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A proposal to store unsteady energy in potential energy via lifting masses
with a rough quantitative overview. Some applications and methods to harvest
the potential energy are also given. A focus is put on photovoltaically
generated energy.
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In recent years, image captioning and segmentation have emerged as crucial
tasks in computer vision, with applications ranging from autonomous driving to
content analysis. Although multiple solutions have emerged to help blind and
visually impaired people move around their environment, few are applications
that help them understand and rebuild a scene in their minds through text. Most
built models focus on helping users move and avoid obstacles, restricting the
number of environments blind and visually impaired people can be in.
In this paper, we will propose an approach that helps them understand their
surroundings using image captioning. The particularity of our research is that
we offer them descriptions with positions of regions and objects regarding them
(left, right, front), as well as positional relationships between regions,
while we aim to give them access to theatre plays by applying the solution to
our TS-RGBD dataset.
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In this paper we investigate the electronic and magnetic properties of
K$_{x}$Fe$_{2-y}$Se$_{2}$ materials at different band fillings utilizing the
multi-orbital Kotliar-Ruckenstein's slave-boson mean field approach. We find
that at three-quarter filling, corresponding to KFe$_{2}$Se$_{2}$, the ground
state is a paramagnetic bad metal. Through band renormalization analysis and
comparison with the angle-resolved photoemission spectra data, we identify that
KFe$_{2}$Se$_{2}$ is also an intermediate correlated system, similar to
iron-pnictide systems. At two-third filling, corresponding to the
Fe$^{2+}$-based systems, the ground state is a striped antiferromagnetic (SAFM)
metal with spin density wave gap partially opened near the Fermi level. In
comparison, at half filling case, corresponding to the Fe$^{3+}$-based
compounds, besides SAFM, a $N\acute{e}el$ antiferromagnetic metallic ground
state without orbital ordering is observed in the intermediate correlation
range, and an orbital selective Mott phase (OSMP) accompanied with an
intermediate-spin to high-spin transition is also found. These results
demonstrate that the band filling and correlation control the electronic state,
Fermi surface topology and magnetism in K$_{x}$Fe$_{2-y}$Se$_{2}$.
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Transformer-based pre-trained language models such as BERT have achieved
remarkable results in Semantic Sentence Matching. However, existing models
still suffer from insufficient ability to capture subtle differences. Minor
noise like word addition, deletion, and modification of sentences may cause
flipped predictions. To alleviate this problem, we propose a novel Dual
Attention Enhanced BERT (DABERT) to enhance the ability of BERT to capture
fine-grained differences in sentence pairs. DABERT comprises (1) Dual Attention
module, which measures soft word matches by introducing a new dual channel
alignment mechanism to model affinity and difference attention. (2) Adaptive
Fusion module, this module uses attention to learn the aggregation of
difference and affinity features, and generates a vector describing the
matching details of sentence pairs. We conduct extensive experiments on
well-studied semantic matching and robustness test datasets, and the
experimental results show the effectiveness of our proposed method.
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Motivated by trapping and cooling experiments with non-spherical
nanoparticles, we discuss how their combined rotational and translational
quantum state is affected by the interaction with a gaseous environment. Based
on the quantum master equation in terms of orientation-dependent scattering
amplitudes, we evaluate the localization rate for gas collisions off an
anisotropic van der Waals-type potential and for photon scattering off an
anisotropic dielectric. We also show how pure angular momentum diffusion arises
from these open quantum dynamics in the limit of weak anisotropies.
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We have found that at least seven hydrogen-deficient carbon (HdC) and R
Coronae Borealis (RCB) stars, have 16O/18O ratios close to and in some cases
less than unity, values that are orders of magnitude lower than measured in
other stars (the Solar value is 500). Greatly enhanced 18O is evident in every
HdC and RCB we have measured that is cool enough to have detectable CO bands.
The three HdC stars measured have 16O/18O < 1, lower values than any of the RCB
stars. These discoveries are important clues in determining the evolutionary
pathways of HdC and RCB stars, for which two models have been proposed: the
double degenerate (white dwarf (WD) merger), and the final helium-shell flash
(FF). No overproduction of 18O is expected in the FF scenario. We have
quantitatively explored the idea that HdC and RCB stars originate in the
mergers of CO- and He-WDs. The merger process is estimated to take only a few
days, with accretion rates of 150 Msun/ yr producing temperatures at the base
of the accreted envelope of 1.2 - 1.9 x 10^8 K. Analysis of a simplified
one-zone calculation shows that nucleosynthesis in the dynamically accreting
material may provide a suitable environment for a significant production of
18O, leading to very low values of 16O/18O, similar to those observed. We also
find qualitative agreement with observed values of 12C/13C and with the CNO
elemental ratios. H-admixture during the accretion process from the small
H-rich C/O WD envelope may play an important role in producing the observed
abundances. Overall our analysis shows that WD mergers may very well be the
progenitors of O18-rich RCB and HdC stars, and that more detailed simulations
and modeling are justified.
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We propose an integrated photonics device for mapping qubits encoded in the
polarization of a photon onto the spin state of a solid-state defect coupled to
a photonic crystal cavity: a `Polarization-Encoded Photon-to-Spin Interface'
(PEPSI). We perform a theoretical analysis of the state fidelity's dependence
on the device's polarization extinction ratio and atom-cavity cooperativity.
Furthermore, we explore the rate-fidelity trade-off through analytical and
numerical models. In simulation, we show that our design enables efficient,
high fidelity photon-to-spin mapping.
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Large language models generate fluent texts and can follow natural language
instructions to solve a wide range of tasks without task-specific training.
Nevertheless, it is notoriously difficult to control their generation to
satisfy the various constraints required by different applications. In this
work, we present InstructCTG, a controlled text generation framework that
incorporates different constraints by conditioning on natural language
descriptions and demonstrations of the constraints. In particular, we first
extract the underlying constraints of natural texts through a combination of
off-the-shelf NLP tools and simple heuristics. We then verbalize the
constraints into natural language instructions to form weakly supervised
training data. By prepending natural language descriptions of the constraints
and a few demonstrations, we fine-tune a pre-trained language model to
incorporate various types of constraints. Compared to existing search-based or
score-based methods, InstructCTG is more flexible to different constraint types
and has a much smaller impact on the generation quality and speed because it
does not modify the decoding procedure. Additionally, InstructCTG allows the
model to adapt to new constraints without re-training through the use of
few-shot task generalization and in-context learning abilities of
instruction-tuned language models.
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The isoscalar and isovector particle densities and the surface tension
coefficients at the average binding energy are used to derive analytical
expressions of the neutron skin thickness and the isovector stiffness of sharp
edged proton-neutron asymmetric nuclei. For most Skyrme forces these quantities
are significantly larger than the well known ones. Using the analytical
isovector surface energy constants in the framework of the hydrodynamical and
the Fermi-liquid droplet models the mean energies and the sum rules of the
isovector giant dipole resonances are in fair agreement with the experimental
data.
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This is one of the two papers where the optimized perturbation theory was
first formulated. The other paper is published in Theor. Math. Phys. 28,
652--660 (1976). The main idea of the theory is to reorganize the perturbative
sequence by introducing control functions, defined by optimization conditions,
so that the reorganized approximation sequence be convergent. In the present
paper, the theory of perturbations is suggested for statistical systems in the
absence of small interaction parameters. A new form is advanced for
self-consistent conditions defining the optimal parameters for trial Green
functions in iterating nonlinear propagator equations. Superharmonic,
semiharmonic, and pseudoharmonic approximations for a molecular crystal are
considered as examples.
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We consider the general procedure for proving no-hair theorems for static,
spherically symmetric black holes. We apply this method to the abelian Higgs
model and find a proof of the no-hair conjecture that circumvents the
objections raised against the original proof due to Adler and Pearson.
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I suggest an effective model between the GUT and the electroweak scale. It
only introduces the two symmetries of $U(1)_{B-L}$ and $U(1)_{D}$ besides the
SM groups. The two symmetries are individually broken at the reheating
temperature of the universe of $10^{12}$ GeV and the scale of $3\sim 4$ TeV.
The model can simultaneously accommodate the tiny neutrino masses, the
matter-antimatter asymmetry and the cold dark matter (CDM). In particular, the
model gives some interesting results and predictions, for instance, the
neutrinos are Dirac nature and their masses are related to the $U(1)_{D}$
breaking, the size of the matter-antimatter asymmetry is closely related to the
mass hierarchy of the quarks and charged leptons, the CDM mass is probably in
the range of $250\sim 350$ GeV. Finally, it is feasible to test the model in
future collider experiments.
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The emergence of quantum-gravity induced corrective terms for the probability
of emission of a particle from a black hole in the Parikh-Wilczek tunneling
framework is studied. It is shown, in particular, how corrections might arise
from modifications of the surface gravity due to near horizon Planck-scale
effects. Our derivation provides an example of the possible linking between
Planck-scale departures from Lorentz invariance and the appearance of higher
order quantum gravity corrections in the black-hole entropy-area relation.
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We present the results of the ethynyl (C2H) emission line observations
towards the HII regions S255 and S257 and the molecular cloud between them.
Radial profiles of line brightness, column density, and abundance of C2H are
obtained. We show that the radial profile of the ethynyl abundance is almost
flat towards the HII regions and drops by a factor of two towards the molecular
cloud. At the same time, we find that the abundance of ethynyl is at maximum
towards the point sources in the molecular cloud -- the stars with emission
lines or emitting in X-ray. The line profiles are consistent with the
assumption that both HII regions have front and back neutral walls that move
relative to each other.
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We characterize the smallest codimension components of the Hodge locus of
smooth degree $d$ hypersurfaces of the projective space $\mathbb{P}^{n+1}$ of
even dimension $n$, passing through the Fermat variety (with $d\neq 3,4,6$).
They correspond to the locus of hypersurfaces containing a linear algebraic
cycle of dimension $\frac{n}{2}$. Furthermore, we prove that among all the
local Hodge loci associated to a non-linear cycle passing through Fermat, the
ones associated to a complete intersection cycle of type $(1,1,\ldots,1,2)$
attain the minimal possible codimension of their Zariski tangent spaces. This
answers a conjecture of Movasati, and generalizes a result of Voisin about the
first gap between the codimension of the components of the Noether-Lefschetz
locus to arbitrary dimension, provided that they contain the Fermat variety.
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We consider two simple models for the formation of polymers where at the
initial time, each monomer has a certain number of potential links (called arms
in the text) that are consumed when aggregations occur. Loosely speaking, this
imposes restrictions on the number of aggregations. The dynamics of
concentrations are governed by modifications of Smoluchowski's coagulation
equations. Applying classical techniques based on generating functions,
resolution of quasi-linear PDE's, and Lagrange inversion formula, we obtain
explicit solutions to these non-linear systems of ODE's. We also discuss the
asymptotic behavior of the solutions and point at some connexions with certain
known solutions to Smoluchowski's coagulation equations with additive or
multiplicative kernels.
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The field-dependent equilibrium thermodynamics is derived with two methods:
either by using the potential formalism either by the statistical method.
Therefore, Pontrjagin's extremum principle of control theory is applied to an
extended ensemble average. This approach allows to derive the grand partition
function of thermodynamics as a result of a control problem with the Hamilton
energy. Furthermore, the maximum entropy principle follows and the second law
in a modified form. The derivation can predict second law violations if cycles
with irreversibilities in varying potential fields are included into
consideration. This conclusion is supported indirectly by experimental data
from literature. The upper maximum gain efficiency of a cycle with a known
polymer solution as dielectrics was estimated to less than 1 promille per
cycle. Note added in proof 28th October 2003: Comparing this preprint work with
an analogous ferrofluidic system discrepancies are is found which show that the
concrete model proposed here in section 4 is insufficient to settle the
question. A way to solve the problem is proposed.
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The first non-trivial case of Hadwiger's conjecture for oriented matroids
reads as follows. If $\mathcal{O}$ is an $M(K_4)$-free oriented matroid, then
$\mathcal{O}$ admits a NZ $3$-coflow, i.e., it is $3$-colourable in the sense
of Hochst\"attler-Ne\v{s}et\v{r}il. The class of gammoids is a class of
$M(K_4)$-free orientable matroids and it is the minimal minor-closed class that
contains all transversal matroids. Towards proving the previous statement for
the class of gammoids, Goddyn, Hochst\"attler, and Neudauer conjectured that
every gammoid has a positive coline (equivalently, a positive double circuit),
which implies that all orientations of gammoids are $3$-colourable. In this
brief note we disprove Goddyn, Hochst\"attler, and Neudauers' conjecture by
exhibiting a large class of bicircular matroids that do not contain positive
double circuits.
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The calculation of the heating rate of cold atoms in vibrating traps requires
a theory that goes beyond the Kubo linear response formulation. If a strong
"quantum chaos" assumption does not hold, the analysis of transitions shows
similarities with a percolation problem in energy space. We show how the
texture and the sparsity of the perturbation matrix, as determined by the
geometry of the system, dictate the result. An improved sparse random matrix
model is introduced: it captures the essential ingredients of the problem, and
leads to a generalized variable range hopping picture.
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A semiconductor quantum dot (QD) embedded within an optical microcavity is a
system of fundamental importance within quantum information processing. The
optimization of quantum coherence is crucial in such applications, requiring an
in-depth understanding of the relevant decoherence mechanisms. We provide
herein a critical review of prevalent theoretical treatments of the QD-cavity
system coupled to longitudinal acoustic phonons, comparing predictions against
a recently obtained exact solution. Within this review we consider a range of
temperatures and exciton-cavity coupling strengths. Predictions of the polaron
Nakajima-Zwanzig (NZ) and time-convolutionless (TCL) master equations, as well
as a variation of the former adapted for adiabatic continuous wave excitation
(CWE), are compared against an asymptotically exact solution based upon
Trotter's decomposition (TD) theorem. The NZ and TCL implementations, which
apply a polaron transformation to the Hamiltonian and subsequently treat the
exciton-cavity coupling to second order, do not offer a significant improvement
accuracy relative to the polaron transformation alone. The CWE adaptation
provides a marked improvement, capturing the broadband features of the
absorption spectrum (not present in NZ and TCL implementations). We attribute
this difference to the effect of the Markov approximation, and particularly its
unsuitability in pulsed excitation regime. Even the CWE adaptation, however,
breaks down in the regime of high temperature ($50K$) and strong exciton-cavity
coupling ($g \gtrsim 0.2$ meV). The TD solution is of comparable computational
complexity to the above-mentioned master equation approaches, yet remains
accurate at higher temperatures and across a broad range of exciton-cavity
coupling strengths (at least up to $g=1.5$ meV).
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These notes are the second part of a common course on Renormalization Theory
given with Professor P. da Veiga at X Jorge Andre Swieca Summer School, Aguas
de Lindoia, Brazil, February 7-12, 1999. I emphasize the rigorous
non-perturbative or constructive aspects of the theory. The usual formalism for
the renormalization group in field theory or statistical mechanics is reviewed,
together with its limits. The constructive formalism is introduced step by
step. Taylor forest formulas allow to perform easily the cluster and Mayer
expansions which are needed for a single step of the renormalization group in
the case of Bosonic theories. The iteration of this single step leads to
further difficulties whose solution is briefly sketched. The second part of the
course is devoted to Fermionic models. These models are easier to treat on the
constructive level, so they are very well suited to beginners in constructive
theory. It is shown how the Taylor forest formulas allow to reorganize
perturbation theory nicely in order to construct the Gross-Neveu2 model without
any need for cluster or Mayer expansions. Finally applications of this
technique to condensed matter and renormalization group around Fermi surface
are briefly reviewed.
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In this article, we study the blow-up of the damped wave equation in the
\textit{scale-invariant case} and in the presence of two nonlinearities. More
precisely, we consider the following equation: $$u_{tt}-\Delta
u+\frac{\mu}{1+t}u_t=|u_t|^p+|u|^q, \quad \mbox{in}\ \R^N\times[0,\infty), $$
with small initial data.\\ For $\mu < \frac{N(q-1)}{2}$ and $\mu \in (0,
\mu_*)$, where $\mu_*>0$ is depending on the nonlinearties' powers and the
space dimension ($\mu_*$ satisfies $(q-1)\left((N+2\mu_*-1)p-2\right) = 4$), we
prove that the wave equation, in this case, behaves like the one without
dissipation ($\mu =0$). Our result completes the previous studies in the case
where the dissipation is given by $\frac{\mu}{(1+t)^\beta}u_t; \ \beta >1$
(\cite{LT3}), where, contrary to what we obtain in the present work, the effect
of the damping is not significant in the dynamics. Interestingly, in our case,
the influence of the damping term $\frac{\mu}{1+t}u_t$ is important.
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In higher Landau levels ($N>1$), the ground state of the two-dimensional
electron gas in a strong perpendicular magnetic field evolves from a Wigner
crystal for small filling $\nu $ of the partially filled Landau level, into a
succession of bubble states with increasing number of guiding centers per
bubble as $\nu $ increases, to a modulated stripe state near $\nu =0.5$. In
this work, we compute the frequency-dependent longitudinal conductivity $%
\sigma_{xx}(\omega) $ of the Wigner and bubble crystal states in the presence
of disorder. We apply an elastic theory to the crystal states which is
characterized by a shear and a bulk modulus. We obtain both moduli from the
microscopic time-dependent Hartree-Fock approximation. We then use the replica
and Gaussian variational methods to handle the effects of disorder. Within the
semiclassical approximation we get the dynamical conductivity as well as the
pinning frequency as functions of the Landau level filling factor and compare
our results with recent microwave experiments.
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The phase structure of the Nambu -- Jona-Lasinio model at zero temperature
and in the presence of baryon- and isospin chemical potentials is investigated.
It is shown that in the chiral limit and for a wide range of model parameters
there exist two different phases with pion condensation. In the first, ordinary
phase, quarks are gapped particles. In the second, gapless pion condensation
phase, there is no energy cost for creating only $u$- or both $u$ and $d$
quarks, and the density of baryons is nonzero.
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Random walk is one of the basic mechanisms found in many network
applications. We study the epidemic spreading dynamics driven by biased random
walks on complex networks. In our epidemic model, each time infected nodes
constantly spread some infected packets by biased random walks to their
neighbor nodes causing the infection of the susceptible nodes that receive the
packets. An infected node get recovered from infection with a fixed
probability. Simulation and analytical results on model and real-world networks
show that the epidemic spreading becomes intense and wide with the increase of
delivery capacity of infected nodes, average node degree, homogeneity of node
degree distribution. Furthermore, there are corresponding optimal parameters
such that the infected nodes have instantaneously the largest population, and
the epidemic spreading process covers the largest part of a network.
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Observations on galactic scales seem to be in contradiction with recent high
resolution N-body simulations. This so-called cold dark matter (CDM) crisis has
been addressed in several ways, ranging from a change in fundamental physics by
introducing self-interacting cold dark matter particles to a tuning of complex
astrophysical processes such as global and/or local feedback. All these efforts
attempt to soften density profiles and reduce the abundance of satellites in
simulated galaxy halos. In this paper, we explore a somewhat different approach
which consists of filtering the dark matter power spectrum on small scales,
thereby altering the formation history of low mass objects. The physical
motivation for damping these fluctuations lies in the possibility that the dark
matter particles have a different nature i.e. are warm (WDM) rather than cold.
We show that this leads to some interesting new results in terms of the merger
history and large-scale distribution of low mass halos, as compared to the
standard CDM scenario. However, WDM does not appear to be the ultimate
solution, in the sense that it is not able to fully solve the CDM crisis, even
though one of the main drawbacks, namely the abundance of satellites, can be
remedied. Indeed, the cuspiness of the halo profiles still persists, at all
redshifts, and for all halos and sub-halos that we investigated. Despite the
persistence of the cuspiness problem of DM halos, WDM seems to be still worth
taking seriously, as it alleviates the problems of overabundant sub-structures
in galactic halos and possibly the lack of angular momentum of simulated disk
galaxies. WDM also lessens the need to invoke strong feedback to solve these
problems, and may provide a natural explanation of the clustering properties
and ages of dwarfs.
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It is shown that wave function renormalization can introduce an important
contribution to the generation of baryon and lepton number asymmetries by heavy
particle decay. These terms, omitted in previous analyses, are of the same
order of magnitude as the standard terms. A complete cancellation of leading
terms can result in some interesting cases.
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Difference equations, such as a Ricker map, for an increased value of the
parameter, experience instability of the positive equilibrium and transition to
deterministic chaos. To achieve stabilization, various methods can be applied.
Proportional Feedback control suggests a proportional reduction of the state
variable at every $k$th step. First, if $k \neq 1$, a cycle is stabilized
rather than an equilibrium. Second, the equation can incorporate an additive
noise term, describing the variability of the environment, as well as
multiplicative noise corresponding to possible deviations in the control
intensity. The present paper deals with both issues, it justifies a possibility
of getting a stable blurred $k$-cycle. Presented examples include the Ricker
model, as well as equations with unbounded $f$, such as the bobwhite quail
population models. Though the theoretical results justify stabilization for
either multiplicative or additive noise only, numerical simulations illustrate
that a blurred cycle can be stabilized when both multiplicative and additive
noises are involved.
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The braneworld cosmology, in which our universe is imbedded as a hypersurface
in a higher dimensional bulk, has the peculiar property that the inflationary
consistency relation derived in a four-dimensional cosmology persists. This
consistency condition relates the ratio of tensor and scalar perturbation
amplitudes to the tensor spectral index produced during an epoch of slow-roll
scalar field inflation. We attempt to clarify this surprising degeneracy. Our
argument involves calculating the power spectrum of scalar field fluctuations
around geometries perturbed away from the exact de Sitter case. This
calculation is expected to be valid for perturbations which would not cause a
late-time acceleration of the universe. We use these results to argue that the
emergence of the same consistency relation in the braneworld can be connected
with a specific property, that five-dimensional observables smoothly approach
their four-dimensional counterparts as one takes the brane to infinite tension.
We exhibit an explicit example where this does not occur, and in which a
consistency relation does not persist.
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Entangled states, like the two-mode squeezed vacuum state, are known to give
quantum advantage in the illumination protocol, a method to detect a weakly
reflecting target submerged in a thermal background. We use non-Gaussian
photon-added and -subtracted states, affected by local Gaussian noise on top of
the omnipresent thermal noise, as probes in the illumination protocol. Based on
the difference between the Chernoff bounds obtained with the coherent state and
the non-Gaussian state having equal signal strengths, whose positive values
denote quantum advantage in illumination, we highlight the hierarchy among
non-Gaussian states, which is compatible with correlations per unit signal
strength, although the Gaussian states offer the best performance.
Interestingly, such hierarchy is different when comparisons are made using the
Chernoff bounds. The entire analysis is performed in the presence of different
imperfect apparatus like faulty twin-beam generator, imperfect photon addition
(subtraction) as well as with noisy non-Gaussian probe states.
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We introduce an approach to building a custom model from ready-made
self-supervised models via their associating instead of training and
fine-tuning. We demonstrate it with an example of a humanoid robot looking at
the mirror and learning to detect the 3D pose of its own body from the image it
perceives. To build our model, we first obtain features from the visual input
and the postures of the robot's body via models prepared before the robot's
operation. Then, we map their corresponding latent spaces by a sample-efficient
robot's self-exploration at the mirror. In this way, the robot builds the
solicited 3D pose detector, which quality is immediately perfect on the
acquired samples instead of obtaining the quality gradually. The mapping, which
employs associating the pairs of feature vectors, is then implemented in the
same way as the key-value mechanism of the famous transformer models. Finally,
deploying our model for imitation to a simulated robot allows us to study, tune
up, and systematically evaluate its hyperparameters without the involvement of
the human counterpart, advancing our previous research.
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Optical control of the lateral quantum confinement and number of electrons
confined in nanofabricated GaAs/AlGaAs quantum dots is achieved by illumination
with a weak laser beam that is absorbed in the AlGaAs barrier. Precise tuning
of energy-level structure and electron population is demonstrated by monitoring
the low-lying transitions of the electrons from the lowest quantum-dot energy
shells by resonant inelastic light scattering. These findings open the way to
the manipulation of single electrons in these quantum dots without the need of
external metallic gates.
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Video gaming streaming services are growing rapidly due to new services such
as passive video streaming, e.g. Twitch.tv, and cloud gaming, e.g. Nvidia
Geforce Now. In contrast to traditional video content, gaming content has
special characteristics such as extremely high motion for some games, special
motion patterns, synthetic content and repetitive content, which makes the
state-of-the-art video and image quality metrics perform weaker for this
special computer generated content. In this paper, we outline our plan to build
a deep learningbased quality metric for video gaming quality assessment. In
addition, we present initial results by training the network based on VMAF
values as a ground truth to give some insights on how to build a metric in
future. The paper describes the method that is used to choose an appropriate
Convolutional Neural Network architecture. Furthermore, we estimate the size of
the required subjective quality dataset which achieves a sufficiently high
performance. The results show that by taking around 5k images for training of
the last six modules of Xception, we can obtain a relatively high performance
metric to assess the quality of distorted video games.
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There are strong evidences in the literature that quantum non-Markovianity
would hinder the presence of Quantum Darwinism. In this Letter, we study the
relation between quantum Darwinism and approximate quantum Markovianity for
open quantum systems by exploiting the properties of quantum conditional mutual
information. We show that for approximately Markovian quantum processes the
conditional mutual information still has the scaling property for Quantum
Darwinism. Then two general bounds on the backflow of information are obtained,
with which we can show that the presence of Quantum Darwinism restricts the
information backflow and the quantum non-Markovianity must be small.
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In this paper we show that it is possible to derive the Kerr solution in an
alternative, intuitive way, based on physical reasoning and starting from an
orthogonal metric ansatz having manifest ellipsoidal space-time symmetry
(ellipsoidal symmetry). This is possible because both flat metric in oblate
spheroidal (ellipsoidal) coordinates and Kerr metric in Boyer-Lindquist
coordinates can be rewritten in such a form that the difference between the two
is only in the time-time and radial-radial metric tensor components, just as is
the case with Schwarzschild metric and flat metric in spherical coordinates.
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An important political and social phenomena discussed in several countries,
like India and Brazil, is the use of WhatsApp to spread false or misleading
content. However, little is known about the information dissemination process
in WhatsApp groups. Attention affects the dissemination of information in
WhatsApp groups, determining what topics or subjects are more attractive to
participants of a group. In this paper, we characterize and analyze how
attention propagates among the participants of a WhatsApp group. An attention
cascade begins when a user asserts a topic in a message to the group, which
could include written text, photos, or links to articles online. Others then
propagate the information by responding to it. We analyzed attention cascades
in more than 1.7 million messages posted in 120 groups over one year. Our
analysis focused on the structural and temporal evolution of attention cascades
as well as on the behavior of users that participate in them. We found specific
characteristics in cascades associated with groups that discuss political
subjects and false information. For instance, we observe that cascades with
false information tend to be deeper, reach more users, and last longer in
political groups than in non-political groups.
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Photo retouching aims at enhancing the aesthetic visual quality of images
that suffer from photographic defects such as over/under exposure, poor
contrast, inharmonious saturation. Practically, photo retouching can be
accomplished by a series of image processing operations. In this paper, we
investigate some commonly-used retouching operations and mathematically find
that these pixel-independent operations can be approximated or formulated by
multi-layer perceptrons (MLPs). Based on this analysis, we propose an extremely
light-weight framework - Conditional Sequential Retouching Network (CSRNet) -
for efficient global image retouching. CSRNet consists of a base network and a
condition network. The base network acts like an MLP that processes each pixel
independently and the condition network extracts the global features of the
input image to generate a condition vector. To realize retouching operations,
we modulate the intermediate features using Global Feature Modulation (GFM), of
which the parameters are transformed by condition vector. Benefiting from the
utilization of $1\times1$ convolution, CSRNet only contains less than 37k
trainable parameters, which is orders of magnitude smaller than existing
learning-based methods. Extensive experiments show that our method achieves
state-of-the-art performance on the benchmark MIT-Adobe FiveK dataset
quantitively and qualitatively. Code is available at
https://github.com/hejingwenhejingwen/CSRNet.
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Optical fibres have transformed the way people interact with the world and
now permeate many areas of science. Optical fibres are traditionally thought of
as insensitive to magnetic fields, however many application areas from mining
to biomedicine would benefit from fibre-based remote magnetometry devices. In
this work, we realise such a device by embedding nanoscale magnetic sensors
into tellurite glass fibres. Remote magnetometry is performed on magnetically
active defect centres in nanodiamonds embedded into the glass matrix. Standard
optical magnetometry techniques are applied to initialize and detect local
magnetic field changes with a measured sensitivity of 26 micron Tesla/square
root(Hz). Our approach utilizes straight-forward optical excitation, simple
focusing elements, and low power components. We demonstrate remote magnetometry
by direct reporting of the magnetic ground states of nitrogen-vacancy defect
centres in the optical fibres. In addition, we present and describe
theoretically an all-optical technique that is ideally suited to remote
fibre-based sensing. The implications of our results broaden the applications
of optical fibres, which now have the potential to underpin a new generation of
medical magneto-endoscopes and remote mining sensors.
|
Observations of the dust and gas around embedded stellar clusters reveal some
of the processes involved in their formation and evolution. Large scale mass
infall with rates dM/dt=4e-4 solar masses/year is found to be disrupted on
small scales by protostellar outflows. Observations of the size and velocity
dispersion of clusters suggest that protostellar migration from their
birthplace begins at very early times and is a potentially useful evolutionary
indicator.
|
We reformulate the manifestly T-dual description of the massless sector of
the closed bosonic string, directly from the geometry associated with the (left
and right) affine Lie algebra of the coset space Poincare/Lorentz. This
construction initially doubles not only the (spacetime) coordinates for
translations but also those for Lorentz transformations (and their dual). As a
result, the Lorentz connection couples directly to the string (as does the
vielbein), rather than being introduced ad hoc to the covariant derivative as
previously. This not only reproduces the old definition of T-dual torsion, but
automatically gives a general, covariant definition of T-dual curvature (but
still with some undetermined connections).
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Limited by fixed step-size and sparsity penalty factor, the conventional
sparsity-aware normalized subband adaptive filtering (NSAF) type algorithms
suffer from trade-off requirements of high filtering accurateness and quicker
convergence behavior for sparse system identification. To deal with this
problem, this paper proposes variable step-size L0-norm constraint NSAF
algorithms (VSS-L0-NSAFs). We first analyze mean-square-deviation (MSD)
statistics behavior of the L0-NSAF innovatively in according to novel weight
recursion form and arrive at corresponding expressions for the cases that
background noise variance is available and unavailable, where correlation
degree of system input is indicated by scaling parameter r. Based on
derivations, we develop an effective variable step-size scheme through
minimizing the upper bounds of the MSD under some reasonable assumptions and
lemma. Furthermore, an effective reset strategy is incorporated into presented
algorithms to tackle with non-stationary situations. Finally, numerical
simulations corroborate that the proposed algorithms achieve better performance
in terms of estimation accurateness and tracking capability in comparison with
existing related algorithms in sparse system identification and adaptive echo
cancellation circumstances.
|
We study the structure of the medium surrounding sites of high-mass star
formation to determine the interrelation between the HII regions and the
environment from which they were formed. The density distribution of the
surroundings is key in determining how the radiation of the newly formed stars
interacts with the surrounds in a way that allows it to be used as a star
formation tracer. We present new Herschel/SPIRE 250, 350 and 500 mum data of
LHA 120-N44 and LHA 120-N63 in the LMC. We construct average spectral energy
distributions (SEDs) for annuli centered on the IR bright part of the star
formation sites. The annuli cover ~10-~100 pc. We use a phenomenological dust
model to fit these SEDs to derive the dust column densities, characterise the
incident radiation field and the abundance of polycyclic aromatic hydrocarbon
molecules. We see a factor 5 decrease in the radiation field energy density as
a function of radial distance around N63. N44 does not show a systematic trend.
We construct a simple geometrical model to derive the 3-D density profile of
the surroundings of these two regions. Herschel/SPIRE data have proven very
efficient in deriving the dust mass distribution. We find that the radiation
field in the two sources behaves very differently. N63 is more or less
spherically symmetric and the average radiation field drops with distance. N44
shows no systematic decrease of the radiation intensity which is probably due
to the inhomogeneity of the surrounding molecular material and to the complex
distribution of several star forming clusters in the region.
|
We show that a sufficient condition for a subset $E$ in the Heisenberg group
(endowed with the Carnot-Carath\'{e}odory metric) to be contained in a
rectifiable curve is that it satisfies a modified analogue of Peter Jones's
geometric lemma. Our estimates improve on those of \cite{FFP}, by replacing the
power $2$ of the Jones-$\beta$-number with any power $r<4$. This complements
(in an open ended way) our work \cite{Li-Schul-beta-leq-length}, where we
showed that such an estimate was necessary, but with $r=4$.
|
We illustrate the detrimental effect, such as overconfident decisions, that
exponential behavior can have in methods like classical LDA and logistic
regression. We then show how polynomiality can remedy the situation. This,
among others, leads purposefully to random-level performance in the tails, away
from the bulk of the training data. A directly related, simple, yet important
technical novelty we subsequently present is softRmax: a reasoned alternative
to the standard softmax function employed in contemporary (deep) neural
networks. It is derived through linking the standard softmax to Gaussian
class-conditional models, as employed in LDA, and replacing those by a
polynomial alternative. We show that two aspects of softRmax, conservativeness
and inherent gradient regularization, lead to robustness against adversarial
attacks without gradient obfuscation.
|
A formalism for spin observables of the reaction
$pd\to ~^3He\eta$ is derived in a model independent way.
The general case with a full set of six independent spin amplitudes is
studied. Furthermore, approximations by five and four spin amplitudes are
investigated in the near threshold region. This region is of great interest to
search for a quasi-bound $^3He-\eta$ state, in particular, by measurement of
energy dependence of relative phases of s- and p-wave amplitudes. Complete
polarization experiments, allowing determination of spin amplitudes, are
analyzed. It is shown that measurement of only analyzing powers and spin
correlation coefficients hardly allows one to separate the s- and p-wave
amplitudes, but additional measurement of polarization transfer coefficients
simplifies this problem. Specific observables, given by products of one s- and
one p-wave amplitudes, are found. Measurement of these observables will provide
new independent information on the $^3He-\eta$ pole position.
|
While deep face recognition (FR) systems have shown amazing performance in
identification and verification, they also arouse privacy concerns for their
excessive surveillance on users, especially for public face images widely
spread on social networks. Recently, some studies adopt adversarial examples to
protect photos from being identified by unauthorized face recognition systems.
However, existing methods of generating adversarial face images suffer from
many limitations, such as awkward visual, white-box setting, weak
transferability, making them difficult to be applied to protect face privacy in
reality. In this paper, we propose adversarial makeup transfer GAN (AMT-GAN), a
novel face protection method aiming at constructing adversarial face images
that preserve stronger black-box transferability and better visual quality
simultaneously. AMT-GAN leverages generative adversarial networks (GAN) to
synthesize adversarial face images with makeup transferred from reference
images. In particular, we introduce a new regularization module along with a
joint training strategy to reconcile the conflicts between the adversarial
noises and the cycle consistence loss in makeup transfer, achieving a desirable
balance between the attack strength and visual changes. Extensive experiments
verify that compared with state of the arts, AMT-GAN can not only preserve a
comfortable visual quality, but also achieve a higher attack success rate over
commercial FR APIs, including Face++, Aliyun, and Microsoft.
|
The unfolding of detector effects in experimental data is critical for
enabling precision measurements in high-energy physics. However, traditional
unfolding methods face challenges in scalability, flexibility, and dependence
on simulations. We introduce a novel unfolding approach using conditional
Denoising Diffusion Probabilistic Models (cDDPM). Our method utilizes the cDDPM
for a non-iterative, flexible posterior sampling approach, which exhibits a
strong inductive bias that allows it to generalize to unseen physics processes
without explicitly assuming the underlying distribution. We test our approach
by training a single cDDPM to perform multidimensional particle-wise unfolding
for a variety of physics processes, including those not seen during training.
Our results highlight the potential of this method as a step towards a
"universal" unfolding tool that reduces dependence on truth-level assumptions.
|
Computing the trajectories of mandibular condyles directly from MRI could
provide a comprehensive examination, allowing for the extraction of both
anatomical and kinematic details. This study aimed to investigate the
feasibility of extracting 3D condylar trajectories from 2D real-time MRI and to
assess their precision.Twenty healthy subjects underwent real-time MRI while
opening and closing their jaws. One axial and two sagittal slices were
segmented using a U-Net-based algorithm. The centers of mass of the resulting
masks were projected onto the coordinate system based on anatomical markers and
temporally adjusted using a common projection. The quality of the computed
trajectories was evaluated using metrics designed to estimate movement
reproducibility, head motion, and slice placement symmetry.The segmentation of
the axial slices demonstrated good-to-excellent quality; however, the
segmentation of the sagittal slices required some fine-tuning. The movement
reproducibility was acceptable for most cases; nevertheless, head motion
displaced the trajectories by 1 mm on average. The difference in the
superior-inferior coordinate of the condyles in the closed jaw position was 1.7
mm on average.Despite limitations in precision, real-time MRI enables the
extraction of condylar trajectories with sufficient accuracy for evaluating
clinically relevant parameters such as condyle displacement, trajectories
aspect, and symmetry.
|
This paper addresses the detection of periodic transients in vibration
signals for detecting faults in rotating machines. For this purpose, we present
a method to estimate periodic-group-sparse signals in noise. The method is
based on the formulation of a convex optimization problem. A fast iterative
algorithm is given for its solution. A simulated signal is formulated to verify
the performance of the proposed approach for periodic feature extraction. The
detection performance of comparative methods is compared with that of the
proposed approach via RMSE values and receiver operating characteristic (ROC)
curves. Finally, the proposed approach is applied to compound faults diagnosis
of motor bearings. The non-stationary vibration data were acquired from a
SpectraQuest's machinery fault simulator. The processed results show the
proposed approach can effectively detect and extract the useful features of
bearing outer race and inner race defect.
|
In this paper we review some of our recent experimental and theoretical
results on transport and thermodynamic properties of heavy-fermion alloys
Ce(1-x)Yb(x)CoIn5. Charge transport measurements under magnetic field and
pressure on these single crystalline alloys revealed that: (i) relatively small
Yb substitution suppresses the field induced quantum critical point, with a
complete suppression for nominal Yb doping x>0.20; (ii) the superconducting
transition temperature Tc and Kondo lattice coherence temperature T* decrease
with x, yet they remain finite over the wide range of Yb concentrations; (iii)
both Tc and T* increase with pressure; (iv) there are two contributions to
resistivity, which show different temperature and pressure dependences,
implying that both heavy and light quasiparticles contribute to inelastic
scattering. We also analyzed theoretically the pressure dependence of both T*
and Tc within the composite pairing theory. In the purely static limit, when we
ignore the lattice dynamics, we find that the composite pairing mechanism
necessarily causes opposite behaviors of T* and Tc with pressure: if T* grows
with pressure, Tc must decrease with pressure and vice versa.
|
Real-time nonlinear Bayesian filtering algorithms are overwhelmed by data
volume, velocity and increasing complexity of computational models. In this
paper, we propose a novel ensemble based nonlinear Bayesian filtering approach
which only requires a small number of simulations and can be applied to
high-dimensional systems in the presence of intractable likelihood functions.
The proposed approach uses linear latent projections to estimate the joint
probability distribution between states, parameters, and observables using a
mixture of Gaussian components generated by the reconstruction error for each
ensemble member. Since it leverages the computational machinery behind linear
latent variable models, it can achieve fast implementations without the need to
compute high-dimensional sample covariance matrices. The performance of the
proposed approach is compared with the performance of ensemble Kalman filter on
a high-dimensional Lorenz nonlinear dynamical system.
|
Robotic systems are becoming pervasive and adopted in increasingly many
domains, such as manufacturing, healthcare, and space exploration. To this end,
engineering software has emerged as a crucial discipline for building
maintainable and reusable robotic systems. Robotics software engineering
research has received increasing attention, fostering autonomy as a fundamental
goal. However, robotics developers are still challenged trying to achieve this
goal given that simulation is not able to deliver solutions to realistically
emulate real-world phenomena. Robots also need to operate in unpredictable and
uncontrollable environments, which require safe and trustworthy self-adaptation
capabilities implemented in software. Typical techniques to address the
challenges are runtime verification, field-based testing, and mitigation
techniques that enable fail-safe solutions. However, there is no clear guidance
to architect ROS-based systems to enable and facilitate runtime verification
and field-based testing. This paper aims to fill in this gap by providing
guidelines that can help developers and QA teams when developing, verifying or
testing their robots in the field. These guidelines are carefully tailored to
address the challenges and requirements of testing robotics systems in
real-world scenarios. We conducted a literature review on studies addressing
runtime verification and field-based testing for robotic systems, mined
ROS-based application repositories, and validated the applicability, clarity,
and usefulness via two questionnaires with 55 answers. We contribute 20
guidelines formulated for researchers and practitioners in robotic software
engineering. Finally, we map our guidelines to open challenges thus far in
runtime verification and field-based testing for ROS-based systems and, we
outline promising research directions in the field.
|
The photon polarization operator in superstrong magnetic fields induces the
dynamical photon "mass" which leads to screening of Coulomb potential at small
distances $z\ll 1/m$, $m$ is the mass of an electron. We demonstrate that this
behaviour is qualitatively different from the case of D=2 QED, where the same
formula for a polarization operator leads to screening at large distances as
well. Because of screening the ground state energy of the hydrogen atom at the
magnetic fields $B \gg m^2/e^3$ has the finite value $E_0 = -me^4/2
\ln^2(1/e^6)$.
|
We report on the thermodynamic and transport properties of the rare-earth
Zintl compound Eu$_5$Sn$_2$As$_6$, which orders as a canted antiferromagnetic
magnetic semiconductor at 10.3~K. The system also displays a complex cascade of
magnetic phases arising from geometric and magnetic exchange frustration, with
high sensitivity to the application and direction of small magnetic fields. At
low temperature, Eu$_5$Sn$_2$As$_6$ exhibits negative colossal
magnetoresistance of up to a factor of $6\times10^3$. This may be a lower bound
as the conductivity appears to be shunted by an unknown conduction channel,
causing the resistivity to saturate. Mechanisms for the low temperature
saturation of resistivity are discussed.
|
For a simple digraph $G$ without directed triangles or digons, let $\beta(G)$
be the size of the smallest subset $X \subseteq E(G)$ such that $G\setminus X$
has no directed cycles, and let $\gamma(G)$ be the number of unordered pairs of
nonadjacent vertices in $G$. In 2008, Chudnovsky, Seymour, and Sullivan showed
that $\beta (G) \le \gamma(G)$, and conjectured that $\beta (G) \le
\gamma(G)/2$. Recently, Dunkum, Hamburger, and P\'or proved that $\beta (G) \le
0.88 \gamma(G)$. In this note, we prove that $\beta (G) \le 0.8616 \gamma(G)$.
|
The stability of nonvolatile thin liquid films and of sessile droplets is
strongly affected by finite size effects. We analyze their stability within the
framework of density functional theory using the sharp kink approximation,
i.e., on the basis of an effective interface Hamiltonian. We show that finite
size effects suppress spinodal dewetting of films because it is driven by a
long-wavelength instability. Therefore nonvolatile films are stable if the
substrate area is too small. Similarly, nonvolatile droplets connected to a
wetting film become unstable if the substrate area is too large. This
instability of a nonvolatile sessile droplet turns out to be equivalent to the
instability of a volatile drop which can attain chemical equilibrium with its
vapor.
|
We report radio observations, made with the Australia Telescope Compact
Array, of the X-ray transient XTE J1701-462. This system has been classified as
a new `Z' source, displaying characteristic patterns of behaviour probably
associated with accretion onto a low magnetic field neutron star at close to
the Eddington limit. The radio counterpart is highly variable, and was detected
in six of sixteen observations over the period 2006 January -- April. The
coupling of radio emission to X-ray state, despite limited sampling, appears to
be similar to that of other `Z' sources, in that there is no radio emission on
the flaring branch. The mean radio and X-ray luminosities are consistent with
the other Z sources for a distance of 5--15 kpc. The radio spectrum is
unusually flat, or even inverted, in contrast to the related sources, Sco X-1
and Cir X-1, which usually display an optically thin radio spectrum. Deep
wide-field observations indicate an extended structure three arcminutes to the
south which is aligned with the X-ray binary. This seems to represent a
significant overdensity of radio sources for the field and so, although a
background source remains a strong possibility, we consider it plausible that
this is a large-scale jet associated with XTE J1701-462.
|
By elaborating on the recent progress made in the area of Feynman integrals,
we apply the intersection theory for twisted de Rham cohomologies to simple
integrals involving orthogonal polynomials, matrix elements of operators in
Quantum Mechanics and Green's functions in Field Theory, showing that the
algebraic identities they obey are related to the decomposition of twisted
cocycles within cohomology groups, and which, therefore, can be derived by
means of intersection numbers. Our investigation suggests an algebraic approach
generically applicable to the study of higher-order moments of probability
distributions, where the dimension of the cohomology groups corresponds to the
number of independent moments; the intersection numbers for twisted cocycles
can be used to derive linear and quadratic relations among them. Our study
offers additional evidence of the intertwinement between physics, geometry, and
statistics.
|
We propose a remarkably simple electronic refrigerator based on the Coulomb
barrier for single-electron tunneling. A fully normal single-electron
transistor is voltage $V$ biased at a gate position such that tunneling through
one of the junctions costs an energy of about $k_BT \ll eV, E_C$, where $T$ is
the temperature and $E_C$ is the transistor charging energy. The tunneling in
the junction with positive energy cost cools both the electrodes attached to
it. Immediate practical realizations of such a refrigerator make use of Andreev
mirrors which suppress heat current while maintaining full electric contact.
|
Non-universal scale transformations of the physical fields are extended to
pure quantum fluids and used to calculate susceptibility, specific heat and the
order parameter along the critical isochore of He3 near its liquid-vapor
critical point. Within the so-called preasymptotic domain, where the Wegner
expansion restricted to the first term of confluent corrections to scaling is
expected valid, the results show agreement with the experimental measurements
and recent predictions, either based on the minimal-substraction
renormalization and the massive renormalization schemes within the
$\Phi\_{d=3}^{4}(n=1)$-model, or based on the crossover parametric equation of
state for Ising-like systems.
|
A digital quantum simulation for the extended Agassi model is proposed using
a quantum platform with eight trapped ions. The extended Agassi model is an
analytically solvable model including both short range pairing and long range
monopole-monopole interactions with applications in nuclear physics and in
other many-body systems. In addition, it owns a rich phase diagram with
different phases and the corresponding phase transition surfaces. The aim of
this work is twofold: on one hand, to propose a quantum simulation of the model
at the present limits of the trapped ions facilities and, on the other hand, to
show how to use a machine learning algorithm on top of the quantum simulation
to accurately determine the phase of the system. Concerning the quantum
simulation, this proposal is scalable with polynomial resources to larger
Agassi systems. Digital quantum simulations of nuclear physics models assisted
by machine learning may enable one to outperform the fastest classical
computers in determining fundamental aspects of nuclear matter.
|
We study the behavior of the Yang-Mills flow for unitary connections on
compact and non-compact oriented surfaces with varying metrics. The flow can be
used to define a one dimensional foliation on the space of SU(2)
representations of a once punctured surface. This foliation universalizes over
Teichm\"uller space and is equivariant with respect to the action of the
mapping class group. It is shown how to extend the foliation as a singular
foliation over the Strebel boundary of Teichm\"uller space, and continuity of
this extension is the main result of the paper.
|
In this paper, we study a few versions of the uncertainty principle for the
short-time Fourier transform on the lattice $\mathbb Z^n \times \mathbb T^n$.
In particular, we establish the uncertainty principle for orthonormal
sequences, Donoho--Stark's uncertainty principle, Benedicks-type uncertainty
principle, Heisenberg-type uncertainty principle and local uncertainty
inequality for this transform on $\mathbb Z^n \times \mathbb T^n$. Also, we
obtain the Heisenberg-type uncertainty inequality using the $k$-entropy of the
short-time Fourier transform on $\mathbb Z^n \times \mathbb T^n$.
|
Assuming only Sobolev regularity of the domain, we prove time-analyticity of
Lagrangian trajectories for solutions of the Euler equations.
|
Developments in IoT applications are playing an important role in our
day-to-day life, starting from business predictions to self driving cars. One
of the area, most influenced by the field of AI and IoT is retail analytics. In
Retail Analytics, Conversion Rates - a metric which is most often used by
retail stores to measure how many people have visited the store and how many
purchases has happened. This retail conversion rate assess the marketing
operations, increasing stock, store outlet and running promotions ..etc. Our
project intends to build a cost-effective people counting system with AI at
Edge, where it calculates Conversion rates using total number of people counted
by the system and number of transactions for the day, which helps in providing
analytical insights for retail store optimization with a very minimum hardware
requirements.
|
Deep neural networks (DNNs) have shown great success in many machine learning
tasks. Their training is challenging since the loss surface of the network
architecture is generally non-convex, or even non-smooth. How and under what
assumptions is guaranteed convergence to a \textit{global} minimum possible? We
propose a reformulation of the minimization problem allowing for a new
recursive algorithmic framework. By using bounded style assumptions, we prove
convergence to an $\varepsilon$-(global) minimum using
$\mathcal{\tilde{O}}(1/\varepsilon^3)$ gradient computations. Our theoretical
foundation motivates further study, implementation, and optimization of the new
algorithmic framework and further investigation of its non-standard bounded
style assumptions. This new direction broadens our understanding of why and
under what circumstances training of a DNN converges to a global minimum.
|
Investigating star formation requires precise knowledge of the properties of
the dense molecular gas. The low metallicity and wide range of star formation
activity of the Large and Small Magellanic Clouds make them prime laboratories
to study how local physical conditions impact the dense gas reservoirs. The aim
of the Dense Gas Survey for the Magellanic Clouds (DeGaS-MC) project is to
expand our knowledge of the relation between dense gas properties and star
formation activity by targeting the LMC and SMC observed in the HCO+(2-1) and
HCN(2-1) transitions. We carried out a pointing survey toward 30 LMC and SMC
molecular clouds using the SEPIA180 instrument installed on the APEX telescope
and a follow-up mapping campaign in 13 star-forming regions. This first paper
provides line characteristic catalogs and integrated line-intensity maps of the
sources. HCO+(2-1) is detected in 20 and HCN(2-1) in 8 of the 29 pointings
observed. The dense gas velocity pattern follows the line-of-sight velocity
field derived from the stellar population. The HCN emission is less extended
than the HCO+ emission. The HCO+(2-1)/HCN(2-1) brightness temperature ratios
range from 1 to 7, which is consistent with the large ratios commonly observed
in low-metallicity environments. A larger number of young stellar objects are
found at high HCO+ intensities and lower HCO+/HCN flux ratios, and thus toward
denser lines of sight. The dense gas luminosities correlate with the star
formation rate traced by the total infrared luminosity over the two orders of
magnitude covered by our observations, although substantial region-to-region
variations are observed.
|
The John-Nirenberg spaces $JN_p$ are generalizations of the space of bounded
mean oscillation $BMO$ with $JN_{\infty}=BMO$. Their vanishing subspaces
$VJN_p$ and $CJN_p$ are defined in similar ways as $VMO$ and $CMO$, which are
subspaces of $BMO$. As our main result, we prove that $VJN_p$ and $CJN_p$
coincide by showing that certain Morrey type integrals of $JN_p$ functions tend
to zero for small and large cubes. We also show that $JN_{p,q}(\mathbb{R}^n) =
L^p(\mathbb{R}^n) / \mathbb{R}$, if $p = q$.
|
Spherical quartz stones of around 1 cm in diameter have been exposed to
anodic arc discharges in a helium atmosphere at 300 Torr. The arc current
flowing between the graphite electrodes was set either in continuous DC mode
(30-150 A) or in pulsed mode at 2 Hz (220 A peak). The ablation rate in each
sample was systematically measured after several seconds of arc plasma
treatment. Optical emission spectroscopy (OES) diagnostics and 2-D fluid
simulations of the arc discharge have shed light on the heat flux transport and
the heating mechanisms of the quartz crystals. A linear correlation is found
between the absorbed power density and the resulting rate of penetration, which
yields a maximal value of 15 cm/h for approximately 150 W/cm2. The linear fit
on the slope provides a specific energy of 40 kJ/cm3. The incident energy flux
onto the sample surface promoted a phase transition from crystalline to glassy
silica, as characterized via Raman spectroscopy. This study points out the
strong potential of arc plasma technology for geothermal drilling applications.
|
Existing techniques for Craig interpolation for the quantifier-free fragment
of the theory of arrays are inefficient for computing sequence and tree
interpolants: the solver needs to run for every partitioning $(A, B)$ of the
interpolation problem to avoid creating $AB$-mixed terms. We present a new
approach using Proof Tree Preserving Interpolation and an array solver based on
Weak Equivalence on Arrays. We give an interpolation algorithm for the lemmas
produced by the array solver. The computed interpolants have worst-case
exponential size for extensionality lemmas and worst-case quadratic size
otherwise. We show that these bounds are strict in the sense that there are
lemmas with no smaller interpolants. We implemented the algorithm and show that
the produced interpolants are useful to prove memory safety for C programs.
|
Dilepton production in intermediate energy nucleus-nucleus collisions as well
as in elementary proton-proton reactions is analysed within the UrQMD transport
model. For C+C collisions at 1 AGeV and 2 AGeV the resulting invariant mass
spectra are compared to recent HADES data. We find that the experimental
spectrum for C+C at 2 AGeV is slightly overestimated by the theoretical
calculations in the region around the vector meson peak, but fairly described
in the low mass region, where the data is satisfactorily saturated by the
Dalitz decay of the $\eta$ meson and the $\Delta$ resonance. At 1 AGeV an
underestimation of the experimental data is found, pointing that at lower
energies the low mass region is not fully saturated by standardly parametrized
$\Delta$ Dalitz decays alone. Furthermore, predictions for dilepton spectra for
$pp$ reactions at 1.25 GeV, 2.2 GeV and 3.5 GeV and Ar+KCl reactions at 1.75
AGeV are presented. The study is complemented by a detailed investigation of
the role of absorption of the parent particles on the corresponding dilepton
yields in the regime which has so far been probed by HADES.
|
Survival prediction is a major concern for cancer management. Deep survival
models based on deep learning have been widely adopted to perform end-to-end
survival prediction from medical images. Recent deep survival models achieved
promising performance by jointly performing tumor segmentation with survival
prediction, where the models were guided to extract tumor-related information
through Multi-Task Learning (MTL). However, these deep survival models have
difficulties in exploring out-of-tumor prognostic information. In addition,
existing deep survival models are unable to effectively leverage multi-modality
images. Empirically-designed fusion strategies were commonly adopted to fuse
multi-modality information via task-specific manually-designed networks, thus
limiting the adaptability to different scenarios. In this study, we propose an
Adaptive Multi-modality Segmentation-to-Survival model (AdaMSS) for survival
prediction from PET/CT images. Instead of adopting MTL, we propose a novel
Segmentation-to-Survival Learning (SSL) strategy, where our AdaMSS is trained
for tumor segmentation and survival prediction sequentially in two stages. This
strategy enables the AdaMSS to focus on tumor regions in the first stage and
gradually expand its focus to include other prognosis-related regions in the
second stage. We also propose a data-driven strategy to fuse multi-modality
information, which realizes adaptive optimization of fusion strategies based on
training data during training. With the SSL and data-driven fusion strategies,
our AdaMSS is designed as an adaptive model that can self-adapt its focus
regions and fusion strategy for different training stages. Extensive
experiments with two large clinical datasets show that our AdaMSS outperforms
state-of-the-art survival prediction methods.
|
Super-entropic black holes possess finite-area but noncompact event horizons
and violate the reverse isoperimetric inequality. It has been conjectured that
such black holes always have negative specific heat at constant volume $C_{V}$
or negative specific heat at constant pressure $C_{P}$ whenever $C_{V}>0$,
making them unstable in extended thermodynamics. In this paper, we test this
instability conjecture on a family of nonlinear electrodynamics black holes,
namely $3$D Einstein-Born-Infeld (EBI) AdS black holes. Our results show that
when nonlinear electrodynamics effects are weak, the instability conjecture is
valid. However, the conjecture can be violated in some parameter region when
nonlinear electrodynamics effects are strong enough. This observation thus
provides a counter example to the instability conjecture, which suggests that
super-entropic black holes could be thermodynamically stable.
|
A Richardson variety $X_\ga^\gc$ in the Orthogonal Grassmannian is defined to
be the intersection of a Schubert variety $X^\gc$ in the Orthogonal
Grassmannian and a opposite Schubert variety $X_\ga$ therein. We give an
explicit description of the initial ideal (with respect to certain conveniently
chosen term order) for the ideal of the tangent cone at any $T$-fixed point of
$X_\ga^\gc$, thus generalizing a result of Raghavan-Upadhyay \cite{Ra-Up2}. Our
proof is based on a generalization of the Robinson-Schensted-Knuth (RSK)
correspondence, which we call the Orthogonal bounded RSK (OBRSK). The OBRSK
correspondence will give a degree-preserving bijection between a set of
monomials defined by the initial ideal of the ideal of the tangent cone (as
mentioned above) and a `standard monomial basis'. A similar work for Richardson
varieties in the ordinary Grassmannian was done by Kreiman in \cite{Kr-bkrs}.
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We study D2-branes on the K3-fibration P^4_(11222)[8] using matrix
factorizations at the Landau-Ginzburg point and analyze their moduli space and
superpotentials in detail. We find that the open string moduli space consists
of various intersecting branches of different dimensions. Families of D2-branes
wrapping rational curves of degree one intersect with bound state branches. The
influence of non-toric complex structure deformations is investigated in the
Landau-Ginzburg framework, where these deformations arise as bulk moduli from
the twisted sectors.
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We study the empirical realisation of the memory effect in Yang-Mills theory,
especially in view of the classical vs. quantum nature of the theory. Gauge
invariant analysis of memory in classical U(1) electrodynamics and its
observation by total change of transverse momentum of a charge is reviewed.
Gauge fixing leads to a determination of a gauge transformation at infinity. An
example of Yang-Mills memory then is obtained by reinterpreting known results
on interactions of a quark and a large high energy nucleus in the theory of
Color Glass Condensate. The memory signal is again a kick in transverse
momentum, but it is only obtained in quantum theory after fixing the gauge,
after summing over an ensemble of classical processes.
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Numerous groups have applied a variety of deep learning techniques to
computer vision problems in highway perception scenarios. In this paper, we
presented a number of empirical evaluations of recent deep learning advances.
Computer vision, combined with deep learning, has the potential to bring about
a relatively inexpensive, robust solution to autonomous driving. To prepare
deep learning for industry uptake and practical applications, neural networks
will require large data sets that represent all possible driving environments
and scenarios. We collect a large data set of highway data and apply deep
learning and computer vision algorithms to problems such as car and lane
detection. We show how existing convolutional neural networks (CNNs) can be
used to perform lane and vehicle detection while running at frame rates
required for a real-time system. Our results lend credence to the hypothesis
that deep learning holds promise for autonomous driving.
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We prove that, for sufficiently large $n$, every graph of order $n$ with
minimum degree at least $0.852n$ has a fractional edge-decomposition into
triangles. We do this by refining a method used by Dross to establish a bound
of $0.9n$. By a result of Barber, K\"{u}hn, Lo and Osthus, our result implies
that, for each $\epsilon >0$, every graph of sufficiently large order $n$ with
minimum degree at least $(0.852+\epsilon)n$ has a triangle decomposition if and
only if it has all even degrees and number of edges a multiple of three.
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Quasi-experimental methods have proliferated over the last two decades, as
researchers develop causal inference tools for settings in which randomization
is infeasible. Two popular such methods, difference-in-differences (DID) and
comparative interrupted time series (CITS), compare observations before and
after an intervention in a treated group to an untreated comparison group
observed over the same period. Both methods rely on strong, untestable
counterfactual assumptions. Despite their similarities, the methodological
literature on CITS lacks the mathematical formality of DID. In this paper, we
use the potential outcomes framework to formalize two versions of CITS - a
general version described by Bloom (2005) and a linear version often used in
health services research. We then compare these to two corresponding DID
formulations - one with time fixed effects and one with time fixed effects and
group trends. We also re-analyze three previously published studies using these
methods. We demonstrate that the most general versions of CITS and DID impute
the same counterfactuals and estimate the same treatment effects. The only
difference between these two designs is the language used to describe them and
their popularity in distinct disciplines. We also show that these designs
diverge when one constrains them using linearity (CITS) or parallel trends
(DID). We recommend defaulting to the more flexible versions and provide advice
to practitioners on choosing between the more constrained versions by
considering the data-generating mechanism. We also recommend greater attention
to specifying the outcome model and counterfactuals in papers, allowing for
transparent evaluation of the plausibility of causal assumptions.
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We describe an electrodynamic mechanism for coherent, quantum mechanical
coupling between spacially separated quantum dots on a microchip. The technique
is based on capacitive interactions between the electron charge and a
superconducting transmission line resonator, and is closely related to atomic
cavity quantum electrodynamics. We investigate several potential applications
of this technique which have varying degrees of complexity. In particular, we
demonstrate that this mechanism allows design and investigation of an on-chip
double-dot microscopic maser. Moreover, the interaction may be extended to
couple spatially separated electron spin states while only virtually populating
fast-decaying superpositions of charge states. This represents an effective,
controllable long-range interaction, which may facilitate implementation of
quantum information processing with electron spin qubits and potentially allow
coupling to other quantum systems such as atomic or superconducting qubits.
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The Born rule postulates that the probability of measurement in quantum
mechanics is related to the squared modulus of the wave function $\psi$. We
rearrange the equation for energy eigenfunctions to define the energy as the
real part of $\hat{E}\psi/\psi$. For an eigenstate, this definition gives a
constant energy eigenvalue. For a general wave function, the energy fluctuates
in space and time. We consider a particle in a one-dimensional square well
potential in a superposition of two states and average the energy over space
and time. We show that, for most cases, such an energy expectation value
differs by only a few percent from that calculated using the Born rule. This
difference is consistent with experimental tests of the expectation value and
suggests that the Born rule may be an approximation of spacetime averaging.
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Some recent methods for lossy signal and image compression store only a few
selected pixels and fill in the missing structures by inpainting with a partial
differential equation (PDE). Suitable operators include the Laplacian, the
biharmonic operator, and edge-enhancing anisotropic diffusion (EED). The
quality of such approaches depends substantially on the selection of the data
that is kept. Optimising this data in the domain and codomain gives rise to
challenging mathematical problems that shall be addressed in our work.
In the 1D case, we prove results that provide insights into the difficulty of
this problem, and we give evidence that a splitting into spatial and tonal
(i.e. function value) optimisation does hardly deteriorate the results. In the
2D setting, we present generic algorithms that achieve a high reconstruction
quality even if the specified data is very sparse. To optimise the spatial
data, we use a probabilistic sparsification, followed by a nonlocal pixel
exchange that avoids getting trapped in bad local optima. After this spatial
optimisation we perform a tonal optimisation that modifies the function values
in order to reduce the global reconstruction error. For homogeneous diffusion
inpainting, this comes down to a least squares problem for which we prove that
it has a unique solution. We demonstrate that it can be found efficiently with
a gradient descent approach that is accelerated with fast explicit diffusion
(FED) cycles. Our framework allows to specify the desired density of the
inpainting mask a priori. Moreover, is more generic than other data
optimisation approaches for the sparse inpainting problem, since it can also be
extended to nonlinear inpainting operators such as EED. This is exploited to
achieve reconstructions with state-of-the-art quality.
We also give an extensive literature survey on PDE-based image compression
methods.
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In this paper we address the relationship between zero temperature Glauber
dynamics and the diffusion-annihilation problem in the free fermion case. We
show that the well-known duality transformation between the two problems can be
formulated as a similarity transformation if one uses appropriate (toroidal)
boundary conditions. This allow us to establish and clarify the precise nature
of the relationship between the two models. In this way we obtain a one-to-one
correspondence between observables and initial states in the two problems. A
random initial state in Glauber dynamics is related to a short range correlated
state in the annihilation problem. In particular the long-time behaviour of the
density in this state is seen to depend on the initial conditions. Hence, we
show that the presence of correlations in the initial state determine the
dependence of the long time behaviour of the density on the initial conditions,
even if such correlations are short-ranged. We also apply a field-theoretical
method to the calculation of multi-time correlation functions in this initial
state.
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We examine the possibility that very massive stars greatly exceeding the
commonly adopted stellar mass limit of 150 Msun may be present in young star
clusters in the local universe. We identify ten candidate clusters, some of
which may host stars with masses up to 600 Msun formed via runaway collisions.
We estimate the probabilities of these very massive stars being in eclipsing
binaries to be >30%. Although most of these systems cannot be resolved at
present, their transits can be detected at distances of 3 Mpc even under the
contamination of the background cluster light, due to the large associated
luminosities ~10^7 Lsun and mean transit depths of ~10^6 Lsun. Discovery of
very massive eclipsing binaries would flag possible progenitors of
pair-instability supernovae and intermediate-mass black holes.
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Recent Spitzer Space Telescope observations of several astrophysical
environments such as Planetary Nebulae, Reflection Nebulae, and R Coronae
Borealis stars show the simultaneous presence of mid-infrared features
attributed to neutral fullerene molecules (i.e., C60) and polycyclic aromatic
hydrocarbons (PAHs). If C60 fullerenes and PAHs coexist in fullerene-rich space
environments, then C60 may easily form adducts with a number of different PAH
molecules; at least with catacondensed PAHs. Here we present the laboratory
infrared spectra (~2-25 um) of C60 fullerene and anthracene Dies-Alder mono-
and bis-adducts as produced by sonochemical synthesis. We find that
C60/anthracene Diels-Alder adducts display spectral features strikingly similar
to those from C60 (and C70) fullerenes and other unidentified infrared emission
features. Thus, fullerene-adducts - if formed under astrophysical conditions
and stable/abundant enough - may contribute to the infrared emission features
observed in fullerene-containing circumstellar/interstellar environments.
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We discuss mock automorphic forms from the point of view of representation
theory, that is, obtained from weak harmonic Maass forms give rise to
nontrivial $(\mathfrak{g},K)$-cohomology. We consider the possibility of
replacing the `holomorphic' condition with `cohomological' when generalizing to
general reductive groups. Such a candidate allows for growing Fourier
coefficients, in contrast to automorphic forms under the Miatello-Wallach
conjecture. In the second part, we provide an overview of the connection with
BPS black hole counts as a physical motivation for studying mock automorphic
forms.
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An improved weighting algorithm applied to hadron showers has been developed
for a fine grained LAr calorimeter. The new method uses tabulated weights which
depend on the density of energy deposited in individual cells and in a
surrounding cone whose symmetry axis connects the interaction vertex with the
highest energy cluster in the shower induced by a hadron. The weighting of the
visible energy and the correction for losses due to noise cuts are applied in
separate steps. In contrast to standard weighting procedures the new algorithm
allows to reconstruct the total energy as well as the spatial energy deposition
on the level of individual calorimeter cells. The linearity and the energy
resolution of the pion signal in the momentum interval 2 GeV/c <= p <= 20 GeV/c
studied in this analysis are considerably improved in comparison to the
standard weighting algorithm as practiced presently by the H1 collaboration.
Moreover the energy spectra reconstructed with the new method follow in a broad
interval a Gaussian distribution and have less pronounced tails.
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We propose a new approximation scheme to obtain analytic expressions for the
bound state energies and eigenfunctions of Yukawa like potentials. The
predicted energies are in excellent agreement with the accurate numerical
values reported in the literature.
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This paper describes low-cost techniques used to collect video data in two
different tutorial classrooms - one in which the recording equipment is
permanently installed and one in which it is temporary. The author explains
what to do before, during, and after class in these two situations, providing
general strategies and technical advice for researchers interested in
videotaping tutorials or similar classrooms.
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We study operator dynamics in many-body quantum systems, focusing on generic
features of systems which are ergodic, spatially extended, and lack conserved
densities, as exemplified by spin chains with Floquet time evolution. To
characterise dynamics we examine, in solvable models and numerically, the
behaviour of operator autocorrelation functions, as a function of time and the
size of the operator support. The standard expectation is that operator
autocorrelation functions in such systems are maximum at time zero and decay,
over a few Floquet periods, to a fluctuating value that reduces to zero under
an average over an ensemble of statistically similar systems. Our central
result is that ensemble-averaged correlation functions also display a second
generic feature, which consists of a peak at a later time. In individual
many-body systems, this peak can also be revealed by averaging autocorrelation
functions over complete sets of operators supported within a finite spatial
region, thereby generating a partial spectral form factor. The duration of the
peak grows indefinitely with the size of the operator support, and its
amplitude shrinks, but both are essentially independent of system size provided
this is sufficiently large to contain the operator. In finite systems, the
averaged correlation functions also show a further feature at still later
times, which is a counterpart to the so-called ramp and plateau of the spectral
form factor; its amplitude in the autocorrelation function decreases to zero
with increasing system size. Both the later-time peak and the ramp-and-plateau
feature are specific to models with time-translation symmetry, such as Floquet
systems or models with a time-independent Hamiltonian, and are absent in models
with an evolution operator that is a random function of time, such as the
extensively-studied random unitary circuits.
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A scalar-response functional model describes the association between a scalar
response and a set of functional covariates. An important problem in the
functional data literature is to test the nullity or linearity of the effect of
the functional covariate in the context of scalar-on-function regression. This
article provides an overview of the existing methods for testing both the null
hypotheses that there is no relationship and that there is a linear
relationship between the functional covariate and scalar response, and a
comprehensive numerical comparison of their performance. The methods are
compared for a variety of realistic scenarios: when the functional covariate is
observed at dense or sparse grids and measurements include noise or not.
Finally, the methods are illustrated on the Tecator data set.
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For a continuous field of the Cuntz algebra over a finite CW complex, we
introduce a topological invariant, which is an element in Dadarlat-Pennig's
generalized cohomology group, and prove that the invariant is trivial if and
only if the field comes from a vector bundle via Pimsner's construction.
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In this correspondence, a novel simultaneous transmitting and reflecting
(STAR) reconfigurable intelligent surfaces (RISs) design is proposed in a
non-orthogonal multiple access (NOMA) enhanced coordinated multi-point
transmission (CoMP) network. Based on the insights of signal-enhancement-based
(SEB) and signal-cancellation-based (SCB) designs, we propose a novel
simultaneous-signal-enhancement-and-cancellation-based (SSECB) design, where
the inter-cell interferences and desired signals can be simultaneously
eliminated and boosted. Our simulation results demonstrate that: i) the
inter-cell interference can be perfectly eliminated, and the desired signals
can be enhanced simultaneously with the aid of a large number of RIS elements;
ii) the proposed SSECB design is capable of outperforming the conventional SEB
and SCB designs.
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The boundary element method (BEM) enables the efficient electromagnetic
modelling of lossy conductors with a surface-based discretization. Existing BEM
techniques for conductor modelling require either expensive dual basis
functions or the use of both single- and double-layer potential operators to
obtain a well-conditioned system matrix. The associated computational cost is
particularly significant when conductors are embedded in stratified media, and
the expensive multilayer Green's function (MGF) must be invoked. In this work,
a novel single-source BEM formulation is proposed, which leads to a
well-conditioned system matrix without the need for dual basis functions. The
proposed single-layer impedance matrix (SLIM) formulation does not require the
double-layer potential to model the background medium, which reduces the cost
associated with the MGF. The accuracy and efficiency of the proposed method is
demonstrated through realistic examples drawn from different applications.
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In crowd labeling, a large amount of unlabeled data instances are outsourced
to a crowd of workers. Workers will be paid for each label they provide, but
the labeling requester usually has only a limited amount of the budget. Since
data instances have different levels of labeling difficulty and workers have
different reliability, it is desirable to have an optimal policy to allocate
the budget among all instance-worker pairs such that the overall labeling
accuracy is maximized. We consider categorical labeling tasks and formulate the
budget allocation problem as a Bayesian Markov decision process (MDP), which
simultaneously conducts learning and decision making. Using the dynamic
programming (DP) recurrence, one can obtain the optimal allocation policy.
However, DP quickly becomes computationally intractable when the size of the
problem increases. To solve this challenge, we propose a computationally
efficient approximate policy, called optimistic knowledge gradient policy. Our
MDP is a quite general framework, which applies to both pull crowdsourcing
marketplaces with homogeneous workers and push marketplaces with heterogeneous
workers. It can also incorporate the contextual information of instances when
they are available. The experiments on both simulated and real data show that
the proposed policy achieves a higher labeling accuracy than other existing
policies at the same budget level.
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The dynamics of N/Z and mass equilibration are investigated in the reactions
112,124Sn + 239Pu by employing the isospin-dependent quantum molecular dynamics
model. It is found that N/Z and mass equilibration take place at different
collision stages. The N/Z relaxation is observed in the approaching phase (from
first contact to deepest contact) with a very short time, whereas interestingly
we find for the first time that mass equilibration only takes place in the
separation phase (from the deepest contact to re-separation), which are
explained by investigating the dynamical asymmetry between the approaching and
separation phases. The mass equilibration also could be clarified with a
dynamical potential energy surface. Our results provide a new insight into the
equilibration dynamics of the quantum systems.
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In this paper, we propose two iterative methods for finding a common solution
of a finite family of equilibrium problems for pseudomonotone bifunctions. The
first is a parallel hybrid extragradient-cutting algorithm which is extended
from the previously known one for variational inequalities to equilibrium
problems. The second is a new cyclic hybrid extragradient-cutting algorithm. In
the cyclic algorithm, using the known techniques, we can perform and develop
practical numerical experiments.
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We study the $\mathfrak{gl}_{1|1}$ supersymmetric XXX spin chains. We give an
explicit description of the algebra of Hamiltonians acting on any cyclic tensor
products of polynomial evaluation $\mathfrak{gl}_{1|1}$ Yangian modules. It
follows that there exists a bijection between common eigenvectors (up to
proportionality) of the algebra of Hamiltonians and monic divisors of an
explicit polynomial written in terms of the Drinfeld polynomials. In particular
our result implies that each common eigenspace of the algebra of Hamiltonians
has dimension one. We also give dimensions of the generalized eigenspaces. We
show that when the tensor product is irreducible, then all eigenvectors can be
constructed using Bethe ansatz. We express the transfer matrices associated to
symmetrizers and anti-symmetrizers of vector representations in terms of the
first transfer matrix and the center of the Yangian.
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Common techniques in Gravitational Wave data analysis assume, to some extent,
the stationarity and Gaussianity of the detector noise. These assumptions are
not always satisfied because of the presence of short-duration transients,
namely glitches, and other slower variations in the statistical properties of
the noise, which might be related to malfunctioning subsystems. We present here
a new technique to test the stationarity hypothesis with minimal assumptions on
the data, exploiting the band-limited root mean square and the two-sample
Kolmogorov-Smirnov test. The outcome is a time-frequency map showing where the
hypothesis is to be rejected. This technique was used as part of the event
validation procedure for assessing the quality of the LIGO and Virgo data
during O3. We also report on the applications of the test to both simulated and
real data, highlighting its sensitivity to various kinds of non-stationarities.
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We present stellar mass measurements for a sample of 36 Luminous Compact Blue
Galaxies (LCBGs) at redshifts z = 0.4-1.2 in the Flanking Fields around the
Hubble Deep Field North. The technique is based on fitting a two-component
galaxy population model to multi-broadband photometry. Best-fit models are
found to be largely independent on the assumed values for the IMF and the
metallicity of the stellar populations, but are sensitive to the amount of
extinction and the extinction law adopted. On average, the best-fit model
corresponds to a LMC extinction law with E(B-V)=0.5. Stellar mass estimates,
however, are remarkably independent on the final model choice. Using a Salpeter
IMF, the derived median stellar mass for this sample is 5 x 10^9 Mo, i.e., ~2
times smaller than previous virial mass estimates. Despite uncertainties of a
factor 2-3, our results strengthen prior claims that L* CBGs at intermediate
redshifts are, on average, about 10 times less massive than a typical L* galaxy
today.
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