  The first measurement of dielectron ($\mathrm{e}^{+}\mathrm{e}^{-}$)
production in central (0$-$10$\%$) Pb-Pb collisions at
$\mathbf{\sqrt{{\textit{s}}_{\mathrm{NN}}}}$ = 2.76 TeV at the LHC is
presented. The dielectron invariant-mass spectrum is compared to the expected
contributions from hadron decays in the invariant-mass range $0 <
m_{\mathrm{ee}}<3.5\ \mathrm{GeV}/\textit{c}^{2}$. The ratio of data and the
cocktail of hadronic contributions without vacuum $\rho^{0}$ is measured in the
invariant-mass range $0.15 < m_{\mathrm{ee}}<0.7\ \mathrm{GeV}/\textit{c}^{2}$,
where an excess of dielectrons is observed in other experiments, and its value
is $1.40 \pm 0.28\ (\mathrm{stat.}) \pm 0.08\ (\mathrm{syst.}) \pm 0.27\
(\mathrm{cocktail})$. The dielectron spectrum measured in the invariant mass
range $0 < m_{\mathrm{ee}}<1\ \mathrm{GeV}/\textit{c}^{2}$ is consistent with
the predictions from two theoretical model calculations that include thermal
dielectron production from both partonic and hadronic phases with in-medium
broadened $\rho^{0}$ meson. The fraction of direct virtual photons over
inclusive virtual photons is extracted for dielectron pairs with invariant mass
$0.1 < m_{\mathrm{ee}}<0.3\ \mathrm{GeV}/\textit{c}^{2}$, and in the
transverse-momentum intervals $1<p_{\mathrm{T}, \mathrm{ee}}<2\
\mathrm{GeV}/\textit{c}$ and $2<p_{\mathrm{T}, \mathrm{ee}}<4\
\mathrm{GeV}/\textit{c}$. The measured fraction of virtual direct photons is
consistent with the measurement of real direct photons by ALICE and with the
expectations from previous dielectron measurements at RHIC within the
experimental uncertainties.


  Major advancements in building general-purpose and customized hardware have
been one of the key enablers of versatility and pervasiveness of machine
learning models such as deep neural networks. To sustain this ubiquitous
deployment of machine learning models and cope with their computational and
storage complexity, several solutions such as low-precision representation of
model parameters using fixed-point representation and deploying approximate
arithmetic operations have been employed. Studying the potency of such
solutions in different applications requires integrating them into existing
machine learning frameworks for high-level simulations as well as implementing
them in hardware to analyze their effects on power/energy dissipation,
throughput, and chip area. Lop is a library for design space exploration that
bridges the gap between machine learning and efficient hardware realization. It
comprises a Python module, which can be integrated with some of the existing
machine learning frameworks and implements various customizable data
representations including fixed-point and floating-point as well as approximate
arithmetic operations.Furthermore, it includes a highly-parameterized Scala
module, which allows synthesizing hardware based on the said data
representations and arithmetic operations. Lop allows researchers and designers
to quickly compare quality of their models using various data representations
and arithmetic operations in Python and contrast the hardware cost of viable
representations by synthesizing them on their target platforms (e.g., FPGA or
ASIC). To the best of our knowledge, Lop is the first library that allows both
software simulation and hardware realization using customized data
representations and approximate computing techniques.


  Accurate evaluation of financial question answering (QA) systems necessitates
a comprehensive dataset encompassing diverse question types and contexts.
However, current financial QA datasets lack scope diversity and question
complexity. This work introduces FinTextQA, a novel dataset for long-form
question answering (LFQA) in finance. FinTextQA comprises 1,262 high-quality,
source-attributed QA pairs extracted and selected from finance textbooks and
government agency websites.Moreover, we developed a Retrieval-Augmented
Generation (RAG)-based LFQA system, comprising an embedder, retriever,
reranker, and generator. A multi-faceted evaluation approach, including human
ranking, automatic metrics, and GPT-4 scoring, was employed to benchmark the
performance of different LFQA system configurations under heightened noisy
conditions. The results indicate that: (1) Among all compared generators,
Baichuan2-7B competes closely with GPT-3.5-turbo in accuracy score; (2) The
most effective system configuration on our dataset involved setting the
embedder, retriever, reranker, and generator as Ada2, Automated Merged
Retrieval, Bge-Reranker-Base, and Baichuan2-7B, respectively; (3) models are
less susceptible to noise after the length of contexts reaching a specific
threshold.


  We find that the simple coupling of network growth to the position of a
random walker on the network generates a traveling wave in the probability
distribution of nodes visited by the walker. We argue that the entropy of this
probability distribution is bounded as the network size tends to infinity. This
means that the growth of a space coupled to a random walker situated in it
constrains its dynamics to a set of typical random walker trajectories, and
walker trajectories inside the growing space are compressible.


  We introduce a new formulation of baryon chiral perturbation theory which
improves the ultraviolet behavior of propagators and can be interpreted as a
smooth cutoff regularization scheme. It is equivalent to the standard approach,
preserves all symmetries and therefore satisfies the Ward identities. Our
formulation is equally well defined in the vacuum, one- and few-nucleon sectors
of the theory. The equations (Bethe-Salpeter, Lippmann-Schwinger, etc.) for the
scattering amplitudes of the few-nucleon sector are free of divergences in the
new approach. Unlike the usual cutoff regularization, our 'cutoffs' are
parameters of the Lagrangian and do not have to be removed.


  For the first time both H$\alpha$ and far-ultraviolet (FUV) observations from
an HI-selected sample are used to determine the dust-corrected star formation
rate density (SFRD: $\dot{\rho}$) in the local Universe. Applying the two star
formation rate indicators on 294 local galaxies we determine log($\dot{\rho}$$
_{H\alpha}) = -1.68~^{+0.13}_{-0.05}$ [M$_{\odot} $ yr$^{-1} $ Mpc$^{-3}]$ and
log($\dot{\rho}_{FUV}$) $ = -1.71~^{+0.12}_{-0.13}$ [M$_\odot $ yr$^{-1} $
Mpc$^{-3}]$. These values are derived from scaling H$\alpha$ and FUV
observations to the HI mass function. Galaxies were selected to uniformly
sample the full HI mass (M$_{HI}$) range of the HI Parkes All-Sky Survey
(M$_{HI} \sim10^{7}$ to $\sim10^{10.7}$ M$_{\odot}$). The approach leads to
relatively larger sampling of dwarf galaxies compared to optically-selected
surveys. The low HI mass, low luminosity and low surface brightness galaxy
populations have, on average, lower H$\alpha$/FUV flux ratios than the
remaining galaxy populations, consistent with the earlier results of Meurer.
The near-identical H$\alpha$- and FUV-derived SFRD values arise with the low
H$\alpha$/FUV flux ratios of some galaxies being offset by enhanced H$\alpha$
from the brightest and high mass galaxy populations. Our findings confirm the
necessity to fully sample the HI mass range for a complete census of local star
formation to include lower stellar mass galaxies which dominate the local
Universe.


  A T6 orbifold compactification is discussed from the somewhat unconventional
perspective as the large radius limit of a Landau-Ginzburg model. The features
of the model are in principle familiar, but the way they enter here is
different from the way they enter when using more commonly used methods. It is
hoped that the point of view presented here can supplement the understanding of
the features used in string compactifications, notably in terms of naturalness
and completeness. More precisely, the analyzed T6 / Z_4 x Z_4 features two
different kinds of O-planes, branes in the bulk as well as fractional branes,
continuous and discrete Wilson lines as well as an orientifold action which can
act in different ways on the Wilson lines. The D-branes are desribed by matrix
factorizations. This work is also intended to be a showcase for the potentials
of matrix factorizations which are for the first time geared to their full
level of sophistication in this paper. Throughout the analyis everything is
mapped from the B-model side of the LG-model to the A side by mirror symmetry.
The work could be extended straightforwardly yet tediously to perform mirror
symmetry on a general intersecting brane configuration and to compute Yukawa
couplings. The analysis presented here can also be applied to non-toroidal
backgrounds with an intersecting brane configuration on it, so I hope that it
will be a helpful basis for later applications of mirror symmetry to models
exhibiting real world properties.


  We apply computational seismic holography to high-frequency helioseismic
observations of the quiet Sun from SDO/HMI to locate predominant sources of
seismic emission with respect to the structure of the solar granulation. The
regions of greatest seismic emission are the edges of photospheric granules.
Seismic emission from regions whose continuum brightnesses are 95-100% of the
mean, as resolved by HMI, are about 2.5 times as emissive as regions whose
brightnesses are 100-104% of the mean. The greater seismic emissivity from
regions whose brightnesses are somewhat less than the mean is roughly in line
with expectations from an understanding that attributes most seismic emission
to cool plumes plummeting from the edges of granules. However, seismic emission
from regions whose continuum brightnesses significantly exceed 104% of the mean
is also remarkably high. This unexpected feature of high-frequency seismic
emission from the solar granulation begs to be understood.


  This article gives the structure of all projective indecomposable modules in
blocks with non-cyclic defect group for $n\leq 11$, and almost all in the case
of $n=12$, leaving four simple modules for $p=2$ and one simple module for
$p=3$.


  We compute the one-dimensional configuration sums of the ABF model using the
fermionic technique introduced in part I of this paper. Combined with the
results of Andrews, Baxter and Forrester, we find proof of polynomial
identities for finitizations of the Virasoro characters
$\chi_{b,a}^{(r-1,r)}(q)$ as conjectured by Melzer. In the thermodynamic limit
these identities reproduce Rogers--Ramanujan type identities for the unitary
minimal Virasoro characters, conjectured by the Stony Brook group. We also
present a list of additional Virasoro character identities which follow from
our proof of Melzer's identities and application of Bailey's lemma.


  We show how theoretical, principally lattice, calculations of the scalar form
factors in semileptonic pseudoscalar-to-pseudoscalar decays can be used to
extract information about the corresponding elastic s-wave scattering channels.
We find values for the scattering lengths m_pi a = 0.179(17)(14), 0.26(26) and
0.29(4) for elastic s-wave isospin-1/2 K pi, B pi and D pi channels
respectively. We also determine phase shifts. For the D K channel we find hints
that there is a bound state which can be identified with the recently
discovered D_{s0}^+(2317).


  We obtain higher order necessary conditions for a minimum of a Mayer optimal
control problem connected with a nonlinear, control-affine system, where the
controls range on an m-dimensional Euclidean space. Since the allowed
velocities are unbounded and the absence of coercivity assumptions makes big
speeds quite likely, minimizing sequences happen to converge toward
"impulsive", namely discontinuous, trajectories. As is known, a distributional
approach does not make sense in such a nonlinear setting, where instead a
suitable embedding in the graph space is needed. We will illustrate how the
chance of using impulse perturbations makes it possible to derive a Higher
Order Maximum Principle which includes both the usual needle variations (in
space-time) and conditions involving iterated Lie brackets. An example, where a
third order necessary condition rules out the optimality of a given extremal,
concludes the paper.


  The recent progress made in Galactic gamma-ray astronomy using the High
Energy Stereoskopic System (H.E.S.S.) instrument provides for the first time a
population of Galactic TeV gamma-rays, and hence potential neutrino sources,
for which the neutrino flux can be estimated. Using the energy spectra and
source morphologies measured by H.E.S.S., together with new parameterisations
of pion production and decay in hadronic interactions, we estimate the signal
and background rates expected for these sources in a first-generation water
Cherenkov detector (ANTARES) and a next-generation neutrino telescope in the
Mediterranean Sea, KM3NeT, with an instrumented volume of 1 km^3. We find that
the brightest gamma-ray sources produce neutrino rates above 1 TeV, comparable
to the background from atmospheric neutrinos. The expected event rates of the
brightest sources in the ANTARES detector make a detection unlikely. However,
for a 1 km^3 KM3NeT detector, event rates of a few neutrinos per year from
these sources are expected, and the detection of individual sources seems
possible. Although generally these estimates should be taken as flux upper
limits, we discuss the conditions and type of gamma-ray sources for which the
neutrino flux predictions can be considered robust.


  An analytic model of the shear modulus applicable at temperatures up to melt
and at all densities is presented. It is based in part on a relation between
the melting temperature and the shear modulus at melt. Experimental data on
argon are shown to agree with this relation to within 1%. The model of the
shear modulus involves seven parameters, all of which can be determined from
zero-pressure experimental data. We obtain the values of these parameters for
11 elemental solids. Both the experimental data on the room-temperature shear
modulus of argon to compressions of \sim 2.5, and theoretical calculations of
the zero-temperature shear modulus of aluminum to compressions of \sim 3.5 are
in good agreement with the model. Electronic structure calculations of the
shear moduli of copper and gold to compressions of 2, performed by us, agree
with the model to within uncertainties.


  In hep-th/0506040 we discussed a classically constrained model of gravity.
This theory contains known solutions of General Relativity (GR), and admits
solutions that are absent in GR. Here we study cosmological implications of
some of these new solutions. We show that a spatially-flat de Sitter universe
can be created from ``nothing''. This universe has boundaries, and its total
energy equals to zero. Although the probability to create such a universe is
exponentially suppressed, it favors initial conditions suitable for inflation.
Then we discuss a finite-energy solution with a nonzero cosmological constant
and zero space-time curvature. There is no tunneling suppression to fluctuate
into this state. We show that for a positive cosmological constant this state
is unstable -- it can rapidly transition to a de Sitter universe providing a
new unsuppressed channel for inflation. For a negative cosmological constant
the space-time flat solutions is stable.


  We relate a part of the abelian etale fundamental group of curves over local
fields to the component group of the Neron model of the jacobian. We apply the
result to the modular curve X_0(p)/Q_p to show that the unramified abelian
covering X_1(p) over X_0(p) (Shimura covering) uses up all the possible
ramification over the special fiber of X_0(p).


  The Mixture-of-Experts (MoE) has gained increasing attention in studying
Large Vision-Language Models (LVLMs). It uses a sparse model to replace the
dense model, achieving comparable performance while activating fewer parameters
during inference, thus significantly reducing the inference cost. Existing MoE
methods in LVLMs encourage different experts to handle different tokens, and
they usually employ a router to predict the routing of each token. However, the
predictions are based solely on sample features and do not truly reveal the
optimization directions of tokens. This may lead to severe optimization
interference between different tokens assigned to an expert. To address this
problem, this paper proposes a novel method based on token-level gradient
analysis, i.e., Solving Token Gradient Conflict (STGC). Specifically, we first
use token-level gradients to identify conflicting tokens in experts. After
that, we add a specialized loss tailored to eliminate conflicts among tokens
within each expert. Our method can serve as a plug-in for diverse Large
Vision-Language Models, and extensive experimental results demonstrate its
effectiveness. The code will be publicly available at
https://github.com/longrongyang/STGC.


  This paper introduces a methodology to develop energy models for the design
space exploration of embedded many-core systems. The design process of such
systems can benefit from sophisticated models. Software and hardware can be
specifically optimized based on comprehensive knowledge about application
scenario and hardware behavior. The contribution of our work is an automated
framework to estimate the energy consumption at an arbitrary abstraction level
without the need to provide further information about the system. We validated
our framework with the configurable many-core system CoreVA-MPSoC. Compared to
a simulation of the CoreVA-MPSoC on gate level in a 28nm FD-SOI standard cell
technology, our framework shows an average estimation error of about 4%.


  In a general graph data structure like an adjacency matrix, when edges are
homogeneous, the connectivity of two nodes can be sufficiently represented
using a single bit. This insight has, however, not yet been adequately
exploited by the existing matrix-centric graph processing frameworks. This work
fills the void by systematically exploring the bit-level representation of
graphs and the corresponding optimizations to the graph operations. It proposes
a two-level representation named Bit-Block Compressed Sparse Row (B2SR) and
presents a series of optimizations to the graph operations on B2SR by
leveraging the intrinsics of modern GPUs. Evaluations on NVIDIA Pascal and
Volta GPUs show that the optimizations bring up to $40\times$ and $6555\times$
for essential GraphBLAS kernels SpMV and SpGEMM, respectively, making
GraphBLAS-based BFS accelerate up to $433\times$, SSSP, PR, and CC up to
$35\times$, and TC up to $52\times$.


  Active materials are capable of converting free energy into mechanical work
to produce autonomous motion, and exhibit striking collective dynamics that
biology relies on for essential functions. Controlling those dynamics and
transport in synthetic systems has been particularly challenging. Here, we
introduce the concept of spatially structured activity as a means to control
and manipulate transport in active nematic liquid crystals consisting of actin
filaments and light-sensitive myosin motors. Simulations and experiments are
used to demonstrate that topological defects can be generated at will, and then
constrained to move along specified trajectories, by inducing local stresses in
an otherwise passive material. These results provide a foundation for design of
autonomous and reconfigurable microfluidic systems where transport is
controlled by modulating activity with light.


  RNA secondary structure prediction and classification are two important
problems in the field of RNA biology. Here, we propose a new permutation based
approach to create logical non-disjoint clusters of different secondary
structures of a single class or type. Many different types of techniques exist
to classify RNA secondary structure data but none of them have ever used
permutation based approach which is very simple and yet powerful. We have
written a small JAVA program to generate permutation, apply our algorithm on
those permutations and analyze the data and create different logical clusters.
We believe that these clusters can be utilized to untangle the mystery of RNA
secondary structure and analyze the development patterns of unknown RNA.


  We establish a regularity result for the metric on any 4-dimensional extremal
K\"ahler manifold, and a weak compactness theorem on the space of such metrics.
Specifically, the sectional curvature at a point is bounded when the quantity
$L^2(|\Riem|)$ in a surrounding ball is sufficiently small compared to the
pointwise norm of its scalar curvature. Consequently sequences of 4-dimensional
extremal K\"ahler metrics with uniformly bounded Calabi energies and scalar
curvature have convergent subsequences in the Gromov-Hausdorff topology.
Gromov-Hausdorff limits are length spaces with the structure of Riemannian
orbifolds away from finitely many point-like singularities of unknown
structure.


  A new notion of a dual Poisson-presymplectic pair is introduced and its
properties are examined. The procedure of Dirac reduction of Poisson operators
onto submanifolds proposed by Dirac is in this paper embedded in a geometric
procedure of reduction of dual Poisson-presymplectic pairs. The method
presented generalizes those used by Marsden and Ratiu for reductions of Poisson
manifolds. Two examples are given.


  The optical afterglows of the gamma ray bursts can be strongly polarized, in
principle up to tens of percents, if: (i) the afterglow is synchrotron
radiation from an ultra-relativistic blast, (ii) the blast is beamed during the
afterglow phase, i.e. the shock propagates within a narrow jet, (iii) we
observe at the right time from the right viewing angle, (iv) magnetic fields
parallel and perpendicular to the jet have different proper strengths.


  Implicit authentication (IA) is gaining popularity over recent years due to
its use of user behavior as the main input, relieving users from explicit
actions such as remembering and entering passwords. However, such convenience
comes with a cost of authentication accuracy and delay which we propose to
improve in this paper. Authentication accuracy deteriorates as users' behaviors
change as a result of mood, age, a change of routine, etc. Current
authentication systems handle failed authentication attempts by locking the
users out of their mobile devices. It is unsuitable for IA whose accuracy
deterioration induces a high false reject rate, rendering the IA system
unusable. Furthermore, existing IA systems leverage computationally expensive
machine learning, which can introduce a large authentication delay. It is
challenging to improve the authentication accuracy of these systems without
sacrificing authentication delay. In this paper, we propose a multi-level
privilege control (MPC) scheme that dynamically adjusts users' access privilege
based on their behavior change. MPC increases the system's confidence in users'
legitimacy even when their behaviors deviate from historical data, thus
improving authentication accuracy. It is a lightweight feature added to the
existing IA schemes that helps avoid frequent and expensive retraining of
machine learning models, thus improving authentication delay. We demonstrate
that MPC increases authentication accuracy by 18.63\% and reduces
authentication delay by 7.02 minutes on average, using a public dataset that
contains comprehensive user behavior data.


  This paper proposes a temporal graph neural network model for forecasting of
graph-structured irregularly observed time series. Our TGNN4I model is designed
to handle both irregular time steps and partial observations of the graph. This
is achieved by introducing a time-continuous latent state in each node,
following a linear Ordinary Differential Equation (ODE) defined by the output
of a Gated Recurrent Unit (GRU). The ODE has an explicit solution as a
combination of exponential decay and periodic dynamics. Observations in the
graph neighborhood are taken into account by integrating graph neural network
layers in both the GRU state update and predictive model. The time-continuous
dynamics additionally enable the model to make predictions at arbitrary time
steps. We propose a loss function that leverages this and allows for training
the model for forecasting over different time horizons. Experiments on
simulated data and real-world data from traffic and climate modeling validate
the usefulness of both the graph structure and time-continuous dynamics in
settings with irregular observations.


  The principle of maximum conformality (PMC) provides a way to eliminate the
conventional renormalization scale ambiguity in a systematic way. By applying
the PMC scale setting, all non-conformal terms in perturbative series are
summed into the running coupling, and one obtains a unique, scale-fixed
prediction at any finite order. In the paper, we make a detailed PMC analysis
for the spin-singlet heavy quarkoniums decay (into light hadrons) at the
next-to-leading order. After applying the PMC scale setting, the decay widths
for all those cases are almost independent of the initial renormalization
scales. The PMC scales for $\eta_c$ and $h_c$ decays are below $1$ GeV, in
order to achieve a confidential pQCD estimation, we adopt several low-energy
running coupling models to do the estimation. By taking the MPT model, we
obtain: $\Gamma(\eta_{c} \to LH)=25.09^{+5.52}_{-4.28}$ MeV, $\Gamma(\eta_{b}
\to LH)=14.34^{+0.92}_{-0.84}$ MeV, $\Gamma(h_{c} \to LH)=0.54^{+0.06}_{-0.04}$
MeV and $\Gamma(h_{b} \to LH)=39.89^{+0.28}_{-0.46}$ KeV, where the errors are
calculated by taking $m_{c}\in[1.40\rm GeV,1.60\rm GeV]$ and $m_{b}\in[4.50\rm
GeV,4.70\rm GeV]$. These decay widths agree with the principle of minimum
sensitivity estimations, in which the decay widths of $\eta_{c,b}$ are also
consistent with the measured ones.


  The status of possible new-physics signals in B_s,d-meson mixing and decay is
reviewed. In particular, it is emphasized that the recent LHCb results, that
find no evidence for a non-standard phase in B_s-barB_s mixing, make a
consistent explanation of the D0 data on the like-sign dimuon charge asymmetry
notoriously difficult. In order to clarify the inconclusive experimental
situation, independent measurements of the semileptonic asymmetries are needed.


  The graphical representation of the correlation matrix by means of different
multivariate statistical methods is reviewed, a comparison of the different
procedures is presented with the use of an example data set, and an improved
representation with better fit is proposed. Principal component analysis is
widely used for making pictures of correlation structure, though as shown a
weighted alternating least squares approach that avoids the fitting of the
diagonal of the correlation matrix outperforms both principal component
analysis and principal factor analysis in approximating a correlation matrix.
Weighted alternating least squares is a very strong competitor for principal
component analysis, in particular if the correlation matrix is the focus of the
study, because it improves the representation of the correlation matrix, often
at the expense of only a minor percentage of explained variance for the
original data matrix, if the latter is mapped onto the correlation biplot by
regression. In this article, we propose to combine weighted alternating least
squares with an additive adjustment of the correlation matrix, and this is seen
to lead to further improved approximation of the correlation matrix.


  In a post-industrial society, the workplace is dominated primarily by
Knowledge Work, which is achieved mostly through human cognitive processing,
such as analysis, comprehension, evaluation, and decision-making. Many of these
processes have limited support from technology in the same way that physical
tasks have been enabled through a host of tools from hammers to shovels and
hydraulic lifts. To develop a suite of cognitive tools, we first need to
understand which processes humans use to complete work tasks. In the past
century several classifications (e.g., Blooms) of cognitive processes have
emerged, and we assessed their viability as the basis for designing tools that
support cognitive work. This study re-used an existing data set composed of
interviews of environmental scientists about their core work. While the
classification uncovered many instances of cognitive process, the results
showed that the existing cognitive process classifications do not provide a
sufficiently comprehensive deconstruction of the human cognitive processes; the
work is quite simply too abstract to be operational.


  We re-formulate the notion of a Newton-Cartan manifold and clarify the
compatibility conditions of a connection with torsion with the Newton-Cartan
structure.


  The solar dipole moment at activity minimum is a good predictor of the
strength of the subsequent solar cycle. Through a systematic analysis using a
state-of-the-art 2$\times$2 D solar dynamo model, we found that bipolar
magnetic regions (BMR) with atypical characteristics can modify the strength of
the next cycle via their impact on the buildup of the dipole moment as a
sunspot cycle unfolds. In addition to summarizing these results, we present
further effects of such "rogue" BMRs. These have the ability to generate
hemispheric asymmetry in the subsequent sunspot cycle, since they modify the
polar cap flux asymmetry of the ongoing cycle. We found strong correlation
between the polar cap flux asymmetry of cycle i and the total pseudo sunspot
number asymmetry of cycle i + 1 . Good correlation also appears in the case of
the time lag of the hemispheres of cycle i + 1.


  Massive BA-type supergiants are among the visually brightest stars in
galaxies with active star formation. As such they are versatile tools for
studies of stellar and galactochemical evolution. Moreover, they can act as
distance indicators for the calibration of the cosmological distance scale. In
the present work abundance patterns of the light elements helium, carbon,
nitrogen and oxygen are investigated in several Galactic BA-type supergiants in
the mass range between 8 and 18 M_sun. Based on high-resolution and high-S/N
Echelle spectra obtained with FOCES on the Calar Alto 2.2m telescope, model
atmosphere analyses are performed using state-of-the-art non-LTE spectrum
synthesis. Stellar parameters and chemical abundances are determined with high
accuracy. This gives tight observational constraints on the evolutionary status
of the stars. Objects evolving from the main sequence to the red supergiant
stage and those on a blue loop can be distinguished by their mixing signature
(pure rotational vs. first dredge-up). The most sensitive tracer of nuclear
processed matter, the N/C ratio, indicates a higher mixing efficiency than
predicted by current evolution models of rotating stars with mass-loss.


  We create broadband SEDs of 761 type 1 AGN. The Scott et al. sample, created
by a cross-correlation of the optical SDSS DR5 quasar catalogue and the 2XMMi
catalogue of serendipitous X-ray sources, is further matched with the FIRST
catalogue of radio sources, the WISE MIR all-sky data release, the 2MASS NIR
point source catalogue, the UKIDSS DR9 Large Area Survey and the GALEX all-sky
and medium UV imaging surveys. This allows broadband SEDs covering
log(nu)~9.2-18.1 to be created. We investigate variations in the SED shape by
binning a subsample of 237 AGN with the best quality SEDs according to their
X-ray spectral parameters, their AGN sub-type and their luminosity, black hole
mass and Eddington ratio. The AGN sub-populations show some significant
differences in their SEDs; X-ray absorbed AGN show a deficit of emission at
X-ray/UV frequencies and an excess in the MIR consistent with absorption and
re-emission, radio-loud AGN show increased radio and X-ray emission, consistent
with the presence of a jet component in addition to the emission seen from
radio-quiet AGN and the SEDs of NLS1s only differ from other type 1s in the
X-ray regime, suggesting any physical differences are limited to their X-ray
emitting region. Binning the AGN according to underlying physical parameters
reveals more subtle differences in the SEDs. The X-ray spectral slope does not
appear to have any influence or dependence on the multiwavelength emission in
the rest of the SED. The contribution of X-rays to Lbol is lower in higher
luminosity sources, and relatively more emission in the optical/UV is seen in
AGN with higher Lx. Variations in the relative flux and peak frequency of the
BBB are observed and may suggest higher inner disc temperatures with increasing
accretion rates. Overall, we find that the diversity in the SED shapes is
relatively small, and we find no apparent single driver for the variations.


  We present a novel Machine Learning (ML) based strategy to search for binary
black hole (BBH) mergers in data from ground-based gravitational wave (GW)
observatories. This is the first ML-based search that not only recovers all the
compact binary coalescences (CBCs) in the first GW transients catalog (GWTC-1),
but also makes a clean detection of GW151216 by only adding a new coincident
ranking statistic (MLStat) to a standard analysis that was used for GWTC-1. In
CBC searches, reducing contamination by terrestrial and instrumental
transients, which create a loud noise background by triggering numerous false
alarms, is crucial to improving the sensitivity for detecting true events. The
sheer volume of data and a large number of expected detections also prompts the
use of ML techniques. We perform transfer learning to train "InceptionV3", a
pre-trained deep neural network, along with curriculum learning to distinguish
GW signals from noisy events by analysing their continuous wavelet transform
(CWT) maps. MLStat incorporates information from this ML classifier into the
coincident search likelihood used by the standard PyCBC search. This leads to
at least an order of magnitude improvement in the inverse false-alarm-rate
(IFAR) for the previously "low significance" events GW151012, GW170729 and
GW151216. We also perform the parameter estimation of GW151216 using
SEOBNRv4HM_ROM. We carry out an injection study to show that MLStat brings
substantial improvement to the detection sensitivity of Advanced LIGO for all
compact binary coalescences. The average improvement in the sensitive volume is
~10% for low chirp masses (0.8-5 Msun), and ~30% for higher masses (5-50 Msun).
This work demonstrates the immense potential and readiness of MLStat for
finding new sources in current data and the possibility of its adaptation in
similar searches.


  Human-robot collaboration (HRC) in a shared workspace has become a common
pattern in real-world robot applications and has garnered significant research
interest. However, most existing studies for human-in-the-loop (HITL)
collaboration with robots in a shared workspace evaluate in either simplified
game environments or physical platforms, falling short in limited realistic
significance or limited scalability. To support future studies, we build an
embodied framework named HumanTHOR, which enables humans to act in the
simulation environment through VR devices to support HITL collaborations in a
shared workspace. To validate our system, we build a benchmark of everyday
tasks and conduct a preliminary user study with two baseline algorithms. The
results show that the robot can effectively assist humans in collaboration,
demonstrating the significance of HRC. The comparison among different levels of
baselines affirms that our system can adequately evaluate robot capabilities
and serve as a benchmark for different robot algorithms. The experimental
results also indicate that there is still much room in the area and our system
can provide a preliminary foundation for future HRC research in a shared
workspace. More information about the simulation environment, experiment
videos, benchmark descriptions, and additional supplementary materials can be
found on the website: https://sites.google.com/view/humanthor/.


  We investigate optical Bloch oscillation, Zener tunneling and breathing modes
in arrays of optical waveguides. We perform a new method of calculation based
on the multiple scattering formalism. To demonstrate Bloch oscillation and
breathing modes, we consider a planar array of parallel cylindrical waveguides
with the refractive index gradually varying across the array. We demonstrate
that the form of Bloch oscillation may be predicted by means of dispersion law
analysis. To demonstrate Zener tunneling, we consider a planar array of
cylindrical waveguides of two types situated by turn. The band structure of
this array contains two bands separated by a narrow gap. If the refractive
indices of waveguides gradually vary across the array, the Zener tunneling
leads to the Bloch-Zener oscillation.


  Using Ly{\alpha} emission line as a tracer of high redshift star forming
galaxies, hundreds of Ly{\alpha} emission line galaxies (LAEs) at z > 5 have
been detected. These LAEs are considered to be low mass young galaxies,
critical to the reionization of the universe and the metal enrichment of
circumgalactic medium (CGM) and intergalactic medium (IGM). It is assumed that
outflows in LAEs can help ionizing photons and Ly{\alpha} photons escape out of
galaxies. However we still know little about the outflows in high redshifts
LAEs due to observational difficulties, especially at redshift > 5. Models of
Ly{\alpha} radiative transfer predict asymmetric Ly{\alpha} line profiles with
broad red wing in LAEs with outflows. Here we report a z ~ 5.7 Ly{\alpha}
emission line with a broad red wing extending to > 1000 km/s relative to the
peak of Ly{\alpha} line, which has been detected in only a couple of z > 5 LAEs
till now. If the broad red wing is ascribed to gas outflow instead of AGN
activity, the outflow velocity could be larger than the escape velocity (~ 500
km/s) of typical halo mass of z ~ 5.7 LAEs, being consistent with the picture
that outflows in LAEs disperse metals to CGM and IGM.


  We identify close pairs of galaxies from 278 deg^2 of Sloan Digital Sky
Survey commissioning imaging data. The pairs are drawn from a sample of 330,041
galaxies with 18 < r^* < 20. We determine the angular correlation function of
galaxy pairs, and find it to be stronger than the correlation function of
single galaxies by a factor of 2.9 +/- 0.4. The two correlation functions have
the same logarithmic slope of 0.77. We invert Limber's equation to estimate the
three-dimensional correlation functions; we find clustering lengths of r_0= 4.2
+/- 0.4 h^{-1} Mpc for galaxies and 7.8 +/- 0.7 h^{-1} Mpc for galaxy pairs.
These results agree well with the global richness dependence of the correlation
functions of galaxy systems.


  Automatically extracting roads from satellite imagery is a fundamental yet
challenging computer vision task in the field of remote sensing. Pixel-wise
semantic segmentation-based approaches and graph-based approaches are two
prevailing schemes. However, prior works show the imperfections that semantic
segmentation-based approaches yield road graphs with low connectivity, while
graph-based methods with iterative exploring paradigms and smaller receptive
fields focus more on local information and are also time-consuming. In this
paper, we propose a new scheme for multi-task satellite imagery road
extraction, Patch-wise Road Keypoints Detection (PaRK-Detect). Building on top
of D-LinkNet architecture and adopting the structure of keypoint detection, our
framework predicts the position of patch-wise road keypoints and the adjacent
relationships between them to construct road graphs in a single pass.
Meanwhile, the multi-task framework also performs pixel-wise semantic
segmentation and generates road segmentation masks. We evaluate our approach
against the existing state-of-the-art methods on DeepGlobe, Massachusetts
Roads, and RoadTracer datasets and achieve competitive or better results. We
also demonstrate a considerable outperformance in terms of inference speed.


  Inside computer networks, different information processing tasks are
necessary to deliver the user data efficiently. This processing can also be
done in the quantum domain. We present simple optical quantum networks where
the orbital angular momentum of a single photon is used as an ancillary degree
of freedom which controls decisions at the network level. Linear optical
elements are enough to provide important network primitives like multiplexing
and routing. First we show how to build a simple multiplexer and demultiplexer
which combine photonic qubits and separate them again at the receiver. We also
give two different self-routing networks where the OAM of an input photon is
enough to make it find its desired destination.


  Concrete domains, especially those that allow to compare features with
numeric values, have long been recognized as a very desirable extension of
description logics (DLs), and significant efforts have been invested into
adding them to usual DLs while keeping the complexity of reasoning in check.
For expressive DLs and in the presence of general TBoxes, for standard
reasoning tasks like consistency, the most general decidability results are for
the so-called $\omega$-admissible domains, which are required to be dense.
Supporting non-dense domains for features that range over integers or natural
numbers remained largely open, despite often being singled out as a highly
desirable extension. The decidability of some extensions of $\mathcal{ALC}$
with non-dense domains has been shown, but existing results rely on powerful
machinery that does not allow to infer any elementary bounds on the complexity
of the problem. In this paper, we study an extension of $\mathcal{ALC}$ with a
rich integer domain that allows for comparisons (between features, and between
features and constants coded in unary), and prove that consistency can be
solved using automata-theoretic techniques in single exponential time, and thus
has no higher worst-case complexity than standard $\mathcal{ALC}$. Our upper
bounds apply to some extensions of DLs with concrete domains known from the
literature, support general TBoxes, and allow for comparing values along paths
of ordinary (not necessarily functional) roles.


  We present the extension of the Wakimoto construction to the $su(2)_k$
quantum current algebra and its associated $Z_k$ quantum parafermion algebra.
This construction is achieved in terms of various deformations of three
classical free boson fields. We also give the vertex operators corresponding to
the quantum spin-$j$ representation.


  Recent studies in speech-driven 3D talking head generation have achieved
convincing results in verbal articulations. However, generating accurate
lip-syncs degrades when applied to input speech in other languages, possibly
due to the lack of datasets covering a broad spectrum of facial movements
across languages. In this work, we introduce a novel task to generate 3D
talking heads from speeches of diverse languages. We collect a new multilingual
2D video dataset comprising over 420 hours of talking videos in 20 languages.
With our proposed dataset, we present a multilingually enhanced model that
incorporates language-specific style embeddings, enabling it to capture the
unique mouth movements associated with each language. Additionally, we present
a metric for assessing lip-sync accuracy in multilingual settings. We
demonstrate that training a 3D talking head model with our proposed dataset
significantly enhances its multilingual performance. Codes and datasets are
available at https://multi-talk.github.io/.


  We study, in the Minimal Supersymmetric Standard Model, the electroweak
symmetry breaking conditions obtained from the one-loop effective potential.
Novel model-independent lower and upper bounds on $\tan \beta$, involving the
other free parameters of the model, are inferred and determined analytically.
We discuss briefly some of the related issues and give an outlook for further
applications.


  In two recent papers, arXiv:0909.1559 and arXiv:0911.4122, it has been
demonstrated that one can obtain quantum corrected Boltzmann kinetic equations
for leptogenesis using a top-down approach based on the
Schwinger-Keldysh/Kadanoff-Baym formalism. These "Boltzmann-like" equations are
similar to the ones obtained in the conventional bottom-up approach but differ
in important details. In particular there is a discrepancy between the
CP-violating parameter obtained in the first-principle derivation and in the
framework of thermal field theory. Here we demonstrate that the two approaches
can be reconciled if causal n-point functions are used in the thermal field
theory approach. The new result for the medium correction to the CP-violating
parameter is qualitatively different from the conventional one. The analogy to
a toy model considered earlier enables us to write down consistent quantum
corrected Boltzmann equations for thermal leptogenesis in the Standard Model
(supplemented by three right-handed neutrinos) which include quantum
statistical terms and medium corrected expressions for the CP-violating
parameter.


  We study a $d$-dimensional wave equation model ($2\leq d\leq 4$) with
quadratic non-linearity and stochastic forcing given by a space-time fractional
noise. Two different regimes are exhibited, depending on the Hurst parameter
$H=(H_0,\ldots,H_d) \in (0,1)^{d+1}$ of the noise: if $\sum_{i=0}^d H_i >
d-\frac12$, then the equation can be treated directly, while in the case
$d-\frac34<\sum_{i=0}^d H_i\leq d-\frac12$, the model must be interpreted in
the Wick sense, through a renormalization procedure. Our arguments essentially
rely on a fractional extension of the considerations of
\cite{gubinelli-koch-oh} for the two-dimensional white-noise situation, and
more generally follow a series of investigations related to stochastic wave
models with polynomial perturbation.


  We derive exact analytical formulas for the radiative heat transfer between
parallel slabs separated by vacuum and subject to arbitrary temperature
profiles. We show that, depending on the derivatives of the temperature at
points close to the slab--vacuum interfaces, the flux can exhibit one of
several different asymptotic low-distance ($d$) behaviors, obeying either
$1/d^2$, $1/d$, or logarithmic power laws, or approaching a constant. Tailoring
the temperature profile within the slabs could enable unprecedented tunability
over heat exchange, leading for instance to sign-flip transitions (where the
flux reverses sign) at tunable distances. Our results are relevant to the
theoretical description of on-going experiments exploring near-field heat
transfer at nanometric distances, where the coupling between radiative and
conductive heat transfer could be at the origin of temperature gradients.


  The electric dipole moment of an electron (eEDM) is one of the sensitive
probes of physics beyond the standard model. The possible existence of the eEDM
gives rise to an experimentally observed energy shift, which is proportional to
the effective electric field (Eeff) of a target molecule. Hence, an analysis of
the quantities that enhance Eeff is necessary to identify suitable molecules
for eEDM searches. In the context of such searches, it is generally believed
that a molecule with larger electric polarization also has a larger value of
Eeff. However, our Dirac-Fock and relativistic coupled-cluster singles and
doubles calculations show that the hydrides of Yb and Hg have larger Eeff than
those of fluorides, even though their polarizations are smaller. This is due to
significant mixing of valence s and p orbitals of the heavy atom in the
molecules. This mixing has been attributed to the energy differences of the
valence atomic orbitals and the overlap of the two atomic orbitals based on the
orbital interaction theory.


  An Ising-type classical statistical model is shown to describe quantum
fermions. For a suitable time-evolution law for the probability distribution of
the Ising-spins our model describes a quantum field theory for Dirac spinors in
external electromagnetic fields, corresponding to a mean field approximation to
quantum electrodynamics. All quantum features for the motion of an arbitrary
number of electrons and positrons, including the characteristic interference
effects for two-fermion states, are described by the classical statistical
model. For one-particle states in the non-relativistic approximation we derive
the Schr\"odinger equation for a particle in a potential from the time
evolution law for the probability distribution of the Ising-spins. Thus all
characteristic quantum features, as interference in a double slit experiment,
tunneling or discrete energy levels for stationary states, are derived from a
classical statistical ensemble. Concerning the particle-wave-duality of quantum
mechanics, the discreteness of particles is traced back to the discreteness of
occupation numbers or Ising-spins, while the continuity of the wave function
reflects the continuity of the probability distribution for the Ising-spins.


  All optical detectors to date annihilate photons upon detection, thus
excluding repeated measurements. Here, we demonstrate a robust photon detection
scheme which does not rely on absorption. Instead, an incoming photon is
reflected off an optical resonator containing a single atom prepared in a
superposition of two states. The reflection toggles the superposition phase
which is then measured to trace the photon. Characterizing the device with
faint laser pulses, a single-photon detection efficiency of 74% and a survival
probability of 66% is achieved. The efficiency can be further increased by
observing the photon repeatedly. The large single-photon nonlinearity of the
experiment should enable the development of photonic quantum gates and the
preparation of novel quantum states of light.


  We study the mass-metallicity relation for 19 members of a
spectroscopically-confirmed protocluster in the COSMOS field at $z=2.2$
(CC2.2), and compare it with that of 24 similarly selected field galaxies at
the same redshift. Both samples are $\rm H\alpha$ emitting sources, chosen from
the HiZELS narrow-band survey, with metallicities derived from $\rm N2\
(\frac{\rm [NII] \lambda 6584}{\rm H \alpha})$ line ratio. For the mass-matched
samples of protocluster and field galaxies, we find that protocluster galaxies
with $10^{9.9} \rm M_\odot \leq M_* \leq 10^{10.9} \rm M_\odot$ are metal
deficient by $0.10 \pm 0.04$ dex ($2.5\sigma$ significance) compared to their
coeval field galaxies. This metal deficiency is absent for low mass galaxies,
$\rm M_* < 10^{9.9} \rm M_\odot$. Moreover, relying on both SED-derived and
$\rm {H\alpha}$ (corrected for dust extinction based on $\rm {M_*}$) SFRs, we
find no strong environmental dependence of SFR-$\rm {M_*}$ relation, however,
we are not able to rule out the existence of small dependence due to inherent
uncertainties in both SFR estimators. The existence of $2.5\sigma$ significant
metal deficiency for massive protocluster galaxies favors a model in which
funneling of the primordial cold gas through filaments dilutes the metal
content of protoclusters at high redshifts ($z \gtrsim 2$). At these redshifts,
gas reservoirs in filaments are dense enough to cool down rapidly and fall into
the potential well of the protocluster to lower the gas-phase metallicity of
galaxies. Moreover, part of this metal deficiency could be originated from
galaxy interactions which are more prevalent in dense environments.


  For the constant-roll tachyon inflation, we derive the analytical expressions
for the scalar and tensor power spectra, the scalar and tensor spectral tilts
and the tensor to scalar ratio up to the first order by using the method of
Bessel function approximation. The derived $n_s-r$ results for the
constant-roll inflation are also compared with the observations, we find that
only one constant-roll inflation is consistent with the observations and
observations constrain the constant-roll inflation to be slow-roll inflation.
The tachyon potential is also reconstructed for the constant-roll inflation
which is consistent with the observations.


  Hydrocarbon films confined between smooth mica surfaces have long provided an
experimental playground for model studies of structure and dynamics of confined
liquids. However fundamental questions regarding the phase behavior and shear
properties in this simple system remain unsolved. With ultra-sensitive
resolution in film thickness and shear stress, and control over the
crystallographic alignment of the confining surfaces, we here investigate the
shear forces transmitted across nanoscale films of dodecane down to a single
molecular layer. We resolve the conditions under which liquid-solid phase
transitions occur and explain friction coefficients spanning several orders of
magnitude. We find that commensurate surface alignment and presence of water at
the interfaces each lead to moderate or high friction, whereas friction
coefficients down to 0.001 are observed for a single molecular layer of
dodecane trapped between crystallographically misaligned dry surfaces. This
ultralow friction is attributed to sliding at the incommensurate interface
between one of the mica surfaces and the laterally ordered solid molecular
film, reconciling previous interpretations.


  We prove the hydrodynamic limit for a particle system in which particles may
have different velocities. We assume that we have two infinite reservoirs of
particles at the boundary: this is the so-called boundary driven process. The
dynamics we considered consists of a weakly asymmetric simple exclusion process
with collision among particles having different velocities.


  Since ancient times, mechanical design aids have been developed to assist
human users, aimed at improving the efficiency and effectiveness of design.
However, even with the widespread use of contemporary Computer-Aided Design
(CAD) systems, there are still high learning costs, repetitive work, and other
challenges. In recent years, the rise of Large Language Models (LLMs) has
introduced new productivity opportunities to the field of mechanical design.
Yet, it remains unrealistic to rely on LLMs alone to complete mechanical design
tasks directly. Through a series of explorations, we propose a method for
constructing a comprehensive Mechanical Design Agent (MDA) by guiding LLM
learning. To verify the validity of our proposed method, we conducted a series
of experiments and presented relevant cases.


  Tuning hyperparameters is a crucial but arduous part of the machine learning
pipeline. Hyperparameter optimization is even more challenging in federated
learning, where models are learned over a distributed network of heterogeneous
devices; here, the need to keep data on device and perform local training makes
it difficult to efficiently train and evaluate configurations. In this work, we
investigate the problem of federated hyperparameter tuning. We first identify
key challenges and show how standard approaches may be adapted to form
baselines for the federated setting. Then, by making a novel connection to the
neural architecture search technique of weight-sharing, we introduce a new
method, FedEx, to accelerate federated hyperparameter tuning that is applicable
to widely-used federated optimization methods such as FedAvg and recent
variants. Theoretically, we show that a FedEx variant correctly tunes the
on-device learning rate in the setting of online convex optimization across
devices. Empirically, we show that FedEx can outperform natural baselines for
federated hyperparameter tuning by several percentage points on the
Shakespeare, FEMNIST, and CIFAR-10 benchmarks, obtaining higher accuracy using
the same training budget.


  Interfaces between materials with different electronic ground states have
become powerful platforms for creating and controlling novel quantum states of
matter, in which inversion symmetry breaking and other effects at the interface
may introduce additional electronic states. Among the emergent phenomena,
superconductivity is of particular interest. In this work, by depositing metal
films on a newly identified topological semimetal tungsten carbide (WC) single
crystal, we have obtained interfacial topological superconductivity evidenced
from soft point contact spectroscopy. This very robust phenomenon has been
demonstrated for a wide range of Metal/WC interfaces, involving both
non-magnetic and ferromagnetic films, and the superconducting transition
temperatures is surprisingly insensitive to the magnetism of thin films,
suggesting a spin-triplet pairing superconducting state. The results offer an
opportunity to implement topological superconductivity using convenient thin
film coating method.


  This paper proposes to learn analysis transform network for dynamic magnetic
resonance imaging (LANTERN) with small dataset. Integrating the strength of
CS-MRI and deep learning, the proposed framework is highlighted in three
components: (i) The spatial and temporal domains are sparsely constrained by
using adaptively trained CNN. (ii) We introduce an end-to-end framework to
learn the parameters in LANTERN to solve the difficulty of parameter selection
in traditional methods. (iii) Compared to existing deep learning reconstruction
methods, our reconstruction accuracy is better when the amount of data is
limited. Our model is able to fully exploit the redundancy in spatial and
temporal of dynamic MR images. We performed quantitative and qualitative
analysis of cardiac datasets at different acceleration factors (2x-11x) and
different undersampling modes. In comparison with state-of-the-art methods,
extensive experiments show that our method achieves consistent better
reconstruction performance on the MRI reconstruction in terms of three
quantitative metrics (PSNR, SSIM and HFEN) under different undersamling
patterns and acceleration factors.


  This paper provides sufficient density conditions for the existence of smooth
vectors generating a frame or Riesz sequence in the lattice orbit of a
square-integrable projective representation of a nilpotent Lie group. The
conditions involve the product of lattice co-volume and formal dimension, and
complement Balian-Low type theorems for the non-existence of smooth frames and
Riesz sequences at the critical density. The proof hinges on a connection
between smooth lattice orbits and generators for an explicitly constructed
finitely generated Hilbert $C^*$-module. An important ingredient in the
approach is that twisted group $C^*$-algebras associated to finitely generated
nilpotent groups have finite decomposition rank, hence finite nuclear
dimension, which allows us to deduce that any matrix algebra over such a simple
$C^*$-algebra has strict comparison of projections.


  Lattice field theory is a non-perturbative tool for studying properties of
strongly interacting field theories, which is particularly amenable to
numerical calculations and has quantifiable systematic errors. In these
lectures we apply these techniques to nuclear Effective Field Theory (EFT), a
non-relativistic theory for nuclei involving the nucleons as the basic degrees
of freedom. The lattice formulation of [1,2] for so-called pionless EFT is
discussed in detail, with portions of code included to aid the reader in code
development. Systematic and statistical uncertainties of these methods are
discussed at length, and extensions beyond pionless EFT are introduced in the
final Section.


  We study numerically the phase diagram and the response under a driving force
of the phase field crystal model for pinned lattice systems introduced recently
for both one and two dimensional systems. The model describes the lattice
system as a continuous density field in the presence of a periodic pinning
potential, allowing for both elastic and plastic deformations of the lattice.
We first present results for phase diagrams of the model in the absence of a
driving force. The nonlinear response to a driving force on an initially pinned
commensurate phase is then studied via overdamped dynamic equations of motion
for different values of mismatch and pinning strengths. For large pinning
strength the driven depinning transitions are continuous, and the sliding
velocity varies with the force from the threshold with power-law exponents in
agreement with analytical predictions. Transverse depinning transitions in the
moving state are also found in two dimensions. Surprisingly, for sufficiently
weak pinning potential we find a discontinuous depinning transition with
hysteresis even in one dimension under overdamped dynamics. We also
characterize structural changes of the system in some detail close to the
depinning transition.


  The long-term behaviors of flows of continuous-state branching processes are
characterized through subordinators and extremal processes. The extremal
processes arise in the case of supercritical processes with infinite mean and
of subcritical processes with infinite variation. The jumps of these extremal
processes are interpreted as specific initial individuals whose progenies
overwhelm the population. These individuals, which correspond to the records of
a certain Poisson point process embedded in the flow, are called
super-individuals. They radically increase the growth rate to $+\infty$ in the
supercritical case, and slow down the rate of extinction in the subcritical
one.


  Financial markets provide a natural quantitative lab for understanding some
of the most advanced human behaviours. Among them is the use of mathematical
tools known as financial instruments. Besides money, the two most fundamental
financial instruments are bonds and equities. More than 30 years ago Mehra and
Prescott found the numerical performance of equities relative to government
bonds could not be explained by consumption-based (mainstream) economic
theories. This empirical observation, known as the Equity Premium Puzzle, has
been defying mainstream economics ever since. The recent financial crisis
revealed an even deeper need for understanding financial products. We show how
understanding the rational nature of product design resolves the Equity Premium
Puzzle. In doing so we obtain an experimentally tested theory of product
design.


  Tabular data -- structured, heterogeneous, spreadsheet-style data with rows
and columns -- is widely used in practice across many domains. However, while
recent foundation models have reduced the need for developing task-specific
datasets and predictors in domains such as language modeling and computer
vision, this transfer learning paradigm has not had similar impact in the
tabular domain. In this work, we seek to narrow this gap and present TabuLa-8B,
a language model for tabular prediction. We define a process for extracting a
large, high-quality training dataset from the TabLib corpus, proposing methods
for tabular data filtering and quality control. Using the resulting dataset,
which comprises over 1.6B rows from 3.1M unique tables, we fine-tune a Llama
3-8B large language model (LLM) for tabular data prediction (classification and
binned regression) using a novel packing and attention scheme for tabular
prediction. Through evaluation across a test suite of 329 datasets, we find
that TabuLa-8B has zero-shot accuracy on unseen tables that is over 15
percentage points (pp) higher than random guessing, a feat that is not possible
with existing state-of-the-art tabular prediction models (e.g. XGBoost,
TabPFN). In the few-shot setting (1-32 shots), without any fine-tuning on the
target datasets, TabuLa-8B is 5-15 pp more accurate than XGBoost and TabPFN
models that are explicitly trained on equal, or even up to 16x more data. We
release our model, code, and data along with the publication of this paper.


  In this paper a simple algebraic formula is obtained for the correspondence
between finite right nilpotent Fp-braces and finite nilpotent pre-Lie algebras.
This correspondence agrees with the correspondence using Lazard's
correspondence between finite Fp-braces and pre-Lie algebras proposed by
Wolfgang Rump in 2014. As an application example, a classification of all right
nilpotent Fp-braces generated by one element of cardinality p^4 is obtained,
answering a question posed by Leandro Vendramin.
  It is also shown that the sum of a finite number of left nilpotent ideals in
a left brace is a left nilpotent ideal, therefore every finite brace contains
the largest left nilpotent ideal.


  Upon employing the analysis in a new time domain, termed natural time, it has
been recently demonstrated that a remarkable change of seismicity emerges
before major mainshocks in California. What constitutes this change is that the
fluctuations of the order parameter of seismicity exhibit a clearly detectable
minimum. This is identified by using a natural time window sliding event by
event through the time series of the earthquakes in a wide area and comprising
a number of events that would occur on the average within a few months or so.
Here, we suggest a method to estimate the epicentral area of an impending
mainshock by an additional study of this minimum using an area window sliding
through the wide area. We find that when this area window surrounds (or is
adjacent to) the future epicentral area, the minimum of the order parameter
fluctuations in this area appears at a date very close to the one at which the
minimum is observed in the wide area. The method is applied here to major
earthquakes that occurred in California during the recent decades including the
largest one, i.e., the 1992 Landers earthquake.


  An elliptic K3 surface having two $II^{*}$ fibers is called the Inose
surface. In this paper, we give a method to find a rational section of an Inose
surface corresponding to an isogeny of general degree between two elliptic
curves. In particular, we show examples of bases of the Mordell-Weil lattices
of Inose surfaces arising from isogenies of degrees 5 and 6.


  Let $A$ be an elementary abelian group of order $p^{k}$ with $k\geq 3$ acting
on a finite $p'$-group $G$. The following results are proved.
  If $\gamma_{k-2}(C_{G}(a))$ is nilpotent of class at most $c$ for any $a\in
A^{#}$, then $\gamma_{k-2}(G)$ is nilpotent and has $\{c,k,p\}$-bounded
nilpotency class.
  If, for some integer $d$ such that $2^{d}+2\leq k$, the $d$th derived group
of $C_{G}(a)$ is nilpotent of class at most $c$ for any $a\in A^{#}$, then the
$d$th derived group $G^{(d)}$ is nilpotent and has $\{c,k,p\}$-bounded
nilpotency class.
  Earlier this was known only in the case where $k\leq 4$.


  We use the quark potential model to calculate the mass spectrum of the S-wave
fully heavy tetraquark systems with different flavors, including the $ bc\bar
b\bar c, bb\bar c\bar c, cc\bar c\bar b $ and $ bb\bar b\bar c $ systems. We
employ the Gaussian expansion method to solve the four-body Schr\"odinger
equation, and the complex scaling method to identify resonant states. The $
bc\bar b\bar c, bb\bar c\bar c, cc\bar c\bar b $ and $ bb\bar b\bar c $
resonant states are obtained in the mass regions of $ (13.2,13.5) $, $
(13.3,13.6) $, $ (10.0,10.3) $, $ (16.5,16.7) $ GeV, respectively. Among these
states, the $ bc\bar b\bar c $ tetraquark states are the most promising ones to
be discovered in the near future. We recommend the experimental exploration of
the $ 1^{++} $ and $ 2^{++} $ $ bc\bar b\bar c $ states with masses near $ 13.3
$ GeV in the $ J/\psi\Upsilon $ channel. From the root-mean-square radii, we
find that all the resonant states we have identified are compact tetraquark
states.


  In a paper by Sanwal et al. (2002), it is supposed to be very difficult to
interpret the absorption features in term of cyclotron lines. However, we would
like to address here that the possibility of the absorption being cyclotron
resonance can not be ruled out.We propose that the isolate neutron star, 1E
1207.4-5209 in the center of supernova remnant PKS 1209-51/52, has a debris
disk and is in a propeller phase, with an accretion rate 6x10^{-11}
M_solar/year.


  CiaoPP is an analyzer and optimizer for logic programs, part of the Ciao
Prolog system. It includes PLAI, a fixpoint algorithm for the abstract
interpretation of logic programs which we adapt to use tabled constraint logic
programming. In this adaptation, the tabling engine drives the fixpoint
computation, while the constraint solver handles the LUB of the abstract
substitutions of different clauses. That simplifies the code and improves
performance, since termination, dependencies, and some crucial operations
(e.g., branch switching and resumption) are directly handled by the tabling
engine. Determining whether the fixpoint has been reached uses semantic
equivalence, which can decide that two syntactically different abstract
substitutions represent the same element in the abstract domain. Therefore, the
tabling analyzer can reuse answers in more cases than an analyzer using
syntactical equality. This helps achieve better performance, even taking into
account the additional cost associated to these checks. Our implementation is
based on the TCLP framework available in Ciao Prolog and is one-third the size
of the initial fixpoint implementation in CiaoPP. Its performance has been
evaluated by analyzing several programs using different abstract domains. This
paper is under consideration for publication in Theory and Practice of Logic
Programming (TPLP).


  In curved space time inside the shell of TeV black holes, many gluons and
quarks produce due to Unruh effect, interact with each other and create Higgs
boson. Studying the Unruh effect, we show that the inside state of the black
hole for gluons and quarks can be represented by a maximally entangled two mode
squeezed state of inside and matter Hilbert spaces of black hole. Comparing the
Higgs boson production outside and inside the shell, we observe that at lower
mass, MBH<4 TeV, and at higher mass, MBH>9 TeV, the Higgs boson will not be
produced outside the shell of black hole. However this particle can be produced
inside the shell for 2.5 TeV<MBH<12.5 TeV. We find that the outside the shell
of black hole is able to produce a quark for 3 TeV<MBH<10 TeV and eventually
for MBH<3 TeV and MBH> 12.5 TeV the black hole can only emit massless gluons.
However, inside the shell of black hole is able to produce a quark for 2.5
TeV<MBH<14 TeV. We also find that the micro black hole can be a source for
Higgs production at LHC. Finally we calculate the effects of Higgs boson
radiation due to inside the shell and outside the shell of mini black holes on
hadronic cross section at LHC. We observe that as the order of perturbation
theory increases, this effect becomes systematically more effective because at
higher orders there exists more channels for Higgs production and their decay
of Higgs into massive quark-anti quarks in our calculation. At smaller mass,
MBH<2 TeV, the NNLO contribution is large while the cross sections at NLO and
at LO are rising and respectively exhibit a turn-over at moderate values of
black hole's mass.The peak moves from about 5 TeV to 2.5 TeV. It is concluded
that the processes of hadronization inside the event horizon of mini black
holes are affected the hadronic cross section outside the event horizon and can
be observed at LHC.


  The relative yields of active and sterile neutrinos in the matter with a high
density and different degree of neutronization are calculated. A significant
increase in the proportion of sterile neutrinos produced in superdense matter
when degree of neutronization approaches the value of two is found. The results
obtained can be used in the calculations of the neutrino fluxes for media with
a high density and different neutronization degrees in astrophysical processes
such as the formation of protoneutron core of a supernova.


  In this paper we study the homology and cohomology of confguration spaces of
two distinct particles on a graph. Our main tool is intersection theory for
cycles in graphs. We obtain an explicit description of the cohomology algebra
of the configuration space in the case of planar graphs.


  We consider in this work the problem of minimizing the von Neumann entropy
under the constraints that the density of particles, the current, and the
kinetic energy of the system is fixed at each point of space. The unique
minimizer is a self-adjoint positive trace class operator, and our objective is
to characterize its form. We will show that this minimizer is solution to a
self-consistent nonlinear eigenvalue problem. One of the main difficulties in
the proof is to parametrize the feasible set in order to derive the
Euler-Lagrange equation, and we will proceed by constructing an appropriate
form of perturbations of the minimizer. The question of deriving quantum
statistical equilibria is at the heart of the quantum hydrody-namical models
introduced by Degond and Ringhofer in [5]. An original feature of the problem
is the local nature of constraints, i.e. they depend on position, while more
classical models consider the total number of particles, the total current and
the total energy in the system to be fixed.


  Using the recently perfected sea-boson method, we compute the momentum
distribution of the one-band Hubbard model in one and two spatial dimensions.
  We compute the asymptotic features of the momentum distribution explicitly
away from half filling for weak coupling in one and two dimensions. While the
results are not exact by any means, they provide the exact asymptotics, namely
they are able to reproduce the exponents obtained by Shulz in one dimension
obtained using Bethe ansatz. The corresponding results in more than one
dimension are therefore as believeable.


  Spectra of OH/IR stars show prominent spectral bands of crystalline olivine
(Mg$_{(2-2x)}$Fe$_{(2x)}$SiO$_{4}$). To learn more about the timescale of the
outflows of OH/IR stars, we study the spectral band of crystalline olivine at
69 {\mu}m. The 69 {\mu}m band is of interest because its width and peak
wavelength position are sensitive to the grain temperature and to the exact
composition of the crystalline olivine. With Herschel/PACS, we observed the 69
{\mu}m band in the outflow of 14 OH/IR stars. By comparing the crystalline
olivine features of our sample with those of model spectra, we determined the
size of the outflow and its crystalline olivine abundance.
  The temperature indicated by the observed 69 {\mu}m bands can only be
reproduced by models with a geometrically compact superwind
($R_{\rm{SW}}\lesssim$ 2500 AU = 1400 R$_{*}$).This means that the superwind
started less than 1200 years ago (assuming an outflow velocity of 10 km/s). The
small amount of mass lost in one superwind and the high progenitor mass of the
OH/IR stars introduce a mass loss and thus evolutionary problem for these
objects, which has not yet been understood.


  Recent developments in experiments with vibrational electron energy loss
spectroscopy (EELS) have revealed spectral shape variations at spatial
resolutions down to sub-atomic scale. Interpretation in terms of local phonon
density of states enables their qualitative understanding, yet a more detailed
analysis is calling for advances in theoretical methods. In Zeiger and Rusz,
Phys. Rev. Lett. 124, 025501 (2020) we have presented a frequency resolved
frozen phonon multislice method for simulations of vibrational EELS. Detailed
simulations for a plane wave electron beam scattering on a vibrating hexagonal
boron nitride are presented in a companion manuscript (Zeiger and Rusz,
arXiv:2104.03197). Here we present simulations of vibrational EELS assuming a
convergent electron probe of nanometer size and atomic size on a hexagonal
boron nitride structure model with a planar defect. With a nanometer beam we
observe spectral shape modifications in the presence of the defect, which are
correlated with local changes of the phonon density of states. With an atomic
size electron beam, we observe the same, although with better contrast. In
addition, we observe atomic level contrast and sub-atomic scale spectral shape
modifications, which are particularly strong for small detector collection
angles.


  Geometrical dimensionality plays a fundamentally important role in the
topological effects arising in discrete lattices. While direct experiments are
limited by three spatial dimensions, the research topic of synthetic dimensions
implemented by the frequency degree of freedom in photonics is rapidly
advancing. The manipulation of light in such artificial lattices is typically
realized through electro-optic modulation, yet their operating bandwidth
imposes practical constraints on the range of interactions between different
frequency components. Here we propose and experimentally realize all-optical
synthetic dimensions involving specially tailored simultaneous short- and
long-range interactions between discrete spectral lines mediated by frequency
conversion in a nonlinear waveguide. We realize triangular chiral-tube lattices
in three-dimensional space and explore their four-dimensional generalization.
We implement a synthetic gauge field with nonzero magnetic flux and observe the
associated multidimensional dynamics of frequency combs, all within one
physical spatial port. We anticipate that our method will provide a new means
for the fundamental study of high-dimensional physics and act as an important
step towards using topological effects in optical devices operating in the time
and frequency domains.


  We report the discovery of six new magnetar counterpart candidates from deep
near-infrared Hubble Space Telescope imaging. The new candidates are among a
sample of nineteen magnetars for which we present HST data obtained between
2018-2020. We confirm the variability of previously established near-infrared
counterparts, and newly identify candidates for PSRJ1622-4950,
SwiftJ1822.3-1606, CXOUJ171405.7-381031, SwiftJ1833-0832, SwiftJ1834.9-0846 and
AXJ1818.8-1559 based on their proximity to X-ray localisations. The new
candidates are compared with the existing counterpart population in terms of
their colours, magnitudes, and near-infrared to X-ray spectral indices. We find
two candidates for AXJ1818.8-1559 which are both consistent with previously
established counterparts. The other new candidates are likely to be chance
alignments, or otherwise have a different origin for their near-infrared
emission not previously seen in magnetar counterparts. Further observations and
studies of these candidates are needed to firmly establish their nature.


  Solar granules are bright patterns surrounded by dark channels called
intergranular lanes in the solar photosphere and are a manifestation of
overshooting convection. Observational studies generally find stronger upflows
in granules and weaker downflows in intergranular lanes. This trend is,
however, inconsistent with the results of numerical simulations in which
downflows are stronger than upflows through the joint action of gravitational
acceleration/deceleration and pressure gradients. One cause of this discrepancy
is the image degradation caused by optical distortion and light diffraction and
scattering that takes place in an imaging instrument. We apply a deconvolution
technique to Hinode/SP data in an attempt to recover the original solar scene.
Our results show a significant enhancement in both, the convective upflows and
downflows, but particularly for the latter. After deconvolution, the up- and
downflows reach maximum amplitudes of -3.0 km/s and +3.0 km/s at an average
geometrical height of roughly 50 km, respectively. We found that the velocity
distributions after deconvolution match those derived from numerical
simulations. After deconvolution the net LOS velocity averaged over the whole
FOV lies close to zero as expected in a rough sense from mass balance.


  Inspired by the analogous result in the algebraic setting (Theorem 1) we show
(Theorem 2) that the product $M \times \mathbb{R}P^n$ of a closed and
orientable topological manifold $M$ with the $n$-dimensional real projective
space cannot be topologically locally flat embedded into $\mathbb{R}P^{m + n +
1}$ for all even $n > m$.


  This is the third part in a series on a mass conserving, high order, mixed
finite element method for Stokes flow. In this part, we study a block-diagonal
preconditioner for the indefinite Schur complement system arising from the
discretization of the Stokes equations using these elements. The underlying
finite element method is uniformly stable in both the mesh size h and
polynomial order p, and we prove bounds on the eigenvalues of the
preconditioned system which are independent of h and grow modestly in p. The
analysis relates the Schur complement system to an appropriate variational
setting with subspaces for which exact sequence properties and inf-sup
stability hold. Several numerical examples demonstrate agreement with the
theoretical results.


  Indirect surveys, in which respondents provide information about other people
they know, have been proposed for estimating (nowcasting) the size of a
\emph{hidden population} where privacy is important or the hidden population is
hard to reach. Examples include estimating casualties in an earthquake,
conditions among female sex workers, and the prevalence of drug use and
infectious diseases. The Network Scale-up Method (NSUM) is the classical
approach to developing estimates from indirect surveys, but it was designed for
one-shot surveys. Further, it requires certain assumptions and asking for or
estimating the number of individuals in each respondent's network. In recent
years, surveys have been increasingly deployed online and can collect data
continuously (e.g., COVID-19 surveys on Facebook during much of the pandemic).
Conventional NSUM can be applied to these scenarios by analyzing the data
independently at each point in time, but this misses the opportunity of
leveraging the temporal dimension. We propose to use the responses from
indirect surveys collected over time and develop analytical tools (i) to prove
that indirect surveys can provide better estimates for the trends of the hidden
population over time, as compared to direct surveys and (ii) to identify
appropriate temporal aggregations to improve the estimates. We demonstrate
through extensive simulations that our approach outperforms traditional NSUM
and direct surveying methods. We also empirically demonstrate the superiority
of our approach on a real indirect survey dataset of COVID-19 cases.


  Entanglement has evolved from an enigmatic concept of quantum physics to a
key ingredient of quantum technology. It explains correlations between
measurement outcomes that contradict classical physics, and has been widely
explored with small sets of individual qubits. Multi-partite entangled states
build up in gate-based quantum-computing protocols, and $\unicode{x2013}$ from
a broader perspective $\unicode{x2013}$ were proposed as the main resource for
measurement-based quantum-information processing. The latter requires the
ex-ante generation of a multi-qubit entangled state described by a graph. Small
graph states such as Bell or linear cluster states have been produced with
photons, but the proposed quantum computing and quantum networking applications
require fusion of such states into larger and more powerful states in a
programmable fashion. Here we achieve this goal by employing an optical
resonator containing two individually addressable atoms. Ring and tree graph
states with up to eight qubits, with the names reflecting the entanglement
topology, are efficiently fused from the photonic states emitted by the
individual atoms. The fusion process itself employs a cavity-assisted gate
between the two atoms. Our technique is in principle scalable to even larger
numbers of qubits, and is the decisive step towards, for instance, a
memory-less quantum repeater in a future quantum internet.


  The general Helfrich shape equation determined by minimizing the curvature
free energy describes the equilibrium shapes of the axisymmetric lipid bilayer
vesicles in different conditions. It is a non-linear differential equation with
variable coefficients. In this letter, by analyzing the unique property of the
solution, we change this shape equation into a system of the two differential
equations. One of them is a linear differential equation. This equation system
contains all of the known rigorous solutions of the general shape equation. And
the more general constraint conditions are found for the solution of the
general shape equation.


  Using the classical field method, we study numerically the characteristics
and decay of the turbulent tangle of superfluid vortices which is created in
the evolution of a Bose gas from highly nonequilibrium initial conditions. By
analysing the vortex line density, the energy spectrum and the velocity
correlation function, we determine that the turbulence resulting from this
effective thermal quench lacks the coherent structures and the Kolmogorov
scaling; these properties are typical of both ordinary classical fluids and of
superfluid helium when driven by grids or propellers. Instead, thermal quench
turbulence has properties akin to a random flow, more similar to another
turbulent regime called ultra-quantum turbulence which has been observed in
superfluid helium.


  In this article, we employed the Quasi-particle debye mass at finite baryonic
chemical potential which can be used in the medium modified heavy quark
potential to solve the N-dimensional Schroedinger equation. The bound state
solution of the Schroedinger equation using Cornell potential is obtained by
Super-Symmetry Quantum Mechanics (SUSYQM) method. The thermodynamical
properties of quark matter is calculated by using baryonic chemical potential
(mu). We found that the binding energy of quarkonia dissociates more with
quasi-particle debye mass in comparison to non-perturbative and leading order
debye mass. The medium modified form of potential (real part) has been used to
study the thermodynamical properties of quark matter with different equation of
states (EoS) (i.e., pressure, energy density and speed of sound) with {mu}. The
mass spectra of quarkonia has been also calculated in the N-dimensional space,
and compared with the experimental data at N=3. We have also calculated the
dissociation temperature (T_D) for the ground states of quarkonium using the
dissociation criteria of thermal width.


  We present infrared absorption studies of solid hydrogen deuteride to
pressures as high as 3.4 megabar in a diamond anvil cell and temperatures in
the range 5 to 295 K. Above 198 GPa the sample transforms to a mixture of HD
,H2 and D2, interpreted as a process of dissociation and recombination. Three
new phases-lines are observed, two of which differ remarkably from those of the
high-pressure homonuclear species, but none are metallic. The time-dependent
spectral changes are analyzed to determine the molecular concentrations as a
function of time; the nucleon exchange achieves steady state concentrations in
~20 hours at ~200 GPa.


  We discuss a construction of quantum many-body scars in the context of
holography. We consider two-dimensional conformal field theories and use their
dynamical symmetries, naturally realized through the Virasoro algebra, to
construct scarred states. By studying their Loschmidt amplitude, we evaluate
the states' periodic properties. A geometrical interpretation allows us to
compute the expectation value of the stress tensor and entanglement entropy of
these scarred states. We show that their holographic dual is related by a
diffeomorphism to empty AdS, even for energies above the black hole threshold.
We also demonstrate that expectation values in the scarred states are generally
non-thermal and that their entanglement entropy grows with the energy as
$\log(E)$ in contrast to $\sqrt{E}$ for the typical (bulk) states. Furthermore,
we identify fixed points on the CFT plane associated with divergent or
vanishing entanglement entropy in the limit where the scarred states have
infinite energy.


  We show that self-interacting vector field theories exhibit unphysical
behaviour even when they are not coupled to any external field. This means any
theory featuring such vectors is in danger of being unphysical, an alarming
prospect for many proposals in cosmology, gravity, high energy physics and
beyond. The problem arises when vector fields with healthy configurations
naturally reach a point where time evolution is mathematically ill-defined. We
develop tools to easily identify this issue, and provide a simple and unifying
framework to investigate it.


  Using the observations from Michelson Doppler Imager (MDI) onboard Solar and
Heliospheric Observatory (SOHO), we develop a computational algorithm to
automatically identify the bipolar magnetic regions (BMRs) in the active
regions, and then study their statistical properties. The individual magnetic
(positive or negative) pole of the BMR is determined from the region with an
absolute strength above 55 G and with an area above 250 pixel^2 (495 Mm^2),
while a BMR is identified as a pair of positive and negative poles with a
shortest area-weight distance between them. Based on this method, 2234 BMRs are
identified from the MDI synoptic magnetograms between the Carrington Rotation
1909 (1996 May 06) and 2104 (2010 December 10). 1005 of them are located in the
northern hemisphere, while the other 1229 are in the southern hemisphere.We
find that the BMR paraments (e.g., latitudes, separations, fragments, and
strength) are similar to those of active regions (ARs). Moreover, based on the
maximum likelihood estimation (MLE)method, the frequency distributions of these
BMRs occurrence as functions of area size and magnetic flux exhibit a power-law
behavior. We also find that their orientation angles follow the Hale's Polarity
Laws and deviate slightly to the solar equator direction. Consistent with the
previous findings, we obtain the orientation angles dependence on the latitudes
for the normal BMRs during the 23rd solar cycle. The north-south asymmetry of
these BMRs is also detected here.


  Microscale fluid flows generated by ensembles of beating eukaryotic flagella
are crucial to fundamental processes such as development, motility and sensing.
Despite significant experimental and theoretical progress, the underlying
physical mechanisms behind this striking coordination remain unclear. Here, we
present a novel series of experiments in which the flagellar dynamics of two
micropipette-held somatic cells of Volvox carteri, with measurably different
intrinsic beating frequencies, are studied by high-speed imaging as a function
of their mutual separation and orientation. From analysis of beating time
series we find that the interflagellar coupling, which is constrained by the
lack of chemical and mechanical connections between the cells to be purely
hydrodynamical, exhibits a spatial dependence that is consistent with
theoretical predictions. At close spacings it produces robust synchrony which
can prevail for thousands of flagellar beats, while at increasing separations
this synchrony is systematically degraded by stochastic processes. Manipulation
of the relative flagellar orientation reveals the existence of both in-phase
and antiphase synchronized states, which is consistent with dynamical theories.
Through dynamic flagellar tracking with exquisite spatio-temporal precision, we
quantify changes in beating waveforms that result from altered coupling
configuration and distance of separation. The experimental results of this
study prove unequivocally that flagella coupled solely through a fluid medium
can achieve robust synchrony despite significant differences in their intrinsic
properties.


  A Langmuir film is a molecularly thin film on the surface of a fluid; we
study the evolution of a Langmuir film with two co-existing fluid phases driven
by an inter-phase line tension and damped by the viscous drag of the underlying
subfluid. Experimentally, we study an 8CB Langmuir film via digitally-imaged
Brewster Angle Microscopy (BAM) in a four-roll mill setup which applies a
transient strain and images the response. When a compact domain is stretched by
the imposed strain, it first assumes a bola shape with two tear-drop shaped
reservoirs connected by a thin tether which then slowly relaxes to a circular
domain which minimizes the interfacial energy of the system. We process the
digital images of the experiment to extract the domain shapes. We then use one
of these shapes as an initial condition for the numerical solution of a
boundary-integral model of the underlying hydrodynamics and compare the
subsequent images of the experiment to the numerical simulation. The numerical
evolutions first verify that our hydrodynamical model can reproduce the
observed dynamics. They also allow us to deduce the magnitude of the line
tension in the system, often to within 1%. We find line tensions in the range
of 200-600 pN; we hypothesize that this variation is due to differences in the
layer depths of the 8CB fluid phases.


  We construct a new class of black brane solutions in Einstein-Maxwell-dilaton
(EMD) theory, which is characterized by two parameters $a,b$. Based on the
obtained solutions, we make detailed analysis on the ground state in zero
temperature limit and find that for many cases it exhibits the behavior of
vanishing entropy density. We also find that the linear-T resistivity can be
realized in a large region of temperature for the specific case of $a^2=1/3$,
which is the Gubser-Rocha model dual to a ground state with vanishing entropy
density. Moreover, for $a=1$ we analytically construct the black brane which is
magnetically charged by virtue of the electric-magnetic (EM) duality. Various
transport coefficients are calculated and their temperature dependence are
obtained in the high temperature region.


  Recurrent neural network (RNN) based reinforcement learning (RL) is used for
learning context-dependent tasks and has also attracted attention as a method
with remarkable learning performance in recent research. However, RNN-based RL
has some issues that the learning procedures tend to be more computationally
expensive, and training with backpropagation through time (BPTT) is unstable
because of vanishing/exploding gradients problem. An approach with replay
memory introducing reservoir computing has been proposed, which trains an agent
without BPTT and avoids these issues. The basic idea of this approach is that
observations from the environment are input to the reservoir network, and both
the observation and the reservoir output are stored in the memory. This paper
shows that the performance of this method improves by using a multi-layered
neural network for the readout layer, which regularly consists of a single
linear layer. The experimental results show that using multi-layered readout
improves the learning performance of four classical control tasks that require
time-series processing.


  A new approach to vacuum decay in quantum field theory, based on a simple
variational formulation in field space using a tunneling potential, is ideally
suited to study the effects of gravity on such decays. The method allows to
prove in new and simple ways many results, among others, that gravitational
corrections tend to make Minkowski or Anti de Sitter false vacua more stable
semiclassically or that higher barriers increase vacuum lifetime. The approach
also offers a very clean picture of gravitational quenching of vacuum decay and
its parametric dependence on the features of a potential and allows to study
the BPS domain-walls between vacua in critical cases. Special attention is
devoted to supersymmetric potentials and to the discussion of near-critical
vacuum decays, for which it is shown how the new method can be usefully applied
beyond the thin-wall approximation.


  We discuss the prospects to probe the light-quark Yukawa couplings to the
Higgs boson. The Higgs coupling to the charm quark can be probed both via
inclusive and exclusive approaches. On the inclusive frontier, we use our
recently proposed method together with published experimental studies for the
sensitivity of the Higgs coupling to bottom quarks to find that the
high-luminosity LHC can be sensitive to modifications of the charm Yukawa of
the order of a few times its standard model (SM) value. We also present a
preliminary study of this mode for a 100 TeV hadronic machine (with similar
luminosity) and find that the bound can be further improved, possibly within
the reach of the expected signal in the SM. On the exclusive frontier, we use
the recent ATLAS search for charmonia and photon final state. This study yields
the first measurement of the background relevant to these modes. Using this
background measurement we project that at the high-luminosity LHC, unless the
analysis strategy is changed, the sensitivity of the exclusive final state to
the charm Yukawa to the charm Yukawa will be rather poor, of the order of 50
times the SM coupling. We then use a Monte-Carlo study to rescale the above
backgrounds to the h->phi gamma case and obtain a much weaker sensitivity to
the strange Yukawa, of order of 3000 times the SM value. We briefly speculate
what would be required to improve the prospects of the exclusive modes.


  In this paper we present a survey about analytic properties of polynomials
orthogonal with respect to a weighted Sobolev inner product such that the
vector of measures has an unbounded support. In particular, we are focused in
the study of the asymptotic behaviour of such polynomials as well as in the
distribution of their zeros. Some open problems as well as some new directions
for a future research are formulated.


  Control flow obfuscation deters software reverse engineering attempts by
altering the program's control flow transfer. The alternation should not affect
the software's run-time behaviour. In this paper, we propose a control flow
obfuscation approach for FJ with exception handling. The approach is based on a
source to source transformation using continuation passing style (CPS). We
argue that the proposed CPS transformation causes malicious attacks using
context insensitive static analysis and context sensitive analysis with fixed
call string to lose precision.


  We investigate the interplay between the magnetic and the superconducting
degrees of freedom in unconventional multi-band superconductors such as iron
pnictides. For this purpose a dynamical mode-mode coupling theory is developed
based on the coupled Bethe-Salpeter equations. In order to investigate the
region of the phase diagram not too far from the tetracritical point where the
magnetic spin density wave, (SDW) and superconducting (SC) transition
temperatures coincide, we also construct a Ginzburg - Landau functional
including both SC and SDW fluctuations in a critical region above the
transition temperatures. The fluctuation corrections tend to suppress the
magnetic transition, but in the superconducting channel the intraband and
interband contribution of the fluctuations nearly compensate each other.