  Automatic machine-based Facial Expression Analysis (FEA) has made substantial
progress in the past few decades driven by its importance for applications in
psychology, security, health, entertainment and human computer interaction. The
vast majority of completed FEA studies are based on non-occluded faces
collected in a controlled laboratory environment. Automatic expression
recognition tolerant to partial occlusion remains less understood, particularly
in real-world scenarios. In recent years, efforts investigating techniques to
handle partial occlusion for FEA have seen an increase. The context is right
for a comprehensive perspective of these developments and the state of the art
from this perspective. This survey provides such a comprehensive review of
recent advances in dataset creation, algorithm development, and investigations
of the effects of occlusion critical for robust performance in FEA systems. It
outlines existing challenges in overcoming partial occlusion and discusses
possible opportunities in advancing the technology. To the best of our
knowledge, it is the first FEA survey dedicated to occlusion and aimed at
promoting better informed and benchmarked future work.


  Boolean locales are "almost discrete", in the sense that a spatial Boolean
locale is just a discrete locale (that is, it corresponds to the frame of open
subsets of a discrete space, namely the powerset of a set). This basic fact,
however, cannot be proven constructively, that is, over intuitionistic logic,
as it requires the full law of excluded middle (LEM). In fact, discrete locales
are never Boolean constructively, except for the trivial locale. So, what is an
almost discrete locale constructively? Our claim is that Sambin's overlap
algebras have good enough features to deserve to be called that. Namely, they
include the class of discrete locales, they arise as smallest strongly dense
sublocales (of overt locales), and hence they coincide with the Boolean locales
if LEM holds.


  Let $G$ be a linear semisimple algebraic group and $B$ its Borel subgroup.
Let $\mathbb{T}\subset B$ be the maximal torus. We study the inductive
construction of Bott-Samelson varieties to obtain recursive formulas for the
twisted motivic Chern classes of Schubert cells in $G/B$. To this end we
introduce two families of operators acting on the equivariant K-theory
$K_\mathbb{T}(G/B)[y]$, the right and left Demazure-Lusztig operators depending
on a parameter. The twisted motivic Chern classes coincide (up to
normalization) with the K-theoretic stable envelopes. Our results imply
wall-crossing formulas for a change of the weight chamber and slope parameters.
The right and left operators generate a twisted double Hecke algebra. We show
that in the type $A$ this algebra acts on the Laurent polynomials. This action
is a natural lift of the action on $K_\mathbb{T}(G/B)[y]$ with respect to the
Kirwan map. We show that the left and right twisted Demazure-Lusztig operators
provide a recursion for twisted motivic Chern classes of matrix Schubert
varieties.


  While 3D object detection in LiDAR point clouds is well-established in
academia and industry, the explainability of these models is a largely
unexplored field. In this paper, we propose a method to generate attribution
maps for the detected objects in order to better understand the behavior of
such models. These maps indicate the importance of each 3D point in predicting
the specific objects. Our method works with black-box models: We do not require
any prior knowledge of the architecture nor access to the model's internals,
like parameters, activations or gradients. Our efficient perturbation-based
approach empirically estimates the importance of each point by testing the
model with randomly generated subsets of the input point cloud. Our
sub-sampling strategy takes into account the special characteristics of LiDAR
data, such as the depth-dependent point density. We show a detailed evaluation
of the attribution maps and demonstrate that they are interpretable and highly
informative. Furthermore, we compare the attribution maps of recent 3D object
detection architectures to provide insights into their decision-making
processes.


  We recount problems, questions and conjectures that arose during a problem
session of the Third International Conference on Permutation Patterns,
University of Florida, March 7-11, 2005.


  The huge advantage of in-pipe robots is that they are able to measure from
inside the pipes, and to sense the geometry, appearance and radiometry
directly. The downside is the inability to know precise, absolute position of
the measurements in very long pipe runs. This paper develops the unprecedented
localization required for this purpose.


  The last decade has seen great progress in both dynamic network modeling and
topic modeling. This paper draws upon both areas to create a Bayesian method
that allows topic discovery to inform the latent network model and the network
structure to facilitate topic identification. We apply this method to the 467
top political blogs of 2012. Our results find complex community structure
within this set of blogs, where community membership depends strongly upon the
set of topics in which the blogger is interested.


  This paper concerns a method of selecting a subset of features for a
sequential logit model. Tanaka and Nakagawa (2014) proposed a mixed integer
quadratic optimization formulation for solving the problem based on a quadratic
approximation of the logistic loss function. However, since there is a
significant gap between the logistic loss function and its quadratic
approximation, their formulation may fail to find a good subset of features. To
overcome this drawback, we apply a piecewise-linear approximation to the
logistic loss function. Accordingly, we frame the feature subset selection
problem of minimizing an information criterion as a mixed integer linear
optimization problem. The computational results demonstrate that our
piecewise-linear approximation approach found a better subset of features than
the quadratic approximation approach.


  Damping typically results in attenuation of vibrations and elastic wave
propagation in mechanical systems. Contrary to this conventional understanding,
we demonstrate experimentally and explain theoretically the revival of an
elastic wave transmitted through a periodic metastructure when a weak
non-Hermitian defect (damping mechanism) induces violation of time-reversal
symmetry. Damping alters the nature of the system's resonant modes, instigating
interference in the scattering field. This leads to transmission revival,
revealing the presence of hidden modes which are otherwise masked by the
symmetry. Our findings offer an innovative approach for designing
dissipation-driven switches and controllers and non-destructive structural
health monitoring systems.


  We establish a relation between higher contact-like structures on
supermanifolds and the N = 1 super-Poincare group via its superspace
realisation. To do this we introduce a vector-valued contact structure, which
we refer to as a polycontact structure.


  Consider the parabolic Anderson model
$\partial_tu=\frac{1}{2}\partial_x^2u+u\, \eta$ on the interval $[0, L]$ with
Neumann, Dirichlet or periodic boundary conditions, driven by space-time white
noise $\eta$. Using Malliavin-Stein method, we establish the central limit
theorem for the fluctuation of the spatial integral $\int_0^Lu(t\,, x)\,
\mathrm{d} x$ as $L$ tends to infinity, where the limiting Gaussian
distribution is independent of the choice of the boundary conditions and
coincides with the Gaussian fluctuation for the spatial average of parabolic
Anderson model on the whole space $\mathbb{R}$.


  Sgr A* is an ideal target to study low-luminosity accreting systems. It has
been recently proposed that properties of the accretion flow around Sgr A* can
be probed through its interactions with the stellar wind of nearby massive
stars belonging to the S-cluster. When a star intercepts the accretion disk,
the ram and thermal pressures of the disk terminate the stellar wind leading to
the formation of a bow shock structure. Here, a semi-analytical model is
constructed which describes the geometry of the termination shock formed in the
wind. With the employment of numerical hydrodynamic simulations, this model is
both verified and extended to a region prone to Kelvin-Helmholtz instabilities.
Because the characteristic wind and stellar velocities are in $\sim10^{8}$ cm
s$^{-1}$ range, the shocked wind may produce detectable X-rays via thermal
bremsstrahlung emission. The application of this model to the pericenter
passage of S2, the brightest member of the S-cluster, shows that the shocked
wind produces roughly a month long X-ray flare with a peak luminosity of
$L\approx 4 \times 10^{33}$ erg s$^{-1}$ for a stellar mass-loss rate, disk
number density, and thermal pressure strength of $\dot{M}_{\rm w}= 10^{-7}
M_\odot\, {\rm yr}^{-1}$, $n_{\rm d} = 10^{5}$ cm$^{-3}$, and $\alpha=0.1$,
respectively. This peak luminosity is comparable to the quiescent X-ray
emission detected from Sgr A* and is within the detection capabilities of
current X-ray observatories. Its detection could constrain the density and
thickness of the disk at a distance of $\sim 3000$ gravitational radii from the
supermassive black hole.


  We use algebraic techniques to study homological filling functions of groups
and their subgroups. If $G$ is a group admitting a finite $(n+1)$--dimensional
$K(G,1)$ and $H \leq G$ is of type $F_{n+1}$, then the $n^{th}$--homological
filling function of $H$ is bounded above by that of $G$. This contrast with
known examples where such inequality does not hold under weaker conditions on
the ambient group $G$ or the subgroup $H$. We include applications to
hyperbolic groups and homotopical filling functions.


  Graph Transformer, due to its global attention mechanism, has emerged as a
new tool in dealing with graph-structured data. It is well recognized that the
global attention mechanism considers a wider receptive field in a fully
connected graph, leading many to believe that useful information can be
extracted from all the nodes. In this paper, we challenge this belief: does the
globalizing property always benefit Graph Transformers? We reveal the
over-globalizing problem in Graph Transformer by presenting both empirical
evidence and theoretical analysis, i.e., the current attention mechanism overly
focuses on those distant nodes, while the near nodes, which actually contain
most of the useful information, are relatively weakened. Then we propose a
novel Bi-Level Global Graph Transformer with Collaborative Training
(CoBFormer), including the inter-cluster and intra-cluster Transformers, to
prevent the over-globalizing problem while keeping the ability to extract
valuable information from distant nodes. Moreover, the collaborative training
is proposed to improve the model's generalization ability with a theoretical
guarantee. Extensive experiments on various graphs well validate the
effectiveness of our proposed CoBFormer.


  State-of-the-art (SOTA) semi-supervised learning (SSL) methods have been
highly successful in leveraging a mix of labeled and unlabeled data by
combining techniques of consistency regularization and pseudo-labeling. During
pseudo-labeling, the model's predictions on unlabeled data are used for
training and thus, model calibration is important in mitigating confirmation
bias. Yet, many SOTA methods are optimized for model performance, with little
focus directed to improve model calibration. In this work, we empirically
demonstrate that model calibration is strongly correlated with model
performance and propose to improve calibration via approximate Bayesian
techniques. We introduce a family of new SSL models that optimizes for
calibration and demonstrate their effectiveness across standard vision
benchmarks of CIFAR-10, CIFAR-100 and ImageNet, giving up to 15.9% improvement
in test accuracy. Furthermore, we also demonstrate their effectiveness in
additional realistic and challenging problems, such as class-imbalanced
datasets and in photonics science.


  This paper establishes a nearly optimal algorithm for estimating the
frequencies and amplitudes of a mixture of sinusoids from noisy equispaced
samples. We derive our algorithm by viewing line spectral estimation as a
sparse recovery problem with a continuous, infinite dictionary. We show how to
compute the estimator via semidefinite programming and provide guarantees on
its mean-square error rate. We derive a complementary minimax lower bound on
this estimation rate, demonstrating that our approach nearly achieves the best
possible estimation error. Furthermore, we establish bounds on how well our
estimator localizes the frequencies in the signal, showing that the
localization error tends to zero as the number of samples grows. We verify our
theoretical results in an array of numerical experiments, demonstrating that
the semidefinite programming approach outperforms two classical spectral
estimation techniques.


  We discuss localization properties of the Dirac-like electronic states in
monolayers of graphite. In the framework of a general disorder model, we
identify the conditions under which such standard localization effects as
logarithmic temperature-dependent conductivity corrections appear to be
strongly suppressed, as compared to the case of a two-dimensional electron gas
with parabolic dispersion, in agreement with recent experimental observations.


  Circa 1962 Hans A. Buchdahl pioneered a program -- and made significant
progress -- seeking vacuo configurations in pure $\mathcal{R}^{2}$ gravity [H.
A. Buchdahl, Nuovo Cimento 23, 141 (1962)]. Unfortunately, he deemed the final
step in his calculations impassable and prematurely suspended his pursuit.
Since then, his achievements on this front have faded into dormancy.
Unbeknownst to Buchdahl himself, the $\mathcal{R}^{2}$ vacua that he sought
were within $\textit{his}$ striking distance. In our recent three-paper body of
work published in Phys. Rev. D, we broke this six-decades-old impasse and
accomplished his goal: A novel class of metrics, describing non-Schwarzschild
spacetimes in quadratic gravity and carrying a hallmark of higher-derivative
characteristic. Intriguing properties of Buchdahl-inspired spacetimes and their
associated Morris-Thorne-Buchdahl wormholes -- summarized herein -- embody a
new branch of phenomenology that transcends the Einstein-Hilbert paradigm.


  In this work we have studied the singular behaviour of gravitational theories
with non symmetric connections. For this purpose we introduce a new criteria
for the appearance of singularities based on the existence of black/white hole
regions of arbitrary codimension defined inside a spacetime of arbitrary
dimension. We discuss this prescription by increasing the complexity of the
particular torsion theory under study. In this sense, we start with
Teleparallel Gravity, then we analyse Einstein-Cartan theory, and finally
dynamical torsion models.


  Some results are presented indicating the distinct advantages that accrue
from choosing a real representation for the generators of SU(N) rather than the
usual and more popular Gell-Mann type matrices. A few examples in the context
of quantum chromodynamics are used to serve as illustrations.


  In applications of centre manifold theory we need more flexible error
estimates than that provided by, for example, the Approximation Theorem~3 by
Carr (1981,1983). Here we extend the theory to cover the case where the order
of approximation in parameters and that in dynamical variables may be
completely different. This allows, for example, the effective evaluation of
low-dimensional dynamical models at finite parameter values.


  Let S be a compact surface of genus >1, and g be a metric on S of constant
curvature K\in\{-1,0,1\} with conical singularities of negative singular
curvature. When K=1 we add the condition that the lengths of the contractible
geodesics are >2\pi. We prove that there exists a convex polyhedral surface P
in the Lorentzian space-form of curvature K and a group G of isometries of this
space such that the induced metric on the quotient P/G is isometric to (S,g).
Moreover, the pair (P,G) is unique (up to global isometries) among a particular
class of convex polyhedra, namely Fuchsian polyhedra. This extends theorems of
A.D. Alexandrov and Rivin--Hodgson concerning the sphere to the higher genus
cases, and it is also the polyhedral version of a theorem of
Labourie--Schlenker.


  We introduce a graph-aware autoencoder ensemble framework, with associated
formalisms and tooling, designed to facilitate deep learning for scholarship in
the humanities. By composing sub-architectures to produce a model isomorphic to
a humanistic domain we maintain interpretability while providing function
signatures for each sub-architectural choice, allowing both traditional and
computational researchers to collaborate without disrupting established
practices. We illustrate a practical application of our approach to a
historical study of the American post-Atlantic slave trade, and make several
specific technical contributions: a novel hybrid graph-convolutional
autoencoder mechanism, batching policies for common graph topologies, and
masking techniques for particular use-cases. The effectiveness of the framework
for broadening participation of diverse domains is demonstrated by a growing
suite of two dozen studies, both collaborations with humanists and established
tasks from machine learning literature, spanning a variety of fields and data
modalities. We make performance comparisons of several different architectural
choices and conclude with an ambitious list of imminent next steps for this
research.


  We look at the various aspects of treating general relativity as a quantum
theory. It is briefly studied how to consistently quantize general relativity
as an effective field theory. A key achievement here is the long-range
low-energy leading quantum corrections to both the Schwarzschild and Kerr
metrics. The leading quantum corrections to the pure gravitational potential
between two sources are also calculated, both in the mixed theory of scalar QED
and quantum gravity and in the pure gravitational theory. The
(Kawai-Lewellen-Tye) string theory gauge/gravity relations is next dealt with.
We investigate if the KLT-operator mapping extends to the case of higher
derivative effective operators. The KLT-relations are generalized, taking the
effective field theory viewpoint, and remarkable tree-level amplitude relations
between the field theory operators are derived. Quantum gravity is finally
looked at from the the perspective of taking the limit of infinitely many
spatial dimensions. It is verified that only a certain class of planar graphs
will in fact contribute to the $n$-point functions at $D=\infty$. This limit is
somewhat an analogy to the large-N limit of gauge theories although the
interpretation of such a graph limit in a gravitational framework is quite
different.


  We present the first stage of an investigation of the interactions of the
jets in the radio galaxy Hydra A with the intracluster medium. We consider the
jet kinetic power, the galaxy and cluster atmosphere, and the inner structure
of the radio source. Analysing radio observations of the inner lobes of Hydra A
by Taylor et al. (1990) we confirm the jet power estimates of about 1e45 ergs/s
derived by Wise et al. (2007) from dynamical analysis of the X-ray cavities.
With this result and a model for the galaxy halo, we explore the
jet-intracluster medium interactions occurring on a scale of 10 kpc using
two-dimensional, axisymmetric, relativistic pure hydrodynamic simulations. A
key feature is that we identify the three bright knots in the northern jet as
biconical reconfinement shocks, which result when an over pressured jet starts
to come into equilibrium with the galactic atmosphere. Through an extensive
parameter space study we deduce that the jet velocity is approximately 0.8 c at
a distance 0.5 kpc from the black hole. The combined constraints of jet power,
the observed jet radius profile along the jet, and the estimated jet pressure
and jet velocity imply a value of the jet density parameter approximately 13
for the northern jet. We show that for a jet velocity = 0.8c and angle between
the jet and the line of sight = 42 deg, an intrinsic asymmetry in the
emissivity of the northern and southern jet is required for a consistent
brightness ratio approximately 7 estimated from the 6cm VLA image of Hydra A.


  We consider the flavor evolution of a dense neutrino gas by taking into
account both vacuum oscillations and self interactions of neutrinos. We examine
the system from a many-body perspective as well as from the point of view of an
effective one-body description formulated in terms of the neutrino polarization
vectors. We show that, in the single angle approximation, both the many-body
picture and the effective one-particle picture possess several constants of
motion. We write down these constants of motion explicitly in terms of the
neutrino isospin operators for the many-body case and in terms of the
polarization vectors for the effective one-body case. The existence of these
constants of motion is a direct consequence of the fact that the collective
neutrino oscillation Hamiltonian belongs to the class of Gaudin Hamiltonians.
This class of Hamiltonians also includes the (reduced) BCS pairing Hamiltonian
describing superconductivity. We point out the similarity between the
collective neutrino oscillation Hamiltonian and the BCS pairing Hamiltonian.
The constants of motion manifest the exact solvability of the system. Borrowing
the well established techniques of calculating the exact BCS spectrum, we
present exact eigenstates and eigenvalues of both the many-body and the
effective one-particle Hamiltonians describing the collective neutrino
oscillations. For the effective one-body case, we show that spectral splits of
neutrinos can be understood in terms of the adiabatic evolution of some
quasi-particle degrees of freedom from a high density region where they
coincide with flavor eigenstates to the vacuum where they coincide with mass
eigenstates. We write down the most general consistency equations which should
be satisfied by the effective one-body eigenstates and show that they reduce to
the spectral split consistency equations for the appropriate initial
conditions.


  The leading account of several salient observable features of our universe
today is provided by the theory of cosmic inflation. But an important and thus
far intractable question is whether inflation is generic, or whether it is
finely tuned---requiring very precisely specified initial conditions. In this
paper I argue that a recent, model-independent characterization of inflation,
known as the 'effective field theory (EFT) of inflation', promises to address
this question in a thoroughly modern and significantly more comprehensive way
than in the existing literature.
  To motivate and provide context for this claim, I distill three core problems
with the theory of inflation, which I dub the permissiveness problem, the
initial conditions problem, and the multiverse problem. I argue that the
initial conditions problem lies within the scope of EFTs of inflation as they
are currently conceived, whereas the other two problems remain largely
intractable: their solution must await a more complete description of the very
early universe. I highlight recent work that addresses the initial conditions
problem within the context of a dynamical systems analysis of a specific
(state-of-the-art) EFT of inflation, and conclude with a roadmap for how such
work might be extended to realize the promise claimed above.


  In this paper, we construct Shintani lifts from integral weight weakly
holomorphic modular forms to half-integral weight weakly holomorphic modular
forms. Although defined by different methods, these coincide with the classical
Shintani lifts when restricted to the space of cusp forms. As a side effect,
this gives the coefficients of the classical Shintani lifts as new cycle
integrals. This yields new formulas for the $L$-values of Hecke eigenforms.
When restricted to the space of weakly holomorphic modular forms orthogonal to
cusp forms, the Shintani lifts introduce a definition of weakly holomorphic
Hecke eigenforms. Along the way, auxiliary lifts are constructed from the space
of harmonic weak Maass forms which yield a "fractional derivative" from the
space of half-integral weight harmonic weak Maass forms to half-integral weight
weakly holomorphic modular forms. This fractional derivative complements the
usual $\xi$-operator introduced by Bruinier and Funke.


  The fermion propagator in an arbitrary covariant gauge can be obtained from
the Landau gauge result via a Landau-Khalatnikov-Fradkin transformation. This
transformation can be written in a practically useful form in both
configuration and momentum space. It is therefore possible to anticipate
effects of a gauge transformation on the propagator's analytic properties.
These facts enable one to establish that if a critical number of flavours for
chiral symmetry restoration and deconfinement exists in noncompact QED3, then
its value is independent of the gauge parameter. This is explicated using
simple forms for the fermion-photon vertex and the photon vacuum polarisation.
The illustration highlights pitfalls that must be avoided in order to arrive at
valid conclusions. Landau gauge is seen to be the covariant gauge in which the
propagator avoids modification by a non-dynamical gauge-dependent exponential
factor, whose presence can obscure truly observable features of the theory.


  This paper provides a full geometric development of a new technique called
un-reduction, for dealing with dynamics and optimal control problems posed on
spaces that are unwieldy for numerical implementation. The technique, which was
originally concieved for an application to image dynamics, uses Lagrangian
reduction by symmetry in reverse. A deeper understanding of un-reduction leads
to new developments in image matching which serve to illustrate the
mathematical power of the technique.


  In this article we initially fix ourselves to smooth (C^r) expanding
dynamical systems. We prove the C^{r-1} differentiability of the topological
pressure, equilibrium states and their densities with respect to smooth
expanding dynamical systems and any smooth potential (C^{r-1}- linear response
formula wiyh respect to the dynamics, and analytical response formula with
respect to the potential). This is done by proving the regularity of the
dominant eigenvalue of the transfer operator with respect to dynamics and
potential. From that, we obtain strong consequences on the regularity of the
dynamical system statistical properties, that apply in more general contexts.
Indeed, we prove that the average and variance obtained from the central limit
theorem vary $C^{r-1}$ with respect to the $C^{r}-$expanding dynamics and
$C^{r}-$potential, and also, there is a large deviations principle with its
rate $C^{r-1}$ with respect to the dynamics and potential. An application for
multifractal analysis is given.


  The magic wand $\mathbin{-\!\!*}$ (also called separating implication) is a
separation logic connective commonly used to specify properties of partial data
structures, for instance during iterative traversals. A footprint of a magic
wand formula $A \mathbin{-\!\!*} B$ is a state that, combined with any state in
which $A$ holds, yields a state in which $B$ holds. The key challenge of
proving a magic wand (also called packaging a wand) is to find such a
footprint. Existing package algorithms either have a high annotation overhead
or, as we show in this paper, are unsound. We present a formal framework that
precisely characterises a wide design space of possible package algorithms
applicable to a large class of separation logics. We prove in Isabelle/HOL that
our formal framework is sound and complete, and use it to develop a novel
package algorithm that offers competitive automation and is sound. Moreover, we
present a novel, restricted definition of wands and prove in Isabelle/HOL that
it is possible to soundly combine fractions of such wands, which is not the
case for arbitrary wands. We have implemented our techniques for the Viper
language, and demonstrate that they are effective in practice.


  Computational chemistry develops fast in recent years due to the rapid growth
and breakthroughs in AI. Thanks for the progress in natural language
processing, researchers can extract more fine-grained knowledge in publications
to stimulate the development in computational chemistry. While the works and
corpora in chemical entity extraction have been restricted in the biomedicine
or life science field instead of the chemistry field, we build a new corpus in
chemical bond field annotated for 7 types of entities: compound, solvent,
method, bond, reaction, pKa and pKa value. This paper presents a novel BERT-CRF
model to build scientific chemical data chains by extracting 7 chemical
entities and relations from publications. And we propose a joint model to
extract the entities and relations simultaneously. Experimental results on our
Chemical Special Corpus demonstrate that we achieve state-of-art and
competitive NER performance.


  We present the results of detailed monitoring of the radio emission from the
Type Ic supernova SN 1994I from 3 days after optical discovery on 1994 March 31
until eight years later at age 2927 days on 2002 April 05. The data were mainly
obtained using the Very Large Array at the five wavelengths, 1.3, 2.0, 3.6,
6.2, and 21 cm, and from the Cambridge 5 km Ryle Telescope at 2.0 cm. Two
additional measurements were obtained at millimeter wavelengths. This data set
represents the most complete, multifrequency radio observations ever obtained
for a Type Ib/c supernova. The radio emission evolves regularly in both time
and frequency and is well described by established SN emission/absorption
models. It is the first radio supernova with sufficient data to show that it is
clearly dominated by the effects of synchrotron self-absorption at early times.


  The size and complexity of modern astronomical surveys has grown to the point
where, in many cases, traditional human scheduling of observations are tedious
at best and impractical at worst. Automated scheduling algorithms present an
opportunity to save human effort and increase scientific productivity. A common
scheduling challenge involves determining the optimal ordering of a set of
targets over a night subject to timing constraints and time-dependent slew
overheads. We present a solution to the `Traveling Telescope Problem' (TTP)
that uses Mixed-Integer Linear Programming (MILP). This algorithm is fast
enough to enable dynamic schedule generation in many astronomical contexts. It
can determine the optimal solution for 100 observations within 10 minutes on a
modern workstation, reducing slew overheads by a factor of 5 compared to random
ordering. We also provide a heuristic method that can return a near-optimal
solution at significantly reduced computational cost. As a case study, we
explore our algorithm's suitability to automatic schedule generation for
Doppler planet searches.


  The fields of AI current lacks methods to quantitatively assess and
potentially alter the moral values inherent in the output of large language
models (LLMs). However, decades of social science research has developed and
refined widely-accepted moral value surveys, such as the World Values Survey
(WVS), eliciting value judgments from direct questions in various geographies.
We have turned those questions into value statements and use NLP to compute to
how well popular LLMs are aligned with moral values for various demographics
and cultures. While the WVS is accepted as an explicit assessment of values, we
lack methods for assessing implicit moral and cultural values in media, e.g.,
encountered in social media, political rhetoric, narratives, and generated by
AI systems such as LLMs that are increasingly present in our daily lives. As we
consume online content and utilize LLM outputs, we might ask, which moral
values are being implicitly promoted or undercut, or -- in the case of LLMs --
if they are intending to represent a cultural identity, are they doing so
consistently? In this paper we utilize a Recognizing Value Resonance (RVR) NLP
model to identify WVS values that resonate and conflict with a given passage of
output text. We apply RVR to the text generated by LLMs to characterize
implicit moral values, allowing us to quantify the moral/cultural distance
between LLMs and various demographics that have been surveyed using the WVS. In
line with other work we find that LLMs exhibit several Western-centric value
biases; they overestimate how conservative people in non-Western countries are,
they are less accurate in representing gender for non-Western countries, and
portray older populations as having more traditional values. Our results
highlight value misalignment and age groups, and a need for social science
informed technological solutions addressing value plurality in LLMs.


  In this article, we define some types of distances between two intuitionistic
fuzzy soft (IFS) sets and proposed similarity measures of two IFS-sets. We then
construct a decision method which is applied to a medical diagnosis problem
that is based on similarity measures of IFS-sets. Finally we give two simple
example to show the possibility of using this method for diagnosis of diseases
which could be improved by incorporating clinical results and other competing
diagnosis.


  LUX, the world's largest dual-phase xenon time-projection chamber, with a
fiducial target mass of 118 kg and 10,091 kg-days of exposure thus far, is
currently the most sensitive direct dark matter search experiment. The initial
null-result limit on the spin-independent WIMP-nucleon scattering cross-section
was released in October 2013, with a primary scintillation threshold of 2 phe,
roughly 3 keVnr for LUX. The detector has been deployed at the Sanford
Underground Research Facility (SURF) in Lead, South Dakota, and is the first
experiment to achieve a limit on the WIMP cross-section lower than $10^{-45}$
cm$^{2}$. Here we present a more in-depth discussion of the novel energy scale
employed to better understand the nuclear recoil light and charge yields, and
of the calibration sources, including the new internal tritium source. We found
the LUX data to be in conflict with low-mass WIMP signal interpretations of
other results.


  We consider the bosonic Fock space over the Hilbert space of transversal
vector fields in three dimensions. This space carries a canonical
representation of the group of rotations. For a certain class of operators in
Fock space we show that rotation invariance implies the absence of terms which
either create or annihilate only a single particle. We outline an application
of this result in an operator theoretic renormalization analysis of Hamilton
operators, which occur in non-relativistic qed.


  In this article, we introduce Skellam process of order k and its running
average. We also discuss the time-changed Skellam process of order k. In
particular we discuss space-fractional Skellam process and tempered
space-fractional Skellam process via time changes in Poisson process by
independent stable subordinator and tempered stable subordinator, respectively.
We derive the marginal probabilities, Levy measures, governing
difference-differential equations of the introduced processes. Our results
generalize Skellam process and running average of Poisson process in several
directions.


  We find that across a wide range of robot policy learning scenarios, treating
supervised policy learning with an implicit model generally performs better, on
average, than commonly used explicit models. We present extensive experiments
on this finding, and we provide both intuitive insight and theoretical
arguments distinguishing the properties of implicit models compared to their
explicit counterparts, particularly with respect to approximating complex,
potentially discontinuous and multi-valued (set-valued) functions. On robotic
policy learning tasks we show that implicit behavioral cloning policies with
energy-based models (EBM) often outperform common explicit (Mean Square Error,
or Mixture Density) behavioral cloning policies, including on tasks with
high-dimensional action spaces and visual image inputs. We find these policies
provide competitive results or outperform state-of-the-art offline
reinforcement learning methods on the challenging human-expert tasks from the
D4RL benchmark suite, despite using no reward information. In the real world,
robots with implicit policies can learn complex and remarkably subtle behaviors
on contact-rich tasks from human demonstrations, including tasks with high
combinatorial complexity and tasks requiring 1mm precision.


  In this article, we give an explicit formula for the universal weight
function of the quantum twisted affine algebra $U_q(A_2^{(2)})$. The
calculations use the technique of projecting products of Drinfeld currents onto
the intersection of Borel subalgebras of different types.


  Defining nonlocality in a no-input closed quantum network scenario is a new
area of interest nowadays. Gisin, in[Entropy 21, 325 (2019)], proposed a
possible condition for non-tri-locality of the trivial no-input closed network
scenario, triangle network, by introducing a new kind of joint measurement
bases and a probability bound. In[npj Quantum Information (2020) 6:70] they
found a shred of numerical evidence in support of Gisin's probability bound.
Now based on that probability bound, we find the nature of the correlation in a
triangle network scenario. We here observe how far the probability lies from
that Gisin's bound with every possible combination of entangled and local pure
states distributed from three independent quantum sources. Here we use the
generalized Elegant Joint Measurements bases for each party and find that there
is a dependency of non-locality on the entanglement of these joint measurement
bases. We also check the probability bound for the polygon structure.


  For $4 \nmid L$ and $g$ large, we calculate the integral Picard groups of the
moduli spaces of curves and principally polarized abelian varieties with level
$L$ structures. In particular, we determine the divisibility properties of the
standard line bundles over these moduli spaces and we calculate the second
integral cohomology group of the level $L$ subgroup of the mapping class group
(in a previous paper, the author determined this rationally). This entails
calculating the abelianization of the level $L$ subgroup of the mapping class
group, generalizing previous results of Perron, Sato, and the author. Finally,
along the way we calculate the first homology group of the mod $L$ symplectic
group with coefficients in the adjoint representation.


  How dissipation affects transport is an important theme in quantum science.
Here we theoretically investigate an impact of a single-particle loss in
mesoscopic transport, which has been an issue in experiments of ultracold
atomic gases. By explicitly analyzing quantum point contact and quantum dot
systems, we obtain a cumulant generating function on the particle current whose
formal expression turns out to be common to two systems. In terms of this
generating function, behaviors of average current, particle loss rate, and
noises in presences of losses introduced in conduction channels are exemplified
for free fermions. It is shown that the current noise contains the component
proportional to the particle loss rate, which may be measurable in experiments.


  Single molecular magnet (SMM) like paramagnetic molecules interacting with
the ferromagnetic electrodes of a magnetic tunnel junction (MTJ) produce a new
system that differs dramatically from the properties of isolated molecules and
ferromagnets. However, it is unknown how far deep in the ferromagnetic
electrode the impact of the paramagnetic molecule and ferromagnet interactions
can travel for various levels of molecular spin states. Our prior experimental
studies showed two types of paramagnetic SMMs, the hexanuclear Mn6 and
octanuclear Fe-Ni molecular complexes, covalently bonded to ferromagnets
produced unprecedented strong antiferromagnetic coupling between two
ferromagnets at room temperature leading to a number of intriguing
observations. In this paper, we report Monte Carlo Simulations (MCS) study
focusing on the impact of the molecular spin state on cross junction shaped MTJ
based molecular spintronics device (MTJMSD). Our MCS study focused on the
Heisenberg model of MTJMSD and investigated the impact of various molecular
coupling strengths, thermal energy, and molecular spin states. To gauge the
impact of the molecular spin state on the region of ferromagnetic electrodes,
we examined the spatial distribution of molecule-ferromagnet correlated phases.
Our MCS study shows that under a strong coupling regime molecular spin state
should be approximately 30 percent of the ferromagnetic electrode atomic spins
to create long-range correlated phases.


  Intermediate valence compounds containing rare earth or actinide ions are
archetypal systems for the investigation of strong electron correlations. Their
effective electron masses of 10 to 50 times the free electron mass result from
a hybridization of the highly localized $f$-electrons with the more itinerant
$d$-electrons, which is strong enough that their properties are dominated by
on-site electron correlations. To a remarkable degree, this can be modeled by
the Anderson Impurity Model, even though the $f$-electrons are situated on a
periodic lattice. However, in recent years, there has been increasing evidence
that the dynamic magnetic susceptibility of intermediate valence compounds is
not purely local, but shows variations across the Brillouin zone that have been
ascribed to $f$-band coherence. So far, this has been based on simplified
qualitative models. In this article, we present a quantitative comparison of
inelastic neutron scattering from a single crystal of CePd$_3$, measured in
four-dimensional (Q,$\omega$)-space, with ab initio calculations, which are in
excellent agreement on an absolute scale. Our results establish that the
Q-dependence of the scattering is caused by particle-hole excitations within
$f$-$d$ hybridized bands that grow in coherence with decreasing temperature.


  We derive a sufficient condition for advantage distillation to be secure
against collective attacks in device-independent quantum key distribution
(DIQKD), focusing on the repetition-code protocol. In addition, we describe a
semidefinite programming method to check whether this condition holds for any
probability distribution obtained in a DIQKD protocol. Applying our method to
various probability distributions, we find that advantage distillation is
possible up to depolarising-noise values of $q \approx 9.1\%$ or limited
detector efficiencies of $\eta \approx 89.1\%$ in a 2-input 2-output scenario.
This exceeds the noise thresholds of $q \approx 7.1\%$ and $\eta \approx
90.7\%$ respectively for DIQKD with one-way error correction using the CHSH
inequality, thereby showing that it is possible to distill secret key beyond
those thresholds.


  Applying Lie symmetry method, we find the most general Lie point symmetries
group of the radiation natural convection flow equation(RNC). Looking the
adjoint representation of the obtained symmetry group on its Lie algebra, we
will find the preliminary classification of its group-invariant solutions.


  Similarity search is a critical primitive for a wide variety of applications
including natural language processing, content-based search, machine learning,
computer vision, databases, robotics, and recommendation systems. At its core,
similarity search is implemented using the k-nearest neighbors (kNN) algorithm,
where computation consists of highly parallel distance calculations and a
global top-k sort. In contemporary von-Neumann architectures, kNN is
bottlenecked by data movement which limits throughput and latency. In this
paper, we present and evaluate a novel automata-based algorithm for kNN on the
Micron Automata Processor (AP), which is a non-von Neumann near-data processing
architecture. By employing near-data processing, the AP minimizes the data
movement bottleneck and is able to achieve better performance. Unlike prior
work in the automata processing space, our work combines temporal encodings
with automata design to augment the space of applications for the AP. We
evaluate our design's performance on the AP and compare to state-of-the-art
CPU, GPU, and FPGA implementations; we show that the current generation of AP
hardware can achieve over 50x speedup over CPUs while maintaining competitive
energy efficiency gains. We also propose several automata optimization
techniques and simple architectural extensions that highlight the potential of
the AP hardware.


  We consider the electronic structure of, and magnetic exchange (spin)
interactions between, nominally nonmagnetic Eu^3+ ions (4f^6, S=3, L=3, J=0)
within the context of the rocksalt structure compounds EuN and EuP. Both
compounds are ionic [Eu^3+; N^3- and P^3-] semimetals similar to isovalent GdN.
Treating the spin polarization within the 4f shell, and then averaging
consistent with the J=0 configuration, we estimate semimetallic band overlaps
(Eu 5d with pnictide 2p or 3p) of ~0.1 eV (EuN) and ~1.0 eV (EuP) that increase
(become more metallic) with pressure. The calculated bulk modulus is 130 (86)
GPa for EuN (EuP). Exchange (spin-spin) coupling calculated from correlated
band theory is small and ferromagnetic in sign for EuN, increasing in magnitude
with pressure. Conversely, the exchange coupling is antiferromagnetic in sign
for EuP and is larger in magnitude, but decreases with compression. Study of a
two-site model with S_1*S_2 coupling within the J=0,1 spaces of each ion
illustrates the dependence of the magnetic correlation functions on the model
parameters, and indicates that the spin coupling is sufficient to alter the Van
Vleck susceptibility. We outline a scenario of a spin-correlation transition in
a lattice of S=3, L=3, J=0 nonmagnetic ions.


  This paper considers the problem of enabling the user to modify the path of a
telepresence robot. The robot is capable of autonomously navigating to a goal
predefined by the user, but the user might still want to modify the path, for
example, to go further away from other people, or to go closer to landmarks she
wants to see on the way. We propose Human-Influenced Dynamic Window Approach
(HI-DWA), a shared control method aimed for telepresence robots based on
Dynamic Window Approach (DWA) that allows the user to influence the control
input given to the robot. To verify the proposed method, we performed a user
study (N=32) in Virtual Reality (VR) to compare HI-DWA with switching between
autonomous navigation and manual control for controlling a simulated
telepresence robot moving in a virtual environment. Results showed that users
reached their goal faster using HI-DWA controller and found it easier to use.
Preference between the two methods was split equally. Qualitative analysis
revealed that a major reason for the participants that preferred switching
between two modes was the feeling of control. We also analyzed the effect of
different input methods, joystick and gesture, on the preference and perceived
workload.


  Lagrange's Four Squares Theorem states that any positive integer can be
expressed as the sum of four integer squares. We investigate the analogous
question over Quaternion rings, focusing on squares of elements of Quaternion
rings with integer coefficients. We determine the minimum necessary number of
squares for infinitely many Quaternion rings, and give global upper and lower
bounds.


  The Heisenberg-Kitaev (HK) model on various lattices have attracted a lot of
attention because they may lead to exotic states such as quantum spin liquid
and topological orders. The rare-earth-based kagome lattice (KL) compounds
$\rm{Mg_2RE_3Sb_3O_{14}}$ $\rm{(RE=Gd, Er)}$ and $\rm{(RE=Nd)}$ have ${\bf
q=0}$, $120^\circ$ order and canted ferromagnetic (CFM) order, respectively.
Interestingly, the HK model on the KL has the same ground state long-range
orders. In the theoretical phase diagram, the CFM phase resides in a continuous
parameter region and there is no phase change across special parameter points,
such as the Kitaev ferromagnetic (KFM) point, the ferromagnetic (FM) point and
its dual FM point. However, a ground state property cannot distinguish a system
with or without topological nontrivial excitations and related phase
transitions. Here, we study the topological magnon excitations and related
thermal Hall conductivity in the HK model on the KL with CFM order. The CFM
phase can be divided into two regions related by the Klein duality, with the
self dual KFM point as their boundary. We find that the scalar spin chirality
which is intrinsic in the CFM order changes sign across the KFM point. This
leads to the opposite Chern numbers of corresponding magnon bands in the two
regions, and also the sign change of the magnon thermal Hall conductivity.


  We give topological characterizations of filters $F$ on $w$ such that the
Mathias forcing $M_F$ adds no dominating reals or preserves ground model
unbounded families. This allows us to answer some questions of Brendle,
Guzm\'an, Hru\v{s}\'ak, Mart\'{\i}nez, Minami, and Tsaban.


  Neutrinos emitted from near the surface of the hot proto-neutron star
produced by a supernova explosion may be subject to significant gravitational
redshift at late times. Electron antineutrinos decouple deeper in the
gravitational potential well of the neutron star than do the electron
neutrinos, so that the electron antineutrinos experience a larger redshift
effect than do the electron neutrinos. We show how this differential redshift
can increase the electron fraction Ye in the neutrino-heated ejecta from the
neutron star. Any r-process nucleosynthesis originating in the neutrino-heated
ejecta would require a low Ye, implying that the differential redshift effect
cannot be too large. In turn, this effect may allow nucleosynthesis to probe
the nuclear equation of state parameters which set the neutron star radius and
surface density scale height at times of order tpb = 10 to 25 s after core
bounce.


  We demonstrate the existence of photon traps within the framework of
nonlinear electrodynamics. The trapping mechanism is based on the fact that,
for null background fields, the optical metric reduces to the Kerr-Schild form,
which plays a prominent role in the context of black hole physics. We then
construct explicit examples where photons are confined in a region of
spacetime, such that a distant observer cannot interact with them. Finally, we
argue that the trapping scheme is quite universal, being entirely compatible
with causality, energy conditions, and hyperbolicity.


  We suggest a quantum cryptographic scheme using continuous EPR-like
correlations of bright optical beams. For binary key encoding, the continuous
information is discretized in a novel way by associating a respective
measurement, amplitude or phase, with a bit value "1" or "0". The secure key
distribution is guaranteed by the quantum correlations. No pre-determined
information is sent through the quantum channel contributing to the security of
the system.


  Algorithmic solutions for multi-object tracking (MOT) are a key enabler for
applications in autonomous navigation and applied ocean sciences.
State-of-the-art MOT methods fully rely on a statistical model and typically
use preprocessed sensor data as measurements. In particular, measurements are
produced by a detector that extracts potential object locations from the raw
sensor data collected for a discrete time step. This preparatory processing
step reduces data flow and computational complexity but may result in a loss of
information. State-of-the-art Bayesian MOT methods that are based on belief
propagation (BP) systematically exploit graph structures of the statistical
model to reduce computational complexity and improve scalability. However, as a
fully model-based approach, BP can only provide suboptimal estimates when there
is a mismatch between the statistical model and the true data-generating
process. Existing BP-based MOT methods can further only make use of
preprocessed measurements. In this paper, we introduce a variant of BP that
combines model-based with data-driven MOT. The proposed neural enhanced belief
propagation (NEBP) method complements the statistical model of BP by
information learned from raw sensor data. This approach conjectures that the
learned information can reduce model mismatch and thus improve data association
and false alarm rejection. Our NEBP method improves tracking performance
compared to model-based methods. At the same time, it inherits the advantages
of BP-based MOT, i.e., it scales only quadratically in the number of objects,
and it can thus generate and maintain a large number of object tracks. We
evaluate the performance of our NEBP approach for MOT on the nuScenes
autonomous driving dataset and demonstrate that it has state-of-the-art
performance.


  We present a first proof-of-concept use-case that demonstrates the efficiency
of interfacing the algorithm framework ParadisEO with the automated algorithm
configuration tool irace and the experimental platform IOHprofiler. By combing
these three tools, we obtain a powerful benchmarking environment that allows us
to systematically analyze large classes of algorithms on complex benchmark
problems. Key advantages of our pipeline are fast evaluation times, the
possibility to generate rich data sets to support the analysis of the
algorithms, and a standardized interface that can be used to benchmark very
broad classes of sampling-based optimization heuristics.
  In addition to enabling systematic algorithm configuration studies, our
approach paves a way for assessing the contribution of new ideas in interplay
with already existing operators -- a promising avenue for our research domain,
which at present may have a too strong focus on comparing entire algorithm
instances.


  Superpixels are widely used in computer vision applications. Nevertheless,
decomposition methods may still fail to efficiently cluster image pixels
according to their local texture. In this paper, we propose a new Nearest
Neighbor-based Superpixel Clustering (NNSC) method to generate texture-aware
superpixels in a limited computational time compared to previous approaches. We
introduce a new clustering framework using patch-based nearest neighbor
matching, while most existing methods are based on a pixel-wise K-means
clustering. Therefore, we directly group pixels in the patch space enabling to
capture texture information. We demonstrate the efficiency of our method with
favorable comparison in terms of segmentation performances on both standard
color and texture datasets. We also show the computational efficiency of NNSC
compared to recent texture-aware superpixel methods.


  Tantalum arsenide is a member of the non-centrosymmetric monopnictides, which
are putative Weyl semimetals. In these materials, three-dimensional chiral
massless quasiparticles, the so-called Weyl fermions, are predicted to induce
novel quantum mechanical phenomena, such as the chiral anomaly and topological
surface states. However, their chirality is only well-defined if the Fermi
level is close enough to the Weyl points that separate Fermi surface pockets of
opposite chirality exist. In this article, we present the bulk Fermi surface
topology of high quality single crystals of TaAs, as determined by
angle-dependent Shubnikov-de Haas and de Haas-van Alphen measurements combined
with ab-initio band-structure calculations. Quantum oscillations originating
from three different types of Fermi surface pocket were found in magnetization,
magnetic torque, and mag- netoresistance measurements performed in magnetic
fields up to 14 T and temperatures down to 1.8 K. Of these Fermi pockets, two
are pairs of topologically non-trivial electron pockets around the Weyl points
and one is a trivial hole pocket. Unlike the other members of the
non-centrosymmetric monopnictides, TaAs is the first Weyl semimetal candidate
with the Fermi energy suffciently close to both types of Weyl points to
generate chiral quasiparticles at the Fermi surface.


  Partite, $3$-uniform hypergraphs are $3$-uniform hypergraphs in which each
hyperedge contains exactly one point from each of the $3$ disjoint vertex
classes. We consider the degree sequence problem of partite, $3$-uniform
hypergraphs, that is, to decide if such a hypergraph with prescribed degree
sequences exists. We prove that this decision problem is NP-complete in
general, and give a polynomial running time algorithm for third almost-regular
degree sequences, that is, when each degree in one of the vertex classes is $k$
or $k-1$ for some fixed $k$, and there is no restriction for the other two
vertex classes. We also consider the sampling problem, that is, to uniformly
sample partite, $3$-uniform hypergraphs with prescribed degree sequences. We
propose a Parallel Tempering method, where the hypothetical energy of the
hypergraphs measures the deviation from the prescribed degree sequence. The
method has been implemented and tested on synthetic and real data. It can also
be applied for $\chi^2$ testing of contingency tables. We have shown that this
hypergraph-based $\chi^2$ test is more sensitive than the standard $\chi^2$
test. The extra sensitivity is especially advantageous on small data sets,
where the proposed Parallel Tempering method shows promising performance.


  The magneto-electrostatic tailoring of the supercurrent in quantum point
contact ballistic Josephson junctions is demonstrated. An etched InAs-based
heterostructure is laterally contacted to superconducting niobium leads and the
existence of two etched side gates permits, in combination with the application
of a perpendicular magnetic field, to modify continuously the magnetic
interference pattern by depleting the weak link. For wider junctions the
supercurrent presents a Fraunhofer-like interference pattern with periodicity
h/2e whereas by shrinking electrostatically the weak link, the periodicity
evolves continuously to a monotonic decay. These devices represent novel
tunable structures that might lead to the study of the elusive Majorana
fermions.


  Geometrical applications of the non-compact form of Cartan's exceptional Lie
group G(2) is considered. This group generates specific rotations of
7-dimensional Minkowski-like space with three extra time-like coordinates and
in some limiting cases imitates standard Poincare transformations. In this
model space-time translations are non-commutative and are represented by the
rotations towards the extra time-like coordinates. The second order Casimir
element of non-compact G(2) and its expression by the Casimir operators of the
Lorentz and Poincare groups are found.


  We show that despite the inherent non-locality of quantum field theories on
the Groenewold-Moyal (GM) plane, one can find a class of ${\bf C}$, ${\bf P}$,
${\bf T}$ and ${\bf CPT}$ invariant theories. In particular, these are theories
without gauge fields or with just gauge fields and no matter fields. We also
show that in the presence of gauge fields, one can have a field theory where
the Hamiltonian is ${\bf C}$ and ${\bf T}$ invariant while the $S$-matrix
violates ${\bf P}$ and ${\bf CPT}$.
  In non-abelian gauge theories with matter fields such as the electro-weak and
$QCD$ sectors of the standard model of particle physics, ${\bf C}$, ${\bf P}$,
${\bf T}$ and the product of any pair of them are broken while ${\bf CPT}$
remains intact for the case $\theta^{0i} =0$. (Here $x^{\mu} \star x^{\nu} -
x^{\nu} \star x^{\mu} = i \theta^{\mu \nu}$, $x^{\mu}$: coordinate functions,
$\theta^{\mu \nu} = -\theta^{\nu \mu}=$ constant.) When $\theta^{0i} \neq 0$,
it contributes to breaking also ${\bf P}$ and ${\bf CPT}$. It is known that the
$S$-matrix in a non-abelian theory depends on $\theta^{\mu \nu}$ only through
$\theta^{0i}$. The $S$-matrix is frame dependent. It breaks (the identity
component of the) Lorentz group. All the noncommutative effects vanish if the
scattering takes place in the center-of-mass frame, or any frame where
$\theta^{0i}P^{\textrm{in}}_{i} = 0$, but not otherwise. ${\bf P}$ and ${\bf
CPT}$ are good symmetries of the theory in this special case.


  Precision frequency and phase synchronization between distinct fiber
interconnected nodes is critical for a wide range of applications, including
atomic timekeeping, quantum networking, database synchronization,
ultra-high-capacity coherent optical communications and hyper-scale data
centers. Today, many of these applications utilize precision, tabletop laser
systems, and would benefit from integration in terms of reduced size, power,
cost, and reliability. In this paper we report a record low 3x10^-4 rad^2
residual phase error variance for synchronization based on independent,
spectrally pure, ultra-high mutual coherence, photonic integrated lasers. This
performance is achieved with stimulated Brillouin scattering lasers that are
stabilized to independent microcavity references, realizing sources with 30 Hz
integral linewidth and a fractional frequency instability less than or equal to
2x10^-13 at 50 ms. This level of low phase noise and carrier stability enables
a new type of optical-frequency-stabilized phase-locked loop (OFS-PLL) that
operates with a less than 800 kHz loop bandwidth, eliminating traditional power
consuming high bandwidth electronics and digital signal processors used to
phase lock optical carriers. Additionally, we measure the residual phase error
down to a received carrier power of -34 dBm, removing the need to transmit
in-band or out-of-band synchronized carriers. These results highlight the
promise for a path to spectrally pure, ultra-stable, integrated lasers for
network synchronization, precision time distribution protocols, quantum-clock
networks, and multiple-Terabit per second coherent DSP-free fiber-optic
interconnects.


  Color confinement is only a supposition, which has not been proved in QCD
yet. It is proposed here that macroscopic quark gluon plasma in astrophysics
could hardly maintain colorless because of causality. The authors expected that
the existence of chromatic strange quark stars as well as chromatic strangelets
preserved from the QCD phase transition in the early universe could be
unavoidable if their colorless correspondents do exist.


  Thanks to the successful performance of the James Webb Space Telescope, our
understanding of the epoch of reionization of the Universe has been advanced.
The ultraviolet luminosity functions (UV LFs) of galaxies span a wide range of
redshift, not only revealing the connection between galaxies and dark matter
(DM) halos but also providing the information during reionization. In this
work, we develop a model connecting galaxy counts and apparent magnitude based
on UV LFs, which incorporates redshift-dependent star formation efficiency
(SFE) and corrections for dust attenuation. By synthesizing some observations
across the redshift range $4\le z \le 10$ from various galaxy surveys, we
discern the evolving SFE with increasing redshift and DM halo mass through
model fitting. Subsequent analyses indicate that the Thomson scattering optical
depth was $\tau_{\rm e} = 0.052^{+0.003}_{-0.002}$ and the epoch of
reionization started (ended) at $z=20.58^{+6.25}_{-6.75}$
($z=5.38^{+0.65}_{-0.70}$) which is insensitive to the choice of the truncated
magnitude of the UV LFs. Incorporating additional dataset and some reasonable
constraints, the amplitude of matter perturbation is found to be
$\sigma_8=0.79\pm0.05$, which is consistent with the standard $\Lambda$CDM
model. Future galaxy surveys and the dynamical simulations of galaxy evolution
will break the degeneracy between SFE and cosmological parameters, improving
the accuracy and the precision of the UV LF model further.


  In expansion of our recent proposal (Physics, 2020, 2, 213-276) that the
solar system's evolution occurred in two stages -- during the first stage, the
gaseous giants formed (via disk instability), and, during the second stage
(caused by an encounter with a particular stellar-object leading to "in-system"
fission-driven nucleogenesis), the terrestrial planets formed (via accretion)
-- we emphasize here that the mechanism of formation of such stellar-objects is
generally universal and therefore encounters of such objects with
stellar-systems may have occurred elsewhere across galaxies. If so, their
aftereffects may perhaps be observed as puzzling features in the spectra of
individual stars (such as idiosyncratic chemical enrichments) and/or in the
structures of exoplanetary systems (such as unusually high planet densities or
short orbital periods). This paper reviews and reinterprets astronomical data
within the "fission-events framework." Classification of stellar systems as
"pristine" or "impacted" is offered.


  Current gaze input methods for VR headsets predominantly utilize the gaze ray
as a pointing cursor, often neglecting depth information in it. This study
introduces FocusFlow, a novel gaze interaction technique that integrates focal
depth into gaze input dimensions, facilitating users to actively shift their
focus along the depth dimension for interaction. A detection algorithm to
identify the user's focal depth is developed. Based on this, a layer-based UI
is proposed, which uses focal depth changes to enable layer switch operations,
offering an intuitive hands-free selection method. We also designed visual cues
to guide users to adjust focal depth accurately and get familiar with the
interaction process. Preliminary evaluations demonstrate the system's
usability, and several potential applications are discussed. Through FocusFlow,
we aim to enrich the input dimensions of gaze interaction, achieving more
intuitive and efficient human-computer interactions on headset devices.


  We study the renormalization group(RG) evolution of four-quark operators that
contribute to the top pair production. In particular, we focus on the cases in
which certain observables are \emph{first} induced from the one-loop RG while
being absent at tree-level. From the operator mixing pattern, we classify all
such RG-induced phenomena and underlying models that can induce them. We then
calculate the full one-loop QCD RG evolution as the leading estimator of the
effects and address the question of which RG-induced phenomena have largest and
observable effects. The answer is related to the color structure of QCD. The
studied topics include the RG-induction of top asymmetries, polarizations and
polarization mixings as well as issues arising at this order. The RG-induction
of top asymmetries is further compared with the generation of asymmetries from
QCD and QED at one-loop order. We finally discuss the validity of using the RG
as the proxy of one-loop effects on the top pair production. As an aside, we
clarify the often-studied relations between top pair observables.


  The analysis of projection-free first order methods is often complicated by
the presence of different kinds of "good" and "bad" steps. In this article, we
propose a unifying framework for projection-free methods, aiming to simplify
the converge analysis by getting rid of such a distinction between steps. The
main tool employed in our framework is the Short Step Chain (SSC) procedure,
which skips gradient computations in consecutive short steps until proper
stopping conditions are satisfied. This technique allows us to give a unified
analysis and converge rates in the general smooth non convex setting, as well
as convergence rates under a Kurdyka-Lojasiewicz (KL) property, a setting that,
to our knowledge, has not been analyzed before for the projection-free methods
under study. In this context, we prove local convergence rates comparable to
those of projected gradient methods under the same conditions. Our analysis
relies on a sufficient slope condition, ensuring that the directions selected
by the methods have the steepest slope possible up to a constant among feasible
directions. This condition is satisfied, among others, by several Frank-Wolfe
(FW) variants on polytopes, and by some projection-free methods on convex sets
with smooth boundary.


  We show the results of our analysis of the pulse broadening phenomenon in 25
pulsars at several frequencies using the data gathered with GMRT and Effelsberg
radiotelescopes. Twenty two of these pulsars were not studied in that regard
before and our work has increased the total number of pulsars with
multi-frequency scattering measurements to almost 50, basically doubling the
amount available so far. The majority of the pulsars we observed have high to
very-high dispersion measures (DM>200) and our results confirm the suggestion
of Loehmer et al.(2001, 2004) that the scatter time spectral indices for
high-DM pulsars deviate from the value predicted by a single thin screen model
with Kolmogorov's distribution of the density fluctuations. In this paper we
discuss the possible explanations for such deviations.


  We prove anomalous-diffusion scaling for a one-dimensional stochastic kinetic
dynamics, in which the stochastic drift is driven by an exogenous Bessel noise,
and also includes endogenous volatility which is permitted to have arbitrary
dependence with the exogenous noise. We identify the superdiffusive scaling
exponent for the model, and prove a weak convergence result on the
corresponding scale. We show how our result extends to admit, as exogenous
noise processes, not only Bessel processes but more general processes
satisfying certain asymptotic conditions.


  Inspired by the recent discovery of a doubly charmed tetraquark state
$T_{cc}^+$ by the LHCb Collaboration, we employ the effective Lagrangian
approach to investigate the decay width of $T_{cc}^{+}\to D^{+}
D^{0}\pi^{0}/D^{0} D^{0}\pi^{+}$ and $T_{cc}^{+}\to D^{0}D^{+}\gamma$ with the
assumption that $T_{cc}^{+}$ is an isoscalar $DD^{\ast}$ molecule. We show that
both the $T_{cc}\to D D\pi$ and $T_{cc}\to DD\gamma$ modes contribute to the
decay width of $T_{cc}$, with the former being dominant. The resulting total
decay width of about $\Gamma=63$ keV is smaller than the experimental decay
width obtained from the Breit-Wigner fit of the LHCb data, $\Gamma=410\pm
165\pm 43^{+18}_{-38}$ keV, while close to the number obtained from the
alternative unitary analysis, $\Gamma=48\pm 2^{+0}_{-14}$ keV, which supports
the molecular nature of $T_{cc}$.


  We present low resolution Spitzer-IRS spectra of 40 ETGs, selected from a
sample of 65 ETGs showing emission lines in their optical spectra. We
homogeneously extract the mid-infrared (MIR) spectra, and after the proper
subtraction of a "passive" ETG template, we derive the intensity of the ionic
and molecular lines and of the polycyclic aromatic hydrocarbon emission
features. We use MIR diagnostic diagrams to investigate the powering mechanisms
of the ionized gas. The mid-infrared spectra of early-type galaxies show a
variety of spectral characteristics. We empirically sub-divide the sample into
five classes of spectra with common characteristics. Class-0, accounting for
20% of the sample, are purely passive ETGs with neither emission lines nor PAH
features. Class-1 show emission lines but no PAH features, and account for
17.5% of the sample. Class-2, in which 50% of the ETGs are found, as well as
having emission lines, show PAH features with unusual ratios, e.g. 7.7
{\mu}m/11.3 {\mu}m \leq 2.3. Class-3 objects have emission lines and PAH
features with ratios typical of star-forming galaxies. 7.5% of objects fall in
this class, likely to be objects in a starburst/post-starburst regime. Class-4,
containing only 5% of the ETGs, is dominated by a hot dust continuum. The
diagnostic diagram [Ne III]15.55{\mu}m/[Ne II]12.8{\mu}m vs. [S
III]33.48{\mu}m/[Si II]34.82{\mu}m, is used to investigate the different
mechanisms ionizing the gas. If we exclude NGC 3258 where a starburst seems
present, most of our ETGs contain gas ionized via either AGN-like or shock
phenomena, or both. Most of the spectra in the present sample are classified as
LINERs in the optical window. The proposed MIR spectral classes show
unambiguously the manifold of the physical processes and ionization mechanisms,
from star formation, low level AGN activity, to shocks, present in LINER
nuclei.


  The dynamic cavity method provides the most efficient way to evaluate
probabilities of dynamic trajectories in systems of stochastic units with
unidirectional sparse interactions. It is closely related to sum-product
algorithms widely used to compute marginal functions from complicated global
functions of many variables, with applications in disordered systems,
combinatorial optimization and computer science. However, the complexity of the
cavity approach grows exponentially with the in-degrees of the interacting
units, which creates a de-facto barrier for the successful analysis of systems
with fat-tailed in-degree distributions. In this manuscript, we present a
dynamic programming algorithm that overcomes this barrier by reducing the
computational complexity in the in-degrees from exponential to quadratic,
whenever couplings are chosen randomly from (or can be approximated in terms
of) discrete, possibly unit-dependent, sets of equidistant values. As a case
study, we analyse the dynamics of a random Boolean network with a fat-tailed
degree distribution and fully asymmetric binary $\pm J$ couplings, and we use
the power of the algorithm to unlock the noise dependent heterogeneity of
stationary node activation patterns in such a system.


  This document contains all proofs omitted from our working paper 'Screening
for breakthroughs'; specifically, the February 2024 version of the paper
(arXiv:2011.10090v8).


  The ability to accurately transfer quantum information through networks is an
important primitive in distributed quantum systems. While perfect quantum state
transfer (PST) can be effected by a single particle undergoing continuous-time
quantum walks on a variety of graphs, it is not known if PST persists for many
particles in the presence of interactions. We show that if single-particle PST
occurs on one-dimensional weighted path graphs, then systems of hard-core
bosons undergoing quantum walks on these paths also undergo PST. The analysis
extends the Tonks-Girardeau ansatz to weighted graphs using techniques in
algebraic graph theory. The results suggest that hard-core bosons do not
generically undergo PST, even on graphs which exhibit single-particle PST.


  The aim of this paper is to study growth properties of group extensions of
hyperbolic dynamical systems, where we do not assume that the extension
satisfies the symmetry conditions seen, for example, in the work of Stadlbauer
on symmetric group extensions and of the authors on geodesic flows. Our main
application is to growth rates of periodic orbits for covers of an Anosov flow:
we reduce the problem of counting periodic orbits in an amenable cover $X$ to
counting in a maximal abelian subcover $X^{\mathrm{ab}}$. In this way, we
obtain an equivalence for the Gurevi\v{c} entropy: $h(X)=h(X^{\mathrm{ab}})$ if
and only if the covering group is amenable. In addition, when we project the
periodic orbits for amenable covers $X$ to the compact factor $M$, they
equidistribute with respect to a natural equilibrium measure -- in the case of
the geodesic flow, the measure of maximal entropy.


  Diverse and realistic traffic scenarios are crucial for evaluating the AI
safety of autonomous driving systems in simulation. This work introduces a
data-driven method called TrafficGen for traffic scenario generation. It learns
from the fragmented human driving data collected in the real world and then can
generate realistic traffic scenarios. TrafficGen is an autoregressive
generative model with an encoder-decoder architecture. In each autoregressive
iteration, it first encodes the current traffic context with the attention
mechanism and then decodes a vehicle's initial state followed by generating its
long trajectory. We evaluate the trained model in terms of vehicle placement
and trajectories and show substantial improvements over baselines. TrafficGen
can be also used to augment existing traffic scenarios, by adding new vehicles
and extending the fragmented trajectories. We further demonstrate that
importing the generated scenarios into a simulator as interactive training
environments improves the performance and the safety of driving policy learned
from reinforcement learning. More project resource is available at
https://metadriverse.github.io/trafficgen


  In the framework of augmented superfield approach, we provide the geometrical
origin and interpretation for the nilpotent (anti-)BRST charges, (anti-)co-BRST
charges and a non-nilpotent bosonic charge. Together, these local and conserved
charges turn out to be responsible for a clear and cogent definition of the
Hodge decomposition theorem in the quantum Hilbert space of states. The above
charges owe their origin to the de Rham cohomological operators of differential
geometry which are found to be at the heart of some of the key concepts
associated with the interacting gauge theories. For our present review, we
choose the two $(1 + 1)$-dimensional (2D) quantum electrodynamics (QED) as a
prototype field theoretical model to derive all the nilpotent symmetries for
all the fields present in this interacting gauge theory in the framework of
augmented superfield formulation and show that this theory is a {\it unique}
example of an interacting gauge theory which provides a tractable field
theoretical model for the Hodge theory.


  This paper presents an analytical approach to explore the damping effect of
inner loops on grid-forming converters. First, an impedance model is proposed
to characterize the behaviors of inner loops, thereby illustrating their
influence on output impedance shaping. Then, based on the impedance
representation, the complex torque coefficient method is employed to assess the
contribution of inner loops to system damping. The interactions among inner
loops, outer loops, and the ac grid are analyzed. It reveals that inner loops
shape the electrical damping torque coefficient and consequently influence both
synchronous and sub-synchronous oscillation modes. The virtual admittance and
current control-based inner-loop scheme is employed to illustrate the proposed
analytical approach. The case study comprises the analysis of impedance
profiles, the analysis of damping torque contributed by inner loops under
various grid strengths, and the comparison between dq-frame and
{\alpha}\b{eta}-frame realizations of inner loops. Finally, simulation and
experimental tests collaborate with theoretical approaches and findings.


  We introduce A-ranked preferential structures and combine them with an
accessibility relation. This framework allows us to formalize contrary to duty
obligations. Representation results are proved.


  In the present paper we continue the project of systematic construction of
invariant differential operators on the example of the non-compact algebra
$G_{2(2)}$ which is split real form of $G_2$. We give the classification of
reducible Verma modules $G_2$. We give also the singular vectors between these
modules, thus setting the stage for construction of the invariant differential
operators over $G_{2(2)}$.


  This paper describes the cascaded multimodal speech translation systems
developed by Imperial College London for the IWSLT 2019 evaluation campaign.
The architecture consists of an automatic speech recognition (ASR) system
followed by a Transformer-based multimodal machine translation (MMT) system.
While the ASR component is identical across the experiments, the MMT model
varies in terms of the way of integrating the visual context (simple
conditioning vs. attention), the type of visual features exploited (pooled,
convolutional, action categories) and the underlying architecture. For the
latter, we explore both the canonical transformer and its deliberation version
with additive and cascade variants which differ in how they integrate the
textual attention. Upon conducting extensive experiments, we found that (i) the
explored visual integration schemes often harm the translation performance for
the transformer and additive deliberation, but considerably improve the cascade
deliberation; (ii) the transformer and cascade deliberation integrate the
visual modality better than the additive deliberation, as shown by the
incongruence analysis.


  The art gallery problem enquires about the least number of guards sufficient
to ensure that an art gallery, represented by a simple polygon $P$, is fully
guarded. Most standard versions of this problem are known to be NP-hard. In
1987, Ghosh provided a deterministic $\mathcal{O}(\log n)$-approximation
algorithm for the case of vertex guards and edge guards in simple polygons. In
the same paper, Ghosh also conjectured the existence of constant ratio
approximation algorithms for these problems. We present here three
polynomial-time algorithms with a constant approximation ratio for guarding an
$n$-sided simple polygon $P$ using vertex guards. (i) The first algorithm, that
has an approximation ratio of 18, guards all vertices of $P$ in
$\mathcal{O}(n^4)$ time. (ii) The second algorithm, that has the same
approximation ratio of 18, guards the entire boundary of $P$ in
$\mathcal{O}(n^5)$ time. (iii) The third algorithm, that has an approximation
ratio of 27, guards all interior and boundary points of $P$ in
$\mathcal{O}(n^5)$ time. Further, these algorithms can be modified to obtain
similar approximation ratios while using edge guards. The significance of our
results lies in the fact that these results settle the conjecture by Ghosh
regarding the existence of constant-factor approximation algorithms for this
problem, which has been open since 1987 despite several attempts by
researchers. Our approximation algorithms exploit several deep visibility
structures of simple polygons which are interesting in their own right.


  Object functionality is often expressed through part articulation -- as when
the two rigid parts of a scissor pivot against each other to perform the
cutting function. Such articulations are often similar across objects within
the same functional category. In this paper, we explore how the observation of
different articulation states provides evidence for part structure and motion
of 3D objects. Our method takes as input a pair of unsegmented shapes
representing two different articulation states of two functionally related
objects, and induces their common parts along with their underlying rigid
motion. This is a challenging setting, as we assume no prior shape structure,
no prior shape category information, no consistent shape orientation, the
articulation states may belong to objects of different geometry, plus we allow
inputs to be noisy and partial scans, or point clouds lifted from RGB images.
Our method learns a neural network architecture with three modules that
respectively propose correspondences, estimate 3D deformation flows, and
perform segmentation. To achieve optimal performance, our architecture
alternates between correspondence, deformation flow, and segmentation
prediction iteratively in an ICP-like fashion. Our results demonstrate that our
method significantly outperforms state-of-the-art techniques in the task of
discovering articulated parts of objects. In addition, our part induction is
object-class agnostic and successfully generalizes to new and unseen objects.


  We analyze 45 spectropolarimetric observations of the eclipsing, interacting
binary star V356 Sgr, obtained over a period of 21 years, to characterize the
geometry of the system's circumstellar material. After removing interstellar
polarization from these data, we find the system exhibits a large intrinsic
polarization signature arising from electron scattering. In addition, the lack
of repeatable eclipses in the polarization phase curves indicates the presence
of a substantial pool of scatterers not occulted by either star. We suggest
that these scatterers form either a circumbinary disk coplanar with the
gainer's accretion disk or an elongated structure perpendicular to the orbital
plane of V356 Sgr, possibly formed by bipolar outflows. We also observe
small-scale, cycle-to-cycle variations in the magnitude of intrinsic
polarization at individual phases, which we interpret as evidence of
variability in the amount of scattering material present within and around the
system. This may indicate a mass transfer or mass loss rate that varies on the
time-scale of the system's orbital period. Finally, we compare the basic
polarimetric properties of V356 Sgr with those of the well studied beta Lyr
system; the significant differences observed between the two systems suggests
diversity in the basic circumstellar geometry of Roche-lobe overflow systems


  Crucial in the performance of microservice applications is the efficient
handling of RPC calls. We found that the asynchronous call implementation in a
popular microservice benchmark suite, DeathStarBench, causes a bottleneck in
thread management, reducing the peak throughput and increasing latency at high
request rates. Replacing the threaded implementation with a fiber
implementation increases peak throughput by up to 6x, meaning that the service
can operate at a higher request rate without significantly increasing response
latency.


  Network analysis has a crucial need for tools to compare networks and assess
the significance of differences between networks. We propose a principled
statistical approach to network comparison that approximates networks as
probability distributions on negatively curved manifolds. We outline the
theory, as well as implement the approach on simulated networks.


  Non-orthogonal communications play an important role in future communication
architectures. In such scenarios, the received signal is corrupted by an
interfering signal which is typically cyclostationary in continuous-time. If
the period of interference is synchronized with the sampling period, the
sampled interference is a discrete-time (DT) cyclostationary process. However,
in the common interference scenario, the period of the interference is not
necessarily synchronized with the sampling period. In such cases, the DT
interference is an almost cyclostationary process. In this work we characterize
the capacity of channels in which the noise arises from a sampled
cyclostationary Gaussian process. For the case of synchronous sampling,
capacity can be obtained in closed form. When sampling is not synchronized with
the symbol rate of the interference, the resulting channel is not information
stable, thus classic tools are not applicable. Using information spectrum
methods, we prove that capacity can be obtained as the limit of a sequence of
capacities of channels with cyclostationary noise. Our results characterize the
effects of changes in the sampling rate and sampling time offset on the
capacity of the resulting DT channel. In particular, we demonstrate that minor
variations in the sampling period can substantially affect capacity.


  Inclusive charm and beauty cross sections are measured in e-p and e+p neutral
current collisions at HERA in the kinematic region of photon virtuality
5<Q^2<2000 GeV^2 and Bjorken scaling variable 0.0002<x<0.05. The data were
collected with the H1 detector in the years 2006 and 2007 corresponding to an
integrated luminosity of 189 pb^-1. The numbers of charm and beauty events are
determined using variables reconstructed by the H1 vertex detector including
the impact parameter of tracks to the primary vertex and the position of the
secondary vertex. The measurements are combined with previous data and compared
to QCD predictions.


  The counterfactuality of the recently proposed protocols for direct quantum
communication is analyzed. It is argued that the protocols can be
counterfactual only for one value of the transmitted bit. The protocols achieve
a reduced probability of detection of the particle in the transmission channel
by increasing the number of paths in the channel. However, this probability is
not lower than the probability of detecting a particle actually passing through
such a multi-path channel, which was found to be surprisingly small. The
relation between security and counterfactuality of the protocols is discussed.
An analysis of counterfactuality of the protocols in the framework of the
Bohmian interpretation is performed.


  Technological advancements allow biometric applications to be more
omnipresent than in any other time before. This paper argues that in the
current EU data protection regulation, classification applications using
biometric data receive less protection compared to biometric recognition. We
analyse preconditions in the regulatory language and explore how this has the
potential to be the source of unique privacy risks for processing operations
classifying individuals based on soft traits like emotions. This can have high
impact on personal freedoms and human rights and therefore, should be subject
to data protection impact assessment.


  Background: Spin-triplet ($S=1$) proton-neutron (pn) pairing in nuclei has
been under debate. It is well known that the dynamical pairing affects the
nuclear matrix element of the Gamow-Teller (GT) transition and the double beta
decay. Purpose: We investigate the effect of the pn-pair interaction in the
$T=0, S=1$ channel on the low-lying spin-dipole (SD) transition. We then aim at
clarifying the distinction of the role in between the SD and GT transitions.
Method: We perform a three-body model calculation for the transition
${}^{80}\mathrm{Ni}\to{}^{80}\mathrm{Cu}$, where ${}^{78}\mathrm{Ni}$ is taken
as a core. The strength of the pair interaction is varied to see the effect on
the SD transition-strength distribution. To fortify the finding obtained by the
three-body model, we employ the nuclear energy-density functional method for
the SD transitions in several nuclei, where one can expect a strong effect.
Results: The effect of the $S=1$ pn-pair interaction depends on the spatial
overlap of the pn pair and the angular momentum of the valence nucleons; the
higher the angular momentum of the orbitals, the more significant the effect.
Conclusions: The dynamical $S=1$ pairing is effective even for SD states
although the spatial overlap of the pn pair can be smaller than GT states. The
SD transition involving high-$\ell$ orbitals with the same principal quantum
number is strongly affected by the dynamical $S=1$ pairing.


  We study the intersection theory of complex Lagrangian subvarieties inside
holomorphic symplectic manifolds. In particular, we study their behaviour under
Mukai flops and give a rigorous proof of the Pl\"ucker type formula for
Legendre dual subvarieties written down by the second author before. Then we
apply the formula to study projective dual varieties in projective spaces.


  Correlations of a Bose gas released from an optical lattice are measured
using superradiant scattering. Conditions are chosen so that after initial
incident light pumping at the Bragg angle for diffraction, due to matter wave
amplification and mode competition, superradiant scattering into the Bragg
diffracted mode is preponderant. A temporal analysis of the superradiant
scattering gain reveals periodical oscillations and damping due to the initial
lack of coherence between lattice sites. Such damping is used for
characterizing first order spatial correlations in our system with a precision
of one lattice period.


  Active learning aims to improve the performance of task model by selecting
the most informative samples with a limited budget. Unlike most recent works
that focused on applying active learning for image classification, we propose
an effective Consistency-based Active Learning method for object Detection
(CALD), which fully explores the consistency between original and augmented
data. CALD has three appealing benefits. (i) CALD is systematically designed by
investigating the weaknesses of existing active learning methods, which do not
take the unique challenges of object detection into account. (ii) CALD unifies
box regression and classification with a single metric, which is not concerned
by active learning methods for classification. CALD also focuses on the most
informative local region rather than the whole image, which is beneficial for
object detection. (iii) CALD not only gauges individual information for sample
selection, but also leverages mutual information to encourage a balanced data
distribution. Extensive experiments show that CALD significantly outperforms
existing state-of-the-art task-agnostic and detection-specific active learning
methods on general object detection datasets. Based on the Faster R-CNN
detector, CALD consistently surpasses the baseline method (random selection) by
2.9/2.8/0.8 mAP on average on PASCAL VOC 2007, PASCAL VOC 2012, and MS COCO.
Code is available at \url{https://github.com/we1pingyu/CALD}


  Targeting specific technological applications requires the control of
nanoparticle properties, especially the crystalline polymorph. Freezing a
nanodroplet deposited on a solid substrate leads to the formation of
crystalline structures. We study the inherent mechanisms underlying this
general phenomenon by means of molecular dynamics simulations. Our work shows
that different crystal structures can be selected by finely tuning the solid
substrate lattice parameter. Indeed, while for our system, face-centered cubic
is usually the most preponderant structure, the growth of two distinct
polymorphs, hexagonal centered packing and body-centered cubic, was also
observed even when the solid substrate was face-centered cubic. Finally, we
also demonstrated that the growth of hexagonal centered packing is conditioned
by the appearance of large enough body-centered cubic clusters thus suggesting
the presence of a cross-nucleation pathway. Our results provide insights into
the impact of nanoscale effects and solid substrate properties towards the
growth of polymorphic nanomaterials.


  We study dilute aqueous solutions of charged disk-like mineral particles
(Laponite) by a combination of static light scattering (SLS) and small-angle
x-ray scattering (SAXS). Laponite solutions are known to form gels above a
certain critical concentration that must be described as non-equilibrium
states. Here we focus on the investigation by SLS and SAXS at concentrations
below gelation (c < 0.016 g/L) and at low concentrations of added salt (0.001
and 0.005 mM). Thus, we have obtained the scattering function of single
Laponite platelets as well as the structure factor describing their interaction
at finite concentration. A detailed analysis of the combined sets of data
proves that the solutions are in a well-defined equilibrium state. Moreover,
this analysis demonstrates the internal consistency and accuracy of the
scattering functions obtained at finite concentrations. We find that Laponite
particles interact through an effective pair potential that is attractive on
short range but repulsive on longer range. This finding demonstrates that
Laponite solutions exhibit only a limited stability at the concentration of
added salt used herein. Raising the ionic strength to 0.005 mM already leads to
slow flocculation as is evidenced from the enhanced scattering intensity at
smallest scattering angles. All data strongly suggest that the gelation
occurring at higher concentration is related to aggregation.


  We report the discovery of a new Kepler first-overtone RR Lyrae pulsator, KIC
2831097. The pulsation shows large, 0.1 d amplitude, systematic phase
variations that can be interpreted as light travel-time effect caused by
orbital motion in a binary system, superimposed on a linear pulsation-period
decrease. The assumed eccentric (e=0.47) orbit with the period of approximately
2 yr is the shortest among the non-eclipsing RR Lyrae binary candidates. The
binary model gives a lowest estimate for the mass of the companion of 8.4
M_Sun, that places it among black hole candidates. Beside the first-overtone
pulsation, numerous additional non-radial pulsation frequencies were also
identified. We detected an ~47-d Blazhko-like irregular light-curve modulation.


  We propose two new outlier detection methods, for identifying and classifying
different types of outliers in (big) functional data sets. The proposed methods
are based on an existing method called Massive Unsupervised Outlier Detection
(MUOD). MUOD detects and classifies outliers by computing for each curve, three
indices, all based on the concept of linear regression and correlation, which
measure outlyingness in terms of shape, magnitude and amplitude, relative to
the other curves in the data. 'Semifast-MUOD', the first method, uses a sample
of the observations in computing the indices, while 'Fast-MUOD', the second
method, uses the point-wise or $L_1$ median in computing the indices. The
classical boxplot is used to separate the indices of the outliers from those of
the typical observations. Performance evaluation of the proposed methods using
simulated data show significant improvements compared to MUOD, both in outlier
detection and computational time. We show that Fast-MUOD is especially well
suited to handling big and dense functional datasets with very small
computational time compared to other methods. Further comparisons with some
recent outlier detection methods for functional data also show superior or
comparable outlier detection accuracy of the proposed methods. We apply the
proposed methods on weather, population growth, and video data.