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Recently, the first collisional family was identified in the trans-Neptunian
belt. The family consists of Haumea and at least ten other ~100km-sized
trans-Neptunian objects (TNOs) located in the region a = 42 - 44.5 AU. In this
work, we model the long-term orbital evolution of an ensemble of fragments
representing hypothetical post-collision distributions at the time of the
family's birth. We consider three distinct scenarios, in which the kinetic
energy of dispersed particles were varied such that their mean ejection
velocities (veje) were of order 200 m/s, 300 m/s and 400 m/s, respectively.
Each simulation considered resulted in collisional families that reproduced
that currently observed. The results suggest that 60-75% of the fragments
created in the collision will remain in the trans-Neptunian belt, even after 4
Gyr of dynamical evolution. The surviving particles were typically concentrated
in wide regions of orbital element space centred on the initial impact
location, with their orbits spread across a region spanning {\Delta}a ~ 6-12
AU, {\Delta}e ~ 0.1-0.15 and {\Delta}i ~ 7-10{\deg}. Most of the survivors
populated the so-called Classical and Detached regions of the trans-Neptunian
belt, whilst a minor fraction entered the Scattered Disk reservoir (<1%), or
were captured in Neptunian mean motion resonances (<10%). In addition, except
for those fragments located near strong resonances, the great majority
displayed negligible long-term orbital variation. This implies that the orbital
distribution of the intrinsic Haumean family can be used to constrain the
orbital conditions and physical nature of the collision that created the
family, billions of years ago. Indeed, our results suggest that the formation
of the Haumean collisional family most likely occurred after the bulk of
Neptune's migration was complete, or even some time after the migration had
completely ceased.
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Contrastive language-image Pre-training (CLIP) [13] can leverage large
datasets of unlabeled Image-Text pairs, which have demonstrated impressive
performance in various downstream tasks. Given that annotating medical data is
time-consuming and laborious, Image-Text Pre-training has promising
applications in exploiting large-scale medical image and radiology report
datasets. However, medical Image-Text Pre-training faces several challenges, as
follows: (1) Due to privacy concerns, the amount of available medical data is
relatively small compared to natural data, leading to weaker generalization
ability of the model. (2) Medical images are highly similar with only
fine-grained differences in subtleties, resulting in a large number of
false-negative sample pairs in comparison learning. (3) The hand-crafted Prompt
usually differs from the natural medical image report, Subtle changes in
wording can lead to significant differences in performance. In this paper, we
propose a unified Image-Text-Label contrastive learning framework based on
continuous prompts, with three main contributions. First, We unified the data
of images, text, and labels, which greatly expanded the training data that the
model could utilize. Second, we address the issue of data diversity and the
impact of hand-crafted prompts on model performance by introducing continuous
implicit prompts. Lastly, we propose a ImageText-Label contrastive Training to
mitigate the problem of too many false-negative samples. We demonstrate through
sufficient experiments that the Unified Medical Contrastive Learning (UMCL)
framework exhibits excellent performance on several downstream tasks.
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We consider three- and four-dimensional pseudo-Riemannian generalized
symmetric spaces, whose invariant metrics were explicitly described in [15].
While four-dimensional pseudo-Riemannian generalized symmetric spaces of types
A, C and D are algebraic Ricci solitons, the ones of type B are not so. The
Ricci soliton equation for their metrics yields a system of partial
differential equations. Solving such system, we prove that almost all the
four-dimensional pseudo-Riemannian generalized symmetric spaces of type B are
Ricci solitons. These examples show some deep differences arising for the Ricci
soliton equation between the Riemannian and the pseudo-Riemannian cases, as any
homogeneous Riemannian Ricci soliton is algebraic [21]. We also investigate
three-dimensional generalized symmetric spaces of any signature and prove that
they are Ricci solitons.
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We present optical, near-infrared, and radio observations of supernova (SN)
SN~IIb 2022crv. We show that it retained a very thin H envelope and
transitioned from a SN~IIb to a SN~Ib; prominent H$\alpha$ seen in the
pre-maximum phase diminishes toward the post-maximum phase, while He {\sc i}
lines show increasing strength. \texttt{SYNAPPS} modeling of the early spectra
of SN~2022crv suggests that the absorption feature at 6200\,\AA\ is explained
by a substantial contribution of H$\alpha$ together with Si {\sc ii}, as is
also supported by the velocity evolution of H$\alpha$. The light-curve
evolution is consistent with the canonical stripped-envelope supernova subclass
but among the slowest. The light curve lacks the initial cooling phase and
shows a bright main peak (peak M$_{V}$=$-$17.82$\pm$0.17 mag), mostly driven by
radioactive decay of $\rm^{56}$Ni. The light-curve analysis suggests a thin
outer H envelope ($M_{\rm env} \sim$0.05 M$_{\odot}$) and a compact progenitor
(R$_{\rm env}$ $\sim$3 R$_{\odot}$). An interaction-powered synchrotron
self-absorption (SSA) model can reproduce the radio light curves with a mean
shock velocity of 0.1c. The mass-loss rate is estimated to be in the range of
(1.9$-$2.8) $\times$ 10$^{-5}$ M$_{\odot}$ yr$^{-1}$ for an assumed wind
velocity of 1000 km s$^{-1}$, which is on the high end in comparison with other
compact SNe~IIb/Ib. SN~2022crv fills a previously unoccupied parameter space of
a very compact progenitor, representing a beautiful continuity between the
compact and extended progenitor scenario of SNe~IIb/Ib.
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We prove $L^{p}$-Caffarelli-Kohn-Nirenberg type inequalities on homogeneous
groups, which is one of most general subclasses of nilpotent Lie groups, all
with sharp constants. We also discuss some of their consequences. Already in
the abelian case of $\mathbb{R}^{n}$ our results provide new insights in view
of the arbitrariness of the choice of the not necessarily Euclidean quasi-norm.
|
Liquids flow, making them remarkably distinct from solids and close to gases.
At the same time, interactions in liquids are strong as in solids. The
combination of these two properties is believed to be the ultimate obstacle to
constructing a general theory of liquids. Here, we adopt a new approach to
liquids: instead of focusing on the problem of strong interactions, we zero in
on the relative contributions of vibrational and diffusional motion in liquids.
We subsequently show that from the point of view of thermodynamics, liquid
energy and specific heat are given, to a very good approximation, by their
vibrational contributions as in solids, for relaxation times spanning 15 orders
of magnitude. We therefore find that liquids show an interesting {\it duality}
not hitherto known: they are close to solids from the thermodynamical point of
view and to gases from the point of view of flow. We discuss the experimental
implications of this approach.
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A number of experiments for measuring anisotropies of the Cosmic Microwave
Background use scanning strategies in which temperature fluctuations are
measured along circular scans on the sky. It is possible, from a large number
of such intersecting circular scans, to build two-dimensional sky maps for
subsequent analysis. However, since instrumental effects --- especially the
excess low-frequency 1/f noise --- project onto such two-dimensional maps in a
non-trivial way, we discuss the analysis approach which focuses on information
contained in the individual circular scans. This natural way of looking at CMB
data from experiments scanning on the circles combines the advantages of
elegant simplicity of Fourier series for the computation of statistics useful
for constraining cosmological scenarios,and superior efficiency in analysing
and quantifying most of the crucial instrumental effects.
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Equilibrium statistical mechanics rests on the assumption of ergodic dynamics
of a system modulo the conservation laws of local observables: extremization of
entropy immediately gives Gibbs' ensemble (GE) for energy conserving systems
and a generalized version of it (GGE) when the number of local conserved
quantities (LCQ) is more than one. Through the last decade, statistical
mechanics has been extended to describe the late-time behaviour of periodically
driven (Floquet) quantum matter starting from a generic state. The structure
built on the fundamental assumptions of ergodicity and identification of the
relevant "conservation laws" in this inherently non-equilibrium setting. More
recently, it has been shown that the statistical mechanics has a much richer
structure due to the existence of {\it emergent} conservation laws: these are
approximate but stable conservation laws arising {\it due to the drive}, and
are not present in the undriven system. Extensive numerical and analytical
results support perpetual stability of these emergent (though approximate)
conservation laws, probably even in the thermodynamic limit. This banks on the
recent finding of a sharp ergodicity threshold for Floquet thermalization in
clean, interacting non-integrable Floquet systems. This opens up a new
possibility of stable Floquet engineering in such systems. This review intends
to give a theoretical overview of these developments. We conclude by briefly
surveying the experimental scenario.
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The preequilibrium (nucleon-in, nucleon-out) angular distributions of
$^{27}$Al, $^{58}$Ni and $^{90}$Zr have been analyzed in the energy region from
90 to 200 MeV in terms of the Quantum Moleculear Dynamics (QMD) theory. First,
we show that the present approach can reproduce the measured (p,xp') and (p,xn)
angular distributions leading to continuous final states without adjusing any
parameters. Second, we show the results of the detailed study of the
preequilibrium reaction processes; the step-wise contribution to the angular
distribution, comparison with the quantum-mechanical Feshbach-Kerman-Koonin
theory, the effects of momentum distribution and surface refraction/reflection
to the quasifree scattering. Finally, the present method was used to assess the
importance of multiple preequilibrium particle emission as a function of
projectile energy up to 1 GeV.
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Natural Language Processing research has recently been dominated by large
scale transformer models. Although they achieve state of the art on many
important language tasks, transformers often require expensive compute
resources, and days spanning to weeks to train. This is feasible for
researchers at big tech companies and leading research universities, but not
for scrappy start-up founders, students, and independent researchers. Stephen
Merity's SHA-RNN, a compact, hybrid attention-RNN model, is designed for
consumer-grade modeling as it requires significantly fewer parameters and less
training time to reach near state of the art results. We analyze Merity's model
here through an exploratory model analysis over several units of the
architecture considering both training time and overall quality in our
assessment. Ultimately, we combine these findings into a new architecture which
we call SHAQ: Single Headed Attention Quasi-recurrent Neural Network. With our
new architecture we achieved similar accuracy results as the SHA-RNN while
accomplishing a 4x speed boost in training.
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A hybrid hydropower power plant is a conventional HydroPower Plant (HPP)
augmented with a Battery Energy Storage System (BESS) to decrease the wear and
tear of sensitive mechanical components and improve the reliability and
regulation performance of the overall plant. A central task of controlling
hybrid power plants is determining how the total power set-point should be
split between the BESS and the hybridized unit (power set-point splitting) as a
function of the operational objectives. This paper describes a Model Predictive
Control (MPC) framework for hybrid medium- and high-head plants to determine
the power set-point of the hydropower unit and the BESS. The splitting policy
relies on an explicit formulation of the mechanical loads incurred by the HPP's
penstock, which can be damaged due to fatigue when providing regulation
services to the grid. By filtering out from the HPP's power set-point the
components conducive to excess penstock fatigue and properly controlling the
BESS, the proposed MPC is able to maintain the same level of regulation
performance while significantly decreasing damages to the hydraulic conduits. A
proof-of-concept by simulations is provided considering a 230 MW medium-head
hydropower plant.
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In video super-resolution, the spatio-temporal coherence between, and among
the frames must be exploited appropriately for accurate prediction of the high
resolution frames. Although 2D convolutional neural networks (CNNs) are
powerful in modelling images, 3D-CNNs are more suitable for spatio-temporal
feature extraction as they can preserve temporal information. To this end, we
propose an effective 3D-CNN for video super-resolution, called the 3DSRnet that
does not require motion alignment as preprocessing. Our 3DSRnet maintains the
temporal depth of spatio-temporal feature maps to maximally capture the
temporally nonlinear characteristics between low and high resolution frames,
and adopts residual learning in conjunction with the sub-pixel outputs. It
outperforms the most state-of-the-art method with average 0.45 and 0.36 dB
higher in PSNR for scales 3 and 4, respectively, in the Vidset4 benchmark. Our
3DSRnet first deals with the performance drop due to scene change, which is
important in practice but has not been previously considered.
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This paper deals with the problem of detecting fallen people lying on the
floor by means of a mobile robot equipped with a 3D depth sensor. In the
proposed algorithm, inspired by semantic segmentation techniques, the 3D scene
is over-segmented into small patches. Fallen people are then detected by means
of two SVM classifiers: the first one labels each patch, while the second one
captures the spatial relations between them. This novel approach showed to be
robust and fast. Indeed, thanks to the use of small patches, fallen people in
real cluttered scenes with objects side by side are correctly detected.
Moreover, the algorithm can be executed on a mobile robot fitted with a
standard laptop making it possible to exploit the 2D environmental map built by
the robot and the multiple points of view obtained during the robot navigation.
Additionally, this algorithm is robust to illumination changes since it does
not rely on RGB data but on depth data. All the methods have been thoroughly
validated on the IASLAB-RGBD Fallen Person Dataset, which is published online
as a further contribution. It consists of several static and dynamic sequences
with 15 different people and 2 different environments.
|
We prove upper and lower bounds for the number of eigenvalues of semi-bounded
Schr\"odinger operators in all spatial dimensions. As a corollary, we obtain
two-sided estimates for the sum of the negative eigenvalues of atomic
Hamiltonians with Kato potentials. Instead of being in terms of the potential
itself, as in the usual Lieb-Thirring result, the bounds are in terms of the
landscape function, also known as the torsion function, which is a solution of
$(-\Delta + V +M)u_M =1$ in $\mathbb{R}^d$; here $M\in\mathbb{R}$ is chosen so
that the operator is positive. We further prove that the infimum of $(u_M^{-1}
- M)$ is a lower bound for the ground state energy $E_0$ and derive a simple
iteration scheme converging to $E_0$.
|
In complex power systems, nonlinear load flow equations have multiple
solutions. Under typical load conditions only one solution is stable and
corresponds to a normal operating point, whereas the second solution is not
stable and is never realized in practice. However, in future distribution grids
with high penetration of distributed generators more stable solutions may
appear because of active or reactive power reversal. The systems can operate at
different states, and additional control measures may be required to ensure
that it remains at the appropriate point. This paper focuses on the analysis of
several cases where multiple solution phenomena is observed. A non-iterative
approach for solving load flow equations based on the Gr\"{o}bner basis is
introduced to overcome the convergence and computational efficiency associated
with standard iterative approaches. All the solutions of load flow problems
with their existence boundaries are analyzed for a simple 3-bus model.
Furthermore, the stability of the solutions is analyzed using a derived
aggregated load dynamics model, and suggestions for preventive control are
proposed and discussed. The failure of na\"{i}ve voltage stability criteria is
demonstrated and new voltage stability criteria is proposed. Some of the new
solutions of load flow equations are proved to be stable and/or acceptable to
the EN 50610 voltage fluctuation standard.
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This notebook paper presents our system in the ActivityNet Dense Captioning
in Video task (task 3). Temporal proposal generation and caption generation are
both important to the dense captioning task. Therefore, we propose a proposal
ranking model to employ a set of effective feature representations for proposal
generation, and ensemble a series of caption models enhanced with context
information to generate captions robustly on predicted proposals. Our approach
achieves the state-of-the-art performance on the dense video captioning task
with 8.529 METEOR score on the challenge testing set.
|
The spontaneous nucleation and dynamics of topological kink defects have been
studied in trapped arrays of 41-43 Yb ions. The number of kinks formed as a
function of quench rate across the linear-zigzag transition is measured in the
under-damped regime of the inhomogeneous Kibble-Zurek theory. The experimental
results agree well with molecular dynamics simulations, which show how losses
mask the intrinsic nucleation rate. Simulations indicate that doubling the ion
number and optimization of laser cooling can help reduce the effect of losses.
A range of kink dynamics is observed including configural change, motion and
lifetime, and behavioral sensitivity to ion number.
|
Supermassive black holes appear to be uniquely associated with galactic
bulges. The mean ratio of black hole mass to bulge mass was until recently very
uncertain, with ground based, stellar kinematical data giving a value roughly
an order of magnitude larger than other techniques. The discrepancy was
resolved with the discovery of the M-sigma relation, which simultaneously
established a tight corrrelation between black hole mass and bulge velocity
dispersion, and confirmed that the stellar kinematical mass estimates were
systematically too large due to failure to resolve the black hole's sphere of
influence. There is now excellent agreement between the various techniques for
estimating the mean black hole mass, including dynamical mass estimation in
quiescent galaxies; reverberation mapping in active galaxies and quasars; and
computation of the mean density of compact objects based on integrated quasar
light. Implications of the M-sigma relation for the formation of black holes
are discussed.
|
Bounding volumes are an established concept in computer graphics and vision
tasks but have seen little change since their early inception. In this work, we
study the use of neural networks as bounding volumes. Our key observation is
that bounding, which so far has primarily been considered a problem of
computational geometry, can be redefined as a problem of learning to classify
space into free or occupied. This learning-based approach is particularly
advantageous in high-dimensional spaces, such as animated scenes with complex
queries, where neural networks are known to excel. However, unlocking neural
bounding requires a twist: allowing -- but also limiting -- false positives,
while ensuring that the number of false negatives is strictly zero. We enable
such tight and conservative results using a dynamically-weighted asymmetric
loss function. Our results show that our neural bounding produces up to an
order of magnitude fewer false positives than traditional methods. In addition,
we propose an extension of our bounding method using early exits that
accelerates query speeds by 25%. We also demonstrate that our approach is
applicable to non-deep learning models that train within seconds. Our project
page is at: https://wenxin-liu.github.io/neural_bounding/.
|
Ontology-based query answering with existential rules is well understood and
implemented for positive queries, in particular conjunctive queries. The
situation changes drastically for queries with negation, where there is no
agreed-upon semantics or standard implementation. Stratification, as used for
Datalog, is not enough for existential rules, since the latter still admit
multiple universal models that can differ on negative queries. We therefore
propose universal core models as a basis for a meaningful (non-monotonic)
semantics for queries with negation. Since cores are hard to compute, we
identify syntactic descriptions of queries that can equivalently be answered
over other types of models. This leads to fragments of queries with negation
that can safely be evaluated by current chase implementations. We establish new
techniques to estimate how the core model differs from other universal models,
and we incorporate our findings into a new reasoning approach for existential
rules with negation.
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A large component of the building material concrete consists of aggregate
with varying particle sizes between 0.125 and 32 mm. Its actual size
distribution significantly affects the quality characteristics of the final
concrete in both, the fresh and hardened states. The usually unknown variations
in the size distribution of the aggregate particles, which can be large
especially when using recycled aggregate materials, are typically compensated
by an increased usage of cement which, however, has severe negative impacts on
economical and ecological aspects of the concrete production. In order to allow
a precise control of the target properties of the concrete, unknown variations
in the size distribution have to be quantified to enable a proper adaptation of
the concrete's mixture design in real time. To this end, this paper proposes a
deep learning based method for the determination of concrete aggregate grading
curves. In this context, we propose a network architecture applying multi-scale
feature extraction modules in order to handle the strongly diverse object sizes
of the particles. Furthermore, we propose and publish a novel dataset of
concrete aggregate used for the quantitative evaluation of our method.
|
We present the results of a 40 ks XMM-Newton observation centered on the
variable star V1818 Ori. Using a combination of the XMM-Newton and AllWISE
catalog data, we identify a group of about 31 young stellar objects around
V1818 Ori. This group is coincident with the eastern edge of the dust ring
surrounding Kappa Ori. Previously, we concluded that the young stellar objects
on the western side of ring were formed in an episode of star formation that
started 3-5 Myr ago, and are at a distance similar to that of kappa Ori
(250-280 pc) and in the foreground to the Orion A cloud. Here we use the
XMM-Newton observation to calculate X-ray fluxes and luminosities of the young
stars around V1818 Ori. We find that their X-ray luminosity function (XLF),
calculated for a distance of ~270 pc, matches the XLF of the YSOs west of Kappa
Ori. We rule out that this group of young stars is associated to Mon R2 as
assumed in the literature, but rather they are part of the same Kappa Ori's
ring stellar population.
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It is a known phenomenon that adversarial robustness comes at a cost to
natural accuracy. To improve this trade-off, this paper proposes an ensemble
approach that divides a complex robust-classification task into simpler
subtasks. Specifically, fractal divide derives multiple training sets from the
training data, and fractal aggregation combines inference outputs from multiple
classifiers that are trained on those sets. The resulting ensemble classifiers
have a unique property that ensures robustness for an input if certain
don't-care conditions are met. The new techniques are evaluated on MNIST and
Fashion-MNIST, with no adversarial training. The MNIST classifier has 99%
natural accuracy, 70% measured robustness and 36.9% provable robustness, within
L2 distance of 2. The Fashion-MNIST classifier has 90% natural accuracy, 54.5%
measured robustness and 28.2% provable robustness, within L2 distance of 1.5.
Both results are new state of the art, and we also present new state-of-the-art
binary results on challenging label-pairs.
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We aim to use the concept of sheaf to establish a link between certain
aspects of the set of positive integers numbers, a topic corresponding to the
elementary mathematics, and some fundamental ideas of contemporary mathematics.
We hope that this type of approach helps the school students to restate some
problems of elementary mathematics in an environment deeper and suitable for
its study.
|
EEG-based Emotion recognition holds significant promise for applications in
human-computer interaction, medicine, and neuroscience. While deep learning has
shown potential in this field, current approaches usually rely on large-scale
high-quality labeled datasets, limiting the performance of deep learning.
Self-supervised learning offers a solution by automatically generating labels,
but its inter-subject generalizability remains under-explored. For this reason,
our interest lies in offering a self-supervised learning paradigm with better
inter-subject generalizability. Inspired by recent efforts in combining
low-level and high-level tasks in deep learning, we propose a cascaded
self-supervised architecture for EEG emotion recognition. Then, we introduce a
low-level task, time-to-frequency reconstruction (TFR). This task leverages the
inherent time-frequency relationship in EEG signals. Our architecture
integrates it with the high-level contrastive learning modules, performing
self-supervised learning for EEG-based emotion recognition. Experiment on DEAP
and DREAMER datasets demonstrates superior performance of our method over
similar works. The outcome results also highlight the indispensability of the
TFR task and the robustness of our method to label scarcity, validating the
effectiveness of the proposed method.
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In the second magnetohydrodynamic (MHD) ballooning stable domain of a
high-beta tokamak plasma, the Schroedinger equation for ideal MHD shear Alfven
waves has discrete solutions corresponding to standing waves trapped between
pressure-gradient-induced potential wells. Our goal is to understand how these
so-called alpha-induced toroidal Alfven eigenmodes alpha-TAE are modified by
the effects of finite Larmor radii (FLR) and kinetic compression of thermal
ions in the limit of massless electrons. In the present paper, we neglect
kinetic compression in order to isolate and examine in detail the effect of FLR
terms. After a review of the physics of ideal MHD alpha-TAE, the effect of FLR
on the Schroedinger potential, eigenfunctions and eigenvalues are described
with the use of parameter scans. The results are used in a companion paper to
identify instabilities driven by wave-particle resonances in the second stable
domain.
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In the analysis of neutron scattering measurements of condensed matter
structure, it normally suffices to treat the incident and scattered neutron
beams as if composed of incoherent distributions of plane waves with
wavevectors of different magnitudes and directions which are taken to define an
instrumental resolution. However, despite the wide-ranging applicability of
this conventional treatment, there are cases in which the wave function of an
individual neutron in the beam must be described more accurately by a spatially
localized packet, in particular with respect to its transverse extent normal to
its mean direction of propagation. One such case involves the creation of
orbital angular momentum (OAM) states in a neutron via interaction with a
material device of a given size. It is shown in the work reported here that
there exist two distinct measures of coherence of special significance and
utility for describing neutron beams in scattering studies of materials in
general. One measure corresponds to the coherent superposition of basis
functions and their wavevectors which constitute each individual neutron packet
state function whereas the other measure can be associated with an incoherent
distribution of mean wavevectors of the individual neutron packets in a beam.
Both the distribution of the mean wavevectors of individual packets in the beam
as well as the wavevector components of the superposition of basis functions
within an individual packet can contribute to the conventional notion of
instrumental resolution. However, it is the transverse spatial extent of packet
wavefronts alone that determines the area within which a coherent scattering
process can occur in the first place. This picture is shown to be consistent
with standard quantum theory. It is also demonstrated that these two measures
of coherence can be distinguished from one another experimentally.
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We propose a dielectric structure which focuses the laser light well beyond
the diffraction limit and thus considerably enhances the exerted optical
trapping force upon dielectric nanoparticles. Although the structure supports a
Fabry-Perot resonance, it actually acts as a nanoantenna in that the role of
the resonance is to funnel the laser light into the structure. In comparison
with the lens illuminating the structure, the proposed structure offers roughly
a 10000-fold enhancement in the trapping force - part of this enhancement comes
from an 80-fold enhancement in the field intensity, and the remaining comes
from a 130-fold enhancement in the normalized gradient of the field intensity
(viz. the gradient of the field intensity divided by the field intensity).
Also, the proposed structure offers roughly a 100-fold enhancement in the depth
of the trapping potential. It is noteworthy that 'self-induced back-action
trapping' (SIBA), which has recently been the focus of interest in the context
of optical resonators, does not take place in the proposed resonator. In this
paper, we also point out some misconceptions about SIBA together with some
hitherto unappreciated subtleties of the dipole approximation.
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A trainable filter-based higher-order Markov Random Fields (MRFs) model - the
so called Fields of Experts (FoE), has proved a highly effective image prior
model for many classic image restoration problems. Generally, two options are
available to incorporate the learned FoE prior in the inference procedure: (1)
sampling-based minimum mean square error (MMSE) estimate, and (2) energy
minimization-based maximum a posteriori (MAP) estimate. This letter is devoted
to the FoE prior based single image super resolution (SR) problem, and we
suggest to make use of the MAP estimate for inference based on two facts: (I)
It is well-known that the MAP inference has a remarkable advantage of high
computational efficiency, while the sampling-based MMSE estimate is very time
consuming. (II) Practical SR experiment results demonstrate that the MAP
estimate works equally well compared to the MMSE estimate with exactly the same
FoE prior model. Moreover, it can lead to even further improvements by
incorporating our discriminatively trained FoE prior model. In summary, we hold
that for higher-order natural image prior based SR problem, it is better to
employ the MAP estimate for inference.
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The goal of this paper is the analytical validation of a model of Cermelli
and Gurtin for an evolution law for systems of screw dislocations under the
assumption of antiplane shear. The motion of the dislocations is restricted to
a discrete set of glide directions, which are properties of the material. The
evolution law is given by a "maximal dissipation criterion", leading to a
system of differential inclusions. Short time existence, uniqueness,
cross-slip, and fine cross-slip of solutions are proved.
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Displacement flows are common in hydraulic fracturing, as fracking fluids of
different composition are injected sequentially in the fracture. The injection
of an immiscible fluid at the center of a liquid-filled fracture results in the
growth of the fracture and the outward displacement of the interface between
the two liquids. We study the dynamics of the fluid-driven fracture which is
controlled by the competition between viscous, elastic, and toughness-related
stresses. We use a model experiment to characterize the dynamics of the
fracture for a range of mechanical properties of the fractured material and
fracturing fluids. We form the liquid-filled pre-fracture in an elastic brittle
matrix of gelatin. The displacing liquid is then injected. We record the radius
and aperture of the fracture, and the position of the interface between the two
liquids. In a typical experiment, the axisymmetric radial viscous flow is
accommodated by the elastic deformation and fracturing of the matrix. We model
the coupling between elastic deformation, viscous dissipation, and fracture
propagation and recover the two fracturing regimes identified for single fluid
injection. For the viscous-dominated and toughness-dominated regimes, we derive
scaling equations that describe the crack growth due to a displacement flow and
show the influence of the pre-existing fracture on the crack dynamics through a
finite initial volume and an average viscosity of the fluid in the fracture.
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Let $I\supsetneq J$ be two squarefree monomial ideals of a polynomial algebra
over a field generated in degree $\geq d$, resp. $\geq d+1$ . Suppose that $I$
is either generated by four squarefree monomials of degrees $d$ and others of
degrees $\geq d+1$, or by five special monomials of degrees $d$. If the Stanley
depth of $I/J$ is $\leq d+1$ then the usual depth of $I/J$ is $\leq d+1$ too.
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A generic qubit unitary operator affected by quantum noise is duplicated and
inserted in a coherently superposed channel, superposing two paths offered to a
probe qubit across the noisy unitary, and driven by a control qubit. A
characterization is performed of the transformation realized by the superposed
channel on the joint state of the probe-control qubit pair. The superposed
channel is then specifically analyzed for the fundamental metrological task of
phase estimation on the noisy unitary, with the performance assessed by the
Fisher information, classical or quantum. A comparison is made with
conventional estimation techniques and also with a quantum switched channel
with indefinite causal order recently investigated for a similar task of phase
estimation. In the analysis here, a first important observation is that the
control qubit of the superposed channel, although it never directly interacts
with the unitary being estimated, can nevertheless be measured alone for
effective estimation, while discarding the probe qubit that interacts with the
unitary. This property is also present with the switched channel but is
inaccessible with conventional techniques. The optimal measurement of the
control qubit here is characterized in general conditions. A second important
observation is that the noise plays an essential role in coupling the control
qubit to the unitary, and that the control qubit remains operative for phase
estimation at very strong noise, even with a fully depolarizing noise, whereas
conventional estimation and the switched channel become inoperative in these
conditions. The results extend the analysis of the capabilities of coherently
controlled channels which represent novel devices exploitable for quantum
signal and information processing.
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In the past decade quantum algorithms have been found which outperform the
best classical solutions known for certain classical problems as well as the
best classical methods known for simulation of certain quantum systems. This
suggests that they may also speed up the simulation of some classical systems.
I describe one class of discrete quantum algorithms which do so--quantum
lattice gas automata--and show how to implement them efficiently on standard
quantum computers.
|
Collisional relaxation rates of collective modes in nuclei are calculated
using the Levinson equation for the reduced density matrix with a memory
dependent collision term. Linearizing the collision integral two contribution
have to be distinguished, the one from the quasiparticle energy and the one
from occupation factors. The first one yields the known Landau formula of zero
sound damping and the second one leads to the Fermi gas model of Ref.1 with the
additional factor 3 in front of the frequencies. Adding both contribution we
obtain a final relaxation rate for the Fermi liquid model. Calculations of the
temperature dependence of the damping rates and of the shape evolution of IVGDR
are in good agreement with the experiment and show only minor differences
between both models.
|
The inclusive production of charged hadrons in the collisions of quasi-real
photons e+e- -> e+e- +X has been measured using the OPAL detector at LEP. The
data were taken at e+e- centre-of-mass energies from 183 to 209 GeV. The
differential cross-sections as a function of the transverse momentum and the
pseudorapidity of the hadrons are compared to theoretical calculations of up to
next-to-leading order (NLO) in the strong coupling constant alpha{s}. The data
are also compared to a measurement by the L3 Collaboration, in which a large
deviation from the NLO predictions is observed.
|
We adopt A. J. Irving's sieve method to study the almost-prime values
produced by products of irreducible polynomials evaluated at prime arguments.
This generalizes the previous results of Irving and Kao, who separately
examined the almost-prime values of a single irreducible polynomial evaluated
at prime arguments.
|
Measured acoustic data can be contaminated by noise. This typically happens
when microphones are mounted in a wind tunnel wall or on the fuselage of an
aircraft, where hydrodynamic pressure fluctuations of the Turbulent Boundary
Layer (TBL) can mask the acoustic pressures of interest. For measurements done
with an array of microphones, methods exist for denoising the acoustic data.
Use is made of the fact that the noise is usually concentrated in the diagonal
of the Cross-Spectral Matrix, because of the short spatial coherence of TBL
noise. This paper reviews several existing denoising methods and considers the
use of Conventional Beamforming, Source Power Integration and CLEAN-SC for this
purpose. A comparison between the methods is made using synthesized array data.
|
This letter addresses the constraint compatibility problem of control barrier
functions (CBFs), which occurs when a safety-critical CBF requires a system to
apply more control effort than it is capable of generating. This inevitably
leads to a safety violation, which transitions the system to an unsafe (and
possibly dangerous) trajectory. We resolve the constraint compatibility problem
by constructing a control barrier function that maximizes the feasible action
space for first and second-order constraints, and we prove that the optimal CBF
encodes a dynamical motion primitive. Furthermore, we show that this dynamical
motion primitive contains an implicit model for the future trajectory for
time-varying components of the system. We validate our optimal CBF in
simulation, and compare its behavior with a linear CBF.
|
We present an improved catalog of halo wide binaries, compiled from an
extensive literature search. Most of our binaries stem from the common proper
motion binary catalogs by Allen et al. (2004), and Chanam\'e \& Gould. (2004)
but we have also included binaries from the lists of Ryan (1992) and
Zapatero-Osorio \& Martin (2004). All binaries were carefully checked and their
distances and systemic radial velocities are included, when available. Probable
membership to the halo population was tested by means of reduced proper motion
diagrams for 251 candidate halo binaries. After eliminating obvious disk
binaries we ended up with 211 probable halo binaries, for 150 of which radial
velocities are available. We compute galactic orbits for these 150 binaries and
calculate the time they spend within the galactic disk. Considering the full
sample of 251 candidate halo binaries as well as several subsamples, we find
that the distribution of angular separations (or expected major semiaxes)
follows a power law $f(a) \sim a^{-1}$ (Oepik's relation) up to different
limits. For the 50 most disk-like binaries, those that spend their entire lives
within $z = \pm 500$~pc, this limit is found to be 19,000 AU (0.09 pc), while
for the 50 most halo-like binaries, those that spend on average only 18\% of
their lives within $z = \pm 500$~pc, the limit is 63,000 AU (0.31 pc). In a
companion paper we employ this catalog to establish limits on the masses of the
halo massive perturbers (MACHOs).
|
This paper provides a survey of the state-of-the-art information theoretic
analysis for overlay multi-user (more than two pairs) cognitive networks and
reports new capacity results. In an overlay scenario, cognitive / secondary
users share the same frequency band with licensed / primary users to
efficiently exploit the spectrum. They do so without degrading the performance
of the incumbent users, and may possibly even aid in transmitting their
messages as cognitive users are assumed to possess the message(s) of primary
user(s) and possibly other cognitive user(s). The survey begins with a short
overview of the two-user overlay cognitive interference channel. The evolution
from two-user to three-user overlay cognitive interference channels is
described next, followed by generalizations to multi-user (arbitrary number of
users) cognitive networks. The rest of the paper considers K-user cognitive
interference channels with different message knowledge structures at the
transmitters. Novel capacity inner and outer bounds are proposed. Channel
conditions under which the bounds meet, thus characterizing the information
theoretic capacity of the channel, for both Linear Deterministic and Gaussian
channel models, are derived. The results show that for certain channel
conditions distributed cognition, or having a cumulative message knowledge
structure at the nodes, may not be worth the overhead as (approximately) the
same capacity can be achieved by having only one global cognitive user whose
role is to manage all the interference in the network. The paper concludes with
future research directions.
|
We study non-equilibrium transport through a superconducting flat-band
lattice in a two-terminal setup with the Schwinger-Keldysh method. We find that
quasiparticle transport is suppressed and coherent pair transport dominates.
For superconducting leads, the AC supercurrent overcomes the DC current which
relies on multiple Andreev reflections. With normal-normal and
normal-superconducting leads, the Andreev reflection and normal currents
vanish. Flat band superconductivity is thus promising not only for high
critical temperatures but also for suppressing unwanted quasiparticle
processes.
|
Hot, Dust-Obscured Galaxies (Hot DOGs), selected from the WISE all sky
infrared survey, host some of the most powerful Active Galactic Nuclei (AGN)
known, and might represent an important stage in the evolution of galaxies.
Most known Hot DOGs are at $z> 1.5$, due in part to a strong bias against
identifying them at lower redshift related to the selection criteria. We
present a new selection method that identifies 153 Hot DOG candidates at $z\sim
1$, where they are significantly brighter and easier to study. We validate this
approach by measuring a redshift $z=1.009$, and an SED similar to higher
redshift Hot DOGs for one of these objects, WISE J1036+0449
($L_{\rm\,Bol}\simeq 8\times 10^{46}\rm\,erg\,s^{-1}$), using data from
Keck/LRIS and NIRSPEC, SDSS, and CSO. We find evidence of a broadened component
in MgII, which, if due to the gravitational potential of the supermassive black
hole, would imply a black hole mass of $M_{\rm\,BH}\simeq 2 \times 10^8
M_{\odot}$, and an Eddington ratio of $\lambda_{\rm\,Edd}\simeq 2.7$. WISE
J1036+0449 is the first Hot DOG detected by NuSTAR, and the observations show
that the source is heavily obscured, with a column density of
$N_{\rm\,H}\simeq(2-15)\times10^{23}\rm\,cm^{-2}$. The source has an intrinsic
2-10 keV luminosity of $\sim 6\times 10^{44}\rm\,erg\,s^{-1}$, a value
significantly lower than that expected from the mid-infrared/X-ray correlation.
We also find that the other Hot DOGs observed by X-ray facilities show a
similar deficiency of X-ray flux. We discuss the origin of the X-ray weakness
and the absorption properties of Hot DOGs. Hot DOGs at $z\lesssim1$ could be
excellent laboratories to probe the characteristics of the accretion flow and
of the X-ray emitting plasma at extreme values of the Eddington ratio.
|
Explosive phenomena are known to trigger a wealth of shocks in warm plasma
environments, including the solar chromosphere and molecular clouds where the
medium consists of both ionised and neutral species. Partial ionisation is
critical in determining the behaviour of shocks, since the ions and neutrals
locally decouple, allowing for substructure to exist within the shock.
Accurately modelling partially ionised shocks requires careful treatment of the
ionised and neutral species, and their interactions. Here we study a
partially-ionised switch-off slow-mode shock using a multi-level hydrogen model
with both collisional and radiative ionisation and recombination rates that are
implemented into the two-fluid (P\underline{I}P) code, and study physical
parameters that are typical of the solar chromosphere. The multi-level hydrogen
model differs significantly from MHD solutions due to the macroscopic thermal
energy loss during collisional ionisation. In particular, the plasma
temperature both post-shock and within the finite-width is significantly cooler
that the post-shock MHD temperature. Furthermore, in the mid to lower
chromosphere, shocks feature far greater compression then their single-fluid
MHD analogues. The decreased temperature and increased compression reveal the
importance of non-equilibrium ionised in the thermal evolution of shocks in
partially ionised media. Since partially ionised shocks are not accurately
described by the Rankine-Hugoniot shock jump conditions, it may be incorrect to
use these to infer properties of lower atmospheric shocks.
|
The modified algebraic Bethe ansatz, introduced by Cramp\'e and the author
[8], is used to characterize the spectral problem of the Heisenberg XXZ
spin-$\frac{1}{2}$ chain on the segment with lower and upper triangular
boundaries. The eigenvalues and the eigenvectors are conjectured. They are
characterized by a set of Bethe roots with cardinality equal to $N$ the length
of the chain and which satisfies a set of Bethe equations with an additional
term. The conjecture follows from exact results for small chains. We also
present a factorized formula for the Bethe vectors of the Heisenberg XXZ
spin-$\frac{1}{2}$ chain on the segment with two upper triangular boundaries.
|
We analyse semiclassical strings in AdS in the limit of one large spin. In
this limit, classical string dynamics is described by a finite number of
collective coordinates corresponding to spikes or cusps of the string. The
semiclassical spectrum consists of two branches of excitations corresponding to
"large" and "small" spikes respectively. We propose that these states are dual
to the excitations known as large and small holes in the spin chain description
of N=4 SUSY Yang-Mills. The dynamics of large spikes in classical string theory
can be mapped to that of a classical spin chain of fixed length. In turn, small
spikes correspond to classical solitons propagating on the background formed by
the large spikes. We derive the dispersion relation for these excitations
directly in the finite gap formalism.
|
We present spectral measurements made in the soft (20-100 keV) gamma-ray band
of the region containing the composite supernova remnant G11.2-0.3 and its
associated pulsar PSR J1811-1925. Analysis of INTEGRAL/IBIS data allows
characterisation of the system above 10 keV. The IBIS spectrum is best fitted
by a power law having photon index of 1.8^{+0.4}_{-0.3} and a 20-100 keV flux
of 1.5E{-11} erg/cm^2/s. Analysis of archival Chandra data over different
energy bands rules out the supernova shell as the site of the soft gamma-ray
emission while broad band (1-200 keV) spectral analysis strongly indicates that
the INTEGRAL/IBIS photons originate in the central zone of the system which
contains both the pulsar and its nebula. The composite X-ray and soft gamma-ray
spectrum indicates that the pulsar provides around half of the emission seen in
the soft gamma-ray domain; its spectrum is hard with no sign of a cut off up to
at least 80 keV. The other half of the emission above 10 keV comes from the
PWN; with a power law slope of 1.7 its spectrum is softer than that of the
pulsar. From the IBIS/ISGRI mosaics we are able to derive 2 sigma upper limits
for the 20-100 keV flux from the location of the nearby TeV source HESS
J1809-193 to be 4.8E{-12} erg/cm^2/s. We have also examined the likelihood of
an association between PSR J1811-1925 and HESS J1809-193. Although PSR
J1811-1925 is the most energetic pulsar in the region, the only one detected
above 10 keV and thus a possible source of energy to fuel the TeV fluxes, there
is no morphological evidence to support this pairing, making it an unlikely
counterpart.
|
A survey is performed of various Multi-Armed Bandit (MAB) strategies in order
to examine their performance in circumstances exhibiting non-stationary
stochastic reward functions in conjunction with delayed feedback. We run
several MAB simulations to simulate an online eCommerce platform for grocery
pick up, optimizing for product availability. In this work, we evaluate several
popular MAB strategies, such as $\epsilon$-greedy, UCB1, and Thompson Sampling.
We compare the respective performances of each MAB strategy in the context of
regret minimization. We run the analysis in the scenario where the reward
function is non-stationary. Furthermore, the process experiences delayed
feedback, where the reward function is not immediately responsive to the arm
played. We devise a new adaptive technique (AG1) tailored for non-stationary
reward functions in the delayed feedback scenario. The results of the
simulation show show superior performance in the context of regret minimization
compared to traditional MAB strategies.
|
We present a spectral rigidity result for the Dirac operator on lens spaces.
More specifically, we show that each homogeneous lens space and each three
dimensional lens space $L(q;p)$ with $q$ prime is completely characterized by
its Dirac spectrum in the class of all lens spaces.
|
This paper presents a new open source Python framework for causal discovery
from observational data and domain background knowledge, aimed at causal graph
and causal mechanism modeling. The 'cdt' package implements the end-to-end
approach, recovering the direct dependencies (the skeleton of the causal graph)
and the causal relationships between variables. It includes algorithms from the
'Bnlearn' and 'Pcalg' packages, together with algorithms for pairwise causal
discovery such as ANM. 'cdt' is available under the MIT License at
https://github.com/Diviyan-Kalainathan/CausalDiscoveryToolbox.
|
Attenuated Radon projections with respect to the weight function $W_\mu(x,y)
= (1-x^2-y^2)^{\mu-1/2}$ are shown to be closely related to the orthogonal
expansion in two variables with respect to $W_\mu$. This leads to an algorithm
for reconstructing two dimensional functions (images) from attenuated Radon
projections. Similar results are established for reconstructing functions on
the sphere from projections described by integrals over circles on the sphere,
and for reconstructing functions on the three-dimensional ball and cylinder
domains.
|
The opportunity to tell a white lie (i.e., a lie that benefits another
person) generates a moral conflict between two opposite moral dictates, one
pushing towards telling always the truth and the other pushing towards helping
others. Here we study how people resolve this moral conflict. What does telling
a white lie signal about a person's pro-social tendencies? To answer this
question, we conducted a two-stage 2x2 experiment. In the first stage, we used
a Deception Game to measure aversion to telling a Pareto white lie (i.e., a lie
that helps both the liar and the listener), and aversion to telling an
altruistic white lie (i.e., a lie that helps the listener at the expense of the
liar). In the second stage we measured altruistic tendencies using a Dictator
Game and cooperative tendencies using a Prisoner's dilemma. We found three
major results: (i) both altruism and cooperation are positively correlated with
aversion to telling a Pareto white lie; (ii) both altruism and cooperation are
negatively correlated with aversion to telling an altruistic white lie; (iii)
men are more likely than women to tell an altruistic white lie, but not to tell
a Pareto white lie. Our results shed light on the moral conflit between
pro-sociality and truth-telling. In particular, the first finding suggests that
a significant proportion of people have non-distributional notions of what the
right thing to do is: irrespective of their economic consequences, they tell
the truth, they cooperate, they share their money.
|
In this paper, we give two elementary constructions of homogeneous
quasi-morphisms defined on the group of Hamiltonian diffeomorphisms of certain
closed connected symplectic manifolds (or on its universal cover). The first
quasi-morphism, denoted by $\calabi\_{S}$, is defined on the group of
Hamiltonian diffeomorphisms of a closed oriented surface $S$ of genus greater
than 1. This construction is motivated by a question of M. Entov and L.
Polterovich. If $U\subset S$ is a disk or an annulus, the restriction of
$\calabi\_{S}$ to the subgroup of diffeomorphisms which are the time one map of
a Hamiltonian isotopy in $U$ equals Calabi's homomorphism. The second
quasi-morphism is defined on the universal cover of the group of Hamiltonian
diffeomorphisms of a symplectic manifold for which the cohomology class of the
symplectic form is a multiple of the first Chern class.
|
Inspired from perturbative calculations, this work introduces imaginary
($\Omega_{\rm I}$) and real ($\Omega$) rotation effects to the pure $SU(3)$
gauge potentials simply through variable transformations: The empirical
Polyakov loop (PL) potentials can be rewritten as functions of the imaginary
chemical potentials of gluons and ghosts $(q_{\rm ij})$, and the
transformations are taken as $q_{\rm ij}\rightarrow q_{\rm ij}\pm\Omega_{\rm
I}/T$ and $q_{\rm ij}\rightarrow q_{\rm ij}\pm i\,\Omega/T$, respectively. For
the PL potential of Fukushima $(V_1)$, a smaller imaginary rotation
$\Omega_{\rm I}$ tends to suppress PL at all temperature and the deconfinement
transition keeps of first order. However, for the PL potential of Munich group
$(V_2)$, $\Omega_{\rm I}$ tends to enhance PL at low temperature $T$,
consistent with lattice simulations; but suppress PL at high $T$, consistent
with perturbative calculations. Moreover, the deconfinement alters from first
order to crossover with increasing $\Omega_{\rm I}$ as is expected from lattice
simulations. On the other hand, the real rotation $\Omega$ tends to enhance PL
at relatively low $T$ for both potentials, and the (pseudo-)critical
temperature decreases with $\Omega$ as expected. Therefore, we find that
analytic continuation of the phase diagram from imaginary to real rotation is
not necessarily valid in the non-perturbative region. Finally, we apply the
more successful PL potential $V_2$ to the Polyakov--Nambu-Jona-Lasinio (PNJL)
model and discover that $\Omega_{\rm I}$ tends to break chiral symmetry while
$\Omega$ tends to restore it. Especially, the modified model is even able to
qualitatively explain the lattice result that a larger $T$ would catalyze
chiral symmetry breaking for a large $\Omega_{\rm I}$.
|
We derive an analytical expression for the growth rate of matter density
perturbations on the phantom brane (which is the normal branch of the
Dvali-Gabadadze-Porrati model). This model is characterized by a phantomlike
effective equation of state for dark energy at the present epoch. It agrees
very well with observations. We demonstrate that the traditional
parametrization $f=\Omega_m^\gamma$ with a quasiconstant growth index $\gamma$
is not successful in this case. Based on a power series expansion at large
redshifts, we propose a different parametrization for this model:
$f=\Omega_m^\gamma\left(1+\frac{b}{\ell H}\right)^\beta$, where $\beta$ and $b$
are constants. Our numerical simulations demonstrate that this new
parametrization describes the growth rate with great accuracy - the maximum
error being $\leq 0.1\%$ for parameter values consistent with observations.
|
In this work a new method is developed to investigate the Aharonov-Casher
effect in a noncommutative space. It is shown that the holonomy receives
non-trivial kinematical corrections.
|
We present results from the first simulations of networks of Type I Abelian
Higgs cosmic strings to include both matter and radiation eras and Cosmic
Microwave Background (CMB) constraints. In Type I strings, the string tension
is a slowly decreasing function of the ratio of the scalar and gauge
mass-squared, $\beta$. We find that the mean string separation shows no
dependence on $\beta$, and that the energy-momentum tensor correlators decrease
approximately in proportion to the square of the string tension, with
additional O(1) correction factors which asymptote to constants below $\beta
\lesssim 0.01$. Strings in models with low self-couplings can therefore satisfy
current CMB bounds at higher symmetry-breaking scales. This is particularly
relevant for models where the gauge symmetry is broken in a supersymmetric flat
direction, for which the effective self-coupling can be extremely small. If our
results can be extrapolated to $\beta \simeq 10^{-15}$, even strings formed at
$10^{16}$ GeV (approximately the grand unification scale in supersymmetric
extensions of the Standard Model) can be compatible with CMB constraints.
|
This paper is about the use of a novel, exact functional quantization method
as applied to two commonly studied actions in theoretical physics. The
functional method in question has its roots in the exact renormalisation group
flow techniques pioneered by Wilson, but with the flow parameter not limited to
the familiar momentum cutoff. Finding a configuration satisfying an expression
for the exact effective action which does not vary with this parameter provides
the basis for finding solutions to the physical actions we study. Firstly, the
method is applied to an expression for the bare action of the pseudo-scalar
axion used to explain the strong CP problem in QCD. When quantized, we find
that the effective potential of the axion, when interactions are not
considered, is necessarily flattened by spinodal instability effects. We regard
this flattening asrepresenting the very early stage in the development of the
axion potential, when the Peccei-Quinn U(1) symmetry is spontaneously broken
resulting in a double-well potential. Using commonly quoted values for the
parameters of such a potential, we devise an expression for the energy density
of the emerging axion potential and this is compared to dark energy. We then
apply the functional method to the bosonic string with time varying graviton,
dilaton and antisymmetric tensor (resulting in the string-axion) background
fields. We achieve a demonstration of conformal invariance in a
non-perturbative manner in the beta functions, contrasting with conventional
string cosmology where cancellation of a perturbative expansion is performed.
We then offer some hints as to possible cosmological implications of our
configuration in terms of optical anisotropy.
|
We consider a filtration $\mathbb{G}$ obtained as enlargement of a filtration
$\mathbb{F}$ by a filtration $\mathbb{H}$. We assume that all
$\mathbb{F}$-local martingales are represented by a martingale $M$ and all
$\mathbb{H}$-local martingales are represented by a martingale $N$. $M$ and $N$
are not necessarily quasi-left continuous processes and their jump times may
overlap. We first analyze the contribution of the accessible jump times of $M$
and $N$ to the Jacod's dimension of the space of the
$\mathcal{H}^1(\mathbb{G})$-martingales. Then we prove a new martingale
representation theorem on $\mathbb{G}$.
|
Inductive programming frequently relies on some form of search in order to
identify candidate solutions. However, the size of the search space limits the
use of inductive programming to the production of relatively small programs. If
we could somehow correctly predict the subset of instructions required for a
given problem then inductive programming would be more tractable. We will show
that this can be achieved in a high percentage of cases. This paper presents a
novel model of programming language instruction co-occurrence that was built to
support search space partitioning in the Zoea distributed inductive programming
system. This consists of a collection of intersecting instruction subsets
derived from a large sample of open source code. Using the approach different
parts of the search space can be explored in parallel. The number of subsets
required does not grow linearly with the quantity of code used to produce them
and a manageable number of subsets is sufficient to cover a high percentage of
unseen code. This approach also significantly reduces the overall size of the
search space - often by many orders of magnitude.
|
Early prediction of mortality and length of stay(LOS) of a patient is vital
for saving a patient's life and management of hospital resources. Availability
of electronic health records(EHR) makes a huge impact on the healthcare domain
and there has seen several works on predicting clinical problems. However, many
studies did not benefit from the clinical notes because of the sparse, and high
dimensional nature. In this work, we extract medical entities from clinical
notes and use them as additional features besides time-series features to
improve our predictions. We propose a convolution based multimodal
architecture, which not only learns effectively combining medical entities and
time-series ICU signals of patients, but also allows us to compare the effect
of different embedding techniques such as Word2vec, FastText on medical
entities. In the experiments, our proposed method robustly outperforms all
other baseline models including different multimodal architectures for all
clinical tasks. The code for the proposed method is available at
https://github.com/tanlab/ConvolutionMedicalNer.
|
One billion people live in informal settlements worldwide. The complex and
multilayered spaces that characterize this unplanned form of urbanization pose
a challenge to traditional approaches to mapping and morphological analysis.
This study proposes a methodology to study the morphological properties of
informal settlements based on terrestrial LiDAR (Light Detection and Ranging)
data collected in Rocinha, the largest favela in Rio de Janeiro, Brazil. Our
analysis operates at two resolutions, including a \emph{global} analysis
focused on comparing different streets of the favela to one another, and a
\emph{local} analysis unpacking the variation of morphological metrics within
streets. We show that our methodology reveals meaningful differences and
commonalities both in terms of the global morphological characteristics across
streets and their local distributions. Finally, we create morphological maps at
high spatial resolution from LiDAR data, which can inform urban planning
assessments of concerns related to crowding, structural safety, air quality,
and accessibility in the favela. The methods for this study are automated and
can be easily scaled to analyze entire informal settlements, leveraging the
increasing availability of inexpensive LiDAR scanners on portable devices such
as cellphones.
|
We present a preliminary measurement of CP-violating asymmetries in fully
reconstructed $B^0{\to}D^{(*)\pm}\pi^{\mp}$ and $\B^0{\to}D^{\pm}\rho^{\mp}$
decays in approximately 110 million $\Upsilon(\rm 4S) \to B\bar{B}$ decays
collected with the BaBar detector at the PEP-II asymmetric-energy $B$ factory
at SLAC. % From a maximum likelihood fit to the time-dependent decay
distributions we obtain for the CP-violating parameters: $a^{D\pi} =
-0.032\pm0.031 (\textrm{stat.})\pm 0.020 (\textrm{syst.}), c_{\rm lep}^{D\pi} =
-0.059\pm0.055 (\textrm{stat.})\pm 0.033 (\textrm{syst.})$ on the
$B^0{\to}D^{\pm}\pi^{\mp}$ sample, $a^{D^*\pi} = -0.049\pm0.031
(\textrm{stat.})\pm 0.020 (\textrm{syst.}), c_{\rm lep}^{D^*\pi} =
+0.044\pm0.054 (\textrm{stat.})\pm 0.033 (\textrm{syst.})$ on the
$B^0{\to}D^{*\pm}\pi^{\mp}$ sample, and $a^{D\rho} = -0.005\pm0.044
(\textrm{stat.})\pm 0.021 (\textrm{syst.}), c_{\rm lep}^{D\rho} =
-0.147\pm0.074 (\textrm{stat.})\pm 0.035 (\textrm{syst.})$ on the
$B^0{\to}D^{\pm}\rho^{\mp}$ sample.
|
This paper contains a proof of a conjecture of Braverman concerning Laumon
quasiflag spaces. We consider the generating function Z(m), whose coefficients
are the integrals of the equivariant Chern polynomial (with variable m) of the
tangent bundles of the Laumon spaces. We prove Braverman's conjecture, which
states that Z(m) coincides with the eigenfunction of the Calogero-Sutherland
hamiltonian, up to a simple factor which we specify. This conjecture was
inspired by the work of Nekrasov in the affine \hat{sl}_n setting, where a
similar conjecture is still open.
|
A new method for extracting neutron densities from intermediate energy
elastic proton-nucleus scattering observables uses a global Dirac
phenomenological (DP) approach based on the Relativistic Impulse Approximation
(RIA). Data sets for Ca40, Ca48 and Pb208 in the energy range from 500 MeV to
1040 MeV are considered. The global fits are successful in reproducing the data
and in predicting data sets not included in the analysis. Using this global
approach, energy independent neutron densities are obtained. The vector point
proton density distribution is determined from the empirical charge density
after unfolding the proton form factor. The other densities are parametrized.
This work provides energy independent values for the RMS neutron radius, R_n
and the neutron skin thickness, S_n, in contrast to the energy dependent values
obtained by previous studies. In addition, the results presented in paper show
that the expected rms neutron radius and skin thickness for Ca40 is accurately
reproduced. The values of R_n and S_n obtained from the global fits that we
consider to be the most reliable are given as follows: for Ca40 R_n is 3.314 >
R_n > 3.310 fm and S_n is -0.063 > S_n > -0.067 fm; for Ca48 R_n is 3.459 > R_n
> 3.413 fm and S_n is 0.102 > S_n > 0.056 fm; and for Pb208 R_n is 5.550 > R_n
> 5.522 and S_n is 0.111 > S_n > 0.083 fm. These values are in reasonable
agreement with nonrelativistic Skyrme Hartree-Fock models and with relativistic
Hartree-Bogoliubov models with density-dependent meson-nucleon couplings. The
results from the global fits for Ca48 and Pb208 are generally not in agreement
with the usual relativistic mean-field models.
|
The Special Affine Fourier Transformation or the SAFT generalizes a number of
well known unitary transformations as well as signal processing and optics
related mathematical operations. Shift-invariant spaces also play an important
role in sampling theory, multiresolution analysis, and many other areas of
signal and image processing. Shannon's sampling theorem, which is at the heart
of modern digital communications, is a special case of sampling in
shift-invariant spaces. Furthermore, it is well known that the Poisson
summation formula is equivalent to the sampling theorem and that the Zak
transform is closely connected to the sampling theorem and the Poisson
summation formula. These results have been known to hold in the Fourier
transform domain for decades and were recently shown to hold in the Fractional
Fourier transform domain by A. Bhandari and A. Zayed.
The main goal of this article is to show that these results also hold true in
the SAFT domain. We provide a short, self-contained proof of Shannon's theorem
for functions bandlimited in the SAFT domain and then show that sampling in the
SAFT domain is equivalent to orthogonal projection of functions onto a subspace
of bandlimited basis associated with the SAFT domain. This interpretation of
sampling leads to least-squares optimal sampling theorem. Furthermore, we show
that this approximation procedure is linked with convolution and semi-discrete
convolution operators that are associated with the SAFT domain. We conclude the
article with an application of fractional delay filtering of SAFT bandlimited
functions.
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With the emergence of new photonic and plasmonic materials with optimized
properties as well as advanced nanofabrication techniques, nanophotonic devices
are now capable of providing solutions to global challenges in energy
conversion, information technologies, chemical/biological sensing, space
exploration, quantum computing, and secure communication. Addressing grand
challenges poses inherently complex, multi-disciplinary problems with a
manifold of stringent constraints in conjunction with the required system's
performance. Conventional optimization techniques have long been utilized as
powerful tools to address multi-constrained design tasks. One example is
so-called topology optimization that has emerged as a highly successful
architect for the advanced design of non-intuitive photonic structures. Despite
many advantages, this technique requires substantial computational resources
and thus has very limited applicability to highly constrained optimization
problems within high-dimensions parametric space. In our approach, we merge the
topology optimization method with machine learning algorithms such as
adversarial autoencoders and show substantial improvement of the optimization
process by providing unparalleled control of the compact design space
representations. By enabling efficient, global optimization searches within
complex landscapes, the proposed compact hyperparametric representations could
become crucial for multi-constrained problems. The proposed approach could
enable a much broader scope of the optimal designs and data-driven materials
synthesis that goes beyond photonic and optoelectronic applications.
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We study the in-medium modification of the isovector pi N amplitude using a
non-linear representation of the sigma model but keeping the scalar degree of
freedom. We check that our result does not depend on the representation. We
discuss the connection with other approaches based on chiral perturbation
theory.
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We present novel convex-optimization-based solutions to the problem of blind
beamforming of constant modulus signals, and to the related problem of linearly
constrained blind beamforming of constant modulus signals. These solutions
ensure global optimality and are parameter free, namely, do not contain any
tuneable parameters and do not require any a-priori parameter settings. The
performance of these solutions, as demonstrated by simulated data, is superior
to existing methods.
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Without higher moment assumptions, this note establishes the decay of the
Kolmogorov distance in a central limit theorem for L\'evy processes. This
theorem can be viewed as a continuous-time extension of the classical random
walk result by Friedman, Katz and Koopmans.
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A new scheme for testing the nuclear matter (NM) equation of state (EoS) at
high densities using constraints from compact star (CS) phenomenology is
applied to neutron stars with a core of deconfined quark matter (QM). An
acceptable EoS shall not to be in conflict with the mass measurement of 2.1 +/-
0.2 solar mass (1 sigma level) for PSR J0751+1807 and the mass radius relation
deduced from the thermal emission of RX J1856-3754. Further constraints for the
state of matter in CS interiors come from temperature-age data for young,
nearby objects. The CS cooling theory shall agree not only with these data, but
also with the mass distribution inferred via population synthesis models as
well as with LogN-LogS data. The scheme is applied to a set of hybrid EsoS with
a phase transition to stiff, color superconducting QM which fulfills all above
constraints and is constrained otherwise from NM saturation properties and flow
data of heavy-ion collisions. We extrapolate our description to low
temperatures and draw conclusions for the QCD phase diagram to be explored in
heavy-ion collision experiments.
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The clusters of a distribution are often defined by the connected components
of a density level set. However, this definition depends on the user-specified
level. We address this issue by proposing a simple, generic algorithm, which
uses an almost arbitrary level set estimator to estimate the smallest level at
which there are more than one connected components. In the case where this
algorithm is fed with histogram-based level set estimates, we provide a finite
sample analysis, which is then used to show that the algorithm consistently
estimates both the smallest level and the corresponding connected components.
We further establish rates of convergence for the two estimation problems, and
last but not least, we present a simple, yet adaptive strategy for determining
the width-parameter of the involved density estimator in a data-depending way.
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A novel geomechanics concept is presented for studying the behavior of
geomaterials and structures by capturing the underlying dynamics as
realistically as possible for earthquake excitation applied in time domain.
Enormous amount of damages caused to infrastructures during recent earthquakes
in all over the world indicate that there is a considerable room for
improvement. Causes for extensive damages are generally attributed to poor soil
conditions at the region. It is interesting to note that all structures in a
region with poor soil condition do not suffer similar damages; in fact, some of
them remain damage-free. There are many reasons for this including inability to
model the soil-structural systems properly, predict the future design
earthquake time history at the site, model the dynamic amplification of
responses caused by the excitation, incorporate major sources of nonlinearity
and energy dissipation, and most importantly consider the presence of a
considerable amount of uncertainty at every phase of the evaluation process.
The most recent research trend is to capture complicated behavior by conducting
multiple deterministic analyses by taking advantage of current significantly
improved computational capability. By conducting few dozens of deterministic
analyses at very intelligently selected points, structures can be designed more
seismic load-tolerant. The performance based seismic design concept recently
introduced in the U.S. is showcased in this paper. The requirements in the
guidelines appear to be reasonable. The concept is expected to change the
current engineering design paradigm. The authors believe that the proposed
alternatives to the simulation and the basic random vibration concept.
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We present an effective-field-theory calculation of the effect of a
dimension-six operator involving the top quark on precision electroweak data
via a top-quark loop. We demonstrate the renormalizability, in the modern
sense, of the effective field theory. We use the oblique parameter U to bound
the coefficient of the operator, and compare with the bound derived from
top-quark decay.
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This article discusses open problems, implemented solutions, and future
research in the area of responsible AI in healthcare. In particular, we
illustrate two main research themes related to the work of two laboratories
within the Department of Informatics, Systems, and Communication at the
University of Milano-Bicocca. The problems addressed concern, in particular,
{uncertainty in medical data and machine advice}, and the problem of online
health information disorder.
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We present a new graph compressor that works by recursively detecting
repeated substructures and representing them through grammar rules. We show
that for a large number of graphs the compressor obtains smaller
representations than other approaches. Specific queries such as reachability
between two nodes or regular path queries can be evaluated in linear time (or
quadratic times, respectively), over the grammar, thus allowing speed-ups
proportional to the compression ratio.
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We define a random walk of a particle in $\mathbb{R}^3$ where the space is
rotating. The particle is not glued to the space and will collide with it at
random times, resulting in changes in its velocity and direction. After many
collisions, the random walk starts to have some asymptotic behaviors inherited
from the movement of space. The paper will find the limit movement of the
particle, and explain how the randomness of the random walk gives rise to the
particle asymptotic deterministic movement.
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In this paper, we propose a fuzzy adaptive loss function for enhancing deep
learning performance in classification tasks. Specifically, we redefine the
cross-entropy loss to effectively address class-level noise conditions,
including the challenging problem of class imbalance. Our approach introduces
aggregation operators, leveraging the power of fuzzy logic to improve
classification accuracy. The rationale behind our proposed method lies in the
iterative up-weighting of class-level components within the loss function,
focusing on those with larger errors. To achieve this, we employ the ordered
weighted average (OWA) operator and combine it with an adaptive scheme for
gradient-based learning. Through extensive experimentation, our method
outperforms other commonly used loss functions, such as the standard
cross-entropy or focal loss, across various binary and multiclass
classification tasks. Furthermore, we explore the influence of hyperparameters
associated with the OWA operators and present a default configuration that
performs well across different experimental settings.
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An implementation of coupled-cluster (CC) theory to treat atoms and molecules
in finite magnetic fields is presented. The main challenges stem from the
magnetic-field dependence in the Hamiltonian, or, more precisely, the
appearance of the angular momentum operator, due to which the wave function
becomes complex and which introduces a gauge-origin dependence. For this
reason, an implementation of a complex CC code is required together with the
use of gauge-including atomic orbitals to ensure gauge-origin independence.
Results of coupled-cluster singles--doubles--perturbative-triples (CCSD(T))
calculations are presented for atoms and molecules with a focus on the
dependence of correlation and binding energies on the magnetic field.
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Processes involving bottom quarks play a crucial role in the LHC
phenomenology, from flavour physics to Higgs characterisation and as a window
to new physics, appearing both as signals and irreducible background in BSM
searches. These processes can be described in QCD either in a 4-flavor or
5-flavor scheme. In the former, $b$ quarks appear only in the final state and
are considered massive. In 5-flavor schemes, calculations include $b$ quarks in
the initial state. Possibly large logarithms originating from the collinear
splitting of gluons into bottom pairs are resummed into the $b$ parton
distribution function (PDF). In this contribution, I describe a simple method
to assess the size of the logarithms in processes initiated by bottom quarks
and show how a substantial and justified agreement between calculations in the
two schemes can be achieved. As a consequence both calculations can be used in
different context. To conclude, an overview of the current studies aiming to
generalise the current appraisal is given and some preliminary results are
discussed.
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Monolayer FeSe films grown on SrTiO3 (STO) substrate show superconducting
gap-opening temperatures (Tc) which are almost an order of magnitude higher
than those of the bulk FeSe and are highest among all known Fe-based
superconductors. Angle-resolved photoemission spectroscopy (ARPES) observed
"replica bands" suggesting the importance of the interaction between FeSe
electrons and STO phonons. These facts rejuvenated the quest for Tc enhancement
mechanisms in iron-based, especially iron-chalcogenide, superconductors. Here,
we perform the first numerically-exact sign-problem-free quantum Monte Carlo
simulations to iron-based superconductors. We (i) study the electronic pairing
mechanism intrinsic to heavily electron doped FeSe films, and (ii) examine the
effects of electron-phonon interaction between FeSe and STO as well as nematic
fluctuations on Tc. Armed with these results, we return to the question "what
makes the Tc of monolayer FeSe on SrTiO3 so high?" in the conclusion and
discussions.
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In the article we give some estimations of the {\L}ojasiewicz exponent of
nondegenerate surface singularities in terms of their Newton diagrams. We also
give an exact formula for the {\L}ojasiewicz exponent of such singularities in
some special cases. The results are stronger than Fukui inequality [8]. It is
also a multidimensional generalization of the Lenarcik theorem [13].
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The problem of front propagation in a stirred medium is addressed in the case
of cellular flows in three different regimes: slow reaction, fast reaction and
geometrical optics limit. It is well known that a consequence of stirring is
the enhancement of front speed with respect to the non-stirred case. By means
of numerical simulations and theoretical arguments we describe the behavior of
front speed as a function of the stirring intensity, $U$. For slow reaction,
the front propagates with a speed proportional to $U^{1/4}$, conversely for
fast reaction the front speed is proportional to $U^{3/4}$. In the geometrical
optics limit, the front speed asymptotically behaves as $U/\ln U$.
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UHE neutrinos may transfer highest cosmic-rays energies overcoming
$2.75K^\circ$ BBR and radio-waves opacities (the GZK cut off) from most distant
AGN sources at the age of the Universe. These UHE $\nu$ might scatter onto
those (light and cosmological) relic neutrinos clustered around our galactic
halo or nearby neutrino hot dark halo clustered around the AGN blazar and its
jets. The branched chain reactions from a primordial nucleon (via photo
production of pions and decay to UHE neutrinos) toward the consequent beam dump
scattering on galactic relic neutrinos is at least three order of magnitude
more efficient than any known neutrino interactions with Earth atmosphere or
direct nucleon propagation. Therefore the rarest cosmic rays (as the 320 EeV
event) might be originated at far $(\tilde{>} 100 Mpc)$ distances (as Seyfert
galaxy MCG 8-11-11); its corresponding UHE radiation power is in agreement with
the observed one in MeV gamma energies. The final chain products observed on
Earth by the Fly's Eye and AGASA detectors might be mainly neutron and
anti-neutrons and delayed, protons and anti-protons at symmetric off-axis
angles. These hadronic products are most probably secondaries of $W^+ W^-$ or
$ZZ$ pair productions and might be consistent with the last AGASA discoveries
of doublets and one triplet event.
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Quantum metamaterials generalize the concept of metamaterials (artificial
optical media) to the case when their optical properties are determined by the
interplay of quantum effects in the constituent 'artificial atoms' with the
electromagnetic field modes in the system. The theoretical investigation of
these structures demonstrated that a number of new effects (such as quantum
birefringence, strongly nonclassical states of light, etc) are to be expected,
prompting the efforts on their fabrication and experimental investigation. Here
we provide a summary of the principal features of quantum metamaterials and
review the current state of research in this quickly developing field, which
bridges quantum optics, quantum condensed matter theory and quantum information
processing.
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We classify all possible allowed constitutive relations of relativistic
fluids in a statistical mechanical limit using the Schwinger-Keldysh effective
action for hydrodynamics. We find that microscopic unitarity enforces genuinely
new constraints on the allowed transport coefficients that are invisible in the
classical hydrodynamic description; they are not implied by the second law or
the Onsager relations. We term these conditions Schwinger-Keldysh positivity
and provide explicit examples of the various allowed terms.
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Momentum-based acceleration of stochastic gradient descent (SGD) is widely
used in deep learning. We propose the quasi-hyperbolic momentum algorithm (QHM)
as an extremely simple alteration of momentum SGD, averaging a plain SGD step
with a momentum step. We describe numerous connections to and identities with
other algorithms, and we characterize the set of two-state optimization
algorithms that QHM can recover. Finally, we propose a QH variant of Adam
called QHAdam, and we empirically demonstrate that our algorithms lead to
significantly improved training in a variety of settings, including a new
state-of-the-art result on WMT16 EN-DE. We hope that these empirical results,
combined with the conceptual and practical simplicity of QHM and QHAdam, will
spur interest from both practitioners and researchers. Code is immediately
available.
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We present a numerical method to approximate the long-time asymptotic
solution $\rho_\infty(t)$ to the Lindblad master equation for an open quantum
system under the influence of an external drive. The proposed scheme uses
perturbation theory to rank individual drive terms according to their dynamical
relevance, and adaptively determines an effective Hamiltonian. In the
constructed rotating frame, $\rho_\infty$ is approximated by a
time-independent, nonequilibrium steady-state. This steady-state can be
computed with much better numerical efficiency than asymptotic long-time
evolution of the system in the lab frame. We illustrate the use of this method
by simulating recent transmission measurements of the heavy-fluxonium device,
for which ordinary time-dependent simulations are severely challenging due to
the presence of metastable states with lifetimes of the order of milliseconds.
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In this article, we study the transport properties of
Graphene-Superconductor-Graphene (GSG) heterojunction where the superconducting
region is created in the middle of a graphene sheet, as contrasted to widely
studied transport properties through a Superconductor-Graphene-Superconductor
(SGS) type of Josephson junction. We particularly analyse in detail the
Goos-H\"anchen shift of the electron and the hole at the GS interface in such a
junction, due to normal as well as Andreev reflection, using a transfer
matrix-based approach. Additionally, we evaluate the normalised differential
conductance as a function of bias voltage that characterises the transport
through such junction and point out how they are influenced by Andreev and
normal reflection. In the subsequent parts of the article we demonstrate how
the GH shift for both electron and hole changes with the width of the
superconducting region. The behavior of the differential conductance in such
junctions as a function of the bias voltage in the region, dominated by Andreev
and normal reflection, is also presented and analysed.
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We present an analytical and numerical study of the orbital migration and
resonance capture of fictitious two-planet systems with masses in the
super-Earth range undergoing Type-I migration. We find that, depending on the
flare index and proximity to the central star, the average value of the period
ratio, $P_2/P_1$, between both planets may show a significant deviation with
respect to the nominal value. For planets trapped in the 2:1 commensurability,
offsets may reach values on the order of $0.1$ for orbital periods on the order
of $1$ day, while systems in the 3:2 mean-motion resonance (MMR) show much
smaller offsets for all values of the semimajor axis. These properties are in
good agreement with the observed distribution of near-resonant exoplanets,
independent of their detection method. We show that 2:1-resonant systems far
from the star, such as HD82943 and HR8799, are characterized by very small
resonant offsets, while higher values are typical of systems discovered by
Kepler with orbital periods approximately a few days. Conversely, planetary
systems in the vicinity of the 3:2 MMR show little offset with no significant
dependence on the orbital distance. In conclusion, our results indicate that
the distribution of Kepler planetary systems around the 2:1 and 3:2 MMR are
consistent with resonant configurations obtained as a consequence of a smooth
migration in a laminar flared disk, and no external forces are required to
induce the observed offset or its dependence with the commensurability or
orbital distance from the star.
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The gas giant HD 80606 b has a highly eccentric orbit (e $\sim$ 0.93). The
variation due to the rapid shift of stellar irradiation provides a unique
opportunity to probe the physical and chemical timescales and to study the
interplay between climate dynamics and atmospheric chemistry. In this work, we
present integrated models to study the atmospheric responses and the underlying
physical and chemical mechanisms of HD 80606 b. We first run three-dimensional
general circulation models (GCMs) to establish the atmospheric thermal and
dynamical structures for different atmospheric metallicities and internal heat.
Based on the GCM output, we then adopted a 1D time-dependent photochemical
model to investigate the compositional variation along the eccentric orbit. The
transition of the circulation patterns of HD 80606 b matched the dynamics
regimes in previous works. Our photochemical models show that efficient
vertical mixing leads to deep quench levels of the major carbon and nitrogen
species and the quenching behavior does not change throughout the eccentric
orbit. Instead, photolysis is the main driver of the time-dependent chemistry.
While CH$_4$ dominates over CO through most of the orbits, a transient state of
[CO]/[CH$_4$}] $>$ 1 after periastron is confirmed for all metallicity and
internal heat cases. The upcoming JWST Cycle 1 GO program will be able to track
this real-time CH$_4$--CO conversion and infer the chemical timescale.
Furthermore, sulfur species initiated by sudden heating and photochemical
forcing exhibit both short-term and long-term cycles, opening an interesting
avenue for detecting sulfur on exoplanets.
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We study the S=1 Heisenberg antiferromagnet on a spatially anisotropic
triangular lattice by the numerical diagonalization method. We examine the
stability of the long-range order of a three-sublattice structure observed in
the isotropic system between the isotropic case and the case of isolated
one-dimensional chains. It is found that the long-range-ordered ground state
with this structure exists in the range of 0.7 \simle J_2/J_1 \le 1, where J_1
is the interaction amplitude along the chains and J_2 is the amplitude of other
interactions.
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With the tremendous success of deep learning, there exists imminent need to
deploy deep learning models onto edge devices. To tackle the limited computing
and storage resources in edge devices, model compression techniques have been
widely used to trim deep neural network (DNN) models for on-device inference
execution. This paper targets the commonly used FPGA (field programmable gate
array) devices as the hardware platforms for DNN edge computing. We focus on
the DNN quantization as the main model compression technique, since DNN
quantization has been of great importance for the implementations of DNN models
on the hardware platforms. The novelty of this work comes in twofold: (i) We
propose a mixed-scheme DNN quantization method that incorporates both the
linear and non-linear number systems for quantization, with the aim to boost
the utilization of the heterogeneous computing resources, i.e., LUTs (look up
tables) and DSPs (digital signal processors) on an FPGA. Note that all the
existing (single-scheme) quantization methods can only utilize one type of
resources (either LUTs or DSPs for the MAC (multiply-accumulate) operations in
deep learning computations. (ii) We use a quantization method that supports
multiple precisions along the intra-layer dimension, while the existing
quantization methods apply multi-precision quantization along the inter-layer
dimension. The intra-layer multi-precision method can uniform the hardware
configurations for different layers to reduce computation overhead and at the
same time preserve the model accuracy as the inter-layer approach.
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The MEPED instruments on board the NOAA POES andMetOp satellites have been
continuously measuring energetic particles in the magnetosphere since 1978.
However, degradation of the proton detectors over time leads to an increase in
the energy thresholds of the instrument and imposes great challenges to studies
of long-term variability in the near-Earth space environment as well as a
general quantification of the proton fluxes. By comparing monthly mean
accumulated integral flux from a new and an old satellite at the same magnetic
local time (MLT) and time period, we estimate the change in energy thresholds.
The first 12 monthly energy spectra of the new satellite are used as a
reference, and the derived monthly correction factors over a year for an old
satellite show a small spread, indicating a robust calibration procedure. The
method enables us to determine for the first time the correction factors also
for the highest-energy channels of the proton detector. In addition, we make
use of the newest satellite in orbit (MetOp-01) to find correction factors for
2013 for the NOAA 17 and MetOp-02 satellites. Without taking into account the
level of degradation, the proton data from one satellite cannot be used
quantitatively for more than 2 to 3 years after launch. As the electron
detectors are vulnerable to contamination from energetic protons, the corrected
proton measurements will be of value for electron flux measurements too. Thus,
the correction factors ensure the correctness of both the proton and electron
measurements.
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Many image enhancement or editing operations, such as forward and inverse
tone mapping or color grading, do not have a unique solution, but instead a
range of solutions, each representing a different style. Despite this, existing
learning-based methods attempt to learn a unique mapping, disregarding this
style. In this work, we show that information about the style can be distilled
from collections of image pairs and encoded into a 2- or 3-dimensional vector.
This gives us not only an efficient representation but also an interpretable
latent space for editing the image style. We represent the global color mapping
between a pair of images as a custom normalizing flow, conditioned on a
polynomial basis of the pixel color. We show that such a network is more
effective than PCA or VAE at encoding image style in low-dimensional space and
lets us obtain an accuracy close to 40 dB, which is about 7-10 dB improvement
over the state-of-the-art methods.
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CDW/Normal metal/CDW junctions and nanoconstrictions in crystals of the
quasi-one-dimensional conductor NbSe$_3$ are manufactured using a
focused-ion-beam. It is found that the low-temperature conduction of these
structures changes dramatically and loses the features of the
charge-density-wave transition. Instead, a dielectric phase is developed. Up to
6-order power-law variations of the conduction as a function of both
temperature and electric field can be observed for this new phase. The
transition from quasi-one-dimensional behavior to one-dimensional behavior is
associated with destruction of the three-dimensional order of the
charge-density waves by fluctuations. It results in a recovery of the
Luttinger-liquid properties of metallic chains, like it takes place in sliding
Luttinger liquid phase.
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Network theory is rapidly changing our understanding of complex systems, but
the relevance of topological features for the dynamic behavior of metabolic
networks, food webs, production systems, information networks, or cascade
failures of power grids remains to be explored. Based on a simple model of
supply networks, we offer an interpretation of instabilities and oscillations
observed in biological, ecological, economic, and engineering systems. We find
that most supply networks display damped oscillations, even when their units -
and linear chains of these units - behave in a non-oscillatory way. Moreover,
networks of damped oscillators tend to produce growing oscillations. This
surprising behavior offers, for example, a new interpretation of business
cycles and of oscillating or pulsating processes. The network structure of
material flows itself turns out to be a source of instability, and cyclical
variations are an inherent feature of decentralized adjustments.
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By employing Hopf's functional method, we find the exact characteristic
functional for a simple nonlinear dynamical system introduced by Orszag.
Steady-state equal-time statistics thus obtained are compared to direct
numerical simulation. The solution is both non-trivial and strongly
non-Gaussian.
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We show how to derive exact boundary $S$ matrices for integrable quantum
field theories in 1+1 dimensions using lattice regularization. We do this
calculation explicitly for the sine-Gordon model with fixed boundary conditions
using the Bethe ansatz for an XXZ-type spin chain in a boundary magnetic field.
Our results agree with recent conjectures of Ghoshal and Zamolodchikov, and
indicate that the only solutions to the Bethe equations which contribute to the
scaling limit are the standard strings.
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One-flip stable configurations of an Ising-model on a random graph with
fluctuating connectivity are examined. In order to perform the quenched average
of the number of stable configurations we introduce a global order-parameter
function with two arguments. The analytical results are compared with numerical
simulations.
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