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Edge termination plays a vital role in determining the properties of 2D
materials. By performing compelling ab initio simulations, a lowest-energy
U-edge [ZZ(U)] reconstruction is revealed in the bilayer phosphorene. Such
reconstruction reduces 60% edge energy compared with the pristine one and
occurs almost without energy barrier, implying it should be the dominating edge
in reality. The electronic band structure of phosphorene nanoribbon with such
reconstruction resembles that of intrinsic 2D layer, exhibiting nearly edgeless
band characteristics. Although ZZ(U) changes the topology of phosphorene
nanoribbon (PNR), simulated TEM, STEM and STM images indicates it is very hard
to be identified. One possible identify method is IR/Raman analyses because
ZZ(U) edge alters vibrational modes dramatically. Beyond, it also increases the
thermal conductivity of PNR 1.4 and 2.3 times than the pristine and Klein
edges.
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Hegyv\'ari and Hennecart showed that if $B$ is a sufficiently large brick of
a Heisenberg group, then the product set $B\cdot B$ contains many cosets of the
center of the group. We give a new, robust proof of this theorem that extends
to all extra special groups as well as to a large family of quasigroups.
|
In this article, we propose a bivariate polynomial interpolation problem for
matrices (BVPIPM), for real matrices of the order $m\times n$. In the process
of solving the proposed problem, we establish the existence of a class of
$mn$-dimensional bivariate polynomial subspaces (BVPS) in which the BVPIPM
always posses a unique solution. Two formulas are presented to construct the
respective polynomial maps from the space of real matrices of the order
$m\times n$ to two of the particular established BVPS, which satisfy the
BVPIPM, by introducing an approach of bivariate polynomial interpolation.
Further, we prove that these polynomial maps are isomorphisms. Some numerical
examples are also provided to validate and show the applicability of our
theoretical findings.
|
We report on the magnetic and superconducting properties of LaO0.5F0.5BiS2 by
means of zero- (ZF) and transverse-field (TF) muon-spin spectroscopy
measurements (uSR). Contrary to previous results on iron-based superconductors,
measurements in zero field demonstrate the absence of magnetically ordered
phases. TF-uSR data give access to the superfluid density, which shows a marked
2D character with a dominant s-wave temperature behavior. The field dependence
of the magnetic penetration depth confirms this finding and further suggests
the presence of an anisotropic superconducting gap.
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In this paper, we present some of the most prominent realizations of the HBD
concept in real experiments. We describe the first implementation of an HBD
that was made in the CERES experiment at CERN using a spectrometer based on a
doublet of hadron blind RICH detectors for the measurement of low-mass electron
pairs in pA and AA collisions at the SPS. We next present a detailed account of
a more extensive realization of the HBD that was made in the PHENIX experiment
for the measurement of low-mass electron pairs in central heavy-ion collisions
at RHIC, followed by a description of a very similar detector that is currently
under construction at J-PARC for the measurement of vector mesons though their
$e^+e^-$ decay in pA collisions. We conclude with a brief discussion of
possible evolutions of the HBD concept as well as possible developments and
uses of HBDs in experiments at the future Electron Ion Collider.
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Composite hadronic states exhibit interesting properties in the presence of
very intense magnetic fields, such as those conjectured to exist in the
vicinity of certain astrophysical objects. We discuss three scenarios. (i) The
presence of vector particles with anomalous magnetic moment couplings to scalar
particles, induces an instability of the vacuum. (ii) A delicate interplay
between the anomalous magnetic moments of the proton and neutron makes, in
magnetic fields $B\ge 2\times 10^{14}$ T, the neutron stable and for fields
$B\ge 5\times 10^{14}$ T the proton becomes unstable to a decay into a neutron
via $\beta$ emission. (iii) In the unbroken chiral $\sigma$ model magnetic
fields would be screened out as in a superconductor. It is the explicit
breaking of chiral invariance that restores standard electrodynamics.
Astrophysical consequences of all these phenomena are discussed.
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In the framework of a flat Friedmann-Lema{\^\i}tre-Robertson-Walker (FLRW)
geometry, we present a nonsingular model (no big bang singularity at finite
time) of our universe describing its evolution starting from its early
inflationary era up to the present accelerating phase. We found that a
hydrodynamical fluid with nonlinear equation of state could result in such a
non singular scenario, which after the end of this inflationary stage, suffers
a sudden phase transition and enters into the stiff matter dominated era, and
the universe becomes reheated due to a huge amount of particle production.
Finally, it asymptotically enters into the de Sitter phase concluding the
present accelerated expansion. We show that the background providing an
inflationary potential leads to a power spectrum of the cosmological
perturbations which fit well with the latest Planck estimations. At the end, we
compared our viable potential with some known inflationary quintessential
potentials, which shows that, our model is an improved version of them because
it contains an analytic solution that allows us to perform analytic
calculations.
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In the present paper we construct plans orthogonal through the block factor
(POTBs). We describe procedures for adding blocks as well as factors to an
initial plan and thus generate a bigger plan. Using these procedures we
construct POTBs for symmetrical experiments with factors having three or more
levels. We also construct a series of plans inter-class orthogonal through the
block factor for two-level factors.
|
OAuth 2.0 is a popular authorization framework that allows third-party
clients such as websites and mobile apps to request limited access to a user's
account on another application. The specification classifies clients into
different types based on their ability to keep client credentials confidential.
It also describes different grant types for obtaining access to the protected
resources, with the authorization code and implicit grants being the most
commonly used. Each client type and associated grant type have their unique
security and usability considerations. In this paper, we propose a new approach
for OAuth ecosystem that combines different client and grant types into a
unified singular protocol flow for OAuth (USPFO), which can be used by both
confidential and public clients. This approach aims to reduce the
vulnerabilities associated with implementing and configuring different client
types and grant types. Additionally, it provides built-in protections against
known OAuth 2.0 vulnerabilities such as client impersonation, token (or code)
thefts and replay attacks through integrity, authenticity, and audience
binding. The proposed USPFO is largely compatible with existing Internet
Engineering Task Force (IETF) Proposed Standard Request for Comments (RFCs),
OAuth 2.0 extensions and active internet drafts.
|
This paper is devoted to the question, whether there is an order barrier
$p\leq2$ for time integration in computational elasto-plasticity. In the
analysis we use an implicit Runge-Kutta (RK) method of order $p=3$ for
integrating the evolution equations of plastic flow within a nonlinear finite
element framework. We show that two novel algorithmic conditions are necessary
to overcome the order barrier, (i) total strains must have the same order in
time as the time integrator itself, (ii) accurate initial data must be
calculated via detecting the elastic-plastic switching point (SP) in the
predictor step. Condition (i) is for a \emph{consistent} coupling of the global
boundary value problem (BVP) with the local initial value problems (IVP) via
displacements/strains. Condition (ii) generates consistent initial data of the
IVPs. The third condition, which is not algorithmic but physical in nature, is
that (iii) the total strain path in time must be smooth such that condition (i)
can be fulfilled at all. This requirement is met by materials showing a
sufficiently smooth elastic-plastic transition in the stress-strain curve. We
propose effective means to fulfil conditions (i) and (ii). We show in finite
element simulations that, if condition (iii) is additionally met, the present
method yields the full, theoretical convergence order 3 thus overcoming the
barrier $p\leq 2$ for the first time. The observed speed-up for a 3rd order RK
method is considerable compared with Backward Euler.
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Classical learning assumes the learner is given a labeled data sample, from
which it learns a model. The field of Active Learning deals with the situation
where the learner begins not with a training sample, but instead with resources
that it can use to obtain information to help identify the optimal model. To
better understand this task, this paper presents and analyses the simplified
"(budgeted) active model selection" version, which captures the pure
exploration aspect of many active learning problems in a clean and simple
problem formulation. Here the learner can use a fixed budget of "model probes"
(where each probe evaluates the specified model on a random indistinguishable
instance) to identify which of a given set of possible models has the highest
expected accuracy. Our goal is a policy that sequentially determines which
model to probe next, based on the information observed so far. We present a
formal description of this task, and show that it is NPhard in general. We then
investigate a number of algorithms for this task, including several existing
ones (eg, "Round-Robin", "Interval Estimation", "Gittins") as well as some
novel ones (e.g., "Biased-Robin"), describing first their approximation
properties and then their empirical performance on various problem instances.
We observe empirically that the simple biased-robin algorithm significantly
outperforms the other algorithms in the case of identical costs and priors.
|
Context: The star cluster R136 inside the LMC hosts a rich population of
massive stars, including the most massive stars known. The strong stellar winds
of these very luminous stars impact their evolution and the surrounding
environment. We currently lack detailed knowledge of the wind structure that is
needed to quantify this impact. Aims: To observationally constrain the stellar
and wind properties of the massive stars in R136, in particular the parameters
related to wind clumping. Methods: We simultaneously analyse optical and UV
spectroscopy of 53 O-type and 3 WNh-stars using the FASTWIND model atmosphere
code and a genetic algorithm. The models account for optically thick clumps and
effects related to porosity and velocity-porosity, as well as a non-void
interclump medium. Results: We obtain stellar parameters, surface abundances,
mass-loss rates, terminal velocities and clumping characteristics and compare
these to theoretical predictions and evolutionary models. The clumping
properties include the density of the interclump medium and the
velocity-porosity of the wind. For the first time, these characteristics are
systematically measured for a wide range of effective temperatures and
luminosities. Conclusions: We confirm a cluster age of 1.0-2.5 Myr and derive
an initial stellar mass of $\geq 250 {\rm M}_\odot$ for the most massive star
in our sample, R136a1. The winds of our sample stars are highly clumped, with
an average clumping factor of $f_{\rm cl}=29\pm15$. We find tentative trends in
the wind-structure parameters as a function of mass-loss rate, suggesting that
the winds of stars with higher mass-loss rates are less clumped. We compare
several theoretical predictions to the observed mass-loss rates and terminal
velocities and find that none satisfactorily reproduces both quantities. The
prescription of Krti\v{c}ka & Kub\'at (2018) matches best the observed
mass-loss rates.
|
IoT devices are in general considered to be straightforward to use. However,
we find that there are a number of situations where the usability becomes poor.
The situations include but not limited to the followings: 1) when initializing
an IoT device, 2) when trying to control an IoT device which is initialized and
registered by another person, and 3) when trying to control an IoT device out
of many of the same type. We tackle these situations by proposing a new
association-free communication method, QuickTalk. QuickTalk lets a user device
such as a smartphone pinpoint and activate an IoT device with the help of an IR
transmitter and communicate with the pinpointed IoT device through the
broadcast channel of WiFi. By the nature of its association-free communication,
QuickTalk allows a user device to immediately give a command to a specific IoT
device in proximity even when the IoT device is uninitialized, unregistered to
the control interface of the user, or registered but being physically confused
with others. Our experiments of QuickTalk implemented on Raspberry Pi 2 devices
show that the end-to-end delay of QuickTalk is upper bounded by 2.5 seconds and
its median is only about 0.74 seconds. We further confirm that even when an IoT
device has ongoing data sessions, QuickTalk can still establish a reliable
communication channel to the IoT device with little impact to the ongoing
sessions.
|
The interior flux of a giant planet impacts atmospheric motion, and the
atmosphere dictates the interior's cooling. Here we use a non-hydrostatic
general circulation model (Simulating Nonhydrostatic Atmospheres on Planets,
SNAP) coupled with a multi-stream multi-scattering radiative module
(High-performance Atmospheric Radiation Package, HARP) to simulate the weather
impacts on the heat flow of hot Jupiters. We found that the vertical heat flux
is primarily transported by convection in the lower atmosphere and regulated by
dynamics and radiation in the overlying ``radiation-circulation" zone. The
temperature inversion occurs on the dayside and reduces the upward radiative
flux. The atmospheric dynamics relay the vertical heat transport until the
radiation becomes efficient in the upper atmosphere. The cooling flux increases
with atmospheric drag due to increased day-night contrast and spatial
inhomogeneity. The temperature dependence of the infrared opacity greatly
amplifies the opacity inhomogeneity. Although atmospheric circulation could
transport heat downward in a narrow region above the radiative-convective
boundary, the opacity inhomogeneity effect overcomes the dynamical effect and
leads to a larger overall interior cooling than the local simulations with the
same interior entropy and stellar flux. The enhancement depends critically on
the equilibrium temperature, drag, and atmospheric opacity. In a strong-drag
atmosphere hotter than 1600 K, a significant inhomogeneity effect in
three-dimensional (3D) models can boost interior cooling several-fold compared
to the 1D radiative-convective equilibrium models. This study confirms the
analytical argument of the inhomogeneity effect in Zhang (2023a,b). It
highlights the importance of using 3D atmospheric models in understanding the
inflation mechanisms of hot Jupiters and giant planet evolution in general.
|
Images of handwritten digits are different from natural images as the
orientation of a digit, as well as similarity of features of different digits,
makes confusion. On the other hand, deep convolutional neural networks are
achieving huge success in computer vision problems, especially in image
classification. BDNet is a densely connected deep convolutional neural network
model used to classify (recognize) Bengali handwritten numeral digits. It is
end-to-end trained using ISI Bengali handwritten numeral dataset. During
training, untraditional data preprocessing and augmentation techniques are used
so that the trained model works on a different dataset. The model has achieved
the test accuracy of 99.775%(baseline was 99.40%) on the test dataset of ISI
Bengali handwritten numerals. So, the BDNet model gives 62.5% error reduction
compared to previous state-of-the-art models. Here we have also created a
dataset of 1000 images of Bengali handwritten numerals to test the trained
model, and it giving promising results. Codes, trained model and our own
dataset are available at: {https://github.com/Sufianlab/BDNet}.
|
It is suggested that fast radio bursts can probe gravitational lensing by
clumpy dark matter objects that range in mass from $10^{-3}M_{\odot}$ to $10^2
M_{\odot}$. They may provide a more sensitive probe than observations of
lensing of objects in the Magellanic Clouds, and could find or rule out clumpy
dark matter with an extended mass spectrum.
|
This paper is a brief introduction to idempotent and tropical mathematics.
Tropical mathematics can be treated as a result of the so-called Maslov
dequantization of the traditional mathematics over numerical fields as the
Planck constant $\hbar$ tends to zero taking imaginary values.
|
NGC 4993 is the shell galaxy host of the GRB170817A short gamma-ray burst and
the GW170817 gravitational-wave event produced during a binary-neutron-star
coalescence. The galaxy shows signs, including the stellar shells, that it has
recently accreted a smaller, late-type galaxy. The accreted galaxy might be the
original host of the binary neutron star. We measured the positions of the
stellar shells of NGC 4993 in an HST/ACS archival image and use the shell
positions to constrain the time of the galactic merger. According to the
analytical model of the evolution of the shell structure in the expected
gravitational potential of NGC 4993, the galactic merger happened at least 200
Myr ago, with a probable time roughly around 400 Myr and the estimates higher
than 600 Myr being improbable. This constitutes the lower limit on the age of
the binary neutron star, because the host galaxy was probably quenched even
before the galactic merger, and the merger has likely shut down the star
formation in the accreted galaxy. We roughly estimate the probability that the
binary neutron star originates in the accreted galaxy to be around 30%.
|
The Alesker-Poincare pairing for smooth valuations on manifolds is expressed
in terms of the Rumin differential operator acting on the cosphere-bundle. It
is shown that the derivation operator, the signature operator and the Laplace
operator acting on smooth valuations are formally self-adjoint with respect to
this pairing. As an application, the product structure of the space of SU(2)-
and translation invariant valuations on the quaternionic line is described. The
principal kinematic formula on the quaternionic line is stated and proved.
|
We present exact calculations of the zero-temperature partition function of
the $q$-state Potts antiferromagnet (equivalently the chromatic polynomial) for
Moebius strips, with width $L_y=2$ or 3, of regular lattices and homeomorphic
expansions thereof. These are compared with the corresponding partition
functions for strip graphs with (untwisted) periodic longitudinal boundary
conditions.
|
A granular system confined in a quasi two-dimensional box that is vertically
vibrated can transit to an absorbing state in which all particles bounce
vertically in phase with the box, with no horizontal motion. In principle, this
state can be reached for any density lower than the one corresponding to one
complete monolayer, which is then the critical density. Below this critical
value, the transition to the absorbing state is of first order, with long
metastable periods, followed by rapid transitions driven by homogeneous
nucleation. Molecular dynamics simulations and experiments show that there is a
dramatic increase on the metastable times far below the critical density; in
practice, it is impossible to observe spontaneous transitions close to the
critical density. This peculiar feature is a consequence of the non-equilibrium
nature of this first order transition to the absorbing state. A Ginzburg-Landau
model, with multiplicative noise, describes qualitatively the observed
phenomena and explains the macroscopic size of the critical nuclei. The nuclei
become of small size only close to a second critical point where the active
phase becomes unstable via a saddle node bifurcation. It is only close to this
second critical point that experiments and simulations can evidence spontaneous
transitions to the absorbing state while the metastable times grow dramatically
moving away from it.
|
We investigate the quantum hadrodynamic equation of state for neutron stars
(with and without including hyperons) in the presence of strong magnetic
fields. The deduced masses and radii are consistent with recent observations of
high mass neutron stars even in the case of hyperonic nuclei for sufficiently
strong magnetic fields. The calculated adiabatic index and the moments of
inertia for magnetized neutron stars exhibit rapid changes with density. This
may provide some insight into the mechanism of star-quakes and flares in
magnetars.
|
Aggregated metapopulation lifetime statistics has been used to access
stylized facts that might help identify the underlying patch-level dynamics.
For instance, the emergence of scaling laws in the aggregated probability
distribution of patch lifetimes can be associated to critical phenomena, in
which the correlation length among system units tends to diverge. Nevertheless,
an aggregated approach is biased by patch-level variability, a fact that can
blur the interpretation of the data. Here, I propose a weakly-coupled
metapopulation model to show how patch variability can solely trigger
qualitatively different lifetime probability distribution at the aggregated
level. In a generalized approach, I obtain a two-way connection between the
variability of a certain patch property (e.g. carrying capacity, environment
condition or connectivity) and the aggregated lifetime probability
distribution. Furthermore, for a particular case, assuming that scaling laws
are observed at the aggregated-level, I speculate the heterogeneity that could
be behind it, relating the qualitative features the variability (mean, variance
and concentration) to the scaling exponents. In this perspective, the
application points to the possibility of equivalence between heterogeneous
weakly-coupled metapopulations and homogeneous ones that exhibit critical
behavior.
|
Medical digital twins are computational models of human biology relevant to a
given medical condition, which can be tailored to an individual patient,
thereby predicting the course of disease and individualized treatments, an
important goal of personalized medicine. The immune system, which has a central
role in many diseases, is highly heterogeneous between individuals, and thus
poses a major challenge for this technology. If medical digital twins are to
faithfully capture the characteristics of a patient's immune system, we need to
answer many questions, such as: What do we need to know about the immune system
to build mathematical models that reflect features of an individual? What data
do we need to collect across the different scales of immune system action? What
are the right modeling paradigms to properly capture immune system complexity?
In February 2023, an international group of experts convened in Lake Nona, FL
for two days to discuss these and other questions related to digital twins of
the immune system. The group consisted of clinicians, immunologists,
biologists, and mathematical modelers, representative of the interdisciplinary
nature of medical digital twin development. A video recording of the entire
event is available. This paper presents a synopsis of the discussions, brief
descriptions of ongoing digital twin projects at different stages of progress.
It also proposes a 5-year action plan for further developing this technology.
The main recommendations are to identify and pursue a small number of promising
use cases, to develop stimulation-specific assays of immune function in a
clinical setting, and to develop a database of existing computational immune
models, as well as advanced modeling technology and infrastructure.
|
Let $d=\frac{(3^{2k}+1)^{2}}{20}$, where $k$ is an odd integer. We show that
the magnitude of the cross-correlation values of a ternary $m$-sequence
$\{s_{t}\}$ of period $3^{4k}-1$ and its decimated sequence $\{s_{dt}\}$ is
upper bounded by $5\sqrt{3^{n}}+1$, where $n=4k$.
|
We present the application of simultaneous diagonalization and minimum energy
(SDME) high-order finite element modal bases for simulation of transient
non-linear elastodynamic problem, including impact cases with neo-hookean
hyperelastic materials. The bases are constructed using procedures for
simultaneous diagonalization of the internal modes and Schur complement of the
boundary modes from the standard nodal and modal bases, constructed using
Lagrange and Jacobi polynomials, respectively. The implementation of these
bases in a high-order finite element code is straightforward, since the
procedure is applied only to the one-dimensional expansion bases. Non-linear
transient structural problems with large deformation, hyperelastic materials
and impact are solved using the obtained bases with explicit and implicit time
integration procedures. Iterative solutions based on preconditioned conjugate
gradient methods are considered. The performance of the proposed bases in terms
of the number of iterations of pre-conditioned conjugate gradient methods and
computational time are compared with the standard nodal and modal bases. Our
numerical tests obtained speedups up to 41 using the considered bases when
compared to the standard ones.
|
We give an explicit upper bound for non-principal Dirichlet $L$-functions on
the line $s=1+it$. This result can be applied to improve the error in the
zero-counting formulae for these functions.
|
Deep reinforcement learning (DRL) has great potential for acquiring the
optimal action in complex environments such as games and robot control.
However, it is difficult to analyze the decision-making of the agent, i.e., the
reasons it selects the action acquired by learning. In this work, we propose
Mask-Attention A3C (Mask A3C), which introduces an attention mechanism into
Asynchronous Advantage Actor-Critic (A3C), which is an actor-critic-based DRL
method, and can analyze the decision-making of an agent in DRL. A3C consists of
a feature extractor that extracts features from an image, a policy branch that
outputs the policy, and a value branch that outputs the state value. In this
method, we focus on the policy and value branches and introduce an attention
mechanism into them. The attention mechanism applies a mask processing to the
feature maps of each branch using mask-attention that expresses the judgment
reason for the policy and state value with a heat map. We visualized
mask-attention maps for games on the Atari 2600 and found we could easily
analyze the reasons behind an agent's decision-making in various game tasks.
Furthermore, experimental results showed that the agent could achieve a higher
performance by introducing the attention mechanism.
|
A new system of general Navier-Stokes-like equations is proposed to model
electromagnetic analogous to hydrodynamic. While most attempts to derive
analogues of hydrodynamic to electromagnetic, and vice-versa, start with
Navier-Stokes or a Euler approximation, we propose general conservation
equations as a starting point. Such equations provide a structured framework
from which additional insights into the problem at hand could be obtained. To
that end, we propose a system of momentum and mass-energy conservation
equations coupled through both momentum density and velocity vectors.
|
Occlusions are very common in face images in the wild, leading to the
degraded performance of face-related tasks. Although much effort has been
devoted to removing occlusions from face images, the varying shapes and
textures of occlusions still challenge the robustness of current methods. As a
result, current methods either rely on manual occlusion masks or only apply to
specific occlusions. This paper proposes a novel face de-occlusion model based
on face segmentation and 3D face reconstruction, which automatically removes
all kinds of face occlusions with even blurred boundaries,e.g., hairs. The
proposed model consists of a 3D face reconstruction module, a face segmentation
module, and an image generation module. With the face prior and the occlusion
mask predicted by the first two, respectively, the image generation module can
faithfully recover the missing facial textures. To supervise the training, we
further build a large occlusion dataset, with both manually labeled and
synthetic occlusions. Qualitative and quantitative results demonstrate the
effectiveness and robustness of the proposed method.
|
We present a computationally efficient 1-D seasonal radiative model, with
convective adjustment, of Jupiter's atmosphere. Our model takes into account
radiative forcings from the main hydrocarbons (methane, ethane, acetylene),
ammonia, collision-induced absorption, four cloud and haze layers (including a
UV-absorbing "polar" stratospheric haze) and an internal heat flux. We detail
sensitivity studies of the equilibrium temperature profile to several
parameters. We discuss the expected seasonal, vertical and meridional thermal
structure and compare it to that derived from Cassini and ground-based thermal
infrared observations. We find that the equilibrium temperature in the 5-30
mbar pressure range is very sensitive to the chosen stratospheric haze optical
properties, sizes and number of monomers. The polar haze can significantly warm
the lower stratosphere (10-30 mbar) by up to 20K at latitudes 45-60{\deg}. At
pressures lower than 3 mbar, our modeled temperatures systematically
underestimate the observed ones by 5K. This might suggest that other processes,
such as dynamical heating by wave breaking or by eddies, or a coupling with
thermospheric circulation, play an important role. In the troposphere, we can
only match the observed lack of meridional gradient of temperature by varying
the internal heat flux with latitude. We then exploit knowledge of heating and
cooling rates to diagnose the residual-mean circulation in Jupiter's
stratosphere, under the assumption that the eddy heat flux convergence term is
negligible. In the lower stratosphere (5-30 mbar), the residual-mean
circulation strongly depends on the assumed properties of the stratospheric
haze. Our main conclusion is that it is crucial to improve our knowledge on the
radiative forcing terms to increase our confidence in the estimated
circulation. By extension, this will also be crucial for future 3D GCM studies.
|
We present a novel lambda calculus that casts the categorical approach to the
study of quantum protocols into the rich and well established tradition of type
theory. Our construction extends the linear typed lambda calculus with a linear
negation of "trivialised" De Morgan duality. Reduction is realised through
explicit substitution, based on a symmetric notion of binding of global scope,
with rules acting on the entire typing judgement instead of on a specific
subterm. Proofs of subject reduction, confluence, strong normalisation and
consistency are provided, and the language is shown to be an internal language
for dagger compact categories.
|
The analysis of the CKM parameters will take a leap forward when the hadronic
B factories receive their first data. I describe the challenges faced by
B-physics at hadronic colliders and the expected reach in specific channels for
the LHCb, BTeV, ATLAS and CMS experiments.
|
In this article, constant dimension subspace codes whose codewords have
subspace distance in a prescribed set of integers, are considered. The easiest
example of such an object is a {\it junta}; i.e. a subspace code in which all
codewords go through a common subspace. We focus on the case when only two
intersection values for the codewords, are assigned. In such a case we
determine an upper bound for the dimension of the vector space spanned by the
elements of a non-junta code. In addition, if the two intersection values are
consecutive, we prove that such a bound is tight, and classify the examples
attaining the largest possible dimension as one of four infinite families.
|
Optically driven electronic spins coupled in quantum dots to nuclear spins
show a pre-pulse signal (revival amplitude) after having been trained by long
periodic sequences of pulses. The size of this revival amplitude depends on the
external magnetic field in a specific way due to the varying commensurability
of the nuclear Larmor precession period with the time $T_\text{rep}$ between
two consecutive pulses. In theoretical simulations, sharp dips occur at fields
when an integer number of precessions fits in $T_\text{rep}$; this feature
could be used to identify nuclear isotopes spectroscopically. But these sharp
and characteristic dips have not (yet) been detected in experiment. We study
whether the nuclear quadrupolar interaction is the reason for this discrepancy
because it perturbs the nuclear precessions. But our simulations show that the
absolute width of the dips and their relative depth are not changed by
quadrupolar interactions. Only the absolute depth decreases. We conclude that
quadrupolar interaction alone cannot be the reason for the absence of the
characteristic dips in experiment.
|
It is widely conjectured that the reason that training algorithms for neural
networks are successful because all local minima lead to similar performance,
for example, see (LeCun et al., 2015, Choromanska et al., 2015, Dauphin et al.,
2014). Performance is typically measured in terms of two metrics: training
performance and generalization performance. Here we focus on the training
performance of single-layered neural networks for binary classification, and
provide conditions under which the training error is zero at all local minima
of a smooth hinge loss function. Our conditions are roughly in the following
form: the neurons have to be strictly convex and the surrogate loss function
should be a smooth version of hinge loss. We also provide counterexamples to
show that when the loss function is replaced with quadratic loss or logistic
loss, the result may not hold.
|
Blazars are the most active extragalactic gamma-ray sources. They show
sporadic bursts of activity, lasting from hours to months. In this work we
present a 10-year analysis of a sample of bright sources detected by Fermi-LAT
(100 MeV - 300 GeV). Using 2-week binned lightcurves (LC) we estimated the Duty
Cycle (DC): fraction of time that the source spends in an active state. The
objects present different DC values, with an average of $22.74\%$ and $23.08
\%$ when considering (and not) the Extragalactic Background Light ( EBL).
Additionally we study the so called "blazar sequence" trend for the sample of
selected blazars in the ten years of data. This analysis constrains a possible
counterpart of sub-PeV neutrino emission during the quiescent states, leaving
the possibility to explain the observed IceCube signal during the flaring
states.
|
In this Chapter I review the role that galaxy clusters play as tools to
constrain cosmological parameters. I will concentrate mostly on the application
of the mass function of galaxy clusters, while other methods, such as that
based on the baryon fraction, are covered by other Chapters of the book. Since
most of the cosmological applications of galaxy clusters rely on precise
measurements of their masses, a substantial part of my Lectures concentrates on
the different methods that have been applied so far to weight galaxy clusters.
I provide in Section 2 a short introduction to the basics of cosmic structure
formation. In Section 3 I describe the Press--Schechter (PS) formalism to
derive the cosmological mass function, then discussing extensions of the PS
approach and the most recent calibrations from N--body simulations. In Section
4 I review the methods to build samples of galaxy clusters at different
wavelengths. Section 5 is devoted to the discussion of different methods to
derive cluster masses. In Section 6 I describe the cosmological constraints,
which have been obtained so far by tracing the cluster mass function with a
variety of methods. Finally, I describe in Section 7 the future perspectives
for cosmology with galaxy clusters and the challenges for clusters to keep
playing an important role in the era of precision cosmology.
|
Multiple analogues of certain families of combinatorial numbers are recently
constructed by the author in terms of well poised Macdonald functions, and some
of their fundamental properties are developed. In this paper, we present
combinatorial formulas for the well poised Macdonald functions, the multiple
binomial coefficients, the multiple bracket function, and the multiple Catalan
and Lah numbers.
|
Given the limited performance of 2D cellular automata in terms of space when
the number of documents increases and in terms of visualization clusters, our
motivation was to experiment these cellular automata by increasing the size to
view the impact of size on quality of results. The representation of textual
data was carried out by a vector model whose components are derived from the
overall balancing of the used corpus, Term Frequency Inverse Document Frequency
(TF-IDF). The WorldNet thesaurus has been used to address the problem of the
lemmatization of the words because the representation used in this study is
that of the bags of words. Another independent method of the language was used
to represent textual records is that of the n-grams. Several measures of
similarity have been tested. To validate the classification we have used two
measures of assessment based on the recall and precision (f-measure and
entropy). The results are promising and confirm the idea to increase the
dimension to the problem of the spatiality of the classes. The results obtained
in terms of purity class (i.e. the minimum value of entropy) shows that the
number of documents over longer believes the results are better for 3D cellular
automata, which was not obvious to the 2D dimension. In terms of spatial
navigation, cellular automata provide very good 3D performance visualization
than 2D cellular automata.
|
Singular fourth-order Abreu equations have been used to approximate
minimizers of convex functionals subject to a convexity constraint in
dimensions higher than or equal to two. For Abreu type equations, they often
exhibit different solvability phenomena in dimension one and dimensions at
least two. We prove the analogues of these results for the variational problem
and singular Abreu equations in dimension one, and use the approximation scheme
to obtain a characterization of limiting minimizers to the one-dimensional
variational problem.
|
Searches in ep collisions for heavy excited fermions have been performed with
the ZEUS detector at HERA. Excited states of electrons and quarks have been
searched for in e^+p collisions at a centre-of-mass energy of 300 GeV using an
integrated luminosity of 47.7 pb^-1. Excited electrons have been sought via the
decays e*->egamma, e*->eZ and e*->nuW. Excited quarks have been sought via the
decays q*->qgamma and q*->qW. A search for excited neutrinos decaying via
nu*->nugamma, nu*->nuZ and nu*->eW is presented using e^-p collisions at 318
GeV centre-of-mass energy, corresponding to an integrated luminosity of 16.7
pb^-1. No evidence for any excited fermion is found, and limits on the
characteristic couplings are derived for masses below 250 GeV.
|
I propose a new method to determine the running coupling in a
Schrodinger-functional setup. The method utilizes the scattering amplitude of
massless fermions propagating between the time boundaries. Preliminary tests
show the statistical fluctuations of the new observable to be about half those
of the standard Schrodinger-functional running coupling.
|
We show that the finite satisfiability problem for the unary negation
fragment with arbitrary number of transitive relations is decidable and
2-ExpTime-complete. Our result actually holds for a more general setting in
which one can require that some binary symbols are interpreted as arbitrary
transitive relations, some as partial orders and some as equivalences. We also
consider finite satisfiability of various extensions of our primary logic, in
particular capturing the concepts of nominals and role hierarchies known from
description logic. As the unary negation fragment can express unions of
conjunctive queries our results have interesting implications for the problem
of finite query answering, both in the classical scenario and in the
description logics setting.
|
The set of differential equations obeyed by the redshift in the general
$\beta' \neq 0$ Szekeres spacetimes is derived. Transversal components of the
ray's momentum have to be taken into account, which leads to a set of 3 coupled
differential equations. It is shown that in a general Szekeres model, and in a
general Lema\^{\i}tre -- Tolman (L--T) model, generic light rays do not have
repeatable paths (RLPs): two rays sent from the same source at different times
to the same observer pass through different sequences of intermediate matter
particles. The only spacetimes in the Szekeres class in which {\em all} rays
are RLPs are the Friedmann models. Among the proper Szekeres models, RLPs exist
only in the axially symmetric subcases, and in each one the RLPs are the null
geodesics that intersect each $t =$ constant space on the symmetry axis. In the
special models with a 3-dimensional symmetry group (L--T among them), the only
RLPs are radial geodesics. This shows that RLPs are very special and in the
real Universe should not exist. We present several numerical examples which
suggest that the rate of change of positions of objects in the sky, for the
studied configuration, is $10^{-6} - 10^{-7}$ arc sec per year. With the
current accuracy of direction measurement, this drift would become observable
after approx. 10 years of monitoring. More precise future observations will be
able, in principle, to detect this effect, but there are basic problems with
determining the reference direction that does not change.
|
We present a novel framework for 3D object-centric representation learning.
Our approach effectively decomposes complex scenes into individual objects from
a single image in an unsupervised fashion. This method, called slot-guided
Volumetric Object Radiance Fields (sVORF), composes volumetric object radiance
fields with object slots as a guidance to implement unsupervised 3D scene
decomposition. Specifically, sVORF obtains object slots from a single image via
a transformer module, maps these slots to volumetric object radiance fields
with a hypernetwork and composes object radiance fields with the guidance of
object slots at a 3D location. Moreover, sVORF significantly reduces memory
requirement due to small-sized pixel rendering during training. We demonstrate
the effectiveness of our approach by showing top results in scene decomposition
and generation tasks of complex synthetic datasets (e.g., Room-Diverse).
Furthermore, we also confirm the potential of sVORF to segment objects in
real-world scenes (e.g., the LLFF dataset). We hope our approach can provide
preliminary understanding of the physical world and help ease future research
in 3D object-centric representation learning.
|
How reliably an automatic summarization evaluation metric replicates human
judgments of summary quality is quantified by system-level correlations. We
identify two ways in which the definition of the system-level correlation is
inconsistent with how metrics are used to evaluate systems in practice and
propose changes to rectify this disconnect. First, we calculate the system
score for an automatic metric using the full test set instead of the subset of
summaries judged by humans, which is currently standard practice. We
demonstrate how this small change leads to more precise estimates of
system-level correlations. Second, we propose to calculate correlations only on
pairs of systems that are separated by small differences in automatic scores
which are commonly observed in practice. This allows us to demonstrate that our
best estimate of the correlation of ROUGE to human judgments is near 0 in
realistic scenarios. The results from the analyses point to the need to collect
more high-quality human judgments and to improve automatic metrics when
differences in system scores are small.
|
We investigate the effects of finite temperature, dc pulse, and ac drives on
the charge transport in metallic arrays using numerical simulations. For finite
temperatures there is a finite conduction threshold which decreases linearly
with temperature. Additionally we find a quadratic scaling of the
current-voltage curves which is independent of temperature for finite
thresholds. These results are in excellent agreement with recent experiments on
2D metallic dot arrays. We have also investigated the effects of an ac drive as
well as a suddenly applied dc drive. With an ac drive the conduction threshold
decreases for fixed frequency and increasing amplitude and saturates for fixed
amplitude and increasing frequency. For sudden applied dc drives below
threshold we observe a long time power law conduction decay.
|
The absolute upper bound on the number of equiangular lines that can be found
in $\mathbf{R}^d$ is $d(d+1)/2$. Examples of sets of lines that saturate this
bound are only known to exist in dimensions $d=2,3,7$ or $23$. By considering
the additional property of incoherence, we prove that there exists a set of
equiangular lines that saturates the absolute bound and the incoherence bound
if and only if $d=2,3,7$ or $23$. This allows us classify all tight spherical
$5$-designs $X$ in $\mathbf{S}^{d-1}$, the unit sphere, with the property that
there exists a set of $d$ points in $X$ whose pairwise inner products are
positive.
For a given angle $\kappa$, there exists a relative upper bound on the number
of equiangular lines in $\mathbf{R}^d$ with common angle $\kappa$. We prove
that classifying sets of lines that saturate this bound along with the
incoherence bound is equivalent to classifying certain quasi-symmetric designs,
which are combinatorial designs with two block intersection numbers. Given a
further natural assumption, we classify the known sets of lines that saturate
these two bounds. This family comprises of the lines mentioned above and the
maximal set of $16$ equiangular lines found in $\mathbf{R}^6$. There are
infinitely many known sets of lines that saturate the relative bound, so this
result is surprising. To shed some light on this, we identify the $E_8$ lattice
with the projection onto an $8$-dimensional subspace of a sublattice of the
Leech lattice defined by $276$ equiangular lines in $\mathbf{R}^{23}$. This
identification leads us to observe a correspondence between sets of equiangular
lines in small dimensions and the exceptional curves of del Pezzo surfaces.
|
When used in bulk applications, mechanical metamaterials set forth a
multiscale problem with many orders of magnitude in scale separation between
the micro and macro scales. However, mechanical metamaterials fall outside
conventional homogenization theory on account of the flexural, or bending,
response of their members, including torsion. We show that homogenization
theory, based on calculus of variations and notions of Gamma-convergence, can
be extended to account for bending. The resulting homogenized metamaterials
exhibit intrinsic generalized elasticity in the continuum limit. We illustrate
these properties in specific examples including two-dimensional honeycomb and
three-dimensional octet-truss metamaterials.
|
It has been a fascinating topic in the study of boundary layer theory about
the well-posedness of Prandtl equation that was derived in 1904. Recently, new
ideas about cancellation to overcome the loss of tangential derivatives were
obtained so that Prandtl equation can be shown to be well-posed in Sobolev
spaces to avoid the use of Crocco transformation as in the classical work of
Oleinik. This short note aims to show that the cancellation mechanism is in
fact related to some intrinsic directional derivative that can be used to
recover the tangential derivative under some structural assumption on the fluid
near the boundary.
|
In this work, we have studied the hydrogen adsorption-desorption properties
and storage capacities of Li functionalized [2,2,2]paracyclophane (PCP222)
using dispersion-corrected density functional theory and molecular dynamic
simulation. The Li atom was found to bond strongly with the benzene ring of
PCP222 via Dewar interaction. Subsequently, the calculation of the diffusion
energy barrier revealed a significantly high energy barrier of 1.38 eV,
preventing the Li clustering on PCP222. The host material, PCP222-3Li adsorbed
up to 15H2 molecules via a charge polarization mechanism with an average
adsorption energy of 0.145 eV/5H2, suggesting a physisorption type of
adsorption. The PCP222 functionalized with three Li atom showed maximum
hydrogen uptake capacity up to 8.32 wt%, which was fairly above the US-DOE
criterion. The practical storage estimation revealed that the PCP222-3Li
desorbed 100% of adsorbed H2 molecules at the temperature range of 260 K-300 K
and pressure range of 1-10 bar. The maximum H2 desorption temperature estimated
by the Vant-Hoff relation was found to be 219 K and 266 K at 1 bar and 5 bar,
respectively. The ADMP molecular dynamics simulations assured the reversibility
of adsorbed H2 and the structural integrity of the host material at
sufficiently above the desorption temperature (300K and 500K). Therefore, the
Li-functionalized PCP222 can be considered as a thermodynamically viable and
potentially reversible H2 storage material below room temperature.
|
Retrosynthesis, which aims to find a route to synthesize a target molecule
from commercially available starting materials, is a critical task in drug
discovery and materials design. Recently, the combination of ML-based
single-step reaction predictors with multi-step planners has led to promising
results. However, the single-step predictors are mostly trained offline to
optimize the single-step accuracy, without considering complete routes. Here,
we leverage reinforcement learning (RL) to improve the single-step predictor,
by using a tree-shaped MDP to optimize complete routes. Specifically, we
propose a novel online training algorithm, called Planning with Dual Value
Networks (PDVN), which alternates between the planning phase and updating
phase. In PDVN, we construct two separate value networks to predict the
synthesizability and cost of molecules, respectively. To maintain the
single-step accuracy, we design a two-branch network structure for the
single-step predictor. On the widely-used USPTO dataset, our PDVN algorithm
improves the search success rate of existing multi-step planners (e.g.,
increasing the success rate from 85.79% to 98.95% for Retro*, and reducing the
number of model calls by half while solving 99.47% molecules for RetroGraph).
Additionally, PDVN helps find shorter synthesis routes (e.g., reducing the
average route length from 5.76 to 4.83 for Retro*, and from 5.63 to 4.78 for
RetroGraph). Our code is available at \url{https://github.com/DiXue98/PDVN}.
|
Reliable short term forecasting can provide potentially lifesaving insights
into logistical planning, and in particular, into the optimal allocation of
resources such as hospital staff and equipment. By reinterpreting COVID-19
daily cases in terms of candlesticks, we are able to apply some of the most
popular stock market technical indicators to obtain predictive power over the
course of the pandemics. By providing a quantitative assessment of MACD, RSI,
and candlestick analyses, we show their statistical significance in making
predictions for both stock market data and WHO COVID-19 data. In particular, we
show the utility of this novel approach by considering the identification of
the beginnings of subsequent waves of the pandemic. Finally, our new methods
are used to assess whether current health policies are impacting the growth in
new COVID-19 cases.
|
A stable non-commutative solution with symmetry breaking is presented for a
system of Dp-branes in the presence of a RR (p+5)-form.
|
Tetrahedrite-based ($\textrm{Cu}_{12}\textrm{Sb}_{4}\textrm{S}_{13}$)
materials are candidates for good thermoelectric generators due to their
intrinsic, very low thermal conductivity and high power factor. One of the
current limitations is virtual absence of tetrahedrites exhibiting n--type
conductivity. In this work, first-principles calculations are carried out to
study Mg-doped tetrahedrite,
$\textrm{Mg}_{x}\textrm{Cu}_{12}\textrm{Sb}_{4}\textrm{S}_{13}$ with
possibility of predicting n--type material in mind. Different concentrations
and modifications of the structure are investigated for their formation
energies, preferred site occupation and change in local environment around
dopants. Mg atoms tend to occupy 6b site, while introduced excess Cu prefers
24g site. Introduction of elements in those sites display different effect on
nearby rattling Cu(2) atom. Topological analysis shows that tetrahedrite
exhibits ionic, closed-shell bonds with some degree of covalency. Majority of
the bonds weakens with increasing content of Mg; structure becomes increasingly
less stable, which is also expressed by global instability and bond strain
indexes. Achieving n--type conductivity was predicted by the calculations for
structures with $x>1.0$, however increasing enthalpy of formation and lack of
stability might suggest limit of solubility and difficulties in obtaining those
experimentally.
|
This paper describes the development of a magnetic attitude control subsystem
for a 2U cubesat. Due to the presence of gravity gradient torques, the
satellite dynamics are open-loop unstable near the desired pointing
configuration. Nevertheless the linearized time-varying system is completely
controllable, under easily verifiable conditions, and the system's disturbance
rejection capabilities can be enhanced by adding air drag panels exemplifying a
beneficial interplay between hardware design and control. In the paper,
conditions for the complete controllability for the case of a magnetically
controlled satellite with passive air drag panels are developed, and simulation
case studies with the LQR and MPC control designs applied in combination with a
nonlinear time-varying input transformation are presented to demonstrate the
ability of the closed-loop system to satisfy mission objectives despite
disturbance torques.
|
Let $b$ be a numeration base. A $b$-additive Ramanujan-Hardy number $N$ is an
integer for which there exists at least an integer $M$, called additive
multiplier, such that the product of $M$ and the sum of base $b$ digits of $N$,
added to the reversal of the product, gives $N$. We show that for any $b$ there
exists an infinity of $b$-additive Ramanujan-Hardy numbers and an infinity of
additive multipliers. A $b$-multiplicative Ramanujan-Hardy number $N$ is an
integer for which there exists at least an integer $M$, called multiplicative
multiplier, such that the product of $M$ and the sum of base $b$ digits of $N$,
multiplied by the reversal of the product, gives $N$. We show that for an even
$b$, $b\equiv 1 \pmod {3}$, and for $b=2$, there exists an infinity of
$b$-multiplicative Ramanujan-Hardy numbers and an infinity of multiplicative
multipliers.
These results completely answer two questions and partially answer two other
questions among those asked in V. Ni\c{t}ic\u{a}, \emph{About some relatives of
the taxicab number}, arXiv:1805.10739v4.
|
Due to increasing environmental and economic constraints, optimization of ion
beam transport and equipment design becomes essential. The future should be
equipped with planet-friendly facilities, that is, solutions that reduce
environmental impact and improve economic competitiveness. The tendency to
increase the intensity of the current and the power of the beams obliges us and
brings us to new challenges. Installations tend to have larger dimensions with
increased areas, volumes, weights and costs. A new ion beam transport prototype
was developed and used as a test bed to identify key issues to reduce beam
losses and preserve transverse phase-space distributions with large acceptance
conditions.
|
Recurrent neural networks (RNNs), specifically long-short term memory
networks (LSTMs), can model natural language effectively. This research
investigates the ability for these same LSTMs to perform next "word" prediction
on the Java programming language. Java source code from four different
repositories undergoes a transformation that preserves the logical structure of
the source code and removes the code's various specificities such as variable
names and literal values. Such datasets and an additional English language
corpus are used to train and test standard LSTMs' ability to predict the next
element in a sequence. Results suggest that LSTMs can effectively model Java
code achieving perplexities under 22 and accuracies above 0.47, which is an
improvement over LSTM's performance on the English language which demonstrated
a perplexity of 85 and an accuracy of 0.27. This research can have
applicability in other areas such as syntactic template suggestion and
automated bug patching.
|
We include a new 7-form ansatz in 11-dimensional supergravity over AdS_4 x
S^7/Z_k when the internal space is considered as a U(1) bundle on CP^3. After a
general analysis of the ansatz, we take a special form of it and obtain a
scalar equation from which we focus on a few massive bulk modes that are SU(4)
x U(1) R-singlet and break all supersymmetries. The mass term breaks the scale
invariance and so the (perturbative) solutions we obtain are SO(4) invariant in
Euclidean AdS_4 (or SO(3,1) in its dS_3 slicing). The corresponding bare
operators are irrelevant in probe approximation; and to realize the AdS_4/CFT_3
correspondence, we need to swap the fundamental representations of $SO(8)$ for
supercharges with those for scalars and fermions. In fact, we have domain-walls
arising from (anti)M5-branes wrapping around S^3/Z_k of the internal space with
parity breaking scheme. As a result, the duals may be in three-dimensional U(N)
or O(N) Chern-Simon models with matters in fundamental representations.
Accordingly, we present dual boundary operators and build instanton solutions
in a truncated version of the boundary ABJM action; and, because of the
unboundedness of bulk potential from below, it is thought that they lead to big
crunch singularities in the bulk.
|
The PICASSO experiment reports an improved limit for the existence of cold
dark matter WIMPs interacting via spin-dependent interactions with nuclei. The
experiment is installed in the Sudbury Neutrino Observatory at a depth of 2070
m. With superheated C4F10 droplets as the active material, and an exposure of
1.98+-0.19 kgd, no evidence for a WIMP signal was found. For a WIMP mass of 29
GeV/c2, limits on the spin-dependent cross section on protons of sigma_p = 1.31
pb and on neutrons of sigma_n = 21.5 pb have been obtained at 90% C.L. In both
cases, some new parameter space in the region of WIMP masses below 20 GeV/c2
has now been ruled out. The results of these measurements are also presented in
terms of limits on the effective WIMP-proton and neutron coupling strengths a_p
and a_n.
|
Several aspects of the recently proposed DMC-CIPSI approach consisting in
using selected Configuration Interaction (SCI) approaches such as CIPSI
(Configuration Interaction using a Perturbative Selection done Iteratively) to
build accurate nodes for diffusion Monte Carlo (DMC) calculations are presented
and discussed. The main ideas are illustrated with a number of calculations for
diatomics molecules and for the benchmark G1 set.
|
We propose a generalization of the linked-cluster expansions to study
driven-dissipative quantum lattice models, directly accessing the thermodynamic
limit of the system. Our method leads to the evaluation of the desired
extensive property onto small connected clusters of a given size and topology.
We first test this approach on the isotropic spin-1/2 Hamiltonian in two
dimensions, where each spin is coupled to an independent environment that
induces incoherent spin flips. Then we apply it to the study of an anisotropic
model displaying a dissipative phase transition from a magnetically ordered to
a disordered phase. By means of a Pad\'e analysis on the series expansions for
the average magnetization, we provide a viable route to locate the phase
transition and to extrapolate the critical exponent for the magnetic
susceptibility.
|
We study the effect of critical fluctuations on the $(B,T)$ phase diagram in
extreme type-II superconductors in zero and finite magnetic field using
large-scale Monte Carlo simulations on the Ginzburg-Landau model in a frozen
gauge approximation. We show that a vortex-loop unbinding gives a correct
picture of the zero field superconducting-normal transition even in the
presence of amplitude fluctuations, which are far from being critical at $T_c$.
We extract critical exponents of the dual model by studying the topological
excitations of the original model. From the vortex-loop distribution function
we extract the anomalous dimension of the dual field $\eta \simeq -0.18$, and
conclude that the charged Ginzburg-Landau model and the neutral 3DXY model
belong to different universality classes. We find are two distinct scaling
regimes for the vortex-line lattice melting line: a high-field scaling regime
and a distinct low-field 3DXY critical scaling regime. We also find indications
of an abrupt change in the connectivity of the vortex-tangle in the vortex
liquid along a line $T_L \geq T_M$. This is the finite field counter-part of
the zero-field vortex-loop blowout. Which at low enough fields appears to
coincide with $T_M$. Here, a description of the vortex system only in terms of
field induced vortex lines is inadequate at and above the VLL melting
temperature.
|
Quantum devices formed in high-electron-mobility semiconductor
heterostructures provide a route through which quantum mechanical effects can
be exploited on length scales accessible to lithography and integrated
electronics. The electrostatic definition of quantum dots in semiconductor
heterostructure devices intrinsically involves the lithographic fabrication of
intricate patterns of metallic electrodes. The formation of metal/semiconductor
interfaces, growth processes associated with polycrystalline metallic layers,
and differential thermal expansion produce elastic distortion in the active
areas of quantum devices. Understanding and controlling these distortions
presents a significant challenge in quantum device development. We report
synchrotron x-ray nanodiffraction measurements combined with dynamical x-ray
diffraction modeling that reveal lattice tilts with a depth-averaged value up
to 0.04 deg. and strain on the order of 10^-4 in the two-dimensional electron
gas (2DEG) in a GaAs/AlGaAs heterostructure. Elastic distortions in GaAs/AlGaAs
heterostructures modify the potential energy landscape in the 2DEG due to the
generation of a deformation potential and an electric field through the
piezoelectric effect. The stress induced by metal electrodes directly impacts
the ability to control the positions of the potential minima where quantum dots
form and the coupling between neighboring quantum dots.
|
Owing to both electronic and dielectric confinement effects, two-dimensional
organic-inorganic hybrid perovskites sustain strongly bound excitons at room
temperature. Here, we demonstrate that there are non-negligible contributions
to the excitonic correlations that are specific to the lattice structure and
its polar fluctuations, both of which are controlled via the chemical nature of
the organic counter-cation. We present a phenomenological, yet quantitative
framework to simulate excitonic absorption lineshapes in single-layer
organic-inorganic hybrid perovskites, based on the two-dimensional Wannier
formalism. We include four distinct excitonic states separated by
$35\pm5$\,meV, and additional vibronic progressions. Intriguingly, the
associated Huang-Rhys factors and the relevant phonon energies show substantial
variation with temperature and the nature of the organic cation. This points to
the hybrid nature of the lineshape, with a form well described by a Wannier
formalism, but with signatures of strong coupling to localized vibrations, and
polaronic effects perceived through excitonic correlations. Our work highlights
the complexity of excitonic properties in this class of nanostructured
materials.
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We introduce a shortcut to the adiabatic gate teleportation model of quantum
computation. More specifically, we determine fast local counterdiabatic
Hamiltonians able to implement teleportation as a universal computational
primitive. In this scenario, we provide the counterdiabatic driving for
arbitrary n-qubit gates, which allows to achieve universality through a variety
of gate sets. Remarkably, our approach maps the superadiabatic Hamiltonian for
an arbitrary n-qubit gate teleportation into the implementation of a rotated
superadiabatic dynamics of an n-qubit state teleportation. This result is
rather general, with the speed of the evolution only dictated by the quantum
speed limit. In particular, we analyze the energetic cost for different
Hamiltonian interpolations in the context of the energy-time complementarity.
|
This paper aims to discuss and analyze the potentialities of Recurrent Neural
Networks (RNN) in control design applications. The main families of RNN are
considered, namely Neural Nonlinear AutoRegressive eXogenous, (NNARX), Echo
State Networks (ESN), Long Short Term Memory (LSTM), and Gated Recurrent Units
(GRU). The goal is twofold. Firstly, to survey recent results concerning the
training of RNN that enjoy Input-to-State Stability (ISS) and Incremental
Input-to-State Stability ($\delta$ISS) guarantees. Secondly, to discuss the
issues that still hinder the widespread use of RNN for control, namely their
robustness, verifiability, and interpretability. The former properties are
related to the so-called generalization capabilities of the networks, i.e.
their consistency with the underlying real plants, even in presence of unseen
or perturbed input trajectories. The latter is instead related to the
possibility of providing a clear formal connection between the RNN model and
the plant. In this context, we illustrate how ISS and $\delta$ISS represent a
significant step towards the robustness and verifiability of the RNN models,
while the requirement of interpretability paves the way to the use of
physics-based networks. The design of model predictive controllers with RNN as
plant's model is also briefly discussed. Lastly, some of the main topics of the
paper are illustrated on a simulated chemical system.
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A graph pair $(\Gamma, \Sigma)$ is called stable if
$\aut(\Gamma)\times\aut(\Sigma)$ is isomorphic to $\aut(\Gamma\times\Sigma)$
and unstable otherwise, where $\Gamma\times\Sigma$ is the direct product of
$\Gamma$ and $\Sigma$. A graph is called $R$-thin if distinct vertices have
different neighbourhoods. $\Gamma$ and $\Sigma$ are said to be coprime if there
is no nontrivial graph $\Delta$ such that $\Gamma \cong \Gamma_1 \times \Delta$
and $\Sigma \cong \Sigma_1 \times \Delta$ for some graphs $\Gamma_1$ and
$\Sigma_1$. An unstable graph pair $(\Gamma, \Sigma)$ is called nontrivially
unstable if $\Gamma$ and $\Sigma$ are $R$-thin connected coprime graphs and at
least one of them is non-bipartite. This paper contributes to the study of the
stability of graph pairs with a focus on the case when $\Sigma = C_n$ is a
cycle. We give two sufficient conditions for $(\Gamma, C_n)$ to be nontrivially
unstable, where $n \ne 4$ and $\Gamma$ is an $R$-thin connected graph. In the
case when $\Gamma$ is an $R$-thin connected non-bipartite graph, we obtain the
following results: (i) if $(\Gamma, K_2)$ is unstable, then $(\Gamma, C_{n})$
is unstable for every even integer $n \geq 4$; (ii) if an even integer $n \ge
6$ is compatible with $\Gamma$ in some sense, then $(\Gamma, C_{n})$ is
nontrivially unstable if and only if $(\Gamma, K_2)$ is unstable; (iii) if
there is an even integer $n \ge 6$ compatible with $\Gamma$ such that $(\Gamma,
C_{n})$ is nontrivially unstable, then $(\Gamma, C_{m})$ is unstable for all
even integers $m \ge 6$. We also prove that if $\Gamma$ is an $R$-thin
connected graph and $n \ge 3$ is an odd integer compatible with $\Gamma$, then
$(\Gamma, C_{n})$ is stable.
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We present a new method of training energy-based models (EBMs) for anomaly
detection that leverages low-dimensional structures within data. The proposed
algorithm, Manifold Projection-Diffusion Recovery (MPDR), first perturbs a data
point along a low-dimensional manifold that approximates the training dataset.
Then, EBM is trained to maximize the probability of recovering the original
data. The training involves the generation of negative samples via MCMC, as in
conventional EBM training, but from a different distribution concentrated near
the manifold. The resulting near-manifold negative samples are highly
informative, reflecting relevant modes of variation in data. An energy function
of MPDR effectively learns accurate boundaries of the training data
distribution and excels at detecting out-of-distribution samples. Experimental
results show that MPDR exhibits strong performance across various anomaly
detection tasks involving diverse data types, such as images, vectors, and
acoustic signals.
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We investigate the Landau-Zener tunneling (LZT) of a self-interacting
two-level system in which the coupling between the levels is nonreciprocal. In
such a non-Hermitian system, when the energy bias between two levels is
adjusted very slowly, i.e., in the adiabatic limit, we find that a quantum
state can still closely follow the eigenstate solution until it encounters the
exceptional points (EPs) at which two eigenvalues and their corresponding
eigenvectors coalesce. In the absence of the nonlinear self-interaction, we can
obtain explicit expressions for the eigenvectors and eigenvalues and
analytically derive the adiabatic LZT probability from invariants at EPs. In
the presence of the nonlinear interaction, the dynamics of the adiabatic
evolutions are explicitly demonstrated with the help of classical trajectories
in the plane of the two canonical variables of the corresponding classical
Josephson Hamiltonian. We show that the adiabatic tunneling probabilities can
be precisely predicted by the classical action at EPs in the weak nonreciprocal
regime. In a certain region of strong nonreciprocity, we find that
interestingly, the nonlinear interaction effects can be completely suppressed
so that the adiabatic tunneling probabilities are identical to their linear
counterparts. We also obtain a phase diagram for large ranges of nonreciprocity
and nonlinear interaction parameters to explicitly demonstrate where the
adiabaticity can break down, i.e., the emergence of the nonzero tunneling
probabilities even in adiabatic limit.
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For conforming finite element approximations of the Laplacian eigenfunctions,
a fully computable guaranteed error bound in the $L^2$ norm sense is proposed.
The bound is based on the a priori error estimate for the Galerkin projection
of the conforming finite element method, and has an optimal speed of
convergence for the eigenfunctions with the worst regularity. The resulting
error estimate bounds the distance of spaces of exact and approximate
eigenfunctions and, hence, is robust even in the case of multiple and tightly
clustered eigenvalues. The accuracy of the proposed bound is illustrated by
numerical examples. The demonstration code is available at
https://ganjin.online/xfliu/EigenfunctionEstimation4FEM .
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This issue discusses the fault-trajectory approach suitability for fault
diagnosis on analog networks. Recent works have shown promising results
concerning a method based on this concept for ATPG for diagnosing faults on
analog networks. Such method relies on evolutionary techniques, where a generic
algorithm (GA) is coded to generate a set of optimum frequencies capable to
disclose faults.
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Exploiting a topological soliton on a hypersphere, we construct nucleon
charge profile functions and find the density distributions for proton and
neutron plotted versus the hypersphere third angle $\mu$. The neutron charge
density is shown to possess a nontrivial $\mu$ dependence, consisting of both
positive and negative charge density fractions. We next investigate the inner
topology of the hypersphere soliton, by making use of the schematic M\"obius
strips which are related with the tubular neighborhood of half-twist circle in
the manifold $S^{3}$. In particular, we find that in the hypersphere soliton
the nucleons are delineated in terms of a knot structure of two M\"obius strip
type circles in $S^{3}$. Moreover, the two Hopf-linked M\"obius strip type
circles in the hypersphere soliton are shown to correspond to (uu, d) in proton
and (dd, u) in neutron, respectively, in the quark model.
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Existing approaches for 3D garment reconstruction either assume a predefined
template for the garment geometry (restricting them to fixed clothing styles)
or yield vertex colored meshes (lacking high-frequency textural details). Our
novel framework co-learns geometric and semantic information of garment surface
from the input monocular image for template-free textured 3D garment
digitization. More specifically, we propose to extend PeeledHuman
representation to predict the pixel-aligned, layered depth and semantic maps to
extract 3D garments. The layered representation is further exploited to UV
parametrize the arbitrary surface of the extracted garment without any human
intervention to form a UV atlas. The texture is then imparted on the UV atlas
in a hybrid fashion by first projecting pixels from the input image to UV space
for the visible region, followed by inpainting the occluded regions. Thus, we
are able to digitize arbitrarily loose clothing styles while retaining
high-frequency textural details from a monocular image. We achieve
high-fidelity 3D garment reconstruction results on three publicly available
datasets and generalization on internet images.
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The problem of reconstructing a sparse signal vector from magnitude-only
measurements (a.k.a., compressive phase retrieval), emerges naturally in
diverse applications, but it is NP-hard in general. Building on recent advances
in nonconvex optimization, this paper puts forth a new algorithm that is termed
compressive reweighted amplitude flow and abbreviated as CRAF, for compressive
phase retrieval. Specifically, CRAF operates in two stages. The first stage
seeks a sparse initial guess via a new spectral procedure. In the second stage,
CRAF implements a few hard thresholding based iterations using reweighted
gradients. When there are sufficient measurements, CRAF provably recovers the
underlying signal vector exactly with high probability under suitable
conditions. Moreover, its sample complexity coincides with that of the
state-of-the-art procedures. Finally, substantial simulated tests showcase
remarkable performance of the new spectral initialization, as well as improved
exact recovery relative to competing alternatives.
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In this work, we focus on the task of generating SPARQL queries from natural
language questions, which can then be executed on Knowledge Graphs (KGs). We
assume that gold entity and relations have been provided, and the remaining
task is to arrange them in the right order along with SPARQL vocabulary, and
input tokens to produce the correct SPARQL query. Pre-trained Language Models
(PLMs) have not been explored in depth on this task so far, so we experiment
with BART, T5 and PGNs (Pointer Generator Networks) with BERT embeddings,
looking for new baselines in the PLM era for this task, on DBpedia and Wikidata
KGs. We show that T5 requires special input tokenisation, but produces state of
the art performance on LC-QuAD 1.0 and LC-QuAD 2.0 datasets, and outperforms
task-specific models from previous works. Moreover, the methods enable semantic
parsing for questions where a part of the input needs to be copied to the
output query, thus enabling a new paradigm in KG semantic parsing.
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A new discrete symmetry is shown to govern and simplify low-energy properties
of the supersymmetric N=2 gauge theory with an arbitrary gauge group. Each
element of the related symmetry group S_r, r being the rank of the gauge group,
represents a permutation of r electric charges available in the theory
accompanied by a concurrent permutation of r monopoles, provided the sets of
charges and monopoles are chosen properly. The superpotential is symmetric
under S_r. This symmetry strongly manifests itself for the degenerate case;
when the masses of r electric charges are chosen to be equal, then the masses
of r monopoles are necessarily degenerate as well, and vice versa. This
condition uniquely defines the vital for the theory VEV of the scalar field,
which makes all monopoles massless.
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Massive gas outflows are considered a key component in the process of galaxy
formation and evolution. It is, therefore, not surprising that a lot of effort
is going in quantifying their impact via detailed observations. This short
contribution presents recent results obtained from HI and CO observations of
different objects where the AGN - and in particular the radio jet - is likely
playing an important role in producing the gas outflows. These preliminary
results are reinforcing the conclusion that these outflows have a complex and
multiphase structure where cold gas in different phases (atomic and molecular)
is involved and likely represent a major component. These results will also
provide important constraints for establishing how the interaction between
AGN/radio jet and the surrounding ISM occurs and how efficiently the gas should
cool to produce the observed properties of the outflowing gas. HI likely
represents an intermediate phase in this process, while the molecular gas would
be the final stage. Whether the estimated outflow masses match what expected
from simulations of galaxy formation, it is still far from clear.
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Decision makers are often confronted with complex tasks which cannot be
solved by an individual alone, but require collaboration in the form of a
coalition. Previous literature argues that instability, in terms of the
re-organization of a coalition with respect to its members over time, is
detrimental to performance. Other lines of research, such as the dynamic
capabilities framework, challenge this view. Our objective is to understand the
effects of instability on the performance of coalitions which are formed to
solve complex tasks. In order to do so, we adapt the NK-model to the context of
human decision-making in coalitions, and introduce an auction-based mechanism
for autonomous coalition formation and a learning mechanism for human agents.
Preliminary results suggest that re-organizing innovative and well-performing
teams is beneficial, but that this is true only in certain situations.
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We have studied the dynamics of morphology-dependent resonances by openness
in a dielectric microdisk for TE polarization. For the first time, we report
that the dynamics exhibits avoided resonance crossings between inner and outer
resonances even though the corresponding billiard is integrable. Due to the
avoidance, inner and outer resonances can be exchanged and $Q$-factor of inner
resonances is strongly affected. We analyze the diverse phenomena aroused from
the dynamics including the avoided crossings.
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Off-policy evaluation (OPE) in reinforcement learning is an important problem
in settings where experimentation is limited, such as education and healthcare.
But, in these very same settings, observed actions are often confounded by
unobserved variables making OPE even more difficult. We study an OPE problem in
an infinite-horizon, ergodic Markov decision process with unobserved
confounders, where states and actions can act as proxies for the unobserved
confounders. We show how, given only a latent variable model for states and
actions, policy value can be identified from off-policy data. Our method
involves two stages. In the first, we show how to use proxies to estimate
stationary distribution ratios, extending recent work on breaking the curse of
horizon to the confounded setting. In the second, we show optimal balancing can
be combined with such learned ratios to obtain policy value while avoiding
direct modeling of reward functions. We establish theoretical guarantees of
consistency, and benchmark our method empirically.
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We show that the epimorphism problem is solvable for targets that are
virtually cyclic or a product of an Abelian group and a finite group.
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The GAM group velocity is estimated from the ratio of the radial free energy
flux to the total free energy applying gyrokinetic and two-fluid theory. This
method is much more robust than approaches that calculate the group velocity
directly and can be generalized to include additional physics, e.g. magnetic
geometry. The results are verified with the gyrokinetic code GYRO [J. Candy and
R. E. Waltz, J. Comp. Phys. 186, pp. 545-581 (2003)], the two-fluid code NLET
[K. Hallatschek and A. Zeiler, Physics of Plasmas 7, pp. 2554-2564 (2000)], and
analytical calculations. GAM propagation must be kept in mind when discussing
the windows of GAM activity observed experimentally and the match between
linear theory and experimental GAM frequencies.
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In the field of intracity freight transportation, changes in order volume are
significantly influenced by temporal and spatial factors. When building subsidy
and pricing strategies, predicting the causal effects of these strategies on
order volume is crucial. In the process of calculating causal effects,
confounding variables can have an impact. Traditional methods to control
confounding variables handle data from a holistic perspective, which cannot
ensure the precision of causal effects in specific temporal and spatial
dimensions. However, temporal and spatial dimensions are extremely critical in
the logistics field, and this limitation may directly affect the precision of
subsidy and pricing strategies. To address these issues, this study proposes a
technique based on flexible temporal-spatial grid partitioning. Furthermore,
based on the flexible grid partitioning technique, we further propose a
continuous entropy balancing method in the temporal-spatial domain, which named
TS-EBCT (Temporal-Spatial Entropy Balancing for Causal Continue Treatments).
The method proposed in this paper has been tested on two simulation datasets
and two real datasets, all of which have achieved excellent performance. In
fact, after applying the TS-EBCT method to the intracity freight transportation
field, the prediction accuracy of the causal effect has been significantly
improved. It brings good business benefits to the company's subsidy and pricing
strategies.
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The growth in the complexity of Convolutional Neural Networks (CNNs) is
increasing interest in partitioning a network across multiple accelerators
during training and pipelining the backpropagation computations over the
accelerators. Existing approaches avoid or limit the use of stale weights
through techniques such as micro-batching or weight stashing. These techniques
either underutilize of accelerators or increase memory footprint. We explore
the impact of stale weights on the statistical efficiency and performance in a
pipelined backpropagation scheme that maximizes accelerator utilization and
keeps memory overhead modest. We use 4 CNNs (LeNet-5, AlexNet, VGG and ResNet)
and show that when pipelining is limited to early layers in a network, training
with stale weights converges and results in models with comparable inference
accuracies to those resulting from non-pipelined training on MNIST and CIFAR-10
datasets; a drop in accuracy of 0.4%, 4%, 0.83% and 1.45% for the 4 networks,
respectively. However, when pipelining is deeper in the network, inference
accuracies drop significantly. We propose combining pipelined and non-pipelined
training in a hybrid scheme to address this drop. We demonstrate the
implementation and performance of our pipelined backpropagation in PyTorch on 2
GPUs using ResNet, achieving speedups of up to 1.8X over a 1-GPU baseline, with
a small drop in inference accuracy.
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Grammatical error correction (GEC) is a well-explored problem in English with
many existing models and datasets. However, research on GEC in morphologically
rich languages has been limited due to challenges such as data scarcity and
language complexity. In this paper, we present the first results on Arabic GEC
using two newly developed Transformer-based pretrained sequence-to-sequence
models. We also define the task of multi-class Arabic grammatical error
detection (GED) and present the first results on multi-class Arabic GED. We
show that using GED information as an auxiliary input in GEC models improves
GEC performance across three datasets spanning different genres. Moreover, we
also investigate the use of contextual morphological preprocessing in aiding
GEC systems. Our models achieve SOTA results on two Arabic GEC shared task
datasets and establish a strong benchmark on a recently created dataset. We
make our code, data, and pretrained models publicly available.
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We compare the burst distribution of the new (2B) BATSE catalogue to a
cosmological distribution. We find that the distribution is insensitive to
cosmological parameters such as Omega and Lambda and to the width of the bursts
luminosity function. The maximal red shift of the long bursts is ~2.1 (assuming
no evolution) while Zm(long) of the short bursts is significantly lower
Zm(short) =~ 0.5 In agreement with this relatively nearby origin of the short
burst we find an indication that these bursts are correlated ( >=2 sigma level
at 10 degrees) with Abell clusters. This is the first known correlation of the
bursts with any other astrophysical population and if confirmed by further
observations it will provides additional evidence for the cosmological origin
of those bursts.
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The stability and instability of quantum motion is studied in the context of
cavity quantum electrodynamics (QED). It is shown that the Jaynes-Cummings
dynamics can be unstable in the regime of chaotic walking of an atom in the
quantized field of a standing wave in the absence of any other interaction with
environment. This quantum instability manifests itself in strong variations of
quantum purity and entropy and in exponential sensitivity of fidelity of
quantum states to small variations in the atom-field detuning. It is quantified
in terms of the respective classical maximal Lyapunov exponent that can be
estimated in appropriate in-out experiments.
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We give new bounds for the number of integral points on elliptic curves. The
method may be said to interpolate between approaches via diophantine techniques
([BP], [HBR]) and methods based on quasiorthogonality in the Mordell-Weil
lattice ([Sil6], [GS], [He]). We apply our results to break previous bounds on
the number of elliptic curves of given conductor and the size of the 3-torsion
part of the class group of a quadratic field. The same ideas can be used to
count rational points on curves of higher genus.
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The intracluster medium of galaxy clusters is an extremely hot and diffuse,
nearly collisionless plasma, which hosts dynamically important magnetic fields
of $\sim \mu {\rm G}$ strength. Seed magnetic fields of much weaker strength of
astrophysical or primordial origin can be present in the intracluster medium.
In collisional plasmas, which can be approximated in the magneto-hydrodynamical
(MHD) limit, the turbulent dynamo mechanism can amplify weak seed fields to
strong dynamical levels efficiently by converting turbulent kinetic energy into
magnetic energy. However, the viability of this mechanism in weakly collisional
or completely collisionless plasma is much less understood. In this study, we
explore the properties of the collisionless turbulent dynamo by using
three-dimensional hybrid-kinetic particle-in-cell simulations. We explore the
properties of the collisionless turbulent dynamo in the kinematic regime for
different values of the magnetic Reynolds number, ${\rm Rm}$, initial
magnetic-to-kinetic energy ratio, $(E_{\rm{mag}}/E_{\rm{kin}})_{\rm{i}}$, and
initial Larmor ratio, $(r_{\rm Larmor}/L_{\rm box})_{\rm i}$, i.e., the ratio
of the Larmor radius to the size of the turbulent system. We find that in the
`un-magnetised' regime, $(r_{\rm Larmor}/L_{\rm box})_{\rm i} > 1$, the
critical magnetic Reynolds number for the dynamo action ${\rm Rm}_{\rm crit}
\approx 107 \pm 3$. In the `magnetised' regime, $(r_{\rm Larmor}/L_{\rm
box})_{\rm i} \lesssim 1$, we find a marginally higher ${\rm Rm}_{\rm crit} =
124 \pm 8$. We find that the growth rate of the magnetic energy does not depend
on the strength of the seed magnetic field when the initial magnetisation is
fixed. We also study the distribution and evolution of the pressure anisotropy
in the collisionless plasma and compare our results with the MHD turbulent
dynamo.
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We compare the BFKL prediction for the associated production of forward jets
at HERA with fixed-order matrix element calculations taking into account the
kinematical cuts imposed by experimental conditions. Comparison with H1 data of
the 1993 run favours the BFKL prediction. As a further signal of BFKL dynamics,
we propose to look for the azimuthal dependence of the forward jets.
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We determine projected rotation velocities v sini in DAZ white dwarfs, for
the first time using the rotational broadening of the CaII K line. The results
confirm previous findings that white dwarfs are very slow rotators, and set
even more stringent upper limits of typically less than 10 km/s. The few
exceptions include 3 stars known or suspected to be variable ZZ Ceti stars,
where the line broadening is very likely not due to rotation. The results
demonstrate that the angular momentum of the core cannot be preserved
completely between main sequence and final stage.
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Text-to-Face (TTF) synthesis is a challenging task with great potential for
diverse computer vision applications. Compared to Text-to-Image (TTI) synthesis
tasks, the textual description of faces can be much more complicated and
detailed due to the variety of facial attributes and the parsing of high
dimensional abstract natural language. In this paper, we propose a Text-to-Face
model that not only produces images in high resolution (1024x1024) with
text-to-image consistency, but also outputs multiple diverse faces to cover a
wide range of unspecified facial features in a natural way. By fine-tuning the
multi-label classifier and image encoder, our model obtains the vectors and
image embeddings which are used to transform the input noise vector sampled
from the normal distribution. Afterwards, the transformed noise vector is fed
into a pre-trained high-resolution image generator to produce a set of faces
with the desired facial attributes. We refer to our model as TTF-HD.
Experimental results show that TTF-HD generates high-quality faces with
state-of-the-art performance.
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We conducted an extensive CCD search for faint, unresolved dwarf galaxies of
very low surface brightness in the whole Centaurus group region encompassing
the Cen A and M 83 subgroups lying at a distance of roughly 4 and 5 Mpc,
respectively. The aim is to significantly increase the sample of known
Centaurus group members down to a fainter level of completeness, serving as a
basis for future studies of the 3D structure of the group. Following our
previous survey of 60 square degrees covering the M 83 subgroup, we extended
and completed our survey of the Centaurus group region by imaging another 500
square degrees area in the g and r bands with the wide-field Dark Energy Survey
Camera at the 4m Blanco telescope at CTIO. The limiting central surface
brightness reached for suspected Centaurus members is $\mu_r \approx 29$ mag
arcsec$^{-2}$, corresponding to an absolute magnitude $M_r \approx -9.5$. The
images were enhanced using different filtering techniques. We found 41 new
dwarf galaxy candidates, which together with the previously discovered 16 dwarf
candidates in the M 83 subgroup amounts to almost a doubling of the number of
known galaxies in the Centaurus complex, if the candidates are confirmed. We
carried out surface photometry in g and r, and report the photometric
parameters derived therefrom, for all new candidates as well as previously
known members in the surveyed area. The photometric properties of the
candidates, when compared to those of LG dwarfs and previously known Centaurus
dwarfs, suggest membership in the Centaurus group. The sky distribution of the
new objects is generally following a common envelope around the Cen A and M 83
subgroups. How the new dwarfs are connected to the intriguing double-planar
feature recently reported by Tully et al. (2015) must await distance
information for the candidates.
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We study the photon blockade of two-photon scattering in a one-dimensional
waveguide, which contains two atoms coupled via the Rydberg interaction. We
obtain the analytic scattering solution of photonic wave packets with the
Laplace transform method. We examine the photon correlation by addressing the
two-photon relative wave function and the second-order correlation function in
the single- and two-photon resonance cases. It is found that, under the
single-photon resonance condition, photon bunching and antibunching can be
observed in the two-photon transmission and reflection, respectively. In
particular, the bunching and antibunching effects become stronger with the
increasing of the Rydberg coupling strength. In addition, we find a phenomenon
of bunching-antibunching transition caused by the two-photon resonance.
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We present a modification of a recently developed volume of fluid method for
multiphase problems, so that it can be used in conjunction with a fractional
step-method and fast Poisson solver, and validate it with standard benchmark
problems. We then consider emulsions of two-fluid systems and study their
rheology in a plane Couette flow in the limit of vanishing inertia. We examine
the dependency of the effective viscosity on the volume-fraction (from 10% to
30%) and the Capillary number (from 0.1 to 0.4) for the case of density and
viscosity ratio 1. We show that the effective viscosity decreases with the
deformation and the applied shear (shear-thinning) while exhibits a
non-monotonic behavior with respect to the volume fraction. We report the
appearance of a maximum in the effective viscosity curve and compare the
results with those of suspensions of rigid and deformable particles and
capsules. We show that the flow in the solvent is mostly a shear flow, while it
is mostly rotational in the suspended phase; moreover this behavior tends to
reverse as the volume fraction increases. Finally, we evaluate the
contributions to the total shear stress of the viscous stresses in the two
fluids and of the interfacial force between them.
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Anderson's theorem states that non-magnetic impurities do not change the bulk
properties of conventional superconductors. However, as the dimensionality is
reduced, the effect of impurities becomes more significant. Here we investigate
superconducting nanowires with diameter less than the superconducting coherence
length by using a microscopic description based on the Bogoliubov-de Gennes
method. We find that: 1) impurities strongly affect the superconducting
properties, 2) the effect is impurity position-dependent, and 3) it exhibits
opposite behavior for resonant and off-resonant wire widths. We show that this
is due to the interplay between the shape resonances of the order parameter and
the sub-band energy spectrum induced by the lateral quantum confinement. These
effects can be used to manipulate the Josephson current, filter electrons by
subband and investigate the symmetries of the superconducting subbands.
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Domain walls in type I degenerate optical parametric oscillators are
numerically investigated. Both steady Ising and moving Bloch walls are found,
bifurcating one into another through a nonequilibrium Ising--Bloch transition.
Bloch walls are found that connect either homogeneous or roll planforms.
Secondary bifurcations affecting Bloch wall movement are characterized that
lead to a transition from a steady drift state to a temporal chaotic movement
as the system is moved far from the primary, Ising--Bloch bifurcation. Two
kinds of routes to chaos are found, both involving tori: a usual Ruelle-Takens
and an intermittent scenarios.
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