  A recent cross section measurement of the deuteron breakup reaction $pd\to
(pp)(0^\circ)+n(180^\circ)$, in the GeV region in a kinematics similar to
backward $pd$ elastic scattering, strongly contradicts predictions of a $pd \to
dp$ model based on the one-nucleon exchange, single pN scattering and $\Delta$
excitation mechanisms, and on the wave functions of the Reid soft core and
Paris $NN$ potentials. We show within the same model that for the CD Bonn $NN$
potential there is qualitative agreement with the data. It is attributed to a
reduction of the one-nucleon exchange at energies above 1 GeV and an increase
of the $\Delta(1232)$-isobar contribution, both related to the short-range
properties of the wave functions generated by this potential.


  Quantum Landauer's principle provides a fundamental lower bound for energy
dissipation occurred with information erasure in the quantum regime. While most
studies have related the entropy reduction incorporated with the erasure to the
lower bound~(entropic bound), recent efforts have also provided another lower
bound associated with the thermal fluctuation of the dissipated
energy~(thermodynamic bound). The coexistence of the two bounds has stimulated
comparative studies of their properties; however, these studies were performed
for systems where the time-evolution of diagonal (population) and off-diagonal
(coherence) elements of the density matrix are decoupled. In this paper, we
aimed to broaden the comparative study to include the influence of quantum
coherence induced by the tilted system--reservoir interaction direction. By
examining their dependence on the initial state of the information-bearing
system, we find that the following properties of the bounds are generically
held regardless of whether the influence of the coherence is present or not:
the entropic bound serves as the tighter bound for a sufficiently mixed initial
state, while the thermodynamic bound is tighter when the purity of the initial
state is sufficiently high. The exception is the case where the system dynamics
involve only phase relaxation; in this case, the two bounds coincide when the
initial coherence is zero; otherwise, the thermodynamic bound serves the
tighter bound. We also find the quantum information erasure inevitably
accompanies constant energy dissipation caused by the creation of
system--reservoir correlation, which may cause an additional source of
energetic cost for the erasure.


  We propose novel methods for change-point testing for nonparametric
estimators of expected shortfall and related risk measures in weakly dependent
time series. We can detect general multiple structural changes in the tails of
marginal distributions of time series under general assumptions.
Self-normalization allows us to avoid the issues of standard error estimation.
The theoretical foundations for our methods are functional central limit
theorems, which we develop under weak assumptions. An empirical study of S&P
500 and US Treasury bond returns illustrates the practical use of our methods
in detecting and quantifying market instability via the tails of financial time
series.


  A new class of partial order-types, class $\gbqo^+$ is defined and
investigated here. A poset $P$ is in the class $W^+ $ iff the free poset
algebra $F(P)$ is generated by a better quasi-order $G$ that is included in the
free lattice $L(P)$.
  We prove that if $P$ is any well quasi-ordering, then $L(P)$ is well founded,
and is a countable union of well quasi-orderings. We prove that the class $W^+$
is contained in the class of well quasi-ordered sets. We prove that $W^+$ is
preserved under homomorphic image, finite products, and lexicographic sum over
better quasi-ordered index sets. We prove also that every countable well
quasi-ordered set is in $W^+$. We do not know, however if the class of well
quasi-ordered sets is contained in $W^+$. Additional results concern
homomorphic images of posets algebras.


  Poincar{\'e} inequalities are ubiquitous in probability and analysis and have
various applications in statistics (concentration of measure, rate of
convergence of Markov chains). The Poincar{\'e} constant, for which the
inequality is tight, is related to the typical convergence rate of diffusions
to their equilibrium measure. In this paper, we show both theoretically and
experimentally that, given sufficiently many samples of a measure, we can
estimate its Poincar{\'e} constant. As a by-product of the estimation of the
Poincar{\'e} constant, we derive an algorithm that captures a low dimensional
representation of the data by finding directions which are difficult to sample.
These directions are of crucial importance for sampling or in fields like
molecular dynamics, where they are called reaction coordinates. Their knowledge
can leverage, with a simple conditioning step, computational bottlenecks by
using importance sampling techniques.


  A new model for a cluster of hybrid sensors network with multi sub-clusters
is proposed. The model is in particular relevant to the early warning system in
a large scale monitoring system in, for example, a nuclear power plant. It
mainly addresses to a safety critical system which requires real-time processes
with high accuracy. The mathematical model is based on the extended
conventional search algorithm with certain interactions among the nearest
neighborhood of sensors. It is argued that the model could realize a highly
accurate decision support system with less number of parameters. A case of one
dimensional interaction function is discussed, and a simple algorithm for the
model is also given.


  We report on recent work about the study of quark mass dependence of nucleon
magnetic moments and axial-vector coupling constant. We examine the feasibility
of chiral effective field theory methods for the extrapolation of lattice QCD
data obtained at relative large pion masses down to the physical values.


  We present the first Dyson-Schwinger equation calculation of the light hadron
spectrum that simultaneously correlates the masses of meson and baryon ground-
and excited-states within a single framework. At the core of our analysis is a
symmetry-preserving treatment of a vector-vector contact interaction. In
comparison with relevant quantities the
root-mean-square-relative-error/degree-of freedom is 13%. Notable amongst our
results is agreement between the computed baryon masses and the bare masses
employed in modern dynamical coupled-channels models of pion-nucleon reactions.
Our analysis provides insight into numerous aspects of baryon structure; e.g.,
relationships between the nucleon and Delta masses and those of the
dressed-quark and diquark correlations they contain.


  We propose a novel approach to estimating the precision matrix of
multivariate Gaussian data that relies on decomposing them into a low-rank and
a diagonal component. Such decompositions are very popular for modeling large
covariance matrices as they admit a latent factor based representation that
allows easy inference. The same is however not true for precision matrices due
to the lack of computationally convenient representations which restricts
inference to low-to-moderate dimensional problems. We address this remarkable
gap in the literature by building on a latent variable representation for such
decomposition for precision matrices. The construction leads to an efficient
Gibbs sampler that scales very well to high-dimensional problems far beyond the
limits of the current state-of-the-art. The ability to efficiently explore the
full posterior space also allows the model uncertainty to be easily assessed.
The decomposition crucially additionally allows us to adapt sparsity inducing
priors to shrink the insignificant entries of the precision matrix toward zero,
making the approach adaptable to high-dimensional small-sample-size sparse
settings. Exact zeros in the matrix encoding the underlying conditional
independence graph are then determined via a novel posterior false discovery
rate control procedure. A near minimax optimal posterior concentration rate for
estimating precision matrices is attained by our method under mild regularity
assumptions. We evaluate the method's empirical performance through synthetic
experiments and illustrate its practical utility in data sets from two
different application domains.


  Curating high quality datasets that play a key role in the emergence of new
AI applications requires considerable time, money, and computational resources.
So, effective ownership protection of datasets is becoming critical. Recently,
to protect the ownership of an image dataset, imperceptible watermarking
techniques are used to store ownership information (i.e., watermark) into the
individual image samples. Embedding the entire watermark into all samples leads
to significant redundancy in the embedded information which damages the
watermarked dataset quality and extraction accuracy. In this paper, a
multi-segment encoding-decoding method for dataset watermarking (called AMUSE)
is proposed to adaptively map the original watermark into a set of shorter
sub-messages and vice versa. Our message encoder is an adaptive method that
adjusts the length of the sub-messages according to the protection requirements
for the target dataset. Existing image watermarking methods are then employed
to embed the sub-messages into the original images in the dataset and also to
extract them from the watermarked images. Our decoder is then used to
reconstruct the original message from the extracted sub-messages. The proposed
encoder and decoder are plug-and-play modules that can easily be added to any
watermarking method. To this end, extensive experiments are preformed with
multiple watermarking solutions which show that applying AMUSE improves the
overall message extraction accuracy upto 28% for the same given dataset
quality. Furthermore, the image dataset quality is enhanced by a PSNR of
$\approx$2 dB on average, while improving the extraction accuracy for one of
the tested image watermarking methods.


  We discuss the application of multilevel Monte Carlo methods to elliptic
partial differential equations with random coefficients. Such problems arise,
for example, in uncertainty quantification in subsurface flow modeling. We give
a brief review of recent advances in the numerical analysis of the multilevel
algorithm under minimal assumptions on the random coefficient, and extend the
analysis to cover also tensor--valued coefficients, as well as point
evaluations. Our analysis includes as an example log--normal random
coefficients, which are frequently used in applications.


  A relativistic petawatt laser light can heat heavy metals over keV
temperature isochorically and ionize them almost fully. Copious hard X-rays are
emitted from the high-Z hot plasma which acts as X-ray sources, while they work
as a cooling process of the plasma. The cooling process can affect on the
creation of high energy density plasma via the interaction, however, the
details are unknown. The X-ray spectrum depends on the plasma temperature, so
that it is worthwhile to investigate the radiation cooling effects. We here
study the isochoric heating of a solid silver foil irradiated by relativistic
laser lights with a help of particle-in-cell simulations including Coulomb
collisions, ionizations, and radiation processes. We have conducted a parameter
survey varying laser intensity, $10^{18-20}\,\rm{W/cm^2}$, to check the cooling
effects while keeping the incident laser energy constant. The silver plasma
heated mainly by the resistive heating dissipates its energy by keV X-ray
emissions in a picosecond time scale. The radiation power from the silver foil
is found to be comparable to the incident laser power when the laser intensity
is less than $10^{19}\,{\rm W/cm^2}$ under the constant energy situation. The
evolution of the plasma energy density inside the target is then suppressed,
due to which a highly compressed collisional shock is formed at the target
surface and propagates into the plasma. The radiation spectra of the keV silver
plasma are also demonstrated.


  Hyperledger Fabric (HLF), one of the most popular private blockchains, has
recently received attention for blockchain-enabled Internet of Things (IoT).
However, for IoT applications to handle time-sensitive data, the processing
latency in HLF has emerged as a new challenge. In this article, therefore, we
establish a practical HLF latency model for HLF-enabled IoT. We first discuss
the structure and transaction flow of HLF-enabled IoT. After implementing real
HLF, we capture the latencies that each transaction experiences and show that
the total latency of HLF can be modeled as a Gamma distribution, which is
validated by conducting a goodness-of-fit test (i.e., the Kolmogorov-Smirnov
(KS) test). We also provide the parameter values of the modeled latency
distribution for various HLF environments. Furthermore, we explore the impacts
of three important HLF parameters including transaction generation rate, block
size, and block-generation timeout on the HLF latency. As a result, this
article provides design insights on minimizing the latency for HLF-enabled IoT.


  We discuss many new subleading processes for inclusive production of $W^+
W^-$ pairs not included in the literature so far. We focus on photon-photon
induced processes. We include elastic-elastic, elastic-inelastic,
inelastic-elastic and inelastic-inelastic contributions. The inelastic photon
distributions in the proton are calculated in two different ways: naive
approach used already in the literature and using photon distributions by
solving special evolution equation with photon being a parton in the proton.
The results strongly depend on the approach used. We calculate also
contributions with resolved photons. The diffractive components have similar
characteristics as the photon-photon elastic-inelastic and inelastic-elastic
mechanisms. The subleading contributions are compared with the well known $q
\bar q$ and $g g$ as well as with double-parton scattering contributions.
Predictions for the total cross section and differential distributions in $W$-
boson rapidity and transverse momentum as well as $WW$ invariant mass are
presented. The $\gamma \gamma$ components constitute only about 1-2 % of the
inclusive $W^+ W^-$ cross section but about 10 % at large $W^{\pm}$ transverse
momenta, and are even comparable to the dominant $q \bar q$ component at large
$M_{WW}$, i.e. are much larger than the often celebrated $g g \to W^+ W^-$
component. Its size is comparable to double parton scattering contribution.
Only elastic-elastic, elastic-inelastic and inelastic-elastic contributions
could be potentially measured to verify our predictions using forward proton
detectors.


  This paper offers an overview of the mobile Boolean stochastic geometric
model which is a time-dependent version of the ordinary Boolean model in a
Euclidean space of dimension $d$. The main question asked is that of obtaining
the law of the detection time of a fixed set. We give various ways of thinking
about this which result into some general formulas. The formulas are solvable
in some special cases, such the inertial and Brownian mobile Boolean models. In
the latter case, we obtain some expressions for the distribution of the
detection time of a ball, when the dimension $d$ is odd and asymptotics when
$d$ is even. Finally, we pose some questions for future research.


  Topological charge pumping represents an important quantum phenomenon that
shows the fundamental connection to the topological properties of dynamical
systems. Here, we introduce a pumping process in a spin-dependent double-well
optical lattice with glide symmetry. In the dynamic process, the glide symmetry
protects the band touching points and topological properties of the system are
characterised by the non-Abelian Berry curvature. By engineering suitable form
of interaction between different spin components, the model not only
demonstrates topological phase transition, but also shows hybridisation between
the spatial and temporal domain with novel topological features captured by the
Wilson line along the synthetic directions. Our work provides a new model based
on ultracold atoms towards the implementation of versatile topological matters
and topological phenomena.


  Optical coherence tomography (OCT) is a volumetric imaging modality that
empowers clinicians and scientists to noninvasively visualize the
cross-sections of biological samples. As the latest generation of its kind,
Fourier-domain OCT (FD-OCT) offers a micrometer-scale axial resolution by
taking advantage of coherence gating. Based on the current theory, it is
believed the only way to obtain a higher-axial-resolution OCT image is to
physically extend the system's spectral bandwidth given a certain central
wavelength. Here, we showed the belief is wrong. We proposed a novel
reconstruction framework, which integrates prior knowledge and exploits the
\emph{shift-variance}, to retrospectively super-resolve OCT images without
altering the system configurations. Both numerical and experimental results
confirmed the processed image manifested an axial resolution beyond the
previous theoretical prediction. We believe this result not only opens new
horizons for future research directions in OCT reconstruction but also promises
an immediate upgrade to tens of thousands of legacy OCT units currently
deployed.


  We study the antiferromagnetic spin-half Heisenberg ladder in the presence of
an additional frustrating rung spin which is motivated and relevant also for
the description of real two-dimensional materials such as the two-dimensional
trimer magnet Ba$_4$Ir$_3$O$_{10}$. We study the zero-temperature phase
diagram, where we combine numerical and analytical methods into an overall
consistent description. All numerical simulations are also accompanied by
studies of the dynamical spin structure factor obtained via the density matrix
renormalization group. Overall, we find in the regime of strong rung coupling a
gapped dimerized phase related to competing symmetry sectors in Hilbert space
that ultimately results in frustration-driven spin-Peierls transition. In the
weak rung-coupling regime, the system is uniform, yet shows a gapped spinon
continuum together with a sharp coherent low-energy branch which renders the
system critical overall. In either case, the additional rung spin quickly get
sidelined and nearly decouple once their bare coupling to the ladder drops
somewhat below the direct Heisenberg coupling of the legs.


  Van Marle et al. (2005) showed that circumstellar absorption lines in early
Type Ib/c supernova and gamma-ray burst afterglow spectra may reveal the
progenitor evolution of the exploding Wolf-Rayet star. While the quoted paper
deals with Wolf-Rayet stars which evolved through a red supergiant stage, we
investigate here the initially more massive Wolf-Rayet stars which are thought
to evolve through a Luminous Blue Variable (LBV) stage. We perform hydrodynamic
simulations of the evolution of the circumstellar medium around a 60 Msol star,
from the main sequence through the LBV and Wolf-Rayet stages, up to core
collapse. We then compute the column density of the circumstellar matter as a
function of radial velocity, time and angle. This allows a comparison with the
number and blue-shifts, of absorption components in the spectra of LBVs,
Wolf-Rayet stars, Type Ib/c supernovae and gamma-ray burst afterglows. Our
simulation for the post-LBV stage shows the formation of various absorption
components, which are, however, rather short lived; they dissipate on time
scales shorter than 50,000yr. As the LBV stage is thought to occur at the
beginning of core helium burning, the remaining Wolf-Rayet life time is
expected to be one order of magnitude larger. When interpreting the absorption
components in the afterglow spectrum of GRB-021004 as circumstellar, it can be
concluded that the progenitor of this source did most likely not evolve through
an LBV stage. However, a close binary with late common-envelope phase (Case C)
may produce a circumstellar medium that closely resembles the LBV to Wolf-Rayet
evolution, but with a much shorter Wolf-Rayet period.


  This paper deals with the estimation of rare event probabilities using
importance sampling (IS), where an optimal proposal distribution is computed
with the cross-entropy (CE) method. Although, IS optimized with the CE method
leads to an efficient reduction of the estimator variance, this approach
remains unaffordable for problems where the repeated evaluation of the score
function represents a too intensive computational effort. This is often the
case for score functions related to the solution of a partial differential
equation (PDE) with random inputs. This work proposes to alleviate computation
by the parsimonious use of a hierarchy of score function approximations in the
CE optimization process. The score function approximation is obtained by
selecting the surrogate of lowest dimensionality, whose accuracy guarantees to
pass the current CE optimization stage. The selection relies on certified upper
bounds on the error norm. An asymptotic analysis provides some theoretical
guarantees on the efficiency and convergence of the proposed algorithm.
Numerical results demonstrate the gain brought by the method in the context of
pollution alerts and a system modeled by a PDE.


  The Infrared Spectrograph (IRS) is one of the three instruments on board the
Space Infrared Telescope Facility (SIRTF) to be launched in December 2001. The
IRS will provide high resolution spectra (R = 600) from 10-37 microns and low
resolution spectra (R >= 60) from 5-40microns. Its high sensitivity and
``spectral mapping''-mode make it a powerful instrument for observing both
faint point-like and extended sources. We discuss the performance of the IRS on
faint extragalactic targets and present simulated spectra of starbursts and
AGNs at high redshift. In addition, we discuss the determination of redshifts
from the low resolution spectra.


  We calculate the resistance and mean free path in long metallic and
semiconducting silicon nanowires (SiNWs) using two different numerical
approaches: A real space Kubo method and a recursive Green's function method.
We compare the two approaches and find that they are complementary: depending
on the situation a preferable method can be identified. Several numerical
results are presented to illustrate the relative merits of the two methods. Our
calculations of relaxed atomic structures and their conductance properties are
based on density functional theory without introducing adjustable parameters.
Two specific models of disorder are considered: Un-passivated, surface
reconstructed SiNWs are perturbed by random on-site (Anderson) disorder whereas
defects in hydrogen passivated wires are introduced by randomly removed H
atoms. The un-passivated wires are very sensitive to disorder in the surface
whereas bulk disorder has almost no influence. For the passivated wires, the
scattering by the hydrogen vacancies is strongly energy dependent and for
relatively long SiNWs (L>200 nm) the resistance changes from the Ohmic to the
localization regime within a 0.1 eV shift of the Fermi energy. This high
sensitivity might be used for sensor applications.


  We give an algorithmic framework for minimizing general convex objectives
(that are differentiable and monotone non-decreasing) over a set of covering
constraints that arrive online. This substantially extends previous work on
online covering for linear objectives (Alon {\em et al.}, STOC 2003) and online
covering with offline packing constraints (Azar {\em et al.}, SODA 2013). To
the best of our knowledge, this is the first result in online optimization for
generic non-linear objectives; special cases of such objectives have previously
been considered, particularly for energy minimization.
  As a specific problem in this genre, we consider the unrelated machine
scheduling problem with startup costs and arbitrary $\ell_p$ norms on machine
loads (including the surprisingly non-trivial $\ell_1$ norm representing total
machine load). This problem was studied earlier for the makespan norm in both
the offline (Khuller~{\em et al.}, SODA 2010; Li and Khuller, SODA 2011) and
online settings (Azar {\em et al.}, SODA 2013). We adapt the two-phase approach
of obtaining a fractional solution and then rounding it online (used
successfully to many linear objectives) to the non-linear objective. The
fractional algorithm uses ideas from our general framework that we described
above (but does not fit the framework exactly because of non-positive entries
in the constraint matrix). The rounding algorithm uses ideas from offline
rounding of LPs with non-linear objectives (Azar and Epstein, STOC 2005; Kumar
{\em et al.}, FOCS 2005). Our competitive ratio is tight up to a logarithmic
factor. Finally, for the important special case of total load ($\ell_1$ norm),
we give a different rounding algorithm that obtains a better competitive ratio
than the generic rounding algorithm for $\ell_p$ norms. We show that this
competitive ratio is asymptotically tight.


  We study analytical properties of the generalized $\lambda$-deformation,
which modifies string theories while preserving integrability, and construct
the explicit backgrounds corresponding to AdS_p x S^p, including the
Ramond-Ramond fluxes. For an arbitrary coset, we find the general form of the
R-matrix underlying the deformation, and prove that the dilaton is not modified
by the deformation, while the frames are multiplied by a constant matrix. Our
explicit solutions describe families of integrable string theories depending on
several continuous parameters.


  For high-dimensional classification Fishers rule performs poorly due to noise
from estimation of the covariance matrix. Fan, Feng and Tong (2012) introduced
the ROAD classifier that puts an $L_1$-constraint on the classification vector.
In their Theorem 1 Fan, Feng and Tong (2012) show that the ROAD classifier
asymptotically has the same misclassification rate as the corresponding oracle
based classifier. Unfortunately, the proof contains an error. Here we restate
the theorem and provide a new proof.


  Consider a large number of detectors each generating a data stream. The task
is to detect online, distribution changes in a small fraction of the data
streams. Previous approaches to this problem include the use of mixture
likelihood ratios and sum of CUSUMs. We provide here extensions and
modifications of these approaches that are optimal in detecting normal mean
shifts. We show how the (optimal) detection delay depends on the fraction of
data streams undergoing distribution changes as the number of detectors goes to
infinity. There are three detection domains. In the first domain for moderately
large fractions, immediate detection is possible. In the second domain for
smaller fractions, the detection delay grows logarithmically with the number of
detectors, with an asymptotic constant extending those in sparse normal mixture
detection. In the third domain for even smaller fractions, the detection delay
lies in the framework of the classical detection delay formula of Lorden. We
show that the optimal detection delay is achieved by the sum of detectability
score transformations of either the partial scores or CUSUM scores of the data
streams.


  The electron-cyclotron maser is a process that generates intense and coherent
radio emission in plasma. In this paper, we present a comprehensive parametric
investigation on the electron-cyclotron-maser instability driven by non-thermal
ring-beam electrons with intrinsic Alfv\'en waves which pervade the solar
atmosphere and interplanetary space. It is found that both forward propagating
and backward propagating waves can be excited in the fast ordinary (O) and
extraordinary (X) electromagnetic modes. The growth rates of X1 mode are almost
always weakened by Alfv\'en waves. The average pitch-angle $\phi_0$ of
electrons is a key parameter for the effect of Alfv\'en waves on the growth
rate of modes O1, O2 and X2. For a beam-dominated electron distribution
($\phi_0 \lesssim 30^\circ$ ), the growth rates of the maser instability for
O1, O2 and X2 modes are enhanced with the increase of Alfv\'en wave energy
density. In other conditions, the growth rates of O1, O2 and X2 modes weakened
with increasing Alfv\'en wave intensity, except that the growth of O1 mode may
also be enhanced by Alfv\'en waves for a ring distribution. The results may be
important for us in analyzing the mechanism of radio bursts with various fine
structures observed in space and astrophysical plasmas.


  Few materials undergo cooperative Jahn-Teller (JT) transitions at low
temperatures, but zircon-type oxides are one class that includes DyVO$_4$,
which transforms from a tetragonal to an orthorhombic structure at around 13.6
K, with a narrow transition temperature range within 0.5 K. Since many
rare-earth ions can be accommodated in the structure, there should be ample
routes to vary the transition temperature and structural effects of the
transition. We have synthesized pure DyVO$_4$ and solid solutions
Dy$_{1-x}$Tm$_x$VO$_4$ ($x$ = 0.05, 0.1, 0.15, 0.2, and 0.5) and
Dy$_{1-y}$Pr$_y$VO$_4$ ($y$ = 0.03, 0.05, 0.1, 0.2, and 0.5), all by solution
precipitation. X-ray diffraction shows a systematic peak shift and a linear
change of lattice parameters with increasing substitution. We demonstrate
through heat capacity measurements that both Tm$^{3+}$ and Pr$^{3+}$
substitutions cause a depression of the cooperative JT transition temperature.
When the substitution level increases, the JT transition is eventually
suppressed. We examine a mean-field approximation model that can explain the
both the JT transition temperature shift and its eventual disappearance. The
cooperative JT effect in these zircon-type oxides is known to exhibit a large
magnetoelectric response, which should follow from the mean-field behavior. The
structural transformation can be easily detected via diffraction and can be
used as a temperature calibration in low temperature experiments.


  Given a dynamic graph subject to edge insertions and deletions, we show how
to update an implicit representation of a proper vertex colouring, such that
colours of vertices are computable upon query time. We give a deterministic
algorithm that uses $O(\alpha^2)$ colours for a dynamic graph of arboricity
$\alpha$, and a randomised algorithm that uses $O(\min\{\alpha \log \alpha,
\alpha \log \log \log n\})$ colours in the oblivious adversary model. Our
deterministic algorithm has update- and query times polynomial in $\alpha$ and
$\log n$, and our randomised algorithm has amortised update- and query time
that with high probability is polynomial in $\log n$ with no dependency on the
arboricity.
  Thus, we improve the number of colours exponentially compared to the
state-of-the art for implicit colouring, namely from $O(2^\alpha)$ colours, and
we approach the theoretical lower bound of $\Omega(\alpha)$ for this
arboricity-parameterised approach. Simultaneously, our randomised algorithm
improves the update- and query time to run in time solely polynomial in $\log
n$ with no dependency on $\alpha$. Our algorithms are fully adaptive to the
current value of the dynamic arboricity at query or update time.


  Optimal hematocrit $H_o$ maximizes oxygen transport. In healthy humans, the
average hematocrit $H$ is in the range of 40-45$\%$, but it can significantly
change in blood pathologies such as severe anemia (low $H$) and polycythemia
(high $H$). Whether the hematocrit level in humans corresponds to the optimal
one is a long standing physiological question. Here, using numerical
simulations with the Lattice Boltzmann method and two mechanical models of the
red blood cell (RBC) we predict the optimal hematocrit, and explore how
altering the mechanical properties of RBCs affects $H_o$. We develop a
simplified analytical theory that accounts for results obtained from numerical
simulations and provides insight into the physical mechanisms determining
$H_o$. Our numerical and analytical models can easily be modified to
incorporate a wide range of mechanical properties of RBCs as well as other soft
particles thereby providing means for the rational design of blood substitutes.
Our work lays the foundations for systematic theoretical study of the optimal
hematocrit and its link with pathological RBCs associated with various diseases
(e.g. sickle cell anemia, diabetes mellitus, malaria, elliptocytosis).


  In sustained growth with random dynamics stationary distributions can exist
without detailed balance. This suggests thermodynamical behavior in fast
growing complex systems. In order to model such phenomena we apply both a
discrete and a continuous master equation. The derivation of elementary rates
from known stationary distributions is a generalization of the
fluctuation--dissipation theorem. Entropic distance evolution is given for such
systems. We reconstruct distributions obtained for growing networks, particle
production, scientific citations and income distribution.


  We investigate whether a baryonic dark galaxy or `galaxy without stars' could
persist indefinitely in the local universe, while remaining stable against star
formation. To this end, a simple model has been constructed to determine the
equilibrium distribution and composition of a gaseous protogalactic disk.
Specifically, we determine the amount of gas that will transit to a Toomre
unstable cold phase via the H2 cooling channel in the presence of a UV--X-ray
cosmic background radiation field.
  All but one of the models are predicted to become unstable to star formation.
Moreover, we find that all our model objects would be detectable via HI line
emission, even in the case that star formation is potentially avoided. These
results are consistent with the non-detection of isolated extragalactic HI
clouds with no optical counterpart (galaxies without stars) by HIPASS.
  Additionally, where star formation is predicted to occur, we determine the
minimum interstellar radiation field required to restore gravothermal
stability, which we then relate to a minimum global star formation rate. This
leads to the prediction of a previously undocumented relation between HI mass
and star formation rate that is observed for a wide variety of dwarf galaxies
in the HI mass range 10^8--10^10 M_sun. The existence of such a relation
strongly supports the notion that the well observed population of dwarf
galaxies represent the minimum rates of self-regulating star formation in the
universe. (Barely abridged)


  Parity-time ($PT$) symmetric Hamiltonians are generally non-Hermitian and
give rise to exotic behaviour in quantum systems at exceptional points, where
eigenvectors coalesce. The recent realisation of $PT$-symmetric Hamiltonians in
quantum systems has ignited efforts to simulate and investigate many-particle
quantum systems across exceptional points. Here we use a programmable
integrated photonic chip to simulate a model comprised of twin pairs of
$PT$-symmetric Hamiltonians, with each the time reverse of its twin. We
simulate quantum dynamics across exceptional points including two- and
three-particle interference, and a particle-trembling behaviour that arises due
to interference between subsystems undergoing time-reversed evolutions. These
results show how programmable quantum simulators can be used to investigate
foundational questions in quantum mechanics.


  We investigate accessibility and controllability of a quantum system S
coupled to a quantum probe P, both described by two-dimensional Hilbert spaces,
under the hypothesis that the external control affects only P. In this context
accessibility and controllability properties describe to what extent it is
possible to drive the state of the system S by acting on P and using the
interaction between the two systems. We give necessary and sufficient
conditions for these properties and we discuss the relation with the entangling
capability of the interaction between S and P. In particular, we show that
controllability can be expressed in terms of the SWAP operator, acting on the
composite system, and its square root.


  We study the stochastic homogenization for a Cauchy problem for a first-order
Hamilton-Jacobi equation whose operator is not coercive w.r.t. the gradient
variable. We look at Hamiltonians like $H(x,\sigma(x)p,\omega)$ where
$\sigma(x)$ is a matrix associated to a Carnot group. The rescaling considered
is consistent with the underlying Carnot group structure, thus anisotropic. We
will prove that under suitable assumptions for the Hamiltonian, the solutions
of the $\varepsilon$-problem converge to a deterministic function which can be
characterized as the unique (viscosity) solution of a suitable deterministic
Hamilton-Jacobi problem.


  The subject of this paper is a special class of closed-chain manipulators.
First, we analyze a family of two-degree-of-freedom (dof) five-bar planar
linkages. Two Jacobian matrices appear in the kinematic relations between the
joint-rate and the Cartesian-velocity vectors, which are called the ``inverse
kinematics" and the "direct kinematics" matrices. It is shown that the loci of
points of the workspace where the condition number of the direct-kinematics
matrix remains constant, i.e., the isoconditioning loci, are the coupler points
of the four-bar linkage obtained upon locking the middle joint of the linkage.
Furthermore, if the line of centers of the two actuated revolutes is used as
the axis of a third actuated revolute, then a three-dof hybrid manipulator is
obtained. The isoconditioning loci of this manipulator are surfaces of
revolution generated by the isoconditioning curves of the two-dof manipulator,
whose axis of symmetry is that of the third actuated revolute.


  Two major causes of death in the United States and worldwide are stroke and
myocardial infarction. The underlying cause of both is thrombi released from
ruptured or eroded unstable atherosclerotic plaques that occlude vessels in the
heart (myocardial infarction) or the brain (stroke). Clinical studies show that
plaque composition plays a more important role than lesion size in plaque
rupture or erosion events. To determine the plaque composition, various cell
types in 3D cardiovascular immunofluorescent images of plaque lesions are
counted. However, counting these cells manually is expensive, time-consuming,
and prone to human error. These challenges of manual counting motivate the need
for an automated approach to localize and count the cells in images. The
purpose of this study is to develop an automatic approach to accurately detect
and count cells in 3D immunofluorescent images with minimal annotation effort.
In this study, we used a weakly supervised learning approach to train the
HoVer-Net segmentation model using point annotations to detect nuclei in
fluorescent images. The advantage of using point annotations is that they
require less effort as opposed to pixel-wise annotation. To train the HoVer-Net
model using point annotations, we adopted a popularly used cluster labeling
approach to transform point annotations into accurate binary masks of cell
nuclei. Traditionally, these approaches have generated binary masks from point
annotations, leaving a region around the object unlabeled (which is typically
ignored during model training). However, these areas may contain important
information that helps determine the boundary between cells. Therefore, we used
the entropy minimization loss function in these areas to encourage the model to
output more confident predictions on the unlabeled areas. Our comparison
studies indicate that the HoVer-Net model trained using our weakly ...


  In this paper, we will evaluate integrals that define the conditional
expectation, variance and characteristic function of stochastic processes with
respect to fractional Brownian motion (fBm) for all relevant Hurst indices,
i.e. $H \in (0,1)$. The fractional Ornstein-Uhlenbeck (fOU) process, for
example, gives rise to highly nontrivial integration formulas that need careful
analysis when considering the whole range of Hurst indices. We will show that
the classical technique of analytic continuation, from complex analysis,
provides a way of extending the domain of validity of an integral, from
$H\in(1/2,1)$, to the larger domain, $H\in(0,1)$. Numerical experiments for
different Hurst indices confirm the robustness and efficiency of the integral
formulations presented here. Moreover, we provide accurate and highly efficient
financial option pricing results for processes that are related to the fOU
process, with the help of Fourier cosine expansions.


  We present the classically simulated integration of a hadronization model,
based on neutral Rydberg atoms, with the PYTHIA event generator. The real-time
evolution of an interpreted charge-anticharge, in our Rydberg model, displays
features similar to string-breaking - reminiscent of the Lund string
fragmentation model used in PYTHIA for hadronization. We calculate the
real-time evolution classically for a Rydberg simulator with up to 26 atoms.
The behavior for increasing sites suggests that the model would be approaching
semi-realistic hadron multiplicities using current QuEra hardware.


  By means of a variational calculation using Matrix Product States with
periodic boundary conditions, we accurately determine the extension of the
spin-supersolid phase predicted to exist in the spin-1 anisotropic Heisenberg
chain. We compute both the structure factor and the superfluid stiffness, and
extract the critical exponents of the supersolid-to-solid phase transition.


  We explicitly construct the metric and torsion couplings of two-dimensional
(4,0)-super\-sym\-metric sigma models with target space a four-manifold that
are invariant under a $U(1)$ symmetry generated by a tri-holomorphic Killing
vector field that leaves in addition the torsion invariant. We show that the
metric couplings arise from magnetic monopoles on the three-sphere which is the
space of orbits of the group action generated by the tri-holomorphic Killing
vector field on the sigma model target manifold. We also examine the global
structure of a subclass of these metrics that are in addition $SO(3)$-invariant
and find that the only non-singular one, for models with non-zero torsion, is
that of $SU(2)\times U(1)$ WZW model.


  A plausible model is proposed for the enhancement of the abundance of
molecular species in bipolar outflow sources. In this model, levels of HCO+
enhancement are considered based on previous chemical calculations, that are
assumed to result from shock-induced desorption and photoprocessing of dust
grain ice mantles in the boundary layer between the outflow jet and the
surrounding envelope. A radiative transfer simulation that incorporates
chemical variations within the flow shows that the proposed abundance
enhancements in the boundary layer are capable of reproducing the observed
characteristics of the outflow seen in HCO+ emission in the star forming core
L1527. The radiative transfer simulation also shows that the emission lines
from the enhanced molecular species that trace the boundary layer of the
outflow exhibit complex line profiles indicating that detailed spatial maps of
the line profiles are essential in any attempt to identify the kinematics of
potential infall/outflow sources. This study is one of the first applications
of a full three dimensional radiative transfer code which incorporates chemical
variations within the source.


  The spatiotemporal stochastic dynamics of the voltage as well as the
upcrossing rate are derived for a model neuron comprising a long dendrite with
uniformly distributed filtered excitatory and inhibitory synaptic drive. A
cascade of ordinary and partial differential equations is obtained describing
the evolution of first-order means and second-order spatial covariances of the
voltage and its rate of change. These quantities provide an analytical form for
the general, steady-state and linear response of the upcrossing rate to dynamic
synaptic input. It is demonstrated that this minimal dendritic model has an
unexpectedly sustained high-frequency response despite synaptic, membrane and
spatial filtering.


  We show that, unlike vacuum General Relativity, Einstein-scalar theories
allow balanced static, neutral, asymptotically flat, double-black hole
solutions, for scalar field models minimally coupled to gravity, with
appropriate self-interactions. These are scalar hairy versions of the
double-Schwarzschild (or Bach-Weyl) solution, but regular on and outside the
two (topologically spherical) horizons. The balancing repulsive force is
provided by the scalar field. An explicit illustration is presented, using a
Weyl-type construction adapted to numerical solutions, requiring no partial
linearisation, or integrability structure, of the Einstein-scalar equations.
Fixing the couplings of the model, the balanced configurationsform a
one-parameter family of solutions, labelled by the proper distance between the
black holes.


  Solar analogues are important stars to study for understanding the properties
of the Sun. Evolutionary modeling, combined with seismic and spectroscopic
analysis, becomes a powerful method to characterize stellar intrinsic
parameters, such as mass, radius, metallicity and age.However, these
characteristics, relevant for other aspects of astrophysics or exoplanetary
system physics for example, are difficult to obtain with a high precision
and/or accuracy. The goal of this study is to characterize the two solar
analogues HD42618 and HD43587, observed by CoRoT. In particular, we aim to
infer precise mass, radius, and age, using evolutionary modeling constrained by
spectroscopic, photometric, and seismic analysis. These stars show evidences of
being older than the Sun but with a relatively large lithium abundance. We
present the seismic analysis of HD42618, and the modeling of the two solar
analogs HD42618 andHD43587 using the CESTAM stellar evolution code. Models were
computed to reproduce the spectroscopic (effective temperature and metallicity)
and seismic (mode frequencies) data,and the luminosity of the stars, based on
Gaia parallaxes. We infer very similar values of mass and radius for both stars
compared to the literature, within the uncertainties, and reproduce correctly
the seismic constraints. For HD42618, the modeling shows it is slightly less
massive and older than the Sun. For HD43587, it confirms it is more massive and
older than the Sun,in agreement with previous results. The use of chemical
clocks improves the reliability of our age estimates.


  In this work, we prove a weak Harnack estimate for the weak supersolutions to
the porous medium equation. The proof is based on a priori estimates for the
supersolutions and measure theoretical arguments.


  High spectral resolution mid-IR observations of ethylene (C2H4) towards the
AGB star IRC+10216 were obtained using the Texas Echelon Cross Echelle
Spectrograph (TEXES) at the NASA Infrared Telescope Facility (IRTF). Eighty
ro-vibrational lines from the 10.5 um vibrational mode nu7 with J<30 were
detected in absorption. The observed lines are divided into two groups with
rotational temperatures of 105 and 400 K (warm and hot lines). The warm lines
peak at ~-14 km/s with respect to the systemic velocity, suggesting that they
are mostly formed outwards from ~20R*. The hot lines are centered at -10 km/s
indicating that they come from a shell between 10 and 20R*. 35% of the observed
lines are unblended and can be fitted with a code developed to model the
emission of a spherically symmetric circumstellar envelope. The analysis of
several scenarios reveal that the C2H4 abundance relative to H2 in the range
5-20R* is 6.9E-8 in average and it could be as high as 1.1E-7. Beyond 20R*, it
is 8.2E-8. The total column density is 6.5(3.0)E15 cm^-2. C2H4 is found to be
rotationally under local thermodynamical equilibrium (LTE) and vibrationally
out of LTE. One of the scenarios that best reproduce the observations suggests
that up to 25% of the C2H4 molecules at 20R* could condense onto dust grains.
This possible depletion would not influence significantly the gas acceleration
although it could play a role in the surface chemistry on the dust grains.


  We consider the two dimensional pure gravity water waves with nonzero
constant vorticity in infinite depth, working in the holomorphic coordinates
introduced by Hunter, Ifrim, and Tataru. We show that close to the critical
velocity corresponding to zero frequency, a solitary wave exists. We use a
fixed point argument to construct the solitary wave whose profile resembles a
rescaled Benjamin-Ono soliton. The solitary wave is smooth and has an
asymptotic expansion in terms of powers of the Benjamin-Ono soliton.


  We present elemental abundances for all seven stars in Moving Group W11450
(Latham 1) to determine if they may be chemically related. These stars appear
to be both spatially and kinematically related, but no spectroscopic abundance
analysis exists in literature. Abundances for eight elements were derived via
equivalent width analyses of high resolution (R $\sim$60,000), high
signal-to-noise ratio ($\langle$SNR$\rangle\sim$100) spectra obtained with the
Otto Struve 2.1m telescope and Sandiford Echelle Spectrograph at McDonald
Observatory. The large star-to-star scatter in metallicity, -0.55 $\leq$ [Fe/H]
$\leq$ 0.06 dex ($\sigma$= 0.25), implies these stars were not produced from
the same chemically homogeneous molecular cloud, and are therefore not part of
a remnant or open cluster as previously proposed. Prior to this analysis, it
was suggested that two stars in the group, W11449 & W11450, are possible wide
binaries. The candidate wide binary pair show similar chemical abundance
patterns with not only iron, but with other elements analyzed in this study,
suggesting the proposed connection between these two stars may be real.


  We study the binary classification problem for Poisson point processes, which
are allowed to take values in a general metric space. The problem is tackled in
two different ways: estimating nonparametricaly the intensity functions of the
processes (and then plugged into a deterministic formula which expresses the
regression function in terms of the intensities), and performing the classical
$k$ nearest neighbor rule by introducing a suitable distance between patterns
of points. In the first approach we prove the consistency of the estimated
intensity so that the rule turns out to be also consistent. For the $k$-NN
classifier, we prove that the regression function fulfils the so called
"Besicovitch condition", usually required for the consistency of the classical
classification rules. The theoretical findings are illustrated on simulated
data, where in one case the $k$-NN rule outperforms the first approach.


  An Adaptive secondary mirror (ASM) allows for the integration of adaptive
optics (AO) into the telescope itself. Adaptive secondary mirrors, based on
hybrid variable reluctance (HVR) actuator technology, developed by TNO, provide
a promising path to telescope-integrated AO. HVR actuators have the advantage
of allowing mirrors that are stiffer, more power efficient, and potentially
less complex than similar, voice-coil based ASM's. We are exploring the
application of this technology via a laboratory testbed that will validate the
technical approach. In parallel, we are developing conceptual designs for ASMs
at several telescopes including the Automated Planet Finder Telescope (APF) and
for Keck Observatory. An ASM for APF has the potential to double the light
through the slit for radial velocity measurements, and dramatically improved
the image stability. An ASM for WMKO enables ground layer AO correction and
lower background infrared AO observations, and provides for more flexible
deployment of instruments via the ability to adjust the location of the
Cassegrain focus.


  In this paper we show that in addition to the known minimal surfaces which
appear in the literature for computing the entanglement entropy there are other
minimal surfaces with non-zero extrinsic curvature. We use the approach of
regularization procedure for computing the quadratic and cubic curvature
invariants on manifolds with squashed cones. The results can be used to find
the leading and universal terms of the holographic entanglement entropy to
understand which solution corresponds to the actual minimal surface.


  This work proposes an interval observer design for nonlinear discrete-time
systems based on the Kazantzis-Kravaris/Luenberger (KKL) paradigm. Our design
extends to generic nonlinear systems without any assumption on the structure of
its dynamics and output maps. Relying on a transformation putting the system
into a target form where an interval observer can be directly designed, we then
propose a method to reconstruct the bounds in the original coordinates using
the bounds in the target coordinates, thanks to the Lipschitz injectivity of
this transformation achieved under Lipschitz distinguishability when the target
dynamics have a high enough dimension and are pushed sufficiently fast. An
academic example serves to illustrate our methods.


  The electronic spectrum of sheets of graphite (plane honeycomb lattice)
folded into regular polihedra is studied. A continuum limit valid for
sufficiently large molecules and based on a tight binding approximation is
derived. It is found that a Dirac equation describes the flat graphite lattice.
Curving the lattice by insertion of odd numbered rings can be mimicked by
coupling effective gauge fields. In particular the $C_{60}$ and related
molecules are well described by the Dirac equation on the surface of a sphere
coupled to a color monopole sitting at its center.


  We present a class of models with a third generation seesaw mixing with new
vector-like weak-doublet quarks. We analyze a low-energy phenomenology and
present several strong dynamics, high-energy realizations of these models. In
the Topcolor type scenario, named Top-Bottom Color, we obtain an effective,
composite two Higgs doublet model where the third generation isospin splitting
is introduced via tilting interactions related to the broken non-abelian gauge
groups (i.e. without strong, triviality-sensitive U(1) groups). In addition, we
discuss $t\bar{t}$ production at the Next Linear Collider (NLC) and suggest how
one can experimentally observe and distinguish between the weak-doublet and the
weak-singlet types of seesaw mixing.


  Coherent analyses of experimental results from LHC and ILC will allow us to
draw a comprehensive and precise picture of the supersymmetric particle sector.
Based on this platform the fundamental supersymmetric theory can be
reconstructed at the high scale which is potentially close to the Planck scale.
This procedure will be reviewed for three characteristic examples: minimal
supergravity as the paradigm; a left-right symmetric extension incorporating
intermediate mass scales; and a specific realization of string effective
theories.


  We consider the novel Kaluza-Klein (KK) scenario where gravity propagates in
the $4+n$ dimensional bulk of spacetime, while gauge and matter fields are
confined to the 3+1 dimensional world-volume of a brane configuration. For
simplicity we assume compactification of the extra $n$ dimensions on a torus
with a common scale $R$, and identify the massive KK states in the
four-dimensional spacetime. For a given KK level $\vec{n}$ there are one spin-2
state, $(n-1)$ spin-1 states and $n(n-1)/2$ spin-0 states, all mass-degenerate.
We construct the effective interactions between these KK states and ordinary
matter fields (fermions, gauge bosons and scalars). We find that the spin-1
states decouple and that the spin-0 states only couple through the dilaton
mode. We then derive the interacting Lagrangian for the KK states and Standard
Model fields, and present the complete Feynman rules. We discuss some low
energy phenomenology for these new interactions for the case when 1/R is small
compared to the electroweak scale, and the ultraviolet cutoff of the effective
KK theory is on the order of 1 TeV.


  We present a neural network technique for the analysis and extrapolation of
time-series data called Neural Decomposition (ND). Units with a sinusoidal
activation function are used to perform a Fourier-like decomposition of
training samples into a sum of sinusoids, augmented by units with nonperiodic
activation functions to capture linear trends and other nonperiodic components.
We show how careful weight initialization can be combined with regularization
to form a simple model that generalizes well. Our method generalizes
effectively on the Mackey-Glass series, a dataset of unemployment rates as
reported by the U.S. Department of Labor Statistics, a time-series of monthly
international airline passengers, the monthly ozone concentration in downtown
Los Angeles, and an unevenly sampled time-series of oxygen isotope measurements
from a cave in north India. We find that ND outperforms popular time-series
forecasting techniques including LSTM, echo state networks, ARIMA, SARIMA, SVR
with a radial basis function, and Gashler and Ashmore's model.


  The 5D Holographic Big Bang is a novel model for the emergence of the early
universe out of a 5D collapsing star (an apparent white hole), in the context
of Dvali-Gabadadze-Porrati (DGP) cosmology. The model does not have a big bang
singularity, and yet can address cosmological puzzles that are traditionally
solved within inflationary cosmology. In this paper, we compute the exact power
spectrum of cosmological curvature perturbations due to the effect of a thin
atmosphere accreting into our 3-brane. The spectrum is scale-invariant on small
scales and red on intermediate scales, but becomes blue on scales larger than
the height of the atmosphere. While this behaviour is broadly consistent with
the non-parametric measurements of the primordial scalar power spectrum, it is
marginally disfavoured relative to a simple power law (at 2.7$\sigma$ level).
Furthermore, we find that the best fit nucleation temperature of our 3-brane is
at least 3 orders of magnitude larger than the 5D Planck mass, suggesting an
origin in a 5D quantum gravity phase.


  Ionic electro-active polymer (Nafion for example) can be used as sensor or
actuator. To this end, a thin film of the water-saturated material is
sandwiched between two electrodes. Water saturation causes a quasi-complete
dissociation of the polymer and the release of small cations. The application
of an electric field across the thickness results in the bending of the strip.
Conversely, a voltage can be detected between the two electrodes when the strip
is bent. This phenomenon involves multiphysics couplings of
electro-mechanical-chemical type. We have previously modeled this system and
determined its constitutive equations using the thermodynamics of linear
irreversible processes.We applied this model to the case of a cantilevered PEA
strip subjected to a continuous voltage between its two faces (static case).
The applied forces and the tip displacement are calculated using a beam model
in large displacements. We have also studied the force to be exercised on the
free end to prevent its displacement (blocking force).Numerical simulations
were performed in the case of Nafion. We have drawn the profiles of cations
concentration, pressure, electric field and potential in the thickness of the
strip. These quantities, which are almost constant in the central part of the
strip, vary drastically near the electrodes. The obtained values of the tip
displacement and the blocking force are in good agreement with the experimental
data published in the literature. These two quantities are linear functions of
the imposed electrical potential ; the tip displacement varies as the length
square, and the blocking force is proportional to the width and inversely
proportional to the length.


  We show two Freidlin-Wentzell type Large Deviations Principles (LDP) in path
space topologies (uniform and H\"older) for the solution process of
McKean-Vlasov Stochastic Differential Equations (MV-SDEs) using techniques
which directly address the presence of the law in the coefficients and
altogether avoiding decoupling arguments or limits of particle systems. We
provide existence and uniqueness results along with several properties for a
class of MV-SDEs having random coefficients and drifts of super-linear growth.
  As an application of our results, we establish a Functional Strassen type
result (Law of Iterated Logarithm) for the solution process of a MV-SDE.


  Neural architecture search (NAS) is a promising technique to design efficient
and high-performance deep neural networks (DNNs). As the performance
requirements of ML applications grow continuously, the hardware accelerators
start playing a central role in DNN design. This trend makes NAS even more
complicated and time-consuming for most real applications. This paper proposes
FLASH, a very fast NAS methodology that co-optimizes the DNN accuracy and
performance on a real hardware platform. As the main theoretical contribution,
we first propose the NN-Degree, an analytical metric to quantify the
topological characteristics of DNNs with skip connections (e.g., DenseNets,
ResNets, Wide-ResNets, and MobileNets). The newly proposed NN-Degree allows us
to do training-free NAS within one second and build an accuracy predictor by
training as few as 25 samples out of a vast search space with more than 63
billion configurations. Second, by performing inference on the target hardware,
we fine-tune and validate our analytical models to estimate the latency, area,
and energy consumption of various DNN architectures while executing standard ML
datasets. Third, we construct a hierarchical algorithm based on simplicial
homology global optimization (SHGO) to optimize the model-architecture
co-design process, while considering the area, latency, and energy consumption
of the target hardware. We demonstrate that, compared to the state-of-the-art
NAS approaches, our proposed hierarchical SHGO-based algorithm enables more
than four orders of magnitude speedup (specifically, the execution time of the
proposed algorithm is about 0.1 seconds). Finally, our experimental evaluations
show that FLASH is easily transferable to different hardware architectures,
thus enabling us to do NAS on a Raspberry Pi-3B processor in less than 3
seconds.


  We address the macroscopic theory of superconductivity - the Ginzburg-Landau
theory. This theory %Macroscopic theory of superconductivity is based on the
celebrated Ginzburg - Landau equations. First developed to explain and predict
properties of superconductors, these equations form an integral part -
Abelean-Higgs component - of the standard model of particle physics and, in
general, have a profound influence on physics well beyond their original
designation area. %These are a pair of coupled nonlinear equations for a
complex function (called order parameter or Higgs field) and a vector field
(magnetic potential or gauge field). They are the simplest representatives of a
large family of equations appearing in physics and mathematics. (The latest
variant of these equations is the Seiberg - Witten equations.)


  We study duality twisted reductions of the Double Field Theory (DFT) of the
RR sector of massless Type II theory, with twists belonging to the duality
group $Spin^+(10,10)$. We determine the action and the gauge algebra of the
resulting theory and determine the conditions for consistency. In doing this,
we work with the DFT action constructed by Hohm, Kwak and Zwiebach, which we
rewrite in terms of the Mukai pairing: a natural bilinear form on the space of
spinors, which is manifestly $Spin(n,n)$ invariant. If the duality twist is
introduced via the $Spin^+(10,10)$ element $S$ in the RR sector, then the NS-NS
sector should also be deformed via the duality twist $U = \rho(S)$, where
$\rho$ is the double covering homomorphism between $Pin(n,n)$ and $O(n,n)$. We
show that the set of conditions required for the consistency of the reduction
of the NS-NS sector are also crucial for the consistency of the reduction of
the RR sector, owing to the fact that the Lie algebras of $Spin(n,n)$ and
$SO(n,n)$ are isomorphic. In addition, requirement of gauge invariance imposes
an extra constraint on the fluxes that determine the deformations.


  In this paper, we propose a variational autoencoder with disentanglement
priors, VAE-DPRIOR, for task-specific natural language generation with none or
a handful of task-specific labeled examples. In order to tackle compositional
generalization across tasks, our model performs disentangled representation
learning by introducing a conditional prior for the latent content space and
another conditional prior for the latent label space. Both types of priors
satisfy a novel property called $\epsilon$-disentangled. We show both
empirically and theoretically that the novel priors can disentangle
representations even without specific regularizations as in the prior work. The
content prior enables directly sampling diverse content representations from
the content space learned from the seen tasks, and fuse them with the
representations of novel tasks for generating semantically diverse texts in the
low-resource settings. Our extensive experiments demonstrate the superior
performance of our model over competitive baselines in terms of i) data
augmentation in continuous zero/few-shot learning, and ii) text style transfer
in the few-shot setting.


  The nanoPU is a new networking-optimized CPU designed to minimize tail
latency for RPCs. By bypassing the cache and memory hierarchy, the nanoPU
directly places arriving messages into the CPU register file. The wire-to-wire
latency through the application is just 65ns, about 13x faster than the current
state-of-the-art. The nanoPU moves key functions from software to hardware:
reliable network transport, congestion control, core selection, and thread
scheduling. It also supports a unique feature to bound the tail latency
experienced by high-priority applications. Our prototype nanoPU is based on a
modified RISC-V CPU; we evaluate its performance using cycle-accurate
simulations of 324 cores on AWS FPGAs, including real applications (MICA and
chain replication).


  An analytic phenomenological shell model mass formula for light nuclei is
constructed., The formula takes into account the non locality of the self
consistent single particle potential and the special features of light nuclei,
namely: a) charge and mass distributions are closer to a Gaussian shape than to
the shape characteristic in medium and heavy nuclei; b) the central charge and
mass densities are larger than, and decrease towards, the "asymptotic" values
that are the reference parameters for nuclear matter; and c) after a shell
closure, the next level has a larger orbital angular momentum and a noticeably
larger mean square radius. Only then a good numerical fit is obtained with
parameters consistent with optical model analysis and empirical spin-orbit
couplings. A correlation between the "skin effect" and the symmetry dependence
of the optical potential is established. Towards the neutron drip line the
potential well depth, the spin-orbit splitting of the single particle levels
and the gap between major shells decrease, as has been observed. The ensuing
shift and contraction of the single particle level scheme may lead to: a) to
strong configuration mixing and new magic numbers, and b) the onset of the halo
effect, to avoid the expulsion of single particle levels to the continuum.


  Motivated by the work of Fulman and Goldstein, comparing the distribution of
the corank of random matrices in $\mathbb F_q[n]$ with the limit distribution
as $n \to \infty$, we define a countdown process, driven by independent
geometric random variables related to random integer partitions. Analysis of
this process leads to sharper bounds on the total variation distance.


  In the early Universe, a dual component made of coupled CDM and a scalar
field $\Phi$, if their coupling $\beta > \sqrt{3}/2$, owns an attractor
solution, making them a stationary fraction of cosmic energy during the
radiation dominated era. Along the attractor, both such components expand
$\propto a^{-4}$ and have early density parameters $\Omega_{d} = 1/ (4\beta^2)$
and $\Omega_c= 2, \Omega_d$ (field and CDM, respectively). In a previous paper
it was shown that, if a further component, expanding $\propto a^{-3}$, breaks
such stationary expansion at $z \sim 3$--$5 \times 10^3$, cosmic components
gradually acquire densities consistent with observations. This paper, first of
all, considers the case that this component is warm. However, its main topic is
the analysis of fluctuation evolution: out of horizon modes are then
determined; their entry into horizon is numerically evaluated as well as the
dependence of Meszaros effect on the coupling $\beta$; finally, we compute: (i)
transfer function and linear spectral function; (ii) CMB $C_l$ spectra. Both
are close to standard $\Lambda$CDM models; in particular, the former one can be
so down to a scale smaller than Milky Way, in spite of its main DM component
being made of particles of mass $<1$ keV. The previously coupled CDM component,
whose present density parameter is $\cal O$$(10^{-3})$, exhibits wider
fluctuations $\delta \rho/\rho$, but approximately $\beta$-independent $\delta
\rho$ values. We discuss how lower scale features of these cosmologies might
ease quite a few problems that $\Lambda$CDM does not easily solve.


  We propose a new type of earthquake precursor based on the analysis of
correlation dynamics between geophysical signals of different nature. The
precursor is found using a two-parameter cross-correlation function introduced
within the framework of flicker-noise spectroscopy, a general statistical
physics approach to the analysis of time series. We consider an example of
cross-correlation analysis for water salinity time series, an integral
characteristic of the chemical composition of groundwater, and geoacoustic
emissions recorded at the G-1 borehole on the Kamchatka peninsula in the time
frame from 2001 to 2003, which is characterized by a sequence of three groups
of significant seismic events. We found that cross-correlation precursors took
place 27, 31, and 35 days ahead of the strongest earthquakes for each group of
seismic events, respectively. At the same time, precursory anomalies in the
signals themselves were observed only in the geoacoustic emissions for one
group of earthquakes.


  Let $\mathcal{I}$ be an ideal on $\mathbb{N}$. A mapping $f:X\to Y$ is called
an $\mathcal{I}$-covering mapping provided a sequence $\{y_{n}\}_{n\in\mathbb
N}$ is $\mathcal{I}$-converging to a point $y$ in $Y$, there is a sequence
$\{x_{n}\}_{n\in\mathbb N}$ converging to a point $x$ in $X$ such that $x\in
f^{-1}(y)$ and each $x_n\in f^{-1}(y_n)$. In this paper we study the spaces
with certain $\mathcal{I}$-$cs$-networks and investigate the characterization
of the images of metric spaces under certain $\mathcal{I}$-covering mappings,
which prompts us to discover $\mathcal{I}$-$csf$-networks. The following main
results are obtained:
  (1) A space $X$ has an $\mathcal{I}$-$csf$-network if and only if $X$ is a
continuous and $\mathcal{I}$-covering image of a metric space.
  (2) A space $X$ is an $\mathcal{I}$-$csf$-countable space if and only if $X$
is a continuous $\mathcal{I}$-covering and boundary $s$-image of a metric
space.
  (3) A space $X$ has a point-countable $\mathcal{I}$-$cs$-network if and only
if $X$ is a continuous $\mathcal{I}$-covering and $s$-image of a metric space.


  We propose a model for the acceleration of charged particles in
interplanetary space that appear during quiet time periods, that is, not
associated with solar activity events like intense flares or coronal mass
ejections. The interaction of charged particles with modeled turbulent
electromagnetic fields, which mimic the fields observed in the interplanetary
medium, is studied. The turbulence is modeled by means of a dynamical
system,the Gledzer-Ohkitani-Yamada (GOY) shell model, which describes the gross
features of the Navier-Stokes equations. The GOY model is used to build a 3-D
velocity field, which in turn is used to numerically solve the ideal
magneto-hydrodynamic (MHD) induction equation, while the electric field is
calculated from the ideal Ohm's law. Particle acceleration in such an
environment is investigated by test particle simulations, and the resulting
energy distributions are discussed and compared to observations of suprathermal
electrons and ions during quiet periods in interplanetary space.


  We introduce our approaches, in particular the modifications of the primitive
recovery procedure, to handle bare quark stars in numerical relativity
simulations. Reliability and convergence of our implementation are demonstrated
by evolving two triaxially rotating quark star models with different mass as
well as a differentially rotating quark star model which has sufficiently large
kinetic energy to be dynamically unstable. These simulations allow us to verify
that our method is capable of resolving the evolution of the discontinuous
surface of quark stars and possible mass ejection from them. The evolution of
the triaxial deformation and the properties of the gravitational-wave emission
from triaxially rotating quark stars have been also studied, together with the
mass ejection of the differentially rotating case. It is found that
supramassive quark stars are not likely to be ideal sources of continuous
gravitational wave as the star recovers axisymmetry much faster than models
with smaller mass and gravitational-wave amplitude decays rapidly in a
timescale of $10\,$ms, although the instantaneous amplitude from more massive
models is larger. As with the differentially rotating case, our result confirms
that quark stars could experience non-axisymmetric instabilities similar to the
neutron star case but with quite small degree of differential rotation, which
is expected according to previous initial data studies.


  By the use of the latest experimental data on the spectra of $^{133}$Sb and
$^{131}$Sn and on the analysis of properties of other odd nuclei adjacent to
doubly magic closed shells the isospin dependence of a mean spin-orbit
potential is defined. Such a dependence received the explanation in the
framework of different theoretical approaches.


  Internet supercomputing is an approach to solving partitionable,
computation-intensive problems by harnessing the power of a vast number of
interconnected computers. This paper presents a new algorithm for the problem
of using network supercomputing to perform a large collection of independent
tasks, while dealing with undependable processors. The adversary may cause the
processors to return bogus results for tasks with certain probabilities, and
may cause a subset $F$ of the initial set of processors $P$ to crash. The
adversary is constrained in two ways. First, for the set of non-crashed
processors $P-F$, the \emph{average} probability of a processor returning a
bogus result is inferior to $\frac{1}{2}$. Second, the adversary may crash a
subset of processors $F$, provided the size of $P-F$ is bounded from below. We
consider two models: the first bounds the size of $P-F$ by a fractional
polynomial, the second bounds this size by a poly-logarithm. Both models yield
adversaries that are much stronger than previously studied. Our randomized
synchronous algorithm is formulated for $n$ processors and $t$ tasks, with
$n\le t$, where depending on the number of crashes each live processor is able
to terminate dynamically with the knowledge that the problem is solved with
high probability. For the adversary constrained by a fractional polynomial, the
round complexity of the algorithm is
$O(\frac{t}{n^\varepsilon}\log{n}\log{\log{n}})$, its work is $O(t\log{n}
\log{\log{n}})$ and message complexity is $O(n\log{n}\log{\log{n}})$. For the
poly-log constrained adversary, the round complexity is $O(t)$, work is $O(t
n^{\varepsilon})$, %$O(t \, poly \log{n})$, and message complexity is
$O(n^{1+\varepsilon})$ %$O(n \, poly \log{n})$. All bounds are shown to hold
with high probability.


  Suppose a locally compact group G acts freely and properly on a locally
compact Hausdorff space X, and let gamma be the induced action on C_0(X). We
consider a category in which the objects are C*-dynamical systems (A, G, alpha)
for which there is an equivariant homomorphism of (C_0(X), gamma) into the
multiplier algebra M(A). Rieffel has shown that such systems are proper and
saturated, and hence have a generalized fixed-point algebra A^alpha which is
Morita equivalent to A times_{alpha,r} G. We show that the assignment (A,
alpha) maps to A^alpha is functorial, and that Rieffel's Morita equivalence is
natural in a suitable sense. We then use our results to prove a categorical
version of Landstad duality which characterizes crossed products by coactions,
and to prove that Mansfield imprimitivity for crossed products by homogeneous
spaces is natural.


  A theoretical model for the folding of proteins containing disulfide bonds is
introduced. The model exploits the knowledge of the native state to favour the
progressive establishment of native interactions. At variance with traditional
approaches based on native topology, not all native bonds are treated in the
same way; in particular, a suitable energy term is introduced to account for
the special strength of disulfide bonds (irrespective of whether they are
native or not) as well as their ability to undergo intra-molecular reshuffling.
The model thus possesses the minimal ingredients necessary to investigated the
much debated issue of whether the re-folding process occurs through partially
structured intermediates with native or non-native disulfide bonds. This
strategy is applied to a context of particular interest, the re-folding process
of Hirudin, a thrombin-specific protease inhibitor, for which conflicting
folding pathways have been proposed. We show that the only two parameters in
the model (temperature and disulfide strength) can be tuned to reproduce well a
set of experimental transitions between species with different number of formed
disulfide. This model is then used to provide a characterisation of the folding
process and a detailed description of the species involved in the rate-limiting
step of Hirudin refolding.


  Over the past decade, various improvements have been made to Tardos'
collusion-resistant fingerprinting scheme [Tardos, STOC 2003], ultimately
resulting in a good understanding of what is the minimum code length required
to achieve collusion-resistance. In contrast, decreasing the cost of the actual
decoding algorithm for identifying the potential colluders has received less
attention, even though previous results have shown that using joint decoding
strategies, deemed too expensive for decoding, may lead to better code lengths.
Moreover, in dynamic settings a fast decoder may be required to provide answers
in real-time, further raising the question whether the decoding costs of
score-based fingerprinting schemes can be decreased with a smarter decoding
algorithm. In this paper we show how to model the decoding step of score-based
fingerprinting as a nearest neighbor search problem, and how this relation
allows us to apply techniques from the field of (approximate) nearest neighbor
searching to obtain decoding times which are sublinear in the total number of
users. As this does not affect the encoding and embedding steps, this decoding
mechanism can easily be deployed within existing fingerprinting schemes, and
this may bring a truly efficient joint decoder closer to reality. Besides the
application to fingerprinting, similar techniques can be used to decrease the
decoding costs of group testing methods, which may be of independent interest.


  The optimal (Monge-Kantorovich) transportation problem is discussed from
several points of view. The Lagrangian formulation extends the action of the
{\em Lagrangian} $L(v,x,t)$ from the set of orbits in $\R^n$ to a set of
measure-valued orbits. The {\em Eulerian}, dual formulation leads an
optimization problem on the set of sub-solutions of the corresponding
Hamilton-Jacobi equation. Finally, the Monge problem and its Kantorovich
relaxation are obtained by reducing the optimization problem to the set of
measure preserving mappings and two point distribution measures subjected to an
appropriately defined cost function.
  In this paper we concentrate on mechanical Lagrangians $L=|v|^2/2+P(x,t)$
leading, in general, to a non-homogeneous cost function. The main results yield
existence of a unique {\em flow} of homomorphisms which transport the optimal
measure valued orbit of the extended Lagrangian, as well as the existence of an
optimal solution to the dual Euler problem and its relation to the Monge- and
Kantorovich formulations.


  Analysis of the 2007-8 credit crisis has concentrated on issues of relaxed
lending standards, and the perception of irrational behaviour by speculative
investors in real estate and other assets. Asset backed securities have been
extensively criticised for creating a moral hazard in loan issuance and an
associated increase in default risk, by removing the immediate lender's
incentive to ensure that the underlying loans could be repaid. However
significant monetary issues can accompany any form of increased commercial bank
lending, and these appear to have been overlooked by this analysis. In this
paper we propose a general explanation for credit crises based on an
examination of the mechanics of the banking system, and in particular its
internal controls on the supply of credit. We suggest that the current credit
crisis is the result of multiple failures in the Basel regulatory framework,
including the removal of central bank reserve requirements from some classes of
deposit accounts within the banking system, allowing financial instruments
representing debt to be used as regulatory capital, and in particular the
introduction of securitized lending which effectively removed a previously
implicit control over the total quantity of lending originating from the
banking system. We further argue that the interaction of these problems has led
to a destabilising imbalance between total money and loan supply growth, in
that total lending sourced from the commercial bank sector increased at a
faster rate than accompanying growth in the money supply. This not only created
a multi-decade macro-economic debt spiral, but by increasing the ratio of debt
to money within the monetary system acted to increase the risk of loan
defaults, and consequentially reduce the overall stability of the banking
system.


  An earlier investigation found that the performance of advanced students in a
quantum mechanics course did not automatically improve from midterm to final
exam on identical problems even when they were provided the correct solutions
and their own graded exams. Here, we describe a study, which extended over four
years, in which upper-level undergraduate students in a quantum physics course
were given four identical problems in both the midterm exam and final exam.
Approximately half of the students were given explicit incentives to correct
their mistakes in the midterm exam. In particular, they could get back up to
50\% of the points lost on each midterm exam problem. The solutions to the
midterm exam problems were provided to all students in both groups but those
who corrected their mistakes were provided the solution after they submitted
their corrections to the instructor. The performance on the same problems on
the final exam suggests that students who were given incentives to correct
their mistakes significantly outperformed those who were not given an
incentive. The incentive to correct the mistakes had greater impact on the
final exam performance of students who had not performed well on the midterm
exam.


  Motivated by understanding Majorana zero modes in topological superfluids in
particle-number conserving framework beyond the present framework, we study the
effect of particle number conservation on the Berry phase resulting from
transport of a bound quasiparticle around a superfluid vortex. We find that
particle-number non-conserving calculations based on Bogoliubov-de Gennes (BdG)
equations are unable to capture the correct physics when the quasiparticle is
within the penetration depth of the vortex core where the superfluid velocity
is non-zero. Particle number conservation is crucial for deriving the correct
Berry phase in this context, and the Berry phase takes non-universal values
depending on the system parameters and the external trap imposed to bind the
quasiparticle. Of particular relevance to Majorana physics are the findings
that superfluid condensate affects the part of the Berry phase not accounted
for in the standard BdG framework, and that the superfluid many-body ground
state of odd number of fermions involves superfluid condensate deformation due
to the presence of the bound quasiparticle - an effect which is beyond the
description of the BdG equations.


  We utilize a sample of galaxy clusters at 0.35<z<0.6 drawn from the Las
Campanas Distant Cluster Survey (LCDCS) to provide the first non-local
constraint on the cluster-cluster spatial correlation function. The LCDCS
catalog, which covers an effective area of 69 square degrees, contains over
1000 cluster candidates. Estimates of the redshift and velocity dispersion
exist for all candidates, which enables construction of statistically
completed, volume-limited subsamples. In this analysis we measure the angular
correlation function for four such subsamples at z~0.5. After correcting for
contamination, we then derive spatial correlation lengths via Limber inversion.
We find that the resulting correlation lengths depend upon mass, as
parameterized by the mean cluster separation, in a manner that is consistent
with both local observations and CDM predictions for the clustering strength at
z=0.5.


  In this paper we propose a Multi-Objective Ant Colony Optimization (MOACO)
algorithm called CHAC, which has been designed to solve the problem of finding
the path on a map (corresponding to a simulated battlefield) that minimizes
resources while maximizing safety. CHAC has been tested with two different
state transition rules: an aggregative function that combines the heuristic and
pheromone information of both objectives and a second one that is based on the
dominance concept of multiobjective optimization problems. These rules have
been evaluated in several different situations (maps with different degree of
difficulty), and we have found that they yield better results than a greedy
algorithm (taken as baseline) in addition to a military behaviour that is also
better in the tactical sense. The aggregative function, in general, yields
better results than the one based on dominance.


  We propose an algorithm to construct optimal exact designs (EDs). Most of the
work in the optimal regression design literature focuses on the approximate
design (AD) paradigm due to its desired properties, including the optimality
verification conditions derived by Kiefer (1959, 1974). ADs may have unbalanced
weights, and practitioners may have difficulty implementing them with a
designated run size $n$. Some EDs are constructed using rounding methods to get
an integer number of runs at each support point of an AD, but this approach may
not yield optimal results. To construct EDs, one may need to perform new
combinatorial constructions for each $n$, and there is no unified approach to
construct them. Therefore, we develop a systematic way to construct EDs for any
given $n$. Our method can transform ADs into EDs while retaining high
statistical efficiency in two steps. The first step involves constructing an AD
by utilizing the convex nature of many design criteria. The second step employs
a simulated annealing algorithm to search for the ED stochastically. Through
several applications, we demonstrate the utility of our method for various
design problems. Additionally, we show that the design efficiency approaches
unity as the number of design points increases.


  In the quarter plane, five lattice path models with unit steps have resisted
the otherwise general approach of Fayolle, Rachel, and Kurkova. Here we
consider these five models, called the singular models, and prove that the
generating functions marking the number of walks of a given length are not
D-finite -- thus finishing the proof of a conjecture of Bousquet-M\'elou and
Mishna. Furthermore, we provide exact and asymptotic enumerative formulas for
the number of such walks.


  Layered tin monoxide (SnO) offers an exciting two-dimensional (2D)
semiconducting system with great technological potential for next-generation
electronics and photocatalytic applications. Using a combination of
first-principles simulations and strain field analysis, this study investigates
the structural dynamics of oxygen (O) vacancies in monolayer SnO and their
functionalization by complementary lightweight dopants, namely C, Si, N, P, S,
F, Cl, H and H$_{2}$. Our results show that O vacancies are the dominant native
defect under Sn-rich growth conditions with active diffusion characteristics
that are comparable to that of graphene vacancies. Depending on the choice of
substitutional species and its concentration within the material, significant
opportunities are revealed in the doped-SnO system for facilitating
$n$/$p$-type tendencies, work function reduction, and metallization of the
monolayer. N and F dopants are found to demonstrate superior mechanical
compatibility with the host lattice, with F being especially likely to take
part in substitution and lead to degenerately doped phases with high open-air
stability. The findings reported here suggest that post-growth filling of O
vacancies in Sn-rich conditions presents a viable channel for doping 2D tin
monoxide, opening up new avenues in harnessing defect-engineered SnO
nanostructures for emergent technologies.


  Radial differential rotation is an important parameter for stellar dynamo
theory and for understanding angular momentum transport. We investigate the
potential of using a large number of similar stars simultaneously to constrain
their average radial differential rotation gradient: we call this 'ensemble
fitting'. We use a range of stellar models along the main sequence, each with a
synthetic rotation profile. The rotation profiles are step functions with a
step of -350 nHz, which is located at the base of the convection zone. These
models are used to compute the rotational splittings of the p modes and to
model their uncertainties. We then fit an ensemble of stars to infer the
average step size. All the uncertainties on the inferred step size for
individual stars are of the order 1 micro Hz. Using 15 stellar models in an
ensemble fit, we show that the uncertainty on the average step size is reduced
to less than the input step size, which allows us to constrain the sign of the
radial differential rotation. We show that a solar-like step size
(approximately 30 nHz) can be constrained by an ensemble fit of thousands of
main-sequence stars. Observing the number of stars required to successfully
exploit the ensemble fitting method will be possible with future
asteroseismology missions, such as PLATO. We demonstrate the potential of
ensemble fitting by showing that any systematic differences in the average step
size between F, G, and K-type stars larger than 100 nHz can be detected.


  In the hard edge scaling limit of the Jacobi unitary ensemble generated by
the weight $x^{\alpha}(1-x)^{\beta},~x\in[0,1],~\alpha,\beta>0$, the
probability that all eigenvalues of Hermitian matrices from this ensemble lie
in the interval $[t,1]$ is given by the Fredholm determinant of the Bessel
kernel. We derive the constant in the asymptotics of this Bessel-kernel
determinant. A specialization of the results gives the constant in the
asymptotics of the probability that the interval $(-a,a),a>0,$ is free of
eigenvalues in the Jacobi unitary ensemble with the symmetric weight
$(1-x^2)^{\beta}, x\in[-1,1]$.


  We examine the effect of Compton drag on the dynamics of a relativistic shock
wave. Similarity solutions describing a radiation-supported shock are obtained
for certain profiles of the external radiation intensity and the density of the
unshocked ejecta, and are compared with 1D numerical simulations of a blast
wave expanding into an ambient medium containing isotropic seed radiation. Both
the analytic model and the simulations indicate that under realistic conditions
the radiation drag should strongly affect the dynamics and structure of the
shocked layer. In particular, our calculations show significant strengthening
of the reverse shock and weakening of the forward shock over time of the order
of the inverse Compton cooling time. We conclude that the effect of radiation
drag on the evolution of the emitting plasma should affect the resultant light
curves and, conceivably, spectra of the observed emission during strong blazar
flares.


  We present the temporal evolution of line profiles ranging from near
ultraviolet to optical wavelengths by analyzing 59 Subaru telescope spectra of
normal Type Ia Supernovae (SNe Ia) in the intermediate redshift range (0.05 < z
< 0.4) discovered by the Sloan Digital Sky Survey-II (SDSS-II) Supernova
Survey. We derive line velocities, peak wavelengths and pseudo-equivalent
widths (pEWs) of these lines. Additionally, we compare the line profiles around
the date of maximum brightness with those from their nearby counterparts. We
find that line profiles represented by their velocities and pEWs for
intermediate redshift SNe Ia are consistent with their nearby counterparts
within 2 $\sigma$. These findings support the picture that SNe Ia are a
"standard" candle for the intermediate redshift range as has been shown between
SNe Ia at nearby and high redshifts. There is a hint that the "MgII \lambda
4300" pEW distribution for intermediate redshift SNe Ia is larger than for the
nearby sample, which could be interpreted as a difference in the progenitor
abundance.


  This paper investigates the trade-off between computational resource
utilization and image quality in the context of image fusion techniques for
smartphone camera capture. The study explores various combinations of fusion
methods, fusion weights, number of frames, and stacking (a.k.a. merging)
techniques using a proprietary dataset of images captured with Motorola
smartphones. The objective was to identify optimal configurations that balance
computational efficiency with image quality. Our results indicate that
multi-scale methods and their single-scale fusion counterparts return similar
image quality measures and runtime, but single-scale ones have lower memory
usage. Furthermore, we identified that fusion methods operating in the YUV
color space yield better performance in terms of image quality, resource
utilization, and runtime. The study also shows that fusion weights have an
overall small impact on image quality, runtime, and memory. Moreover, our
results reveal that increasing the number of highly exposed input frames does
not necessarily improve image quality and comes with a corresponding increase
in computational resources usage and runtime; and that stacking methods,
although reducing memory usage, may compromise image quality. Finally, our work
underscores the importance of thoughtful configuration selection for image
fusion techniques in constrained environments and offers insights for future
image fusion method development, particularly in the realm of smartphone
applications.


  We propose a new mechanism towards the solution to the doublet-triplet Higgs
mass splitting problem in the supersymmetric grand unified theory. Our model is
based on the gauge group $SU(5)_H \times SU(5)_{GUT}$, where $SU(5)_H$ and
$SU(5)_{GUT}$ are a new strong gauge interaction and the ordinary grand unified
gauge group, respectively. The doublet-triplet Higgs mass splitting is realized
through the quantum deformation of moduli space caused by the strong $SU(5)_H$
gauge dynamics. The low energy description of our model is given by the minimal
supersymmetric standard model.


  This paper is a contribution to the search for efficient and high-level
mathematical tools to specify and reason about (abstract) programming languages
or calculi. Generalising the reduction monads of Ahrens et al., we introduce
transition monads, thus covering new applications such as
lambda-bar-mu-calculus, pi-calculus, Positive GSOS specifications, differential
lambda-calculus, and the big-step, simply-typed, call-by-value lambda-calculus.
Moreover, we design a suitable notion of signature for transition monads.


  Lookup table (LUT) has shown its efficacy in low-level vision tasks due to
the valuable characteristics of low computational cost and hardware
independence. However, recent attempts to address the problem of single image
super-resolution (SISR) with lookup tables are highly constrained by the small
receptive field size. Besides, their frameworks of single-layer lookup tables
limit the extension and generalization capacities of the model. In this paper,
we propose a framework of series-parallel lookup tables (SPLUT) to alleviate
the above issues and achieve efficient image super-resolution. On the one hand,
we cascade multiple lookup tables to enlarge the receptive field of each
extracted feature vector. On the other hand, we propose a parallel network
which includes two branches of cascaded lookup tables which process different
components of the input low-resolution images. By doing so, the two branches
collaborate with each other and compensate for the precision loss of
discretizing input pixels when establishing lookup tables. Compared to previous
lookup table-based methods, our framework has stronger representation abilities
with more flexible architectures. Furthermore, we no longer need interpolation
methods which introduce redundant computations so that our method can achieve
faster inference speed. Extensive experimental results on five popular
benchmark datasets show that our method obtains superior SISR performance in a
more efficient way. The code is available at https://github.com/zhjy2016/SPLUT.