  Two-dimensional transition metal dichalcogenides (TMDs) exist in two
polymorphs, referred to as $1T$ and $1H$, depending on the coordination sphere
of the transition metal atom. The broken octahedral and trigonal prismatic
symmetries lead to different crystal and ligand field splittings of the $d$
electron states, resulting in distinct electronic properties. In this work, we
quantify the crystal and ligand field parameters of two-dimensional TMDs using
a Wannier-function approach. We adopt the methodology proposed by Scaramucci et
al. [A. Scaramucci et al., J. Phys.: Condens. Matter 27, 175503 (2015)]. that
allows to separate various contributions to the ligand field by choosing
different manifolds in the construction of the Wannier functions. We discuss
the relevance of the crystal and ligand fields in determining the relative
stability of the two polymorphs as a function of the filling of the $d$-shell.
Based on the calculated parameters, we conclude that the ligand field, while
leading to a small stabilizing factor for the $1H$ polymorph in the $d^1$ and
$d^2$ TMDs, plays mostly an indirect role and that hybridization between
different $d$ orbitals is the dominant feature. We investigate trends across
the periodic table and interpret the variations of the calculated crystal and
ligand fields in terms of the change of charge-transfer energy, which allows
developing simple chemical intuition.


  Professor Graham Higman defined januarial as a special instance of map
constructed from embedding of a coset diagram for an action of $\Delta (2,\ell
,k)$, on finite sets yielding exactly two orbits of the product of the two
generators, having equal sizes. In this paper we determine a condition for the
existence of a januarial from $\Delta (2,\ell ,k),$ the quotients of Hecke
groups $H_{\Lambda _{\ell }},$ when acting on the projective lines over finite
fields $PL(F_{q})$. We develope a method to find all the januarials from Hecke
groups $H_{\Lambda _{\ell }}$, when the triangle group $\Delta (2,\ell ,k)$
acts on $PL(F_{q})$. We evelove a formula for calculating genus of coset
diagram depending on the fixed points. By using it, we determine genus of the
januarials.


  We summarize the status of art of the secular evolution of low mass X-ray
binaries (LMXBs) and take a close look at the orbital period distribution of
LMXBs and of binary millisecond pulsars (MSP), in the hypothesis that this
latter results from the LMXB evolution. The deficiency of systems below the
period gap, which in cataclysmic binaries occurs between ~ 2 and 3 hr, points
to a very different secular evolution of LMXBs with respect to their
counterparts containing a white dwarf compact object. The presence of several
ultrashort period LMXBs (some of which are also X-ray millisecond pulsars), the
important fraction of binary MSPs at periods between 0.1 and 1 day, the periods
(26 and 32hr) of two ``interacting'' MSPs in Globular Clusters are other pieces
of the puzzle in the period distribution. We consider the possible explanations
for these peculiarities, and point out that Grindlay's old proposal that all
(most of) LMXBs in the field were originally born in globular clusters must be
carefully reconsidered.


  Asteroid exploration has been attracting more attention in recent years.
Nevertheless, we have just visited tens of asteroids while we have discovered
more than one million bodies. As our current observation and knowledge should
be biased, it is essential to explore multiple asteroids directly to better
understand the remains of planetary building materials. One of the mission
design solutions is utilizing asteroid flyby cycler trajectories with multiple
Earth gravity assists. An asteroid flyby cycler trajectory design problem is a
subclass of global trajectory optimization problems with multiple flybys,
involving a trajectory optimization problem for a given flyby sequence and a
combinatorial optimization problem to decide the sequence of the flybys. As the
number of flyby bodies grows, the computation time of this optimization problem
expands maliciously. This paper presents a new method to design asteroid flyby
cycler trajectories utilizing a surrogate model constructed by deep neural
networks approximating trajectory optimization results. Since one of the
bottlenecks of machine learning approaches is the computation time to generate
massive trajectory databases, we propose an efficient database generation
strategy by introducing pseudo-asteroids satisfying the Karush-Kuhn-Tucker
conditions. The numerical result applied to JAXA's DESTINY+ mission shows that
the proposed method is practically applicable to space mission design and can
significantly reduce the computational time for searching asteroid flyby
sequences.


  Black hole (BH) binary mergers formed through dynamical interactions in dense
star clusters are believed to be one of the main sources of gravitational waves
for Advanced LIGO and Virgo. Here we present a fast numerical method for
simulating the evolution of star clusters with BHs, including a model for the
dynamical formation and merger of BH binaries. Our method is based on
H\'{e}non's principle of balanced evolution, according to which the flow of
energy within a cluster must be balanced by the energy production inside its
core. Because the heat production in the core is powered by the BHs, one can
then link the evolution of the cluster to the evolution of its BH population.
This allows us to construct evolutionary tracks of the cluster properties
including its BH population and its effect on the cluster and, at the same
time, determine the merger rate of BH binaries as well as their eccentricity
distributions. The model is publicly available and includes the effects of a BH
mass spectrum, mass-loss due to stellar evolution, the ejection of BHs due to
natal and dynamical kicks, and relativistic corrections during binary-single
encounters. We validate our method using direct $N$-body simulations, and find
it to be in excellent agreement with results from recent Monte Carlo models of
globular clusters. This establishes our new method as a robust tool for the
study of BH dynamics in star clusters and the modelling of gravitational wave
sources produced in these systems. Finally, we compute the rate and
eccentricity distributions of merging BH binaries for a wide range of cluster
initial conditions, spanning more than two orders of magnitude in mass and
radius.


  Deep learning methods for brain tumor segmentation are typically trained in
an ad hoc fashion on all available data. Brain tumors are tremendously
heterogeneous in image appearance and labeled training data is limited. We
argue that incorporation of additional prior information, specifically tumor
grade, associated with tumor imaging phenotypes during model training can
significantly improve segmentation performance. Two strategies for
incorporation of tumor grade during model training are proposed and their
impact on segmentation performance is demonstrated on the BRATS 2018 dataset.


  We study the interplay between Mott physics, driven by Coulomb repulsion U,
and Hund physics, driven by Hund's coupling J, for a minimal model for Hund
metals, the orbital-symmetric three-band Hubbard-Hund model (3HHM) for a
lattice filling of 1/3. Hund-correlated metals are characterized by
spin-orbital separation (SOS), a Hund's-rule-induced two-stage Kondo-type
screening process, in which spin screening occurs at much lower energy scales
than orbital screening. By contrast, in Mott-correlated metals, lying close to
the phase boundary of a metal-insulator transition, the SOS window becomes
negligibly small and the Hubbard bands are well separated. Using dynamical
mean-field theory and the numerical renormalization group as real-frequency
impurity solver, we identify numerous fingerprints distinguishing Hundness from
Mottness in the temperature dependence of various physical quantities. These
include ARPES-type spectra, the local self-energy, static local orbital and
spin susceptibilities, resistivity, thermopower, and lattice and impurity
entropies. Our detailed description of the behavior of these quantities within
the context of a simple model Hamiltonian will be helpful for distinguishing
Hundness from Mottness in experimental and theoretical studies of real
materials.


  Thanks to their highly tunable band gaps, graphene nanoribbons (GNRs) with
atomically precise edges are emerging as mechanically and chemically robust
candidates for nanoscale light emitting devices of modulable emission color.
While their optical properties have been addressed theoretically in depth, only
few experimental studies exist, limited to ensemble measurements and without
any attempt to integrate them in an electronic-like circuit. Here we report on
the electroluminescence of individual GNRs suspended between the tip of a
scanning tunneling microscope (STM) and a Au(111) substrate, constituting thus
a realistic opto-electronic circuit. Emission spectra of such GNR junctions
reveal a bright and narrow band emission of red light, whose energy can be
tuned with the bias voltage applied to the junction, but always lying below the
gap of infinite GNRs. Comparison with {\it ab initio} calculations indicate
that the emission involves electronic states localized at the GNR termini. Our
results shed light on unpredicted optical transitions in GNRs and provide a
promising route for the realization of bright, robust and controllable
graphene-based light emitting devices.


  We show that the quantization ambiguities of loop quantum cosmology, when
considered in wider generality, can be used to produce discretionary dynamical
behavior. There is an infinite dimensional space of ambiguities which parallels
the infinite list of higher curvature corrections in perturbative quantum
gravity. There is however an ensemble of qualitative consequences which are
generic in the sense that they are independent of these ambiguities. Among
these, one has well defined fundamental dynamics across the big bang, and the
existence of extra microscopic quantum degrees of freedom that might be
relevant in discussions about unitarity in quantum gravity. We show that (in
addition to the well known bouncing solutions of the effective equations) there
are other generic type of solutions for sufficiently soft initial conditions in
the matter sector (tunneling solutions) where the scale factor goes through
zero and the spacetime orientation is inverted. We also show that generically,
a contracting semiclassical universe branches off at the big bang into a
quantum superposition of universes with different quantum numbers. Despite
their lack of quantitative predictive power these models offer a fertile
playground for the discussion of qualitative and conceptual issues in quantum
gravity.


  The purpose of this paper is to obtain asymptotics of shifted sums of Hecke
eigenvalue squares on average. We show that for $X^{\frac{2}{3}+\epsilon} < H
<X^{1-\epsilon},$ there are constants $B_{h}$ such that $$ \sum_{X\leq n \leq
2X} \lambda_{f}(n)^{2}\lambda_{f}(n+h)^{2}-B_{h}X=O_{f,A,\epsilon}\big(X (\log
X)^{-A}\big)$$ for all but $O_{f,A,\epsilon}\big(H(\log X)^{-3A}\big)$ integers
$h \in [1,H]$ where $\{\lambda_{f}(n)\}_{n\geq1}$ are normalized Hecke
eigenvalues of a fixed holomorphic cusp form $f.$ Our method is based on the
Hardy-Littlewood circle method. We divide the minor arcs into two parts $m_{1}$
and $m_{2}.$ In order to treat $m_{2},$ we use the Hecke relations, a bound of
Miller to apply some arguments from a paper of Matom\"{a}ki, Radziwill and Tao.
We apply Parseval's identity and Gallagher's lemma so as to treat $m_{1}.$


  The famous Nakayama conjecture states that the dominant dimension of a
non-selfinjective finite dimensional algebra is finite. In \cite{Yam}, Yamagata
stated the stronger conjecture that the dominant dimension of a
non-selfinjective finite dimensional algebra is bounded by a function depending
on the number of simple modules of that algebra. With a view towards those
conjectures, new bounds on dominant dimensions seem desirable. We give a new
approach to bounds on the dominant dimension of gendo-symmetric algebras via
counting non-isomorphic indecomposable summands of rigid modules in the module
category of those algebras. On the other hand, by Mueller's theorem, the
calculation of dominant dimensions is directly related to the calculation of
certain Ext-groups. Motivated by this connection, we generalize a theorem of
Tachikawa about non-vanishing of $Ext^{1}(M,M)$ for a non-projective module $M$
in group algebras of $p$-groups to local Hopf algebras and we also give new
results for showing the non-vanishing of $Ext^{1}(M,M)$ for certain modules in
other local selfinjective algebras, which specializes to show that blocks of
category $\mathcal{O}$ and 1-quasi-hereditary algebras with a special duality
have dominant dimension exactly 2. In the final section we raise different
questions with the hope of a new developement on those conjectures in the
future.


  Accurate modeling of 3D objects exhibiting transparency, reflections and thin
structures is an extremely challenging problem. Inspired by billboards and
geometric proxies used in computer graphics, this paper proposes Generative
Latent Textured Objects (GeLaTO), a compact representation that combines a set
of coarse shape proxies defining low frequency geometry with learned neural
textures, to encode both medium and fine scale geometry as well as
view-dependent appearance. To generate the proxies' textures, we learn a joint
latent space allowing category-level appearance and geometry interpolation. The
proxies are independently rasterized with their corresponding neural texture
and composited using a U-Net, which generates an output photorealistic image
including an alpha map. We demonstrate the effectiveness of our approach by
reconstructing complex objects from a sparse set of views. We show results on a
dataset of real images of eyeglasses frames, which are particularly challenging
to reconstruct using classical methods. We also demonstrate that these coarse
proxies can be handcrafted when the underlying object geometry is easy to
model, like eyeglasses, or generated using a neural network for more complex
categories, such as cars.


  We study the problem of continuum percolation in infinite volume Gibbs
measures for particles with an attractive pair potential, with a focus on low
temperatures (large $\beta$). The main results are bounds on percolation
thresholds $\rho_\pm(\beta)$ in terms of the density rather than the chemical
potential or activity. In addition, we prove a variational formula for a large
deviations rate function for cluster size distributions. This formula
establishes a link with the Gibbs variational principle and a form of
equivalence of ensembles, and allows us to combine knowledge on finite volume,
canonical Gibbs measures with infinite volume, grand-canonical Gibbs measures.


  In my previaou paper of K. Horihata, we have proposed a Ginzburg-Landau
system with a time-dependent parameter and then passing to the limit we have
constructed a harmonic heat flow into spheres. Thanks to this scheme, we
establish a few energy inequalities of our flow: (i) monotonical inequalities
and (ii) a reverse Poincare inequality at any boundary point. These
inequalities (i) and (ii) derive the smaller estimates on the set on
noncontinuouspoints for pur flow contrast to the former results. We refer to
them by Y. Chen and Y. Chen, J. Li, F. H. Lin. Next we introduce two sufficient
condition for the whole domain's regularity for it; The one is a boundary
energy smallness and the another is an one-sided condition proposed by S.
Hildebrandt and K. O. Widman.


  Using deep archival observations from the Chandra X-ray Observatory, we
present an analysis of linear X-ray-emitting features located within the
southern portion of the Galactic center chimney, and oriented orthogonal to the
Galactic plane, centered at coordinates l = 0.08 deg, b = -1.42 deg. The
surface brightness and hardness ratio patterns are suggestive of a cylindrical
morphology which may have been produced by a plasma outflow channel extending
from the Galactic center. Our fits of the feature's spectra favor a complex
two-component model consisting of thermal and recombining plasma components,
possibly a sign of shock compression or heating of the interstellar medium by
outflowing material. Assuming a recombining plasma scenario, we further
estimate the cooling timescale of this plasma to be on the order of a few
hundred to thousands of years, leading us to speculate that a sequence of
accretion events onto the Galactic Black Hole may be a plausible
quasi-continuous energy source to sustain the observed morphology.


  Time series data in the retail world are particularly rich in terms of
dimensionality, and these dimensions can be aggregated in groups or
hierarchies. Valuable information is nested in these complex structures, which
helps to predict the aggregated time series data. From a portfolio of brands
under HUUB's monitoring, we selected two to explore their sales behaviour,
leveraging the grouping properties of their product structure. Using
statistical models, namely SARIMA, to forecast each level of the hierarchy, an
optimal combination approach was used to generate more consistent forecasts in
the higher levels. Our results show that the proposed methods can indeed
capture nested information in the more granular series, helping to improve the
forecast accuracy of the aggregated series. The Weighted Least Squares (WLS)
method surpasses all other methods proposed in the study, including the Minimum
Trace (MinT) reconciliation.


  We make a detailed comparison between the direct method and the HAL QCD
potential method for the baryon-baryon interactions, taking the $\Xi\Xi$ system
at $m_\pi= 0.51$ GeV in 2+1 flavor QCD and using both smeared and wall quark
sources. The energy shift $\Delta E_\mathrm{eff}(t)$ in the direct method shows
the strong dependence on the choice of quark source operators, which means that
the results with either (or both) source are false. The time-dependent HAL QCD
method, on the other hand, gives the quark source independent $\Xi\Xi$
potential, thanks to the derivative expansion of the potential, which absorbs
the source dependence to the next leading order correction. The HAL QCD
potential predicts the absence of the bound state in the $\Xi\Xi$($^1$S$_0$)
channel at $m_\pi= 0.51$ GeV, which is also confirmed by the volume dependence
of finite volume energy from the potential. We also demonstrate that the origin
of the fake plateau in the effective energy shift $\Delta E_\mathrm{eff}(t)$ at
$t \sim 1$ fm can be clarified by a few low-lying eigenfunctions and
eigenvalues on the finite volume derived from the HAL QCD potential, which
implies that the ground state saturation of $\Xi\Xi$($^1$S$_0$) requires $t
\sim 10$ fm in the direct method for the smeared source on $(4.3 \
\mathrm{fm})^3$ lattice, while the HAL QCD method does not suffer from such a
problem.


  Cryptographic protocols aim at securing communications over insecure networks
such as the Internet, where dishonest users may listen to communications and
interfere with them. A secure communication has a different meaning depending
on the underlying application. It ranges from the confidentiality of a data to
e.g. verifiability in electronic voting systems. Another example of a security
notion is privacy.
  Formal symbolic models have proved their usefulness for analysing the
security of protocols. Until quite recently, most results focused on trace
properties like confidentiality or authentication. There are however several
security properties, which cannot be defined (or cannot be naturally defined)
as trace properties and require a notion of behavioural equivalence. Typical
examples are anonymity, and privacy related properties. During the last decade,
several results and verification tools have been developed to analyse
equivalence-based security properties.
  We propose here a synthesis of decidability and undecidability results for
equivalence-based security properties. Moreover, we give an overview of
existing verification tools that may be used to verify equivalence-based
security properties.


  A new descent algebra $\sum_{W}(A_{n})$ of Weyl groups of type $A_n$,
constructed by present authors in [1], is generated by equivalence classes
$[x_J]$ arising from the equivalence relation defined on the set of all $x_J$.
In this paper, we introduce the structure of this new descent algebra for
standard parabolic subgroups $W_J$ of Weyl groups of type $A_n$.


  The link between data and governance are key to making public health supply
chains more integrated and responsive in order to get life-saving commodities
to those in need. In particular, considering its significant health challenges,
poor maternal and child health indicators, and major recent devolution in
political authority, Kenya represents a country in need of an innovative revamp
of their data management and governance. John Snow, Inc. (JSI) adapted various
elements of proven interventions to build a customized structure to support
routine data collection in order to drive decision making around supply chain
improvement.


  The development of generative Machine Learning (ML) models in creative
practices, enabled by the recent improvements in usability and availability of
pre-trained models, is raising more and more interest among artists,
practitioners and performers. Yet, the introduction of such techniques in
artistic domains also revealed multiple limitations that escape current
evaluation methods used by scientists. Notably, most models are still unable to
generate content that lay outside of the domain defined by the training
dataset. In this paper, we propose an alternative prospective framework,
starting from a new general formulation of ML objectives, that we derive to
delineate possible implications and solutions that already exist in the ML
literature (notably for the audio and musical domain). We also discuss existing
relations between generative models and computational creativity and how our
framework could help address the lack of creativity in existing models.


  Periodically driven thermodynamic systems support stable non-equilibrium
oscillating states with properties drastically different from equilibrium. They
exhibit even more exotic features for low viscous drives, which is a regime
that is hard to probe due to singular behavior of the underlying Langevin
dynamics near vanishing viscosity. We propose a method, based on singular
perturbation and Floquet theories, that allows us to obtain oscillating states
in this limit. We then find two distinct classes of distributions, each
exhibiting interesting features that can be exploited for a range of practical
applicability, including cooling a system and triggering chemical reactions
through weakly interacting driven environments.


  We study the overlaps between right and left eigenvectors for random matrices
of the spherical and truncated unitary ensembles. Conditionally on all
eigenvalues, diagonal overlaps are shown to be distributed as a product of
independent random variables. This enables us to prove that the scaled diagonal
overlaps, conditionally on one eigenvalue, converge in distribution to a
heavy-tail limit, namely, the inverse of a $\gamma_2$ distribution. These
results are analogous to what is known for the complex Ginibre ensemble. We
also provide formulae for the conditional expectation of diagonal and
off-diagonal overlaps, with respect to all eigenvalues.


  The thermodynamic potential of ideal gases described by the simplest
non-abelian statistics is investigated. I show that the potential is the linear
function of the element of the abelian-part statistics matrix. Thus, the
factorizable property in the Haldane (abelian) fractional exclusion shown by
the author [W. H. Huang, Phys. Rev. Lett. 81, 2392 (1998)] is now extended to
the non-abelian case. The complete expansion of the thermodynamic potential is
also given.


  Recently, perfect matching in bounded planar cutwidth bipartite graphs
(\BGGM) was shown to be in ACC$^0$ by Hansen et al.. They also conjectured that
the problem is in AC$^0$.
  In this paper, we disprove their conjecture by showing that the problem is
not in AC$^0[p^{\alpha}]$ for every prime $p$. Our results show that the
previous upper bound is almost tight. Our techniques involve giving a reduction
from Parity to BGGM. A further improvement in lower bounds is difficult since
we do not have an algebraic characterization for AC$^0[m]$ where $m$ is not a
prime power. Moreover, this will also imply a separation of AC$^0[m]$ from P.
Our results also imply a better lower bound for perfect matching in general
bounded planar cutwidth graphs.


  In this communication, we show how asteroids observations from the Gaia
mission can be used to perform local tests of General Relativity (GR). This ESA
mission, launched in December 2013, will observe --in addition to the stars-- a
large number of small Solar System Objects (SSOs) with unprecedented
astrometric precision. Indeed, it is expected that about 360,000 asteroids will
be observed with a nominal sub-mas precision.
  Here, we show how these observations can be used to constrain some extensions
to General Relativity. We present results of SSOs simulations that take into
account the time sequences over 5 years and geometry of the observations that
are particular to Gaia. We present a sensitivity study on various GR extensions
and dynamical parameters including: the Sun quadrupolar moment $J_2$, the
parametrized post-Newtonian parameter $\beta$, the Nordtvedt parameter $\eta$,
the fifth force formalism, the Lense-Thirring effect, a temporal variation of
the gravitational parameter $GM_\textrm{sun}$ (a linear variation as well as a
periodic variation), the Standard Model Extension formalism,... Some
implications for planetary ephemerides analysis are also briefly discussed.


  We take up an idea from the folklore of Answer Set Programming, namely that
choices, integrity constraints along with a restricted rule format is
sufficient for Answer Set Programming. We elaborate upon the foundations of
this idea in the context of the logic of Here-and-There and show how it can be
derived from the logical principle of extension by definition. We then provide
an austere form of logic programs that may serve as a normalform for logic
programs similar to conjunctive normalform in classical logic. Finally, we take
the key ideas and propose a modeling methodology for ASP beginners and
illustrate how it can be used.


  Subspace clustering refers to the problem of clustering unlabeled
high-dimensional data points into a union of low-dimensional linear subspaces,
whose number, orientations, and dimensions are all unknown. In practice one may
have access to dimensionality-reduced observations of the data only, resulting,
e.g., from undersampling due to complexity and speed constraints on the
acquisition device or mechanism. More pertinently, even if the high-dimensional
data set is available it is often desirable to first project the data points
into a lower-dimensional space and to perform clustering there; this reduces
storage requirements and computational cost. The purpose of this paper is to
quantify the impact of dimensionality reduction through random projection on
the performance of three subspace clustering algorithms, all of which are based
on principles from sparse signal recovery. Specifically, we analyze the
thresholding based subspace clustering (TSC) algorithm, the sparse subspace
clustering (SSC) algorithm, and an orthogonal matching pursuit variant thereof
(SSC-OMP). We find, for all three algorithms, that dimensionality reduction
down to the order of the subspace dimensions is possible without incurring
significant performance degradation. Moreover, these results are order-wise
optimal in the sense that reducing the dimensionality further leads to a
fundamentally ill-posed clustering problem. Our findings carry over to the
noisy case as illustrated through analytical results for TSC and simulations
for SSC and SSC-OMP. Extensive experiments on synthetic and real data
complement our theoretical findings.


  The characterization and analysis of microstructure is the foundation of
microstructural science, connecting the materials structure to its composition,
process history, and properties. Microstructural quantification traditionally
involves a human deciding a priori what to measure and then devising a
purpose-built method for doing so. However, recent advances in data science,
including computer vision (CV) and machine learning (ML) offer new approaches
to extracting information from microstructural images. This overview surveys CV
approaches to numerically encode the visual information contained in a
microstructural image, which then provides input to supervised or unsupervised
ML algorithms that find associations and trends in the high-dimensional image
representation. CV/ML systems for microstructural characterization and analysis
span the taxonomy of image analysis tasks, including image classification,
semantic segmentation, object detection, and instance segmentation. These tools
enable new approaches to microstructural analysis, including the development of
new, rich visual metrics and the discovery of
processing-microstructure-property relationships.


  We consider the recently developed diagrammatic approach to soft-gluon
exponentiation in multiparton scattering amplitudes, where the exponent is
written as a sum of webs - closed sets of diagrams whose colour and kinematic
parts are entangled via mixing matrices. A complementary approach to
exponentiation is based on the multiplicative renormalizability of intersecting
Wilson lines, and their subsequent finite anomalous dimension. Relating this
framework to that of webs, we derive renormalization constraints expressing all
multiple poles of any given web in terms of lower-order webs. We examine these
constraints explicitly up to four loops, and find that they are realised
through the action of the web mixing matrices in conjunction with the fact that
multiple pole terms in each diagram reduce to sums of products of lower-loop
integrals. Relevant singularities of multi-eikonal amplitudes up to three loops
are calculated in dimensional regularization using an exponential infrared
regulator. Finally, we formulate a new conjecture for web mixing matrices,
involving a weighted sum over column entries. Our results form an important
step in understanding non-Abelian exponentiation in multiparton amplitudes, and
pave the way for higher-loop computations of the soft anomalous dimension.


  The sequence-dependent structural variability and conformational dynamics of
DNA play pivotal roles in many biological milieus, such as in the site-specific
binding of transcription factors to target regulatory elements. To better
understand DNA structure, function, and dynamics in general, and protein-DNA
recognition in the 'kB' family of genetic regulatory elements in particular, we
performed molecular dynamics simulations of a 20-base pair DNA encompassing a
cognate kB site recognized by the proto-oncogenic 'c-Rel' subfamily of NF-kB
transcription factors. Simulations of the kB DNA in explicit water were
extended to microsecond duration, providing a broad, atomically-detailed
glimpse into the structural and dynamical behavior of double helical DNA over
many timescales. Of particular note, novel (and structurally plausible)
conformations of DNA developed only at the long times sampled in this
simulation -- including a peculiar state arising at ~ 0.7 us and characterized
by cross-strand intercalative stacking of nucleotides within a
longitudinally-sheared base pair, followed (at ~ 1 us) by spontaneous base
flipping of a neighboring thymine within the A-rich duplex. Results and
predictions from the us-scale simulation include implications for a dynamical
NF-kB recognition motif, and are amenable to testing and further exploration
via specific experimental approaches that are suggested herein.


  Simulations of the viscous hydrodynamic model for relativistic heavy-ion
collisions at RHIC and LHC energies are presented. Results for spectra,
femtoscopy radii, and transverse momentum fluctuations are favorably compared
to the experimental data. Effects of the local charge conservation on
correlation observables are also studied.


  In this paper we obtain conserved charges of spin-3 topologically massive
gravity by using a quasi-local formalism. We find a general formula to
calculate conserved charge of the spin-3 topologically massive gravity which
corresponds to a Killing vector field $\xi$. We show that this general formula
reduces to the previous one for the ordinary spin-3 gravity presented in
\cite{31} when we take into account only transformation under diffeomorphism,
without considering generalized Lorentz gauge transformation (i.e. $\lambda
_{\xi} =0$), and by taking $\frac{1}{\mu}\rightarrow 0$. Then we obtain a
general formula for the entropy of black hole solutions of the spin-3
topologically massive gravity. Finally we apply our formalism to calculate
energy, angular momentum and entropy of a special black hole solution and we
find that obtained results are consistent with previous results in the limiting
cases. Moreover our result for energy, angular momentum and entropy are
consistent with the first law of black hole mechanics.


  In this work we present a new method for the estimation of Mutual Information
(MI) between random variables. Our approach is based on an original
interpretation of the Girsanov theorem, which allows us to use score-based
diffusion models to estimate the Kullback Leibler divergence between two
densities as a difference between their score functions. As a by-product, our
method also enables the estimation of the entropy of random variables. Armed
with such building blocks, we present a general recipe to measure MI, which
unfolds in two directions: one uses conditional diffusion process, whereas the
other uses joint diffusion processes that allow simultaneous modelling of two
random variables. Our results, which derive from a thorough experimental
protocol over all the variants of our approach, indicate that our method is
more accurate than the main alternatives from the literature, especially for
challenging distributions. Furthermore, our methods pass MI self-consistency
tests, including data processing and additivity under independence, which
instead are a pain-point of existing methods.


  We investigate the IceCube detection potential of very high energy neutrinos
from blazars, for different classes of "hadronic" models, taking into account
the limits imposed on the neutrino flux by the recent Fermi telescope
observations. Assuming the observed gamma-ray emission is produced by the decay
of neutral pions from proton-proton interactions, the measurement of the
time-averaged spectral characteristics of blazars in the GeV energy band
imposes upper limits on the time-averaged neutrino flux. Comparing these upper
limits to the 5 sigma discovery threshold of IceCube for different neutrino
spectra and different source locations in the sky, we find that several BL Lacs
with hard spectra in the GeV band are within the detection potential of
IceCube. If the gamma-ray emission is dominated by the neutral pion decay flux,
none of the flat-spectrum radio quasars are detectable with IceCube. If the
primary high energy proton spectrum is very hard and/or neutrinos are produced
in proton-photon, rather than proton-proton reactions, the upper limit on the
neutrino flux imposed by the measured gamma-ray spectra is relaxed and
gamma-ray observations impose only lower bounds on the neutrino flux. We
investigate whether these lower bounds guarantee the detection of blazars with
very hard neutrino spectra, expected in the latter type model. We show that all
the "hadronic" models of activity of blazars are falsifiable with IceCube.
Furthermore, we show that models with gamma-ray emission produced by the decay
of neutral pions from proton-proton interactions can be readily distinguished
from the models based on proton-gamma interactions and/or models predicting
very hard high energy proton spectra via a study of the distribution of
spectral indices of gamma-ray spectra of sources detected with IceCube.


  The ETH model of the pion-nucleon ($\pi N$) interaction contains $t$-channel
$\sigma$- and $\rho$-exchange graphs, as well as the $s$- and $u$-channel
contributions with the well-established $s$ and $p$ baryon states with masses
below $2$ GeV as virtual particles; the model amplitudes obey crossing symmetry
and isospin invariance. In the present work, we give the analytical expressions
for the model contributions to the $K$-matrix elements up to (and including)
the $f$ waves. We also extract a new phase-shift solution after performing a
partial-wave analysis of meson-factory $\pi^\pm p$ elastic-scattering data
below $100$ MeV; included in our results now are also the effects of the
variation of the $\sigma$-meson mass in the interval which is currently
recommended by the Particle-Data Group. Finally, we revisit the subject of the
$\pi N$ $\Sigma$ term and, using the model amplitudes, obtain $\Sigma = 72.4
\pm 3.1$ MeV. Our prediction agrees well with the result extracted with
Olsson's method, after a few flaws in his paper [Phys. Lett. B 482 (2000) 50]
were corrected.


  In this paper, we study the existence of multiple solutions to a generalized
$p(\cdot)$-Laplace equation with two parameters involving critical growth. More
precisely, we give sufficient "local" conditions, which mean that growths
between the main operator and nonlinear term are locally assumed for the cases
$p(\cdot)$-sublinear, $p(\cdot)$-superlinear, and sandwich-type. Compared to
constant exponent problems (for examples, $p$-Laplacian and $(p,q)$-Laplacian),
this characterizes the study of variable exponent problems. We show this by
applying variants of the Mountain Pass Theorem for $p(\cdot)$-sublinear and
$p(\cdot)$-superlinear cases and constructing critical values defined by a
minimax argument in the genus theory for sandwich-type case. Moreover, we also
obtain a nontrivial nonnegative solution for sandwich-type case changing a role
of parameters. Our work is a generalization of several existing works in the
literature.


  We outline the theory of reflections for prederivators, derivators and stable
derivators. In order to parallel the classical theory valid for categories, we
outline how reflections can be equivalently described as categories of
fractions, reflective factorization systems, and categories of algebras for
idempotent monads. This is a further development of the theory of monads and
factorization systems for derivators.


  We revisit the setting and the assumptions that underlie the methodology of
Dynamic Mode Decomposition (DMD) in order to highlight caveats as well as
potential measures of when the applicability is warranted.


  The importance of the quantum Fisher information metric is testified by the
number of applications that this has in very different fields, ranging from
hypothesis testing to metrology, passing through thermodynamics. Still, from
the rich range of possible quantum Fisher information, only a handful are
typically used and studied. This review aims at collecting a number of results
scattered in the literature that can be useful to people who begin the study of
Fisher information and to those who are already working on it to have a more
organic understanding of the topic. Moreover, we complement the review with new
results about the relation between Fisher information and physical evolutions.
Extending the study done in [1], we prove that all the physically realisable
dynamics can be defined solely in terms of their relation with respect to the
Fisher information metric. Moreover, other properties as Markovianity,
retrodiction or detailed balance can be expressed in the same formalism. These
results show a fact that was partially overseen in the literature, namely the
inherently dynamical nature of Fisher information.


  QCD-based analysis of nonfactorizable parts of weak nonleptonic amplitudes is
reported.
  Nonperturbative effects due to soft gluon exchange play a key role leading to
the emergence of a dynamical rule of discarding $1/N_c$ corrections.


  Integrating nano-scale objects, such as single molecules or carbon nanotubes,
into impedance transformers and performing radio-frequency measurements allows
for high time-resolution transport measurements with improved signal-to-noise
ratios. The realization of such transformers implemented with superconducting
transmission lines for the 2-10 GHz frequency range is presented here.
Controlled electromigration of an integrated gold break junction is used to
characterize a 6 GHz impedance matching device. The real part of the RF
impedance of the break junction extracted from microwave reflectometry at a
maximum bandwidth of 45 MHz of the matching circuit is in good agreement with
the measured direct current resistance.


  Probabilistic sentential decision diagrams are a class of
structured-decomposable probabilistic circuits especially designed to embed
logical constraints. To adapt the classical LearnSPN scheme to learn the
structure of these models, we propose a new scheme based on a partial
closed-world assumption: data implicitly provide the logical base of the
circuit. Sum nodes are thus learned by recursively clustering batches in the
initial data base, while the partitioning of the variables obeys a given input
vtree. Preliminary experiments show that the proposed approach might properly
fit training data, and generalize well to test data, provided that these remain
consistent with the underlying logical base, that is a relaxation of the
training data base.


  We formulate and solve the equations governing the transonic behaviour of a
general relativistic black-hole accretion disc with non-zero advection
velocity. We demonstrate that a relativistic Rankine-Hugoniot shock may form
leading to the formation of accretion powered outflow. We show that the
critical points of transonic discs generally do not coincide with the
corresponding sonic points. The collection of such sonic points forms an
axisymmetric hypersurface, generators of which are the acoustic null geodesics,
i.e. the phonon trajectories. Such a surface is shown to be identical with an
acoustic event horizon. The acoustic surface gravity and the corresponding
analogue horizon temperature $T_{AH}$ at the acoustic horizon are then computed
in terms of fundamental accretion parameters. Physically, the analogue
temperature is associated with the thermal phonon radiation analogous to the
Hawking radiation of the black-hole horizon.Thus, an axisymmetric black-hole
accretion disc is established as a natural example of the classical analogue
gravity model, for which two kinds of horizon exist simultaneously. We have
shown that for some values of astrophysically relevant accretion parameters,
the analogue temperature exceeds the corresponding Hawking temperature. We
point out that acoustic {\it white holes} can also be generated for a
multi-transonic black-hole accretion with a shock. Such a white hole, produced
at the shock, is always flanked by two acoustic black holes generated at the
inner and the outer sonic points. Finally, we discuss possible applications of
our work to other astrophysical events which may exhibit analogue effects.


  In the semiclassical picture of photoionization process in intense laser
fields, the ionization rate solely depends on the amplitude of the electric
field and the final photoelectron momentum corresponds to the instant of
ionization of the photoelectron, however, this picture has never been checked
rigorously. Recently an attosecond angular streaking technique based on this
semiclassical perspective has been widely applied to temporal measurement of
the atomic and molecular dynamics in intense laser fields. We use a
Wigner-distribution-like function to calculate the time-emission angle
distribution, angular distribution and ionization time distribution for atomic
ionization process in elliptically polarized few-cycle laser fields. By
comparing with semiclassical calculations, we find that the two methods always
show discrepancies except in some specific cases and the offset angles are
generally not consistent with the offset times of the ionization time
distributions obtained by the two methods even when the non-adiabatic effect is
taken into account, indicating that the "attoclock" technique is in principle
inaccurate. Moreover, calculations for linearly polarized laser fields also
show similar discrepancies between two methods in the ionization time
distribution. Our analysis indicates that the discrepancy between the
semiclassical and quantum calculations can be attributed to correlation, i. e.,
temporal nonlocalization effect.


  We present estimates of the GALEX NUV and FUV luminosity functions (LFs) of
the Coma cluster, over a total area of ~9 deg^2 (~25 Mpc^2), i.e. from the
cluster center to the virial radius. Our analysis represents the widest and
deepest UV investigation of a nearby cluster of galaxies made to date. The Coma
UV LFs show a faint-end slope steeper than the one observed in the local field.
This difference, more evident in NUV, is entirely due to the contribution of
massive quiescent systems (e.g. ellipticals, lenticulars and passive spirals),
more frequent in high density environments. On the contrary, the shape of the
UV LFs for Coma star-forming galaxies does not appear to be significantly
different from that of the field, consistently with previous studies of local
and high redshift clusters. We demonstrate that such similarity is only a
selection effect, not providing any information on the role of the environment
on the star formation history of cluster galaxies. By integrating the UV LFs
for star-forming galaxies (corrected for the first time for internal dust
attenuation), we show that the specific star formation rate of Coma is
significantly lower than the integrated SSFR of the field and that Coma-like
clusters contribute only <7% of the total SFR density of the local universe.
Approximately 2/3 of the whole star-formation in Coma is occurring in galaxies
with M_star < 10^10 M_sol. The vast majority of star-forming galaxies has
likely just started its first dive into the cluster core and has not yet been
affected by the cluster environment. The total stellar mass accretion rate of
Coma is ~(0.6-1.8) x 10^12 M_sol Gyr^-1, suggesting that a significant fraction
of the population of lenticular and passive spirals observed today in Coma
could originate from infalling galaxies accreted between z~1 and z~0.


  One of the crown jewels of complexity theory is Valiant's 1979 theorem that
computing the permanent of an n*n matrix is #P-hard. Here we show that, by
using the model of linear-optical quantum computing---and in particular, a
universality theorem due to Knill, Laflamme, and Milburn---one can give a
different and arguably more intuitive proof of this theorem.


  In the context of flow in porous media, up-scaling is the coarsening of a
geological model and it is at the core of water resources research and
reservoir simulation. An ideal up-scaling procedure preserves heterogeneities
at different length-scales but reduces the computational costs required by
dynamic simulations. A number of up-scaling procedures have been proposed. We
present a block renormalization algorithm using Haar wavelets which provide a
representation of data based on averages and fluctuations.
  In this work, absolute permeability will be discussed for single-phase
incompressible creeping flow in the Darcy regime, leading to a finite
difference diffusion type equation for pressure. By transforming the terms in
the flow equation, given by Darcy's law, and assuming that the change in scale
does not imply a change in governing physical principles, a new equation is
obtained, identical in form to the original. Haar wavelets allow us to relate
the pressures to their averages and apply the transformation to the entire
equation, exploiting their orthonormal property, thus providing values for the
coarse permeabilities.
  Focusing on the mean-field approximation leads to an up-scaling where the
solution to the coarse scale problem well approximates the averaged fine scale
pressure profile.


  Federated Domain Generalization (FedDG), aims to tackle the challenge of
generalizing to unseen domains at test time while catering to the data privacy
constraints that prevent centralized data storage from different domains
originating at various clients. Existing approaches can be broadly categorized
into four groups: domain alignment, data manipulation, learning strategies, and
optimization of model aggregation weights. This paper proposes a novel approach
to Federated Domain Generalization that tackles the problem from the
perspective of the backbone model architecture. The core principle is that
objects, even under substantial domain shifts and appearance variations,
maintain a consistent hierarchical structure of parts and wholes. For instance,
a photograph and a sketch of a dog share the same hierarchical organization,
consisting of a head, body, limbs, and so on. The introduced architecture
explicitly incorporates a feature representation for the image parse tree. To
the best of our knowledge, this is the first work to tackle Federated Domain
Generalization from a model architecture standpoint. Our approach outperforms a
convolutional architecture of comparable size by over 12\%, despite utilizing
fewer parameters. Additionally, it is inherently interpretable, contrary to the
black-box nature of CNNs, which fosters trust in its predictions, a crucial
asset in federated learning.


  This paper presents a key recovery attack on the cryptosystem proposed by Lau
and Tan in a talk at ACISP 2018. The Lau-Tan cryptosystem uses Gabidulin codes
as the underlying decodable code. To hide the algebraic structure of Gabidulin
codes, the authors chose a matrix of column rank $n$ to mix with a generator
matrix of the secret Gabidulin code. The other part of the public key, however,
reveals crucial information about the private key. Our analysis shows that the
problem of recovering the private key can be reduced to solving a multivariate
linear system over the base field, rather than solving a multivariate quadratic
system as claimed by the authors. Solving the linear system for any nonzero
solution permits us to recover the private key. Apparently, this attack costs
polynomial time, and therefore completely breaks the cryptosystem.


  We present a first morphometric investigation of a preliminary sample from
the SDSS of 154287 galaxies with apparent magnitude 14.5<m_r<17.5 and redshift
0.001<z<0.4. We measure the Minkowski Functionals, which are a complete set of
morphological descriptors. To account for the complicated wedge--like geometry
of the present survey data, we construct isodensity contour surfaces from the
galaxy positions in redshift space and employ two complementary methods of
computing the Minkowski Functionals. We find that the observed Minkowski
Functionals for SDSS galaxies are consistent with the prediction of a
Lambda--dominated spatially--flat Cold Dark Matter model with random--Gaussian
initial conditions, within the cosmic variance estimated from the corresponding
mock catalogue. We expect that future releases of the SDSS survey will allow us
to distinguish morphological differences in the galaxy distribution with regard
to different morphological type and luminosity ranges.


  The spectrum of a selfadjoint second order elliptic differential operator in
$L^2(\mathbb{R}^n)$ is described in terms of the limiting behavior of
Dirichlet-to-Neumann maps, which arise in a multi-dimensional Glazman
decomposition and correspond to an interior and an exterior boundary value
problem. This leads to PDE analogs of renowned facts in spectral theory of
ODEs. The main results in this paper are first derived in the more abstract
context of extension theory of symmetric operators and corresponding Weyl
functions, and are applied to the PDE setting afterwards.


  We consider standard and extended CMV matrices with small quasi-periodic
Verblunsky coefficients and show that on their essential spectrum, all spectral
measures are purely absolutely continuous. This answers a question of Barry
Simon from 2005.


  Although it has been surpassed by many subsequent coding standards, JPEG
occupies a large share of the storage load of the current data hosting service.
To reduce the storage costs, DropBox proposed a lossless secondary compression
algorithm, Lepton, to further improve the compression rate of JPEG images.
However, the bloated probability models defined by Lepton severely restrict its
throughput and energy efficiency. To solve this problem, we construct an
efficient access probability-based hash function for the probability models,
and then propose a hardware-friendly memory optimization method by combining
the proposed hash function and the N-way Set-Associative unit. After that, we
design a highly parameterized hardware structure for the probability models and
finally implement a power and area efficient Lepton hardware encoder. To the
best of our knowledge, this is the first hardware implementation of Lepton. The
synthesis result shows that the proposed hardware structure reduces the total
area of the probability models by 70.97%. Compared with DropBox's software
solution, the throughput and the energy efficiency of the proposed Lepton
hardware encoder are increased by 55.25 and 4899 times respectively. In terms
of manufacturing cost, the proposed Lepton hardware encoder is also
significantly lower than the general-purpose CPU used by DropBox.


  We propose a definition of compact quantum groupoids in the setting of
C*-algebras, associate to such a quantum groupoid a regular
C*-pseudo-multiplicative unitary, and use this unitary to construct a dual Hopf
C*-bimodule and to pass to a measurable quantum groupoid in the sense of Enock
and Lesieur. Moreover, we discuss examples related to compact and to \'etale
groupoids and study principal compact C*-quantum groupoids.


  A novel method for segmenting bright objects from dark background for
grayscale image is proposed. The concept of this method can be stated simply
as: to pick out the local-thinnest bands on the grayscale grade-map. It turns
out to be a threshold-based method with local adaptive thresholds, where each
local threshold is determined by requiring the average normal-direction
gradient on the object boundary to be local minimal. The method is highly
automatic and the segmentation mimics a man's natural expectation even the
object boundaries are fuzzy.


  We analyze the ordered phases of Bernal stacked multilayer graphene in the
presence of interaction induced band gaps due to sublattice symmetry breaking
potentials, whose solutions can be analyzed in terms of light-mass and
heavy-mass pseudospin doublets which have the same Chern numbers but opposite
charge polarization directions. The application of a perpendicular external
electric field reveals an effective Hund's rule for the ordering of the
sublattice pseudospin doublets in a tetralayer, while a similar but more
complex phase diagram develops with increasing layer number.


  The ability to recognize dynamical phenomena (e.g., dynamical phases) and
dynamical processes in physical events from videos, then to abstract physical
concepts and reveal physical laws, lies at the core of human intelligence. The
main purposes of this paper are to use neural networks for classifying the
dynamical phases of some videos and to demonstrate that neural networks can
learn physical concepts from them. To this end, we employ multiple neural
networks to recognize the static phases (image format) and dynamical phases
(video format) of a particle-based skyrmion model. Our results show that neural
networks, without any prior knowledge, can not only correctly classify these
phases, but also predict the phase boundaries which agree with those obtained
by simulation. We further propose a parameter visualization scheme to interpret
what neural networks have learned. We show that neural networks can learn two
order parameters from videos of dynamical phases and predict the critical
values of two order parameters. Finally, we demonstrate that only two order
parameters are needed to identify videos of skyrmion dynamical phases. It shows
that this parameter visualization scheme can be used to determine how many
order parameters are needed to fully recognize the input phases. Our work sheds
light on the future use of neural networks in discovering new physical concepts
and revealing unknown yet physical laws from videos.


  This paper extends previous work with network fragments and
situation-specific network construction. We formally define the asymmetry
network, an alternative representation for a conditional probability table. We
also present an object-oriented representation for partially specified
asymmetry networks. We show that the representation is parsimonious. We define
an algebra for the elements of the representation that allows us to 'factor'
any CPT and to soundly combine the partially specified asymmetry networks.


  Measurement feedback is a versatile and powerful tool, although its
performance is limited by several practical imperfections resulting from
classical components. This paper shows that, for some typical quantum feedback
control problems for state preparation (stabilization of a qubit or a qutrit,
spin squeezing, and Fock state generation), the classical feedback operation
can be replaced by a fully quantum one such that the state autonomously
dissipates into the target or a state close to the target. The main common
feature of the proposed quantum operation, which is called coherent feedback,
is that it is composed of a series of dispersive and dissipative couplings
inspired by the corresponding measurement feedback scheme.


  Bayesian optimization (BO) is among the most effective and widely-used
blackbox optimization methods. BO proposes solutions according to an
explore-exploit trade-off criterion encoded in an acquisition function, many of
which are computed from the posterior predictive of a probabilistic surrogate
model. Prevalent among these is the expected improvement (EI) function. The
need to ensure analytical tractability of the predictive often poses
limitations that can hinder the efficiency and applicability of BO. In this
paper, we cast the computation of EI as a binary classification problem,
building on the link between class-probability estimation and density-ratio
estimation, and the lesser-known link between density-ratios and EI. By
circumventing the tractability constraints, this reformulation provides
numerous advantages, not least in terms of expressiveness, versatility, and
scalability.


  Classical population genetics a priori assigns fitness to alleles without
considering molecular or functional properties of proteins that these alleles
encode. Here we study population dynamics in a model where fitness can be
inferred from physical properties of proteins under a physiological assumption
that loss of stability of any protein encoded by an essential gene confers a
lethal phenotype. Accumulation of mutations in organisms containing Gamma genes
can then be represented as diffusion within the Gamma dimensional hypercube
with adsorbing boundaries which are determined, in each dimension, by loss of a
protein stability and, at higher stability, by lack of protein sequences.
Solving the diffusion equation whose parameters are derived from the data on
point mutations in proteins, we determine a universal distribution of protein
stabilities, in agreement with existing data. The theory provides a fundamental
relation between mutation rate, maximal genome size and thermodynamic response
of proteins to point mutations. It establishes a universal speed limit on rate
of molecular evolution by predicting that populations go extinct (via lethal
mutagenesis) when mutation rate exceeds approximately 6 mutations per essential
part of genome per replication for mesophilic organisms and 1 to 2 mutations
per genome per replication for thermophilic ones. Further, our results suggest
that in absence of error correction, modern RNA viruses and primordial genomes
must necessarily be very short. Several RNA viruses function close to the
evolutionary speed limit while error correction mechanisms used by DNA viruses
and non-mutant strains of bacteria featuring various genome lengths and
mutation rates have brought these organisms universally about 1000 fold below
the natural speed limit.


  In this paper, using Donaldson's heat flow, we show that the semi-stability
of a Higgs bundle over a compact K\"ahler manifold implies the existence of
approximate Hermitian-Einstein structure on the Higgs bundle.


  Connection coefficients between different orthonormal bases satisfy two
discrete orthogonal relations themselves. For classical orthogonal polynomials
whose weights are invariant under the action of the symmetric group, connection
coefficients between a basis consisting of products of hypergeometric functions
and another basis obtained from the first one by applying a permutation are
studied. For the Jacobi polynomials on the simplex, it is shown that the
connection coefficients can be expressed in terms of Tratnik's multivariable
Racah polynomials and their weights. This gives, in particular, a new
interpretation of the hidden duality between the variables and the degree
indices of the Racah polynomials, which lies at the heart of their bispectral
properties. These techniques also lead to explicit formulas for connection
coefficients of Hahn and Krawtchouk polynomials of several variables, as well
as for orthogonal polynomials on balls and spheres.


  We investigate exact non-stationary quantum states of vacuum toroidal black
holes with a negative cosmological constant in arbitrary dimensions using the
framework of throat quantization pioneered by Louko and M\"akel\"a for
Schwarzschild black holes. The system is equivalent to a harmonic oscillator on
the half line, in which the central singularity is resolved quantum
mechanically by imposing suitable boundary conditions that preserve unitarity.
We identify two suitable families of exact time-dependent wave functions with
Dirichlet or Neumann boundary conditions at the location of the classical
singularity. We find that for highly non-stationary states of large-mass black
holes, quantum fluctuations are not negligible in one family, while they are
greatly suppressed in the other. The latter, therefore, may provide candidates
for describing the dynamics of semi-classical black holes.


  Over the last decade, the infrared behavior of Yang-Mills theory in the
Landau gauge has been scrutinized with the help of Dyson-Schwinger equations
and lattice calculations. In this contribution, we describe a technically
simple approach to the deep infrared regime via Callan-Symanzik renormalization
group equations in an epsilon expansion. This approach recovers, in an
analytical and systematically improvable way, all the solutions previously
found as solutions of the Dyson-Schwinger equations and singles out the
solution favored by lattice calculations as the infrared-stable fixed point
(for space-time dimensions above two).


  These three metallic systems do not exhibit any magnetic ordering despite
experiments show the existence of localized moments with large
antiferromagnetic exchange: this is a consequence of the strong geometric
frustration (Y(Sc)Mn_{2} and LiV_{2}O_{4} have the Pyrochlore structure, while
beta-Mn has a more complicated frustrated structure). Another common feature is
their very large specific heat coefficient \gamma =C/T (420 mJ mole^{-1} K^{-2}
for LiV_{2}O_{4}). Several explanations have been proposed for this ''3d heavy
fermion behavior'', including a 3d-Kondo effect. However the similarities
between the three compounds indicate that frustration plays a big role. We
propose a new model which takes into account the existence of two types of
3d-electrons (localized and itinerant) and a frustrated antiferromagnetic
exchange between the localized 3d electrons.


  We continue to investigate various instabilities of the fixed backgrounds
related to the de Sitter space. It is shown that in many cases the in/in
perturbation theory contains IR/UV mixing and thus is non-renormalizible. The
application of this result to the global de Sitter space leads to the
conclusion that even massive particles generate IR divergence and the huge back
reaction. The expanding universe is also unstable but in a weaker sense. We
further discuss, the strange features of the Gibbons-Hawking radiation and its
relation to the above instabilities. .


  A wide variety of problems in machine learning, including exemplar
clustering, document summarization, and sensor placement, can be cast as
constrained submodular maximization problems. Unfortunately, the resulting
submodular optimization problems are often too large to be solved on a single
machine. We develop a simple distributed algorithm that is embarrassingly
parallel and it achieves provable, constant factor, worst-case approximation
guarantees. In our experiments, we demonstrate its efficiency in large problems
with different kinds of constraints with objective values always close to what
is achievable in the centralized setting.


  Inspired by regularization in quantum field theory, we study topological and
metric properties of spaces in which a cut-off is introduced. We work in the
framework of noncommutative geometry, and focus on Connes distance associated
to a spectral triple (A, H, D). A high momentum (short distance) cut-off is
implemented by the action of a projection P on the Dirac operator D and/or on
the algebra A. This action induces two new distances. We individuate conditions
making them equivalent to the original distance. We also study the
Gromov-Hausdorff limit of the set of truncated states, first for compact
quantum metric spaces in the sense of Rieffel, then for arbitrary spectral
triples. To this aim, we introduce a notion of "state with finite moment of
order 1" for noncommutative algebras. We then focus on the commutative case,
and show that the cut-off induces a minimal length between points, which is
infinite if P has finite rank. When P is a spectral projection of $D$, we work
out an approximation of points by non-pure states that are at finite distance
from each other. On the circle, such approximations are given by Fejer
probability distributions. Finally we apply the results to Moyal plane and the
fuzzy sphere, obtained as Berezin quantization of the plane and the sphere
respectively.


  We report results from the second and third seasons of observation with the
QUaD experiment. Angular power spectra of the Cosmic Microwave Background are
derived for both temperature and polarization at both 100 GHz and 150 GHz, and
as cross frequency spectra. All spectra are subjected to an extensive set of
jackknife tests to probe for possible systematic contamination. For the
implemented data cuts and processing technique such contamination is
undetectable. We analyze the difference map formed between the 100 and 150 GHz
bands and find no evidence of foreground contamination in polarization. The
spectra are then combined to form a single set of results which are shown to be
consistent with the prevailing LCDM model. The sensitivity of the polarization
results is considerably better than that of any previous experiment -- for the
first time multiple acoustic peaks are detected in the E-mode power spectrum at
high significance.


  Prior human parsing models are limited to parsing humans into classes
pre-defined in the training data, which is not flexible to generalize to unseen
classes, e.g., new clothing in fashion analysis. In this paper, we propose a
new problem named one-shot human parsing (OSHP) that requires to parse human
into an open set of reference classes defined by any single reference example.
During training, only base classes defined in the training set are exposed,
which can overlap with part of reference classes. In this paper, we devise a
novel Progressive One-shot Parsing network (POPNet) to address two critical
challenges , i.e., testing bias and small sizes. POPNet consists of two
collaborative metric learning modules named Attention Guidance Module and
Nearest Centroid Module, which can learn representative prototypes for base
classes and quickly transfer the ability to unseen classes during testing,
thereby reducing testing bias. Moreover, POPNet adopts a progressive human
parsing framework that can incorporate the learned knowledge of parent classes
at the coarse granularity to help recognize the descendant classes at the fine
granularity, thereby handling the small sizes issue. Experiments on the ATR-OS
benchmark tailored for OSHP demonstrate POPNet outperforms other representative
one-shot segmentation models by large margins and establishes a strong
baseline. Source code can be found at
https://github.com/Charleshhy/One-shot-Human-Parsing.


  It is natural to call the trinity of foreshocks, main shock and aftershocks a
classical triad. The magnitude of the main shock is always greater than the
maximum magnitudes of foreshocks and aftershocks. In the classical triad, the
number of foreshocks is less than the number of aftershocks. In many cases,
foreshocks are completely absent even before very strong earthquakes. In this
work, we found a rare but extremely interesting species of triad (we called it
the mirror triad), in which the number of foreshocks is greater than the number
of aftershocks at the interval of 24 h before and 24 h after the main shock.
Quite often, aftershocks are absent in mirror triads at all. In this paper, we
described the properties of mirror triads and made an attempt to understand
their origin. A schematic classification of tectonic triads is proposed.
Keywords: foreshock, main shock, aftershock, Gutenberg-Richter law, Bath law,
Omori law, solitary earthquake.


  We present the logic iJT4, which is an explicit version of intuitionistic S4
and establish soundness and completeness with respect to modular models.


  End-to-end learning-based video compression has made steady progress over the
last several years. However, unlike learning-based image coding, which has
already surpassed its handcrafted counterparts, learning-based video coding
still has some ways to go. In this paper we present learned conditional coding
modes for video coding (LCCM-VC), a video coding model that achieves
state-of-the-art results among learning-based video coding methods. Our model
utilizes conditional coding engines from the recent conditional augmented
normalizing flows (CANF) pipeline, and introduces additional coding modes to
improve compression performance. The compression efficiency is especially good
in the high-quality/high-bitrate range, which is important for broadcast and
video-on-demand streaming applications. The implementation of LCCM-VC is
available at https://github.com/hadihdz/lccm_vc


  The iterated monodromy group of a post-critically finite complex polynomial
of degree d \geq 2 acts naturally on the complete d-ary rooted tree T of
preimages of a generic point. This group, as well as its pro-finite completion,
act on the boundary of T, which is given by extending the branches to their
"ends" at infinity. We show that for nearly all polynomials, elements that have
fixed points on the boundary are rare, in that they belong to a set of Haar
measure zero. The exceptions are those polynomials linearly conjugate to
multiples of Chebyshev polynomials and a case that remains unresolved, where
the polynomial has a non-critical fixed point with many critical pre-images.
The proof involves a study of the finite automaton giving the action of
generators of the iterated monodromy group, and an application of a martingale
convergence theorem. Our result is motivated in part by applications to
arithmetic dynamics, where iterated monodromy groups furnish the "geometric
part" of certain Galois extensions encoding information about densities of
dynamically interesting sets of prime ideals.


  We consider small nonlinear perturbations of linear systems on a time scale
with the phase space being finite or infinite-dimensional. For
$\Delta$-differential operators, corresponding to linear dynamic systems we
consider their solvability in various functional spaces. Based on these
techniques, we prove several results on the existence of a bounded solution for
some systems with small nonlinearities. Thus we introduce some generalizations
of the classic hyperbolicity property (exponential dichotomy) for systems of
ordinary differential equations.
  Besides, we introduce the Lyapunov regularity condition that coincides with
the classic one for ordinary differential equations. For regular systems, we
prove some criteria for the existence of bounded solutions of perturbed
systems.


  (Abridged)The temperature (T) and entropy (S) fields of baryonic gas/IGM are
analyzed using simulation samples by a cosmological hydro/N-body code. We show
that in the nonlinear regime the dynamical similarity between the IGM and dark
matter will be broken by strong shocks. The heating and entropy production by
the shocks breaks the IGM into multiple phases. The mean entropy, or the
cosmological entropy floor, is found to be more than 100 h^(-1/3) keV cm^2 in
all regions when z < 1. At redshift z ~ 2 - 3, high-entropy gas (S > 50
h^(-1/3) keV cm^2) mostly resides in areas on scales larger than 1 h^(-1) Mpc
and with density $\rho_{dm}>10^2$. Therefore, gravitational shocks are an
effective preheating mechanism of the IGM, and probably enough to provide the
entropy excess of clusters and groups if the epoch of the gas falling in
cluster cores is not earlier than z ~ 2 - 3. On the other hand, at redshifts z
< 4, there is always a more than 90% volume of the low dark matter mass density
regions filled by the IGM with T < 10^4.5 K. Therefore, the multiphased
character and non-Gaussianity of the IGM field would explain the
high-temperature and high-entropy gas observed in groups and clusters.


  In this paper, a co-infection of malaria and visceral helminthiasis with
immune stimulation and impairment is studied. We have assumed that an
individual gets malaria infection during invasion by helminths larvae. In
absence of immune response, our results show that the antigens invade the blood
system if the rate of red cell rupture per invading merozoite is greater than
one. If fewer merozoites are released, the initial state is globally
asymptotically stable. If more merozoites are released, there exists
malaria-only endemic point. However, both antigens coexist if the mean
infection burden is greater than one. In this case, there is a threshold value
for drug action below which no recovery of host is expected. In presence of
immune response, three equilibrium states exist. The initial invasion state,
and secondly, the unstable state when the immune population has been triggered
and the antigens have been eliminated. The third state represents the endemic
state which is stable if the infection-induced rupture rate per erythrocyte
with immune activation is less than the total mortality of the erythrocytes. A
model for severity of the co-infection shows that an immune response will be
delayed until immunological barrier values for malaria and helminths are
exceeded.


  Various datasets have been proposed for simultaneous localization and mapping
(SLAM) and related problems. Existing datasets often include small
environments, have incomplete ground truth, or lack important sensor data, such
as depth and infrared images. We propose an easy-to-use framework for acquiring
building-scale 3D reconstruction using a consumer depth camera. Unlike complex
and expensive acquisition setups, our system enables crowd-sourcing, which can
greatly benefit data-hungry algorithms. Compared to similar systems, we utilize
raw depth maps for odometry computation and loop closure refinement which
results in better reconstructions. We acquire a building-scale 3D dataset
(BS3D) and demonstrate its value by training an improved monocular depth
estimation model. As a unique experiment, we benchmark visual-inertial odometry
methods using both color and active infrared images.


  Co-evolution is a powerful problem-solving approach. However, fitness
evaluation in co-evolutionary algorithms can be computationally expensive, as
the quality of an individual in one population is defined by its interactions
with many (or all) members of one or more other populations. To accelerate
co-evolutionary systems, we introduce phylogeny-informed interaction
estimation, which uses runtime phylogenetic analysis to estimate interaction
outcomes between individuals based on how their relatives performed against
each other. We test our interaction estimation method with three distinct
co-evolutionary systems: two systems focused on measuring problem-solving
success and one focused on measuring evolutionary open-endedness. We find that
phylogeny-informed estimation can substantially reduce the computation required
to solve problems, particularly at the beginning of long-term evolutionary
runs. Additionally, we find that our estimation method initially jump-starts
the evolution of neural complexity in our open-ended domain, but
estimation-free systems eventually "catch-up" if given enough time. More
broadly, continued refinements to these phylogeny-informed interaction
estimation methods offers a promising path to reducing the computational cost
of running co-evolutionary systems while maintaining their open-endedness.


  The complementary strands of DNA molecules can be separated when stretched
apart by a force; the unzipping signal is correlated to the base content of the
sequence but is affected by thermal and instrumental noise. We consider here
the ideal case where opening events are known to a very good time resolution
(very large bandwidth), and study how the sequence can be reconstructed from
the unzipping data. Our approach relies on the use of statistical Bayesian
inference and of Viterbi decoding algorithm. Performances are studied
numerically on Monte Carlo generated data, and analytically. We show how
multiple unzippings of the same molecule may be exploited to improve the
quality of the prediction, and calculate analytically the number of required
unzippings as a function of the bandwidth, the sequence content, the elasticity
parameters of the unzipped strands.


  The concept of a Magnetic Resonance Imaging (MRI) device is based on the
emission of radio waves produced by the protons of the hydrogen atoms in water
molecules when placed in a constant magnetic field after they interact with a
pulsed radio frequency (RF) current. When the RF field is turned on, the
protons are brought to a spin excited state. When the RF field is turned off,
the MRI sensors are able to detect the energy released as the protons realign
their spins with the magnetic field. In this work we provide a simple model to
describe the basic physical mechanism responsible for the operation of MRI
devices. We model the water molecule in terms of a central force problem, where
the protons move around the (unstructured) doubly negatively charged oxygen
atom. First, we employ an analytical treatment to obtain the system's wave
function as well as its energy levels, which we show are degenerate. Next, the
energy levels from the water molecule are studied in the presence of a uniform
external magnetic field. As a result, they get shifted and the degeneration is
lifted. We provide numerical results for a magnetic field strength commonly
used in MRI devices.


  Z' exclusion limits and errors of Z' model measurements are compared for
different reactions at future linear colliders. The influence of the c.m.
energy, integrated luminosity, beam polarization and systematic errors is
discussed. The sensitivity to a Z' depends only on the product Ls and not on
the integrated luminosity and the c.m. energy separately.


  A classical problem in analytic number theory is to study the distribution of
fractional part $\alpha p^k+\beta,\,k\ge 1$ modulo 1, where $\alpha$ is
irrational and $p$ runs over the set of primes. For $k=2$ we consider the
subsequence generated by the primes $p$ such that $p+2$ is an almost-prime (the
existence of infinitely many such $p$ is another topical result in prime number
theory) and prove that its distribution has a similar property.


  This paper describes a new method, HGV2C, for pattern analysis. The HGV2C
method involves the construction of a computer ego (CE) based on an individual
object that can be either a part of the system under analysis or a newly
created object based on a certain hypothesis. The CE provides a capability to
analyze data from a specific standpoint, e.g. from a viewpoint of a certain
object. The CE is constructed from two identical copies of a query object, and
its functioning mechanism involves: a hypothesis-parameter (HP) and
infothyristor (IT). HP is a parameter that is introduced into an existing set
of parameters. The HP value for one of the clones of a query object is set to
equal 1, whereas for another clone it is greater than 1. The IT is based on the
previously described algorithm of iterative averaging and performs three
functions: 1) computation of a similarity matrix for the group of three objects
including two clones of a query object and a target object; 2) division of the
group into two alternative subgroups; and 3) a successive increase of the HP
weight in the totality of all the parameters. Initially, both clones of the
query object appear together in one of the subgroups as all of their parameter
values, except the HP, are identical. At a certain point of the HP
multiplication, one of the clones moves to the group of the target object. A
respective number of the HP multiplications represents the dissimilarity (D)
between the query and target objects. The product of D multiplied by the
difference in HP values of the clones is strictly constant and linearly
increases as the difference in HP values of the clones decreases. This new
approach to knowledge representation is demonstrated on the example of
population pyramids of 220 countries.


  We prove the following uniqueness result for the buckling plate. Assume there
exists a smooth domain which minimizes the first buckling eigenvalue for a
plate among all smooth domains of given volume. Then the domain must be a ball.
The proof uses the second variation for the buckling eigenvalue and an
inequality by L. E. Payne to establish this result.


  We have studied the phonon specific heat in single-layer, bilayer and twisted
bilayer graphene. The calculations were performed using the Born-von Karman
model of lattice dynamics for intralayer atomic interactions and spherically
symmetric interatomic potential for interlayer interactions. We found that at
temperature T<15 K, specific heat varies with temperature as T^n, where n = 1
for graphene, n = 1.6 for bilayer graphene and n = 1.3 for the twisted bilayer
graphene. The phonon specific heat reveals an intriguing dependence on the
twist angle in bilayer graphene, which is particularly pronounced at low
temperature. The results suggest a possibility of phonon engineering of thermal
properties of layered materials by twisting the atomic planes.


  A uniqueness result for the recovery of the electric and magnetic
coefficients in the time-harmonic Maxwell equations from local boundary
measurements is proven. No special geometrical condition is imposed on the
inaccessible part of the boundary of the domain, apart from imposing that the
boundary of the domain is $C^{1,1}$. The coefficients are assumed to coincide
on a neighbourhood of the boundary, a natural property in applications.


  A target using a paisley pattern generates 100-kT-level magnetic fields.
Laser irradiation induces local charge separation on the target, which creates
surface currents along the concave surface, generating a magnetic field. For a
laser intensity of $10^{21}$ W/cm$^2$, the target generates a 150-kT magnetic
field. We developed a simple model to describe the magnetic field as a function
of laser intensity and target radius. A double paisley configuration extends
the lifetime of the magnetic field to the picosecond scale. The paisley design
generates comparable results even if it is simplified. Thus, it is a robust and
modular target suitable for magnetic field applications such as 100-kT magnetic
field generation and magnetic reconnection.


  To measure the supernova (SN) rates at intermediate redshift we performed the
Southern inTermediate Redshift ESO Supernova Search (STRESS). Unlike most of
the current high redshift SN searches, this survey was specifically designed to
estimate the rate for both type Ia and core collapse (CC) SNe. We counted the
SNe discovered in a selected galaxy sample measuring SN rate per unit blue band
luminosity. Our analysis is based on a sample of ~43000 galaxies and on 25
spectroscopically confirmed SNe plus 64 selected SN candidates. Our approach is
aimed at obtaining a direct comparison of the high redshift and local rates and
at investigating the dependence of the rates on specific galaxy properties,
most notably their colour. The type Ia SN rate, at mean redshift z=0.3, amounts
to 0.22^{+0.10+0.16}_{-0.08 -0.14} h_{70}^2 SNu, while the CC SN rate, at
z=0.21, is 0.82^{+0.31 +0.30}_{-0.24 -0.26} h_{70}^2 SNu. The quoted errors are
the statistical and systematic uncertainties. With respect to local value, the
CC SN rate at z=0.2 is higher by a factor of ~2 already at redshift, whereas
the type Ia SN rate remains almost constant. This implies that a significant
fraction of SN Ia progenitors has a lifetime longer than 2-3 Gyr. We also
measured the SN rates in the red and blue galaxies and found that the SN Ia
rate seems to be constant in galaxies of different colour, whereas the CC SN
rate seems to peak in blue galaxies, as in the local Universe. SN rates per
unit volume were found to be consistent with other measurements showing a
steeper evolution with redshift for CC SNe with respect to SNe Ia. Finally we
have exploited the link between star formation (SF) and SN rates to predict the
evolutionary behaviour of the SN rates and compare it with the path indicated
by observations.


  Successful transfer of the results of research projects into practice is of
great interest to all project participants. It can be assumed that different
transfer mediums fulfill technology transfer (TT) with different levels of
success and that they are impaired by different kinds of barriers. The goal of
this study is to gain a better understanding about the different mediums used
for TT in software engineering, and to identify barriers weakening the success
of the application of such mediums. We conducted an exploratory study
implemented by a survey in the context of a German research project with a
broad range of used mediums. The main reported barriers were low expectations
of usefulness, no awareness of existence, lack of resources, or inadequateness
in terms of outdated material or being in an immature state. We interpreted our
results as symptoms of a lack of a dissemination plan in the project. Further
work will be needed to explore the implications for the transfer of research
results (knowledge and techniques) to practice.


  For a root system R, a field K and a "choice of coefficients in K" we define
a category of graded spaces with operators and study some of its properties.
Then we assume that the coefficients are given by quantum binomials. We use
basic arithmetic properties of binomial coefficients (such as q-versions of
Lucas' theorem and the Pfaff-Saalsch\"utz identity) to construct a Frobenius
pull back functor and prove a Steinberg's tensor product formula. Then we show
that these results imply the corresponding results for reductive algebraic
groups in positive characteristics and for quantum groups at roots of unity.


  With the rapid development of information transmission, Software as a Service
(SaaS) is developing at a rapid speed that everything originally local tends to
be transplanted onto servers and executed on the cloud. WebGPU is such a SaaS
system that it holds the GPU-equipped server to execute students' CUDA code and
releases the RESTful front-end website for students to write their code on.
However, programming on an HTML-based interface is not satisfactory due to a
lack of syntax highlighting and automatic keyword complement. On the other
side, Visual Studio Code is now becoming the most popular programming interface
due to its strong community and eclectic functionalities. Thus, we propose such
a system that, students write code locally using VS Code with its
coding-auxiliary extensions, and push the code to WebGPU with only one button
pressed using our VSC-WebGPU extension. The extension is divided into 4 parts:
the login process for automatically logging the student into WebGPU, the pull
process that pulls the code down to the local workspace, the push process that
copies the code to the browser for compiling and running, and the exit process
to exit the browser and close the connection. This 4-step architecture is also
applicable for any other automated tools to push local code to
authorization-required SaaS systems using Web automata.


  IceCube is a 1 km^3 neutrino detector now being built at the Amundsen-Scott
South Pole Station. It consists of 4800 Digital Optical Modules (DOMs) which
detect Cherenkov radiation from the charged particles produced in neutrino
interactions. IceCube will observe astrophysical neutrinos with energies above
about 100 GeV. IceCube will be able to separate \nu_\mu, \nu_e and \nu_\tau
interactions because of their different topologies. IceCube construction is
currently 50% complete.


  A bipartite graph $G=(U,V,E)$ is convex if the vertices in $V$ can be
linearly ordered such that for each vertex $u\in U$, the neighbors of $u$ are
consecutive in the ordering of $V$. An induced matching $H$ of $G$ is a
matching such that no edge of $E$ connects endpoints of two different edges of
$H$. We show that in a convex bipartite graph with $n$ vertices and $m$
weighted edges, an induced matching of maximum total weight can be computed in
$O(n+m)$ time. An unweighted convex bipartite graph has a representation of
size $O(n)$ that records for each vertex $u\in U$ the first and last neighbor
in the ordering of $V$. Given such a compact representation, we compute an
induced matching of maximum cardinality in $O(n)$ time.
  In convex bipartite graphs, maximum-cardinality induced matchings are dual to
minimum chain covers. A chain cover is a covering of the edge set by chain
subgraphs, that is, subgraphs that do not contain induced matchings of more
than one edge. Given a compact representation, we compute a representation of a
minimum chain cover in $O(n)$ time. If no compact representation is given, the
cover can be computed in $O(n+m)$ time.
  All of our algorithms achieve optimal running time for the respective problem
and model. Previous algorithms considered only the unweighted case, and the
best algorithm for computing a maximum-cardinality induced matching or a
minimum chain cover in a convex bipartite graph had a running time of $O(n^2)$.


  Recent theoretical investigations have indicated that rapid optical cycling
should be feasible in complex polyatomic molecules with diverse constituents,
geometries and symmetries. However, as a composite molecular mass grows, so
does the required number of photon scattering events necessary to decelerate
and confine molecular beams using laser light. Utilizing coherent momentum
exchange between light fields and molecules can suppress spontaneous emission
and significantly reduce experimental complexity for slowing and trapping.
Working with BaH as a test species, we have identified a robust, experimentally
viable configuration to achieve large molasses-like cooling forces for
molecules using polychromatic optical fields addressing both $X-A$ and $X-B$
electronic transitions, simultaneously. Using numerical solutions of the
time-dependent density matrix as well as Monte Carlo simulations, we
demonstrate that creation of Suppressed Emission Rate (SupER) molasses with
large capture velocities ($\sim 40$ m/s) is generically feasible for polyatomic
molecules of increasing complexity that have an optical cycling center.
Proposed SupER molasses are anticipated to not only extend quantum control to
novel molecular species with abundant vibrational decay channels, but also
significantly increase trapped densities for previously laser-cooled diatomic
and triatomic species.


  We examine whether the spectral energy distribution of UV continuum emission
of active galactic nuclei changes during flux variation. We used multi-epoch
photometric data of QSOs in the Stripe 82 observed by the SDSS Legacy Survey
and selected 10 bright QSOs observed with high photometric accuracies, in the
redshift range of z = 1.0-2.4 where strong broad emission lines such as
Ly\alpha and CIV do not contaminate SDSS filters, to examine spectral variation
of the UV continuum emission with broadband photometries. All target QSOs
showed clear flux variations during the monitoring period 1998-2007, and the
multi-epoch flux data in two different bands obtained on the same night showed
a linear flux-to-flux relationship for all target QSOs. Assigning the flux in
the longer wavelength to the x-axis in the flux-to-flux diagram, the
x-intercept of the best-fit linear regression line was positive for most
targets, which means that their colors in the observing bands become bluer as
they become brighter. Then, the host-galaxy flux was estimated on the basis of
the correlation between the stellar mass of the bulge of the host galaxy and
the central black hole mass. We found that the longer-wavelength flux of the
host galaxy was systematically smaller than that of the fainter extension of
the best-fit regression line at the same shorter-wavelength flux for most
targets. This result strongly indicates that the spectral shape of the
continuum emission of QSOs in the UV region usually becomes bluer as it becomes
brighter. We found that the multi-epoch flux-to-flux plots could be fitted well
with the standard accretion disk model changing the mass accretion rate with a
constant black hole mass for most targets. This finding strongly supports the
standard accretion disk model for UV continuum emission of QSOs.


  These notes are from the Database of Automorphic L-functions at
http://www.math.rutgers.edu/~sdmiller/l-functions . They were written up by
Stephen Miller, and are based on discussions with Freydoon Shahidi, Purdue
University. They are meant to serve as an introduction to the Langlands-Shahidi
method of studying L-functions through the Fourier coefficients of Eisenstein
series.


  We consider linear Hamiltonian equations in $\mathbb{R}^{4}$ of the following
type \begin{equation}
  \frac{\mathrm{d}\gamma}{\mathrm{d}t}(t)=J_{4}A(t)\gamma(t),
\gamma(0)\in\operatorname{Sp}(4,\mathbb{R}), \end{equation} where
$J=J_{4}\overset{\text{def}}{=}\begin{bmatrix}0 &
\operatorname{Id}_2\\-\operatorname{Id}_2 & 0\end{bmatrix}$ and $A:t\mapsto
A(t)$ is a $C^1$-continuous curve in the space of $4\times 4$ real matrices
which are symmetric. We obtain second order asymptotics for the eigenvalues
bifurcated from non-real Krein indefinite eigenvalues with multiplicity two.


  One of the main objectives of cloud computing providers is increasing the
revenue of their cloud datacenters by accommodating virtual network requests as
many as possible. However, arrival and departure of virtual network requests
fragment physical network's resources and reduce the possibility of accepting
more virtual network requests. To increase the number of virtual network
requests accommodated by fragmented physical networks, we propose two virtual
network embedding algorithms, which coarsen virtual networks using Heavy Edge
Matching (HEM) technique and embed coarsened virtual networks on best-fit
sub-substrate networks. The performance of the proposed algorithms are
evaluated and compared with existing algorithms using extensive simulations,
which show that the proposed algorithms increase the acceptance ratio and the
revenue.


  We consider effective actions of a compact torus $T^{n-1}$ on an
even-dimensional smooth manifold $M^{2n}$ with isolated fixed points. We prove
that under certain conditions on weights of tangent representations, the orbit
space is a manifold with corners. Given that the action is Hamiltonian, the
orbit space is homeomorphic to $S^{n+1} \setminus (U_1 \sqcup \ldots \sqcup
U_l)$ where $S^{n+1}$ is the $(n+1)$--sphere and $U_1, \ldots, U_l$ are open
domains. We apply the results to regular Hessenberg varieties and manifolds of
isospectral Hermitian matrices of staircase form.


  This study investigates measurement strategies in a scenario where multiple
pairs of Alices and Bobs independently and sequentially observe entangled
states. The aim is to maximize the number of observer pairs $(A_k,B_l)$ that
can witness entanglement. Prior research has demonstrated that arbitrary pairs
$(A_k, B_k)$ ($k\leq n$) can observe entanglement in all pure entangled states
and a specific class of mixed entangled states [Phys. Rev. A 106 032419
(2022)]. However, it should be noted that other pairs $(A_k, B_l)$ with $(k\neq
l \leq n)$ may not observe entanglement using the same strategy. Moreover, a
novel strategy is presented, enabling every pair of arbitrarily many Alices and
Bobs to witness entanglement regardless of the initial state being a Bell state
or a particular class of mixed entangled states. These findings contribute to
understanding measurement strategies for maximizing entanglement observation in
various contexts.


  The Open Whisper-style Speech Model (OWSM) series was introduced to achieve
full transparency in building advanced speech-to-text (S2T) foundation models.
To this end, OWSM models are trained on 25 public speech datasets, which are
heterogeneous in multiple ways. In this study, we advance the OWSM series by
introducing OWSM v3.2, which improves on prior models by investigating and
addressing the impacts of this data heterogeneity. Our study begins with a
detailed analysis of each dataset, from which we derive two key strategies:
data filtering with proxy task to enhance data quality, and the incorporation
of punctuation and true-casing using an open large language model (LLM). With
all other configurations staying the same, OWSM v3.2 improves performance over
the OWSM v3.1 baseline while using 15% less training data.