  Common time-explicit numerical methods for kinetic simulations of plasmas in
the low-collisions limit fall into two classes of algorithms: momentum
conserving and energy conserving. Each has certain drawbacks. The PIC algorithm
does not conserve total energy, which may lead to spurious numerical heating
(grid heating). Its overall accuracy is at most second due to the nature of the
force interpolation between grid and particle position. Energy-conserving
algorithms do not exhibit grid heating, but because their formulation uses
potentials, computationally undesirable matrix inversions may be necessary. In
addition, compared to PIC algorithms for the same accuracy, these algorithms
have higher numerical noise due to the restricted choice of particle shapes.
Here we formulate time-explicit, finite-size particle algorithms using
particular reductions of the particle distribution function. These reductions
are used in two variational principles, a Lagrangian-based and a
Hamiltonian-based in conjunction with a non-canonical Poisson bracket. The
Lagrangian formulations here generalize previous such formulations. The
Hamiltonian formulation is presented here for the first time. Many drawbacks of
the two classes of particle methods are mitigated. For example, restrictions on
particle shapes are relaxed in energy conserving algorithms, which allows to
decrease the numerical noise in these methods. The Hamiltonian formulation of
particle algorithms is done in terms of fields instead of potentials, thus
avoiding solving Poisson's equation. An algorithm that conserves both energy
and momentum is presented. Other features of the algorithms include a natural
way to perform coordinate transformations, the use of various time integrating
methods, and the ability to increase the overall accuracy beyond second order,
including all generalizations.


  The evolution of marginally bound supercluster-like objects in an
accelerating LambdaCDM Universe is followed, by means of cosmological
simulations, from the present time to an expansion factor a = 100. The objects
are identified on the basis of the binding density criterion introduced by
Dunner et al. (2006). superclusters are identified with the ones whose mass M >
10^15 M_sun/h, the most massive one with M ~ 8x10^15 M_sun/h, comparable to the
Shapley supercluster. The spatial distribution of the superclusters remains
essentially the same after the present epoch, reflecting the halting growth of
the Cosmic Web as Lambda gets to dominate the expansion of the Universe. The
same trend can be seen in the stagnation of the development of the mass
function of virialized haloes and bound objects. The situation is considerably
different when looking at the internal evolution, quantified in terms of their
shape, compactness and density profile, and substructure in terms of their
multiplicity function. We find a continuing evolution from a wide range of
triaxial shapes at a = 1 to almost perfect spherical shapes at a = 100. We also
find a systematic trend towards a higher concentration. Meanwhile, we see their
substructure gradually disappearing, as the surrounding subclumps fall in and
merge to form one coherent, virialized system.


  Neural Architecture Search (NAS) has achieved great success in image
classification task. Some recent works have managed to explore the automatic
design of efficient backbone or feature fusion layer for object detection.
However, these methods focus on searching only one certain component of object
detector while leaving others manually designed. We identify the inconsistency
between searched component and manually designed ones would withhold the
detector of stronger performance. To this end, we propose a hierarchical
trinity search framework to simultaneously discover efficient architectures for
all components (i.e. backbone, neck, and head) of object detector in an
end-to-end manner. In addition, we empirically reveal that different parts of
the detector prefer different operators. Motivated by this, we employ a novel
scheme to automatically screen different sub search spaces for different
components so as to perform the end-to-end search for each component on the
corresponding sub search space efficiently. Without bells and whistles, our
searched architecture, namely Hit-Detector, achieves 41.4\% mAP on COCO minival
set with 27M parameters. Our implementation is available at
https://github.com/ggjy/HitDet.pytorch.


  Graph neural network architectures aligned with the $k$-dimensional
Weisfeiler--Leman ($k$-WL) hierarchy offer theoretically well-understood
expressive power. However, these architectures often fail to deliver
state-of-the-art predictive performance on real-world graphs, limiting their
practical utility. While recent works aligning graph transformer architectures
with the $k$-WL hierarchy have shown promising empirical results, employing
transformers for higher orders of $k$ remains challenging due to a prohibitive
runtime and memory complexity of self-attention as well as impractical
architectural assumptions, such as an infeasible number of attention heads.
Here, we advance the alignment of transformers with the $k$-WL hierarchy,
showing stronger expressivity results for each $k$, making them more feasible
in practice. In addition, we develop a theoretical framework that allows the
study of established positional encodings such as Laplacian PEs and SPE. We
evaluate our transformers on the large-scale PCQM4Mv2 dataset, showing
competitive predictive performance with the state-of-the-art and demonstrating
strong downstream performance when fine-tuning them on small-scale molecular
datasets. Our code is available at
https://github.com/luis-mueller/wl-transformers.


  Compressive sensing (CS) is a new methodology to capture signals at lower
rate than the Nyquist sampling rate when the signals are sparse or sparse in
some domain. The performance of CS estimators is analyzed in this paper using
tools from statistical mechanics, especially called replica method. This method
has been used to analyze communication systems like Code Division Multiple
Access (CDMA) and multiple input multi- ple output (MIMO) systems with large
size. Replica analysis, now days rigorously proved, is an efficient tool to
analyze large systems in general. Specifically, we analyze the performance of
some of the estimators used in CS like LASSO (the Least Absolute Shrinkage and
Selection Operator) estimator and Zero-Norm regularizing estimator as a special
case of maximum a posteriori (MAP) estimator by using Bayesian framework to
connect the CS estimators and replica method. We use both replica symmetric
(RS) ansatz and one-step replica symmetry breaking (1RSB) ansatz, clamming the
latter is efficient when the problem is not convex. This work is more
analytical in its form. It is deferred for next step to focus on the numerical
results.


  A study of two-pion scattering for the isospin channels, $I=0$ and $I=2$,
using lattice QCD is presented. M\"obius domain wall fermions on top of the
Iwasaki-DSDR gauge action for gluons with periodic boundary conditions are used
for the lattice computations which are carried out on two ensembles of gauge
field configurations generated by the RBC and UKQCD collaborations with
physical masses, inverse lattice spacings of 1.023 and 1.378 GeV, and spatial
extents of $L=4.63$ and 4.58 fm, respectively. The all-to-all propagator method
is employed to compute a matrix of correlation functions of two-pion operators.
The generalized eigenvalue problem (GEVP) is solved for a matrix of correlation
functions to extract phase shifts with multiple states, two pions with a
non-zero relative momentum as well as two pions at rest. Our results for phase
shifts for both $I=0$ and $I=2$ channels are consistent with and the Roy
Equation and chiral perturbation theory, though at this preliminary stage our
errors for $I=0$ are large. An important outcome of this work is that we are
successful in extracting two-pion excited states, which are useful for studying
$K\to\pi\pi$ decay, on physical-mass ensembles using GEVP.


  A perfect code $C$ in a graph $\Gamma$ is an independent set of vertices of
$\Gamma$ such that every vertex outside of $C$ is adjacent to a unique vertex
in $C$, and a total perfect code $C$ in $\Gamma$ is a set of vertices of
$\Gamma$ such that every vertex of $\Gamma$ is adjacent to a unique vertex in
$C$. Let $G$ be a finite group and $X$ a normal subset of $G$. The Cayley sum
graph $\mathrm{CS}(G,X)$ of $G$ with the connection set $X$ is the graph with
vertex set $G$ and two vertices $g$ and $h$ being adjacent if and only if
$gh\in X$ and $g\neq h$. In this paper, we give some necessary conditions of a
subgroup of a given group being a (total) perfect code in a Cayley sum graph of
the group. As applications, the Cayley sum graphs of some families of groups
which admit a subgroup as a (total) perfect code are classified.


  In this paper, we present an analytical solution for the Bohr Hamiltonian
with the trigonometric P\"oschl Teller (P.T) potential in the cases of {\gamma}
unstable nuclei and {\gamma} stable axially symmetric prolate deformed ones
with {\gamma} = 0. The energy spectra and corresponding wave functions are
derived by means of the asymptotic iteration method. In addition, B(E2)
transition rates are calculated and compared with experimental data. Overall
good agreement is obtained for inter and intra band transitions within ground
state and \b{eta} bands. Our numerical results, particularly for transition
rates are much closer to experimental ones in comparison with those obtained by
Davidson and Kratzer potentials which are widely used in the literature.


  Predictive control is frequently used for control problems involving
constraints. Being an optimization based technique utilizing a user specified
so-called stage cost, performance properties, i.e., bounds on the infinite
horizon accumulated stage cost, aside closed-loop stability are of interest. To
achieve good performance and to influence the region of attraction associated
with the prediction horizon, the terminal cost of the predictive controller's
optimization objective is a key design factor. Approximate dynamic programming
refers to one particular approximation paradigm that pursues iterative cost
adaptation over a state domain. Troubled by approximation errors, the
associated approximate optimal controller is, in general, not necessarily
stabilizing nor is its performance quantifiable on the entire approximation
domain. Using a parametric terminal cost trained via approximate dynamic
programming, a stabilizing predictive controller is proposed whose performance
can directly be related to cost approximation errors. The controller further
ensures closed-loop asymptotic stability beyond the training domain of the
approximate optimal controller associated to the terminal cost.


  The Kuramoto-Sivashinsky PDE on the line with odd and periodic boundary
conditions and with parameter $\nu=0.1212$ is considered. We give a
computer-assisted proof the existence of symbolic dynamics and countable
infinity of periodic orbits with arbitrary large periods.


  We show that the nonlocal two-flavor Nambu--Jona-Lasinio model predicts the
enhancement of both chiral and axial symmetry breaking as the chiral imbalance
of hot QCD matter, regulated by a chiral chemical potential $\mu_5$, increases.
The two crossovers are reasonably close to each other in the range of $\mu_5$
examined here and the pseudocritical temperatures rise with $\mu_5$. The
curvatures of the chiral and axial crossovers for the chiral quark chemical
potential approximately coincide and give $\kappa_5 \simeq - 0.011$. We point
out that the presence of $\mu_5$ in thermodynamic equilibrium is inconsistent
with the fact that the chiral charge is not a Noether-conserved quantity for
massive fermions. The chiral chemical potential should not, therefore, be
considered as a true chemical potential that sets a thermodynamically stable
environment in the massive theory, but rather than as a new coupling that may
require a renormalization in the ultraviolet domain. The divergence of an
unrenormalized chiral density, \corr{coming from zero-point fermionic
fluctuations,} is a consequence of this property. We propose a solution to this
problem via a renormalization procedure.


  Principal component analysis (PCA) is a popular dimension reduction technique
often used to visualize high-dimensional data structures. In genomics, this can
involve millions of variables, but only tens to hundreds of observations.
Theoretically, such extreme high-dimensionality will cause biased or
inconsistent eigenvector estimates, but in practice the principal component
scores are used for visualization with great success. In this paper, we explore
when and why the classical principal component scores can be used to visualize
structures in high-dimensional data, even when there are few observations
compared to the number of variables. Our argument is two-fold: First, we argue
that eigenvectors related to pervasive signals will have eigenvalues scaling
linearly with the number of variables. Second, we prove that for linearly
increasing eigenvalues, the sample component scores will be scaled and rotated
versions of the population scores, asymptotically. Thus the visual information
of the sample scores will be unchanged, even though the sample eigenvectors are
biased. In the case of pervasive signals, the principal component scores can be
used to visualize the population structures, even in extreme high-dimensional
situations.


  In this chapter, we present an overview of experiments with trapped Rydberg
ions and outline the advantages and challenges of developing applications of
this new platform for quantum computing, sensing and simulation. Trapped
Rydberg ions feature several important properties, unique in their combination:
they are tightly bound in a harmonic potential of a Paul trap, in which their
internal and external degrees of freedom can be controlled in a precise
fashion. High fidelity state preparation of both internal and motional states
of the ions has been demonstrated, and the internal states have been employed
to store and manipulate qubit information. Furthermore, strong dipolar
interactions can be realised between ions in Rydberg states and be explored for
investigating correlated many-body systems. By laser coupling to Rydberg
states, the polarisability of the ions can be both enhanced and tuned. This can
be used to control the interactions with the trapping fields in a Paul trap as
well as dipolar interactions between the ions. Thus, trapped Rydberg ions
present an attractive alternative for fast entangling operations as compared to
those mediated by normal modes of trapped ions, which are advantageous for a
future quantum computer or a quantum simulator.


  Where can we find malware source code? This question is motivated by a real
need: there is a dearth of malware source code, which impedes various types of
security research. Our work is driven by the following insight: public
archives, like GitHub, have a surprising number of malware repositories.
Capitalizing on this opportunity, we propose, SourceFinder, a
supervised-learning approach to identify repositories of malware source code
efficiently. We evaluate and apply our approach using 97K repositories from
GitHub. First, we show that our approach identifies malware repositories with
89% precision and 86% recall using a labeled dataset. Second, we use
SourceFinder to identify 7504 malware source code repositories, which arguably
constitutes the largest malware source code database. Finally, we study the
fundamental properties and trends of the malware repositories and their
authors. The number of such repositories appears to be growing by an order of
magnitude every 4 years, and 18 malware authors seem to be "professionals" with
well-established online reputation. We argue that our approach and our large
repository of malware source code can be a catalyst for research studies, which
are currently not possible.


  Though the neutron mass is larger than the proton mass and obviously one
expects in $e^+e^-$ annihilation a creation of more $p \bar p$ pairs in
comparison with $n \bar n$ at the same energy, just the opposite inequality for
the corresponding total cross sections $\sigma_{tot}(e^+e^- \to n \bar n) >
\sigma_{tot}(e^+e^- \to p \bar p)$ has been revealed in the analysis of only
the present time existing proton electromagnetic form factors data by the
unitary and analytic approach.


  Consider the wave propagation in a two-layered medium consisting of a
homogeneous compressible air or fluid on top of a homogeneous isotropic elastic
solid. The interface between the two layers is assumed to be an unbounded rough
surface. This paper concerns the time-domain analysis of such an
acoustic-elastic interaction problem in an unbounded structure in three
dimensions. Using an exact transparent boundary condition and suitable
interface conditions, we study an initial-boundary value problem for the
coupling of the Helmholtz equation and the Navier equation. The well-posedness
and stability are established for the reduced problem. Our proof is based on
the method of energy, the Lax--Milgram lemma, and the inversion theorem of the
Laplace transform. Moreover, a priori estimates with explicit dependence on the
time are achieved for the quantities of acoustic pressure and elastic
displacement by taking special test functions for the time-domain variational
problem.


  Within the Rayleigh-Helmholtz model of active Brownian particles activity is
due to a non-linear velocity dependent force. In the presence of an external
trapping potential or a constant force, the steady state of the system breaks
detailed balance producing a net entropy. Using molecular dynamics simulations,
we obtain the probability distributions of entropy production in these steady
states. The distribution functions obey detailed fluctuation theorem for
entropy production. Using simulation results, we further show that the steady
state response function obeys a modified fluctuation-dissipation relation.


  Fuzzing is a highly-scalable software testing technique that uncovers bugs in
a target program by executing it with mutated inputs. Over the life of a
fuzzing campaign, the fuzzer accumulates inputs inducing new and interesting
target behaviors, drawing from these inputs for further mutation. This rapidly
results in a large number of inputs to select from, making it challenging to
quickly and accurately select the "most promising" input for mutation.
Reinforcement learning (RL) provides a natural solution to this "seed
scheduling" problem: the fuzzer dynamically adapts its selection strategy by
learning from past results. However, existing RL approaches are (a)
computationally expensive (reducing fuzzer throughput) and/or (b) require
hyperparameter tuning (reducing generality across targets and input types). To
this end, we propose T-Scheduler, a seed scheduler built on multi-armed bandit
theory that automatically adapts to the target without any hyperparameter
tuning. We evaluate T-Scheduler over 35 CPU-yr of fuzzing, comparing it to 11
state-of-the-art schedulers. Our results show that T-Scheduler improves on
these 11 schedulers on both bug-finding and coverage-expansion abilities.


  We study the rotational motion of nano-flake ferromagnetic discs suspended in
a Newtonian fluid, as a potential material owing the vortex-like magnetic
configuration. Using analytical expressions for hydrodynamic, magnetic and
Brownian torques, the stochastic angular momentum equation is determined in the
dilute limit conditions under applied magnetic field. Results are compared
against experimental ones and excellent agreement is observed. We also estimate
the uncertainty in the orientation of the discs due to the Brownian torque when
an external magnetic field aligns them. Interestingly, this uncertainty is
roughly proportional to the ratio of thermal energy of fluid to the magnetic
energy stored in the discs. Our approach can be implemented in many practical
applications including biotechnology and multi-functional fluidics.


  The standard imaging algorithm for interferometric radio data, CLEAN, is
optimal for point source observations, but suboptimal for diffuse emission.
Recently, RESOLVE, a new Bayesian algorithm has been developed, which is ideal
for extended source imaging. Unfortunately, RESOLVE is computationally very
expensive. In this paper we present fastRESOLVE, a modification of RESOLVE
based on an approximation of the interferometric likelihood that allows us to
avoid expensive gridding routines and consequently gain a factor of roughly 100
in computation time. Furthermore, we include a Bayesian estimation of the
measurement uncertainty of the visibilities into the imaging, a procedure not
applied in aperture synthesis before. The algorithm requires little to no user
input compared to the standard method CLEAN while being superior for extended
and faint emission. We apply the algorithm to VLA data of Abell 2199 and show
that it resolves more detailed structures.


  More and more works deal with statistical systems far from equilibrium,
dominated by unidirectional stochastic processes augmented by rare resets. We
analyze the construction of the entropic distance measure appropriate for such
dynamics. We demonstrate that a power-like nonlinearity in the state
probability in the master equation naturally leads to the Tsallis
(Havrda-Charv\'at, Acz\'el-Dar\'oczy) q-entropy formula in the context of
seeking for the maximal entropy state at stationarity. A few possible
applications of a certain simple and linear master equation to phenomena
studied in statistical physics are listed at the end.


  For fixed $k$ we prove exponential lower bounds on the equilateral number of
subspaces of $\ell_{\infty}^n$ of codimension $k$. In particular, we show that
if the unit ball of a normed space of dimension $n$ is a centrally symmetric
polytope with at most $\frac{4n}{3}-o(n)$ pairs of facets, then it has an
equilateral set of cardinality at least $n+1$. These include subspaces of
codimension $2$ of $\ell_{\infty}^{n+2}$ for $n\geq 9$ and of codimension $3$
of $\ell_{\infty}^{n+3}$ for $n\geq 15$.


  In this paper, a new mathematical formulation for the problem of
de-anonymizing social network users by actively querying their membership in
social network groups is introduced. In this formulation, the attacker has
access to a noisy observation of the group membership of each user in the
social network. When an unidentified victim visits a malicious website, the
attacker uses browser history sniffing to make queries regarding the victim's
social media activity. Particularly, it can make polar queries regarding the
victim's group memberships and the victim's identity. The attacker receives
noisy responses to her queries. The goal is to de-anonymize the victim with the
minimum number of queries. Starting with a rigorous mathematical model for this
active de-anonymization problem, an upper bound on the attacker's expected
query cost is derived, and new attack algorithms are proposed which achieve
this bound. These algorithms vary in computational cost and performance. The
results suggest that prior heuristic approaches to this problem provide
sub-optimal solutions.


  Nuclear interactions evolved via renormalization group methods to lower
resolution become increasingly non-local (off-diagonal in coordinate space) as
they are softened. This inhibits both the development of intuition about the
interactions and their use with some methods for solving the quantum many-body
problem. By applying "local projections", a softened interaction can be reduced
to a local effective interaction plus a non-local residual interaction. At the
two-body level, a local projection after similarity renormalization group (SRG)
evolution manifests the elimination of short-range repulsive cores and the flow
toward universal low-momentum interactions. The SRG residual interaction is
found to be relatively weak at low energy, which motivates a perturbative
treatment.


  Predicting ATP-Protein Binding sites in genes is of great significance in the
field of Biology and Medicine. The majority of research in this field has been
conducted through time- and resource-intensive 'wet experiments' in
laboratories. Over the years, researchers have been investigating computational
methods computational methods to accomplish the same goals, utilising the
strength of advanced Deep Learning and NLP algorithms. In this paper, we
propose to develop methods to classify ATP-Protein binding sites. We conducted
various experiments mainly using PSSMs and several word embeddings as features.
We used 2D CNNs and LightGBM classifiers as our chief Deep Learning Algorithms.
The MP3Vec and BERT models have also been subjected to testing in our study.
The outcomes of our experiments demonstrated improvement over the
state-of-the-art benchmarks.


  We study non-Hermitian quantum mechanics in the presence of a minimal length.
In particular we obtain exact solutions of a non-Hermitian displaced harmonic
oscillator and the Swanson model with minimal length uncertainty. The spectrum
in both the cases are found to be real. It is also shown that the models are
$\eta$ pseudo-Hermitian and the metric operator is found explicitly in both the
cases.


  A few decades after Hill's work on nano-thermodynamics, the development of a
thermodynamic framework, to account consistently for the fluctuations of small
systems due to their interactions with the surrounding environment, is still
underway. Here we discuss how, in a small system, the interaction energy with
the environment may be described through a conjugate pair of intensive and
extensive variables, giving rise to a Gibbs thermodynamics with an additional
thermodynamic degree of freedom. The relevant thermodynamic potentials help
describe the equilibrium conditions and the material properties that measure
the susceptibility of the system to the interaction with the environment. The
resulting generalized ensembles, which describe the non-negligible, small
system fluctuations, are shown to be equivalent. Away from the average
thermodynamic state, the availability describes the distance between system and
the environment, in terms of the maximum work extractable from the fluctuation,
and a proper definition of entropy extends the thermodynamics to the generic
fluctuating state. From the latter state, entropic forces arise to restore the
average thermodynamic state. Our framework unifies and extends the ensemble
thermodynamics by Hill and the recent advances in statistical mechanics under
strong coupling and reduces to classical macroscopic thermodynamics when the
system is large. The particular case of a small ideal gas system is discussed
in detail and the example of a single particle immersed in a bath is revisited
in the light of the new formalism.


  We introduce Mathador-LM, a new benchmark for evaluating the mathematical
reasoning on large language models (LLMs), combining ruleset interpretation,
planning, and problem-solving. This benchmark is inspired by the Mathador game,
where the objective is to reach a target number using basic arithmetic
operations on a given set of base numbers, following a simple set of rules. We
show that, across leading LLMs, we obtain stable average performance while
generating benchmark instances dynamically, following a target difficulty
level. Thus, our benchmark alleviates concerns about test-set leakage into
training data, an issue that often undermines popular benchmarks. Additionally,
we conduct a comprehensive evaluation of both open and closed-source
state-of-the-art LLMs on Mathador-LM. Our findings reveal that contemporary
models struggle with Mathador-LM, scoring significantly lower than average 3rd
graders. This stands in stark contrast to their strong performance on popular
mathematical reasoning benchmarks.


  Inelastic scattering of photons is a promising technique to manipulate
magnons but it suffers from weak intrinsic coupling. We theoretically discuss
an idea to increase optomagnonic coupling in optical whispering gallery mode
cavities, by generalizing previous analysis to include the exchange
interaction. We predict that the optomagnonic coupling constant to surface
magnons in yttrium iron garnet (YIG) spheres with radius $300\,\mathrm{\mu}$m
can be up to $40$ times larger than that to the macrospin Kittel mode. Whereas
this enhancement falls short of the requirements for magnon manipulation in
YIG, nanostructuring and/or materials with larger magneto-optical constants can
bridge this gap.


  We introduce SimBAL, a novel spectral-synthesis procedure that uses large
grids of ionic column densities generated by the photoionization code Cloudy
and a Bayesian model calibration to forward-model broad absorption line quasar
spectra. We used SimBAL to analyze the HST COS spectrum of the low-redshift
BALQ SDSS J085053.12+445122.5. SimBAL analysis yielded velocity-resolved
information about the physical conditions of the absorbing gas. We found that
the ionization parameter and column density increase, and the covering fraction
decreases as a function of velocity. The total log column density is 22.9
(22.4) [cm^-2] for solar (Z=3Z_\odot) metallicity. The outflow lies 1--3
parsecs from the central engine, consistent with the estimated location of the
torus. The mass outflow rate is 17--28 M_\odot yr^-1, the momentum flux is
consistent with L_Bol/c, and the ratio of the kinematic to bolometric
luminosity is 0.8--0.9%. The outflow velocity is similar to the escape velocity
at the absorber's location, and force multiplier analysis indicates that part
of the outflow could originate in resonance-line driving. The location near the
torus suggests that dust scattering may play a role in the acceleration,
although the lack of reddening in this UV-selected object indictes a relatively
dust-free line of sight. The low accretion rate (0.06 L_Edd) and compact
outflow suggests that SDSS~J0850+4451 might be a quasar past its era of
feedback, although since its mass outflow is about 8 times the accretion rate,
the wind is likely integral to the accretion physics of the central engine.


  We introduce a new family of temporal logics designed to finely balance the
trade-off between expressivity and complexity. Their key feature is the
possibility of defining operators of a new kind that we call transformation
operators. Some of them subsume existing temporal operators, while others are
entirely novel. Of particular interest are transformation operators based on
semigroups. They enable logics to harness the richness of semigroup theory, and
we show them to yield logics capable of creating hierarchies of increasing
expressivity and complexity which are non-trivial to characterise in existing
logics. The result is a genuinely novel and yet unexplored landscape of
temporal logics, each of them with the potential of matching the trade-off
between expressivity and complexity required by specific applications.


  A cyclic cover over the Riemann sphere branched at four points inherits a
natural flat structure from the "pillow" flat structure on the basic sphere. We
give an explicit formula for all individual Lyapunov exponents of the Hodge
bundle over the corresponding arithmetic Teichmuller curve. The key technical
element is evaluation of degrees of line subbundles of the Hodge bundle,
corresponding to eigenspaces of the induced action of deck transformations.


  The effective on-site Coulomb interaction (Hubbard $U$) between localized
electrons at crystal surfaces is expected to be enhanced due to the reduced
coordination number and reduced subsequent screening. By means of first
principles calculations employing the constrained random-phase approximation
(cRPA) we show that this is indeed the case for simple metals and insulators
but not necessarily for transition metals and insulators that exhibit
pronounced surface states. In the latter case, the screening contribution from
surface states as well as the influence of the band narrowing increases the
electron polarization to such an extent as to overcompensate the decrease
resulting from the reduced effective screening volume. The Hubbard $U$
parameter is thus substantially reduced in some cases, e.g., by around 30% for
the (100) surface of bcc Cr.


  Extracting communities using existing community detection algorithms yields
dense sub-networks that are difficult to analyse. Extracting a smaller sample
that embodies the relationships of a list of suspects is an important part of
the beginning of an investigation. In this paper, we present the efficacy of
our shortest paths network search algorithm (SPNSA) that begins with an
"algorithm feed", a small subset of nodes of particular interest, and builds an
investigative sub-network. The algorithm feed may consist of known criminals or
suspects, or persons of influence. This sets our approach apart from existing
community detection algorithms. We apply the SPNSA on the Enron Dataset of
e-mail communications starting with those convicted of money laundering in
relation to the collapse of Enron as the algorithm feed. The algorithm produces
sparse and small sub-networks that could feasibly identify a list of persons
and relationships to be further investigated. In contrast, we show that
identifying sub-networks of interest using either community detection
algorithms or a k-Neighbourhood approach produces sub-networks of much larger
size and complexity. When the 18 top managers of Enron were used as the
algorithm feed, the resulting sub-network identified 4 convicted criminals that
were not managers and so not part of the algorithm feed. We also directly
tested the SPNSA by removing one of the convicted criminals from the algorithm
feed and re-running the algorithm; in 5 out of 9 cases the left out criminal
occurred in the resulting sub-network.


  We present a study on quantum gravity effects on the shadow of a rotating
black hole (BH) obtained in the setting of the asymptotically safe gravity. The
rotating metric, which results from a static regular one recently presented in
the literature, is generated by using the generalized Newman-Janis algorithm.
The novelty of the static regular metric lies in the fact that it is the
outcome of an effective Lagrangian which describes dust whose spherically
symmetric collapse is non-singular as a consequence of the antiscreening
character of gravity at small distances. The effective Lagrangian includes a
multiplicative coupling, denoted as chi, with the Lagrangian of the collapsing
fluid. The resulting exterior metric for large radii depends on a free
parameter xi which captures the quantum gravity effects. The form of the
coupling chi and its connection with the quantum parameter xi are determined by
the running of the Newton coupling G(k) along a renormalization group
trajectory that stops at the ultraviolet non-gaussian fixed point of the
asymptotic safety theory for quantum gravity. Varying both the spin parameter
a/M and the quantum parameter xi, we explore the quantum gravity effects on
several astronomical observables used to describe the morphology of the shadow
cast by rotating BHs. In order to obtain constraints on the parameter xi, we
confront our results with the recent Event Horizon Telescope (EHT) observations
of the shadows of the supermassive BHs M87 and Sgr A. We find that the ranges
of variation of all the studied shadow observables fall entirely within the
ranges determined by the EHT collaboration. We then conclude that the current
astronomical data do not rule out the renormalization group improved rotating
BH.


  The Frank-Wolfe algorithm is a method for constrained optimization that
relies on linear minimizations, as opposed to projections. Therefore, a
motivation put forward in a large body of work on the Frank-Wolfe algorithm is
the computational advantage of solving linear minimizations instead of
projections. However, the discussions supporting this advantage are often too
succinct or incomplete. In this paper, we review the complexity bounds for both
tasks on several sets commonly used in optimization. Projection methods onto
the $\ell_p$-ball, $p\in\left]1,2\right[\cup\left]2,+\infty\right[$, and the
Birkhoff polytope are also proposed.


  Quantum mechanics can emerge from classical statistics. A typical quantum
system describes an isolated subsystem of a classical statistical ensemble with
infinitely many classical states. The state of this subsystem can be
characterized by only a few probabilistic observables. Their expectation values
define a density matrix if they obey a "purity constraint". Then all the usual
laws of quantum mechanics follow, including Heisenberg's uncertainty relation,
entanglement and a violation of Bell's inequalities. No concepts beyond
classical statistics are needed for quantum physics - the differences are only
apparent and result from the particularities of those classical statistical
systems which admit a quantum mechanical description. Born's rule for quantum
mechanical probabilities follows from the probability concept for a classical
statistical ensemble. In particular, we show how the non-commuting properties
of quantum operators are associated to the use of conditional probabilities
within the classical system, and how a unitary time evolution reflects the
isolation of the subsystem. As an illustration, we discuss a classical
statistical implementation of a quantum computer.


  At present, there are a large number of quantum neural network models to deal
with Euclidean spatial data, while little research have been conducted on
non-Euclidean spatial data. In this paper, we propose a novel quantum graph
convolutional neural network (QGCN) model based on quantum parametric circuits
and utilize the computing power of quantum systems to accomplish graph
classification tasks in traditional machine learning. The proposed QGCN model
has a similar architecture as the classical graph convolutional neural
networks, which can illustrate the topology of the graph type data and
efficiently learn the hidden layer representation of node features as well.
Numerical simulation results on a graph dataset demonstrate that the proposed
model can be effectively trained and has good performance in graph level
classification tasks.


  The solution to a stochastic optimal control problem can be determined by
computing the value function from a discretization of the associated
Hamilton-Jacobi-Bellman equation. Alternatively, the problem can be
reformulated in terms of a pair of forward-backward SDEs, which makes
Monte-Carlo techniques applicable. More recently, the problem has also been
viewed from the perspective of forward and reverse time SDEs and their
associated Fokker-Planck equations. This approach is closely related to
techniques used in diffusion-based generative models. Forward and reverse time
formulations express the value function as the ratio of two probability density
functions; one stemming from a forward McKean-Vlasov SDE and another one from a
reverse McKean-Vlasov SDE. In this paper, we extend this approach to a more
general class of stochastic optimal control problems and combine it with
ensemble Kalman filter type and diffusion map approximation techniques in order
to obtain efficient and robust particle-based algorithms.


  A discussion of the AdS/CFT correspondence in IIB is given in a superspace
context. The main emphasis is on the properties of SCFT correlators on the
boundary which are studied using harmonic superspace techniques. These
techniques provide the easiest way of implementing the superconformal Ward
identities. The Ward identities, together with analyticity, can be used to give
a compelling argument in support of the non-renormalisation theorems for two-
and three-point functions, and to establish the triviality of extremal and
next-to-extremal correlation functions. The OPE in is also briefly discussed.


  We present the results of resonant x-ray scattering measurements and
electronic structure calculations on the monoarsenide FeAs. We elucidate
details of the magnetic structure, showing the ratio of ellipticity of the spin
helix is larger than previously thought, at 2.58(3), and reveal both a
right-handed chirality and an out of plane component of the magnetic moments in
the spin helix. We find that electronic structure calculations and analysis of
the spin-orbit interaction are able to qualitatively account for this canting.


  The basic ingredient of CCFT holography is to regard four-dimensional
amplitudes describing conformal wave packets as two-dimensional conformal
correlation functions of the operators associated to external particles. By
construction, these operators transform as quasi-primary fields under SL(2,C)
conformal symmetry group of the celestial sphere. We derive the OPE of the CCFT
energy-momentum tensor with the operators representing gauge bosons and show
that they transform as Virasoro primaries under diffeomorphisms of the
celestial sphere.


  A system of N classical Coulomb charges trapped in a harmonic potential
displays shell structure and orientational ordering. The local density profile
is well understood from theory, simulation, and experiment. Here, pair
correlations are considered for this highly inhomogeneous system for both the
fluid and ordered states. In the former, it is noted that there is a close
relationship to pair correlations in the uniform OCP. For the ordered state, it
is shown that the disordered "tiling" is closely related to the ground state
Thomson sites for a single sphere.


  We provide a simple transfer function that determines the effect of an early
matter dominated era on the gravitational wave background and show that a large
class of compactifications of superstring theory might be tested by
observations of the gravitational wave background from inflation. For large
enough reheating temperatures $> 10^9 \GeV$ the test applies to all models
containing at least one scalar with mass $< 10^{12}\GeV$ that acquires a large
initial oscillation amplitude after inflation and has only gravitational
interaction strength, i.e., a field with the typical properties of a modulus.


  The first representation theorem establishes a correspondence between
positive, self-adjoint operators and closed, positive forms on Hilbert spaces.
The aim of this paper is to show that some of the results remain true if the
underlying space is a reflexive Banach space. In particular, the construction
of the Friedrichs extension and the form sum of positive operators can be
carried over to this case.


  Here, we study the selection problem for the vanishing discount approximation
of non-convex, first-order Hamilton-Jacobi equations. While the selection
problem is well understood for convex Hamiltonians, the selection problem for
non-convex Hamiltonians has thus far not been studied. We begin our study by
examining a generalized discounted Hamilton-Jacobi equation. Next, using an
exponential transformation, we apply our methods to strictly quasi-convex and
to some non-convex Hamilton-Jacobi equations. Finally, we examine a non-convex
Hamiltonian with flat parts to which our results do not directly apply. In this
case, we establish the convergence by a direct approach.


  The term integrable asymptotically conformal at a point for a quasiconformal
map defined on a domain is defined. Furthermore, we prove that there is a
normal form for this kind attracting or repelling or super-attracting fixed
point with the control condition under a quasiconformal change of coordinate
which is also asymptotically conformal at this fixed point. The change of
coordinate is essentially unique. These results generalize K\"onig's Theorem
and B\"ottcher's Theorem in classical complex analysis. The idea in proofs is
new and uses holomorphic motion theory and provides a new understanding of the
inside mechanism of these two famous theorems too.


  In the last years, several hierarchical frameworks have been proposed to deal
with highly-redundant robotic systems. Some of that systems are expected to
perform multiple tasks and physically to interact with the environment.
However, none of the proposed frameworks is able to manage multiple tasks with
arbitrary task dimensions, while respecting unilateral constraints at position,
velocity, acceleration and force level, and at the same time, to react
intuitively to external forces. This work proposes a framework that addresses
this problem. The framework is tested in simulation and on a real robot. The
experiments on the redundant collaborative industrial robot (KUKA LBR iiwa)
demonstrate the advantage of the framework compared to state-of-the-art
approaches. The framework reacts intuitively to external forces and is able to
limit joint positions, velocities, accelerations and forces.


  We study the depth properties of the associated graded ring of an m-primary
ideal I in terms of numerical data attached to the ideal I. We also find bounds
on the Hilbert coefficients of I by means of the Sally module S_J(I) of I with
respect to a minimal reduction J of I.


  In this work, we present novel analytical solutions for static and
spherically symmetric wormhole geometries threaded by an anisotropic
distribution of matter conformally coupled to a scalar ghost field. We explore
the main features of the theory, such as the dynamics of the scalar field and
matter throughout the wormhole, as well as the role played by the non-minimal
coupling. Furthermore, coupled ghosts in the presence of a scalar potential are
considered and traversability conditions are analysed within such geometrical
scheme. More specifically, we find analytical solutions that although the
energy density of the ghost is strictly negative, the energy density of matter
may attain positive values.


  Supersymmetric (SUSY) models with heavy sfermions ($m_{\tilde{f}} \sim 10$
TeV) in the first two generations and the third generation sfermion masses
below 1 TeV can solve the SUSY flavor and the CP problems as well as satisfy
naturalness constraints. We study the phenomenology of a string-inspired
scenario and compare it with the minimal supergravity unified model (mSUGRA).
The SUSY trilepton signature at the upgraded Tevatron, the $b\to s\gamma$
branching fraction and the neutralino dark matter relic density in this model
can differ significantly from the mSUGRA model.


  We review some experimental consequences of the presence of superstrong
magnetic fields of order of the nuclear scale in noncentral heavy-ion
collisions. We present lattice estimates for the strength of the Chiral
Magnetic Effect (CME) for different quark flavours and argue that the
dependence of the anisotropy of the distribution of emitted hadrons on their
flavor content might be used as another experimental evidence of the CME.
Another possible effect of superstrong magnetic field might be the observed
abnormal enhancement of dilepton yield. We show that the presence of the
magnetic field leads to a specific anisotropy of the dilepton emission rate.


  We prove useful necessary and sufficient conditions for an elliptic curve
over a number field to admit a surjective adelic Galois representation. Using
these conditions, we compute an example of a number field K and an elliptic
curve E/K whose corresponding adelic representation is surjective.


  We investigate the local fluctuations of filamentous actin (F-actin), with
focus on the skeletal thin filament, using single-particle optical trapping
interferometry. This experimental technique allows us to detect the Brownian
motion of a tracer bead immersed in a complex fluid with nanometric resolution
at the microsecond time-scale. The mean square displacement, loss modulus, and
velocity autocorrelation function (VAF) of the trapped microprobes in the fluid
follow power-law behaviors, whose exponents can be determined in the
short-time/high-frequency regime along several decades. We obtain 7/8
subdiffusive power-law exponents for polystyrene depleted microtracers at low
optical trapping forces. Microrheologically, the elastic modulus of these
suspensions is observed to be constant up to the limit of high frequencies,
confirming the origin of this subdiffusive exponent on the local longitudinal
fluctuations of the polymers. Deviations from this value are measured and
discussed in relation to the characteristic lengths scales of these F-actin
networks and probes' properties, and also in connection with the different
power-law exponents detected in the VAFs. Finally, we observe that the thin
filament, composed by tropomyosin (Tm) and troponin (Tn) coupled to F-actin in
the presence of Ca$^{2+}$, returns exponent values less dispersed than F-actin
alone, which we interpret as a micro-measurement of the filament stabilization.


  Bluetooth Low Energy (BLE) is a short-range data transmission technology that
is used for multimedia file sharing, home automation, and internet-of-things
application. In this work, we perform packet error rate (PER) measurement and
RF testing of BLE receiver in the harsh electromagnetic environment and in
presence of RF interference. We check the PER performance in the line-of-sight
(LOS) and non-line-of-sight (NLOS) scenario in absence of any interfering
signal and in presence of wideband WLAN interference. The BLE PER measurements
are conducted in a large reverberation chamber which is a rich scattering
environment. Software-defined-radio has been used to create BLE communication
link for PER measurement in LOS and NLOS configuration. The BLE PER is measured
both in the presence and in absence of WLAN interference. Our measurement
results show a higher PER for uncoded BLE PHY modes in NLOS channel condition
and in presence of wideband interference. Whereas coded BLE PHY modes i.e.
LE500K and LE125K are robust to interference with lower PER measurements.


  We investigate whether it is feasible to remove gendered information from
resumes to mitigate potential bias in algorithmic resume screening. Using a
corpus of 709k resumes from IT firms, we first train a series of models to
classify the self-reported gender of the applicant, thereby measuring the
extent and nature of gendered information encoded in resumes. We then conduct a
series of gender obfuscation experiments, where we iteratively remove gendered
information from resumes. Finally, we train a resume screening algorithm and
investigate the trade-off between gender obfuscation and screening algorithm
performance. Results show: (1) There is a significant amount of gendered
information in resumes. (2) Lexicon-based gender obfuscation method (i.e.
removing tokens that are predictive of gender) can reduce the amount of
gendered information to a large extent. However, after a certain point, the
performance of the resume screening algorithm starts suffering. (3)
General-purpose gender debiasing methods for NLP models such as removing gender
subspace from embeddings are not effective in obfuscating gender.


  We introduce three simple randomized variants of byte pair encoding (BPE) and
explore whether randomizing the selection of merge operations substantially
affects a downstream machine translation task. We focus on translation into
morphologically rich languages, hypothesizing that this task may show
sensitivity to the method of choosing subwords. Analysis using a Bayesian
linear model indicates that two of the variants perform nearly
indistinguishably compared to standard BPE while the other degrades performance
less than we anticipated. We conclude that although standard BPE is widely
used, there exists an interesting universe of potential variations on it worth
investigating. Our code is available at: https://github.com/bltlab/random-bpe.


  A general form of $N$-dark soliton solutions of the multi-component Mel'nikov
system is presented. Taking the coupled Mel'nikov system comprised of
two-component short waves and one-component long wave as an example, its
general $N$-dark-dark soliton solutions in Gram determinant form are
constructed through the KP hierarchy reduction method. The dynamics of single
dark-dark soliton and two dark-dark solitons are discussed in detail. It can be
shown that the collisions of dark-dark solitons are elastic and energies of the
solitons in different components completely transmit through. In addition, the
dark-dark soliton bound states including both stationary and moving cases are
also investigated. An interesting feature for the coupled Mel'nikov system is
that the stationary dark-dark soliton bound states can exist for all possible
combinations of nonlinearity coefficients including all-positive, all-negative
and mixed types, while the moving case are possible when they take opposite
signs or they are both negative. The dynamics and several interesting
structures of the solutions are illustrated through some figures.


  Parametric autoregressive moving average models with exogenous terms (ARMAX)
have been widely used in the literature. Usually, these models consider a
conditional mean or median dynamics, which limits the analysis. In this paper,
we introduce a class of quantile ARMAX models based on log-symmetric
distributions. This class is indexed by quantile and dispersion parameters. It
not only accommodates the possibility to model bimodal and/or
light/heavy-tailed distributed data but also accommodates heteroscedasticity.
We estimate the model parameters by using the conditional maximum likelihood
method. Furthermore, we carry out an extensive Monte Carlo simulation study to
evaluate the performance of the proposed models and the estimation method in
retrieving the true parameter values. Finally, the proposed class of models and
the estimation method are applied to a dataset on the competition "M5
Forecasting - Accuracy" that corresponds to the daily sales history of several
Walmart products. The results indicate that the proposed log-symmetric quantile
ARMAX models have good performance in terms of model fitting and forecasting.


  We give "hybrid" proofs of the $q$-binomial theorem and other identities. The
proofs are "hybrid" in the sense that we use partition arguments to prove a
restricted version of the theorem, and then use analytic methods (in the form
of the Identity Theorem) to prove the full version. We prove three somewhat
unusual summation formulae, and use these to give hybrid proofs of a number of
identities due to Ramanujan. Finally, we use these new summation formulae to
give new partition interpretations of the Rogers-Ramanujan identities and the
Rogers-Selberg identities.


  Value functions derived from Markov decision processes arise as a central
component of algorithms as well as performance metrics in many statistics and
engineering applications of machine learning techniques. Computation of the
solution to the associated Bellman equations is challenging in most practical
cases of interest. A popular class of approximation techniques, known as
Temporal Difference (TD) learning algorithms, are an important sub-class of
general reinforcement learning methods. The algorithms introduced in this paper
are intended to resolve two well-known difficulties of TD-learning approaches:
Their slow convergence due to very high variance, and the fact that, for the
problem of computing the relative value function, consistent algorithms exist
only in special cases. First we show that the gradients of these value
functions admit a representation that lends itself to algorithm design. Based
on this result, a new class of differential TD-learning algorithms is
introduced. For Markovian models on Euclidean space with smooth dynamics, the
algorithms are shown to be consistent under general conditions. Numerical
results show dramatic variance reduction when compared to standard methods.


  We consider conformal perturbation theory for $n$-point functions on the
sphere in general 2D CFTs to first order in coupling constant. We regulate
perturbation integrals using canonical hard disk excisions of size $\epsilon$
around the fixed operator insertions, and identify the full set of counter
terms which are sufficient to regulate all such integrated $n$-point functions.
We further explore the integrated 4-point function which computes changes to
the structure constants of the theory. Using an $sl(2)$ map, the three fixed
locations of operators are mapped to $0$, $1$, and $\infty$. We show that
approximating the mapped excised regions to leading order in $\epsilon$ does
not lead to the same perturbative shift to the structure constant as the exact
in $\epsilon$ region. We explicitly compute the correction back to the exact in
$\epsilon$ region of integration in terms of the CFT data. We consider the
compact boson, and show that one must use the exact in $\epsilon$ region to
obtain agreement with the exact results for structure constants in this theory.


  Suppose we are given a submodular function $f$ over a set of elements, and we
want to maximize its value subject to certain constraints. Good approximation
algorithms are known for such problems under both monotone and non-monotone
submodular functions. We consider these problems in a stochastic setting, where
elements are not all active and we can only get value from active elements.
Each element $e$ is active independently with some known probability $p_e$, but
we don't know the element's status \emph{a priori}. We find it out only when we
\emph{probe} the element $e$---probing reveals whether it's active or not,
whereafter we can use this information to decide which other elements to probe.
Eventually, if we have a probed set $S$ and a subset $\text{active}(S)$ of
active elements in $S$, we can pick any $T \subseteq \text{active}(S)$ and get
value $f(T)$. Moreover, the sequence of elements we probe must satisfy a given
\emph{prefix-closed constraint}---e.g., these may be given by a matroid, or an
orienteering constraint, or deadline, or precedence constraint, or an arbitrary
downward-closed constraint---if we can probe some sequence of elements we can
probe any prefix of it. What is a good strategy to probe elements to maximize
the expected value?
  In this paper we study the gap between adaptive and non-adaptive strategies
for $f$ being a submodular or a fractionally subadditive (XOS) function. If
this gap is small, we can focus on finding good non-adaptive strategies
instead, which are easier to find as well as to represent. We show that the
adaptivity gap is a constant for monotone and non-monotone submodular
functions, and logarithmic for XOS functions of small \emph{width}. These
bounds are nearly tight. Our techniques show new ways of arguing about the
optimal adaptive decision tree for stochastic problems.


  The possibility of explaining the current value of the muon anomalous
magnetic moment in models with an additional U(1) gauge symmetry that has
kinetic mixing with hypercharge are increasingly constrained by dark photon
searches at electron accelerators. Here we present a scenario in which the
couplings of new, light gauge bosons to standard model leptons are naturally
weak and flavor non-universal. A vector-like state that mixes with standard
model leptons serves as a portal between the dark and standard model sectors.
The flavor symmetry of the model assures that the induced couplings of the new
gauge sector to leptons of the first generation are very small and
lepton-flavor-violating processes are adequately suppressed. The model provides
a framework for constructing ultraviolet complete theories in which new, light
gauge fields couple weakly and dominantly to leptons of the second or third
generations.


  We consider a wireless communication system with a passive eavesdropper, in
which a transmitter and legitimate receiver generate and use key bits to secure
the transmission of their data. These bits are added to and used from a pool of
available key bits. In this work, we analyze the reliability of the system in
terms of the probability that the budget of available key bits will be
exhausted. In addition, we investigate the latency before a transmission can
take place. Since security, reliability, and latency are three important
metrics for modern communication systems, it is of great interest to jointly
analyze them in relation to the system parameters. In particular, we show under
what conditions the system may remain in an active state indefinitely, i.e.,
never run out of available secret-key bits. The results presented in this work
will allow system designers to adjust the system parameters in such a way that
the requirements of the application in terms of both reliability and latency
are met.


  We obtain theoretical expressions for the photocurrent in the Heterojunction
solar cells with Intrinsic Thin layer (HIT cells). Our calculations take into
account tunneling of electrons and holes through wide-bandgap layers of
$\alpha$-Si:H or $\alpha$-SiC:H. We introduce the criteria, under which
tunneling does not lead to the deterioration of solar cell characteristics, in
particular, to the reduction of the short-circuit current and open-circuit
voltage. We propose an algorithm to compute the photoconversion efficiency of
HIT elements, taking into account the peculiarities of the open-circuit voltage
generation, in particular, its rather high values. We test our theoretical
predictions against the experimental results. For this, we fabricate HIT
elements with the efficiency of about $20\,\%$. We measured the temperature
dependence of the short-circuit current, open-circuit voltage, photoconversion
power, and fill factor of the current-voltage curve of these elements in a wide
temperature range from 80 to 420\,K. In the low-temperature range, the
open-circuit voltage and the photoconversion power decrease on cooling. At $T
\ge 200$\,K, the theoretical expressions and the experimental curves agree
rather well. The behavior of the fill factor and output power at low
temperatures is explained by the increase of the series resistance on cooling.
We discuss the reasons behind the reduction of the power temperature
coefficient in HIT elements. We show that they are related to the low value of
the combined surface and volume recombination rate. Finally, we derive a
theoretical expression for the HIT element's operation temperature under
natural working conditions.


  We study the translation surfaces obtained by considering the unfoldings of
the surfaces of Platonic solids. We show that they are all lattice surfaces and
we compute the topology of the associated Teichm\"uller curves. Using an
algorithm that can be used generally to compute Teichm\"uller curves of
translation covers of primitive lattice surfaces, we show that the
Teichm\"uller curve of the unfolded dodecahedron has genus 131 with 19 cone
singularities and 362 cusps. We provide both theoretical and rigorous
computer-assisted proofs that there are no closed saddle connections on the
surfaces associated to the tetrahedron, octahedron, cube, and icosahedron. We
show that there are exactly 31 equivalence classes of closed saddle connections
on the dodecahedron, where equivalence is defined up to affine automorphisms of
the translation cover. Techniques established here apply more generally to
Platonic surfaces and even more generally to translation covers of primitive
lattice surfaces and their Euclidean cone surface and billiard table quotients.


  The QED four-photon amplitude has been well-studied by many authors, and
on-shell is treated in many textbooks. However, a calculation with all four
photons off-shell is presently still lacking, despite of the fact that this
amplitude appears off-shell as a subprocess in many different contexts, in
vacuum as well as with some photons connecting to external fields. The present
paper is the first in a series of four where we use the worldline formalism to
obtain this amplitude explicitly in terms of hypergeometric functions, and
derivatives thereof, for both scalar and spinor QED. The formalism allows us to
unify the scalar and spinor loop calculations, to avoid the usual breaking up
of the amplitude into three inequivalent Feynman diagrams, and to achieve
manifest transversality as well as UV finiteness at the integrand level by an
optimized version of the integration-by-parts procedure originally introduced
by Bern and Kosower for gluon amplitudes. The full permutation symmetry is
maintained throughout, and the amplitudes get projected naturally into the
basis of five tensors introduced by Costantini et al. in 1971. Since in many
applications of the "four-photon box" some of the photons can be taken in the
low-energy limit, and the formalism makes it easy to integrate out any such
leg, apart from the case of general kinematics (part 4) we also treat the
special cases of one (part 3) or two (part 2) photons taken at low energy. In
this first part of the series, we summarize the application of the worldline
formalism to the N-photon amplitudes and its relation to Feynman diagrams,
derive the optimized tensor-decomposed integrands of the four-photon amplitudes
in scalar and spinor QED, and outline the computational strategy to be followed
in parts 2 to 4.


  The decay dynamical path is determined within the macroscopic-microscopic
model for the emission of 24Ne from 232U. The nuclear shape parametrization is
characterized five degrees of freedom. The single particle energies and the
nucleon wave functions are obtained within the superasymmetric Woods-Saxon two
center shell model. It turns out that the cluster decay follows a potential
magic valley, starting from the ground state of the parent and reaching a
configuration of two touching nuclei at scission. A small pocket in the
potential barrier is evidenced, as a result of large shell effects in the
nascent fragments. The half-life is computed by using several approaches for
the effective mass. It is shown that the inertia within by the gaussian overlap
approach gives the closest values to the experimental ones. Half-lives for
different cluster decays are predicted. The theoretical values are compared to
various phenomenological estimates.


  Let $L$ be a homogeneous divergence form higher order elliptic operator with
complex bounded measurable coefficients and $(p_-(L),\, p_+(L))$ be the maximal
interval of exponents $q\in[1,\,\infty]$ such that the semigroup
$\{e^{-tL}\}_{t>0}$ is bounded on $L^q(\mathbb{R}^n)$. In this article, the
authors establish the non-tangential maximal function characterizations of the
associated Hardy spaces $H_L^p(\mathbb{R}^n)$ for all $p\in(0,\,p_+(L))$,
which, when $p=1$, answers a question asked by Deng et al. in [J. Funct. Anal.
263 (2012), 604-674]. Moreover, the authors characterize $H_L^p(\mathbb{R}^n)$
via various versions of square functions and Lusin-area functions associated to
the operator $L$.


  We present an implementation of absorbing boundary conditions for the
Einstein equations based on the recent work of Buchman and Sarbach. In this
paper, we assume that spacetime may be linearized about Minkowski space close
to the outer boundary, which is taken to be a coordinate sphere. We reformulate
the boundary conditions as conditions on the gauge-invariant
Regge-Wheeler-Zerilli scalars. Higher-order radial derivatives are eliminated
by rewriting the boundary conditions as a system of ODEs for a set of auxiliary
variables intrinsic to the boundary. From these we construct boundary data for
a set of well-posed constraint-preserving boundary conditions for the Einstein
equations in a first-order generalized harmonic formulation. This construction
has direct applications to outer boundary conditions in simulations of isolated
systems (e.g., binary black holes) as well as to the problem of
Cauchy-perturbative matching. As a test problem for our numerical
implementation, we consider linearized multipolar gravitational waves in TT
gauge, with angular momentum numbers l=2 (Teukolsky waves), 3 and 4. We
demonstrate that the perfectly absorbing boundary condition B_L of order L=l
yields no spurious reflections to linear order in perturbation theory. This is
in contrast to the lower-order absorbing boundary conditions B_L with L<l,
which include the widely used freezing-Psi_0 boundary condition that imposes
the vanishing of the Newman-Penrose scalar Psi_0.


  We show that for a large class of evolutionary nonlinear and nonlocal partial
differential equations, symmetry of solutions implies very restrictive
properties of the solutions and symmetry axes. These restrictions are
formulated in terms of three principles, based on the structure of the
equations. The first principle covers equations that allow for steady solutions
and shows that any spatially symmetric solution is in fact steady with a speed
determined by the motion of the axis of symmetry at the initial time. The
second principle includes equations that admit breathers and steady waves, and
therefore is less strong: it holds that the axes of symmetry are constant in
time. The last principle is a mixed case, when the equation contains terms of
the kind from both earlier principles, and there may be different outcomes; for
a class of such equations one obtains that a spatially symmetric solution must
be constant in both time and space. We list and give examples of more than 30
well-known equations and systems in one and several dimensions satisfying these
principles; corresponding results for weak formulations of these equations may
be attained using the same techniques. Our investigation is a generalisation of
a local and one-dimensional version of the first principle from [E., Holden,
and Raynaud, 2009] to nonlocal equations, systems and higher dimensions, as
well as a study of the standing and mixed cases.


  To investigate the topological structure of Morse flows with a sink on the
2-sphere we use the planar tree as complete topological invariant of the flow.
We give a list of all planar tree with at least 7 edges. We use a list of
rooted planar trees.


  Motived by experimentally synthesized $\mathrm{MoSi_2N_4}$
(\textcolor[rgb]{0.00,0.00,1.00}{Science 369, 670-674 (2020})), the intrinsic
piezoelectricity in monolayer $\mathrm{XSi_2N_4}$ (X=Ti, Zr, Hf, Cr, Mo and W)
are studied by density functional theory (DFT). Among the six monolayers, the
$\mathrm{CrSi_2N_4}$ has the best piezoelectric strain coefficient $d_{11}$ of
1.24 pm/V, and the second is 1.15 pm/V for $\mathrm{MoSi_2N_4}$. Taking
$\mathrm{MoSi_2N_4}$ as a example, strain engineering is applied to improve
$d_{11}$. It is found that tensile biaxial strain can enhance $d_{11}$ of
$\mathrm{MoSi_2N_4}$, and the $d_{11}$ at 4\% can improve by 107\% with respect
to unstrained one. By replacing the N by P or As in $\mathrm{MoSi_2N_4}$, the
$d_{11}$ can be raise substantially. For $\mathrm{MoSi_2P_4}$ and
$\mathrm{MoSi_2As_4}$, the $d_{11}$ is as high as 4.93 pm/V and 6.23 pm/V,
which is mainly due to smaller $C_{11}-C_{12}$ and very small minus or positive
ionic contribution to piezoelectric stress coefficient $e_{11}$ with respect to
$\mathrm{MoSi_2N_4}$. The discovery of this piezoelectricity in monolayer
$\mathrm{XSi_2N_4}$ enables active sensing, actuating and new electronic
components for nanoscale devices, and is recommended for experimental
exploration.


  Evolutionary models measure the probability of amino acid substitutions
occurring over different evolutionary distances. We examine various
evolutionary models based on empirically derived amino acid substitution
matrices. The models are constructed using the PAM and BLOSUM amino acid
substitution matrices. We rescale these matrices by raising them to powers to
model substitution patterns that account for different evolutionary distances.
We also examine models that account for the dissimilarity of substitution rates
along a protein sequence. We compare the models by computing the likelihood of
each model across different alignments. We also present a specific example to
illustrate the subtle differences in the estimation of evolutionary distance
computed using the different models.


  In our preceeding reports, we have pointed out that a unified description of
weak decays accompanying neutrinos and the oscillation process is obtained on
the basis of the expectation values of flavor-neutrino numbers with respect to
the neutrino-source hadron state. In the present report, we investigate the
effect on the expectation values due to the deviation from Fermi's golden
relation, and give concrete features of these deviations in the case of $\pi^+$
and $K^+$-decays under the simple situation with the $3$-momentum $\vec{p_A}=0$
for $A=\pi^+$, $K^+$. %numerical results under simple situations.


  Lipschitz constants for linear MPC are useful for certifying inherent
robustness against unmodeled disturbances or robustness for neural
network-based approximations of the control law. In both cases, knowing the
minimum Lipschitz constant leads to less conservative certifications. Computing
this minimum Lipschitz constant is trivial given the explicit MPC. However, the
computation of the explicit MPC may be intractable for complex systems. The
paper discusses a method for efficiently computing the minimum Lipschitz
constant without using the explicit control law. The proposed method simplifies
a recently presented mixed-integer linear program (MILP) that computes the
minimum Lipschitz constant. The simplification is obtained by exploiting
saturation and symmetries of the control law and irrelevant constraints of the
optimal control problem.


  Let $M$ be a complex manifold of dimension $n$ with smooth boundary $X$.
Given $q\in\{0,1,\ldots,n-1\}$, let $\Box^{(q)}$ be the $\ddbar$-Neumann
Laplacian for $(0,q)$ forms. We show that the spectral kernel of $\Box^{(q)}$
admits a full asymptotic expansion near the non-degenerate part of the boundary
$X$ and the Bergman projection admits an asymptotic expansion under some local
closed range condition. As applications, we establish Bergman kernel asymptotic
expansions for some domains with weakly pseudoconvex boundary and
$S^1$-equivariant Bergman kernel asymptotic expansions and embedding theorems
for domains with holomorphic $S^1$-action.


  Observations of luminous flares resulting from the possible tidal disruption
of stars by supermassive black holes have raised a number of puzzles.
Outstanding questions include the origin of the optical and ultraviolet (UV)
flux, the weakness of hydrogen lines in the spectrum, and the occasional
simultaneous observation of x-rays. Here we study the emission from tidal
disruption events (TDEs) produced as radiation from black hole accretion
propagates through an extended, optically thick envelope formed from stellar
debris. We analytically describe key physics controlling spectrum formation,
and present detailed radiative transfer calculations that model the spectral
energy distribution (SED) and optical line strengths of TDEs near peak
brightness. The steady-state transfer is coupled to a non local thermodynamic
equilibrium treatment of the excitation and ionization states of hydrogen,
helium and oxygen (as a representative metal). Our calculations show how an
extended envelope can reprocess a fraction of soft x-rays and produce the
observed optical fluxes of order 10^43 ergs per second. Variations in the mass
or size of the envelope may help explain how the optical flux changes over time
with roughly constant color. For high enough accretion luminosities, x-rays can
highly ionize the reprocessing region and escape to be observed simultaneously
with the optical flux, producing an SED not described by a single blackbody.
Due to optical depth effects, hydrogen Balmer line emission is often strongly
suppressed relative to helium line emission (with HeII-to-H line ratios of at
least 5:1 in some cases) even in the disruption of a solar-composition star. We
discuss the implications of our results to understanding the type of stars
destroyed in TDEs and the physical processes responsible for producing the
observed flares.


  Transitions between multiple stable states of nonlinear systems are
ubiquitous in physics, chemistry, and beyond. Two types of behaviors are
usually seen as mutually exclusive: unpredictable noise-induced transitions and
predictable bifurcations of the underlying vector field. Here, we report a new
situation, corresponding to a fluctuating system approaching a bifurcation,
where both effects collaborate. We show that the problem can be reduced to a
single control parameter governing the competition between deterministic and
stochastic effects. Two asymptotic regimes are identified: when the control
parameter is small (e.g. small noise), deviations from the deterministic case
are well described by the Freidlin-Wentzell theory. In particular, escapes over
the potential barrier are very rare events. When the parameter is large (e.g.
large noise), such events become typical. Unlike pure noise-induced
transitions, the distribution of the escape time is peaked around a value which
is asymptotically predicted by an adiabatic approximation. We show that the two
regimes are characterized by qualitatively different reacting trajectories,
with algebraic and exponential divergence, respectively.


  The survival probabilities of a ``prisoner'' diffusing in an expanding cage
and a ``daredevil'' diffusing at the edge of a receding cliff are investigated.
When the diffuser reaches the boundary, he dies. For ``marginal'' boundary
motion, i.e., the cage length grows as $\sqrt{At}$ or the cliff location
recedes as $x_0(t)=-\sqrt{At}$ and the daredevil diffuses within the domain
$x>x_0$, the survival probability of the diffuser exhibits non-universal
power-law behavior, $S(t)\sim t^{-\b}$, which depends on the relative rates of
boundary and diffuser motion. Heuristic approaches are applied for the cases of
``slow'' and ``fast'' boundary motion which yield approximate expressions for
$\b$. An asymptotically exact analysis of these two problems is also performed
and the approximate expressions for $\b$ coincide with the exact results for
nearly entire range of possible boundary motions.


  In this paper following the same methods in [M. Kadakal, O. Sh. Mukhtarov,
Sturm-Liouville problems with discontinuities at two points, Comput. Math.
Appl., 54 (2007) 1367-1379] we investigate discontinuous two-point boundary
value problems with eigenparameter in the boundary conditions and with
transmission conditions at the finitely many points of discontinuity. A
self-adjoint linear operator A is defined in a suitable Hilbert space H such
that the eigenvalues of such a problem coincide with those of A. We obtain
asymptotic formulas for the eigenvalues and eigenfunctions. Also we show that
the eigenfunctions of A are complete in H.


  We consider a recently introduced class of network construction problems
where edges of a transportation network need to be constructed by a server
(construction crew). The server has a constant construction speed which is much
lower than its travel speed, so relocation times are negligible with respect to
construction times. It is required to find a construction schedule that
minimizes a non-decreasing function of the times when various connections of
interest become operational. Most problems of this class are strongly NP-hard
on general networks, but are often tree-efficient, that is, polynomially
solvable on trees. We develop a generic local search heuristic approach and two
metaheuristics (Iterated Local Search and Tabu Search) for solving
tree-efficient network construction problems on general networks, and explore
them computationally. Results of computational experiments indicate that the
methods have excellent performance.


  Let $L_t:=\Delta_t+Z_t$ for a $C^{1,1}$-vector field $Z$ on a differential
manifold $M$ with possible boundary $\partial M$, where $\Delta_t$ is the
Laplacian induced by a time dependent metric $g_t$ differentiable in $t\in
[0,T_c)$. We first introduce the damp gradient operator, defined on the path
space with reference measure $\mathbb{P}$, the law of the (reflecting)
diffusion process generated by $L_t$ on the base manifold; then establish the
integration by parts formula for underlying directional derivatives and prove
the log-Sobolev inequality for the associated Dirichlet form, which is further
applied to the free path spaces; and finally, establish numbers of
transportation-cost inequalities associated to the uniform distance, which are
equivalent to the curvature lower bound and the convexity of the boundary.


  Detection system and software package coded in Builder C ++ are developed for
the new analog spectrometer of the DGFRS-2 setup installed on the new DC-280
cyclotron. This software allows providing data acquisition using a 48x128 DSSSD
(Double Side Silicon Strip Detector) detector and a multi-wire gaseous
detector. The main feature of this software package is the use of flexible
real-time algorithms to provide deep suppression of the background in reactions
for the synthesis of superheavy elements, using the detection of correlations
ER-{\alpha} (Recoil-alpha particle). The block-diagram of analog spectrometer
is presented.


  We consider deep-inelastic lepton scattering, Drell-Yan lepton pair and heavy
quark production in the reference frame of the target. These reactions
traditionally treated as hard have, however, a substantial leading twist soft
contribution. One of the manifestations of such a soft component, nuclear
shadowing, is overviewed.


  We studied the exchange coupling and decoupling occurring in a nanocomposite
spin system based on a 3D Heisenberg model by means of Monte Carlo numerical
computation simulation. Different from conventional micromagnetism approach
which usually adopts finite elements method to compute, in a top-down way, the
magnetic property of micromagnetic ensemble in micron even nanometer scale, our
approach in this paper is peculiar to the structure of a complex spin lattice,
i.e. two species of spins building up from single spin to cluster spins in a
bottom-up way. The simulation revealed the influence of exchange coupling
constant Jab, the size of cluster spins d and system reduced temperature t upon
the exchange coupling and decoupling between component spin phases of a
nanocomposite magnets, respectively. Smaller value of Jab, larger d and lower
temperature t usually lead to the decoupling of originally exchange-coupled
component phases and the occurrence of a characteristic two-stage shoulder with
an inflexion on the demagnetization curve. The results reported in this paper
are of, to some extent, universality and applicable to other dual-phase
magnetic systems since our simulation simply focus on a pure duplex spin system
rather than a specific material and all physical variables were treated in a
reduced form.


  In terms of a simple holographic model, we study the absorption cross section
and the shear viscosity of a pure Yang-Mills field at low temperature where the
system is in the confinement phase. Then we expect that the glueball states are
the dominant modes in this phase. In our holographic model an infrared cutoff
r_m is introduced as a parameter which fixes the lowest mass of the glueball.
As a result the critical temperature of gluon confinement T_c is estimated to
be about 127 MeV. For T < T_c, we find that both the absorption cross section
and the shear viscosity are independent of the temperature. Their values are
frozen at the values corresponding to the critical point, for 0 < T < T_c. We
discuss this behavior by considering the glueball mass and its temperature
dependence.


  The recently reported observation of VFTS 243 is the first example of a
massive black-hole binary system with negligible binary interaction following
black-hole formation. The black-hole mass ($\approx 10\ M_{\odot}$) and
near-circular orbit ($e\approx 0.02$) of VFTS 243 suggest that the progenitor
star experienced complete collapse, with energy-momentum being lost
predominantly through neutrinos. VFTS 243 enables us to constrain the natal
kick and neutrino-emission asymmetry during black-hole formation. At 68% C.L.,
the natal kick velocity (mass decrement) is $\lesssim 10$ km/s ($\lesssim 1.0\
M_{\odot}$), with a full probability distribution that peaks when $\approx 0.3\
M_{\odot}$ were ejected, presumably in neutrinos, and the black hole
experienced a natal kick of $4$ km/s. The neutrino-emission asymmetry is
$\lesssim 4$%, with best fit values of $\sim$0-0.2%. Such a small neutrino
natal kick accompanying black-hole formation is in agreement with theoretical
predictions.


  A coding scheme based on irregular low-density parity-check (LDPC) codes is
proposed to send secret messages from a source over the Gaussian wiretap
channel to a destination in the presence of a wiretapper, with the restriction
that the source can send only binary phase-shift keyed (BPSK) symbols. The
secrecy performance of the proposed coding scheme is measured by the secret
message rate through the wiretap channel as well as the equivocation rate about
the message at the wiretapper. A code search procedure is suggested to obtain
irregular LDPC codes that achieve good secrecy performance in such context.


  We give a general treatment of deformation theory from the point of view of
homotopical algebra following Hinich, Manetti and Pridham. In particular, we
show that any deformation functor in characteristic zero is controlled by a
certain differential graded Lie algebra defined up to homotopy, and also
formulate a noncommutative analogue of this result valid in any characteristic.


  We study a model of fluent material universe from a modified Newtonian
cosmology proposed by D'Inverno and Tawfik. From this perspective, it shows a
list of space-time curvature k with energy E, density \rho, specific heat
$C_{p}$ and the fluid temperature gradient considered $\Delta T$ corresponding
to standard thermodynamic variables. We determined the coupling constants
accompanying the matter density for different values we can take k


  Real-world multi-layer networks feature nontrivial dependencies among links
of different layers. Here we argue that, if links are directed, dependencies
are twofold. Besides the ordinary tendency of links of different layers to
align as the result of `multiplexity', there is also a tendency to anti-align
as the result of what we call `multireciprocity', i.e. the fact that links in
one layer can be reciprocated by \emph{opposite} links in a different layer.
Multireciprocity generalizes the scalar definition of single-layer reciprocity
to that of a square matrix involving all pairs of layers. We introduce
multiplexity and multireciprocity matrices for both binary and weighted
multiplexes and validate their statistical significance against maximum-entropy
null models that filter out the effects of node heterogeneity. We then perform
a detailed empirical analysis of the World Trade Multiplex (WTM), representing
the import-export relationships between world countries in different
commodities. We show that the WTM exhibits strong multiplexity and
multireciprocity, an effect which is however largely encoded into the degree or
strength sequences of individual layers. The residual effects are still
significant and allow to classify pairs of commodities according to their
tendency to be traded together in the same direction and/or in opposite ones.
We also find that the multireciprocity of the WTM is significantly lower than
the usual reciprocity measured on the aggregate network. Moreover, layers with
low (high) internal reciprocity are embedded within sets of layers with
comparably low (high) mutual multireciprocity. This suggests that, in the WTM,
reciprocity is inherent to groups of related commodities rather than to
individual commodities. We discuss the implications for international trade
research focusing on product taxonomies, the product space, and
fitness/complexity metrics.


  We present an MPI + OpenACC implementation of the kernel-independent
barycentric Lagrange treecode (BLTC) for fast summation of particle
interactions on GPUs. The distributed memory parallelization uses recursive
coordinate bisection for domain decomposition and MPI remote memory access to
build locally essential trees on each rank. The particle interactions are
organized into target batch/source cluster interactions which efficiently map
onto the GPU; target batching provides an outer level of parallelism, while the
direct sum form of the barycentric particle-cluster approximation provides an
inner level of parallelism. The GPU-accelerated BLTC performance is
demonstrated on several test cases up to 1~billion particles interacting via
the Coulomb potential and Yukawa potential.


  Given a real cubic form f(x,y,z), there is a pseudo-Riemannian metric given
by its Hessian matrix, defined on the open subset of R^3 where the Hessian
determinant h is non-zero. We determine the full curvature tensor of this
metric in terms of h and the S-invariant of f, obtaining in the process various
different characterizations of S. Motivated by the case of intersection forms
associated with complete intersection threefolds in the product of three
projective spaces, we then study ternary cubic forms which arise as follows: we
choose positive integers d1, d2, d3, set r = d1 + d2 + d3 - 3, and consider the
coefficient F(x,y,z) of H1^d1 H2^d2 H3^d3 in the product (x H1 + y H2 + z H3)^3
(a_1 H1 + b_1 H2 + c_1 H3) ... (a_r H1 + b_r H2 + c_r H3), the a_j, b_j and c_j
denoting non-negative real numbers; we assume also that F is non-degenerate.
Previous work of the author on sectional curvatures of Kahler moduli suggests a
number of combinatorial conjectures concerning the invariants of F. It is
proved here for instance that the Hessian determinant, considered as a
polynomial in x,y,z and the a_j, b_j, c_j, has only positive coefficients. The
same property is also conjectured to hold for the S-invariant; the evidence and
background to this conjecture is explained in detail in the paper.


  Janus particles with the ability to move phoretically in self-generated
chemical concentration gradients are model systems for active matter. Their
motion typically consists of straight paths with rotational diffusion being the
dominant reorientation mechanism. In this paper, we show theoretically that by
a suitable surface coverage of both activity and mobility, translational and
rotational motion can be induced arbitrarily in three dimensions. The resulting
trajectories are in general helical, and their pitch and radius can be
controlled by adjusting the angle between the translational and angular
velocity. Building on the classical mathematical framework for axisymmetric
self-phoretic motion under fixed-flux chemical boundary condition, we first
show how to calculate the most general three-dimensional motion for an
arbitrary surface coverage of a spherical particle. After illustrating our
results on surface distributions, we next introduce a simple intuitive patch
model to serve as a guide for designing arbitrary phoretic spheres.


  We evaluate dominant two-loop corrections to the triple Higgs coupling and
strength of a first-order electroweak phase transition in the inert Higgs
doublet model. It is found that sunset diagrams can predominantly enhance the
former and reduce the latter. As a result, the triple Higgs coupling normalized
by the standard model value at two-loop level is more enhanced than the
corresponding one-loop value.


  We present a method to resolve combinatorial issues in multi-particle final
states at hadron colliders. The use of kinematic variables such as MT2 and
invariant mass significantly reduces combinatorial ambiguities in the signal,
but at a cost of losing statistics. We illustrate this idea with gluino pair
production leading to 4 jets $+\met$ in the final state as well as $t\bar{t}$
production in the dilepton channel. Compared to results in recent studies, our
method provides greater efficiency with similar purity


  A generalization of the Onsager-Machlup theory from equilibrium to
nonequilibrium steady states and its connection with recent fluctuation
theorems are discussed for a dragged particle restricted by a harmonic
potential in a heat reservoir. Using a functional integral approach, the
probability functional for a path is expressed in terms of a Lagrangian
function from which an entropy production rate and dissipation functions are
introduced, and nonequilibrium thermodynamic relations like the energy
conservation law and the second law of thermodynamics are derived. Using this
Lagrangian function we establish two nonequilibrium detailed balance relations,
which not only lead to a fluctuation theorem for work but also to one related
to energy loss by friction. In addition, we carried out the functional
integrals for heat explicitly, leading to the extended fluctuation theorem for
heat. We also present a simple argument for this extended fluctuation theorem
in the long time limit.


  In this article, we analyse a stabilised equal-order finite element
approximation for the Stokes equations on anisotropic meshes. In particular, we
allow arbitrary anisotropies in a sub-domain, for example along the boundary of
the domain, with the only condition that a maximum angle is fulfilled in each
element.This discretisation is motivated by applications on moving domains as
arising e.g. in fluid-structure interaction or multiphase-flow problems. To
deal with the anisotropies, we define a modification of the original Continuous
Interior Penalty stabilisation approach. We show analytically the discrete
stability of the method and convergence of order ${\cal O}(h^{3/2})$ in the
energy norm and ${\cal O}(h^{5/2})$ in the $L^2$-norm of the velocities. We
present numerical examples for a linear Stokes problem and for a non-linear
fluid-structure interaction problem, that substantiate the analytical results
and show the capabilities of the approach.


  Serious Games (SGs) have experienced a tremendous outburst these last years.
Video game companies have been producing fun, user-friendly SGs, but their
educational value has yet to be proven. Meanwhile, cognition research scientist
have been developing SGs in such a way as to guarantee an educational gain, but
the fun and attractive characteristics featured often would not meet the
public's expectations. The ideal SG must combine these two aspects while still
being economically viable. In this article, we propose a production chain model
to efficiently conceive and produce SGs that are certified for their
educational gain and fun qualities. Each step of this chain will be described
along with the human actors, the tools and the documents that intervene.


  We present a scheme to generate steady-state atomic spin squeezing in a
cavity QED system using cavity-mediated Raman transitions to engineer effective
atom-photon interactions, which include both linear and nonlinear (dispersive)
atom-cavity couplings, on a potentially equal footing. We focus on a regime
where the dispersive coupling is very large and find that the steady state of
the system can in fact be a strongly spin-squeezed Dicke state,
$|N/2,0\rangle$, of the atomic ensemble. These states offer Heisenberg-limited
metrological properties and feature genuine multipartite entanglement among the
entire atomic ensemble.


  We construct a new algorithm for estimating the star formation rate (SFR) of
galaxies from their infrared (IR) luminosity by developing the theory of the IR
emission from a dusty H II region.
  The derived formula is ${\rm SFR}/(\MO {\rm yr^{-1}})=\{3.3\times
10^{-10}(1-\eta)/
  (0.4-0.2f+0.6 \epsilon)\}(L{\rm ^{obs}_{IR}}/\LO)$, where $f$ is the fraction
of ionizing photons absorbed by hydrogen,
  $\epsilon$ is the efficiency of dust absorption for nonionizing photons from
OB stars, and $\eta$ is the cirrus fraction of observed IR luminosity.
  The previous conversion formulae of SFR from the IR luminosity is applicable
to only the case where the observed IR luminosity is nearly equal to the
bolometric luminosity (starburst galaxies etc.), except for some empirical
formulae.
  On the other hand, our theoretical SFR is applicable to galaxies even with a
moderate star formation activity.
  That is, our simple and convenient formula is significantly useful for
estimating the SFR of various morphologies and types of galaxies --- from early
elliptical to late spiral and irregular galaxies, or from active starburst to
quiescent galaxies --- as far as they have neither an abnormal dust-to-gas
ratio nor an evident active galactic nucleus.


  Vision-language foundation models like CLIP have revolutionized the field of
artificial intelligence. Nevertheless, VLM models supporting multi-language,
e.g., in both Chinese and English, have lagged due to the relative scarcity of
large-scale pretraining datasets. Toward this end, we introduce a comprehensive
bilingual (Chinese-English) dataset BM-6B with over 6 billion image-text pairs,
aimed at enhancing multimodal foundation models to well understand images in
both languages. To handle such a scale of dataset, we propose a novel grouped
aggregation approach for image-text contrastive loss computation, which reduces
the communication overhead and GPU memory demands significantly, facilitating a
60% increase in training speed. We pretrain a series of bilingual image-text
foundation models with an enhanced fine-grained understanding ability on BM-6B,
the resulting models, dubbed as $M^2$-Encoders (pronounced "M-Square"), set new
benchmarks in both languages for multimodal retrieval and classification tasks.
Notably, Our largest $M^2$-Encoder-10B model has achieved top-1 accuracies of
88.5% on ImageNet and 80.7% on ImageNet-CN under a zero-shot classification
setting, surpassing previously reported SoTA methods by 2.2% and 21.1%,
respectively. The $M^2$-Encoder series represents one of the most comprehensive
bilingual image-text foundation models to date, so we are making it available
to the research community for further exploration and development.


  We prove an $\epsilon$-regularity theorem for vector-valued p-harmonic maps,
which are critical with respect to a partially free boundary condition, namely
that they map the boundary into a round sphere.
  This does not seem to follow from the reflection method that Scheven used for
harmonic maps with free boundary (i.e., the case $p=2$): the reflected equation
can be interpreted as a $p$-harmonic map equation into a manifold, but the
regularity theory for such equations is only known for round targets.
  Instead, we follow the spirit of the last-named author's recent work on free
boundary harmonic maps and choose a good frame directly at the free boundary.
This leads to growth estimates, which, in the critical regime $p=n$, imply
H\"older regularity of solutions. In the supercritical regime, $p < n$, we
combine the growth estimate with the geometric reflection argument: the
reflected equation is super-critical, but, under the assumption of growth
estimates, solutions are regular.
  In the case $p<n$, for stationary $p$-harmonic maps with free boundary, as a
consequence of a monotonicity formula we obtain partial regularity up to the
boundary away from a set of $(n-p)$-dimensional Hausdorff measure.