_RP. This
comparison indicates that Upper Sco is a factor of two younger than the beta
Pic association (21-24 Myr) according to both non-magnetic and magnetic
evolutionary models.


  We analyze a quantum measurement $\hat{x}$ by solving the dynamics of
stochastic amplitudes that propagate both forward and backward in the time
direction. The dynamics is derived from quantum mechanics: The instantaneous
joint density of amplitudes $x$ and $p$ is proved equivalent to the positive
$Q(x,p,t)$ phase-space distribution, which establishes causal consistency. We
model the measurement $\hat{x}$ as amplification, confirming Born's rule for a
system prepared in a superposition of eigenstates $|x_{j}\rangle$ of $\hat{x}$.
The trajectories for the backward-propagating variable $x$ are governed by a
future boundary condition determined by the measurement setting, as though the
system were prepared in a mixture of $|x_{j}\rangle$. Causal relations are
deduced from the simulations. For superpositions and entangled states, we
identify causal loops for variables that are not observable. A hybrid causal
structure exists that is consistent with macroscopic realism. Further, the
model allows forward-backward simulation of Einstein-Podolsky-Rosen and Bell
correlations, which addresses a question raised by Schr\"odinger. The
simulations reveal consistency with a weak form of local realism defined for
the system after the unitary interactions determining the measurement settings,
the Bell violations emerging due to a breakdown of a subset of Bell's
local-realism conditions. Our results elucidate how hidden causal loops can
explain Bell nonlocality, without requiring retrocausality at a macroscopic
level.


  After playing a pivotal role in the birth of the Standard Model in the 70's,
the study of charm physics has undergone a revival during the last decade,
triggered by a wealth of precision measurements from the charm and $B$
factories, and from the CDF and especially the LHCb experiments. In this
article, we sum up how the unique phenomenology of charmed hadrons can be used
to test the Standard Model and we review the latest measurements performed in
this field by the LHCb experiment. These include the historic first
observations of $CP$ violation and of a nonzero mass difference between the
charmed neutral-meson mass eigenstates, the most precise determination of their
decay-width difference to date, and a search for time-dependent $CP$ violation
reaching the unprecedented precision of $10^{-4}$. These results challenge our
comprehension of nonperturbative strong interactions, and their interpretation
calls for further studies on both the theoretical and experimental sides. The
upcoming upgrades of the LHCb experiment will play a leading role in this
quest.


  We examine the effects of instantons in four dimensional N=1 supersymmetric
gauge theory by including D0-branes in type IIA brane constructions. We examine
instanton generated superpotentials in supersymmetric QCD and find that they
are due to a repulsive force between D4-branes bound to D0-branes ending on NS
5-branes. We study situations where instanton effects break supersymmetry such
as the Intriligator-Thomas-Izawa-Yangagida model and relate this to a IIA brane
construction. We also argue how confinement due to a condensate of fractional
instantons manifests itself in Super Yang-Mills theory using fractional D0
branes, D4 branes, and NS strings.


  The evolution toward sixth-generation (6G) wireless networks has introduced
programmable wireless environments (PWEs) and reconfigurable intelligent
surfaces (RISs) as transformative elements for achieving near-deterministic
wireless communications. However, the enhanced capabilities of RISs within
PWEs, especially as we move toward more complex electromagnetic functions by
increasing the number of reflecting elements, underscore the need for
high-precision user localization, since inaccurate localization could lead to
erroneous configuration of RISs, which would then compromise the effectiveness
of PWEs. In this direction, this paper investigates the integration of RISs and
optical anchors within PWEs, emphasizing the crucial role of ultra-precise
localization in unlocking advanced electromagnetic functionalities.
Specifically, we present an in-depth analysis of various localization
techniques, both RISbased and RIS-independent, while introducing the concept of
empowering PWEs with optical anchors for enhanced localization precision. Our
findings highlight that accurate localization is essential to fully exploit the
capabilities of RISs, paving the way for future applications. Through this
exploration, we contribute to the advancement of PWEs in line with the
ambitious goals of the 6G standards and improve the quality of service in next
generation wireless networks.


  We demonstrate the capabilities of nonlinear Volterra models to simulate the
behavior of an audio system and compare them to linear filters. In this paper a
nonlinear model of an audio system based on Volterra series is presented and
Normalized Least Mean Square algorithm is used to determine the Volterra series
to third order. Training data for the models were collected measuring a
physical speaker using a laser interferometer. We explore several training
signals and filter's parameters. Results indicate a decrease in Mean Squared
Error compared to the linear model with a dependency on the particular test
signal, the order and the parameters of the model.


  We study accretion flow dynamics of Galactic transient black hole candidate
(BHC) H 1743-322 during its 2010 outburst by analyzing spectral data using Two
Component (Keplerian and sub-Keplerian) Advective Flow (TCAF) solution, after
its inclusion in XSPEC as a local model. We compare our TCAF solution fitted
results with combined disk black body and power-law model fitted results and
find a similar smooth variation of thermal (Keplerian or disk black body) and
non-thermal (power-law or sub-Keplerian) fluxes/rates in two types of model
fits. For a spectral analysis, 2.5-25 keV spectral data from RXTE PCA
instrument are used. From the TCAF solution fit, accretion flow parameters,
such as Keplerian rate, sub-Keplerian rate, location of centrifugal pressure
supported shock and strength of the shock are extracted, thus providing a
deeper understanding of accretion process and properties of accretion disks
around BHC H 1743-322 during its X-ray outburst. Based on the halo to disk
accretion rate ratio (ARR), shock properties, accretion rates and nature of
quasi-periodic oscillations (QPOs, if observed) entire outburst is classified
into four different spectral states, such as, hard, hard-intermediate,
soft-intermediate, and soft. From time variation of intrinsic flow parameters
it appears that their evolutions in decline phase do not retrace path of rising
phase. Since our current model does not include magnetic fields, spectral
turnover at energies beyond 500-600 keV cannot be explained.


  Recent advances in artificial intelligence (AI) capabilities have increased
the eagerness of companies to integrate AI into software systems. While AI can
be used to have a positive impact on several dimensions of sustainability, this
is often overshadowed by its potential negative influence. While many studies
have explored sustainability factors in isolation, there is insufficient
holistic coverage of potential sustainability benefits or costs that
practitioners need to consider during decision-making for AI adoption. We
therefore aim to synthesize trade-offs related to sustainability in the context
of integrating AI into software systems. We want to make the sustainability
benefits and costs of integrating AI more transparent and accessible for
practitioners.
  The study was conducted in collaboration with a Dutch financial organization.
We first performed a rapid review that led to the inclusion of 151 research
papers. Afterward, we conducted six semi-structured interviews to enrich the
data with industry perspectives. The combined results showcase the potential
sustainability benefits and costs of integrating AI. The labels synthesized
from the review regarding potential sustainability benefits were clustered into
16 themes, with "energy management" being the most frequently mentioned one. 11
themes were identified in the interviews, with the top mentioned theme being
"employee wellbeing". Regarding sustainability costs, the review discovered
seven themes, with "deployment issues" being the most popular one, followed by
"ethics & society". "Environmental issues" was the top theme from the
interviews. Our results provide valuable insights to organizations and
practitioners for understanding the potential sustainability implications of
adopting AI.


  After a short review of the ultrahigh energy cosmic ray puzzle - the apparent
observation of cosmic rays originating from cosmological distances with
energies above the expected Greisen-Zatsepin-Kuzmin cutoff 4x10^{19} eV - we
consider strongly interacting neutrino scenarios as an especially interesting
solution. We show that all features of the ultrahigh energy cosmic ray spectrum
from 10^{17} eV to 10^{21} eV can be described to originate from a simple
power-like injection spectrum of protons, under the assumption that the
neutrino-nucleon cross-section is significantly enhanced at center of mass
energies above ~ 100 TeV. In such a scenario, the cosmogenic neutrinos produced
during the propagation of protons through the cosmic microwave background
initiate air showers in the atmosphere, just as the protons. The total air
shower spectrum induced by protons and neutrinos shows excellent agreement with
the observations. We shortly discuss TeV-scale extensions of the Standard Model
which may lead to a realization of a strongly interacting neutrino scenario. We
emphasize, however, that such a scenario may even be realized within the
standard electroweak model: electroweak instanton/sphaleron induced processes
may get strong at ultrahigh energies. Possible tests of strongly interacting
neutrino scenarios range from observations at cosmic ray facilities and
neutrino telescopes to searches at lepton nucleon scattering experiments.


  UAV-based wireless systems, such as wireless relay and remote sensing, have
attracted great attentions from academia and industry. To realize them, a
high-performance wireless aerial communication system, which bridges UAVs and
ground stations, is one of the key enablers. However, there are still issues
hindering its development, such as the severe co-channel interference among
UAVs, and the limited payload/battery-life of UAVs. To address the challenges,
we propose an aerial communication system which enables system-level
full-duplex communication of multiple UAVs with lower hardware complexities
than ideal full-duplex communication systems. In the proposed system, each
channel is re-assigned to the uplink and downlink of a pair of UAVs, and each
UAV employ a pair of separated channels for its uplink and downlink. The
co-channel interference between UAVs that reuse same channels is eliminated by
exploiting advantages of UAVs' maneuverability and high-gain directional
antennas equipped in UAVs and ground stations, so that dedicated cancellers are
not necessary in the proposed system. The system design and performance
analysis are given, and the simulation results well agree with the designs.


  Open string boundary conditions for non-BPS D-branes in type II string
theories discussed in hep-th/0505157 give rise to two sectors with integer (R
sector) and half-integer (NS sector) modes for the combined fermionic matter
and bosonic ghost variables in pure spinor formalism. Exploiting the manifest
supersymmetry of the formalism we explicitly construct the DDF (Del Giudice, Di
Vecchia, Fubini) states in both the sectors which are in one-to-one
correspondence with the states in light-cone Green-Schwarz formalism. We also
give a proof of validity of this construction. A similar construction in the
closed string sector enables us to define a physical Hilbert space in pure
spinor formalism which is used to project the covariant boundary states of both
the BPS and non-BPS instantonic D-branes. These projected boundary states take
exactly the same form as those found in light-cone Green-Schwarz formalism and
are suitable for computing the cylinder diagram with manifest open-closed
duality.


  In this paper we reconsider the sub-Riemannian cortical model of image
completion introduced by Sarti and Citti in 2003. This model combines two
mechanisms, the sub-Riemannian diffusion and the concentration, giving rise to
a diffusion driven motion by curvature. In this paper we give a formal proof of
the existence of viscosity solutions of the sub-Riemannian motion by curvature.
Results of completion and enhancement on a number of natural images are shown
and compared with other models.


  We embed a thermal dark matter (DM) candidate within the clockwork framework.
This mechanism allows to stabilize the DM particle over cosmological time
because it suppresses its decay into Standard Model (SM) particles. At the same
time, pair annihilations are unsuppressed, so that the relic density is set by
the usual freeze-out of the DM particle from the thermal bath. The slow decay
of the DM candidate is induced by "clockwork" particles that can be quite light
(rather than at some GUT or Planck scale) and could be searched for at current
or future colliders. According to the scenario considered, the very same
particles also mediate the annihilation process, thus providing a connection
between DM annihilation and DM decay, and fixing the mass scale of the
clockwork states, otherwise unconstrained, to be in the TeV range or lighter.
We then show how this setup can minimally emerge from the deconstruction of an
extra dimension in flat spacetime. Finally, we argue that the clockwork
mechanism that we consider could induce Majorana neutrino masses, with a seesaw
scale of order TeV or less and Yukawa couplings of order unity.


  In this work we build a certain machine that allows to construct almost
periodic Jacobi matrices with singularly continuous spectrum a prescribed
p-adic hull.


  We combine MUSE spectroscopy and Hubble Space Telescope ultraviolet (UV)
photometry to perform a study of the chemistry and dynamics of the Galactic
globular cluster Messier 80 (M80, NGC 6093). Previous studies have revealed
three stellar populations that not only vary in their light-element abundances,
but also in their radial distributions, with concentration decreasing with
increasing nitrogen enrichment. This remarkable trend, which sets M80 apart
from the other Galactic globular clusters, points towards a complex formation
and evolutionary history. To better understand how M80 formed and evolved,
revealing its internal kinematics is key. We find that the most N-enriched
population rotates faster than the other two populations at a 2 sigma
confidence level. While our data further suggest that the intermediate
population shows the least amount of rotation, this trend is rather marginal (1
- 2 sigma). Using axisymmetric Jeans models, we show that these findings can be
explained from the radial distributions of the populations if they possess
different angular momenta. Our findings suggest that the populations formed
with primordial kinematical differences.


  Some consequences of a classical vector field (chromo-electromagnetic field)
coupled to quarks, which undergo to superfluid and/or superconductive states
with diquark / diantiquark condensation, are investigated. For this, one scalar
field exchange is considered in the lines investigated by Pisarski and Rischke
\cite{PISARSKI-RISCHKE} in the mean field approach. Some effects and possible
consequences are discussed.


  The selective entrapment of mutually annihilating species within a
phase-changing carrier fluid is explored by both analytical and numerical
means. The model takes full account of the dynamic heterogeneity which arises
as a result of the coupling between hydrodynamic transport, dynamic
phase-transitions and chemical reactions between the participating species, in
the presence of a selective droplet interface. Special attention is paid to the
dynamic symmetry breaking between the mass of the two species entrapped within
the expanding droplet as a function of time. It is found that selective sources
are much more effective symmetry breakers than selective diffusion. The present
study may be of interest for a broad variety of advection-diffusion-reaction
phenomena with selective fluid interfaces, including the problem of electroweak
baryogenesis.


  Given $f: M \to N$ a homotopy equivalence of compact manifolds with boundary,
we use a construction of Geoghegan and Nicas to define its Reidemeister trace
$[T] \in \pi_1^{st}(\mathcal{L} N, N)$. We realize the Goresky-Hingston
coproduct as a map of spectra, and show that the failure of $f$ to entwine the
spectral coproducts can be characterized by Chas-Sullivan multiplication with
$[T]$. In particular, when $f$ is a simple homotopy equivalence, the spectral
coproducts of $M$ and $N$ agree.


  This paper studies the behaviour of iterates of weighted composition
operators acting on spaces of analytic functions, with particular emphasis on
the Hardy space $H^2$. Questions relating to uniform, strong and weak
convergence are resolved in many cases. Connected to this is the question when
a weighted composition operators is an isometry, and new results are given in
the case of the Hardy and Bergman spaces.


  For a finite group $G$, the power graph $\Gamma_G$ is a graph whose set of
vertices is equal to $G$ and two distinct elements of $G$ are adjacent if and
only if one of them is a positive integer power of the other. An
$L(2,1)$-labelling of $\Gamma_G$ is an integer-valued function defined on $G$
so that the distance between the images of two adjacent vertices (resp.
vertices with distance two) are at least two (resp. at least one). The lambda
number $\lambda(G)$ is defined to be the least difference between the largest
and the smallest integer values assigned to the vertices of $\Gamma_G$ for all
possible $L(2,1)$-labellings of $\Gamma_G$. It is known that $\lambda(G) \geq
|G|$. In this paper, we prove that if $G$ is a finite simple group, then
$\lambda(G) = |G|$ except when $G$ is cyclic of prime order. This settles a
partial classification of finite groups $G$ that achieve the lower bound on of
lambda number.


  We prove the flow tree formula conjectured by Alexandrov and Pioline which
computes Donaldson-Thomas invariants of quivers with potentials in terms of a
smaller set of attractor invariants. This result is obtained as a particular
case of a more general flow tree formula reconstructing a consistent scattering
diagram from its initial walls.


  Space-based observations show that the solar atmosphere from the solar
chromosphere to the solar corona is filled with small-scale jets and is linked
with small-scale explosions. These jets may be produced by mechanisms similar
to that of large-scale flares and such jets may be related to the heating of
corona and chromosphere as well as the acceleration of solar wind. The
chromospheric anemone jets on the Sun remain puzzling because their footpoints
(or bright knots) have not been well resolved and the formation process of such
enigmatic small-scale jets remains unclear. We propose a new model for
chromospheric jets using the three-dimensional magnetohydrodynamic (MHD)
simulations, which show that the continuous, upward rising of small-scale
twisted magnetic flux ropes in a magnetized solar chromosphere drive
small-scale magnetic reconnection and the launching of several small-scale jets
during the evolution of the chromospheric anemone jets. Our new,
self-consistent, three-dimensional computer modeling of small-scale, but
ever-changing flux rope emergence in the magnetized solar atmosphere is fully
consistent with observations and provides a universal mechanism for nanoflare
and jet formation.


  We evaluate a new 3-loop sum-integral which contributes to the Debye
screening mass in hot QCD. While we manage to derive all divergences
analytically, its finite part is mapped onto simple integrals and evaluated
numerically.


  Let G be a connected reductive real Lie group, and H a compact connected
subgroup. Harish-Chandra associates to a regular coadjoint admissible orbit M
of G some unitary representations of G. Using the character formula for these
representations, we show that the multiplicities of the restriction to H can be
computed, under a suitable properness assumption, in terms of the fibers of the
restriction map from M to the dual of the Lie algebra of H. In particular, this
gives an alternate proof of a result of Paradan.


  Radial substructure in the form of rings and gaps has been shown to be
ubiquitous among protoplanetary discs. This could be the case in exoKuiper
belts as well, and evidence for this is emerging. In this paper we present ALMA
observations of the debris/planetesimal disc surrounding HD 206893, a system
that also hosts two massive companions at 2 and 11 au. Our observations reveal
a disc extending from 30 to 180 au, split by a 27 au wide gap centred at 74 au,
and no dust surrounding the reddened brown dwarf (BD) at 11 au. The gap width
suggests the presence of a 0.9 M$_\mathrm{Jup}$ planet at 74 au, which would be
the third companion in this system. Using previous astrometry of the BD,
combined with our derived disc orientation as a prior, we were able to better
constrain its orbit finding it is likely eccentric ($0.14^{+0.05}_{-0.04}$).
For the innermost companion, we used RV, proper motion anomaly and stability
considerations to show its mass and semi-major axis are likely in the range
4-100 M$_\mathrm{Jup}$ and 1.4-4.5 au. These three companions will interact on
secular timescales and perturb the orbits of planetesimals, stirring the disc
and potentially truncating it to its current extent via secular resonances.
Finally, the presence of a gap in this system adds to the growing evidence that
gaps could be common in wide exoKuiper belts. Out of 6 wide debris discs
observed with ALMA with enough resolution, 4-5 show radial substructure in the
form of gaps.


  Shapes of four dimensional spaces can be studied effectively via maps to
standard surfaces. We explain, and illustrate by quintessential examples, how
to simplify such generic maps on 4-manifolds topologically, in order to derive
simple decompositions into much better understood manifold pieces. Our methods
not only allow us to produce various interesting families of examples, but also
to establish a correspondence between simplified broken Lefschetz fibrations
and simplified trisections of closed, oriented 4-manifolds.


  To determine the state of spin polarization of the 3D electron gas at very
low densities and zero temperature, we calculate the energy versus spin
polarization using Diffusion Quantum Monte Carlo methods with backflow
wavefunctions and twist averaged boundary conditions. We find a second order
phase transition to a partially polarized phase at r_s = 50 \pm 2. The magnetic
transition temperature is estimated using an effective mean field method, the
Stoner model.


  The range, local times, and periodicity of symmetric, weakly asymmetric and
asymmetric random walks at the time of exit from a strip with $N$ locations are
considered. Several results on asymptotic distributions are obtained.


  Certain biological neurons demonstrate a remarkable capability to optimally
compress the history of sensory inputs while being maximally informative about
the future. In this work, we investigate if the same can be said of artificial
neurons in recurrent neural networks (RNNs) trained with maximum likelihood.
Empirically, we find that RNNs are suboptimal in the information plane. Instead
of optimally compressing past information, they extract additional information
that is not relevant for predicting the future. We show that constraining past
information by injecting noise into the hidden state can improve RNNs in
several ways: optimality in the predictive information plane, sample quality,
heldout likelihood, and downstream classification performance.


  The experimental realization of quantum-degenerate Bose gases made of atoms
with sizeable magnetic dipole moments has created a new type of fluid, known as
a quantum ferrofluid, which combines the extraordinary properties of
superfluidity and ferrofluidity. A hallmark of superfluids is that they are
constrained to rotate through vortices with quantized circulation. In quantum
ferrofluids the long-range dipolar interactions add new ingredients by inducing
magnetostriction and instabilities, and also affect the structural properties
of vortices and vortex lattices. Here we give a review of the theory of
vortices in dipolar Bose-Einstein condensates, exploring the interplay of
magnetism with vorticity and contrasting this with the established behaviour in
non-dipolar condensates. We cover single vortex solutions, including structure,
energy and stability, vortex pairs, including interactions and dynamics, and
also vortex lattices. Our discussion is founded on the mean-field theory
provided by the dipolar Gross-Pitaevskii equation, ranging from analytic
treatments based on the Thomas-Fermi (hydrodynamic) and variational approaches
to full numerical simulations. Routes for generating vortices in dipolar
condensates are discussed, with particular attention paid to rotating
condensates, where surface instabilities drive the nucleation of vortices, and
lead to the emergence of rich and varied vortex lattice structures. We also
present an outlook, including potential extensions to degenerate Fermi gases,
quantum Hall physics, toroidal systems and the Berezinskii-Kosterlitz-Thouless
transition.


  Computable estimates for the error of finite element discretisations of
parabolic problems in the $L^\infty(0,T; L^2)$ norm are developed, which
exhibit constant effectivities (the ratio of the estimated error to the true
error) with respect to the simulation time. These estimates, which are of
optimal order, represent a significant advantage for long-time simulations, and
are derived using energy techniques based on elliptic reconstructions. The
effectivities of previous optimal order error estimates in this norm derived
using energy techniques are shown numerically to grow either in proportion to
the simulation duration or its square root, a key disadvantage compared with
earlier estimators derived using parabolic duality arguments. The new estimates
form a continuous family, almost all of which are new, reproducing certain
familiar energy-based estimates well suited for short-time simulations and not
available through the parabolic duality framework. For clarity, we demonstrate
the technique applied to a linear parabolic problem discretised using standard
conforming finite element methods in space coupled with backward Euler and
Crank-Nicolson time discretisations, although it can be applied much more
widely.


  We consider a two-dimensional bi-layered loop model with a certain interlayer
coupling and study its spectrum on a torus. Each layer consists of an $O(n)$
model on a honeycomb lattice with periodic boundary conditions; these layers
are stacked such that the links of the lattice intersect each other. A complex
Boltzmann weight $\lambda$ with unit modulus is assigned to each intersection
of two loops each from each layer. The model is reduced to an inhomogeneous
vertex model at a special point of parameters. The continuum partition function
is represented, based on the idea of the Coulomb gas, by a path integral over
two compact bosonic fields. The modular invariance of the partition function
follows naturally. Further, because of the topological nature of the interlayer
coupling, the fluctuation of loops decomposes into a local and a global part.
The existence of the latter leads to a sum over all the pairs of torus knots,
which can be Poisson ressummed by the M\"{o}bius inversion formula. This
reveals the operator content of the theory. The multiplicity of each operator
is explicitly given by a combination of two Ramanujan sums. We calculate each
scaling dimension as a function of $\lambda$. We present the flow of dimensions
which connects the decoupled-$O(1)$ models at $\lambda=1$ and the
layered-$O(1)$ model with the non-trivial coupling $\lambda=-1$. The lower
spectrum in the latter model is related to that of a known coset model.


  There is current interest in a possible new massive gauge boson $X$ which
mixes slightly with the $Z$ boson and accounts for certain anomalies in the LEP
data. We show why constraints on models in which the $X$ boson does not couple
to the first two families suggest dynamical electroweak symmetry breaking. The
associated TeV mass fermions make up a fourth family. Constraints on the
effects of the fourth left-handed neutrino also suggest a dynamical origin for
its Majorana mass. We finally comment on related implications for the origin of
quark masses.


  We present the design of a mesh quality indicator that can predict the
behavior of the Virtual Element Method (VEM) on a given mesh family or finite
sequence of polyhedral meshes (dataset). The mesh quality indicator is designed
to measure the violation of the mesh regularity assumptions that are normally
considered in the convergence analysis. We investigate the behavior of this new
mathematical tool on the lowest-order conforming approximation of the
three-dimensional Poisson equation. This work also assesses the convergence
rate of the VEM when applied to very general polyhedral meshes, including
non-convex and skewed three-dimensional elements. Such meshes are created
within an original mesh generation framework, which is designed to allow the
generation of meshes with very different sizes, connectivity and geometrical
properties. The obtained results show a significant correlation between the
quality measured a priori by the indicator and the effective performance of the
VEM.


  As the only semimetallic $d^{10}$-based delafossite, AgNiO$_2$ has received a
great deal of attention due to both its unique semimetallicity and its
antiferromagnetism in the NiO$_2$ layer that is coupled with a lattice
distortion. In contrast, other delafossites such as AgCoO$_2$ are insulating.
Here we study how the electronic structure of AgNi$_{1-x}$Co$_{x}$O$_2$ alloys
vary with Ni/Co concentration, in order to investigate the electronic
properties and phase stability of the intermetallics. While the electronic and
magnetic structure of delafossites have been studied using Density Functional
Theory (DFT), earlier studies have not included corrections for strong on-site
Coulomb interactions. In order to treat these interactions accurately, in this
study we use Quantum Monte Carlo (QMC) simulations to obtain accurate estimates
for the electronic and magnetic properties of AgNiO$_2$. By comparison to DFT
results we show that these electron correlations are critical to account for.
We show that Co doping on the magnetic Ni sites results in a metal-insulator
transition near $x\sim 0.33$, and reentrant behavior near $x\sim 0.66$


  We analyze the associated production at future high--energy $e^+e^-$
colliders, of first generation sleptons with neutralinos and charginos in the
modes $e^+ e^-$ and $e \gamma$, in the framework of the Minimal Supersymmetric
extension of the Standard Model. We show that the production rates, in
particular for associated production of right--handed selectrons and the
lightest neutralino which in general is the first accessible kinematically, can
be much larger than the corresponding ones for second and third generation
scalar leptons and for scalar quarks. With the high--luminosities expected at
these colliders, the detection of first generation sleptons with masses
significantly above the kinematical two--body threshold, $\sqrt{s}=
2m_{\tilde{l}}$, is thus possible in favourable regions of the parameter space.


  We consider an ensemble of diatomic molecules resonantly coupled to an
optical cavity under strong coupling conditions at normal incidence.
Photodissociation dynamics is examined via direct numerical integration of the
coupled Maxwell-Schrodinger equations with molecular ro-vibrational degrees of
freedom explicitly taken into account. It is shown that the dissociation is
significantly affected (slowed down) when the system is driven at its
polaritonic frequencies. The observed effect is demonstrated to be of transient
nature and has no classical analog. An intuitive explanation of the
dissociation slowdown at polaritonic frequencies is proposed.


  We provide a decision theoretic analysis of bandit experiments under local
asymptotics. Working within the framework of diffusion processes, we define
suitable notions of asymptotic Bayes and minimax risk for these experiments.
For normally distributed rewards, the minimal Bayes risk can be characterized
as the solution to a second-order partial differential equation (PDE). Using a
limit of experiments approach, we show that this PDE characterization also
holds asymptotically under both parametric and non-parametric distributions of
the rewards. The approach further describes the state variables it is
asymptotically sufficient to restrict attention to, and thereby suggests a
practical strategy for dimension reduction. The PDEs characterizing minimal
Bayes risk can be solved efficiently using sparse matrix routines or
Monte-Carlo methods. We derive the optimal Bayes and minimax policies from
their numerical solutions. These optimal policies substantially dominate
existing methods such as Thompson sampling; the risk of the latter is often
twice as high.


  In this paper, we investigate representation learning for low-resource
keyword spotting (KWS). The main challenges of KWS are limited labeled data and
limited available device resources. To address those challenges, we explore
representation learning for KWS by self-supervised contrastive learning and
self-training with pretrained model. First, local-global contrastive siamese
networks (LGCSiam) are designed to learn similar utterance-level
representations for similar audio samplers by proposed local-global contrastive
loss without requiring ground-truth. Second, a self-supervised pretrained
Wav2Vec 2.0 model is applied as a constraint module (WVC) to force the KWS
model to learn frame-level acoustic representations. By the LGCSiam and WVC
modules, the proposed small-footprint KWS model can be pretrained with
unlabeled data. Experiments on speech commands dataset show that the
self-training WVC module and the self-supervised LGCSiam module significantly
improve accuracy, especially in the case of training on a small labeled
dataset.


  These lecture notes provide a pedagogical introduction to some aspects of the
inflationary cosmology, including the background scalar field dynamics,
generation of primordial seed perturbations via quantum fluctuations during
inflation, and the process of reheating after inflation in the single-field
inflationary paradigm.


  Transverse-mass spectra, their inverse slopes and mean transverse masses in
relativistic collisions of heavy nuclei are analyzed in a wide range of
incident energies 2.7 GeV $\le \sqrt{s_{NN}}\le$ 39 GeV. The analysis is
performed within the three-fluid model employing three different equations of
state (EoS's): a purely hadronic EoS, an EoS with the first-order phase
transition and that with a smooth crossover transition into deconfined state.
Calculations show that inverse slopes and mean transverse masses of all the
species (with the exception of antibaryons within the hadronic scenario)
exhibit a step-like behavior similar to that observed for mesons and protons in
available experimental data. This step-like behavior takes place for all
considered EoS's and results from the freeze-out dynamics rather than is a
signal of the deconfinement transition. A good reproduction of experimental
inverse slopes and mean transverse masses for light species (up to proton) is
achieved within all the considered scenarios. The freeze-out parameters are
precisely the same as those used for reproduction of particles yields in
previous papers of this series. This became possible because the freeze-out
stage is not completely equilibrium.


  Magic-angle twisted bilayer graphene (TBG) has attracted significant interest
recently due to the discoveries of diverse correlated and topological states in
this system. Despite the extensive research on the electron-electron
interaction effects and topological properties of the electrons, the phonons of
magic-angle TBG are relatively less explored. In this work, we study the phonon
properties in magic-angle TBG based on \textit{ab} \textit{initio} deep
potential molecular dynamics. We have calculated phonon band structures and
density of states at the magic angle, and have systematically analyzed the
phonon eigenmodes at high-symmetry points in the moir\'e Brillouin zone. In
particular, at the moir\'e $\Gamma$ point, we have discovered a number of soft
modes which can exhibit dipolar-like, stripe-like, and octupolar-like
vibrational patterns within the moir\'e supercell, as well as some "vortical"
modes with nonzero curl in real space. At the moir\'e $K$/$K'$ points, there
are time-reversal breaking chiral phonon modes with nonzero local phonon
polarizations. We have further studied the phonon effects on the electronic
structures by freezing certain soft phonon modes. We find that if a soft
"stripe" phonon mode at moir\'e $\Gamma$ point is assumed to be frozen, the
system would exhibit a charge order which naturally explains the recent
observations from scanning tunnelling microscopy. Moreover, there are also
low-frequency $C_{2z}$-breaking modes at moir\'e $\Gamma$ point, which would
gap out the Dirac points at the charge neutrality point once these modes get
frozen. This provides a new perspective to the origin of correlated insulator
state at the charge neutrality point.


  Mean-field theory is a powerful tool for studying large neural networks.
However, when the system is composed of a few neurons, macroscopic differences
between the mean-field approximation and the real behavior of the network can
arise. Here we introduce a study of the dynamics of a small firing-rate network
with excitatory and inhibitory populations, in terms of local and global
bifurcations of the neural activity. Our approach is analytically tractable in
many respects, and sheds new light on the finite-size effects of the system. In
particular, we focus on the formation of multiple branching solutions of the
neural equations through spontaneous symmetry-breaking, since this phenomenon
increases considerably the complexity of the dynamical behavior of the network.
For these reasons, branching points may reveal important mechanisms through
which neurons interact and process information, which are not accounted for by
the mean-field approximation.