  We study nonlinear interferometry applied to a measurement of atomic spin and
demonstrate a sensitivity that cannot be achieved by any linear-optical
measurement with the same experimental resources. We use
alignment-to-orientation conversion, a nonlinear-optical technique from optical
magnetometry, to perform a nondestructive measurement of the spin alignment of
a cold $^{87}$Rb atomic ensemble. We observe state-of-the-art spin sensitivity
in a single-pass measurement, in good agreement with covariance-matrix theory.
Taking the degree of measurement-induced spin squeezing as a figure of merit,
we find that the nonlinear technique's experimental performance surpasses the
theoretical performance of any linear-optical measurement on the same system,
including optimization of probe strength and tuning. The results confirm the
central prediction of nonlinear metrology, that superior scaling can lead to
superior absolute sensitivity.


  The blazar 1ES 1959+650 was observed in a flaring state with the Whipple 10 m
Imaging Atmospheric Cherenkov Telescope during May of 2002. A spectral analysis
has been carried out on the data from that time period and the resulting very
high energy gamma-ray spectrum ($E \geq 316$ GeV) can be well fit by a
power-law of differential spectral index \alpha = 2.78 +/- 0.12_{stat.} +/-
0.21_{sys.}. On June 4th 2002, the source flared dramatically in the gamma-ray
range without any coincident increase in the X-ray emission, providing the
first unambiguous example of an `orphan' gamma-ray flare from a blazar. The
gamma-ray spectrum for these data can also be described by a simple power-law
fit with \alpha = 2.82 +/- 0.15_{stat.} +/- 0.30_{sys.}. There is no compelling
evidence for spectral variability, or for any cut-off to the spectrum.


  The graph homomorphism problem (HOM) asks whether the vertices of a given
$n$-vertex graph $G$ can be mapped to the vertices of a given $h$-vertex graph
$H$ such that each edge of $G$ is mapped to an edge of $H$. The problem
generalizes the graph coloring problem and at the same time can be viewed as a
special case of the $2$-CSP problem. In this paper, we prove several lower
bound for HOM under the Exponential Time Hypothesis (ETH) assumption. The main
result is a lower bound $2^{\Omega\left( \frac{n \log h}{\log \log h}\right)}$.
This rules out the existence of a single-exponential algorithm and shows that
the trivial upper bound $2^{{\mathcal O}(n\log{h})}$ is almost asymptotically
tight.
  We also investigate what properties of graphs $G$ and $H$ make it difficult
to solve HOM$(G,H)$. An easy observation is that an ${\mathcal O}(h^n)$ upper
bound can be improved to ${\mathcal O}(h^{\operatorname{vc}(G)})$ where
$\operatorname{vc}(G)$ is the minimum size of a vertex cover of $G$. The second
lower bound $h^{\Omega(\operatorname{vc}(G))}$ shows that the upper bound is
asymptotically tight. As to the properties of the "right-hand side" graph $H$,
it is known that HOM$(G,H)$ can be solved in time $(f(\Delta(H)))^n$ and
$(f(\operatorname{tw}(H)))^n$ where $\Delta(H)$ is the maximum degree of $H$
and $\operatorname{tw}(H)$ is the treewidth of $H$. This gives
single-exponential algorithms for graphs of bounded maximum degree or bounded
treewidth. Since the chromatic number $\chi(H)$ does not exceed
$\operatorname{tw}(H)$ and $\Delta(H)+1$, it is natural to ask whether similar
upper bounds with respect to $\chi(H)$ can be obtained. We provide a negative
answer to this question by establishing a lower bound $(f(\chi(H)))^n$ for any
function $f$. We also observe that similar lower bounds can be obtained for
locally injective homomorphisms.


  Let $p_n$ be the $n$-th orthonormal polynomial on the real line, whose zeros
are $\lambda_j^{(n)}$, $j=1, ..., n$. Then for each $j=1, ..., n$, $$ \vec
\Psi_j^2 = (\Psi_{1j}^2, ..., \Psi_{nj}^2) $$ with $$ \Psi_{ij}^2= p_{i-1}^2
(\lambda_j^{(n)}) (\sum_{k=0}^{n-1} p_k^2(\lambda_j^{(n)}))^{-1}, \quad i=1,
>..., n, $$ defines a discrete probability distribution. The Shannon entropy of
the sequence $\{p_n\}$ is consequently defined as $$ \mathcal S_{n,j} =
-\sum_{i=1}^n \Psi_{ij}^{2} \log (\Psi_{ij}^{2}) . $$ In the case of Chebyshev
polynomials of the first and second kinds an explicit and closed formula for
$\mathcal S_{n,j}$ is obtained, revealing interesting connections with the
number theory. Besides, several results of numerical computations exemplifying
the behavior of $\mathcal S_{n,j}$ for other families are also presented.


  The approach to thermal equilibrium, or thermalization, in isolated quantum
systems is among the most fundamental problems in statistical physics. Recent
theoretical studies have revealed that thermalization in isolated quantum
systems has several remarkable features, which emerge from quantum entanglement
and are quite distinct from those in classical systems. Experimentally, well
isolated and highly controllable ultracold quantum gases offer an ideal system
to study the nonequilibrium dynamics in isolated quantum systems, triggering
intensive recent theoretical endeavors on this fundamental subject. Besides
thermalization, many isolated quantum systems show intriguing behavior in
relaxation processes, especially prethermalization. Prethermalization occurs
when there is a clear separation in relevant time scales and has several
different physical origins depending on individual systems. In this review, we
overview theoretical approaches to the problems of thermalization and
prethermalization.


  The physical diagnosis of the solar atmosphere is achieved by solving the
polarized radiative transfer problem for plasmas in Non-Local Thermodynamical
Equilibrium (NLTE). This scenario poses theoretical challenges for integrating
the radiative transfer equation (RTE) efficiently. Namely, current methods are
limited to constant propagation matrices, thus imposing local solutions. To
spark significant advances, this paper lays the foundations of a formalism that
achieves an efficient non-local integration of the RTE based on the Magnus
expansion. First, we revisit the problem and its solutions in Jones and Stokes
formalisms. Looking at them as equivalent representations of the
Lorentz/Poincar\'e group of rotations, we interpret the RTE in terms of Lie
group theory to show the suitability of the Magnus expansion for obtaining
non-local solutions. We then present a detailed algebraic characterization of
the propagation matrix and combine it with the Magnus expansion to reformulate
the homogenous solution to the RTE in Stokes formalism. Thus, we obtain a
compact evolution operator supporting arbitrary variations of the propagation
matrix to first order in the Magnus expansion. Finally, we reformulate the
corresponding inhomogeneous solution as an equivalent homogeneous system, which
is then solved with the Magnus expansion again. This gives the first efficient
and consistent formal solution of the RTE that furthermore is non-local,
natively accurate, and that separates the integration from the formal solution.
Such disruptive formulation leads to a new whole family of numerical radiative
transfer methods and suggests accelerating NLTE syntheses and inversions with
non-local radiative transfer. With minor cosmetic changes, our results are
valid for other universal physical problems sharing the Lorentz/Poincar\'e
algebra of the RTE and special relativity


  It is known experimentally that at not very large filling factors $\nu$ the
quantum Hall conductivity peaks corresponding to the same Landau level number
$N$ and two different spin orientations are well separated. These peaks occur
at half-integer filling factors $\nu = 2 N + 1/2$ and $\nu = 2 N + 3/2$ so that
the distance between them $\delta\nu$ is unity. As $\nu$ increases $\delta\nu$
shrinks. Near certain $N = N_c$ two peaks abruptly merge into a single peak at
$\nu = 2N + 1$. We argue that this collapse of the spin-splitting at low
magnetic fields is attributed to the disorder-induced destruction of the
exchange enhancement of the electron $g$-factor. We use the mean-field approach
to show that in the limit of zero Zeeman energy $\delta\nu$ experiences a
second-order phase transition as a function of the magnetic field. We give
explicit expressions for $N_c$ in terms of a sample's parameters. For example,
we predict that for high-mobility heterostructures $N_c = 0.9 d n^{5/6}
n_i^{-1/3},$ where $d$ is the spacer width, $n$ is the density of the
two-dimensional electron gas, and $n_i$ is the two-dimensional density of
randomly situated remote donors.


  We have carried out an ALMA survey of 15 confirmed or candidate low-mass
(<0.2M$_\odot$) members of the TW Hya Association (TWA) with the goal of
detecting molecular gas in the form of CO emission, as well as providing
constraints on continuum emission due to cold dust. Our targets have spectral
types of M4-L0 and hence represent the extreme low end of the TWA's mass
function. Our ALMA survey has yielded detections of 1.3mm continuum emission
around 4 systems (TWA 30B, 32, 33, & 34), suggesting the presence of cold dust
grains. All continuum sources are unresolved. TWA 34 further shows 12CO(2-1)
emission whose velocity structure is indicative of Keplerian rotation. Among
the sample of known ~7-10 Myr-old star/disk systems, TWA 34, which lies just
~50 pc from Earth, is the lowest mass star thus far identified as harboring
cold molecular gas in an orbiting disk.


  Hybrid tabular-textual question answering (QA) requires reasoning from
heterogeneous information, and the types of reasoning are mainly divided into
numerical reasoning and span extraction. Current numerical reasoning methods
autoregressively decode program sequences, and each decoding step produces
either an operator or an operand. However, the step-by-step decoding suffers
from exposure bias, and the accuracy of program generation drops sharply as the
decoding steps unfold due to error propagation. In this paper, we propose a
non-autoregressive program generation framework, which independently generates
complete program tuples containing both operators and operands, can address the
error propagation issue while significantly boosting the speed of program
generation. Experiments on the ConvFinQA and MultiHiertt datasets show that our
non-autoregressive program generation method can bring about substantial
improvements over the strong FinQANet (+5.06 Exe Acc and +4.80 Prog Acc points)
and MT2Net (+7.97 EM and +6.38 F1 points) baselines, establishing the new
state-of-the-art performance, while being much faster (21x) in program
generation. Finally, with increasing numbers of numerical reasoning steps the
performance drop of our method is significantly smaller than that of the
baselines. Our code will be publicly available soon.


  We report the study of an "Einstein Cross" configuration first identified in
a set of HST images by Cerny et al. 2018. Deep spectroscopic observations
obtained at the Spanish 10.4m GTC telescope, allowed us to demonstrate the lens
nature of the system, that consists of a Lyman-break galaxy, not a QSO as is
usually the case, at z = 3.03 lensed by a galaxy at z=0.556. Combining the new
spectroscopy with the archival HST data, it turns out that the lens is an
elliptical galaxy with M_V =-21.0, effective radius 2.8 kpc and stellar
velocity dispersion sigma=208+-39 km/sec. The source is a Lyman break galaxy
with Ly_alpha luminosity ~L* at that redshift. From the modeling of the system,
performed by assuming a singular isothermal ellipsoid (SIE) with external
shear, we estimate that the flux source is magnified about 4.5 times, and the
velocity dispersion of the lens is sigma_SIE=197.9-1.3+2.6 km/s, in good
agreement with the value derived spectroscopically. This is the second case
known of an Einstein cross of a Lyman-break galaxy.


  In this paper, we study the dynamic regret of online linear quadratic
regulator (LQR) control with time-varying cost functions and disturbances. We
consider the case where a finite look-ahead window of cost functions and
disturbances is available at each stage. The online control algorithm studied
in this paper falls into the category of model predictive control (MPC) with a
particular choice of terminal costs to ensure the exponential stability of MPC.
It is proved that the regret of such an online algorithm decays exponentially
fast with the length of predictions. The impact of inaccurate prediction on
disturbances is also investigated in this paper.


  A novel method for real-time solar generation forecast using weather data,
while exploiting both spatial and temporal structural dependencies is proposed.
The network observed over time is projected to a lower-dimensional
representation where a variety of weather measurements are used to train a
structured regression model while weather forecast is used at the inference
stage. Experiments were conducted at 288 locations in the San Antonio, TX area
on obtained from the National Solar Radiation Database. The model predicts
solar irradiance with a good accuracy (R2 0.91 for the summer, 0.85 for the
winter, and 0.89 for the global model). The best accuracy was obtained by the
Random Forest Regressor. Multiple experiments were conducted to characterize
influence of missing data and different time horizons providing evidence that
the new algorithm is robust for data missing not only completely at random but
also when the mechanism is spatial, and temporal.


  Gonz{\'a}lez-Acu{\~n}a showed that Artin presentations characterize closed,
orientable $3$-manifold groups. Winkelnkemper later discovered that each Artin
presentation determines a smooth, compact, simply-connected $4$-manifold. We
utilize triangle groups to find all Artin presentations on two generators that
present the trivial group. We then determine all smooth, closed,
simply-connected $4$-manifolds with second betti number at most two that appear
in Artin presentation theory.


  Recently, mathematicians have been interested in studying the theory of
discrete dynamical system, specifically difference equation, such that
considerable works about discussing the behavior properties of its solutions
(boundedness and unboundedness) are discussed and published in many areas of
mathematics which involves several interesting results and applications in
applied mathematics and physics ,One of the most important discrete dynamics
which is become of interest for researchers in the field is the rational
dynamical system .In this paper we may discuss qualitative behavior and
properties of the difference equation $x_{n+1}=ax^2_{n}+bx^2_{n-1}$ with $a$
and $b$ are two parameters and we shall show its application to medicine.


  Galaxy evolution by interaction driven transformation is probably highly
efficient in groups of galaxies. Dwarf galaxies with their shallow potential
are expected to reflect the interaction most prominently in their observable
structure. The major aim of this series of papers is to establish a data base
which allows to study the impact of group interaction onto the morphology and
star-forming properties of dwarf galaxies. Firstly, we present our selection
rules for target groups and the morphological selection method of target dwarf
member candidates. Secondly, the spectroscopic follow-up observations with the
HET are present. Thirdly, we applied own reduction methods based on adaptive
filtering to derive surface photometry of the candidates. The spectroscopic
follow-up indicate a dwarf identification success rate of roughly 55%, and a
group member success rate of about 33%. A total of 17 new low surface
brightness members is presented. For all candidates, total magnitudes, colours,
and light distribution parameters are derived and discussed in the context of
scaling relations. We point out short comings of the SDSS standard pipeline for
surface photometry for these dim objects. We conclude that our selection
strategy is rather efficient to obtain a sample of dim, low surface brightness
members of groups of galaxies within the Virgo super-cluster. The photometric
scaling relation in these X-ray dim, rather isolated groups does not
significantly differ from those of the galaxies within the Local Volume.


  Indium selenide, In2Se3, has recently attracted growing interest due to its
novel properties, including room temperature ferroelectricity, outstanding
photoresponsivity, and exotic in-plane ferroelectricity, which open up new
regimes for next generation electronics. In2Se3 also provides the important
advantage of tuning the electrical properties of ultra-thin layers with an
external electrical and magnetic field, making it a potential platform to study
novel two-dimensional physics. Yet, In2Se3 has many different polymorphs, and
it has been challenging to synthesize single-phase material, especially using
scalable growth methods, as needed for technological applications. In this
paper, we use aberration-corrected scanning transmission electron microscopy to
characterize the microstructure of twin-free single-phase ultra-thin layers of
beta-In2Se3, prepared by a unique molecular beam epitaxy approach. We emphasize
features of the In2Se3 layer and In2Se3/InP interface which provide evidence
for understanding the growth mechanism of the single-phase In2Se3. This novel
approach for forming high-quality twin-free single phase two-dimensional
crystals on InP substrates is likely to be applicable to other technologically
important substrates.


  Circle-shaped transformation cavities of shifted center are the most simple
transformation cavities in the sense that they have only spatial index
variation without boundary shape deformation. For these cavities, we analyze
the characteristics of conformal whispering gallery modes according to
center-shift coordinate transformation. For this study, we use an alternative
scheme for designing a transformation cavity without using a shrinking
parameter that is needed to satisfy total internal reflection condition. It is
observed that the isotropic emission of whispering gallery modes in the uniform
index circular cavity changes to the bi-directional emission of conformal
whispering gallery modes as the center-shift increases. Also, using a purity
factor that quantitatively measures in RV space the degree of intactness for
the internal wave pattern of resonant modes in transformation cavities compared
with corresponding whispering gallery mode in uniform disk cavity, we show that
the conformal whispering gallery modes in the circle-shaped transformation
cavity has not only directionality but also high persistence for
characteristics of whispering gallery modes.


  Compensated isocurvature perturbations (CIPs) are perturbations to the
primordial baryon density that are accompanied by dark-matter-density
perturbations so that the total matter density is unperturbed. Such CIPs, which
may arise in some multi-field inflationary models, can be long-lived and only
weakly constrained by current cosmological measurements. Here we show that the
CIP-induced modulation of the electron number density interacts with the
electron-temperature fluctuation associated with primordial adiabatic
perturbations to produce, via the Biermann-battery mechanism, a magnetic field
in the post-recombinaton Universe. Assuming the CIP amplitude saturates the
current BBN bounds, this magnetic field can be stronger than
$10^{-15}\,\mathrm{nG}$ at $z\simeq20$ and stronger by an order of magnitude
than that (produced at second order in the adiabatic-perturbation amplitude) in
the standard cosmological model, and thus can serve as a possible seed for
galactic dynamos.


  Stochastic control with both inherent random system noise and lack of
knowledge on system parameters constitutes the core and fundamental topic in
reinforcement learning (RL), especially under non-episodic situations where
online learning is much more demanding. This challenge has been notably
addressed in Bayesian RL recently where some approximation techniques have been
developed to find suboptimal policies. While existing approaches mainly focus
on approximating the value function, or on involving Thompson sampling, we
propose a novel two-layer solution scheme in this paper to approximate the
optimal policy directly, by combining the time-decomposition based dynamic
programming (DP) at the lower layer and the scenario-decomposition based
revised progressive hedging algorithm (PHA) at the upper layer, for a type of
Bayesian RL problem. The key feature of our approach is to separate reducible
system uncertainty from irreducible one at two different layers, thus
decomposing and conquering. We demonstrate our solution framework more
especially via the linear-quadratic-Gaussian problem with unknown gain, which,
although seemingly simple, has been a notorious subject over more than half
century in dual control.


  We scrutinize congruence as one of the basic definitions of equality in
geometry and pit it against physics of Special Relativity. We show that two
non-rigid rods permanently kept congruent during their common expansion or
compression may have different instantaneous proper lengths (when measured at
the same time of their respective reference clocks) if they have different mass
distributions over their lengths. Alternatively, their proper lengths can come
out equal only when measured at different but strictly correlated moments of
time of their respective clocks. The derived expression for the ratio of
instantaneous proper lengths of two permanently congruent changing objects
explicitly contains information about the objects mass distribution. The same
is true for the ratio of readings of the two reference clocks, for which the
instantaneous measurements of respective proper lengths produce the same
result. In either case the characteristics usually considered as purely
kinematic depend on mass distribution, which is a dynamic property. This is a
spectacular demonstration of dynamic aspect of geometry already in the
framework of Special Relativity.


  The intensity and the linear scattering polarization profiles of the hydrogen
Ly-alpha line encode valuable information on the thermodynamic and magnetic
structure of the upper layers of the solar chromosphere. The Chromospheric
Lyman-Alpha Spectro-Polarimeter (CLASP) sounding rocket experiment provided
unprecedented spectropolarimetric data of this line, as well as two-dimensional
broadband images in intensity and linear polarization. We theoretically
investigate the potential of the Ly-alpha broadband polarimetric signals for
probing the solar chromosphere and its magnetic fields. We analyze the
synthetic Stokes profiles obtained from a series of radiative transfer (RT)
calculations out of local thermodynamic equilibrium, considering semi-empirical
one-dimensional models of the solar atmosphere. The wavelength-integrated
linear polarization signal is found to be dominated by the contribution from
the wings when considering a Gaussian weighting function with a FWHM that
corresponds to the CLASP slit-jaw broadband filter. These broadband linear
polarization signals are strongly sensitive to magnetic fields of strengths on
the order of 50 G, via the action of magneto-optical (MO) effects, and are
expected to encode information on the middle-upper chromosphere. The
two-dimensional broadband intensity and linear polarization images observed by
CLASP can be suitably mimicked using synthetic wavelength-integrated signals
obtained considering atmospheric models and magnetic fields that are
representative of solar regions with different levels of activity, provided
that the impact of MO effects is taken into account. Despite the limitations of
a one-dimensional RT modeling, this work illustrates the diagnostic potential
of filter-polarimetric Ly-alpha signals for probing the solar chromosphere and
its magnetism.


  We study the spectrum of a one-dimensional Schroedinger operator perturbed by
a fast oscillating potential. The oscillation period is a small parameter. The
essential spectrum is found in an explicit form. The existence and multiplicity
of the discrete spectrum are studied. The complete asymptotics expansions for
the eigenvalues and the associated eigenfunctions are constructed.


  We have used a set of archived HST/WFPC2 exposures of the inner regions of
the Crab Nebula to obtain a new measurement of the pulsar proper motion, the
first after the original work of Wyckoff & Murray, more than 20 years ago. Our
measurement of the pulsar displacement, mu = 18 +/- 3 mas/yr, agrees well with
the value obtained previously. This is noteworthy, since the data we have used
span less than 2 years, as opposed to the 77 years required in the previous
work. With a position angle of 292 +/- 10 deg, the proper motion vector appears
aligned with the axis of symmetry of the inner Crab nebula, as defined by the
direction of the X-ray jet observed by ROSAT. Indeed, if the neutron star
rotation is to be held responsible both for the X-ray jet and for the observed
symmetry, the Crab could provide an example of alignment between spin axis and
proper motion.


  We present the next-to-leading order calculation of two four-jet event shape
variables, the D parameter and acoplanarity differential distributions. We find
large, more than 100% radiative corrections. The theoretical prediction for the
D parameter is compared to L3 data obtained at the Z peak and corrected to
hadron level.


  We review the main advances brought by the Spitzer Space Telescope in the
field of nearby galaxies studies, concentrating on a few subject areas,
including: (1) the physics of the Polycyclic Aromatic Hydrocarbons that
generate the mid-infrared features between ~3.5 micron and ~20 micron; (2) the
use of the mid- and far-infrared emission from galaxies as star formation rate
indicators; and (3) the improvement of mid-infrared diagnostics to discriminate
between thermal (star-formation) and non-thermal (AGN) emission in galaxies and
galaxy centers.


  In contemporary society, the effective utilization of public resources
remains a subject of significant concern. A common issue arises from defectors
seeking to obtain an excessive share of these resources for personal gain,
potentially leading to resource depletion. To mitigate this tragedy and ensure
sustainable development of resources, implementing mechanisms to either reward
those who adhere to distribution rules or penalize those who do not, appears
advantageous. We introduce two models: a tax-reward model and a tax-punishment
model, to address this issue. Our analysis reveals that in the tax-reward
model, the evolutionary trajectory of the system is influenced not only by the
tax revenue collected but also by the natural growth rate of the resources.
Conversely, the tax-punishment model exhibits distinct characteristics when
compared to the tax-reward model, notably the potential for bistability. In
such scenarios, the selection of initial conditions is critical, as it can
determine the system's path. Furthermore, our study identifies instances where
the system lacks stable points, exemplified by a limit cycle phenomenon,
underscoring the complexity and dynamism inherent in managing public resources
using these models.


  This work proves a Burgess bound for short mixed character sums in $n$
dimensions. The non-principal multiplicative character of prime conductor $q$
may be evaluated at any "admissible" form, and the additive character may be
evaluated at any real-valued polynomial. The resulting upper bound for the
mixed character sum is nontrivial when the length of the sum is at least
$q^{\beta}$ with $\beta> 1/2 - 1/(2(n+1))$ in each coordinate. This work
capitalizes on the recent stratification of multiplicative character sums due
to Xu, and the resolution of the Vinogradov Mean Value Theorem in arbitrary
dimensions.


  I present SUSY_FLAVOR - a Fortran 77 program able to calculate simultaneously
29 low-energy flavor and CP-violating observables in the general R-parity
conserving MSSM, including the case of large flavor violation in the sfermion
sector. SUSY_FLAVOR v2 performs also the resummation of chirally enhanced
corrections, arising in large $\tan\beta$ regime and/or large trilinear soft
mixing terms, to all orders of perturbation theory. I discuss an example of
application of SUSY_FLAVOR to analysis of the $B_s \to \mu^+ \mu^-$ decay rate
in the MSSM.


  Noisy labeled data is more a norm than a rarity for crowd sourced contents.
It is effective to distill noise and infer correct labels through aggregation
results from crowd workers. To ensure the time relevance and overcome slow
responses of workers, online label aggregation is increasingly requested,
calling for solutions that can incrementally infer true label distribution via
subsets of data items. In this paper, we propose a novel online label
aggregation framework, BiLA, which employs variational Bayesian inference
method and designs a novel stochastic optimization scheme for incremental
training. BiLA is flexible to accommodate any generating distribution of labels
by the exact computation of its posterior distribution. We also derive the
convergence bound of the proposed optimizer. We compare BiLA with the state of
the art based on minimax entropy, neural networks and expectation maximization
algorithms, on synthetic and real-world data sets. Our evaluation results on
various online scenarios show that BiLA can effectively infer the true labels,
with an error rate reduction of at least 10 to 1.5 percent points for synthetic
and real-world datasets, respectively.


  Many municipalities and road authorities seek to implement automated
evaluation of road damage. However, they often lack technology, know-how, and
funds to afford state-of-the-art equipment for data collection and analysis of
road damages. Although some countries, like Japan, have developed less
expensive and readily available Smartphone-based methods for automatic road
condition monitoring, other countries still struggle to find efficient
solutions. This work makes the following contributions in this context.
Firstly, it assesses the usability of the Japanese model for other countries.
Secondly, it proposes a large-scale heterogeneous road damage dataset
comprising 26620 images collected from multiple countries using smartphones.
Thirdly, we propose generalized models capable of detecting and classifying
road damages in more than one country. Lastly, we provide recommendations for
readers, local agencies, and municipalities of other countries when one other
country publishes its data and model for automatic road damage detection and
classification. Our dataset is available at
(https://github.com/sekilab/RoadDamageDetector/).


  We demonstrate how to determine numerically nearly exact orthonormal orbitals
that are optimal for evaluation of the energy of arbitrary (correlated) states
of atoms and molecules by minimization of the energy Lagrangian. Orbitals are
expressed in real space using a multiresolution spectral element basis that is
refined adaptively to achieve the user-specified target precision while
avoiding the ill-conditioning issues that plague AO basis set expansions
traditionally used for correlated models of molecular electronic structure. For
light atoms, the orbital solver, in conjunction with a variational electronic
structure model [selected Configuration Interaction(CI)] provides energies of
comparable precision to a state-of-the-art atomic CI solver. The computed
electronic energies of atoms and molecules are significantly more accurate than
the counterparts obtained with the Gaussian AO bases of the same rank, and can
be determined even when linear dependence issues preclude the use of the AO
bases. It is feasible to optimize more than 100 fully-correlated numerical
orbitals on a single computer node, and significant room exists for additional
improvement. These findings suggest that the real-space orbital representations
might be the preferred alternative to AO representations for high-end models of
correlated electronic states of molecules and materials.


  Several determinants with gamma functions as elements are evaluated. This
kind of determinants are encountered in the computation of the probability
density of the determinant of random matrices. The s-shifted factorial is
defined as a generalization for non-negative integers of the power function,
the rising factorial (or Pochammer's symbol) and the falling factorial. It is a
special case of polynomial sequence of the binomial type studied in
combinatorics theory. In terms of the gamma function, an extension is defined
for negative integers and even complex values. Properties, mainly composition
laws and binomial formulae, are given. They are used to evaluate families of
generalized Vandermonde determinants with s-shifted factorials as elements,
instead of power functions.


  The arrow of time is an irreversible phenomenon for a system of particles
undergoing reversible dynamics. Since the time of Boltzmann to this day, the
arrow of time has led to debate and research. However, the enormous growth of
nanotechnology and associated experimental techniques has brought the arrow of
time at the forefront because of its practical implications. Using simulations
of one-dimensional diffusion of a system of particles, we show that the arrow
of time is an emergent property of a large system. We show that the recurrence
time for a system of particles to return to its original configuration grows
rapidly as the number of particles grows. Based on the simulations, we have
provided the expressions for recurrence times for classical particles,
Fermions, and Bosons. A system of Bosons has the shortest recurrence time,
whereas a system of classical particles has the longest recurrence time. The
underlying distribution around the mean recurrence time is Poisson-distributed
for Bosons and Gaussian-distributed for Fermions and classical particles. The
probabilistic approach to encode dynamics enables testing processes other than
diffusion and quantify their effects on the recurrence time.


  This paper considers the use of energy harvesters, instead of conventional
time-invariant energy sources, in wireless cooperative communication. For the
purpose of exposition, we study the classic three-node Gaussian relay channel
with decode-and-forward (DF) relaying, in which the source and relay nodes
transmit with power drawn from energy-harvesting (EH) sources. Assuming a
deterministic EH model under which the energy arrival time and the harvested
amount are known prior to transmission, the throughput maximization problem
over a finite horizon of $N$ transmission blocks is investigated. In
particular, two types of data traffic with different delay constraints are
considered: delay-constrained (DC) traffic (for which only one-block decoding
delay is allowed at the destination) and no-delay-constrained (NDC) traffic
(for which arbitrary decoding delay up to $N$ blocks is allowed). For the DC
case, we show that the joint source and relay power allocation over time is
necessary to achieve the maximum throughput, and propose an efficient algorithm
to compute the optimal power profiles. For the NDC case, although the
throughput maximization problem is non-convex, we prove the optimality of a
separation principle for the source and relay power allocation problems, based
upon which a two-stage power allocation algorithm is developed to obtain the
optimal source and relay power profiles separately. Furthermore, we compare the
DC and NDC cases, and obtain the sufficient and necessary conditions under
which the NDC case performs strictly better than the DC case. It is shown that
NDC transmission is able to exploit a new form of diversity arising from the
independent source and relay energy availability over time in cooperative
communication, termed "energy diversity", even with time-invariant channels.


  It is shown that for every problem within dimensional regularization, using
the Integration-By-Parts method, one is able to construct a set of master
integrals such that each corresponding coefficient function is finite in the
limit of dimension equal to four. We argue that the use of such a basis
simplifies and stabilizes the numerical evaluation of the master integrals. As
an example we explicitly construct the ep-finite basis for the set of all
QED-like four-loop massive tadpoles. Using a semi-numerical approach based on
Pade approximations we evaluate analytically the divergent and numerically the
finite part of this set of master integrals.
  The calculations confirm the recent results of Schr\"oder and Vuorinen. All
the contributions found there by fitting the high precision numerical results
have been confirmed by direct analytical calculation without using any
numerical input.


  Strongly interacting gauge mediation (SIGM) of supersymmetry breaking is very
attractive, since it naturally predicts a light gravitino of mass $\lsim{\cal
O}(10)$ eV, which causes no cosmological problem. We discuss various signatures
of the SIGM in the early stage (a low integrated luminosity period) of the LHC
experiments. We show, in particular, a possible way to discriminate it from the
conventional gauge mediation by counting the number of high $P_{\rm T}$
leptons.


  We present a methodology for fitting interatomic potentials to ab initio
data, using the particle swarm optimization (PSO) algorithm, needing only a set
of positions and energies as input. The prediction error of energies associated
with the fitted parameters can be close to 1 meV/atom or lower, for reference
energies having a standard deviation of about 0.5 eV/atom. We tested our method
by fitting a Sutton-Chen potential for copper from \emph{ab initio} data, which
is able to recover structural and dynamical properties, and obtain a better
agreement of the predicted melting point versus the experimental value, as
compared to the prediction of the standard Sutton-Chen parameters.


  In continuation of the macroscopic market making \`a la Avellaneda-Stoikov as
a control problem, this paper explores its stochastic game. Concerning the
price competition, each agent is compared with the best quote from the others.
We start with the linear case. While constructing the solution directly, the
ordering property and the dimension reduction in the equilibrium are revealed.
For the non-linear case, extending the decoupling approach, we introduce a
multidimensional characteristic equation to study the well-posedness of
forward-backward stochastic differential equations. Properties of coefficients
in the characteristic equation are obtained via non-smooth analysis. In
addition to novel well-posedness results, the linear price impact arises and
the impact function can be further decomposed into two parts in some examples.


  In this paper, we develop a cascadic multigrid algorithm for fast computation
of the Fiedler vector of a graph Laplacian, namely, the eigenvector
corresponding to the second smallest eigenvalue. This vector has been found to
have applications in fields such as graph partitioning and graph drawing. The
algorithm is a purely algebraic approach based on a heavy edge coarsening
scheme and pointwise smoothing for refinement. To gain theoretical insight, we
also consider the related cascadic multigrid method in the geometric setting
for elliptic eigenvalue problems and show its uniform convergence under certain
assumptions. Numerical tests are presented for computing the Fiedler vector of
several practical graphs, and numerical results show the efficiency and
optimality of our proposed cascadic multigrid algorithm.


  Residual plots are often used to interrogate regression model assumptions,
but interpreting them requires an understanding of how much sampling variation
to expect when assumptions are satisfied. In this paper, we propose
constructing global envelopes around data (or around trends fitted to data) on
residual plots, exploiting recent advances that enable construction of global
envelopes around functions by simulation. While the proposed tools are
primarily intended as a graphical aid, they can be interpreted as formal tests
of model assumptions, which enables the study of their properties via
simulation experiments. We considered three model scenarios -- fitting a linear
model, generalized linear model or generalized linear mixed model -- and
explored the power of global simulation envelope tests constructed around data
on quantile-quantile plots, or around trend lines on residual vs fits plots or
scale-location plots. Global envelope tests compared favorably to commonly used
tests of assumptions at detecting violations of distributional and linearity
assumptions. Freely available \texttt{R} software
(\texttt{ecostats::plotenvelope}) enables application of these tools to any
fitted model that has methods for the \texttt{simulate}, \texttt{residuals} and
\texttt{predict} functions.


  We review recent work on the phase behaviour of binary charged sphere
mixtures as a function of particle concentration and composition. Both size
ratios and charge ratios are varied over a wide range. By contrast to hard
spheres the long ranged Coulomb interaction stabilizes the crystal phase at low
particle concentrations and shifts the occurrence of amorphous solids to
particle concentrations considerably larger than the freezing concentration.
Depending on size- and charge ratios we observe upper azeotrope, spindle, lower
azeotrope and eutectic types of phase diagrams, all known well from metal
systems. Most solids are of body centred cubic structure. Occasionally
stoichiometric compounds are formed at large particle concen-trations. For very
low size ratios entropic effects dominate and induce a fluid-fluid phase
separation. As for charged spheres also the charge ratio is decisive for the
type of phase behaviour, future experiments with charge variable silica spheres
are suggested.


  In the last decade, online social media has become the primary platform for
protesters to organize and express their agenda in various parts of the world.
Nevertheless, scholars still debate whether online tools induce offline
protests or facilitate them. Unfortunately, studies of protests often lack
panel data and cannot address how particular users change their behaviour over
time in line with the protest agenda. To this end, we analyze a new dataset of
the Facebook page EuroMaydan that was explicitly created to facilitate the
protest in Ukraine from November 2013 to February 2014. Moreover, our analysis
follows this page even after the end of the protest till June 2014. In total,
the dataset includes 26,631 posts and 1,470,593 comments that were generated by
124,790 users during and after the protests. We use this panel data to test how
particular users switch between the two most popular languages of this page:
Ukrainian and Russian. Previous studies have puzzled with language behaviour
during the Ukrainian protest. Although researchers expected to see more
Ukrainian language due to national mobilization, studies discovered that
Ukrainian protesters frequently used Russian, especially after the end of the
protest. A hypothesis was suggested that protesters use language strategically
depending on circumstances (e.g., to maximize outreach). However, previous
studies relied on aggregated data and did not explore the within-subject
variation of language behaviour. Our study adds to this scholarship by adding a
longitudinal analysis of language behaviour. Considering the broader
contribution of this paper, we add to the literature on protests by validating
previous findings derived from surveys that activists change their behaviour to
reflect prior preferences and situational goals rather than modify their
preferences.


  Recently, many efforts have been made to build dark energy models whose
equation-of-state parameter can cross the so-called phantom divide $w_{de}=-1$.
One of them is the so-called hessence dark energy model in which the role of
dark energy is played by a non-canonical complex scalar field. In this work, we
develop a simple method based on Hubble parameter $H(z)$ to reconstruct the
hessence dark energy. As examples, we use two familiar parameterizations for
$H(z)$ and fit them to the latest 182 type Ia supernovae Gold dataset. In the
reconstruction, measurement errors are fully considered.


  We consider the Navier-Stokes equations in $\mathbb{R}^3$ subject to the
initial condition with initial velocity field in $L^{2}_{\rm loc}
(\mathbb{R}^3)$ such that $\limsup_{R \to +\infty } R^{-1} \|u_{0} \|_{
L^{2}(B(R))} < +\infty$. Our aim is to show the local existence of a weak
solution, global existence of weak solution if $C=0$ and the partial regularity
in the sense of Caffarelli-Kohn-Nirenberg.


  Current efforts of modelling COVID-19 are often based on the standard
compartmental models such as SEIR and their variations. As pre-symptomatic and
asymptomatic cases can spread the disease between populations through travel,
it is important to incorporate mobility between populations into the
epidemiological modelling. In this work, we propose to modify the commonly-used
SEIR model to account for the dynamic flight network, by estimating the
imported cases based on the air traffic volume as well as the test positive
rate at the source. This modification, called Flight-SEIR, can potentially
enable 1). early detection of outbreaks due to imported pre-symptomatic and
asymptomatic cases, 2). more accurate estimation of the reproduction number and
3). evaluation of the impact of travel restrictions and the implications of
lifting these measures. The proposed Flight-SEIR is essential in navigating
through this pandemic and the next ones, given how interconnected our world has
become.


  While there are many approaches for automatically proving termination of term
rewrite systems, up to now there exist only few techniques to disprove their
termination automatically. Almost all of these techniques try to find loops,
where the existence of a loop implies non-termination of the rewrite system.
However, most programming languages use specific evaluation strategies, whereas
loop detection techniques usually do not take strategies into account. So even
if a rewrite system has a loop, it may still be terminating under certain
strategies.
  Therefore, our goal is to develop decision procedures which can determine
whether a given loop is also a loop under the respective evaluation strategy.
In earlier work, such procedures were presented for the strategies of
innermost, outermost, and context-sensitive evaluation. In the current paper,
we build upon this work and develop such decision procedures for important
strategies like leftmost-innermost, leftmost-outermost,
(max-)parallel-innermost, (max-)parallel-outermost, and forbidden patterns
(which generalize innermost, outermost, and context-sensitive strategies). In
this way, we obtain the first approach to disprove termination under these
strategies automatically.


  High-resolution X-ray diffraction data show that the low-temperature
superstructure of alpha-NaV2O5 has an F-centered orthorhombic 2a x 2b x 4c
superlattice. A structure model is proposed, that is characterized by layers
with zigzag charge order on all ladders and stacking disorder, such that the
averaged structure has space group Fmm2. This model is in accordance with both
X-ray scattering and NMR data. Variations in the stacking order and disorder
offer an explanation for the recently observed devils staircase of the
superlattice period along c.


  Recovering sparse conditional independence graphs from data is a fundamental
problem in machine learning with wide applications. A popular formulation of
the problem is an $\ell_1$ regularized maximum likelihood estimation. Many
convex optimization algorithms have been designed to solve this formulation to
recover the graph structure. Recently, there is a surge of interest to learn
algorithms directly based on data, and in this case, learn to map empirical
covariance to the sparse precision matrix. However, it is a challenging task in
this case, since the symmetric positive definiteness (SPD) and sparsity of the
matrix are not easy to enforce in learned algorithms, and a direct mapping from
data to precision matrix may contain many parameters. We propose a deep
learning architecture, GLAD, which uses an Alternating Minimization (AM)
algorithm as our model inductive bias, and learns the model parameters via
supervised learning. We show that GLAD learns a very compact and effective
model for recovering sparse graphs from data.


  The incompressibility (compression modulus) $K_{\rm 0}$ of infinite symmetric
nuclear matter at saturation density has become one of the major constraints on
mean-field models of nuclear many-body systems as well as of models of high
density matter in astrophysical objects and heavy-ion collisions. We present a
comprehensive re-analysis of recent data on GMR energies in even-even $^{\rm
112-124}$Sn and $^{\rm 106,100-116}$Cd and earlier data on 58 $\le$ A $\le$ 208
nuclei. The incompressibility of finite nuclei $K_{\rm A}$ is expressed as a
leptodermous expansion with volume, surface, isospin and Coulomb coefficients
$K_{\rm vol}$, $K_{\rm surf}$, $K_\tau$ and $K_{\rm coul}$. \textit{Assuming}
that the volume coefficient $K_{\rm vol}$ is identified with $K_{\rm 0}$, the
$K_{\rm coul}$ = -(5.2 $\pm$ 0.7) MeV and the contribution from the curvature
term K$_{\rm curv}$A$^{\rm -2/3}$ in the expansion is neglected, compelling
evidence is found for $K_{\rm 0}$ to be in the range 250 $ < K_{\rm 0} < $ 315
MeV, the ratio of the surface and volume coefficients $c = K_{\rm surf}/K_{\rm
vol}$ to be between -2.4 and -1.6 and $K_{\rm \tau}$ between -840 and -350 MeV.
We show that the generally accepted value of $K_{\rm 0}$ = (240 $\pm$ 20) MeV
can be obtained from the fits provided $c \sim$ -1, as predicted by the
majority of mean-field models. However, the fits are significantly improved if
$c$ is allowed to vary, leading to a range of $K_{\rm 0}$, extended to higher
values. A self-consistent simple (toy) model has been developed, which shows
that the density dependence of the surface diffuseness of a vibrating nucleus
plays a major role in determination of the ratio K$_{\rm surf}/K_{\rm vol}$ and
yields predictions consistent with our findings.


  We classify all non-abelian groups G such that there exists a pair (V,W) of
absolutely simple Yetter-Drinfeld modules over G such that the Nichols algebra
of the direct sum of V and W is finite-dimensional under two assumptions: the
square of the braiding between V and W is not the identity, and G is generated
by the support of V and W. As a corollary, we prove that the dimensions of such
V and W are at most six. As a tool we use the Weyl groupoid of (V,W).


  A fundamental unit of work in programming is the code contribution ("commit")
that a developer makes to the code base of the project in work. We use
statistical methods to derive a model of the probabilistic distribution of
commit sizes in open source projects and we show that the model is applicable
to different project sizes. We use both graphical as well as statistical
methods to validate the goodness of fit of our model. By measuring and modeling
a fundamental dimension of programming we help improve software development
tools and our understanding of software development.


  Reconfigurable Smart Surface (RSS) is assumed to be a key enabler for future
wireless communication systems due to its ability to control the wireless
propagation environment and, thus, enhance communications quality. Although
optimal and continuous phase-shift configuration can be analytically obtained,
practical RSS systems are prone to both channel estimation errors, discrete
control, and curse of dimensionality. This leads to relaying on a finite number
of phase-shift configurations that is expected to degrade the system's
performances. In this paper, we tackle the problem of quantized RSS phase-shift
configuration, aiming to maximize the data rate of an orthogonal frequency
division multiplexing (OFDM) point-to-point RSS-assisted communication. Due to
the complexity of optimally solving the formulated problem, we propose here a
sub-optimal greedy algorithm to solve it. Simulation results illustrate the
performance superiority of the proposed algorithm compared to baseline
approaches. Finally, the impact of several parameters ,e.g., quantization
resolution and RSS placement, is investigated.


  A program can be considered as a device that generates discrete time signals,
where a signal is an execution. Shannon information rate, or bit rate, of the
signals may not be uniformly distributed. When the program is specified by a
finite state transition system, algorithms are provided in identifying
information-rich components. For a black-box program that has a partial
specification or does not even have a specification, a bit rate signal and its
spectrum are studied, which make use of data compression and the Fourier
transform. The signal provides a bit-rate coverage for testing the black-box
while its spectrum indicates a visual representation for execution's
information characteristics.


  The direct or algorithmic approach for the Jacobian problem, consisting of
the direct construction of the inverse polynomials is proposed. The so called
principle and derived Jacobi conditions are proposed and discussed. The
algorithmic approach is shown to be extendable to higher dimensions by
proceeding on exactly identical lines. As per the important result due to Bass,
Connell, and Wright [3] it is enough to show the validity of the Jacobian
conjecture for cubic polynomials of special type (BCW form) in two, three, and
n variables. Firstly, the method of proof for the cases of two and three
variables is discussed at length. It is then indicated that the extension to
the several variables case follows automatically by just following the same
steps and there is no hindrance as there is essentially no change in the basic
situation and the same line of thought used for the case of two and three
variables remains applicable. Thus, we show that the problem can be solved
completely using the important reduction of the problem to the case of special
cubic degree polynomials [3]. We have shown how to obtain inverse polynomials.
We fully obtain them for two variables case and almost obtain them for three
variables case.


  The radiative recombination of electron-hole pairs represents a great
challenge to the photon-to-charge efficiency in photocell. In this paper, we
visit the radiative recombination rate (RRR) in a quantum photocell with or
without three dipole-dipole coupled electron donors. The results show that
different gaps play the same roles while the ambient temperatures play
different roles in the suppressed RRR with or without three dipole-dipole
coupled electron donors. What's more, the dipole-dipole coupling strength J can
greatly inhibit the RRRs with three dipole-dipole coupled electron donors,
which indicates the quantum coherence generated by three coupled donors is an
efficient approach to suppress RRR, and it is different from the quantum
coherence mentioned by Marlan O. Scully [PRL 104, 207701 (2010)]. This
presented scheme may propose some regulating strategies for efficient
conversion efficiency via the suppressed RRR.


  A quantum receiver is an essential element of quantum illumination (QI) which
outperforms its classical counterpart, called classical-illumination (CI).
However, there are only few proposals for realizable quantum receiver, which
exploits nonlinear effects leading to increasing the complexity of receiver
setups. To compensate this, in this article, we design a quantum receiver with
linear optical elements for Gaussian QI. Rather than exploiting nonlinear
effect, our receiver consists of a 50:50 beam splitter and homodyne detection.
Using double homodyne detection after the 50:50 beam splitter, we analyze the
performance of the QI in different regimes of target reflectivity, source
power, and noise level. We show that our receiver has better signal-to-noise
ratio and more robust against noise than the existing simple-structured
receivers.


  We observe a high level of imbalance in the accuracy of different classes in
the same old task for the first time. This intriguing phenomenon, discovered in
replay-based Class Incremental Learning (CIL), highlights the imbalanced
forgetting of learned classes, as their accuracy is similar before the
occurrence of catastrophic forgetting. This discovery remains previously
unidentified due to the reliance on average incremental accuracy as the
measurement for CIL, which assumes that the accuracy of classes within the same
task is similar. However, this assumption is invalid in the face of
catastrophic forgetting. Further empirical studies indicate that this
imbalanced forgetting is caused by conflicts in representation between
semantically similar old and new classes. These conflicts are rooted in the
data imbalance present in replay-based CIL methods. Building on these insights,
we propose CLass-Aware Disentanglement (CLAD) to predict the old classes that
are more likely to be forgotten and enhance their accuracy. Importantly, CLAD
can be seamlessly integrated into existing CIL methods. Extensive experiments
demonstrate that CLAD consistently improves current replay-based methods,
resulting in performance gains of up to 2.56%.


  Exactly how high-mass star clusters form, especially the young massive
clusters (YMCs: age $<100$ Myr; mass $>10^4$ solar masses), remains an open
problem, largely because they are so rare that examples of their cold, dense,
molecuar progenitors remain elusive. The molecular cloud G337.342$-$0.119, the
`Pebble,' is a candidate for such a cold progenitor. Although G337.342$-$0.119
was originally identified as four separate ATLASGAL clumps, the similarity in
their molecular line velocities and linewidths in the MALT90 dataset
demonstrate that these four clumps are in fact one single, coherent cloud. This
cloud is unique in the MALT90 survey for its combination of both cold
temperatures ($T_{dust} \sim 14$ K) and large linewidths $(\Delta V \sim 10$ km
s$^{-1}$). The near/far kinematic distance ambiguity is difficult to resolve
for G337.342$-$0.119. At the near kinematic distance (4.7 kpc), the mass is
5,000 solar masses and the size is $7\times2$ pc. At the far kinematic distance
(11 kpc), the mass is 27,000 solar masses and the size is $15 \times 4$ pc. The
unusually large linewidths of G337.342$-$0.119 are difficult to reconcile with
a gravitationally bound system in equilibrium. If our current understanding of
the Galaxy's Long Bar is approximately correct, G337.342$-$0.119 cannot be
located at its end. Rather, it is associated with a large star-forming complex
that contains multiple clumps with large linewidths. If G337.342$-$0.119 is a
prototypical cold progenitor for a high-mass cluster, its properties may
indicate that the onset of high-mass star cluster formation is dominated by
extreme turbulence.


  To clarify the relation between confinement and chiral symmetry breaking in
QCD, we consider a temporally odd-number lattice, with the temporal lattice
size $N_t$ being odd. We here use an ordinary square lattice with the normal
(nontwisted) periodic boundary condition for link-variables in the temporal
direction. By considering ${\rm Tr} (\hat{U}_4\hat{\not D}^{N_t-1})$, we
analytically derive a gauge-invariant relation between the Polyakov loop
$\langle L_P \rangle$ and the Dirac eigenvalues $\lambda_n$ in QCD, i.e.,
$\langle L_P \rangle \propto \sum_n \lambda_n^{N_t -1} \langle n|\hat U_4|n
\rangle$, which is a Dirac spectral representation of the Polyakov loop in
terms of Dirac eigenmodes $|n\rangle$. Owing to the factor $\lambda_n^{N_t -1}$
in the Dirac spectral sum, this relation generally indicates fairly small
contribution of low-lying Dirac modes to the Polyakov loop, while the low-lying
Dirac modes are essential for chiral symmetry breaking. Also in lattice QCD
calculations in both confined and deconfined phases, we numerically confirm the
analytical relation, non-zero finiteness of $\langle n|\hat U_4|n \rangle$ for
each Dirac mode, and negligibly small contribution from low-lying Dirac modes
to the Polyakov loop, i.e., the Polyakov loop is almost unchanged even by
removing low-lying Dirac-mode contribution from the QCD vacuum generated by
lattice QCD simulations. We thus conclude that low-lying Dirac modes are not
essential modes for confinement, which indicates no direct one-to-one
correspondence between confinement and chiral symmetry breaking in QCD.


  We present our approach, Collision Avoidance Detour (CAD), which won the 3rd
place award in the 2023 Waymo Open Dataset Challenge - Sim Agents, held at the
2023 CVPR Workshop on Autonomous Driving. To satisfy the motion prediction
factorization requirement, we partition all the valid objects into three
mutually exclusive sets: Autonomous Driving Vehicle (ADV),
World-tracks-to-predict, and World-others. We use different motion models to
forecast their future trajectories independently. Furthermore, we also apply
collision avoidance detour resampling, additive Gaussian noise, and
velocity-based heading estimation to improve the realism of our simulation
result.


  We present an implementaion of interface between the full-potential
linearized augmented plane wave package Wien2k and the wannier90 code for the
construction of maximally localized Wannier functions. The FORTRAN code and a
documentation is made available and results are discussed for SrVO$_3$,
Sr$_2$IrO$_4$ (including spin-orbit coupling), LaFeAsO, and FeSb$_2$.


  Images in visualization publications contain rich information, e.g., novel
visualization designs and implicit design patterns of visualizations. A
systematic collection of these images can contribute to the community in many
aspects, such as literature analysis and automated tasks for visualization. In
this paper, we build and make public a dataset, VisImages, which collects
12,267 images with captions from 1,397 papers in IEEE InfoVis and VAST. Built
upon a comprehensive visualization taxonomy, the dataset includes 35,096
visualizations and their bounding boxes in the images.We demonstrate the
usefulness of VisImages through three use cases: 1) investigating the use of
visualizations in the publications with VisImages Explorer, 2) training and
benchmarking models for visualization classification, and 3) localizing
visualizations in the visual analytics systems automatically.


  We consider possible routes to superconductivity in hydrated cobaltates
Na_xCoO_2.yH_2O on the basis of the t-J-V model plus phonons on the triangular
lattice. We studied the stability conditions for the homogeneous Fermi liquid
(HFL) phase against different broken symmetry phases. Besides the
sqrt(3)xsqrt(3)-CDW phase, triggered by the nearest-neighbour Coulomb
interaction V, we have found that the HFL is unstable, at very low doping,
against a bond-ordered phase due to J. We also discuss the occurrence of phase
separation at low doping and V. The interplay between the electron-phonon
interaction and correlations near the sqrt(3)xsqrt(3)-CDW leads to
superconductivity in the unconventional next-nearest neighbour f-wave (NNN-f)
channel with a dome shape for Tc around x ~ 0.35, and with values of a few
Kelvin as seen in experiments. Near the bond-ordered phase at low doping we
found tendencies to superconductivity with d-wave symmetry for finite J and
x<0.15. Contact with experiments is given along the paper.


  We study the issue of AGN-host connection in intermediate-z (1.2>z>0.4)
galaxies with hybrid spectra (hybrid QSOs for short). The observed spectra
redward of the Balmer limit are dominated by starlight, and the spectra at blue
end by both an AGN continuum and a MgII broad emission line. Such unique
property allows us to examine both AGN and its host galaxy in individual galaxy
simultaneously. At first, 15 hybrid QSOs are selected from the Sloan Digital
Sky Survey Data Release 6. The spectra are then analyzed in detail in three
objects: SDSS J162446.49+461946.7, SDSS J102633.32+103443.8 and SDSS
J090036.44+381353.0. Our spectral analyzing shows that the current star
formation activities are strongly suppressed, and that the latest burst ages
range from ~400Myr to 1Gyr. Basing upon the MgII-based black hole masses, the
three hybrid QSOs are consistent with the D_n(4000)-L/L_{Edd} sequence that was
previously established in local AGNs. The three hybrid QSOs are located in the
middle range of the sequence, which implies that the hybrid QSOs are at the
transition stage not only from young to old AGN, but also from host-dominated
phase to AGN-dominated phase.


  This short note deals with the conjugacy classes of monomial birational maps
in the $n$-dimensional Cremona group, $n\geq 2$.


  Denote by $\Sigma n^m$ the sum of the $m$-th powers of the first $n$ positive
integers $1^m+2^m+\ldots +n^m$. Similarly let $\Sigma^r n^m$ be the $r$-fold
sum of the $m$-th powers of the first $n$ positive integers, defined such that
$\Sigma^0 n^{m}=n^m$, and then recursively by $\Sigma^{r+1} n^{m}=\Sigma^{r}
1^{m}+\Sigma^{r} 2^{m}+\ldots + \Sigma^{r} n^{m}$. During the early
17th-century, polynomial expressions for the sums $\Sigma^r n^m$ and their
factorisation and polynomial basis representation properties were examined by
Johann Faulhaber, who published some remarkable theorems relating to these
$r$-fold sums in his Academia Algebrae (1631).
  In this paper we consider families of polynomials related to the Fibonacci
and Lucas polynomials which naturally lend themselves to representing sums and
differences of integer powers, as well as $\Sigma^r n^m$. Using summations over
polynomial basis representations for monomials we generalise this sum for any
polynomial $q(x)\in\mathbb{Q}[x]$, encountering some interesting coefficient
families in the process. Other results include using our polynomial expressions
to state some theorems of Fermat, where in particular, we obtain an explicit
expression for the quotient in Fermat's Little Theorem.
  In the final two sections we examine these sums in the context of the three
pairs of Stirling number varieties and binomial decompositions. We also derive
an expression for $\Sigma n^m$ in terms of the Stirling numbers and Pochhammer
symbols, leading to a seemingly new relation between the Stirling numbers and
the Bernoulli numbers.


  Tree-based models have proven to be an effective solution for web ranking as
well as other problems in diverse domains. This paper focuses on optimizing the
runtime performance of applying such models to make predictions, given an
already-trained model. Although exceedingly simple conceptually, most
implementations of tree-based models do not efficiently utilize modern
superscalar processor architectures. By laying out data structures in memory in
a more cache-conscious fashion, removing branches from the execution flow using
a technique called predication, and micro-batching predictions using a
technique called vectorization, we are able to better exploit modern processor
architectures and significantly improve the speed of tree-based models over
hard-coded if-else blocks. Our work contributes to the exploration of
architecture-conscious runtime implementations of machine learning algorithms.


  We address the problem of identifying the optimal policy with a fixed
confidence level in a multi-armed bandit setup, when \emph{the arms are subject
to linear constraints}. Unlike the standard best-arm identification problem
which is well studied, the optimal policy in this case may not be deterministic
and could mix between several arms. This changes the geometry of the problem
which we characterize via an information-theoretic lower bound. We introduce
two asymptotically optimal algorithms for this setting, one based on the
Track-and-Stop method and the other based on a game-theoretic approach. Both
these algorithms try to track an optimal allocation based on the lower bound
and computed by a weighted projection onto the boundary of a normal cone.
Finally, we provide empirical results that validate our bounds and visualize
how constraints change the hardness of the problem.


  Open-source code development has become widespread in recent years. As a
result, open-source software platforms have also become popular, and millions
of developers from diverse locations are able to contribute to the same
projects. On these platforms, various knowledge about them is obtained from
user activity. This information is used in the form of developer metrics to
solve a variety of challenges. In this study, we proposed new developer
metrics, including commenting and issue-related activity, that require less
information. We concluded that commenting on any feature of a project can be
equally as valuable as code contribution. In addition, besides the quantitative
ones, metrics based on only the existence of the activity have been shown to
offer also considerable results. We saw that issues were crucial in identifying
user contributions. Even if a developer makes a contribution to only one issue
on a project, the relation between the developer and the project is tight. The
hit scores are relatively lower because of the sparsity problem of our dataset;
even so, we believe that we have presented improvable and remarkable new
developer metrics.


  In this paper, we explore an improved framework to train a monoaural neural
enhancement model for robust speech recognition. The designed training
framework extends the existing mixture invariant training criterion to exploit
both unpaired clean speech and real noisy data. It is found that the unpaired
clean speech is crucial to improve quality of separated speech from real noisy
speech. The proposed method also performs remixing of processed and unprocessed
signals to alleviate the processing artifacts. Experiments on the
single-channel CHiME-3 real test sets show that the proposed method improves
significantly in terms of speech recognition performance over the enhancement
system trained either on the mismatched simulated data in a supervised fashion
or on the matched real data in an unsupervised fashion. Between 16% and 39%
relative WER reduction has been achieved by the proposed system compared to the
unprocessed signal using end-to-end and hybrid acoustic models without
retraining on distorted data.


  Location of formation of periodic solar wind number density structures is
discussed. Observation of proton and alpha anticorrelation in these structures
[Viall et al., 2009] indicates that taking into account that bulk velocity of
aplha-particles is higher than that of proton the place of formation for these
structures should be located at distance less 0.002 AU from place of
observation.


  Quantum science and technology promise the realization of a powerful
computational resource that relies on a network of quantum processors connected
with low loss and low noise communication channels capable of distributing
entangled states [1,2]. While superconducting microwave qubits (3-8 GHz)
operating in cryogenic environments have emerged as promising candidates for
quantum processor nodes due to their strong Josephson nonlinearity and low loss
[3], the information between spatially separated processor nodes will likely be
carried at room temperature via telecommunication photons (200 THz) propagating
in low loss optical fibers. Transduction of quantum information [4-10] between
these disparate frequencies is therefore critical to leverage the advantages of
each platform by interfacing quantum resources. Here, we demonstrate coherent
optical control of a superconducting qubit. We achieve this by developing a
microwave-optical quantum transducer that operates with up to 1.18% conversion
efficiency (1.16% cooperativity) and demonstrate optically-driven Rabi
oscillations (2.27 MHz) in a superconducting qubit without impacting qubit
coherence times (800 ns). Finally, we discuss outlooks towards using the
transducer to network quantum processor nodes.


  3D to 2D retinal vessel segmentation is a challenging problem in Optical
Coherence Tomography Angiography (OCTA) images. Accurate retinal vessel
segmentation is important for the diagnosis and prevention of ophthalmic
diseases. However, making full use of the 3D data of OCTA volumes is a vital
factor for obtaining satisfactory segmentation results. In this paper, we
propose a Progressive Attention-Enhanced Network (PAENet) based on attention
mechanisms to extract rich feature representation. Specifically, the framework
consists of two main parts, the three-dimensional feature learning path and the
two-dimensional segmentation path. In the three-dimensional feature learning
path, we design a novel Adaptive Pooling Module (APM) and propose a new
Quadruple Attention Module (QAM). The APM captures dependencies along the
projection direction of volumes and learns a series of pooling coefficients for
feature fusion, which efficiently reduces feature dimension. In addition, the
QAM reweights the features by capturing four-group cross-dimension
dependencies, which makes maximum use of 4D feature tensors. In the
two-dimensional segmentation path, to acquire more detailed information, we
propose a Feature Fusion Module (FFM) to inject 3D information into the 2D
path. Meanwhile, we adopt the Polarized Self-Attention (PSA) block to model the
semantic interdependencies in spatial and channel dimensions respectively.
Experimentally, our extensive experiments on the OCTA-500 dataset show that our
proposed algorithm achieves state-of-the-art performance compared with previous
methods.


  We report specific heat measurements down to 0.4 K on the layered oxide
Na$_x$CoO$_2\cdot\it{y}$H$_2$O/D$_2$O with 0 $\le$ $\it{x}$ $\le$ 0.74 and
$\it{y}$ = 0 and 1.4. For the nonhydrated system ($\it{y}$ = 0), the electronic
specific heat coefficient $\gamma_N$ and the Debye temperature $\Theta_D$ vary
nonmonotonically with $\it{x}$, both displaying minima when $\it{x}$ is close
to 0.5. This indicates a systematic change of the electronic and vibrational
structures with Na content. For both hydrated and deuterated systems ($\it{x}$
= 0.35 and $\it{y}$ = 1.4), the specific heat reveals a sharp peak with
$\Delta$C$_p \sim$ 45.5 mJ/mol-K at T$_c^{mid} \sim$ 4.7 K and an anomaly at
T$_x \sim$ 0.8 K. While the origin of the later is unknown, the former
corresponds to the superconducting transition. Interestingly, the electronic
specific heat, after subtracting lattice and Schottky contributions, exhibits
roughly T$^2$ behavior between 0.2T$_c$ and T$_c$. This can be explained by
assuming an unconventional superconducting symmetry with line nodes. The
results obtained under applied magnetic field further support this scenario.


  The flow equation method has been used to calculate the energy of single
impurity in a superconductor for the Anderson model with $U \neq 0$. We showed
that the energy of the impurity depends only of the $\Delta^{2}_{R}$
(renormalized order parameter) which depends on the renormalized Hubbard
repulsion$U^R$. For a strong Hubbard repulsion $U^R = U$ and $\Delta^R = \Delta
^I$ the effect of the $s-d$ interactions are nonrelevant, a result which is
expected for this model.


  Abrupt changes of behaviour in complex networks can be triggered by a single
node. This work describes the dynamical fundamentals of how the behaviour of
one node affects the whole network formed by coupled phase-oscillators with
heterogeneous coupling strengths. The synchronisation of phase-oscillators is
independent of the distribution of the natural frequencies, weakly depends on
the network size, but highly depends on only one key oscillator whose ratio
between its natural frequency in a rotating frame and its coupling strength is
maximum. This result is based on a novel method to calculate the critical
coupling strength with which the phase-oscillators emerge into frequency
synchronisation. In addition, we put forward an analytical method to
approximately calculate the phase-angles for the synchronous oscillators.


  The angular distribution of the final electrons in the so-called long range
mechanism of the neutrinoless double beta decay ($0\nu2\beta$) is derived for
the general Lorentz invariant effective Lagrangian. Possible theories beyond
the SM are classified from their effects on the angular distribution, which
could be used to discriminate among various particle physics models inducing
$0\nu2\beta$ decays. However, additional input on the effective couplings will
be required to single out the light Majorana-neutrino mechanism. Alternatively,
measurements of the effective neutrino mass and angular distribution in
$0\nu2\beta$ decays can be used to test the correlations among the parameters
of the underlying physics models. This is illustrated for the left-right
symmetric model, taking into account current phenomenological bounds.


  The energy-based stochastic extension of the Schrodinger equation is a rather
special nonlinear stochastic differential equation on Hilbert space, involving
a single free parameter, that has been shown to be very useful for modelling
the phenomenon of quantum state reduction. Here we construct a general closed
form solution to this equation, for any given initial condition, in terms of a
random variable representing the terminal value of the energy and an
independent Brownian motion. The solution is essentially algebraic in
character, involving no integration, and is thus suitable as a basis for
efficient simulation studies of state reduction in complex systems.


  We investigate a spectrum oligopoly market where each primary seeks to sell
secondary access to its channel at multiple locations. Transmission qualities
of a channel evolve randomly. Each primary needs to select a price and a set of
non-interfering locations (which is an independent set in the conflict graph of
the region) at which to offer its channel without knowing the transmission
qualities of the channels of its competitors. We formulate the above problem as
a non-cooperative game. We consider two scenarios-i) when the region is small,
ii) when the region is large. In the first setting, we focus on a class of
conflict graphs, known as mean valid graphs which commonly arise when the
region is small. We explicitly compute a symmetric Nash equilibrium (NE); the
NE is threshold type in that primaries only choose independent set whose
cardinality is greater than a certain threshold. The threshold on the
cardinality increases with increase in quality of the channel on sale. We show
that the symmetric NE strategy profile is unique in a special class of conflict
graphs (linear graph). In the second setting, we consider node symmetric
conflict graphs which arises when the number of locations is large
(potentially, infinite). We explicitly compute a symmetric NE that randomizes
equally among the maximum independent sets at a given channel state vector. In
the NE a primary only selects the maximum independent set at a given channel
state vector. We show that the two symmetric NEs computed in two settings
exhibit important structural difference.


  Twisted stacked few layer black phosphorus heterostructures were successfully
fabricated in this work. Abnormal blue shifts in their Ag1 and Ag2 Raman peaks
and unique optical reflections were observed in these samples. The phonon
behavior difference can be explained by our density functional theory
calculations, which suggest that interlayer coupling has a significant effect
in twisted bilayer black phosphorus. According to the calculations, the
interlayer interactions are not simply van der Waals interactions. Additional
interactions, such as weak valence bonding between the top and bottom flakes,
are considered to be the cause of the blue shifts in their Raman spectra.


  We have observed the effect of pseudo magnetic field originating from the
polaritonic analog of spin-orbit coupling (TE$-$TM splitting) on a polariton
condensate in a ring-shaped microcavity. The effect gives rise to a stable
four-leaf pattern around the ring as seen from the linear polarization
measurements of the condensate photoluminescence. This pattern is found to
originate from the interplay of the cavity potential, energy relaxation, and
TE-TM splitting in the ring. Our observations are compared to the dissipative
one-dimensional spinor Gross-Pitaevskii equation with the TE-TM splitting
energy which shows good qualitative agreement.


  In this paper, we present FASE (Faster Asynchronous Systems Evaluation), a
tool for evaluating the worst-case efficiency of asynchronous systems. The tool
is based on some well-established results in the setting of a timed process
algebra (PAFAS: a Process Algebra for Faster Asynchronous Systems). To show the
applicability of FASE to concrete meaningful examples, we consider three
implementations of a bounded buffer and use FASE to automatically evaluate
their worst-case efficiency. We finally contrast our results with previous ones
where the efficiency of the same implementations has already been considered.


  We compute the index of the inclusions of type $III_{1/2}$ factors arising
from endomorphisms of the Cuntz algebra ${\mathcal O}_2$ associated to the
rank-two permutation matrices.


  We address the problem of belief revision of logic programs, i.e., how to
incorporate to a logic program P a new logic program Q. Based on the structure
of SE interpretations, Delgrande et al. adapted the well-known AGM framework to
logic program (LP) revision. They identified the rational behavior of LP
revision and introduced some specific operators. In this paper, a constructive
characterization of all rational LP revision operators is given in terms of
orderings over propositional interpretations with some further conditions
specific to SE interpretations. It provides an intuitive, complete procedure
for the construction of all rational LP revision operators and makes easier the
comprehension of their semantic and computational properties. We give a
particular consideration to logic programs of very general form, i.e., the
generalized logic programs (GLPs). We show that every rational GLP revision
operator is derived from a propositional revision operator satisfying the
original AGM postulates. Interestingly, the further conditions specific to GLP
revision are independent from the propositional revision operator on which a
GLP revision operator is based. Taking advantage of our characterization
result, we embed the GLP revision operators into structures of Boolean
lattices, that allow us to bring to light some potential weaknesses in the
adapted AGM postulates. To illustrate our claim, we introduce and characterize
axiomatically two specific classes of (rational) GLP revision operators which
arguably have a drastic behavior. We additionally consider two more restricted
forms of logic programs, i.e., the disjunctive logic programs (DLPs) and the
normal logic programs (NLPs) and adapt our characterization result to DLP and
NLP revision operators.


  ALMA observations of a small sample of transitional disks with large dust
cavities observed in Cycle 0 and 1 are summarized. The gas and dust surface
density structures are inferred from the continuum and 12CO, 13CO and C18O line
data using the DALI physical-chemical code. Thanks to its ability to
self-shield, CO can survive inside dust cavities in spite of being exposed to
intense UV radiation and can thus be used as a probe of the gas structure.
Modeling of the existing data shows that gas is present inside the dust
cavities in all cases, but at a reduced level compared with the gas surface
density profile of the outer disk. The gas density decrease inside the dust
cavity radius by factors of up to 10^4 suggests clearing by one or more
planetary-mass companions. The accompanying pressure bumps naturally lead to
trapping of the mm-sized dust grains observed in the ALMA images.


  Certain physical systems that one might consider for fault-tolerant quantum
computing where qubits do not readily interact, for instance photons, are
better suited for measurement-based quantum-computational protocols. Here we
propose a measurement-based model for universal quantum computation that
simulates the braiding and fusion of Majorana modes. To derive our model we
develop a general framework that maps any scheme of fault-tolerant quantum
computation with stabilizer codes into the measurement-based picture. As such,
our framework gives an explicit way of producing fault-tolerant models of
universal quantum computation with linear optics using protocols developed
using the stabilizer formalism. Given the remarkable fault-tolerant properties
that Majorana modes promise, the main example we present offers a robust and
resource efficient proposal for photonic quantum computation.


  Measurement-Based Quantum Computation (MBQC) is a model of quantum
computation, which uses local measurements instead of unitary gates. Here we
explain that the MBQC procedure has a fundamental basis in an underlying gauge
theory. This perspective provides a theoretical foundation for global aspects
of MBQC. The gauge transformations reflect the freedom of formulating the same
MBQC computation in different local reference frames. The main identifications
between MBQC and gauge theory concepts are: (i) the computational output of
MBQC is a holonomy of the gauge field, (ii) the adaptation of measurement basis
that remedies the inherent randomness of quantum measurements is effected by
gauge transformations. The gauge theory of MBQC also plays a role in
characterizing the entanglement structure of symmetry-protected topologically
(SPT) ordered states, which are resources for MBQC. Our framework situates MBQC
in a broader context of condensed matter and high energy theory.


  Hyperentangled Bell states analysis (HBSA) is an essential building block for
certain hyper-parallel quantum information processing. We propose a complete
and deterministic HBSA scheme encoded in spatial and polarization degrees of
freedom (DOFs) of two-photon system assisted by a fixed frequency-based
entanglement and a time interval DOF. The parity information the spatial-based
and polarization-based hyper-entanglement can be distinguished by the distinct
time intervals of the photon pairs, and the phase information can be
distinguished by the detection signature. Compared with previous schemes, the
number of the auxiliary entanglements is reduced from two to one by introducing
time interval DOF. Moreover, the additional frequency and time interval DOFs
suffer less from the collective channel noise.


  We show asymptotic, exponential stability of the equilibrium configuration,
$\smallL$, of a hollow physical pendulum with its inner part entirely filled
with a viscous liquid, corresponding to the center of mass being in the lowest
position. Moreover, we prove that every weak solution with initial data
possessing finite total initial energy and belonging to a "large" open set,
becomes eventually smooth and decays exponentially fast to the equilibrium
$\smallL$. These results are obtained also as byproduct of a "generalized
linearization principle" that we show for evolution equations with non-empty
"slow" center manifold.


  Stochastic heating refers to an increase in the average magnetic moment of
charged particles interacting with electromagnetic fluctuations whose
frequencies are smaller than the particles' cyclotron frequencies. This type of
heating arises when the amplitude of the gyroscale fluctuations exceeds a
certain threshold, causing particle orbits in the plane perpendicular to the
magnetic field to become stochastic rather than nearly periodic. We consider
the stochastic heating of protons by Alfv\'en-wave (AW) and
kinetic-Alfv\'en-wave (KAW) turbulence, which may make an important
contribution to the heating of the solar wind. Using phenomenological
arguments, we derive the stochastic-proton-heating rate in plasmas in which
$\beta_{\rm p} \sim 1-30$, where $\beta_{\rm p}$ is the ratio of the proton
pressure to the magnetic pressure. (We do not consider the $\beta_{\rm p}
\gtrsim 30$ regime, in which KAWs at the proton gyroscale become
non-propagating.) We test our formula for the stochastic-heating rate by
numerically tracking test-particle protons interacting with a spectrum of
randomly phased AWs and KAWs. Previous studies have demonstrated that at
$\beta_{\rm p} \lesssim 1$, particles are energized primarily by time
variations in the electrostatic potential and thermal-proton gyro-orbits are
stochasticized primarily by gyroscale fluctuations in the electrostatic
potential. In contrast, at $\beta_{\rm p} \gtrsim 1$, particles are energized
primarily by the solenoidal component of the electric field and thermal-proton
gyro-orbits are stochasticized primarily by gyroscale fluctuations in the
magnetic field.


  In this paper, we propose a dual-stage architecture for bandwidth extension
(BWE) increasing the effective sampling rate of speech signals from 8 kHz to 48
kHz. Unlike existing end-to-end deep learning models, our proposed method
explicitly models BWE using excitation and linear time-varying (LTV) filter
stages. The excitation stage broadens the spectrum of the input, while the
filtering stage properly shapes it based on outputs from an acoustic feature
predictor. To this end, an acoustic feature loss term can implicitly promote
the excitation subnetwork to produce white spectra in the upper frequency band
to be synthesized. Experimental results demonstrate that the added inductive
bias provided by our approach can improve upon BWE results using the generators
from both SEANet or HiFi-GAN as exciters, and that our means of adapting
processing with acoustic feature predictions is more effective than that used
in HiFi-GAN-2. Secondary contributions include extensions of the SEANet model
to accommodate local conditioning information, as well as the application of
HiFi-GAN-2 for the BWE problem.


  Single-electron capacitance spectroscopy precisely measures the energies
required to add individual electrons to a quantum dot. The spatial extent of
electronic wavefunctions is probed by investigating the dependence of these
energies on changes in the dot confining potential. For low electron densities,
electrons occupy distinct spatial sites localized within the dot. At higher
densities, the electrons become delocalized, and all wavefunctions are spread
over the full dot area. Near the delocalization transition, the last remaining
localized states exist at the perimeter of the dot. Unexpectedly, these
electrons appear to bind with electrons in the dot center.


  Learning accurate dynamics models is necessary for optimal, compliant control
of robotic systems. Current approaches to white-box modeling using analytic
parameterizations, or black-box modeling using neural networks, can suffer from
high bias or high variance. We address the need for a flexible, gray-box model
of mechanical systems that can seamlessly incorporate prior knowledge where it
is available, and train expressive function approximators where it is not. We
propose to parameterize a mechanical system using neural networks to model its
Lagrangian and the generalized forces that act on it. We test our method on a
simulated, actuated double pendulum. We show that our method outperforms a
naive, black-box model in terms of data-efficiency, as well as performance in
model-based reinforcement learning. We also conduct a systematic study of our
method's ability to incorporate available prior knowledge about the system to
improve data efficiency.


  We consider a Weyl-invariant formulation of gravity with a cosmological
constant in d-dimensional spacetime and show that near two dimensions the
classical action reduces to the timelike Liouville action. We show that the
renormalized cosmological term leads to a nonlocal quantum momentum tensor
which satisfies theWard identities in a nontrivial way. The resulting evolution
equations for an isotropic, homogeneous universe lead to a slowly decaying
vacuum energy and a power-law expansion. We outline the implications for the
cosmological constant problem, inflation, and dark energy.


  Direct consequences on kaon production of the picture proposed in a recent
Letter and subsequent publications are discussed. Further evidence supporting
the proposed picture is obtained. Comparison with the data for the inclusive
cross sections in unpolarized reactions is made. Quantitative results for the
left-right asymmetry in single-spin processes are presented.


  Mutually coupled modes of a pair of active LRC circuits, one with
amplification and another with an equivalent amount of attenuation, provide an
experimental realization of a wide class of systems where gain/loss mechanisms
break the Hermiticity while preserving parity-time PT symmetry. For a value PT
of the gain/loss strength parameter the eigen-frequencies undergo a spontaneous
phase transition from real to complex values, while the normal modes coalesce
acquiring a definite chirality. The consequences of the phase-transition in the
spatiotemporal energy evolution are also presented.


  Using a hadron-string cascade model, JPCIAE, we study the effect of nuclear
deformation on J/Psi suppression in the collision of uranium nuclei at 200A
GeV/c. We find that the J/Psi survival probability is much smaller if the major
axes of both deformed nuclei are along the beam direction than if they are
perpendicular to the beam direction.


  Gravitational wave bursts in the formation of neutron stars and black holes
in energetic core-collapse supernovae (CC-SNe) are of potential interest to
LIGO-Virgo and KAGRA. Events nearby are readily discovered using moderately
sized telescopes. CC-SNe are competitive with mergers of neutron stars and
black holes, if the fraction producing an energetic output in gravitational
waves exceeds about 1\%. This opportunity motivates the design of a novel
Sejong University Core-CollapsE Supernova Survey (SUCCESS), to provide triggers
for follow-up searches for gravitational waves. It is based on the 76 cm Sejong
University Telescope (SUT) for weekly monitoring of nearby star-forming
galaxies, i.e., M51, M81-M82 and Blue Dwarf Galaxies from the Unified Nearby
Galaxy Catalog with an expected yield of a few hundred per year. Optical light
curves will be resolved for the true time-of-onset for probes of gravitational
waves by broadband time-sliced matched filtering.


  To facilitate zero-shot generalization in taskoriented dialog, this paper
proposes Language Models as Data (LAD). LAD is a paradigm for creating diverse
and accurate synthetic data which conveys the necessary structural constraints
and can be used to train a downstream neural dialog model. LAD leverages GPT-3
to induce linguistic diversity. LAD achieves significant performance gains in
zero-shot settings on intent prediction (+15%), slot filling (+31.4 F-1) and
next action prediction (+11 F1). Furthermore, an interactive human evaluation
shows that training with LAD is competitive with training on human dialogs. LAD
is open-sourced, with the code and data available at
https://github.com/Shikib/lad.


  We present a detailed analysis on the phases of the WMAP foregrounds
(synchrotron, free-free and dust emission) of the WMAP K-W bands in order to
estimate the significance of the variation of the spectral indices at different
components. We first extract the spectral-index varying signals by assuming
that the invariant part among different frequency bands have 100%
cross-correlation of phases. We then use the minimization of variance, which is
normally used for extracting the CMB signals, to extract the frequency
independent signals. Such a common signal in each foreground component could
play a significant role for any kind of component separation methods, because
the methods cannot discriminate frequency independent foregrounds and CMB.


  The origin of the iron-group elements titanium to zinc in nature is
understood to occur under explosive burning conditions in both Type Ia
(thermonuclear) and Type II (core collapse) supernovae. In these dynamic
environments, the most abundant product is found to be 56Ni ({\tau} = 8.5 days)
that decays through 56Co ({\tau} = 111.5 days) to 56Fe. For the case of SNe Ia,
the peak luminosities are proportional to the mass ejected in the form of 56Ni.
It follows that the diversity of SNe Ia reflected in the range of peak
luminosity provides a direct measure of the mass of 56Ni ejected. In this
contribution, we identify and briefly discuss the factors that can influence
the 56Ni mass and use both observations and theory to quantify their impact. We
address specifically the variations in different stellar populations and
possible distinctions with respect to SNe Ia progenitors.


  The string breaking is discussed in U(1)^{N-1} Abelian effective theories of
QCD. When a screening is expected, the static potential shows a flattening in
the long-range region and a linear behavior in the intermediate region. We show
why the screening is better observed in the Polyakov-loop correlators than in
the Wilson loops. The breaking of the adjoint string is explained without the
Z(N) picture.


  We refine necessary and sufficient conditions for the generating series of a
weighted model of a quarter plane walk to be differentially algebraic. In
addition, we give algorithms based on the theory of Mordell-Weil lattices,
that, for each weighted model, yield polynomial conditions on the weights
determining this property of the associated generating series.


  A practical solution for the mathematical problem of functional calculus with
Laplace-Beltrami operator on surfaces with axial symmetry is found. A
quantitative analysis of the spectrum is presented.


  We present a combined observational and theoretical analysis to investigate
the nature of plasma turbulence at kinetic scales in the Earth's magnetosheath.
In the first decade of the kinetic range, just below the ion gyroscale, the
turbulence was found to be similar to that in the upstream solar wind:
predominantly anisotropic, low-frequency and kinetic Alfv\'en in nature. A key
difference, however, is that the magnetosheath ions are typically much hotter
than the electrons, $T_\mathrm{i}\gg T_\mathrm{e}$, which, together with
$\beta_\mathrm{i}\sim 1$, leads to a change in behaviour in the second decade,
close to electron scales. The turbulence here is characterised by an increased
magnetic compressibility, following a mode we term the inertial kinetic
Alfv\'en wave, and a steeper spectrum of magnetic fluctuations, consistent with
the prediction $E_B(k_\perp)\propto k_\perp^{-11/3}$ that we obtain from a set
of nonlinear equations. This regime of plasma turbulence may also be relevant
for other astrophysical environments with $T_\mathrm{i}\gg T_\mathrm{e}$, such
as the solar corona, hot accretion flows, and regions downstream of
collisionless shocks.


  A nontrivial commutator cannot be a proper power in a torsion-free group
satisfying C'(\lambda) small cancellation condition with sufficiently small
\lambda.