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A new low-dispersion objective-prism search for low-redshift (z<0.045)
emission-line galaxies (ELG) has been carried out by the Universidad
Complutense de Madrid with the Schmidt Telescope at the Calar-Alto Observatory.
This is a continuation of the UCM Survey, which was performed by visual
selection of candidates in photographic plates via the presence of the
Halpha+[NII]6584 blend in emission. In this new list we have applied an
automatic procedure, fully developed by us, for selecting and analyzing the ELG
candidates on the digitized images obtained with the MAMA machine. The analyzed
region of the sky covers 189 square degrees in nine fields near R.A.=14h & 17h,
Dec=25 deg. The final sample contains 113 candidates. Special effort has been
made to obtain a large amount of information directly from our uncalibrated
plates by using several external calibrations. The parameters obtained for the
ELG candidates allow for the study of the statistical properties for the
sample.
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Mukai's program seeks to recover a K3 surface $X$ from any curve $C$ on it by
exhibiting it as a Fourier-Mukai partner to a Brill-Noether locus of vector
bundles on the curve. In the case $X$ has Picard number one and the curve $C\in
|H|$ is primitive, this was confirmed by Feyzbakhsh for $g\geq 11$ and $g\neq
12$. More recently, Feyzbakhsh has shown that certain moduli spaces of stable
bundles on $X$ are isomorphic to the Brill-Noether locus of curves in $|H|$ if
$g$ is sufficiently large. In this paper, we work with irreducible curves in a
non-primitive ample linear system $|mH|$ and prove that Mukai's program is
valid for any irreducible curve when $g\neq 2$, $mg\geq 11$ and $mg\neq 12$.
Furthermore, we introduce the destabilising regions to improve Feyzbakhsh's
analysis. We show that there are hyper-K\"ahler varieties as Brill-Noether loci
of curves in every dimension.
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Let $\Phi(x,y)$ be a bivariate polynomial with complex coefficients. The
zeroes of $\Phi(x,y)$ are given a combinatorial structure by considering them
as arcs of a directed graph $G(\Phi)$. This paper studies some relationship
between the polynomial $\Phi(x,y)$ and the structure of $G(\Phi)$.
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I draw attention to statistical, probabilistic, computer science aspects of
the highly related topics of the Bell game and of a possible future Quantum
Internet.
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For a finitely irreducible countable Markov shift and a potential with
summable variations, we provide a condition on the associated pressure function
which ensures that Bowen's Gibbs state, the equilibrium state, and the
minimizer of the level-2 large deviations rate function are all unique and they
coincide. From this, we deduce that all periodic points weighted with the
potential equidistribute with respect to the Gibbs-equilibrium state as the
periods tend to infinity. Applications are given to the Gauss map, and the
Bowen-Series map associated with a finitely generated free Fuchsian group with
parabolic elements.
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Convolutional neural networks have recently demonstrated high-quality
reconstruction for single image super-resolution. However, existing methods
often require a large number of network parameters and entail heavy
computational loads at runtime for generating high-accuracy super-resolution
results. In this paper, we propose the deep Laplacian Pyramid Super-Resolution
Network for fast and accurate image super-resolution. The proposed network
progressively reconstructs the sub-band residuals of high-resolution images at
multiple pyramid levels. In contrast to existing methods that involve the
bicubic interpolation for pre-processing (which results in large feature maps),
the proposed method directly extracts features from the low-resolution input
space and thereby entails low computational loads. We train the proposed
network with deep supervision using the robust Charbonnier loss functions and
achieve high-quality image reconstruction. Furthermore, we utilize the
recursive layers to share parameters across as well as within pyramid levels,
and thus drastically reduce the number of parameters. Extensive quantitative
and qualitative evaluations on benchmark datasets show that the proposed
algorithm performs favorably against the state-of-the-art methods in terms of
run-time and image quality.
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The Ueda-Guinea model of a dissipative tunnel junction is investigated. This
model accounts for final state effects associated with single-electron
tunneling. A quantum phase transition emerges, marking a boundary between
insulating (Coulomb blockade) and conducting phases. The system is analyzed by
large-N techniques, self-consistent harmonic approximation, and Monte Carlo
methods.
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Van der Waals forces as interactions between neutral and polarisable
particles act at small distances between two objects. Their theoretical origin
lies in the electromagnetic interaction between induced dipole moments caused
by the vacuum fluctuations of the ground-state electromagnetic field. The
resulting theory well describes the experimental situation in the limit of the
point dipole assumption. At smaller distances, where the finite size of the
particles has to be taken into account, this description fails and has to be
corrected by higher orders of the multipole expansion, such as quadrupole
moments and so on. With respect to the complexity of the spatial properties of
the particles this task requires a considerable effort. In order to describe
the van der Waals interaction between such particles, we apply the established
method of a spatially spread out polarisability distribution to approximate the
higher orders of the multipole expansion. We hence construct an effective
theory for effects from anisotropy and finite size on the van der Waals
potential.
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It has recently been proposed that the dwarf spheroidal galaxies located in
the Local Group disks of satellites (DoSs) may be tidal dwarf galaxies (TDGs)
born in a major merger at least 5 Gyr ago. Whether TDGs can live that long is
still poorly constrained by observations. As part of deep optical and HI
surveys with the CFHT MegaCam camera and Westerbork Synthesis Radio Telescope
made within the ATLAS3D project, and follow-up spectroscopic observations with
the Gemini-North telescope, we have discovered old TDG candidates around
several early-type galaxies. At least one of them has an oxygen abundance close
to solar, as expected for a tidal origin. This confirmed pre-enriched object is
located within the gigantic, but very low surface brightness, tidal tail that
emanates from the elliptical galaxy, NGC 5557. An age of 4 Gyr estimated from
its SED fitting makes it the oldest securely identified TDG ever found so far.
We investigated the structural and gaseous properties of the TDG and of a
companion located in the same collisional debris, and thus most likely of tidal
origin as well. Despite several Gyr of evolution close to their parent
galaxies, they kept a large gas reservoir. Their central surface brightness is
low and their effective radius much larger than that of typical dwarf galaxies
of the same mass. This possibly provides us with criteria to identify tidal
objects which can be more easily checked than the traditional ones requiring
deep spectroscopic observations. In view of the above, we discuss the survival
time of TDGs and question the tidal origin of the DoSs.
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The exclusive photoproduction of the $J/\psi$ state is investigated in
peripheral AA collisions for the energies available at the LHC, $\sqrt{s}=2.76$
TeV and $\sqrt{s}=5.02$ TeV. In order to evaluate the robustness of the
light-cone color dipole formalism, previously tested in the ultraperipheral
regime, the rapidity distribution and the nuclear modification factor
($R_{AA}$) were calculated for three centrality classes: 30%-50%, 50%-70% and
70%-90%. In the peripheral regime, three scenarios were considered. In the
scenario 1, a similar formalism adopted in the UPC regime is used; in the
scenario 2, one considers that only the spectators in the target are the ones
that interact coherently with the photon; in the scenario 3, the photonuclear
cross section is modified using the same geometrical constraints applyed in the
scenario 2. The results obtained from the three scenarios were compared with
the ALICE measurements (only $J/\psi$ at the moment), showing a better
agreement in the more complete approach (scenario 3), mainly in the more
central regions (30%-50% and 50%-70%) where the incertainty is smaller.
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Imaging Atmospheric Cherenkov Telescopes (IACTs) detect very-high-energy
gamma rays from ground level by capturing the Cherenkov light of the induced
particle showers. Convolutional neural networks (CNNs) can be trained on IACT
camera images of such events to differentiate the signal from the background
and to reconstruct the energy of the initial gamma ray. Pattern spectra provide
a 2-dimensional histogram of the sizes and shapes of features comprising an
image and they can be used as an input for a CNN to significantly reduce the
computational power required to train it. In this work, we generate pattern
spectra from simulated gamma-ray and proton images to train a CNN for
signal-background separation and energy reconstruction for the Small-Sized
Telescopes (SSTs) of the Cherenkov Telescope Array (CTA). A comparison of our
results with a CNN directly trained on CTA images shows that the pattern
spectra-based analysis is about a factor of three less computationally
expensive but not able to compete with the performance of an CTA image-based
analysis. Thus, we conclude that the CTA images must be comprised of additional
information not represented by the pattern spectra.
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This is a lecture on the theory of formal power series developed entirely
without any analytic machinery. Combining ideas from various authors we are
able to prove Newton's binomial theorem, Jacobi's triple product, the
Rogers--Ramanujan identities and many other prominent results. We apply these
methods to derive several combinatorial theorems including Ramanujan's
partition congruences, generating functions of Stirling numbers and Jacobi's
four-square theorem. We further discuss formal Laurent series and multivariate
power series and end with a proof of MacMahon's master theorem.
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Alkali vapor cells with antirelaxation coating (especially paraffin-coated
cells) have been a central tool in optical pumping and atomic spectroscopy
experiments for 50 years. We have discovered a dramatic change of the alkali
vapor density in a paraffin-coated cell upon application of an electric field
to the cell. A systematic experimental characterization of the phenomenon is
carried out for electric fields ranging in strength from 0-8 kV/cm for
paraffin-coated cells containing rubidium and cells containing cesium. The
typical response of the vapor density to a rapid (duration < 100 ms) change in
electric field of sufficient magnitude includes (a) a rapid (duration of < 100
ms) and significant increase in alkali vapor density followed by (b) a less
rapid (duration of ~ 1 s) and significant decrease in vapor density (below the
equilibrium vapor density), and then (c) a slow (duration of ~ 100 s) recovery
of the vapor density to its equilibrium value. Measurements conducted after the
alkali vapor density has returned to its equilibrium value indicate minimal
change (at the level of < 10%) in the relaxation rate of atomic polarization.
Experiments suggest that the phenomenon is related to an electric-field-induced
modification of the paraffin coating.
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The mechanical properties of thermally excited two-dimensional crystalline
membranes can depend dramatically on their geometry and topology. A
particularly relevant example is the effect on the crumpling transition of
holes in the membrane. Here we use molecular dynamics simulations to study the
case of elastic frames (sheets with a single large hole in the center) and find
that the system approaches the crumpled phase through a sequence of
origami-like folds at decreasing length scales when temperature is increased.
We use normal-normal correlation functions to quantify the
temperature-dependent number of folds.
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Using appropriate transformation, by the coefficient decomposition method,
general solutions with hidden variables (parameters) to the Abel differential
equation are obtained. In the process of solving, a set of entangled function
pairs is discovered.
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We obtain sufficient conditions for an exponential type entire function not
to have zeros in the open lower half-plane. An exact inequality containing the
real and imaginary parts of such functions and their derivatives restricted to
the real axis is deduced. A connection is established to the positive definite
functions.
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Predictions of the nonperturbative Quark Gluon Strings model based on the
1/N-expansion in QCD and string picture of interactions for production of
states containing heavy quarks are considered. Relations between fragmentation
functions for different states are used to predict the fragmentation function
of c-quark to J/psi-mesons. The resulting cross section for J/psi-production in
e+e- annihilation is in a good agreement with recent Belle result. It is argued
that associated production of c\bar{c} states with open charm should give a
substantial contribution to production of these states in hadronic interactions
at very high energies.
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In this paper, we focus on the question of the extent to which online
learning can benefit from distributed computing. We focus on the setting in
which $N$ agents online-learn cooperatively, where each agent only has access
to its own data. We propose a generic data-distributed online learning
meta-algorithm. We then introduce the Distributed Weighted Majority and
Distributed Online Mirror Descent algorithms, as special cases. We show, using
both theoretical analysis and experiments, that compared to a single agent:
given the same computation time, these distributed algorithms achieve smaller
generalization errors; and given the same generalization errors, they can be
$N$ times faster.
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In this contribution we study azimuthal angle decorrelation in inclusive
dijet cross sections taking into account the next-to-leading (NLO) corrections
to the BFKL kernel while keeping the jet vertices at leading order. We show how
the angular decorrelation for jets with a wide relative separation in rapidity
largely decreases when the NLO corrections are included.
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Health-related quality of life (Hr-QoL) scales provide crucial information on
neurodegenerative disease progression, help improving patient care, and
constitute a meaningful endpoint for therapeutic research. However, Hr-QoL
progression is usually poorly documented, as for multiple system atrophy (MSA),
a rare and rapidly progressing alpha-synucleinopathy. This work aimed to
describe Hr-QoL progression during the natural course of MSA, explore
disparities between patients, and identify informative items using a four-step
statistical strategy.We leveraged the data of the French MSA cohort comprising
annual assessments with the MSA-QoL questionnaire for more than 500 patients
over up to 11 years. The four-step strategy (1) determined the subdimensions of
Hr-QoL in MSA; (2) modelled the subdimension trajectories over time, accounting
for the risk of death; (3) mapped the sequence of item impairments with disease
stages; and (4) identified the most informative items specific to each disease
stage.Among the 536 patients included, 50% were women and they were aged on
average 65.1 years old at entry. Among them, 63.1% died during the follow-up.
Four dimensions were identified. In addition to the original motor, nonmotor,
and emotional domains, an oropharyngeal component was highlighted. While the
motor and oropharyngeal domains deteriorated rapidly, the nonmotor and
emotional aspects were already slightly to moderately impaired at cohort entry
and deteriorated slowly over the course of the disease. Impairments were
associated with sex, diagnosis subtype, and delay since symptom onset. Except
for the emotional domain, each dimension was driven by key identified
items.Hr-QoL is a multidimensional concept that deteriorates progressively over
the course of MSA and brings essential knowledge for improving patient care. As
exemplified with MSA, the thorough description of Hr-QoL using the 4-step
original analysis can provide new perspectives on neurodegenerative diseases'
management to ultimately deliver better support focused on the patient's
perspective.
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We investigate the relation between star formation (SF) and black hole
accretion luminosities, using a sample of 492 type-2 active galactic nuclei
(AGNs) at z < 0.22, which are detected in the far-infrared (FIR) surveys with
AKARI and Herschel. We adopt FIR luminosities at 90 and 100 um as SF
luminosities, assuming the proposed linear proportionality of star formation
rate with FIR luminosities. By estimating AGN luminosities from [OIII]5007 and
[OI]6300 emission lines, we find a positive linear trend between FIR and AGN
luminosities over a wide dynamical range. This result appears to be
inconsistent with the recent reports that low-luminosity AGNs show essentially
no correlation between FIR and X-ray luminosities, while the discrepancy is
likely due to the Malmquist and sample selection biases. By analyzing the
spectral energy distribution, we find that pure-AGN candidates, of which FIR
radiation is thought to be AGN-dominated, show significantly low-SF activities.
These AGNs hosted by low-SF galaxies are rare in our sample (~ 1%). However,
the low fraction of low-SF AGN is possibly due to observational limitations
since the recent FIR surveys are insufficient to examine the population of
high-luminosity AGNs hosted by low-SF galaxies.
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Bipolar spherical harmonics (BiPoSHs) provide a general formalism for
quantifying departures in the cosmic microwave background (CMB) from
statistical isotropy (SI) and from Gaussianity. However, prior work has focused
only on BiPoSHs with even parity. Here we show that there is another set of
BiPoSHs with odd parity, and we explore their cosmological applications. We
describe systematic artifacts in a CMB map that could be sought by measurement
of these odd-parity BiPoSH modes. These BiPoSH modes may also be produced
cosmologically through lensing by gravitational waves (GWs), among other
sources. We derive expressions for the BiPoSH modes induced by the weak lensing
of both scalar and tensor perturbations. We then investigate the possibility of
detecting parity-breaking physics, such as chiral GWs, by cross-correlating
opposite parity BiPoSH modes with multipole moments of the CMB polarization. We
find that the expected signal-to-noise of such a detection is modest.
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In quantum computing the decoherence time of the qubits determines the
computation time available and this time is very limited when using current
hardware. In this paper we minimize the execution time (the depth) for a class
of circuits referred to as linear reversible circuits, which has many
applications in quantum computing (e.g., stabilizer circuits, CNOT+T circuits,
etc.). We propose a practical formulation of a divide and conquer algorithm
that produces quantum circuits that are twice as shallow as those produced by
existing algorithms. We improve the theoretical upper bound of the depth in the
worst case for some range of qubits. We also propose greedy algorithms based on
cost minimization to find more optimal circuits for small or simple operators.
Overall, we manage to consistently reduce the total depth of a class of
reversible functions, with up to 92% savings in an ancilla-free case and up to
99% when ancillary qubits are available.
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We study the decay $B^{+} \to K^+ K^- \pi^+$ and investigate the angular
distribution of $K^{+}K^{-}$ pairs with invariant mass below $1.1$ GeV/$c^2$.
This region exhibits both a strong enhancement in signal and very large direct
$CP$ violation. We construct a coherent sum model for the angular distribution
of $S$- and $P$-wave, and report the ratio of their amplitudes, the relative
phase and the forward-backward asymmetry. We also report absolute differential
branching fractions and direct $CP$ asymmetry for the decay in bins of
$M_{K^+K^-}$ and the differential branching fractions in bins of
$M_{K^+\pi^-}$. The results are based on a data sample that contains
$772\times10^6$ $B \bar{B}$ pairs collected at the $\Upsilon(4S)$ resonance
with the Belle detector at the KEKB asymmetric-energy $e^+ e^-$ collider. The
measured overall branching fraction and the direct $CP$ asymmetry are
$(5.38\pm0.40\pm0.35)\times 10^{-6}$ and $-0.170\pm0.073\pm0.017$,
respectively, where the first uncertainties are statistical and the second are
systematic.
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The scrambling of quantum information in closed many-body systems, as
measured by out-of-time-ordered correlation functions (OTOCs), has lately
received considerable attention. Recently, a hydrodynamical description of
OTOCs has emerged from considering random local circuits, aspects of which are
conjectured to be universal to ergodic many-body systems, even without
randomness. Here we extend this approach to systems with locally conserved
quantities (e.g., energy). We do this by considering local random unitary
circuits with a conserved U$(1)$ charge and argue, with numerical and
analytical evidence, that the presence of a conservation law slows relaxation
in both time ordered {\textit{and}} out-of-time-ordered correlation functions,
both can have a diffusively relaxing component or "hydrodynamic tail" at late
times. We verify the presence of such tails also in a deterministic,
peridocially driven system. We show that for OTOCs, the combination of
diffusive and ballistic components leads to a wave front with a specific,
asymmetric shape, decaying as a power law behind the front. These results also
explain existing numerical investigations in non-noisy ergodic systems with
energy conservation. Moreover, we consider OTOCs in Gibbs states, parametrized
by a chemical potential $\mu$, and apply perturbative arguments to show that
for $\mu\gg 1$ the ballistic front of information-spreading can only develop at
times exponentially large in $\mu$ -- with the information traveling
diffusively at earlier times. We also develop a new formalism for describing
OTOCs and operator spreading, which allows us to interpret the saturation of
OTOCs as a form of thermalization on the Hilbert space of operators.
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In recent years, kernel density estimation has been exploited by computer
scientists to model machine learning problems. The kernel density estimation
based approaches are of interest due to the low time complexity of either O(n)
or O(n*log(n)) for constructing a classifier, where n is the number of sampling
instances. Concerning design of kernel density estimators, one essential issue
is how fast the pointwise mean square error (MSE) and/or the integrated mean
square error (IMSE) diminish as the number of sampling instances increases. In
this article, it is shown that with the proposed kernel function it is feasible
to make the pointwise MSE of the density estimator converge at O(n^-2/3)
regardless of the dimension of the vector space, provided that the probability
density function at the point of interest meets certain conditions.
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Implementing a family of differential rotation laws inspired by binary
neutron-star merger remnants, we consider the impact of the rotation profile on
the low-T/W instability. We use time evolutions of the linearised dynamical
equations, in Newtonian gravity, to study non-axisymmetric oscillations and
identify the unstable modes. The presence and evolution of the low-T/W
instability is monitored with the canonical energy and angular momentum, while
the growth time is extracted from the evolved kinetic energy. The results for
the new rotation laws highlight similarities with the commonly considered
j-constant law. The instability sets in when an oscillation mode co-rotates
with the star (i.e. whenever there is a point where the mode's pattern speed
matches the bulk angular velocity) and grows faster deep inside the co-rotation
region. However, the new profiles add features, like an additional co-rotation
point to the problem, which affect the onset of instability. The rotation laws
influence more drastically the oscillation frequencies of the l=m=2 f-mode in
fast rotating models, but affect the instability growth time at any rotation
rate. We also identify models where the low-T/W instability appears to be
triggered by inertial modes. We discuss to what extent the inferred qualitative
behaviour is likely to be of observational relevance.
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Recent work by De Roeck et al. [Phys. Rev. B 95, 155129 (2017)] has argued
that many-body localization (MBL) is unstable in two and higher dimensions due
to a thermalization avalanche triggered by rare regions of weak disorder. To
examine these arguments, we construct several models of a finite ergodic bubble
coupled to an Anderson insulator of non-interacting fermions. We first describe
the ergodic region using a GOE random matrix and perform an exact
diagonalization study of small systems. The results are in excellent agreement
with a refined theory of the thermalization avalanche that includes transient
finite-size effects, lending strong support to the avalanche scenario. We then
explore the limit of large system sizes by modeling the ergodic region via a
Hubbard model with all-to-all random hopping: the combined system, consisting
of the bubble and the insulator, can be reduced to an effective Anderson
impurity problem. We find that the spectral function of a local operator in the
ergodic region changes dramatically when coupling to a large number of
localized fermionic states---this occurs even when the localized sites are
weakly coupled to the bubble. In principle, for a given size of the ergodic
region, this may arrest the avalanche. However, this back-action effect is
suppressed and the avalanche can be recovered if the ergodic bubble is large
enough. Thus, the main effect of the back-action is to renormalize the critical
bubble size.
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We study the multistable behavior of the intersubband optical absorption for
InSb-based tunnel coupled quantum wells. We consider four sublevels coming from
the Zeeman spin splitting of the two deepest levels, caused by a weak in-plane
magnetic field. Photoexcitation with an intense terahertz pump produces the
redistribution of nonequilibrium electrons between the spin sublevels. Based on
the matrix density, we describe this electron redistribution by means of a
system of balance equations for electron concentrations. The redistribution
produces a photoinduced self-consistent potential, giving rise to the
renormalization of energy distance between levels. Depending on total electron
concentration and pumping efficiency, we find different multistable behaviors
in the intersubband optical absorption spectrum.
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Right-handed neutrinos ($\nu_{R}$) are often considered as a portal to new
hidden physics. It is tempting to consider a gauge singlet scalar $(\phi)$ that
exclusively couples to $\nu_{R}$ via a $\nu_{R}\nu_{R}\phi$ term. Such a
$\nu_{R}$-philic scalar does not interact with charged fermions at tree level
but loop-induced effective interactions are inevitable, which are
systematically investigated in this work. The magnitude of the loop-induced
couplings coincidentally meets the current sensitivity of fifth-force searches.
In particular, the loop-induced coupling to muons could be tested in the recent
LIGO observations of neutron star mergers as there might be a sizable Yukawa
force in the binary system mediated by the $\nu_{R}$-philic scalar.
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The question whether an ontology can safely be replaced by another, possibly
simpler, one is fundamental for many ontology engineering and maintenance
tasks. It underpins, for example, ontology versioning, ontology modularization,
forgetting, and knowledge exchange. What safe replacement means depends on the
intended application of the ontology. If, for example, it is used to query
data, then the answers to any relevant ontology-mediated query should be the
same over any relevant data set; if, in contrast, the ontology is used for
conceptual reasoning, then the entailed subsumptions between concept
expressions should coincide. This gives rise to different notions of ontology
inseparability such as query inseparability and concept inseparability, which
generalize corresponding notions of conservative extensions. We survey results
on various notions of inseparability in the context of description logic
ontologies, discussing their applications, useful model-theoretic
characterizations, algorithms for determining whether two ontologies are
inseparable (and, sometimes, for computing the difference between them if they
are not), and the computational complexity of this problem.
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We study diversity in one-shot communication over molecular timing channels.
We consider a channel model where the transmitter simultaneously releases a
large number of information particles, while the information is encoded in the
time of release. The receiver decodes the information based on the random time
of arrival of the information particles. The random propagation is
characterized by the general class of right-sided unimodal densities. We
characterize the asymptotic exponential decrease rate of the probability of
error as a function of the number of released particles, and denote this
quantity as the system diversity gain. Four types of detectors are considered:
the maximum-likelihood (ML) detector, a linear detector, a detector that is
based on the first arrival (FA) among all the transmitted particles, and a
detector based on the last arrival (LA). When the density characterizing the
random propagation is supported over a large interval, we show that the simple
FA detector achieves a diversity gain very close to that of the ML detector. On
the other hand, when the density characterizing the random propagation is
supported over a small interval, we show that the simple LA detector achieves a
diversity gain very close to that of the ML detector.
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We present results for the electronic structure of alpha uranium using a
recently developed quasiparticle self-consistent GW method (QSGW). This is the
first time that the f-orbital electron-electron interactions in an actinide has
been treated by a first-principles method beyond the level of the generalized
gradient approximation (GGA) to the local density approximation (LDA). We show
that the QSGW approximation predicts an f-level shift upwards of about 0.5 eV
with respect to the other metallic s-d states and that there is a significant
f-band narrowing when compared to LDA band-structure results. Nonetheless,
because of the overall low f-electron occupation number in uranium,
ground-state properties and the occupied band structure around the Fermi energy
is not significantly affected. The correlations predominate in the unoccupied
part of the f states. This provides the first formal justification for the
success of LDA and GGA calculations in describing the ground-state properties
of this material.
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We study the macroscopic scaling and weak coupling limit for a random
Schroedinger equation on Z^3. We prove that the Wigner transforms of a large
class of "macroscopic" solutions converge in r-th mean to solutions of a linear
Boltzmann equation, for any finite value of r in R_+. This extends previous
results where convergence in expectation was established.
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We investigate the coherent mixing of co-propagating edge channels in a
quantum Hall bar produced by step potentials. In the case of two edge channels
it is found that, although a single step induces only a few percent mixing, a
series of steps could yield 50% mixing. In addition, a strong mixing is found
when the potential height of a single step allows a different number of edge
channels on the two sides of the step. Charge density probability has been also
calculated even for the case where the step is smoothened.
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With an increasing outreach of digital platforms in our lives, researchers
have taken a keen interest to study different facets of social interactions
that seem to be evolving rapidly. Analysing the spread of information (aka
diffusion) has brought forth multiple research areas such as modelling user
engagement, determining emerging topics, forecasting virality of online posts
and predicting information cascades. Despite such ever-increasing interest,
there remains a vacuum among easy-to-use interfaces for large-scale
visualisation of diffusion models. In this paper, we introduce DiVA --
Diffusion Visualisation and Analysis, a tool that provides a scalable web
interface and extendable APIs to analyse various diffusion trends on networks.
DiVA uniquely offers support for simultaneous comparison of two competing
diffusion models and even the comparison with the ground-truth results, both of
which help develop a coherent understanding of real-world scenarios. Along with
performing an exhaustive feature comparison and system evaluation of DiVA
against publicly-available web interfaces for information diffusion, we
conducted a user study to understand the strengths and limitations of DiVA. We
noticed that evaluators had a seamless user experience, especially when
analysing diffusion on large networks.
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We introduce an iterative method to univocally determine the adiabatic
expansion of the modes of Dirac fields in spatially homogeneous external
backgrounds. We overcome the ambiguities found in previous studies and use this
new procedure to improve the adiabatic regularization/renormalization scheme.
We provide details on the application of the method for Dirac fields living in
a four-dimensional Friedmann-Lemaitre-Robertson-Walker spacetime with a Yukawa
coupling to an external scalar field. We check the consistency of our proposal
by working out the conformal anomaly. We also analyze a two-dimensional Dirac
field in Minkowski space coupled to a homogeneous electric field and reproduce
the known results on the axial anomaly. The adiabatic expansion of the modes
given here can be used to properly characterize the allowed physical states of
the Dirac fields in the above external backgrounds.
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During migration cells exhibit a rich variety of seemingly random migration
patterns, which makes unraveling the underlying mechanisms that control cell
migration a daunting challenge. For efficient migration cells require a
mechanism for polarization, so that traction forces are produced in the
direction of motion, while adhesion is released to allow forward migration. To
simplify the study of this process cells have been studied when placed along
one-dimensional tracks, where single cells exhibit both smooth and stick-slip
migration modes. The stick-slip motility mode is characterized by protrusive
motion at the cell front, coupled with slow cell elongation, which is followed
by rapid retractions of the cell back. In this study, we explore a minimal
physical model that couples the force applied on the adhesion bonds to the
length variations of the cell and the traction forces applied by the polarized
actin retrograde flow. We show that the rich spectrum of cell migration
patterns emerges from this model as different \emph{deterministic} dynamical
phases. This result suggests a source for the large cell-to-cell variability
(CCV) in cell migration patterns observed in single cells over time and within
cell populations. The large heterogeneity can arise from small fluctuations in
the cellular components that are greatly amplified due to moving the cells'
internal state across the dynamical phase transition lines. Temporal noise is
shown to drive random changes in the cellular polarization direction, which is
enhanced during the stick-slip migration mode. These results offer a new
framework to explain experimental observations of migrating cells, resulting
from noisy switching between underlying deterministic migration modes.
|
The technical advances in Computed Tomography (CT) allow to obtain immense
amounts of 3D data. For such datasets it is very costly and time-consuming to
obtain the accurate 3D segmentation markup to train neural networks. The
annotation is typically done for a limited number of 2D slices, followed by an
interpolation. In this work, we propose a pre-training method SortingLoss. It
performs pre-training on slices instead of volumes, so that a model could be
fine-tuned on a sparse set of slices, without the interpolation step. Unlike
general methods (e.g. SimCLR or Barlow Twins), the task specific methods (e.g.
Transferable Visual Words) trade broad applicability for quality benefits by
imposing stronger assumptions on the input data. We propose a relatively mild
assumption -- if we take several slices along some axis of a volume, structure
of the sample presented on those slices, should give a strong clue to
reconstruct the correct order of those slices along the axis. Many biomedical
datasets fulfill this requirement due to the specific anatomy of a sample and
pre-defined alignment of the imaging setup. We examine the proposed method on
two datasets: medical CT of lungs affected by COVID-19 disease, and
high-resolution synchrotron-based full-body CT of model organisms (Medaka
fish). We show that the proposed method performs on par with SimCLR, while
working 2x faster and requiring 1.5x less memory. In addition, we present the
benefits in terms of practical scenarios, especially the applicability to the
pre-training of large models and the ability to localize samples within volumes
in an unsupervised setup.
|
Materials informatics exploiting machine learning techniques, e.g., Bayesian
optimization (BO), has the potential to offer high-throughput optimization of
thin-film growth conditions through incremental updates of machine learning
models in accordance with newly measured data. Here, we demonstrated BO-based
molecular beam epitaxy (MBE) of SrRuO3, one of the most-intensively studied
materials in the research field of oxide electronics, mainly owing to its
unique nature as a ferromagnetic metal. To simplify the intricate search space
of entangled growth conditions, we ran the BO for a single condition while
keeping the other conditions fixed. As a result, high-crystalline-quality
SrRuO3 film exhibiting a high residual resistivity ratio (RRR) of over 50 as
well as strong perpendicular magnetic anisotropy was developed in only 24 MBE
growth runs in which the Ru flux rate, growth temperature, and
O3-nozzle-to-substrate distance were optimized. Our BO-based search method
provides an efficient experimental design that is not as dependent on the
experience and skills of individual researchers, and it reduces experimental
time and cost, which will accelerate materials research.
|
We prove that the non-regular binary matroids with no $P_9^*$-minor have
linear growth rate and the maximum size binary matroids with no $P_9^*$-minor
are graphic. The main technique in the proof is the Strong Splitter Theorem
using which we find the precise infinite families of 3-connected binary
matroids with no $P_9^*$-minor.
|
The effects of combined external electric and magnetic fields on elastic
collisions in ultracold Li--Rb mixtures is studied using recently obtained,
experimentally verified potentials. Our analysis provides both quantitative
predictions for and a detailed physical interpretation of the phenomena arising
from electric-field-induced interactions. It is shown that the electric field
shifts the positions of intrinsic magnetic Feshbach resonances, generates
copies of resonances previously restricted to a particular partial-wave
collision to other partial wave channels, and splits Feshbach resonances into
multiple resonances for states of non-zero angular momenta. It was recently
observed that the magnetic dipole-dipole interaction can also lift the
degeneracy of a p-wave state splitting the associated p-wave Feshbach resonance
into two distinct resonances at different magnetic fields. Our work shows that
the splitting of the resonances produced by an applied electric field is more
than an order of magnitude larger. This new phenomenon offers a complementary
way to produce and tune an anisotropic interaction and to study its effect on
the many-body physics of heteronuclear atomic gases.
|
We present a Feynman graph selection tool {\tt grcsel}, which is an
interpreter written in C language. In the framework of {\tt GRACE}, it enables
us to get a subset of Feynman graphs according to given conditions.
|
Diffusions and related random walk procedures are of central importance in
many areas of machine learning, data analysis, and applied mathematics. Because
they spread mass agnostically at each step in an iterative manner, they can
sometimes spread mass "too aggressively," thereby failing to find the "right"
clusters. We introduce a novel Capacity Releasing Diffusion (CRD) Process,
which is both faster and stays more local than the classical spectral diffusion
process. As an application, we use our CRD Process to develop an improved local
algorithm for graph clustering. Our local graph clustering method can find
local clusters in a model of clustering where one begins the CRD Process in a
cluster whose vertices are connected better internally than externally by an
$O(\log^2 n)$ factor, where $n$ is the number of nodes in the cluster. Thus,
our CRD Process is the first local graph clustering algorithm that is not
subject to the well-known quadratic Cheeger barrier. Our result requires a
certain smoothness condition, which we expect to be an artifact of our
analysis. Our empirical evaluation demonstrates improved results, in particular
for realistic social graphs where there are moderately good---but not very
good---clusters.
|
In a recent work, restricted Schur polynomials have been argued to form a
complete orthogonal set of gauge invariant operators for the 1/4-BPS sector of
free N = 4 super Yang-Mills theory with an SO(N) gauge group. In this work, we
extend these results to the theory with an Sp(N) gauge group. Using these
operators, we develop techniques to compute correlation functions of any
multi-trace operators with two scalar fields exactly in the free theory limit
for both SO(N) and Sp(N).
|
We investigate the asymptotic behavior of the eigenvalues of the Laplacian
with homogeneous Robin boundary conditions, when the (positive) Robin parameter
is diverging. In this framework, since the convergence of the Robin eigenvalues
to the Dirichlet ones is known, we address the question of quantifying the rate
of such convergence. More precisely, in this work we identify the proper
geometric quantity representing (asymptotically) the first term in the
expansion of the eigenvalue variation: it is a novel notion of torsional
rigidity. Then, by performing a suitable asymptotic analysis of both such
quantity and its minimizer, we prove the first-order expansion of any Robin
eigenvalue, in the Dirichlet limit. Moreover, the convergence rate of the
corresponding eigenfunctions is obtained as well. We remark that all our
spectral estimates are explicit and sharp, and cover both the cases of
convergence to simple and multiple Dirichlet eigenvalues.
|
We present theoretical iron emission line strengths for physical conditions
typical of Active Galactic Nuclei with Broad-Line Regions. The non-local
thermodynamic equilibrium (NLTE) models include a new and extensive treatment
of radiative transfer in the FeIII ion, complementing the FeII emission line
strengths predicted in our earlier works. We also briefly present preliminary
results for the FeI emission from AGN using a reduced atom model. We can
satisfactorily reproduce the empirical UV FeIII emission line template of
Vestergaard & Wilkes (2001) for the prototypical narrow-line Seyfert 1 galaxy I
Zw 1, both in terms of the general FeIII flux distribution and the relative
strength of the FeIII and FeII emission. However, a number of detailed features
are still not matched; the most prominent example is the strongest single FeIII
feature observed in the I Zw 1 spectrum, UV47: it is predicted to be strong
only in models suppressing Fe-H charge exchange reactions. We examine the role
of variations in cloud turbulent velocity and iron abundance and carry out
Monte Carlo simulations to demonstrate the effect of uncertainties in atomic
data on the computed spectra.
|
The restriction problem is better understood for hypersurfaces and recent
progresses have been made by bilinear and multilinear approaches and most
recently polynomial partitioning method which is combined with those estimates.
However, for surfaces with codimension bigger than 1, bilinear and multilinear
generalization of restriction estimates are more involved and effectiveness of
these multilinear estimates is not so well understood yet. Regarding the
restriction problem for the surfaces with codimensions bigger than 1, the
current state of the art is still at the level of $TT^*$ method which is known
to be useful for obtaining $L^q$--$L^2$ restriction estimates. In this paper,
we consider a special type of codimension 2 surfaces which are given by graphs
of complex analytic functions and attempt to make progress beyond the $L^2$
restriction estimates.
|
The central star of this nebula has an observed intense magnetic field and
the fast wind is no longer present, indicating that a back flow process has
probably developed. Long-slit, spatially resolved echelle spectra have been
obtained across the main body of NGC 1360 and over its system of bipolar jets.
Deep images of the knotty structures of the jets have also been obtained. The
data allow a detailed study of the structure and kinematics of this object and
the results are modeled considering the effects of a magnetic collimation
process in the development of the nebula and then switching off the fast
stellar wind to follow its evolution to its current state. The model is able to
successfully reproduce many of the key features of NGC 1360 under these
premises.
|
Numerous advanced Large Language Models (LLMs) now support context lengths up
to 128K, and some extend to 200K. Some benchmarks in the generic domain have
also followed up on evaluating long-context capabilities. In the medical
domain, tasks are distinctive due to the unique contexts and need for domain
expertise, necessitating further evaluation. However, despite the frequent
presence of long texts in medical scenarios, evaluation benchmarks of
long-context capabilities for LLMs in this field are still rare. In this paper,
we propose MedOdyssey, the first medical long-context benchmark with seven
length levels ranging from 4K to 200K tokens. MedOdyssey consists of two
primary components: the medical-context "needles in a haystack" task and a
series of tasks specific to medical applications, together comprising 10
datasets. The first component includes challenges such as counter-intuitive
reasoning and novel (unknown) facts injection to mitigate knowledge leakage and
data contamination of LLMs. The second component confronts the challenge of
requiring professional medical expertise. Especially, we design the ``Maximum
Identical Context'' principle to improve fairness by guaranteeing that
different LLMs observe as many identical contexts as possible. Our experiment
evaluates advanced proprietary and open-source LLMs tailored for processing
long contexts and presents detailed performance analyses. This highlights that
LLMs still face challenges and need for further research in this area. Our code
and data are released in the repository:
\url{https://github.com/JOHNNY-fans/MedOdyssey.}
|
The partial differential equation (PDE) plays a significantly important role
in many fields of science and engineering. The conventional case of the
derivation of PDE mainly relies on first principles and empirical observation.
However, the development of machine learning technology allows us to mine
potential control equations from the massive amounts of stored data in a fresh
way. Although there has been considerable progress in the data-driven discovery
of PDE, the extant literature mostly focuses on the improvements of discovery
methods, without substantial breakthroughs in the discovery process itself,
including the principles for the construction of candidates and how to
incorporate physical priors. In this paper, through rigorous derivation of
formulas, novel physically enhanced machining learning discovery methods for
control equations: GSNN (Galileo Symbolic Neural Network) and LSNN (Lorentz
Symbolic Neural Network) are firstly proposed based on Galileo invariance and
Lorentz invariance respectively, setting forth guidelines for building the
candidates of discovering equations. The adoption of mandatory embedding of
physical constraints is fundamentally different from PINN in the form of the
loss function, thus ensuring that the designed Neural Network strictly obeys
the physical prior of invariance and enhancing the interpretability of the
network. By comparing the results with PDE-NET in numerical experiments of
Burgers equation and Sine-Gordon equation, it shows that the method presented
in this study has better accuracy, parsimony, and interpretability.
|
Transport measurements are performed on InAs/GaSb double quantum wells at
zero and finite magnetic fields applied parallel and perpendicular to the
quantum wells. We investigate a sample in the inverted regime where electrons
and holes coexist, and compare it with another sample in the non-inverted
semiconducting regime. Activated behavior in conjunction with a strong
suppression of the resistance peak at the charge neutrality point in a parallel
magnetic field attest to the topological hybridization gap between electron and
hole bands in the inverted sample. We observe an unconventional Landau level
spectrum with energy gaps modulated by the magnetic field applied perpendicular
to the quantum wells. This is caused by strong spin-orbit interaction provided
jointly by the InAs and the GaSb quantum wells.
|
We begin the Article with confusing citations in published papers on the
question recently: how much time does a wave packet spend in a tunnelling
barrier? ..a particle tunnelling through a barrier appears to do so in zero
time 1. .. The pulse transit through the barrier itself seems to be
instantaneous 2. ..tunnelling is unlike to be an instantaneous process 3.
..ionization time is close to zero 4. ..all waves have a zero tunneling time
[5]. ..Our results are inconsistent with claims that tunnelling takes zero time
6
|
We present a study of the evolution of brightest cluster galaxies (BCGs) in a
sample of clusters at $0.05 \leq z<0.35$ from the SDSS and WISE with halo
masses in the range $6 \times 10^{13}M_\odot$ (massive groups) -
$10^{15.5}M_\odot$ (Coma-like clusters). We analyse optical and infrared
colours and stellar masses of BCGs as a function of the mass of their host
haloes. We find that BCGs are mostly red and quiescent galaxies and that a
minority ($\sim 9$\%) of them are star-forming. We find that the optical $g-r$
colours are consistent with those of red sequence galaxies at the same
redshifts; however, we detect the presence of a tail of blue and mostly
star-forming BCGs preferentially located in low-mass clusters and groups.
Although the blue tail is dominated by star-forming galaxies, we find that
star-forming BCGs may also have red $g-r$ colours, indicating dust-enshrouded
star formation. The fraction of star-forming BCGs increases with redshift and
decreases with cluster mass and BCG stellar mass. We find that cool-core
clusters host both star-forming and quiescent BCGs; however, non cool-core
clusters are dominated by quiescent BCGs. Star formation appears thus as the
result of processes that depend on stellar mass, cluster mass and cooling state
of the intra-cluster medium. Our results suggest no significant stellar mass
growth at $z<0.35$, supporting the notion that BCGs had accreted most of their
mass by $z = 0.35$. Overall we find a low (1\%) AGN fraction detected at IR
wavelengths.
|
We present a chatbot implementing a novel dialogue management approach based
on logical inference. Instead of framing conversation a sequence of response
generation tasks, we model conversation as a collaborative inference process in
which speakers share information to synthesize new knowledge in real time. Our
chatbot pipeline accomplishes this modelling in three broad stages. The first
stage translates user utterances into a symbolic predicate representation. The
second stage then uses this structured representation in conjunction with a
larger knowledge base to synthesize new predicates using efficient graph
matching. In the third and final stage, our bot selects a small subset of
predicates and translates them into an English response. This approach lends
itself to understanding latent semantics of user inputs, flexible initiative
taking, and responses that are novel and coherent with the dialogue context.
|
We report a device fabrication strategy of making multi-terminal electrical
contacts on small (< 1 mm) bulk quantum materials using lithography-based
techniques for electrical transport studies. The crystals are embedded in a
polymeric medium to planarize the top surface, and then standard lithography
and microfabrication techniques are directly applied to form electrodes with
various geometries. This approach overcomes the limitations of crystal
thickness and lateral dimensions on establishing electrical contacts. We use
low stress polymers to minimize the extrinsic thermal strain effect at low
temperatures, which allow reliable transport measurements on quantum materials
that are sensitive to strain. The crystal surface planarization method has
enabled electronic transport studies such as in-plane anisotropy, Hall
measurements on small, bulk BaTiS3 (BTS) crystals, and provides unique
opportunities for two-dimensional (2D) heterogeneous integration on
three-dimensional (3D) / quasi-one-dimensional (quasi-1D) bulk materials. Our
strategy is general for many small, non-exfoliable crystals of newly
synthesized quantum materials and paves the way for performing versatile
transport studies on those novel materials.
|
Egocentric spatial memory (ESM) defines a memory system with encoding,
storing, recognizing and recalling the spatial information about the
environment from an egocentric perspective. We introduce an integrated deep
neural network architecture for modeling ESM. It learns to estimate the
occupancy state of the world and progressively construct top-down 2D global
maps from egocentric views in a spatially extended environment. During the
exploration, our proposed ESM model updates belief of the global map based on
local observations using a recurrent neural network. It also augments the local
mapping with a novel external memory to encode and store latent representations
of the visited places over long-term exploration in large environments which
enables agents to perform place recognition and hence, loop closure. Our
proposed ESM network contributes in the following aspects: (1) without feature
engineering, our model predicts free space based on egocentric views
efficiently in an end-to-end manner; (2) different from other deep
learning-based mapping system, ESMN deals with continuous actions and states
which is vitally important for robotic control in real applications. In the
experiments, we demonstrate its accurate and robust global mapping capacities
in 3D virtual mazes and realistic indoor environments by comparing with several
competitive baselines.
|
JavaScript engines inside modern browsers are capable of running
sophisticated multi-player games, rendering impressive 3D scenes, and
supporting complex, interactive visualizations. Can this processing power be
harnessed for information retrieval? This paper explores the feasibility of
building a JavaScript search engine that runs completely self-contained on the
client side within the browser---this includes building the inverted index,
gathering terms statistics for scoring, and performing query evaluation. The
design takes advantage of the IndexDB API, which is implemented by the LevelDB
key-value store inside Google's Chrome browser. Experiments show that although
the performance of the JavaScript prototype falls far short of the open-source
Lucene search engine, it is sufficiently responsive for interactive
applications. This feasibility demonstration opens the door to interesting
applications in offline and private search across multiple platforms as well as
hybrid split-execution architectures whereby clients and servers
collaboratively perform query evaluation. One possible future scenario is the
rise of an online search marketplace in which commercial search engine
companies and individual users participate as rational economic actors,
balancing privacy, resource usage, latency, and other factors based on
customizable utility profiles.
|
This paper presents an estimate of the land area affected in the event of sea
level rise of 0.6 m, 1 m and 2 m for Mexican sates with coasts along Gulf of
Mexico. Likewise, the number of residents in vulnerable areas that would occur
in the scenario of sea level rise of 1 m is estimated. To do so, terrain
elevation data of NASA's Shuttle Radar Topography Mission is used, along with a
proprietary algorithm that allows the reconstruction of the affected area. In
order to estimate the land area digital image processing is used. These results
are geo-referenced for comparison with human settlements in the regions of
interest. Results show that the total affected area corresponds to 1.26% of
Mexico national territorial extension and 3.18% of the Mexico total population.
174 settlements with 1000 inhabitants or more are expected to be affected. The
Mexican state with the largest area affected is Tabasco with more than 21% of
its territory, while the most vulnerable population will be Veracruz, with more
than 1 million people at risk if the scenario 1m increase would appear today.
Meanwhile, 81.1% Quintana Roo population will be at zones with high flood risk.
Vulnerable settlements are listed and the maps corresponding to different
Mexican states are shown.
|
Millimeter wave wireless systems rely heavily on directional communication in
narrow steerable beams. Tools to measure the spatial and temporal nature of the
channel are necessary to evaluate beamforming and related algorithms. This
paper presents a novel 60~GHz phased-array based directional channel sounder
and data analysis procedure that can accurately extract paths and their
transmit and receive directions. The gains along each path can also be measured
for analyzing blocking scenarios. The sounder is validated in an indoor office
environment.
|
We perform an analysis on the electromagnetic form factors of the $\Lambda$
hyperon in the time-like reaction $e^+e^-\rightarrow \Lambda\bar\Lambda$ by
using a modified vector meson dominance model. We consider both the intrinsic
structure components and the meson clouds components. For the latter one, we
not only include the contributions from the $\phi$ and $\omega$ mesons, but
also take into account the contributions from the resonance states
$\omega(1420)$, $\omega(1650)$, $\phi(1680)$ and $\phi(2170)$. We extract the
model parameters by combined fit to the time-like effective form factor
$|G_{\rm{eff}}|$, the electromagnetic form factor ratio $|G_E/G_M|$ and the
relative phase $\Delta\Phi$ of the $\Lambda$ hyperon from the BaBar and BESIII
Collaborations. We find that the vector meson dominance model can
simultaneously describe these observables. Particularly, the inclusion of the
resonance states in the model is necessary for explaining the ratio $|G_E/G_M|$
in a wide range of $\sqrt{s}$ as well as the large phase angle. With the fitted
parameters, we predict the single and double polarization observables, which
could be measured in polarized annihilation reactions. Moreover, we
analytically continue the expression of the form factors to space-like region
and estimate the space-like form factors of $\Lambda$ hyperon.
|
We propose a novel Active Learning framework capable to train effectively a
convolutional neural network for semantic segmentation of medical imaging, with
a limited amount of training labeled data. Our contribution is a practical
Cost-Effective Active Learning approach using dropout at test time as Monte
Carlo sampling to model the pixel-wise uncertainty and to analyze the image
information to improve the training performance. The source code of this
project is available at
https://marc-gorriz.github.io/CEAL-Medical-Image-Segmentation/ .
|
Recently, there has been considerable interest in solving optimization
problems by mapping these onto a binary representation, sparked mostly by the
use of quantum annealing machines. Such binary representation is reminiscent of
a discrete physical two-state system, such as the Ising model. As such,
physics-inspired techniques -- commonly used in fundamental physics studies --
are ideally suited to solve optimization problems in a binary format. While
binary representations can be often found for paradigmatic optimization
problems, these typically result in k-local higher-order unconstrained binary
optimization cost functions. In this work, we discuss the effects of locality
reduction needed for the majority of the currently available quantum and
quantum-inspired solvers that can only accommodate 2-local (quadratic) cost
functions. General locality reduction approaches require the introduction of
ancillary variables which cause an overhead over the native problem. Using a
parallel tempering Monte Carlo solver on Microsoft Azure Quantum, as well as
k-local binary problems with planted solutions, we show that post reduction to
a corresponding 2-local representation the problems become considerably harder
to solve. We further quantify the increase in computational hardness introduced
by the reduction algorithm by measuring the variation of number of variables,
statistics of the coefficient values, and the population annealing entropic
family size. Our results demonstrate the importance of avoiding locality
reduction when solving optimization problems.
|
We measure the rates of type I X-ray bursts, as a function of the bolometric
luminosity, from a likely complete sample of 37 non-pulsing transients
(1996-2004). Our goals are to test the burst model for neutron stars and to
investigate whether black holes have event horizons. We find 135 type I bursts
in 3.7 Ms of exposure for the neutron-star group, and the burst rate function
is generally consistent with model predictions. However, for the black hole
groups (18 sources), there are no confirmed type I bursts in 6.5 Ms of
exposure, and the upper limits in the burst function are inconsistent with the
model predictions for heavy compact objects with a solid surface. There are
systematic spectral differences between the neutron-star and black-hole groups,
supporting the presumption that physical differences underly the sample
classifications. These results provide indirect evidence that black holes do
have event horizons.
|
We study the biased $(2:b)$ Walker--Breaker games, played on the edge set of
the complete graph on $n$ vertices, $K_n$. These games are a variant of the
Maker--Breaker games with the restriction that Walker (playing the role of
Maker) has to choose her edges according to a walk. We look at the two standard
graph games -- the Connectivity game and the Hamilton Cycle game and show that
Walker can win both games even when playing against Breaker whose bias is of
the order of magnitude $n/ \ln n$.
|
The origin of chirality, closely related to the evolution of life on the
earth, has long been debated. In 1991, Abdus Salam suggested a novel approach
to achieve biomolecular homochirality by a phase transition. In his subsequent
publication, he predicted that this phase transition could eventually change
D-amino acids to L-amino acids as C -H bond would break and H atom became a
superconductive atom. Since many experiments denied the configuration change in
amino acids, Salam hypothesis aroused suspicion. This paper is aimed to provide
direct experimental evidence of a phase transition in alanine, valine single
crystals but deny the configuration change of D- to L- enantiomers. New views
on Salam phase transition are presented to revalidate its great importance in
the origin of homochirality.
|
According to the G\"ottsche conjecture (now a theorem), the degree N^{d,
delta} of the Severi variety of plane curves of degree d with delta nodes is
given by a polynomial in d, provided d is large enough. These "node
polynomials" N_delta(d) were determined by Vainsencher and Kleiman-Piene for
delta <= 6 and delta <= 8, respectively. Building on ideas of Fomin and
Mikhalkin, we develop an explicit algorithm for computing all node polynomials,
and use it to compute N_delta(d) for delta <= 14. Furthermore, we improve the
threshold of polynomiality and verify G\"ottsche's conjecture on the optimal
threshold up to delta <= 14. We also determine the first 9 coefficients of
N_delta(d), for general delta, settling and extending a 1994 conjecture of Di
Francesco and Itzykson.
|
Properties of superconducting nanowires set the performance level for
Superconducting Nanowire Single Photon Detectors (SNSPD). Reset time in
commonly employed large area SNSPDs,5-10ns,is known to be limited by the
nanowires kinetic inductance.On the other hand, reduction of the kinetic
inductance in small area (waveguide integrated) SNSPDs prevents biasing them
close to the critical current due to latching into a permanent resistive
state.In order to reduce the reset time in SNSPDs, superconducting nanowires
with both low kinetic inductance and fast electron energy relaxation are
required. In this paper, we report on narrow (15-100nm) and long (up to 120
$\mu$m) superconducting $MgB_{2}$ nanowires offering such combination of
properties.In 5 nm-thick $MgB_{2}$ films, grown using Hybrid Physical Chemical
Vapor Deposition, the electron relaxation time was 12ps, the critical
temperature was 32K, and the critical current density was 5x$10^{7}$ A/$cm^{2}$
(at 4.8K). Using microwave reflectometry, we measured a kinetic inductance of
Lk0(4.8K)=1.3-1.6 pH/sqr regardless of the nanowire width, which results in a
magnetic field penetration depth of 90 nm. These values are very close to those
in pristine $MgB_{2}$. For 120 $\mu$m long nanowires the response time was only
100ps, i.e. 1/80 of that in previously reported NbN nanowire photon detectors
of similar dimensions.
|
This work recollects a non-universal set of quantum gates described by
higher-dimensional Spin groups. They are also directly related with matchgates
in theory of quantum computations and complexity. Various processes of quantum
state distribution along a chain such as perfect state transfer and different
types of quantum walks can be effectively modeled on classical computer using
such approach.
|
We present a general theory of optical coherence tomography (OCT), which
synthesizes the fundamental concepts and implementations of OCT under a common
3D k-space framework. At the heart of this analysis is the Fourier diffraction
theorem, which relates the coherent interaction between a sample and plane wave
to the Ewald sphere in the 3D k-space representation of the sample. While only
the axial dimension of OCT is typically analyzed in k-space, we show that
embracing a fully 3D k-space formalism allows explanation of nearly every
fundamental physical phenomenon or property of OCT, including contrast
mechanism, resolution, dispersion, aberration, limited depth of focus, and
speckle. The theory also unifies diffraction tomography, confocal microscopy,
point-scanning OCT, line-field OCT, full-field OCT, Bessel-beam OCT,
transillumination OCT, interferometric synthetic aperture microscopy (ISAM),
and optical coherence refraction tomography (OCRT), among others. Our unified
theory not only enables clear understanding of existing techniques, but also
suggests new research directions to continue advancing the field of OCT.
|
We analyze the stability of the Einstein static closed and open universe in
two types of exponential $f(T)$ gravity theories. We show that the stable
solutions exist in these two models. In particular, we find that large regions
of parameter space in equation of state $w=p/\rho$ for the stable universe are
allowed in the $f(T)$ theories.
|
The success of deep learning in numerous application domains created the de-
sire to run and train them on mobile devices. This however, conflicts with
their computationally, memory and energy intense nature, leading to a growing
interest in compression. Recent work by Han et al. (2015a) propose a pipeline
that involves retraining, pruning and quantization of neural network weights,
obtaining state-of-the-art compression rates. In this paper, we show that
competitive compression rates can be achieved by using a version of soft
weight-sharing (Nowlan & Hinton, 1992). Our method achieves both quantization
and pruning in one simple (re-)training procedure. This point of view also
exposes the relation between compression and the minimum description length
(MDL) principle.
|
In this paper we introduce radical transversal lightlike hypersurfaces of
almost complex manifolds with Norden metric. The study of these hypersurfaces
is motivated by the fact that for indefinite almost Hermitian manifolds this
class of lightlike hypersurfaces does not exist. We also establish that radical
transversal lightlike hypersurfaces of almost complex manifolds with Norden
metric have nice properties as a unique screen distribution and a symmetric
Ricci tensor of the considered hypersurfaces of Kaehler manifolds with Norden
metric. We obtain new results about lightlike hypersurfaces concerning to their
relations with non-degenerate hypersurfaces of almost complex manifolds with
Norden metric. Examples of the considered hypersurfaces are given.
|
As machine learning has become more relevant for everyday applications, a
natural requirement is the protection of the privacy of the training data. When
the relevant learning questions are unknown in advance, or hyper-parameter
tuning plays a central role, one solution is to release a differentially
private synthetic data set that leads to similar conclusions as the original
training data. In this work, we introduce an algorithm that enjoys fast rates
for the utility loss for sparse Lipschitz queries. Furthermore, we show how to
obtain a certificate for the utility loss for a large class of algorithms.
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The notion of intrinsic algebraic entropy of an endomorphism of a given
Abelian group has been recently introduced in [D. Dikranjan, A. Giordano Bruno,
L. Salce, S. Virili, Intrinsic algebraic entropy, J. Pure Appl. Algebra 219
(2015) 2933-2961]. In this short note we provide a correct argument to prove
one of the basic properties of the intrinsic algebraic entropy: the Logarithmic
Law. In fact, this property was correctly stated in [op. cit.] but, as we will
show with an explicit counterexample, the original proof contains a flaw.
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In this paper we consider some possible approaches to the proof of the
Riemann Hypothesis using the Li criterion.
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We consider the torus compactifications with flux of a class of $6d$ $(1,0)$
SCFTs that can be engineered as the low-energy theories on M$5$-branes near an
M$9$-plane on a $C^2/Z_2$ singularity. Specifically, we concentrate on the two
SCFTs where the $Z_2$ orbifold action acts non-trivially on the $E_8$ global
symmetry. We analyze this problem by compactifying to $5d$, where we can
exploit the relation to $5d$ duality domain walls. By a suitable guess of the
domain wall theories, the resulting $4d$ theories can be conjectured. These can
then be tested by comparing their properties, notably anomalies and symmetries,
against the $6d$ expectations. These constructions lead to various interesting
$4d$ phenomena like dualities and symmetry enhancements.
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Electron-phonon coupling (EPC) is one of the most common and fundamental
interactions in solids. It not only dominates many basic dynamic processes like
resistivity, thermal conductivity etc, but also provides the pairing glue in
conventional superconductors. But in high-temperature superconductors (HTSC),
it is still controversial whether or not EPC is in favor of paring. Despite the
controversies, many experiments have provided clear evidence for EPC in HTSC.
In this paper, we briefly review EPC in cuprate and iron-based superconducting
systems revealed by Raman scattering. We introduce how to extract the coupling
information through phonon lineshape. Then we discuss the strength of EPC in
different HTSC systems and possible factors affecting the strength. The
comparative study between Raman phonon theories and experiments allows us to
gain insight into some crucial electronic properties, especially
superconductivity. Finally we summarize and compare EPC in the two existing
HTSC systems, and discuss what role it may play in HTSC.
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A condition is defined which determines if a supertranslation is induced in
the course of a general evolution from one isolated horizon phase to another
via a dynamical horizon. This condition fixes preferred slices on an isolated
horizon and is preserved along an Isolated Horizon. If it is not preserved, in
the course of a general evolution, then a supertranslation will be said to have
been induced. A simple example of spherically symmetric dynamical horizons is
studied to illustrate the conditions for inducing supertranslations.
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A significant amount of work has been done on adversarial attacks that inject
imperceptible noise to images to deteriorate the image classification
performance of deep models. However, most of the existing studies consider
attacks in the digital (pixel) domain where an image acquired by an image
sensor with sampling and quantization has been recorded. This paper, for the
first time, introduces an optical adversarial attack, which physically alters
the light field information arriving at the image sensor so that the
classification model yields misclassification. More specifically, we modulate
the phase of the light in the Fourier domain using a spatial light modulator
placed in the photographic system. The operative parameters of the modulator
are obtained by gradient-based optimization to maximize cross-entropy and
minimize distortions. We present experiments based on both simulation and a
real hardware optical system, from which the feasibility of the proposed
optical attack is demonstrated. It is also verified that the proposed attack is
completely different from common optical-domain distortions such as spherical
aberration, defocus, and astigmatism in terms of both perturbation patterns and
classification results.
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A simulation model for the spread and control of lesions in the brain is
constructed using a planar network (graph) representation for the Central
Nervous System (CNS). The model is inspired by the lesion structures observed
in the case of Multiple Sclerosis (MS), a chronic disease of the CNS. The
initial lesion site is at the center of a unit square and spreads outwards
based on the success rate in damaging edges (axons) of the network. The damaged
edges send out alarm signals which, at appropriate intensity levels, generate
programmed cell death. Depending on the extent and timing of the programmed
cell death, the lesion may get controlled or aggravated akin to the control of
wild fires by burning of peripheral vegetation. The parameter phase space of
the model shows smooth transition from uncontrolled situation to controlled
situation. The simulations show that the model is capable of generating a wide
variety of lesion growth and arrest scenarios.
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We present the first self-supervised multilingual speech model trained
exclusively on African speech. The model learned from nearly 60 000 hours of
unlabeled speech segments in 21 languages and dialects spoken in sub-Saharan
Africa. On the SSA subset of the FLEURS-102 dataset, our approach based on a
HuBERT$_{base}$ (0.09B) architecture shows competitive results, for ASR
downstream task, compared to the w2v-bert-51 (0.6B) pre-trained model proposed
in the FLEURS benchmark, while being more efficient by using 7x less data and
6x less parameters. Furthermore, in the context of a LID downstream task, our
approach outperforms FLEURS baselines accuracy by over 22\%.
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We examine the deflected mirage mediation supersymmetry breaking (DMMSB)
scenario, which includes contributions from three mediation mechanisms, namely
anomaly mediation, gravity mediation and gauge mediation, using the one-loop
renormalization group invariants (RGIs). We examine the effects on the RGIs at
the threshold where the gauge messengers emerge, and derive the soft
supersymmetry breaking parameters in terms of the RGIs. We further discuss
determining the supersymmetry breaking mechanism using a limited set of
invariants, and derive sum rules valid for the DMMSB. In addition we examine
some of the implications of the measured Higgs mass to the DMMSB spectrum.
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We prove that the a standard adaptive algorithm for the Taylor-Hood
discretization of the stationary Stokes problem converges with optimal rate.
This is done by developing an abstract framework for indefinite problems which
allows us to prove general quasi-orthogonality proposed in [Carstensen et al.,
2014]. This property is the main obstacle towards the optimality proof and
therefore is the main focus of this work. The key ingredient is a new
connection between the mentioned quasi-orthogonality and $LU$-factorizations of
infinite matrices.
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The $J$-matrix method is extended to difference and $q$-difference operators
and is applied to several explicit differential, difference, $q$-difference and
second order Askey-Wilson type operators. The spectrum and the spectral
measures are discussed in each case and the corresponding eigenfunction
expansion is written down explicitly in most cases. In some cases we encounter
new orthogonal polynomials with explicit three term recurrence relations where
nothing is known about their explicit representations or orthogonality
measures. Each model we analyze is a discrete quantum mechanical model in the
sense of Odake and Sasaki [J. Phys. A: Math. Theor. 44 (2011), 353001, 47
pages].
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A conformally flat accelerated charge metric is found in an arbitrary
dimension $D$. It is a solution of the Einstein-Maxwell-null fluid with a
cosmological constant in $D \ge 4$ dimensions. When the acceleration is zero
our solution reduces to the Levi-Civita-Bertotti-Robinson metric. We show that
the charge loses its energy, for all dimensions, due to the acceleration.
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Self-sovereign identity (SSI) is considered to be a "killer application" of
blockchain. However, there is a lack of systematic architecture designs for
blockchain-based SSI systems to support methodical development. An aspect of
such gap is demonstrated in current solutions, which are considered coarse
grained and may increase data security risks. In this paper, we first identify
the lifecycles of three major SSI objects (i.e., key, identifier, and
credential) and present fine-grained design patterns critical for application
development. These patterns are associated with particular state transitions,
providing a systematic view of system interactions and serving as a guidance
for effective use of these patterns. Further, we present an SSI platform
architecture, which advocates the notion of Design-Pattern-as-a-Service. Each
design pattern serves as an API by wrapping the respective pattern code to ease
application development and improve scalability and security. We implement a
prototype and evaluate it on feasibility and scalability.
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Outages and faults cause problems in interconnected power system with huge
economic consequences in modern societies. In the power system blackouts, black
start resources such as micro combined heat and power (CHP) systems and
renewable energies, due to their self-start ability, are one of the solutions
to restore power system as quickly as possible. In this paper, we propose a
model for power system restoration considering CHP systems and renewable energy
sources as being available in blackout states. We define a control variable
representing a level of balance between the distance and importance of loads
according to the importance and urgency of the affected customer. Dynamic power
flow is considered in order to find feasible sequence and combination of loads
for load restoration.
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We calculate the flux-flow resistivity of the Josephson vortex lattice in a
layered superconductor taking into account both the inter-plane and in-plane
dissipation channels. We consider the limiting cases of small fields (isolated
vortices) and high fields (overlapping vortices). In the case of the dominating
in-plane dissipation, typical for high-temperature superconductors, the field
dependence of flux-flow resistivity is characterized by {\it three} distinct
regions. As usual, at low fields the flux-flow resistivity grows linearly with
field. When the Josephson vortices start to overlap the flux-flow resistivity
crosses over to the regime of {\it quadratic} field dependence. Finally, at
very high fields the flux-flow resistivity saturates at the c-axis
quasiparticle resistivity. The intermediate quadratic regime indicates dominant
role of the in-plane dissipation mechanism. Shape of the field dependence of
the flux-flow resistivity can be used to extract both components of the
quasiparticle
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We make the case for the systematic, reliable preservation of event-wise
data, derived data products, and executable analysis code. This preservation
enables the analyses' long-term future reuse, in order to maximise the
scientific impact of publicly funded particle-physics experiments. We cover the
needs of both the experimental and theoretical particle physics communities,
and outline the goals and benefits that are uniquely enabled by analysis
recasting and reinterpretation. We also discuss technical challenges and
infrastructure needs, as well as sociological challenges and changes, and give
summary recommendations to the particle-physics community.
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$\alpha$-clustering study since the pioneering discovery of $^{12}$C+$^{12}$C
molecular resonances half a century ago. Our knowledge on physics of nuclear
molecules has increased considerably and nuclear clustering remains one of the
most fruitful domains of nuclear physics, facing some of the greatest
challenges and opportunities in the years ahead. The occurrence of "exotic"
shapes in light $N$=$Z$ $\alpha$-like nuclei is investigated. Various
approaches of the superdeformed and hyperdeformed bands associated with
quasimolecular resonant structures are presented. Evolution of clustering from
stability to the drip-lines is examined: clustering aspects are, in particular,
discussed for light exotic nuclei with large neutron excess such as
neutron-rich Oxygen isotopes with their complete spectrocopy.
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We report on the structural and optical properties of individual bowtie
nanoantennas both on glass and semiconducting GaAs substrates. The antennas on
glass (GaAs) are shown to be of excellent quality and high uniformity reflected
by narrow size distributions with standard deviations for the triangle and gap
size of $\sigma_s^{glass}=4.5nm$ ($\sigma_s^{GaAs}=2.6nm$) and
$\sigma_g^{glass}=5.4nm$ ($\sigma_g^{GaAs}=3.8nm$), respectively. The
corresponding optical properties of individual nanoantennas studied by
differential reflection spectroscopy show a strong reduction of the localised
surface plasmon polariton resonance linewidth from $0.21eV$ to $0.07eV$ upon
reducing the antenna size from $150nm$ to $100nm$. This is attributed to the
absence of inhomogeneous broadening as compared to optical measurements on
nanoantenna ensembles. The inter-particle coupling of an individual bowtie
nanoantenna, which gives rise to strongly localised and enhanced
electromagnetic hotspots, is demonstrated using polarization-resolved
spectroscopy, yielding a large degree of linear polarization of
$\rho_{max}\sim80\%$. The combination of highly reproducible nanofabrication
and fast, non-destructive and non-contaminating optical spectroscopy paves the
route towards future semiconductor-based nano-plasmonic circuits, consisting of
multiple photonic and plasmonic entities.
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Let $R$ be a commutative complex unital semisimple Banach algebra with the
involution $\cdot ^\star$. Sufficient conditions are given for the existence of
a stabilizing solution to the $H^\infty$ Riccati equation when the matricial
data has entries from $R$. Applications to spatially distributed systems are
discussed.
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We have carried out elastic neutron scattering measurements on
La$_{1.875}$Ba$_{0.075}$Sr$_{0.05}$CuO$_4$ single crystal ($T_c\approx$10K).
Incommensurate elastic magnetic peaks were observed in the low-tamperature
tetragonal phase with the propergation vector parallel/perpendicular to
in-plane Cu-O bond direction. The magnetic peak intensity normalized by the
sample volume is approximately six times larger than that of the orthorhombic
La$_{1.88}$Sr$_{0.12}$CuO$_4$ at low temperature.
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Label-free imaging through two-photon autofluorescence (2PAF) of NAD(P)H
allows for non-destructive and high-resolution visualization of cellular
activities in living systems. However, its application to thick tissues and
organoids has been restricted by its limited penetration depth within 300
$\mu$m, largely due to tissue scattering at the typical excitation wavelength
(~750 nm) required for NAD(P)H. Here, we demonstrate that the imaging depth for
NAD(P)H can be extended to over 700 $\mu$m in living engineered human
multicellular microtissues by adopting multimode fiber (MMF)-based
low-repetition-rate high-peak-power three-photon (3P) excitation of NAD(P)H at
1100 nm. This is achieved by having over 0.5 MW peak power at the band of
1100$\pm$25 nm through adaptively modulating multimodal nonlinear pulse
propagation with a compact fiber shaper. Moreover, the 8-fold increase in pulse
energy at 1100 nm enables faster imaging of monocyte behaviors in the living
multicellular models. These results represent a significant advance for deep
and dynamic metabolic and structural imaging of intact living biosystems. The
modular design (MMF with a slip-on fiber shaper) is anticipated to allow wide
adoption of this methodology for demanding in vivo and in vitro imaging
applications, including cancer research, autoimmune diseases, and tissue
engineering.
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Given an edge-weighted graph and a set of known seed vertices, a network
scientist often desires to understand the graph relationships to explain
connections between the seed vertices. When the seed set is 3 or larger Steiner
minimal tree - min-weight acyclic connected subgraph (of the input graph) that
contains all the seed vertices - is an attractive generalization of shortest
weighted paths. In general, computing a Steiner minimal tree is NP-hard, but
several polynomial-time algorithms have been designed and proven to yield
Steiner trees whose total weight is bounded within 2 times the Steiner minimal
tree. In this paper, we present a parallel 2-approximation Steiner minimal tree
algorithm and its MPI-based distributed implementation. In place of distance
computation between all pairs of seed vertices, an expensive phase in many
algorithms, our solution exploits Voronoi cell computation. Also, this approach
has higher parallel efficiency than others that involve minimum spanning tree
computation on the entire graph. Furthermore, our distributed design exploits
asynchronous processing and a message prioritization scheme to accelerate
convergence of distance computation, and harnesses both vertex and edge centric
processing to offer fast time-to-solution. We demonstrate scalability and
performance of our solution using real-world graphs with up to 128 billion
edges and 512 compute nodes (8K processes). We compare our solution with the
state-of-the-art exact Steiner minimal tree solver, SCIP-Jack, and two serial
algorithms. Our solution comfortably outperforms these related works on graphs
with 10s million edges and offers decent strong scaling - up to 90% efficient.
We empirically show that, on average, the total distance of the Steiner tree
identified by our solution is 1.0527 times greater than the Steiner minimal
tree - well within the theoretical bound of less than equal to 2.
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We review three vector encodings of Bayesian network structures. The first
one has recently been applied by Jaakkola 2010, the other two use special
integral vectors formerly introduced, called imsets [Studeny 2005, Studeny
2010]. The central topic is the comparison of outer polyhedral approximations
of the corresponding polytopes. We show how to transform the inequalities
suggested by Jaakkola et al. to the framework of imsets. The result of our
comparison is the observation that the implicit polyhedral approximation of the
standard imset polytope suggested in [Studeny 2011] gives a closer
approximation than the (transformed) explicit polyhedral approximation from
[Jaakkola 2010]. Finally, we confirm a conjecture from [Studeny 2011] that the
above-mentioned implicit polyhedral approximation of the standard imset
polytope is an LP relaxation of the polytope.
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Near total reflection regime has been widely used in X-ray science,
specifically in grazing incidence small angle X-ray scattering and in hard
X-ray photoelectron spectroscopy. In this work, we introduce some practical
aspects of using near total reflection in ambient pressure X-ray photoelectron
spectroscopy and apply this technique to study chemical concentration gradients
in a substrate/photoresist system. Experimental data are accompanied by X-ray
optical and photoemission simulations to quantitatively probe the photoresist
and the interface with the depth accuracy of ~1 nm. Together, our calculations
and experiments confirm that near total reflection X-ray photoelectron
spectroscopy is a suitable method to extract information from buried interfaces
with highest depth-resolution, which can help address open research questions
regarding our understanding of concentration profiles, electrical gradients,
and charge transfer phenomena at such interfaces. The presented methodology is
especially attractive for solid/liquid interface studies, since it provides all
the strengths of a Bragg-reflection standing-wave spectroscopy without the need
of an artificial multilayer mirror serving as a standing wave generator, thus
dramatically simplifying the sample synthesis.
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We propose a construction of a tensor exact category F_X^m of Artin-Tate
motivic sheaves with finite coefficients Z/m over an algebraic variety X (over
a field K of characteristic prime to m) in terms of etale sheaves of
Z/m-modules over X. Among the objects of F_X^m, in addition to the Tate motives
Z/m(j), there are the cohomological relative motives with compact support
M_cc^m(Y/X) of varieties Y quasi-finite over X. Exact functors of inverse image
with respect to morphisms of algebraic varieties and direct image with compact
supports with respect to quasi-finite morphisms of varieties Y\to X act on the
exact categories F_X^m. Assuming the existence of triangulated categories of
motivic sheaves DM(X,Z/m) over algebraic varities X over K and a weak version
of the "six operations" in these categories, we identify F_X^m with the exact
subcategory in DM(X,Z/m) consisting of all the iterated extensions of the Tate
twists M_cc^m(Y/X)(j) of the motives M_cc^m(Y/X). An isomorphism of the
Z/m-modules Ext between the Tate motives Z/m(j) in the exact category F_X^m
with the motivic cohomology modules predicted by the Beilinson-Lichtenbaum
etale descent conjecture (recently proven by Voevodsky, Rost, et al.) holds for
smooth varieties X over K if and only if the similar isomorphism holds for
Artin-Tate motives over fields containing K. When K contains a primitive m-root
of unity, the latter condition is equivalent to a certain Koszulity hypothesis,
as it was shown in our previous paper arXiv:1006.4343
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When dark matter structures form and equilibrate they have to release a
significant amount of energy in order to obey the virial theorem. Since dark
matter is believed to be unable to radiate, this implies that some of the
accreted dark matter particles must be ejected with high velocities. These
ejected particles may then later hit other cosmological structures and deposit
their momentum within these structures. This induces a pressure between the
cosmological structures which opposes the effect of gravity and may therefore
mimic a cosmological constant. We estimate the magnitude of this effect and
find that it may be as large as the observed accelerated expansion. Our
estimate is accurate only within a few orders of magnitude. It is therefore
important to make a much more careful calculation of this redshift dependent
effect, before beginning to interpret the observed accelerated expansion as a
time dependent generalization of a cosmological constant.
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