  Gray (2015) argued that the Fermi paradox (FP) is a misnomer, and it is not a
valid paradox. Gray also speculated that the argument was misattributed to
Fermi, whose lunchtime remarks did not pertain to the existence of
extraterrestrial intelligence, but to the feasibility of interstellar travel.
Instead, the paradox is ascribed to Hart and Tipler, and it is further
suggested that the paradox is not a real problem or research subject and should
not be used in debates about SETI projects. The arguments given are
unpersuasive, ahistorical, and, in at least one instance, clearly hinge on
literalistic and uncharitable reading of evidence. Instead, I argue the
following three points: (i) Contrary to Gray's assertion, the historical issue
of naming of ideas or concepts is completely divorced from their epistemic
status. (ii) FP is easily and smoothly generalized into the Great Silence
paradox, so it makes no sense either theoretically or empirically to separate
the two. (iii) In sharp contrast to the main implication of Gray's paper, FP
has become more aggravated lately due to advances in astrobiology.


  Charge order has recently been identified as a leading competitor of
high-temperature superconductivity in moderately doped cuprates. We provide a
survey of universal and materials-specific aspects of this phenomenon, with
emphasis on results obtained by scattering methods. In particular, we discuss
the structure, periodicity, and stability range of the charge-ordered state,
its response to various external perturbations, the influence of disorder, the
coexistence and competition with superconductivity, as well as collective
charge dynamics. In the context of this journal issue which honors Roger
Cowley's legacy, we also discuss the connection of charge ordering with lattice
vibrations and the central-peak phenomenon. We end the review with an outlook
on research opportunities offered by new synthesis methods and experimental
platforms, including cuprate thin films and superlattices.


  We show a relationship between the entropy production in stochastic
thermodynamics and the stochastic interaction in the information integrated
theory. To clarify this relationship, we newly introduce an information
geometric interpretation of the entropy production for a total system and the
partial entropy productions for subsystems. We show that the violation of the
additivity of the entropy productions is related to the stochastic interaction.
This framework is a thermodynamic foundation of the integrated information
theory. We also show that our information geometric formalism leads to a novel
expression of the entropy production related to an optimization problem
minimizing the Kullback-Leibler divergence. We analytically illustrate this
interpretation by using the spin model.


  This study explores the design and control of the behaviour of agents and
robots using simple circuits of spiking neurons and Spike Timing Dependent
Plasticity (STDP) as a mechanism of associative and unsupervised learning.
Based on a "reward and punishment" classical conditioning, it is demonstrated
that these robots learnt to identify and avoid obstacles as well as to identify
and look for rewarding stimuli. Using the simulation and programming
environment NetLogo, a software engine for the Integrate and Fire model was
developed, which allowed us to monitor in discrete time steps the dynamics of
each single neuron, synapse and spike in the proposed neural networks. These
spiking neural networks (SNN) served as simple brains for the experimental
robots. The Lego Mindstorms robot kit was used for the embodiment of the
simulated agents. In this paper the topological building blocks are presented
as well as the neural parameters required to reproduce the experiments. This
paper summarizes the resulting behaviour as well as the observed dynamics of
the neural circuits. The Internet-link to the NetLogo code is included in the
annex.


  Given a planar map of $n$ segments in which we wish to efficiently locate
points, we present the first randomized incremental construction of the
well-known trapezoidal-map search-structure that only requires expected $O(n
\log n)$ preprocessing time while deterministically guaranteeing worst-case
linear storage space and worst-case logarithmic query time. This settles a long
standing open problem; the best previously known construction time of such a
structure, which is based on a directed acyclic graph, so-called the history
DAG, and with the above worst-case space and query-time guarantees, was
expected $O(n \log^2 n)$. The result is based on a deeper understanding of the
structure of the history DAG, its depth in relation to the length of its
longest search path, as well as its correspondence to the trapezoidal search
tree. Our results immediately extend to planar maps induced by finite
collections of pairwise interior disjoint well-behaved curves.


  Large language models (LLMs) perform well at a myriad of tasks, but
explaining the processes behind this performance is a challenge. This paper
investigates whether LLMs can give faithful high-level explanations of their
own internal processes. To explore this, we introduce a dataset,
ArticulateRules, of few-shot text-based classification tasks generated by
simple rules. Each rule is associated with a simple natural-language
explanation. We test whether models that have learned to classify inputs
competently (both in- and out-of-distribution) are able to articulate freeform
natural language explanations that match their classification behavior. Our
dataset can be used for both in-context and finetuning evaluations. We evaluate
a range of LLMs, demonstrating that articulation accuracy varies considerably
between models, with a particularly sharp increase from GPT-3 to GPT-4. We then
investigate whether we can improve GPT-3's articulation accuracy through a
range of methods. GPT-3 completely fails to articulate 7/10 rules in our test,
even after additional finetuning on correct explanations. We release our
dataset, ArticulateRules, which can be used to test self-explanation for LLMs
trained either in-context or by finetuning.


  Recently a new class of models has emerged that addresses the naturalness
problem of a light Higgs boson. In these ''little Higgs'' models, the Standard
Model Higgs boson is a pseudo-Nambu-Goldstone boson of an approximate global
symmetry. The Higgs boson acquires mass radiatively only through ''collective
breaking'' of the global symmetry, so that more than one interaction is
required to give the Higgs a mass. This protects the Higgs mass from receiving
quadratically divergent radiative corrections at one-loop. These models contain
new vector bosons, fermions and scalars at the TeV scale that cancel the
quadratic divergences in the Higgs mass due to the Standard Model gauge, top
quark, and Higgs boson loops. In this talk I review the phenomenology of the
little Higgs models, focusing on collider signatures and electroweak precision
constraints.


  Context. The structural scaling relations (SSRs) of galaxies, i.e. the
observed correlations between effective radius, effective surface intensity and
velocity dispersion, are important tools for understanding how evolution
proceeds. Aims. In this paper we aim to demonstrate that the evolution of the
SSRs back in time is governed by the combination of the virial theorem (VT) and
the relation $L=L'_0 \sigma^{\beta(t)}$, where the parameters $\beta$ and
$L'_0$ vary with time and from galaxy to galaxy. Methods. Using the WINGS
database for the galaxies at redshift $z=0$ and the Illustris-1 and
Illustris-TNG databases of artificial galaxies, for the galaxies up to redshift
$z=4$, we analyse the SSRs back in time and, by means of simple algebraic
expressions for $L'_0$ and $\beta$ (functions of time and other physical
quantities), we derive the expected paths followed by galaxies in the various
SSRs toward the distributions observed at $z=0$. Results. The distribution of
galaxies in the SSRs is ultimately related to the evolution in luminosity and
velocity dispersion that are empirically mirrored by the $L=L'_0
\sigma^{\beta(t)}$ law. Furthermore, the $\beta$ parameter works as a
thermometer of the virialization of a galaxy. This parameter can assume either
positive or negative values, and its absolute value attains high values when
the galaxy is close to the virial condition, while it tends to zero when the
galaxy is far from it. Conclusions. As the SSRs change with time, the method we
are proposing allows us to decipher the temporal evolution of galaxies.


  Cruz et al. recently showed that the CMB cold spot can be explained by a
GUT-scale texture. But following Turok's argument that gauged configurations
always relax quickly, they posit a global symmetry, without obvious relation to
GUTs. An observation by Nambu invalidates Turok's argument when the broken
symmetry group has commuting generators. This is demonstrated explicitly in the
standard model of electroweak interactions and holds generally for intermediate
SSB stages in GUTs. The cold spot could therefore be due to a GUT texture, and
electroweak Higgs gradients may evolve indefinitely.


  We prove that impulsive systems, which possess an ISS Lyapunov function, are
ISS for impulse time sequences, which satisfy the fixed dwell-time condition.
If the ISS Lyapunov function is the exponential one, we provide stronger
result, which guarantees uniform ISS of the whole system over sequences of
impulse times, which satisfy the generalized average dwell-time condition.


  In this paper, we give the concepts of properly distributed and simply
distributed sequences, and prove that they are almost convergent. Basing on
these, we review the work of Feng and Li [Feng, B. Q. and Li, J. L., Some
estimations of Banach limits, J. Math. Anal. Appl. 323(2006) No. 1, 481-496.
MR2262220 46B45 (46A45).], which is shown to be a special case of our
generalized theory.


  The choice of the kernel is critical to the success of many learning
algorithms but it is typically left to the user. Instead, the training data can
be used to learn the kernel by selecting it out of a given family, such as that
of non-negative linear combinations of p base kernels, constrained by a trace
or L1 regularization. This paper studies the problem of learning kernels with
the same family of kernels but with an L2 regularization instead, and for
regression problems. We analyze the problem of learning kernels with ridge
regression. We derive the form of the solution of the optimization problem and
give an efficient iterative algorithm for computing that solution. We present a
novel theoretical analysis of the problem based on stability and give learning
bounds for orthogonal kernels that contain only an additive term O(pp/m) when
compared to the standard kernel ridge regression stability bound. We also
report the results of experiments indicating that L1 regularization can lead to
modest improvements for a small number of kernels, but to performance
degradations in larger-scale cases. In contrast, L2 regularization never
degrades performance and in fact achieves significant improvements with a large
number of kernels.


  We propose a mechanism for 1/f-type noise in hopping insulators based on the
multi-electron charge redistribution within the specific aggregates of the
localized states located in the vicinity of the critical resistors. We predict
that the noise with 1/f-type spectrum extends down to practically arbitrarily
low frequencies.


  Ad creative is one of the main mediums for e-commerce advertising. In our
approach we decouple this dynamic creative optimization into two stages, a
cascaded structure that can trade off between effectiveness and efficiency. In
the first stage, we train an automatic creative optimization architecture based
on autoco to simulate complex interactions between creative elements. Although
we obtained the ranking of different creatives under a sku, because we bucketed
and merged historical data according to periods, this confuses the ctr
diversity of the same ad creatives on different days and weakens the ability to
separate ambiguous samples. Therefore, we propose a transformer-based rerank
model. With the help of the rank model, we propose a distillation method to
learn the relative order of ideas and extract the ranking knowledge to guide
the rerank learning. The creative order soft labels under each sku are
generated by the rank model to alleviate the dilemma that a large number of
under-represented creatives cannot obtain real labels. Through the knowledge
diffusion of rerank, the ambiguous samples are associated with the positive and
negative samples. Cascade rerank and autoco to output the estimated value of
the synthetic ad image. In the second stage, we designed a bandit model, and
the bandit selected one of the output ad of the first stage for timely
delivery. Experimental results show that our method can outperform competing
baselines in terms of sctr. Online A/B testing shows that our method improves
ctr by 10% compared to the baseline.


  This work contributes to the limited literature on estimating the diffusivity
or drift coefficient of nonlinear SPDEs driven by additive noise. Assuming that
the solution is measured locally in space and over a finite time interval, we
show that the augmented maximum likelihood estimator introduced in Altmeyer,
Reiss (2020) retains its asymptotic properties when used for semilinear SPDEs
that satisfy some abstract, and verifiable, conditions. The proofs of
asymptotic results are based on splitting the solution in linear and nonlinear
parts and fine regularity properties in $L^p$-spaces. The obtained general
results are applied to particular classes of equations, including stochastic
reaction-diffusion equations. The stochastic Burgers equation, as an example
with first order nonlinearity, is an interesting borderline case of the general
results, and is treated by a Wiener chaos expansion. We conclude with numerical
examples that validate the theoretical results.


  We speculate on the development and availability of new innovative propulsion
techniques in the 2040s, that will allow us to fly a spacecraft outside the
Solar System (at 150 AU and more) in a reasonable amount of time, in order to
directly probe our (gravitational) Solar System neighborhood and answer
pressing questions regarding the dark sector (dark energy and dark matter). We
identify two closely related main science goals, as well as secondary
objectives that could be fulfilled by a mission dedicated to probing the local
dark sector: (i) begin the exploration of gravitation's low-acceleration regime
with a man-made spacecraft and (ii) improve our knowledge of the local dark
matter and baryon densities. Those questions can be answered by directly
measuring the gravitational potential with an atomic clock on-board a
spacecraft on an outbound Solar System orbit, and by comparing the spacecraft's
trajectory with that predicted by General Relativity through the combination of
ranging data and the in-situ measurement (and correction) of non-gravitational
accelerations with an on-board accelerometer. Despite a wealth of new
experiments getting online in the near future, that will bring new knowledge
about the dark sector, it is very unlikely that those science questions will be
closed in the next two decades. More importantly, it is likely that it will be
even more urgent than currently to answer them. Tracking a spacecraft carrying
a clock and an accelerometer as it leaves the Solar System may well be the
easiest and fastest way to directly probe our dark environment.


  In large-scale statistical learning, data collection and model fitting are
moving increasingly toward peripheral devices---phones, watches, fitness
trackers---away from centralized data collection. Concomitant with this rise in
decentralized data are increasing challenges of maintaining privacy while
allowing enough information to fit accurate, useful statistical models. This
motivates local notions of privacy---most significantly, local differential
privacy, which provides strong protections against sensitive data
disclosures---where data is obfuscated before a statistician or learner can
even observe it, providing strong protections to individuals' data. Yet local
privacy as traditionally employed may prove too stringent for practical use,
especially in modern high-dimensional statistical and machine learning
problems. Consequently, we revisit the types of disclosures and adversaries
against which we provide protections, considering adversaries with limited
prior information and ensuring that with high probability, ensuring they cannot
reconstruct an individual's data within useful tolerances. By reconceptualizing
these protections, we allow more useful data release---large privacy parameters
in local differential privacy---and we design new (minimax) optimal locally
differentially private mechanisms for statistical learning problems for
\emph{all} privacy levels. We thus present practicable approaches to
large-scale locally private model training that were previously impossible,
showing theoretically and empirically that we can fit large-scale image
classification and language models with little degradation in utility.


  We construct chiral N=1 gauge theories in 4D by compactifying the 6D
Blum-Intriligator (1,0) theories of 5-branes at $A_k$ singularities on $T^2$
with a nontrivial bundle of the global U(1) symmetry of these theories.


  We present a survey on exoplanetary systems of binary stars with stellar
separations less than 100 au. For a sample of 11 binaries that harbour detected
circumstellar giant planets we investigate the frequency of systems with
secular resonances (SR) affecting the habitable zone (HZ). Secular resonances
are connected to dynamically unstable or chaotic regions by enforcing highly
eccentric motion. We apply a semi-analytical method to determine the locations
of linear SR, which is based on finding the apsidal precession frequencies of
the massive bodies. For configurations where the giant planet is located
exterior to the HZ we find that there is always a SR interior to its orbit, the
exact location of the SR strongly depends on the system's architecture. In
systems with the giant planet interior to the HZ no SR can occur in the
Newtonian framework. Taking into account the general relativistic precession of
the perihelion, which increases the precession frequencies, planets with $a <
0.1$ au can cause SR in the HZ. We find two cases where the SR is located
inside the HZ, and some more where it is close to the HZ. Generally, giant
planets interior to the HZ are more favourable than exterior planets to avoid
SR in the HZ. Around the location of the SR weaker mean-motion resonances are
excited, and resonance overlap is possible. Existing analytical models are not
as accurate as the semi-analytical method in locating the SR and deviate by
$\sim 0.1$ au or more.


  We present results of a study of neutrino oscillation based on a 766 ton-year
exposure of KamLAND to reactor anti-neutrinos. We observe 258 \nuebar\
candidate events with energies above 3.4 MeV compared to 365.2 events expected
in the absence of neutrino oscillation. Accounting for 17.8 expected background
events, the statistical significance for reactor \nuebar disappearance is
99.998%. The observed energy spectrum disagrees with the expected spectral
shape in the absence of neutrino oscillation at 99.6% significance and prefers
the distortion expected from \nuebar oscillation effects. A two-neutrino
oscillation analysis of the KamLAND data gives \DeltaMSq =
7.9$^{+0.6}_{-0.5}\times10^{-5}$ eV$^2$. A global analysis of data from KamLAND
and solar neutrino experiments yields \DeltaMSq =
7.9$^{+0.6}_{-0.5}\times10^{-5}$ eV$^2$ and \ThetaParam =
0.40$^{+0.10}_{-0.07}$, the most precise determination to date.


  Within a confining quark matter model which considers phenomenologically the
quark confinement and asymptotic freedom as well as the chiral symmetry
restoration and quark deconfinement at high baryon density, we find that if the
up-down quark matter ($ud$QM) is more stable than nuclear matter and strange
quark matter (SQM), the maximum mass of static quark stars with $ud$QM is
$2.87M_{\odot}$ under agreement with both the constraints on star tidal
deformability from gravitational wave signal GW170817 and the mass-radius of
PSR J0030+0451 and PSR J0740+6620 measured by NICER. In contrast, the
conventional strange quark star with the SQM that is more stable than nuclear
matter while the nuclear matter is more stable than $ud$QM, has a maximum
static mass of only $1.87M_{\odot}$ and its radius significantly deviates from
NICER's constraint. Our results thus provide circumstantial evidence suggesting
the recently reported GW190814's secondary component with a mass of
$2.59^{+0.08}_{-0.09}M_\odot$ could be an up-down quark star.


  Let $X$ be a $(2+1)$-dimensional globally hyperbolic spacetime with a Cauchy
surface $\Sigma$ whose universal cover is homeomorphic to $\mathbb{R}^2$. We
provide empirical evidence suggesting that the Jones polynomial detects
causality in $X$. We introduce a new invariant of certain tangles related to
the Conway polynomial, and prove that the Conway polynomial does not detect the
connected sum of two Hopf links among relevant 3-component links, which
suggests that the Conway polynomial does not detect causality in the scenario
described.


  We present a data stream algorithm for estimating the size of the maximum
matching of a low arboricity graph. Recall that a graph has arboricity $\alpha$
if its edges can be partitioned into at most $\alpha$ forests and that a planar
graph has arboricity $\alpha=3$. Estimating the size of the maximum matching in
such graphs has been a focus of recent data stream research.
  A surprising result on this problem was recently proved by Cormode et al.
They designed an ingenious algorithm that returned a
$(22.5\alpha+6)(1+\epsilon)$ approximation using a single pass over the edges
of the graph (ordered arbitrarily) and $O(\epsilon^{-2}\alpha \cdot \log n
\cdot \log_{1+\epsilon} n)$ space. In this note, we improve the approximation
factor to $(\alpha+2)(1+\epsilon)$ via a tighter analysis and show that, with a
modification of their algorithm, the space required can be reduced to
$O(\epsilon^{-2} \log n)$.


  Measuring user satisfaction level is a challenging task, and a critical
component in developing large-scale conversational agent systems serving the
needs of real users. An widely used approach to tackle this is to collect human
annotation data and use them for evaluation or modeling. Human annotation based
approaches are easier to control, but hard to scale. A novel alternative
approach is to collect user's direct feedback via a feedback elicitation system
embedded to the conversational agent system, and use the collected user
feedback to train a machine-learned model for generalization. User feedback is
the best proxy for user satisfaction, but is not available for some ineligible
intents and certain situations. Thus, these two types of approaches are
complementary to each other. In this work, we tackle the user satisfaction
assessment problem with a hybrid approach that fuses explicit user feedback,
user satisfaction predictions inferred by two machine-learned models, one
trained on user feedback data and the other human annotation data. The hybrid
approach is based on a waterfall policy, and the experimental results with
Amazon Alexa's large-scale datasets show significant improvements in inferring
user satisfaction. A detailed hybrid architecture, an in-depth analysis on user
feedback data, and an algorithm that generates data sets to properly simulate
the live traffic are presented in this paper.


  Generic glass formers exhibit at least two characteristic changes in their
relaxation behavior, first to an Arrhenius-type relaxation at some
characteristic temperature, and then at a lower characteristic temperature to a
super-Arrhenius (fragile) behavior. We address these transitions by studying
the statistics of free energy barriers for different systems at different
temperatures and space dimensions. We present a clear evidence for changes in
the dynamical behavior at the transition to Arrhenius and then to a
super-Arrhenius behavior. A simple model is presented, based on the idea of
competition between single-particle and cooperative dynamics. We argue that
Arrhenius behavior can take place as long as there is enough free volume for
the completion of a simple $T_1$ relaxation process. Once free volume is absent
one needs a cooperative mechanism to `collect' enough free volume. We show that
this model captures all the qualitative behavior observed in simulations
throughout the considered temperature range.


  Scalar and vector interactions, with the scalar interaction coupled to a
composite spin-1/2 system so as to cause a shift of its mass, are shown to obey
a low-energy theorem which guarantees that the second order interaction due to
z-graphs is the same as for a point Dirac particle. Off-shell and contact
interactions appropriate to the composite system cancel and this is verified in
a model of a composite fermion. The result provides a justification for the use
of the Dirac equation as it has been in relativistic nuclear scattering and
mean field theories.


  We show how to switch on and off the ratchet potential of a collective
Brownian motor, depending only on the position of the particles, in order to
attain a current higher than or at least equal to that induced by any periodic
flashing. Maximization of instant velocity turns out to be the optimal protocol
for one particle but is nevertheless defeated by a periodic switching when a
sufficiently large ensemble of particles is considered. The protocol presented
in this article, although not the optimal one, yields approximately the same
current as the optimal protocol for one particle and as the optimal periodic
switching for an infinite number of them.


  We explore the prospects of determining the octant of $\theta_{23}$ with
atmospheric neutrinos at PINGU. We study in detail the impact of energy and
angle resolutions of the neutrino on the octant sensitivity. We show that the
systematic uncertainties on the atmospheric neutrino flux predictions,
especially the ones which affect the energy and zenith angle spectrum of the
neutrinos, make a rather drastic reduction of the sensitivity of PINGU. We also
study the prospects of measuring the octant of $\theta_{23}$ in the long
baseline experiments T2K and NOvA in conjunction with the reactor experiments.
We study this for two configurations of NOvA and T2K and make a comparative
analysis of them. From just 3 years of PINGU data, the octant could be
determined at more than $3\sigma$ C.L. for $sin^2\theta_{23}<0.419$ and
$sin^2\theta_{23}>0.586$ if we add the reactor data and if normal hierarchy is
true. On addition of the data from T2K and NOvA, the sensitivity improves so
that the octant could be determined at the $4\sigma$ C.L. for
$sin^2\theta_{23}<0.426$ and $sin^2\theta_{23}>0.586$ if normal hierarchy is
true. Even a $5\sigma$ significance for the right octant can be achieved if
$sin^2\theta_{23}<0.413$ for the true normal hierarchy. The sensitivity for the
true inverted hierarchy is lower and we expect a $3\sigma$ determination of
octant for $sin^2\theta_{23}<0.43$ and $>0.585$ from the combined data set for
this case.


  In some interesting work of James Lidsey, the dynamics of
Friedmann-Lema\^itre-Robertson-Walker (FLRW) cosmology with positive curvature
and a perfect fluid matter source is shown to be modeled in terms of a
time-dependent, harmonically trapped Bose-Einstein condensate. In the present
work, we extend this dynamic correspondence to both FLRW and Bianchi I
cosmologies in arbitrary dimension, especially when a cosmological constant is
present.


  Idealized convection-permitting simulations of radiative-convective
equilibrium (RCE) have become a popular tool for understanding the physical
processes leading to horizontal variability of tropical water vapor and
rainfall. However, the applicability of idealized simulations to nature is
still unclear given that important processes are typically neglected, such as
lateral vapor advection by extratropical intrusions, or interactive ocean
coupling. Here, we exploit spectral analysis to compactly summarize the
multi-scale processes supporting convective aggregation. By applying this
framework to high-resolution reanalysis data and satellite observations in
addition to idealized simulations, we compare convective-aggregation processes
across horizontal scales and data sets. The results affirm the validity of the
RCE simulations as an analogy to the real world. Column moist static energy
tendencies share similar signs and scale-selectivity in convection-permitting
models and observations: Radiation increases variance at wavelengths above
1,000km, while advection damps variance across wavelengths, and surface fluxes
mostly reduce variance between 1,000km and 10,000km.


  Globular clusters are stellar dynamical systems which evolve on stellar
evolutionary and both internal and external dynamical timescales. Quantitative
comparison of cluster properties with realistic evolutionary dynamical models
is becoming feasible, and will underpin the subject in the next few years. A
few examples of the types of analysis becoming possible are presented.


  We compare relativistic particle integrators commonly used in plasma physics
showing several test cases relevant for astrophysics. Three explicit particle
pushers are considered, namely the Boris, Vay, and Higuera-Cary schemes. We
also present a new relativistic fully implicit particle integrator that is
energy conserving. Furthermore, a method based on the relativistic guiding
center approximation is included. The algorithms are described such that they
can be readily implemented in magnetohydrodynamics codes or Particle-in-Cell
codes. Our comparison focuses on the strengths and key features of the particle
integrators. We test the conservation of invariants of motion, and the accuracy
of particle drift dynamics in highly relativistic, mildly relativistic, and
non-relativistic settings. The methods are compared in idealized test cases,
i.e., without considering feedback on the electrodynamic fields, collisions,
pair creation, or radiation. The test cases include uniform electric and
magnetic fields, $\mathbf{E}\times\mathbf{B}$-fields, force-free fields, and
setups relevant for high-energy astrophysics, e.g., a magnetic mirror, a
magnetic dipole, and a magnetic null. These tests have direct relevance for
particle acceleration in shocks and in magnetic reconnection.


  We extend the Fourier expansion of automorphic functions of Piateski-Shapiro
and Shalika in a way that the Euclidean algorithm appears nontrivially. Then,
we discuss a potential application in the Rankin-Selberg method.


  In many analyses in high energy physics, attempts are made to remove the
effects of detector smearing in data by techniques referred to as "unfolding"
histograms, thus obtaining estimates of the true values of histogram bin
contents. Such unfolded histograms are then compared to theoretical
predictions, either to judge the goodness of fit of a theory, or to compare the
abilities of two or more theories to describe the data. When doing this, even
informally, one is testing hypotheses. However, a more fundamentally sound way
to test hypotheses is to smear the theoretical predictions by simulating
detector response and then comparing to the data without unfolding; this is
also frequently done in high energy physics, particularly in searches for new
physics. One can thus ask: to what extent does hypothesis testing after
unfolding data materially reproduce the results obtained from testing by
smearing theoretical predictions? We argue that this "bottom-line-test" of
unfolding methods should be studied more commonly, in addition to common
practices of examining variance and bias of estimates of the true contents of
histogram bins. We illustrate bottom-line-tests in a simple toy problem with
two hypotheses.


  This work investigates the embeddings for representing dialog history in
spoken language understanding (SLU) systems. We focus on the scenario when the
semantic information is extracted directly from the speech signal by means of a
single end-to-end neural network model. We proposed to integrate dialogue
history into an end-to-end signal-to-concept SLU system. The dialog history is
represented in the form of dialog history embedding vectors (so-called
h-vectors) and is provided as an additional information to end-to-end SLU
models in order to improve the system performance. Three following types of
h-vectors are proposed and experimentally evaluated in this paper: (1)
supervised-all embeddings predicting bag-of-concepts expected in the answer of
the user from the last dialog system response; (2) supervised-freq embeddings
focusing on predicting only a selected set of semantic concept (corresponding
to the most frequent errors in our experiments); and (3) unsupervised
embeddings. Experiments on the MEDIA corpus for the semantic slot filling task
demonstrate that the proposed h-vectors improve the model performance.


  Talk given at the International Workshop ``Physical Variables in Gauge
Theories", Dubna 1999


  In the context of photoelectron spectroscopy, the $GW$ approach has developed
into the method of choice for computing excitation spectra of weakly correlated
bulk systems and their surfaces. To employ the established computational
schemes that have been developed for three-dimensional crystals,
two-dimensional systems are typically treated in the repeated-slab approach. In
this work we critically examine this approach and identify three important
aspects for which the treatment of long-range screening in two dimensions
differs from the bulk: (1) anisotropy of the macroscopic screening (2) $\mathbf
k$-point sampling parallel to the surface (3) periodic repetition and slab-slab
interaction. For prototypical semiconductor (silicon) and ionic (NaCl) thin
films we quantify the individual contributions of points (1) to (3) and develop
robust and efficient correction schemes derived from the classic theory of
dielectric screening.


  Recently, many numerical evidences of fractional Chern insulator, i.e. the
fractional quantum Hall states on lattices, are proposed when a Chern band is
partially filled. Some trial wavefunctions of fractional Chern insulators can
be obtained by mapping the fractional quantum Hall wavefunctions defined in the
continuum onto the lattice through the Wannier state representation (Phys. Rev.
Lett. 107, 126803 (2011)) in which the single particle Landau orbits in the
Landau levels are identified with the one dimensional Wannier states of the
Chern bands with Chern number C = 1. However, this mapping generically breaks
the lattice point group symmetry. In this paper, we discuss a general approach
of modifying the mapping to accommodate the lattice rotational symmetry. The
wavefunctions constructed through this modified mapping should serve as better
trial wavefunctions to compare with the numerics and also as the basis for
construction of lattice symmetry preserving pseudo-potential formalism for
fractional Chern insulators. The focus of this paper shall be mainly on the
$C_4$ rotational symmetry of square lattices. Similar analysis can be
straightforwardly generalized to triangular or hexagonal lattices with $C_6$
symmetry. We also generalize the discussion to the lattice symmetry of
fractional Chern insulators with high Chern number bands.


  We give an infinite family of embeddings of $\mathbb{R} P^2$ to $S^4$ such
that they are mutually topologically isotopic however are not smoothly isotopic
to each other. Moreover, they are topologically isotopic to the standard
$P^2$-knot.
  To prove that these $P^2$-knots are not smoothly isotopic to each other, we
construct a gauge theoretic invariant of embedded surfaces in $4$-manifolds
using a variant of the Seiberg--Witten theory, which is called the Real
Seiberg--Witten theory.


  We generalize the switching lemma of Griffiths, Hurst and Sherman to the
random current representation of the Ashkin-Teller model. We then use it
together with properties of two-dimensional topology to derive linear relations
for multi-point boundary spin correlations and bulk order-disorder correlations
in planar models. We also show that the same linear relations are satisfied by
products of Pfaffians. As a result a clear picture arises in the noninteracting
case of two independent Ising models where multi-point correlation functions
are given by Pfaffians and determinants of their respective two-point
functions. This gives a unified treatment of both the classical Pfaffian
identities and recent total positivity inequalities for boundary spin
correlations in the planar Ising model. We also derive the Simon and Gaussian
inequality for general Ashkin-Teller models with negative four-body coupling
constants.


  If the sneutrino mass is below the chargino mass, the dominant decay mode of
the lightest chargino is via a two-body decay channel $\chi^{\pm}_1 \ra
\tilde{\nu} + l^{\pm}$. Sneutrinos are invisible in $R$-parity conserving
supersymmetric models and, if the mass gap $m(\chi^{\pm}_1)-m(\tilde{\nu})$ is
sufficiently small, the soft decay lepton may escape detection leading to
invisible chargino decays. This ``blind spot'' of the supersymmetry parameter
space would jeopardize the chargino search at LEP2. We point out that such a
scenario can be tested by searching for single $W$ events in $e^+e^- \ra
W^+W^-$, with one $W$ boson decaying to visible leptons or quark jets, and the
second $W$ boson decaying to invisible charginos and neutralinos.


  We present a dynamical analysis of the globular cluster system associated
with M87 (= NGC 4486), the cD galaxy near the dynamical center of the Virgo
cluster. The analysis utilizes a new spectroscopic and photometric database
which is described in a companion paper (Hanes et al. 2001). Using a sample of
278 globular clusters with measured radial velocities and metallicities, and
new surface density profiles based on wide-field Washington photometry, we
study the dynamics of the M87 globular cluster system both globally --- for the
entire cluster sample --- and separately --- for the metal-rich and metal-poor
globular cluster samples. This constitutes the largest sample of radial
velocities for pure Population II tracers yet assembled for any galaxy. We
discuss the implications of our findings for models for the formation of giant
elliptical galaxies, globular cluster systems, and the Virgo cluster.
(ABRIDGED)


  We consider singular perturbation elliptic problems depending on a parameter
? such that, for ? = 0 the boundary conditions are not adapted to the equation
(they do not satisfy the Shapiro - Lopatinskii condition). The limit only holds
in very abstract spaces out of distribution theory involving complexi?cation
and non-local phenomena. We give a very elementary model problem showing the
main features of the limit process, as well as a heuristic integral procedure
for obtain- ing a description of the solutions for small ?. Such kind of
problems appear in thin shell theory when the middle surface is elliptic and
the shell is fixed by a part of the boundary and free by the rest.


  The rise in hateful and offensive language directed at other users is one of
the adverse side effects of the increased use of social networking platforms.
This could make it difficult for human moderators to review tagged comments
filtered by classification systems. To help address this issue, we present the
ViHOS (Vietnamese Hate and Offensive Spans) dataset, the first human-annotated
corpus containing 26k spans on 11k comments. We also provide definitions of
hateful and offensive spans in Vietnamese comments as well as detailed
annotation guidelines. Besides, we conduct experiments with various
state-of-the-art models. Specifically, XLM-R$_{Large}$ achieved the best
F1-scores in Single span detection and All spans detection, while
PhoBERT$_{Large}$ obtained the highest in Multiple spans detection. Finally,
our error analysis demonstrates the difficulties in detecting specific types of
spans in our data for future research.
  Disclaimer: This paper contains real comments that could be considered
profane, offensive, or abusive.


  Quantum information technologies harness the intrinsic nature of quantum
theory to beat the limitations of the classical methods for information
processing and communication. Recently, the application of quantum features to
metrology has attracted much attention. Quantum optical coherence tomography
(QOCT), which utilizes two-photon interference between entangled photon pairs,
is a promising approach to overcome the problem with optical coherence
tomography (OCT): As the resolution of OCT becomes higher, degradation of the
resolution due to dispersion within the medium becomes more critical. Here we
report on the realization of 0.54 $\mu$m resolution two-photon interference,
which surpasses the current record resolution 0.75 $\mu$m of low-coherence
interference for OCT. In addition, the resolution for QOCT showed almost no
change against the dispersion of a 1 mm thickness of water inserted in the
optical path, whereas the resolution for OCT dramatically degrades. For this
experiment, a highly-efficient chirped quasi-phase-matched lithium tantalate
device was developed using a novel $`$nano-electrode-poling$'$ technique. The
results presented here represent a breakthrough for the realization of quantum
protocols, including QOCT, quantum clock synchronization, and more. Our work
will open up possibilities for medical and biological applications.


  The recent work of Papyan, Han, & Donoho (2020) presented an intriguing
"Neural Collapse" phenomenon, showing a structural property of interpolating
classifiers in the late stage of training. This opened a rich area of
exploration studying this phenomenon. Our motivation is to study the upper
limits of this research program: How far will understanding Neural Collapse
take us in understanding deep learning? First, we investigate its role in
generalization. We refine the Neural Collapse conjecture into two separate
conjectures: collapse on the train set (an optimization property) and collapse
on the test distribution (a generalization property). We find that while Neural
Collapse often occurs on the train set, it does not occur on the test set. We
thus conclude that Neural Collapse is primarily an optimization phenomenon,
with as-yet-unclear connections to generalization. Second, we investigate the
role of Neural Collapse in feature learning. We show simple, realistic
experiments where training longer leads to worse last-layer features, as
measured by transfer-performance on a downstream task. This suggests that
neural collapse is not always desirable for representation learning, as
previously claimed. Finally, we give preliminary evidence of a "cascading
collapse" phenomenon, wherein some form of Neural Collapse occurs not only for
the last layer, but in earlier layers as well. We hope our work encourages the
community to continue the rich line of Neural Collapse research, while also
considering its inherent limitations.


  Widths of the rapidity distributions of various identified hadrons generated
with the UrQMD-3.4 event generator at all the Super Proton Synchrotron (SPS)
energies have been presented and compared with the existing experimental
results. An increase in the width of the rapidity distribution of $\Lambda$
could be seen with both Monte Carlo (MC) and experimental data for the studied
energies. Using MC data, the study has been extended to Relativistic Heavy Ion
Collider (RHIC) and Large Hadron Collider (LHC) energies. A similar jump, as
observed in the plot of rapidity width versus rest mass at Alternating Gradient
Synchrotron (AGS) and all SPS energies, persists even at RHIC and LHC energies,
confirming its universal nature from AGS to the highest LHC energies. Such
observation indicates that pair production may not be the only mechanism of
particle production at the highest LHC energies. However, with MC data, the
separate mass scaling for mesons and baryons is found to exist even at the top
LHC energy.


  Achieving high-performance GPU kernels requires optimizing algorithm
implementations to the targeted GPU architecture. It is of utmost importance to
fully use the compute and memory hierarchy, as well as available specialised
hardware. Currently, vendor libraries like cuBLAS and cuDNN provide the best
performing implementations of GPU algorithms. However the task of the library
programmer is incredibly challenging: for each provided algorithm,
high-performance implementations have to be developed for all commonly used
architectures, input sizes, and different storage formats. These
implementations are generally provided as optimized assembly code because
performance-critical architectural features are only exposed at this level.
This prevents reuse between different implementations of even the same
algorithm, as simple differences can have major effects on low-level
implementation details. In this paper we introduce Fireiron, a DSL and compiler
which allows the specification of high-performance GPU implementations as
compositions of simple and reusable building blocks. We show how to use
Fireiron to optimize matrix multiplication implementations, achieving
performance matching hand-coded CUDA kernels, even when using specialised
hardware such as NIVIDA Tensor Cores, and outperforming state-of-the-art
implementations provided by cuBLAS by more than 2x.


  Intersecting p-branes can be viewed as higher-dimensional interpretations of
multi-charge extremal p-branes, where some of the individual p-branes undergo
diagonal dimensional oxidation, while the others oxidise vertically. Although
the naive vertical oxidation of a single p-brane gives a continuum of p-branes,
a more natural description arises if one considers a periodic array of p-branes
in the higher dimension, implying a dependence on the compactification
coordinates. This still reduces to the single lower-dimensional p-brane when
viewed at distances large compared with the period. Applying the same logic to
the multi-charge solutions, we are led to consider more general classes of
intersecting p-brane solutions, again depending on the compactification
coordinates, which turn out to be described by interacting functions rather
than independent harmonic functions. These new solutions also provide a more
satisfactory interpretation for the lower-dimensional multi-charge p-branes,
which otherwise appear to be nothing more than the improbable coincidence of
charge-centres of individual constituents with zero binding energy.


  Efficient and accurate reconstruction of a relightable, dynamic clothed human
avatar from a monocular video is crucial for the entertainment industry. This
paper introduces the Surfel-based Gaussian Inverse Avatar (SGIA) method, which
introduces efficient training and rendering for relightable dynamic human
reconstruction. SGIA advances previous Gaussian Avatar methods by
comprehensively modeling Physically-Based Rendering (PBR) properties for
clothed human avatars, allowing for the manipulation of avatars into novel
poses under diverse lighting conditions. Specifically, our approach integrates
pre-integration and image-based lighting for fast light calculations that
surpass the performance of existing implicit-based techniques. To address
challenges related to material lighting disentanglement and accurate geometry
reconstruction, we propose an innovative occlusion approximation strategy and a
progressive training approach. Extensive experiments demonstrate that SGIA not
only achieves highly accurate physical properties but also significantly
enhances the realistic relighting of dynamic human avatars, providing a
substantial speed advantage. We exhibit more results in our project page:
https://GS-IA.github.io.


  Recently a vector charmonium-like state $Y(4626)$ was observed in the portal
of $D^+_sD_{s1}(2536)^-$. It intrigues an active discussion on the structure of
the resonance because it has obvious significance for gaining a better
understanding on its hadronic structure with suitable inner constituents. It
indeed concerns the general theoretical framework about possible structures of
exotic states. Since the mass of $Y(4626)$ is slightly above the production
threshold of $D^+_s\bar D_{s1}(2536)^-$ whereas below that of $D^*_s\bar
D_{s1}(2536)$ with the same quark contents as that of $D^+_s\bar
D_{s1}(2536)^-$, it is natural to conjecture $Y(4626)$ to be a molecular state
of $D^{*}_s\bar D_{s1}(2536)$, as suggested in literature. Confirming or
negating this allegation would shed light on the goal we concern. We calculate
the mass spectrum of a system composed of a vector meson and an axial vector
i.e. $D^*_s\bar D_{s1}(2536)$ within the framework of the Bethe-Salpeter
equations. Our numerical results show that the dimensionless parameter
$\lambda$ in the form factor which is phenomenologically introduced to every
vertex, is far beyond the reasonable range for inducing an even very small
binding energy $\Delta E$. It implies that the $D^*_s\bar D_{s1}(2536)$ system
cannot exist in the nature as a hadronic molecule in this model, so that we may
not think the resonance $Y(4626)$ to be a bound state of $D^*_s\bar
D_{s1}(2536)$, but something else, for example a tetraquark and etc.


  Vortices in superconductors can help identify emergent phenomena but certain
fundamental aspects of vortices, such as their entropy, remain poorly
understood. Here, we study the vortex entropy in underdoped
Bi$_2$Sr$_2$CaCu$_2$O$_{8+x}$ by measuring both magneto-resistivity and Nernst
effect on ultrathin flakes ($\le$2 unit-cell). We extract the London
penetration depth from the magneto-transport measurements on samples with
different doping levels. It reveals that the superfluid phase stiffness
$\rho_s$ scales linearly with the superconducting transition temperature $T_c$,
down to the extremely underdoped case. On the same batch of ultrathin flakes,
we measure the Nernst effect via on-chip thermometry. Together, we obtain the
vortex entropy and find that it decays exponentially with $T_c$ or $\rho_s$. We
further analyze the Nernst signal above $T_c$ in the framework of Gaussian
superconducting fluctuations. The combination of electrical and thermoelectric
measurements in the two-dimensional limit provides fresh insight into high
temperature superconductivity.


  In this work, we discuss two component fermionic FIMP dark matter (DM) in a
popular $B-L$ extension of the standard model (SM) with inverse seesaw
mechanism. Due to the introduced $\mathbb{Z}_{2}$ discrete symmetry, a keV SM
gauge singlet fermion is stable and can be a warm DM candidate. Also, this
$\mathbb{Z}_{2}$ symmetry helps the lightest right-handed neutrino, with mass
of order GeV, to be a long-lived or stable particle by choosing a corresponding
Yukawa coupling to be very small. Firstly, in the absence of a GeV DM component
(i.e., without tuning its corresponding Yukawa coupling), we consider only a
keV DM as a single component DM produced by the freeze-in mechanism. Secondly,
we study a two component FIMP DM scenario and emphasize that the correct
ballpark DM relic density bound can be achieved for a wide parameter space.


  The two-point statistics of the cosmic velocity field, measured from galaxy
peculiar velocity (PV) surveys, can be used as a dynamical probe to constrain
the growth rate of large-scale structures in the universe. Most works use the
statistics on scales down to a few tens of Megaparsecs, while using a
theoretical template based on the linear theory. In addition, while the cosmic
velocity is volume-weighted, the observable line-of-sight velocity two-point
correlation is density-weighted, as sampled by galaxies, and therefore the
density-velocity correlation term also contributes, which has often been
neglected. These effects are fourth order in powers of the linear density
fluctuation $\delta_{\rm L}^4$, compared to $\delta_{\rm L}^2$ of the linear
velocity correlation function, and have the opposite sign. We present these
terms up to $\delta_{\rm L}^4$ in real space based on the standard perturbation
theory, and investigate the effect of non-linearity and the density-velocity
contribution on the inferred growth rate $f\sigma_8$, using $N$-body
simulations. We find that for a next-generation PV survey of volume $\sim {\cal
O}(500 \, h^{-1} \, {\rm Mpc})^3$, these effects amount to a shift of
$f\sigma_8$ by $\sim 10$ per cent and is comparable to the forecasted
statistical error when the minimum scale used for parameter estimation is
$r_{\rm min} = 20 \, h^{-1} \, {\rm Mpc}$.


  We consider $p$-variations in some membrane potential data --viewed as a
function of the step size in case where $p$ is fixed, or viewed as a function
of $p$ in case where the step size is fixed-- and compare their shape with
results in Ait-Sahalia and Jacod (2009) which do hold for general
semimartingales. We obtain the following conclusion: in non- or very rarely
spiking cases the membrane potential behaves as a semimartingale, in some cases
as a semimartingale with jumps. Once the neuron is spiking, a semimartingale
modelization is no longer adequate for the membrane potential between
successive spikes, even if interspike intervals are relatively long.


  Autonomous vehicles (AV) require that neural networks used for perception be
robust to different viewpoints if they are to be deployed across many types of
vehicles without the repeated cost of data collection and labeling for each. AV
companies typically focus on collecting data from diverse scenarios and
locations, but not camera rig configurations, due to cost. As a result, only a
small number of rig variations exist across most fleets. In this paper, we
study how AV perception models are affected by changes in camera viewpoint and
propose a way to scale them across vehicle types without repeated data
collection and labeling. Using bird's eye view (BEV) segmentation as a
motivating task, we find through extensive experiments that existing perception
models are surprisingly sensitive to changes in camera viewpoint. When trained
with data from one camera rig, small changes to pitch, yaw, depth, or height of
the camera at inference time lead to large drops in performance. We introduce a
technique for novel view synthesis and use it to transform collected data to
the viewpoint of target rigs, allowing us to train BEV segmentation models for
diverse target rigs without any additional data collection or labeling cost. To
analyze the impact of viewpoint changes, we leverage synthetic data to mitigate
other gaps (content, ISP, etc). Our approach is then trained on real data and
evaluated on synthetic data, enabling evaluation on diverse target rigs. We
release all data for use in future work. Our method is able to recover an
average of 14.7% of the IoU that is otherwise lost when deploying to new rigs.


  We investigate how thin sheets of arbitrary shapes morph under the isotropic
in-plane expansion of their top surface, which may represent several stimuli
such as nonuniform heating, local swelling and differential growth. Inspired by
geometry, an analytical model is presented that rationalizes how the shape of
the disk influences morphing, from the initial spherical bending to the final
isometric limit. We introduce a new measure of slenderness $\gamma$ that
describes a sheet in terms of both thickness and plate shape. We find that the
mean curvature of the isometric state is three fourth's the natural curvature,
which we verify by numerics and experiments. We finally investigate the
emergence of a preferred direction of bending in the isometric state, guided by
numerical analyses. The scalability of our model suggests that it is suitable
to describe the morphing of sheets spanning several orders of magnitude.


  In pulsed laser deposition, along conventional deposition on frontside of
plasma-plume, target is getting coated on its surface too. For reproducibility,
cleaning those residues is the most adopted approach. Herein, we investigate
the target-side coated materials and employ them as a binder-free
supercapacitor electrode. Ballistic aggregated target-side nanofoam is compact
and contains higher sp2-carbon, higher nitrogen content with higher graphitic-N
and lower oxygen content with lower COOH group than that of diffusive
aggregated conventional nanofoams. They are highly hydrogenated graphite-like
amorphous carbon and superhydrophilic. The symmetric microsupercapacitor
delivers higher volumetric capacitance of 522 mF/cm3 at 100 mV/s and 104%
retention after 10000 charge-discharge cycles over conventional nanofoam (215
mF/cm3 and 85% retention) with the areal capacitance of 134 {\mu}F/cm2 at 120
Hz and ultrafast frequency response. Utilizing those residue materials is of
great importance towards sustainable development, zero-waste, and utilization
of deposition techniques in full-phase, which is resource-efficient, energy
competent and cost-effective.


  Let $X_1, X_2, \dots, X_n$ be independent uniform random variables on
$[0,1]^2$. Let $L(X_1, \dots, X_n)$ be the length of the shortest Traveling
Salesman tour through these points. It is known that there exists a constant
$\beta$ such that $$\lim_{n \to \infty} \frac{L(X_1, \dots, X_n)}{\sqrt{n}} =
\beta$$ almost surely (Beardwood 1959). The original analysis in (Beardwood
1959) showed that $\beta \geq 0.625$. Building upon an approach proposed in
(Steinerberger 2015), we improve the lower bound to $\beta \geq 0.6277$.


  In this paper, we investigate a class of information-flow security properties
called opacity in partial-observed discrete-event systems. Roughly speaking, a
system is said to be opaque if the intruder, which is modeled by a passive
observer, can never determine the "secret" of the system for sure. Most of the
existing notions of opacity consider secrets related to the actual behaviors of
the system. In this paper, we consider a new type of secret related to the
knowledge of the system user. Specifically, we assume that the system user also
only has partial observation of the system and has to reason the actual
behavior of the system. We say a system is high-order opaque if the intruder
can never determine that the system user knows some information of importance
based on its own incomparable information. We provide the formal definition of
high-order opacity. Two algorithms are provided for the verification of this
new notion: one with doubly-exponential complexity for the worst case and the
other with single-exponential complexity. Illustrative examples are provided
for the new notion of high-order opacity.


  The study of greedy approximation in the context of convex optimization is
becoming a promising research direction as greedy algorithms are actively being
employed to construct sparse minimizers for convex functions with respect to
given sets of elements. In this paper we propose a unified way of analyzing a
certain kind of greedy-type algorithms for the minimization of convex functions
on Banach spaces. Specifically, we define the class of Weak Biorthogonal Greedy
Algorithms for convex optimization that contains a wide range of greedy
algorithms. We analyze the introduced class of algorithms and establish the
properties of convergence, rate of convergence, and numerical stability, which
is understood in the sense that the steps of the algorithm are allowed to be
performed not precisely but with controlled computational inaccuracies. We show
that the following well-known algorithms for convex optimization -- the Weak
Chebyshev Greedy Algorithm (co) and the Weak Greedy Algorithm with Free
Relaxation (co) -- belong to this class, and introduce a new algorithm -- the
Rescaled Weak Relaxed Greedy Algorithm (co). Presented numerical experiments
demonstrate the practical performance of the aforementioned greedy algorithms
in the setting of convex minimization as compared to optimization with
regularization, which is the conventional approach of constructing sparse
minimizers.


  The studies focused on the Thermally-Pulsing Asymptotic Giant Branch phase
experienced by low- and intermediate-mass stars are extremely important in many
astrophysical contexts. In particular, a detailed computation of their chemical
yields is essential for several issues, ranging from the chemical evolution of
galaxies, to the mechanisms behind the formation of globular clusters. Among
all the uncertainties affecting the theoretical modelling of this phase, and
described in the literature, it remains to be fully clarified which results are
severely affected by the use of inadequate low-temperature opacities, that are
in most cases calculated on the basis of the original chemical composition of
the stars, and do not consider the changes in the surface chemistry due to the
occurrence of the third dredge-up and hot-bottom burning. Our investigation is
aimed at investigating this point. By means of full evolutionary models
including new set of molecular opacities computed specifically with the AESOPUS
tool, we highlight which stellar models, among those present in the literature,
need a substantial revision, mainly in relation to the predicted chemical
yields. The interplay among convection, hot bottom burning and the
low-temperature opacity treatment is also discussed


  LSI +61 303 is one of the few X-ray binaries with a Be star companion from
which radio, X-rays and high-energy gamma-ray (GeV and TeV) emission have been
observed. The nature of the high energy activity of the system is not yet fully
understood, but it is widely believed that it is generated due to the
interaction of the relativistic electrons leaving the compact object with the
photons and non-relativistic wind of the Be star. The superorbital variability
of the system has been observed in the radio, optical and X-ray domains and
could be due to the cyclic change of the Be star disk size. In this paper we
systematically review all publicly available data from Suzaku, XMM-Newton,
Chandra and Swift observatories in order to measure the absorption profile of
the circumstellar Be disk as a function of orbital and superorbital phases. We
also discuss short-term variability of the system, found during the analysis
and its implications for the understanding of the physical processes in this
system.


  Based on the effective Hamiltonian with the generalized factorization
approach, we calculate the branching ratios and CP asymmetries of $B \to VV$
decays in the Topcolor-assisted Technicolor (TC2) model. Within the considered
parameter space we find that: (a) for the penguin-dominated $B \to K^{*+}\phi$
and $K^{*0}\phi$ decays, the new physics enhancements to the branching ratios
are around 40%; (b) the measured branching ratios of $B \to K^{*+} \phi$ and $
K^{*0} \phi$ decays prefer the range of $3 \lesssim \nceff \lesssim 5$; (c) the
SM and TC2 model predictions for the branching ratio ${\cal B}(B^+ \to \rho^+
\rho^0)$ are only about half of the Belle's measurement; and (d) for most $B
\to VV$ decays, the new physics corrections on their CP asymmetries are
generally small or moderate in magnitude and insensitive to the variation of
$\mpcc$ and $\nceff$.


  Generalized dimensions of multifractal measures are usually seen as static
objects, related to the scaling properties of suitable partition functions, or
moments of measures of cells. When these measures are invariant for the flow of
a chaotic dynamical system, generalized dimensions take on a dynamical meaning,
as they provide the rate function for the large deviations of the first hitting
time, which is the (average) time required to connect any two different regions
in phase space. We prove this result rigorously under a set of stringent
assumptions. As a consequence, the statistics of hitting times provides new
algorithms for the computation of the spectrum of generalized dimensions.
Numerical examples, presented along with the theory, suggest that the validity
of this technique reaches far beyond the range covered by the theorem. We state
our result within the framework of extreme value theory. This approach reveals
that hitting times are also linked to dynamical indicators such as stability of
the motion and local dimensions of the invariant measure. This suggests that
one can use local dynamical indicators from finite time series to gather
information on the multifractal spectrum of generalized dimension. We show an
application of this technique to experimental data from climate dynamics.


  For perfect fluids with equation of state $\rho = \rho (n,s)$, Brown gave an
action principle depending only on their Lagrange coordinates $\alpha^i(x)$
without Clebsch potentials. After a reformulation on arbitrary spacelike
hypersurfaces in Minkowski spacetime, the Wigner-covariant rest-frame instant
form of these perfect fluids is given. Their Hamiltonian invariant mass can be
given in closed form for the dust and the photon gas. The action for the
coupling to tetrad gravity is given. Dixon's multipoles for the perfect fluids
are studied on the rest-frame Wigner hyperplane. It is also shown that the same
formalism can be applied to non-dissipative relativistic elastic materials
described in terms of Lagrangian coordinates.


  A subset $A \subset \mathbb R^2$ is said to avoid distance $1$ if: $\forall
x,y \in A, \left\| x-y \right\|_2 \neq 1.$ In this paper we study the number
$m_1(\mathbb R^2)$ which is the supremum of the upper densities of measurable
sets avoiding distance 1 in the Euclidean plane. Intuitively, $m_1(\mathbb
R^2)$ represents the highest proportion of the plane that can be filled by a
set avoiding distance 1. This parameter is related to the fractional chromatic
number $\chi_f(\mathbb R^2)$ of the plane.
  We establish that $m_1(\mathbb R^2) \leq 0.25647$ and $\chi_f(\mathbb R^2)
\geq 3.8991$.


  Keyword-based web queries with local intent retrieve web content that is
relevant to supplied keywords and that represent points of interest that are
near the query location. Two broad categories of such queries exist. The first
encompasses queries that retrieve single spatial web objects that each satisfy
the query arguments. Most proposals belong to this category. The second
category, to which this paper's proposal belongs, encompasses queries that
support exploratory user behavior and retrieve sets of objects that represent
regions of space that may be of interest to the user. Specifically, the paper
proposes a new type of query, namely the top-k spatial textual clusters (k-STC)
query that returns the top-k clusters that (i) are located the closest to a
given query location, (ii) contain the most relevant objects with regard to
given query keywords, and (iii) have an object density that exceeds a given
threshold. To compute this query, we propose a basic algorithm that relies on
on-line density-based clustering and exploits an early stop condition. To
improve the response time, we design an advanced approach that includes three
techniques: (i) an object skipping rule, (ii) spatially gridded posting lists,
and (iii) a fast range query algorithm. An empirical study on real data
demonstrates that the paper's proposals offer scalability and are capable of
excellent performance.


  We present a new QSO selection algorithm using a Support Vector Machine
(SVM), a supervised classification method, on a set of extracted times series
features including period, amplitude, color, and autocorrelation value. We
train a model that separates QSOs from variable stars, non-variable stars and
microlensing events using 58 known QSOs, 1,629 variable stars and 4,288
non-variables using the MAssive Compact Halo Object (MACHO) database as a
training set. To estimate the efficiency and the accuracy of the model, we
perform a cross-validation test using the training set. The test shows that the
model correctly identifies ~80% of known QSOs with a 25% false positive rate.
The majority of the false positives are Be stars.
  We applied the trained model to the MACHO Large Magellanic Cloud (LMC)
dataset, which consists of 40 million lightcurves, and found 1,620 QSO
candidates. During the selection none of the 33,242 known MACHO variables were
misclassified as QSO candidates. In order to estimate the true false positive
rate, we crossmatched the candidates with astronomical catalogs including the
Spitzer Surveying the Agents of a Galaxy's Evolution (SAGE) LMC catalog and a
few X-ray catalogs. The results further suggest that the majority of the
candidates, more than 70%, are QSOs.


  If $V$ is a commutative algebraic group over a field $k$, $O$ is a
commutative ring that acts on $V$, and $I$ is a finitely generated free
$O$-module with a right action of the absolute Galois group of $k$, then there
is a commutative algebraic group $I \otimes_O V$ over $k$, which is a twist of
a power of $V$. These group varieties have applications to cryptography (in the
cases of abelian varieties and algebraic tori over finite fields) and to the
arithmetic of abelian varieties over number fields. For purposes of such
applications we devote this article to making explicit this tensor product
construction and its basic properties.


  We establish new quantitative estimates for localized finite differences of
solutions to the Poisson problem for the fractional Laplace operator with
homogeneous Dirichlet conditions of solid type settled in bounded domains
satisfying the Lipschitz cone regularity condition. We then apply these
estimates to obtain (i)~regularity results for solutions of fractional Poisson
problems in Besov spaces; (ii)~quantitative stability estimates for solutions
of fractional Poisson problems with respect to domain perturbations;
(iii)~quantitative stability estimates for eigenvalues and eigenfunctions of
fractional Laplace operators with respect to domain perturbations.


  For the trace of Besov spaces $B^s_{p,q}$ onto a hyperplane, the borderline
case with $s=\frac{n}{p}-(n-1)$ and $0<p<1$ is analysed and a new dependence on
the sum-exponent $q$ is found. Through examples the restriction operator
defined for $s$ down to $1/p$, and valued in $L_p$, is shown to be distinctly
different and, moreover, unsuitable for elliptic boundary problems. All
boundedness properties (both new and previously known) are found to be easy
consequences of a simple mixed-norm estimate, which also yields continuity with
respect to the normal coordinate. The surjectivity for the classical borderline
$s=\frac1p$ ($1\le p<\infty$) is given a simpler proof for all $q\in\,]0,1]$,
using only basic functional analysis. The new borderline results are based on
corresponding convergence criteria for series with spectral conditions.


  Cycle scenarios are a significant class of contextuality scenarios, with the
Clauser-Horne-Shimony-Holt (CHSH) scenario being a notable example. While
binary outcome measurements in these scenarios are well understood, the
generalization to arbitrary outcomes remains less explored, except in specific
cases. In this work, we employ homotopical methods in the framework of
simplicial distributions to characterize all contextual vertices of the
non-signaling polytope corresponding to cycle scenarios with arbitrary
outcomes. Additionally, our techniques utilize the bundle perspective on
contextuality and the decomposition of measurement spaces. This enables us to
extend beyond scenarios formed by gluing cycle scenarios and describe
contextual extremal simplicial distributions in these generalized contexts.


  Spatial co-location patterns are the subsets of Boolean spatial features
whose instances are often located in close geographic proximity. Co-location
rules can be identified by spatial statistics or data mining approaches. In
data mining method, Association rule-based approaches can be used which are
further divided into transaction-based approaches and distance-based
approaches. Transaction-based approaches focus on defining transactions over
space so that an Apriori algorithm can be used. The natural notion of
transactions is absent in spatial data sets which are embedded in continuous
geographic space. A new distance -based approach is developed to mine
co-location patterns from spatial data by using the concept of proximity
neighborhood. A new interest measure, a participation index, is used for
spatial co-location patterns as it possesses an anti-monotone property. An
algorithm to discover co-location patterns are designed which generates
candidate locations and their table instances. Finally the co-location rules
are generated to identify the patterns.


  In this article, we study properly immersed complete noncompact submanifolds
in a complete shrinking gradient Ricci soliton with weighted mean curvature
vector bounded in norm. We prove that such a submanifold must have polynomial
volume growth under some mild assumption on the potential function. On the
other hand, if the ambient manifold is of bounded geometry, we prove that such
a submanifold must have at least linear volume growth. In particular, we show
that a properly immersed complete noncompact hypersurface in the Euclidean
space with bounded Gaussian weighted mean curvature must have polynomial volume
growth and at least linear volume growth.


  To date, most efforts to demonstrate quantum nonlocality have concentrated on
systems of two (or very few) particles. It is however difficult in many
experiments to address individual particles, making it hard to highlight the
presence of nonlocality. We show how a natural setup with no access to
individual particles allows one to violate the CHSH inequality with many pairs,
including in our analysis effects of noise and losses. We discuss the case of
distinguishable and indistinguishable particles. Finally, a comparison of these
two situations provides new insight into the complex relation between
entanglement and nonlocality.


  Single-particle cryo-electron microscopy (cryo-EM) reconstructs the
three-dimensional (3D) structure of bio-molecules from a large set of 2D
projection images with random and unknown orientations. A crucial step in the
single-particle cryo-EM pipeline is 3D refinement, which resolves a
high-resolution 3D structure from an initial approximate volume by refining the
estimation of the orientation of each projection. In this work, we propose a
new approach that refines the projection angles on the continuum. We formulate
the optimization problem over the density map and the orientations jointly. The
density map is updated using the efficient alternating-direction method of
multipliers, while the orientations are updated through a semi-coordinate-wise
gradient descent for which we provide an explicit derivation of the gradient.
Our method eliminates the requirement for a fine discretization of the
orientation space and does away with the classical but computationally
expensive template-matching step. Numerical results demonstrate the feasibility
and performance of our approach compared to several baselines.


  In this paper, a followup of arXiv: 1802.05722, we describe the many pathways
to generate Dirac neutrino mass through dimension-6 operators. By using only
the Standard Model Higgs doublet in the external legs one gets a unique
operator $\frac{1}{\Lambda^2} \, \bar{L}\, \bar{\Phi} \, \bar{\Phi} \, \Phi \,
\nu_R $. In contrast, the presence of new scalars implies new possible field
contractions, which greatly increase the number of possibilities. Here we study
in detail the simplest ones, involving $SU(2)_L$ singlets, doublets and
triplets. The extra symmetries needed to ensure the Dirac nature of neutrinos
can also be responsible for stabilizing dark matter.


  Recently we introduced T-duality in the study of topological insulators. In
this paper, we study the bulk-boundary correspondence for three phenomena in
condensed matter physics, namely, the quantum Hall effect, the Chern insulator,
and time reversal invariant topological insulators. In all of these cases, we
show that T-duality trivializes the bulk-boundary correspondence.


  We consider the task of computing an approximation of a trembling hand
perfect equilibrium for an n-player game in strategic form, n >= 3. We show
that this task is complete for the complexity class FIXP_a. In particular, the
task is polynomial time equivalent to the task of computing an approximation of
a Nash equilibrium in strategic form games with three (or more) players.


  As a direct source of information on chiral symmetry breaking within QCD, the
sigma commutator is of considerable importance. Since hadron structure is a
non-perturbative problem, numerical calculations on a space-time lattice are
currently the only rigorous approach. With recent advances in the calculation
of hadron masses within full QCD, it is of interest to see whether the sigma
commutator can be calculated directly from the dependence of the nucleon mass
on the input quark mass. We show that, provided the correct chiral behaviour of
QCD is respected in the extrapolation to realistic quark masses, one can indeed
obtain a fairly reliable determination of the sigma commutator using present
lattice data. For two-flavour dynamical fermion QCD the sigma commutator lies
between 45 and 55 MeV based on recent data from CP-PACS and UKQCD.


  We observed the expansion of vortex-free Bose-condensates after their sudden
release from a slowly rotating anisotropic trap. Our results show clear
experimental evidence of the irrotational flow expected for a superfluid. The
expansion from a rotating trap has strong features associated with the
superfluid nature of a Bose-condensate, namely that the condensate cannot at
any point be cylindrically symmetric with respect to the axis of rotation since
such a wavefunction cannot possess angular momentum. Consequently, an initially
rotating condensate expands in a distinctively different way to one released
from a static trap. We report measurements of this phenomenon in absorption
images of the condensate taken along the direction of the rotation axis.


  In this paper, we will extend the falling and rising factorial transforms
\cite{ref. 1} which in this case every arbitrary function can be applied. Then,
the properties of these transforms will be investigated and some corollaries
will be shown. These transforms have interesting properties that led to new
series expansions, representation of functions in terms of operators,
connection between different series and operators, etc. By converting the power
series into the Newton series, useful identities can be derived.


  Two potential sources of tuning exist in composite Higgs models: one comes
from keeping the Higgs VEV below the compositeness scale and one comes from
keeping the Higgs light after constraints on the top partner masses are
applied. We construct a measure that determines whether these tunings are
independent or not and combines them appropriately. We perform a comprehensive
scan of the parameter space for three explicit models and report the minimum
tuning values compatible with existing collider constraints. Tuning values are
given as functions of resonance masses and deviations to the Higgs couplings so
the effect of future constraints can easily be quantified. The current minimum
tuning in the minimal model is 2.5-5% and will be decreased to around 0.8-3.3%
if no top partners are observed over the lifetime of the LHC.


  With the use of twin, co-located, 3D interferometers, Cardiff University's
Gravity Exploration Institute aims to observe quantum fluctuations of
space-time as predicted by some theories of quantum gravity. Our design
displacement sensitivity exceeds that of previous similar experiments, which
have constrained the magnitudes of the fluctuations in the 1-25 MHz band. The
increased sensitivity comes in large part from the comparably higher
circulating power we aim to achieve, which reduces the overall shot noise. One
complication of higher circulating power is an increase in contrast defect
light, which includes higher-order modes. We will use the DC-readout scheme,
whose dark-fringe offset must sufficiently dominate the contrast defect in
order to detect faint signals. However, too much total output power risks
saturating the high-bandwidth photodetectors. Suppressing the higher-order mode
content of the contrast defect is a key strategy to realising the high
circulating power and eliminating non-signal-carrying power that contributes to
shot noise. For this, the inclusion of an output mode cleaner, whose design is
described, is required.


  We introduce a formal model for order queries on lists in zero knowledge in
the traditional authenticated data structure model. We call this model
Privacy-Preserving Authenticated List (PPAL). In this model, the queries are
performed on the list stored in the (untrusted) cloud where data integrity and
privacy have to be maintained. To realize an efficient authenticated data
structure, we first adapt consistent data query model. To this end we introduce
a formal model called Zero-Knowledge List (ZKL) scheme which generalizes
consistent membership queries in zero-knowledge to consistent membership and
order queries on a totally ordered set in zero knowledge. We present a
construction of ZKL based on zero-knowledge set and homomorphic integer
commitment scheme. Then we discuss why this construction is not as efficient as
desired in cloud applications and present an efficient construction of PPAL
based on bilinear accumulators and bilinear maps which is provably secure and
zero-knowledge.


  Considering an environment containing polygonal obstacles, we address the
problem of planning motions for a pair of planar robots connected to one
another via a cable of limited length. Much like prior problems with a single
robot connected via a cable to a fixed base, straight line-of-sight visibility
plays an important role. The present paper shows how the reduced visibility
graph provides a natural discretization and captures the essential topological
considerations very effectively for the two robot case as well. Unlike the
single robot case, however, the bounded cable length introduces considerations
around coordination (or equivalently, when viewed from the point of view of a
centralized planner, relative timing) that complicates the matter. Indeed, the
paper has to introduce a rather more involved formalization than prior
single-robot work in order to establish the core theoretical result -- a
theorem permitting the problem to be cast as one of finding paths rather than
trajectories. Once affirmed, the planning problem reduces to a straightforward
graph search with an elegant representation of the connecting cable, demanding
only a few extra ancillary checks that ensure sufficiency of cable to guarantee
feasibility of the solution. We describe our implementation of A${}^\star$
search, and report experimental results. Lastly, we prescribe an optimal
execution for the solutions provided by the algorithm.


  Recently we developed supervisor localization, a top-down approach to
distributed control of discrete-event systems in the Ramadge-Wonham supervisory
control framework. Its essence is the decomposition of monolithic (global)
control action into local control strategies for the individual agents. In this
paper, we establish a counterpart supervisor localization theory in the
framework of State Tree Structures, known to be efficient for control design of
very large systems. In the new framework, we introduce the new concepts of
local state tracker, local control function, and state-based local-global
control equivalence. As before, we prove that the collective localized control
behavior is identical to the monolithic optimal (i.e. maximally permissive) and
nonblocking controlled behavior. In addition, we propose a new and more
efficient localization algorithm which exploits BDD computation. Finally we
demonstrate our localization approach on a model for a complex semiconductor
manufacturing system.


  Radiative corrections to high energy scattering processes were given
previously in terms of universal soft and collinear functions. This paper gives
the collinear functions for all standard model particles, the general form of
the soft function, and explicit expressions for the soft functions for
fermion-fermion scattering, longitudinal and transverse gauge boson production,
single W/Z production, and associated Higgs production. An interesting subtlety
in the use of the Goldstone boson equivalence theorem for longitudinal W+
production is discussed.


  We systematically analyze total reaction cross sections of carbon isotopes
with N=6--16 on a $^{12}$C target for wide range of incident energy. The
intrinsic structure of the carbon isotope is described by a Slater determinant
generated from a phenomenological mean-field potential, which reasonably well
reproduces the ground state properties for most of the even $N$ isotopes. We
need separate studies not only for odd nuclei but also for $^{16}$C and
$^{22}$C. The density of the carbon isotope is constructed by eliminating the
effect of the center of mass motion. For the calculations of the cross
sections, we take two schemes: one is the Glauber approximation, and the other
is the eikonal model using a global optical potential. We find that both of the
schemes successfully reproduce low and high incident energy data on the cross
sections of $^{12}$C, $^{13}$C and $^{16}$C on $^{12}$C. The calculated
reaction cross sections of $^{15}$C are found to be considerably smaller than
the empirical values observed at low energy. We find a consistent
parameterization of the nucleon-nucleon scattering amplitude, differently from
previous ones. Finally, we predict the total reaction cross section of $^{22}$C
on $^{12}$C.


  In this paper, a wetting boundary scheme used to describe the interactions
among ternary fluids and solid is proposed in the framework of the lattice
Boltzmann method. This scheme for three-phase fluids can preserve the reduction
consistency property with the diphasic situation such that it could give
physically relevant results. Combining this wetting boundary scheme and the
lattice Boltzmann (LB) ternary fluid model based on the multicomponent
phase-field theory, we simulated several ternary fluid flow problems involving
solid substrate, including the spreading of binary drops on the substrate, the
spreading of a compound drop on the substrate, and the shear of a compound
liquid drop on the substrate. The numerical results are found to be good
agreement with the analytical solutions or some available results. Finally, as
an application, we use the LB model coupled with the present wetting boundary
scheme to numerically investigate the impact of a compound drop on a solid
circular cylinder. It is found that the dynamics of a compound drop can be
remarkably influenced by the wettability of the solid surface and the
dimensionless Weber number.


  In this paper, we propose a simple neural net that requires only $O(nlog_2k)$
number of qubits and $O(nk)$ quantum gates: Here, $n$ is the number of input
parameters, and $k$ is the number of weights applied to these parameters in the
proposed neural net. We describe the network in terms of a quantum circuit, and
then draw its equivalent classical neural net which involves $O(k^n)$ nodes in
the hidden layer. Then, we show that the network uses a periodic activation
function of cosine values of the linear combinations of the inputs and weights.
The backpropagation is described through the gradient descent, and then iris
and breast cancer datasets are used for the simulations. The numerical results
indicate the network can be used in machine learning problems and it may
provide exponential speedup over the same structured classical neural net.


  Gaussian graphical models are semi-algebraic subsets of the cone of positive
definite covariance matrices. They are widely used throughout natural sciences,
computational biology and many other fields. Computing the vanishing ideal of
the model gives us an implicit description of the model.
  In this paper, we resolve two conjectures of Sturmfels and Uhler from
\cite{BS n CU}. In particular, we characterize those graphs for which the
vanishing ideal of the Gaussian graphical model is generated in degree $1$ and
$2$. These turn out to be the Gaussian graphical models whose ideals are toric
ideals, and the resulting graphs are the $1$-clique sums of complete graphs.


  Constitutive tensors are of common use in mechanics of materials. To
determine the relevant symmetry class of an experimental tensor is still a
tedious problem. For instance, it requires numerical methods in
three-dimensional elasticity. We address here the more affordable case of plane
(bi-dimensional) elasticity, which has not been fully solved yet. We recall
first Vianello's orthogonal projection method, valid for both the isotropic and
the square symmetric (tetragonal) symmetry classes. We then solve in a
closed-form the problem of the distance to plane elasticity orthotropy, thanks
to the Euler-Lagrange method.


  We show that the process $e^+e^- \to \gamma+$ missing energy, arising from
the pair production of neutralinos, can probe the $\gamma-\tilde\gamma-
\gravitino$ as well as the $Z-\tilde Z-\gravitino$ couplings in Gauge Mediated
Supersymmetry Breaking models. This enables one to study the mutual
relationship of the Goldstino couplings of the different gauginos, a feature
whose testability has not been emphasized so far. The Standard Model
backgrounds get suppresed with the use of a right polarized electron beam. The
energy and angular distribution of the emitted photon can distinguish such
models from the minimal supersymmetric theory and its variants.


  The mechanism for producing polarized emission from protostellar disks at
(sub)millimeter wavelengths is currently uncertain. Classically, polarization
is expected from non-spherical grains aligned with the magnetic field.
Recently, two alternatives have been suggested. One polarization mechanism is
caused by self-scattering from dust grains of sizes comparable to the
wavelength while the other mechanism is due to grains aligned with their short
axes along the direction of radiation anisotropy. The latter has recently been
shown as a likely mechanism for causing the dust polarization detected in HL
Tau at 3.1 mm. In this paper, we present ALMA polarization observations of HL
Tau for two more wavelengths: 870 $\mu$m and 1.3 mm. The morphology at 870
$\mu$m matches the expectation for self-scattering, while that at 1.3 mm shows
a mix between self-scattering and grains aligned with the radiation anisotropy.
The observations cast doubt on the ability of (sub)millimeter continuum
polarization to probe disk magnetic fields for at least HL Tau. By showing two
distinct polarization morphologies at 870 $\mu$m and 3.1 mm and a transition
between the two at 1.3 mm, this paper provides definitive evidence that the
dominant (sub)millimeter polarization mechanism transitions with wavelength. In
addition, if the polarization at 870 $\mu$m is due to scattering, the lack of
polarization asymmetry along the minor axis of the inclined disk implies that
the large grains responsible for the scattering have already settled into a
geometrically thin layer, and the presence of asymmetry along the major axis
indicates that the HL Tau disk is not completely axisymmetric.


  The entanglement content of superpositions of pairs of degenerate eigenstates
of a bipartite system are considered in the case that both are also eigenstates
of the $z$ component of the total angular momentum. It is shown that the von
Neumann entropy of the state that is obtained tracing out one of the parts of
the system has a definite convexity (concavity) as a function of the
superposition parameter and that its convexity (concavity) can be predicted
using a quantity of information that measures the entropy shared by the states
at the extremes of the superposition. Several examples of two particle system,
whose eigenfunctions and density matrices can be obtained exactly, are analyzed
thoroughly.


  We study the effects of clouds on the dynamical and chemical evolution of
gas-rich dwarf galaxies, in particular focusing on two model galaxies similar
to IZw18 and NGC1569. We consider both scenarios, clouds put at the beginning
of the simulation and continuously created infalling ones. Due to dynamical
processes and thermal evaporation, the clouds survive only a few tens of Myr,
but during this time they act as an additional cooling agent and the internal
energy of cloudy models is typically reduced by 20 - 40% in comparison with
models without clouds. The clouds delay the development of large-scale
outflows, therefore helping to retain a larger amount of gas inside the galaxy.
However, especially in models with continuous creation of infalling clouds,
their bullet effect can pierce the expanding supershell and create holes
through which the superbubble can vent freshly produced metals. Moreover,
assuming a pristine chemical composition for the clouds, their interaction with
the superbubble dilutes the gas, reducing the metallicity (by up to ~ 0.4 dex)
with respect to the one attained by diffuse models.


  We calculate the neutrino yield from collisions of cosmic ray (CR) nuclei on
gas using the event generator QGSJET-II. We present first the general
characteristics and numerical results for the neutrino yield assuming power-law
fluxes for the primary CR nuclei. Then we use three parameterisations for the
Galactic CR flux to derive the neutrino yield for energies around and above the
knee. The shape and the normalization of the resulting neutrino flux above
$\sim 10^{14}$ eV depends on the composition of the Galactic CR flux employed,
but is generally dominated by its proton component. The spectral shape and
magnitude of the neutrino flux suggest that the IceCube excess is not connected
to interactions of Galactic sea CRs. If a fraction of these events has a
Galactic origin, then they may be caused by CR overdensities around recent
close-by Galactic sources.


  Hybrid Energy Systems (HES), amalgamating renewable sources, energy storage,
and conventional generation, have emerged as a responsive resource for
providing valuable grid services. Subsequently, modeling and analysis of HES
has become critical, and the quality of grid services hedges on it. Currently,
most HES models are temperature-agnostic. However, the temperature-dependent
factors can significantly impact HES performance, necessitating advanced
modeling and optimization techniques. With the inclusion of
temperature-dependent models, the challenges and complexity of solving
optimization problem increases. In this paper, the electro-thermal modeling of
HES is discussed. Based on this model, a nonlinear predictive optimization
framework is formulated. A simplified model is developed to address the
challenges associated with solving nonlinear problems. Further, projection and
homotopy approaches are proposed. In the homotopy method, the NLP is solved by
incrementally changing the C-rating of the battery. Simulation-based analysis
of the algorithms highlights the effects of different battery ratings, ambient
temperatures, and energy price variations. Finally, comparative assessments
with a temperature-agnostic approach illustrates the effectiveness of
electro-thermal methods in optimizing HES.


  For a given graph $G$, a maximum internal spanning tree of $G$ is a spanning
tree of $G$ with maximum number of internal vertices. The Maximum Internal
Spanning Tree (MIST) problem is to find a maximum internal spanning tree of the
given graph. The MIST problem is a generalization of the Hamiltonian path
problem. Since the Hamiltonian path problem is NP-hard, even for bipartite and
chordal graphs, two important subclasses of graphs, the MIST problem also
remains NP-hard for these graph classes. In this paper, we propose linear-time
algorithms to compute a maximum internal spanning tree of cographs, block
graphs, cactus graphs, chain graphs and bipartite permutation graphs. The
optimal path cover problem, which asks to find a path cover of the given graph
with maximum number of edges, is also a well studied problem. In this paper, we
also study the relationship between the number of internal vertices in maximum
internal spanning tree and number of edges in optimal path cover for the
special graph classes mentioned above.


  Intelligent vehicles in autonomous driving and obstacle avoidance, the
precise relative state of vehicles put forward a higher demand. For a
vehicle-borne sensor network with time-varying transmission delays, the problem
of coordinate fusion of vehicle state is the focus of this paper. By the
ingeniously designed low-complexity integration with a consensus strategy and
buffer technology, an anti-delay distributed Kalman filter (DKF) with
finite-time convergence is proposed.By introducing the matrix weight to assess
local estimates, the optimal fusion state result is available in the sense of
linear minimum variance. In addition, to accommodate practical engineering in
intelligent vehicles, the communication weight coefficient and directed
topology with unidirectional transmission are also considered. From a
theoretical perspective, the proof of error covariances upper bounds with
different communication topologies with delays are presented. Furthermore, the
maximum allowable delays of vehicle-borne sensor network is derived backwards.
Simulations verify that while considering various non-ideal factors above, the
proposed DFK algorithm produces more accurate and robust fusion estimation
state results than existing algorithms, making it more valuable in practical
applications. Simultaneously, a mobile car trajectory tracking experiment is
carried out, which further verifies the feasibility of the proposed algorithm.