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Kaon flavour physics has played in the 1960s and 1970s a very important role
in the construction of the Standard Model (SM) and in the 1980s and 1990s in SM
tests with the help of CP violation in $K_L\to\pi\pi$ decays represented by
$\varepsilon_K$ and the ratio $\varepsilon'/\varepsilon$. In this millennium
this role has been taken over by $B_{s,d}$ and $D$ mesons. However there is no
doubt that in the coming years we will witness the return of kaon flavour
physics with the highlights being the measurements of the theoretically clean
branching ratios for the rare decays $K^+\rightarrow \pi^+\nu\bar\nu$ and
$K_{L}\rightarrow\pi^0\nu\bar\nu$ and the improved SM predictions for the ratio
$\varepsilon'/\varepsilon$, for $\varepsilon_K$ and the $K^0-\bar K^0$ mixing
mass difference $\Delta M_K$. Theoretical progress on the decays
$K_{L,S}\to\mu^+\mu^-$ and $K_L\to\pi^0\ell^+\ell^-$ is also expected. They all
are very sensitive to new physics (NP) contributions and the correlations
between them should help us to identify new dynamics at very short distance
scales. These studies will be enriched when theory on the $K\to\pi\pi$ isospin
amplitudes ${\rm Re} A_0$ and ${\rm Re} A_2$ improves. This talk summarizes
several aspects of this exciting field. In particular we emphasize the role of
the Dual QCD approach in getting the insight into the numerical Lattice QCD
results on $K^0-\bar K^0$ mixing and $K\to\pi\pi$ decays.
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Hypergraphs are mathematical models for many problems in data sciences. In
recent decades, the topological properties of hypergraphs have been studied and
various kinds of (co)homologies have been constructed (cf. [3, 4, 12]). In this
paper, generalising the usual homology of simplicial complexes, we define the
embedded homology of hypergraphs as well as the persistent embedded homology of
sequences of hypergraphs. As a generalisation of the Mayer-Vietoris sequence
for the homology of simplicial complexes, we give a Mayer-Vietoris sequence for
the embedded homology of hypergraphs. Moreover, as applications of the embedded
homology, we study acyclic hypergraphs and construct some indices for the data
analysis of hyper-networks.
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We investigate the applicability of machine learning technologies to the
development of parsimonious, interpretable, catchment-scale hydrologic models
using directed-graph architectures based on the mass-conserving perceptron
(MCP) as the fundamental computational unit. Here, we focus on architectural
complexity (depth) at a single location, rather than universal applicability
(breadth) across large samples of catchments. The goal is to discover a minimal
representation (numbers of cell-states and flow paths) that represents the
dominant processes that can explain the input-state-output behaviors of a given
catchment, with particular emphasis given to simulating the full range (high,
medium, and low) of flow dynamics. We find that a HyMod Like architecture with
three cell-states and two major flow pathways achieves such a representation at
our study location, but that the additional incorporation of an input-bypass
mechanism significantly improves the timing and shape of the hydrograph, while
the inclusion of bi-directional groundwater mass exchanges significantly
enhances the simulation of baseflow. Overall, our results demonstrate the
importance of using multiple diagnostic metrics for model evaluation, while
highlighting the need for properly selecting and designing the training metrics
based on information-theoretic foundations that are better suited to extracting
information across the full range of flow dynamics. This study sets the stage
for interpretable regional-scale MCP-based hydrological modeling (using large
sample data) by using neural architecture search to determine appropriate
minimal representations for catchments in different hydroclimatic regimes.
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Recently, hyperspectral image (HSI) classification approaches based on deep
learning (DL) models have been proposed and shown promising performance.
However, because of very limited available training samples and massive model
parameters, DL methods may suffer from overfitting. In this paper, we propose
an end-to-end 3-D lightweight convolutional neural network (CNN) (abbreviated
as 3-D-LWNet) for limited samples-based HSI classification. Compared with
conventional 3-D-CNN models, the proposed 3-D-LWNet has a deeper network
structure, less parameters, and lower computation cost, resulting in better
classification performance. To further alleviate the small sample problem, we
also propose two transfer learning strategies: 1) cross-sensor strategy, in
which we pretrain a 3-D model in the source HSI data sets containing a greater
number of labeled samples and then transfer it to the target HSI data sets and
2) cross-modal strategy, in which we pretrain a 3-D model in the 2-D RGB image
data sets containing a large number of samples and then transfer it to the
target HSI data sets. In contrast to previous approaches, we do not impose
restrictions over the source data sets, in which they do not have to be
collected by the same sensors as the target data sets. Experiments on three
public HSI data sets captured by different sensors demonstrate that our model
achieves competitive performance for HSI classification compared to several
state-of-the-art methods
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We construct inhomogeneous isoparametric families of hypersurfaces with
non-austere focal set on each symmetric space of non-compact type and rank
greater than or equal to 3. If the rank is greater than or equal to 4, there
are infinitely many such examples. Our construction yields the first examples
of isoparametric families on any Riemannian manifold known to have a
non-austere focal set. They can be obtained from a new general extension method
of submanifolds from Euclidean spaces to symmetric spaces of non-compact type.
This method preserves the mean curvature and isoparametricity, among other
geometric properties.
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The unbound nucleus $^{12}$Li is evaluated by studying three-neutron
one-proton excitations within the multistep shell model in the complex energy
plane. It is found that the ground state of this system consists of an
antibound $2^-$ state. A number of narrow states at low energy are found which
ensue from the coupling of resonances in $^{11}$Li to continuum states close to
threshold.
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An approach to studying lattice gauge models in the weak coupling region is
proposed. Conceptually, it is based on the crucial role of the original Z(N)
symmetry and the invariant gauge group measure. As an example, we calculate an
effective model from the compact Wilson formulation of the SU(2) gauge theory
in $d=3D3$ dimensions at zero temperature. Confining properties and phase
structure of the effective model are studied in details.
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Background: Men and women with a migration background comprise an increasing
proportion of incident HIV cases across Western Europe. Several studies
indicate a substantial proportion acquire HIV post-migration.
Methods: We used partial HIV consensus sequences with linked demographic and
clinical data from the opt-out ATHENA cohort of people with HIV in the
Netherlands to quantify population-level sources of transmission to Dutch-born
and foreign-born Amsterdam men who have sex with men (MSM) between 2010-2021.
We identified phylogenetically and epidemiologically possible transmission
pairs in local transmission chains and interpreted these in the context of
estimated infection dates, quantifying transmission dynamics between
sub-populations by world region of birth.
Results: We estimate the majority of Amsterdam MSM who acquired their
infection locally had a Dutch-born Amsterdam MSM source (56% [53-58%]).
Dutch-born MSM were the predominant source population of infections among
almost all foreign-born Amsterdam MSM sub-populations. Stratifying by two-year
intervals indicated shifts in transmission dynamics, with a majority of
infections originating from foreign-born MSM since 2018, although uncertainty
ranges remained wide.
Conclusions: In the context of declining HIV incidence among Amsterdam MSM,
our data suggest whilst native-born MSM have predominantly driven transmissions
in 2010-2021, the contribution from foreign-born MSM living in Amsterdam is
increasing.
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Higgs Computed Axial Tomography, an excerpt. Taking a closer look at the
camel-shaped tail of the light Higgs boson resonance and looking to the
transformation of the (camel-shaped) signal into a square-root--shaped signal +
interference with particular emphasis on residual theoretical uncertainties.
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The finite-sample as well as the asymptotic distribution of Leung and
Barron's (2006) model averaging estimator are derived in the context of a
linear regression model. An impossibility result regarding the estimation of
the finite-sample distribution of the model averaging estimator is obtained.
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We construct special Lagrangian fibrations for log Calabi-Yau surfaces, and
scattering diagrams from Lagrangian Floer theory of the fibres. Then we prove
that the scattering diagrams recover the scattering diagrams of
Gross-Pandharipande-Siebert and the canonical scattering diagrams of
Gross-Hacking-Keel. With an additional assumption on the non-negativity of
boundary divisors, we compute the disc potentials of the Lagrangian torus
fibres via a holomorphic/tropical correspondence. As an application, we provide
a version of mirror symmetry for rank two cluster varieties.
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Membrane budding and wrapping of particles, such as viruses and
nano-particles, play a key role in intracellular transport and have been
studied for a variety of biological and soft matter systems. We study
nano-particle wrapping by numerical minimization of bending, surface tension,
and adhesion energies. We calculate deformation and adhesion energies as a
function of membrane elastic parameters and adhesion strength to obtain
wrapping diagrams. We predict unwrapped, partially-wrapped, and
completely-wrapped states for prolate and oblate ellipsoids for various aspect
ratios and particle sizes. In contrast to spherical particles, where
partially-wrapped states exist only for finite surface tensions,
partially-wrapped states for ellipsoids occur already for tensionless
membranes. In addition, the partially-wrapped states are long-lived, because of
an increased energy cost for wrapping of the highly-curved tips. Our results
suggest a lower uptake rate of ellipsoidal particles by cells and thereby a
higher virulence of tubular viruses compared with icosahedral viruses, as well
as co-operative budding of ellipsoidal particles on membranes.
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The occurrence of the extensively used herbicide diuron in the environment
poses a severe threat to the ecosystem and human health. Four different
ligninolytic fungi were studied as biodegradation candidates for the removal of
diuron. Among them, T. versicolor was the most effective species, degrading
rapidly not only diuron (83%) but also the major metabolite 3,4-dichloroaniline
(100%), after 7-day incubation. During diuron degradation, five transformation
products (TPs) were found to be formed and the structures for three of them are
tentatively proposed. According to the identified TPs, a hydroxylated
intermediate 3-(3,4-dichlorophenyl)-1-hydroxymethyl-1-methylurea (DCPHMU) was
further metabolized into the N-dealkylated compounds
3-(3,4-dichlorophenyl)-1-methylurea (DCPMU) and 3,4-dichlorophenylurea (DCPU).
The discovery of DCPHMU suggests a relevant role of hydroxylation for
subsequent N-demethylation, helping to better understand the main reaction
mechanisms of diuron detoxification. Experiments also evidenced that
degradation reactions may occur intracellularly and be catalyzed by the
cytochrome P450 system. A response surface method, established by central
composite design, assisted in evaluating the effect of operational variables in
a trickle-bed bioreactor immobilized with T. versicolor on diuron removal. The
best performance was obtained at low recycling ratios and influent flow rates.
Furthermore, results indicate that the contact time between the contaminant and
immobilized fungi plays a crucial role in diuron removal. This study represents
a pioneering step forward amid techniques for bioremediation of
pesticides-contaminated waters using fungal reactors at a real scale.
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Sums play a prominent role in the formalisms of quantum mechanics, be it for
mixing and superposing states, or for composing state spaces. Surprisingly, a
conceptual analysis of quantum measurement seems to suggest that quantum
mechanics can be done without direct sums, expressed entirely in terms of the
tensor product. The corresponding axioms define classical spaces as objects
that allow copying and deleting data. Indeed, the information exchange between
the quantum and the classical worlds is essentially determined by their
distinct capabilities to copy and delete data. The sums turn out to be an
implicit implementation of this capabilities. Realizing it through explicit
axioms not only dispenses with the unnecessary structural baggage, but also
allows a simple and intuitive graphical calculus. In category-theoretic terms,
classical data types are dagger-compact Frobenius algebras, and quantum spectra
underlying quantum measurements are Eilenberg-Moore coalgebras induced by these
Frobenius algebras.
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If the electroweak symmetry-breaking sector becomes strongly interacting at
high energies, it can be probed through longitudinal $W$ scattering. We present
a model with many inelastic channels in the $W_L W_L$ scattering process,
corresponding to the production of heavy fermion pairs. These heavy fermions
affect the elastic scattering of $W_L$'s by propagating in loops, greatly
reducing the amplitudes in some charge channels. We conclude that the
symmetry-breaking sector cannot be fully explored by using, for example, the
$W_L^\pm W_L^\pm$ mode alone, even when no resonance is present; all $W_L W_L
\to W_L W_L$ scattering modes must be measured.
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We give a quantum chemical description of bridge photoisomerization reaction
of green fluorescent protein (GFP) chromophores using a representation over
three diabatic states. Bridge photoisomerization leads to non-radiative decay,
and competes with fluorescence in these systems. In the protein, this pathway
is suppressed, leading to fluorescence. Understanding the electronic structure
of the photoisomerization is a prerequisite to understanding how the protein
suppresses this pathway and preserves the emitting state of the chromophore. We
present a solution to the state-averaged complete active space problem, which
is spanned at convergence by three fragment-localized orbitals. We generate the
diabatic-state representation by applying a block diagonalization
transformation to the Hamiltonian calculated for the anionic chromophore model
HBDI with multi-reference, multi-state perturbation theory. The diabatic states
that emerge are charge-localized structures with a natural valence-bond
interpretation. At planar geometries, the diabatic picture recaptures the
charge transfer resonance of the anion. The strong S0-S1 excitation at these
geometries is reasonably described within a two-state model, but extension to a
three-state model is necessary to describe decay via two possible pathways
associated with photoisomerization of the (methine) bridge. Parametric
Hamiltonians based on the three-state ansatz can be fit directly to data
generated using the underlying active space. We provide an illustrative example
of such a parametric Hamiltonian.
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In surgical oncology, screening colonoscopy plays a pivotal role in providing
diagnostic assistance, such as biopsy, and facilitating surgical navigation,
particularly in polyp detection. Computer-assisted endoscopic surgery has
recently gained attention and amalgamated various 3D computer vision
techniques, including camera localization, depth estimation, surface
reconstruction, etc. Neural Radiance Fields (NeRFs) and Neural Implicit
Surfaces (NeuS) have emerged as promising methodologies for deriving accurate
3D surface models from sets of registered images, addressing the limitations of
existing colon reconstruction approaches stemming from constrained camera
movement.
However, the inadequate tissue texture representation and confused scale
problem in monocular colonoscopic image reconstruction still impede the
progress of the final rendering results. In this paper, we introduce a novel
method for colon section reconstruction by leveraging NeuS applied to
endoscopic images, supplemented by a single frame of depth map. Notably, we
pioneered the exploration of utilizing only one frame depth map in
photorealistic reconstruction and neural rendering applications while this
single depth map can be easily obtainable from other monocular depth estimation
networks with an object scale. Through rigorous experimentation and validation
on phantom imagery, our approach demonstrates exceptional accuracy in
completely rendering colon sections, even capturing unseen portions of the
surface. This breakthrough opens avenues for achieving stable and consistently
scaled reconstructions, promising enhanced quality in cancer screening
procedures and treatment interventions.
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Recently, a few peculiar Type Ia supernovae (SNe) that show exceptionally
large peak luminosity have been discovered. Their luminosity requires more than
1 Msun of 56Ni ejected during the explosion, suggesting that they might have
originated from super-Chandrasekhar mass white dwarfs. However, the nature of
these objects is not yet well understood. In particular, no data have been
taken at late phases, about one year after the explosion. We report on Subaru
and Keck optical spectroscopic and photometric observations of the SN Ia
2006gz, which had been classified as being one of these "overluminous" SNe Ia.
The late-time behavior is distinctly different from that of normal SNe Ia,
reinforcing the argument that SN 2006gz belongs to a different subclass than
normal SNe Ia. However, the peculiar features found at late times are not
readily connected to a large amount of 56Ni; the SN is faint, and it lacks [Fe
II] and [Fe III] emission. If the bulk of the radioactive energy escapes the SN
ejecta as visual light, as is the case in normal SNe Ia, the mass of 56Ni does
not exceed ~ 0.3 Msun. We discuss several possibilities to remedy the problem.
With the limited observations, however, we are unable to conclusively identify
which process is responsible. An interesting possibility is that the bulk of
the emission might be shifted to longer wavelengths, unlike the case in other
SNe Ia, which might be related to dense C-rich regions as indicated by the
early-phase data. Alternatively, it might be the case that SN 2006gz, though
peculiar, was actually not substantially overluminous at early times.
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We report the studies of ultrafast electron nanocrystallography on
size-selected Au nanoparticles (2-20 nm) supported on a molecular interface.
Reversible surface melting, melting, and recrystallization were investigated
with dynamical full-profile radial distribution functions determined with
sub-picosecond and picometer accuracies. In an ultrafast photoinduced melting,
the nanoparticles are driven to a non-equilibrium transformation, characterized
by the initial lattice deformations, nonequilibrium electron-phonon coupling,
and upon melting, the collective bonding and debonding, transforming
nanocrystals into shelled nanoliquids. The displasive structural excitation at
premelting and the coherent transformation with crystal/liquid coexistence
during photomelting differ from the reciprocal behavior of recrystallization,
where a hot lattice forms from liquid and then thermally contracts. The degree
of structural change and the thermodynamics of melting are found to depend on
the size of nanoparticle.
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A critical comparison is made between recent predictions of the cross
sections for diffractive Higgs production at the Tevatron and the LHC. We show
that the huge spread of the predictions arises either because different
diffractive processes are studied or because important effects are overlooked.
Exclusive production offers a reliable, viable Higgs signal at the LHC provided
that proton taggers are installed.
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We have investigated uudd\sbar pentaquarks by employing quark models with the
meson exchange and the effective gluon exchange as qq and q\qbar interactions.
The system for five quarks is dynamically solved; two quarks are allowed to
have a diquark-like qq correlation. It is found that the lowest mass of the
pentaquark is about 1947 -- 2144 MeV. There are parameter sets where the mass
of the lowest positive-parity state become lower than that of the
negative-parity states. Which parity corresponds to the observed peak is still
an open question. Relative distance of two quarks with the attractive
interaction is found to be by about 1.2 -- 1.3 times closer than that of the
repulsive one. The diquark-like quark correlation seems to play an important
role in the pentaquark systems.
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We introduce a new quantity, that we term recoverable information, defined
for stabilizer Hamiltonians. For such models, the recoverable information
provides a measure of the topological information, as well as a physical
interpretation, which is complementary to topological entanglement entropy. We
discuss three different ways to calculate the recoverable information, and
prove their equivalence. To demonstrate its utility, we compute recoverable
information for fracton models using all three methods where appropriate. From
the recoverable information, we deduce the existence of emergent $Z_2$
Gauss-law type constraints, which in turn imply emergent $Z_2$ conservation
laws for point-like quasiparticle excitations of an underlying topologically
ordered phase.
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Our aim in this paper is to investigate the asymptotic behavior of solutions
of the perturbed linear fractional differential system. We show that if the
original linear autonomous system is asymptotically stable then under the
action of small (either linear or nonlinear) nonautonomous perturbations the
trivial solution of the perturbed system is also asymptotically stable.
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Recent advances in data augmentation enable one to translate images by
learning the mapping between a source domain and a target domain. Existing
methods tend to learn the distributions by training a model on a variety of
datasets, with results evaluated largely in a subjective manner. Relatively few
works in this area, however, study the potential use of image synthesis methods
for recognition tasks. In this paper, we propose and explore the problem of
image translation for data augmentation. We first propose a lightweight yet
efficient model for translating texture to augment images based on a single
input of source texture, allowing for fast training and testing, referred to as
Single Image Texture Translation for data Augmentation (SITTA). Then we explore
the use of augmented data in long-tailed and few-shot image classification
tasks. We find the proposed augmentation method and workflow is capable of
translating the texture of input data into a target domain, leading to
consistently improved image recognition performance. Finally, we examine how
SITTA and related image translation methods can provide a basis for a
data-efficient, "augmentation engineering" approach to model training. Codes
are available at https://github.com/Boyiliee/SITTA.
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In the era of Exascale computing, writing efficient parallel programs is
indispensable and at the same time, writing sound parallel programs is very
difficult. Specifying parallelism with frameworks such as OpenMP is relatively
easy, but data races in these programs are an important source of bugs. In this
paper, we propose LLOV, a fast, lightweight, language agnostic, and static data
race checker for OpenMP programs based on the LLVM compiler framework. We
compare LLOV with other state-of-the-art data race checkers on a variety of
well-established benchmarks. We show that the precision, accuracy, and the F1
score of LLOV is comparable to other checkers while being orders of magnitude
faster. To the best of our knowledge, LLOV is the only tool among the
state-of-the-art data race checkers that can verify a C/C++ or FORTRAN program
to be data race free.
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In this paper, we study 2d Floquet conformal field theory, where the external
periodic driving is described by iterated logistic or tent maps. These maps are
known to be typical examples of dynamical systems exhibiting the order-chaos
transition, and we show that, as a result of such driving, the entanglement
entropy scaling develops fractal features when the corresponding dynamical
system approaches the chaotic regime. For the driving set by the logistic map,
fractal contribution to the scaling dominates, making entanglement entropy
highly oscillating function of the subsystem size.
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The equivalence group is determined for systems of linear ordinary
differential equations in both the standard form and the normal form. It is
then shown that the normal form of linear systems reducible by an invertible
point transformation to the canonical equation $\by^{(n)}=0$ consists of copies
of the same iterative equation. Other properties of iterative linear systems
are also derived, as well as the superposition formula for their general
solution.
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In this paper, a cooperative decision-making is presented, which is suitable
for intention-aware automated vehicle functions. With an increasing number of
highly automated and autonomous vehicles on public roads, trust is a very
important issue regarding their acceptance in our society. The most challenging
scenarios arise at low driving speeds of these highly automated and autonomous
vehicles, where interactions with vulnerable road users likely occur. Such
interactions must be addressed by the automation of the vehicle. The novelties
of this paper are the adaptation of a general cooperative and shared control
framework to this novel use case and the application of an explicit prediction
model of the pedestrian. An extensive comparison with state-of-the-art
algorithms is provided in a simplified test environment. The results show the
superiority of the proposed model-based algorithm compared to state-of-the-art
solutions and its suitability for real-world applications due to its real-time
capability.
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We study the dust properties of 192 nearby galaxies from the JINGLE survey
using photometric data in the 22-850micron range. We derive the total dust
mass, temperature T and emissivity index beta of the galaxies through the
fitting of their spectral energy distribution (SED) using a single modified
black-body model (SMBB). We apply a hierarchical Bayesian approach that reduces
the known degeneracy between T and beta. Applying the hierarchical approach,
the strength of the T-beta anti-correlation is reduced from a Pearson
correlation coefficient R=-0.79 to R=-0.52. For the JINGLE galaxies we measure
dust temperatures in the range 17-30 K and dust emissivity indices beta in the
range 0.6-2.2. We compare the SMBB model with the broken emissivity modified
black-body (BMBB) and the two modified black-bodies (TMBB) models. The results
derived with the SMBB and TMBB are in good agreement, thus applying the SMBB,
which comes with fewer free parameters, does not penalize the measurement of
the cold dust properties in the JINGLE sample. We investigate the relation
between T and beta and other global galaxy properties in the JINGLE and
Herschel Reference Survey (HRS) sample. We find that beta correlates with the
stellar mass surface density (R=0.62) and anti-correlates with the HI mass
fraction (M(HI)/M*, R=-0.65), whereas the dust temperature correlates strongly
with the SFR normalized by the dust mass (R=0.73). These relations can be used
to estimate T and beta in galaxies with insufficient photometric data available
to measure them directly through SED fitting.
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Supplementing earlier literature by e.g. Tipler, Clarke, & Ellis (1980),
Israel (1987), Thorne, (1994), Earman (1999), Senovilla & Garfinkle (2015),
Curiel (2019ab), and Landsman (2021ab), I provide a historical and conceptual
analysis of Penrose's path-breaking 1965 singularity (or incompleteness)
theorem. The emphasis is on the nature and historical origin of the assumptions
and definitions used in-or otherwise relevant to-the theorem, as well as on the
discrepancy between the (astro)physical goals of the theorem and its actual
content: even if its assumptions are met, the theorem fails to prove the
existence or formation of black holes.Penrose himself was well aware of this
gap, which he subsequently tried to overcome with his visionary and influential
cosmic censorship conjectures. Roughly speaking, to infer from (null) geodesic
incompleteness that there is a "black" object one needs weak cosmic censorship,
whereas in addition a "hole" exists (as opposed to a boundary of an extendible
space-time causing the incompleteness of geodesics) if strong cosmic censorship
holds.
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Neural radiance fields (NeRFs) are a deep learning technique that can
generate novel views of 3D scenes using sparse 2D images from different viewing
directions and camera poses. As an extension of conventional NeRFs in
underwater environment, where light can get absorbed and scattered by water,
SeaThru-NeRF was proposed to separate the clean appearance and geometric
structure of underwater scene from the effects of the scattering medium. Since
the quality of the appearance and structure of underwater scenes is crucial for
downstream tasks such as underwater infrastructure inspection, the reliability
of the 3D reconstruction model should be considered and evaluated. Nonetheless,
owing to the lack of ability to quantify uncertainty in 3D reconstruction of
underwater scenes under natural ambient illumination, the practical deployment
of NeRFs in unmanned autonomous underwater navigation is limited. To address
this issue, we introduce a spatial perturbation field D_omega based on Bayes'
rays in SeaThru-NeRF and perform Laplace approximation to obtain a Gaussian
distribution N(0,Sigma) of the parameters omega, where the diagonal elements of
Sigma correspond to the uncertainty at each spatial location. We also employ a
simple thresholding method to remove artifacts from the rendered results of
underwater scenes. Numerical experiments are provided to demonstrate the
effectiveness of this approach.
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Quantum matrix models in the large-N limit arise in many physical systems
like Yang-Mills theory with or without supersymmetry, quantum gravity,
string-bit models, various low energy effective models of string theory,
M(atrix) theory, quantum spin chain models, and strongly correlated electron
systems like the Hubbard model. We introduce, in a unifying fashion, a hierachy
of infinite-dimensional Lie superalgebras of quantum matrix models. One of
these superalgebras pertains to the open string sector and another one the
closed string sector. Physical observables of quantum matrix models like the
Hamiltonian can be expressed as elements of these Lie superalgebras. This
indicates the Lie superalgebras describe the symmetry of quantum matrix models.
We present the structure of these Lie superalgebras like their Cartan
subalgebras, root vectors, ideals and subalgebras. They are generalizations of
well-known algebras like the Cuntz algebra, the Virasoro algebra, the Toeplitz
algebra, the Witt algebra and the Onsager algebra. Just like we learnt a lot
about critical phenomena and string theory through their conformal symmetry
described by the Virasoro algebra, we may learn a lot about quantum
chromodynamics, quantum gravity and condensed matter physics through this
symmetry of quantum matrix models described by these Lie superalgebras.
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Obstructive sleep apnea syndrome is now considered as a major health care
topic. An in-vitro setup which reproduces and simplifies upper airway geometry
has been the basis to study the fluid/walls interaction that leads to an apnea.
It consists of a rigid pipe (the pharynx) in contact with a deformable latex
cylinder filled with water (the tongue). Air flows out of the rigid pipe and
induces pressure forces on the cylinder. We present a numerical model of this
setup: a finite element model of the latex cylinder is in interaction with a
fluid model. Simulation of an hypopnea (partial collapsus of the airway) has
been possible and in agreement with observations from the in-vitro setup. The
same phenomenon has been simulated on a soft palate model obtained from a
patient sagittal radiography. These first results encourage us to improve the
model so as it could reproduce the complete apnea phenomenon, and be used for a
planification purpose in sleep apnea surgery.
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Kernel design for Multi-output Gaussian Processes (MOGP) has received
increased attention recently. In particular, the Multi-Output Spectral Mixture
kernel (MOSM) arXiv:1709.01298 approach has been praised as a general model in
the sense that it extends other approaches such as Linear Model of
Corregionalization, Intrinsic Corregionalization Model and Cross-Spectral
Mixture. MOSM relies on Cram\'er's theorem to parametrise the power spectral
densities (PSD) as a Gaussian mixture, thus, having a structural restriction:
by assuming the existence of a PSD, the method is only suited for multi-output
stationary applications. We develop a nonstationary extension of MOSM by
proposing the family of harmonizable kernels for MOGPs, a class of kernels that
contains both stationary and a vast majority of non-stationary processes. A
main contribution of the proposed harmonizable kernels is that they
automatically identify a possible nonstationary behaviour meaning that
practitioners do not need to choose between stationary or non-stationary
kernels. The proposed method is first validated on synthetic data with the
purpose of illustrating the key properties of our approach, and then compared
to existing MOGP methods on two real-world settings from finance and
electroencephalography.
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Along with the development of AI democratization, the machine learning
approach, in particular neural networks, has been applied to wide-range
applications. In different application scenarios, the neural network will be
accelerated on the tailored computing platform. The acceleration of neural
networks on classical computing platforms, such as CPU, GPU, FPGA, ASIC, has
been widely studied; however, when the scale of the application consistently
grows up, the memory bottleneck becomes obvious, widely known as memory-wall.
In response to such a challenge, advanced quantum computing, which can
represent 2^N states with N quantum bits (qubits), is regarded as a promising
solution. It is imminent to know how to design the quantum circuit for
accelerating neural networks. Most recently, there are initial works studying
how to map neural networks to actual quantum processors. To better understand
the state-of-the-art design and inspire new design methodology, this paper
carries out a case study to demonstrate an end-to-end implementation. On the
neural network side, we employ the multilayer perceptron to complete image
classification tasks using the standard and widely used MNIST dataset. On the
quantum computing side, we target IBM Quantum processors, which can be
programmed and simulated by using IBM Qiskit. This work targets the
acceleration of the inference phase of a trained neural network on the quantum
processor. Along with the case study, we will demonstrate the typical procedure
for mapping neural networks to quantum circuits.
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Recently, gauged supergravities in three dimensions with Yang-Mills and
Chern-Simons type interactions have been constructed. In this article, we
demonstrate that any gauging of Yang-Mills type with semisimple gauge group
G_0, possibly including extra couplings to massive Chern-Simons vectors, is
equivalent on-shell to a pure Chern-Simons type gauging with non-semisimple
gauge group $G_0 \ltimes T \subset G$, where T is a certain translation group,
and where G is the maximal global symmetry group of the ungauged theory. We
discuss several examples.
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Entangling two quantum bits by letting them interact is the crucial
requirements for building a quantum processor. For qubits based on the spin of
the electron, these two-qubit gates are typically performed by exchange
interaction of the electrons captured in two nearby quantum dots. Since the
exchange interaction relies on tunneling of the electrons, the range of
interaction for conventional approaches is severely limited as the tunneling
amplitude decays exponentially with the length of the tunneling barrier. Here,
we present a novel approach to couple two spin qubits via a superconducting
coupler. In essence, the superconducting coupler provides a tunneling barrier
for the electrons which can be tuned with exquisite precision. We show that as
a result exchange couplings over a distance of several microns become
realistic, thus enabling flexible designs of multi-qubit systems.
|
The Origins, Spectral Interpretation, Resource Identification, and Security
Regolith Explorer (OSIRIS-REx) spacecraft arrived at its target, near-Earth
asteroid 101955 Bennu, in December 2018. After one year of operating in
proximity, the team selected a primary site for sample collection. In October
2020, the spacecraft descended to the surface of Bennu and collected a sample.
The spacecraft departed Bennu in May 2021 and will return the sample to Earth
in September 2023. The analysis of the returned sample will produce key data to
determine the history of this B-type asteroid and that of its components and
precursor objects. The main goal of the OSIRIS-REx Sample Analysis Plan is to
provide a framework for the Sample Analysis Team to meet the Level 1 mission
requirement to analyze the returned sample to determine presolar history,
formation age, nebular and parent-body alteration history, relation to known
meteorites, organic history, space weathering, resurfacing history, and energy
balance in the regolith of Bennu. To achieve this goal, this plan establishes a
hypothesis-driven framework for coordinated sample analyses, defines the
analytical instrumentation and techniques to be applied to the returned sample,
provides guidance on the analysis strategy for baseline, overguide, and
threshold amounts of returned sample, including a rare or unique lithology,
describes the data storage, management, retrieval, and archiving system,
establishes a protocol for the implementation of a micro-geographical
information system to facilitate co-registration and coordinated analysis of
sample science data, outlines the plans for Sample Analysis Readiness Testing,
and provides guidance for the transfer of samples from curation to the Sample
Analysis Team.
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Traditional pruning methods are known to be challenging to work in Large
Language Models (LLMs) for Generative AI because of their unaffordable training
process and large computational demands. For the first time, we introduce the
information entropy of hidden state features into a pruning metric design,
namely E-Sparse, to improve the accuracy of N:M sparsity on LLM. E-Sparse
employs the information richness to leverage the channel importance, and
further incorporates several novel techniques to put it into effect: (1) it
introduces information entropy to enhance the significance of parameter weights
and input feature norms as a novel pruning metric, and performs N:M sparsity
without modifying the remaining weights. (2) it designs global naive shuffle
and local block shuffle to quickly optimize the information distribution and
adequately cope with the impact of N:M sparsity on LLMs' accuracy. E-Sparse is
implemented as a Sparse-GEMM on FasterTransformer and runs on NVIDIA Ampere
GPUs. Extensive experiments on the LLaMA family and OPT models show that
E-Sparse can significantly speed up the model inference over the dense model
(up to 1.53X) and obtain significant memory saving (up to 43.52%), with
acceptable accuracy loss.
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The transformation of organic molecules into the simplest self-replicating
living system,a microorganism, is accomplished from a unique event or rare
events that occurred early in the Universe. The subsequent dispersal on cosmic
scales and evolution of life is guaranteed, being determined by well-understood
processes of physics and biology. Entire galaxies and clusters of galaxies can
be considered as connected biospheres, with lateral gene transfers, as
initially theorized by Joseph (2000), providing for genetic mixing and
Darwinian evolution on a cosmic scale. Big bang cosmology modified by modern
fluid mechanics suggests the beginning and wide intergalactic dispersal of life
occurred immediately after the end of the plasma epoch when the gas of
protogalaxies in clusters fragmented into clumps of planets. Stars are born
from binary mergers of such planets within such clumps. When stars devour their
surrounding planets to excess they explode, distributing necessary fertilizing
chemicals created only in stars with panspermial templates created only in
adjacent planets, moons and comets, to be gravitationally collected by the
planets and further converted to living organisms. Recent infrared images of
nearby star forming regions suggest that life formation on planets like Earth
is possible, but not inevitable.
|
We establish a connection between the representation theory of certain
noncommutative singular varieties and two-dimensional lattice models.
Specifically, we consider noncommutative biparametric deformations of the fiber
product of two Kleinian singularities of type $A$. Special examples are closely
related to Lie-Heisenberg algebras, the affine Lie algebra $A_1^{(1)}$, and a
finite W-algebra associated to $\mathfrak{sl}_4$.
The algebras depend on two scalars and two polynomials that must satisfy the
Mazorchuk-Turowska Equation (MTE), which we re-interpret as a quantization of
the ice rule (local current conservation) in statistical mechanics. Solutions
to the MTE, previously classified by the author and D. Rosso, can accordingly
be expressed in terms of multisets of higher spin vertex configurations on a
twisted cylinder.
We first reduce the problem of describing the category of weight modules to
the case of a single configuration $\mathscr{L}$. Secondly, we classify all
simple weight modules over the corresponding algebras
$\mathcal{A}(\mathscr{L})$, in terms of the connected components of the
cylinder minus $\mathscr{L}$. Lastly, we prove that $\mathcal{A}(\mathscr{L})$
are crystalline graded rings (as defined by Nauwelaerts and Van Oystaeyen), and
describe the center of $\mathcal{A}(\mathscr{L})$ explicitly in terms of
$\mathscr{L}$.
Along the way we prove several new results about twisted generalized Weyl
algebras and their simple weight modules.
|
Semiconducting single-wall carbon nanotubes (s-SWNTs) have proved to be
promising material for nanophotonics and optoelectronics. Due to the
possibility of tuning their direct band gap and controlling excitonic
recombinations in the near-infrared wavelength range, s-SWNT can be used as
efficient light emitters. We report the first experimental demonstration of
room temperature intrinsic optical gain as high as 190 cm-1 at a wavelength of
1.3 {\mu}m in a thin film doped with s-SWNT. These results constitute a
significant milestone toward the development of laser sources based on carbon
nanotubes for future high performance integrated circuits.
|
We generalize the notion of a Magnus expansion of a free group in order to
extend each of the Johnson homomorphisms defined on a decreasing filtration of
the Torelli group for a surface with one boundary component to the whole of the
automorphism group of a free group $\operatorname{Aut}(F_{n})$. The extended
ones are {\it not} homomorphisms, but satisfy an infinite sequence of
coboundary relations, so that we call them {\it the Johnson maps}. In this
paper we confine ourselves to studying the first and the second relations,
which have cohomological consequences about the group
$\operatorname{Aut}(F_{n})$ and the mapping class groups for surfaces. The
first one means that the first Johnson map is a twisted 1-cocycle of the group
$\operatorname{Aut}(F_{n})$. Its cohomology class coincides with ``the unique
elementary particle" of all the Morita-Mumford classes on the mapping class
group for a surface [Ka1] [KM1]. The second one restricted to the mapping class
group is equal to a fundamental relation among twisted Morita-Mumford classes
proposed by Garoufalidis and Nakamura [GN] and established by Morita and the
author [KM2]. This means we give a simple and coherent proof of the fundamental
relation. The first Johnson map gives the abelianization of the induced
automorphism group $IA_n$ of a free group in an explicit way.
|
A 3D fluid-structure interaction solver based on an improved
weakly-compressible moving particle simulation (WC-MPS) method and a
geometrically nonlinear shell structural model is developed and applied to
hydro-elastic free-surface flows. The fluid-structure coupling is performed by
a polygon wall boundary model that can handle particles and finite elements of
distinct sizes. In WC-MPS, a tuning-free diffusive term is introduced to the
continuity equation to mitigate non-physical pressure oscillations. Discrete
divergence operators are derived and applied to the polygon wall boundary, of
which the numerical stability is enhanced by a repulsive Lennard-Jones force.
Additionally, an efficient technique to deal with the interaction between fluid
particles placed at opposite sides of zero-thickness walls is proposed. The
geometrically nonlinear shell is modeled by an unstructured mesh of six-node
triangular elements. Finite rotations are considered with Rodrigues parameters
and a hyperelastic constitutive model is adopted. Benchmark examples involving
free-surface flows and thin-walled structures demonstrate that the proposed
model is robust, numerically stable and offers more efficient computation by
allowing mesh size larger than that of fluid particles.
|
Proof-theoretic semantics (P-tS) is the paradigm of semantics in which
meaning in logic is based on proof (as opposed to truth). A particular instance
of P-tS for intuitionistic propositional logic (IPL) is its base-extension
semantics (B-eS). This semantics is given by a relation called support,
explaining the meaning of the logical constants, which is parameterized by
systems of rules called bases that provide the semantics of atomic
propositions. In this paper, we interpret bases as collections of definite
formulae and use the operational view of the latter as provided by uniform
proof-search -- the proof-theoretic foundation of logic programming (LP) -- to
establish the completeness of IPL for the B-eS. This perspective allows
negation, a subtle issue in P-tS, to be understood in terms of the
negation-as-failure protocol in LP. Specifically, while the denial of a
proposition is traditionally understood as the assertion of its negation, in
B-eS we may understand the denial of a proposition as the failure to find a
proof of it. In this way, assertion and denial are both prime concepts in P-tS.
|
Learning from Demonstrations, the field that proposes to learn robot behavior
models from data, is gaining popularity with the emergence of deep generative
models. Although the problem has been studied for years under names such as
Imitation Learning, Behavioral Cloning, or Inverse Reinforcement Learning,
classical methods have relied on models that don't capture complex data
distributions well or don't scale well to large numbers of demonstrations. In
recent years, the robot learning community has shown increasing interest in
using deep generative models to capture the complexity of large datasets. In
this survey, we aim to provide a unified and comprehensive review of the last
year's progress in the use of deep generative models in robotics. We present
the different types of models that the community has explored, such as
energy-based models, diffusion models, action value maps, or generative
adversarial networks. We also present the different types of applications in
which deep generative models have been used, from grasp generation to
trajectory generation or cost learning. One of the most important elements of
generative models is the generalization out of distributions. In our survey, we
review the different decisions the community has made to improve the
generalization of the learned models. Finally, we highlight the research
challenges and propose a number of future directions for learning deep
generative models in robotics.
|
Biomedical literature is growing rapidly, making it challenging to curate and
extract knowledge manually. Biomedical natural language processing (BioNLP)
techniques that can automatically extract information from biomedical
literature help alleviate this burden. Recently, large Language Models (LLMs),
such as GPT-3 and GPT-4, have gained significant attention for their impressive
performance. However, their effectiveness in BioNLP tasks and impact on method
development and downstream users remain understudied. This pilot study (1)
establishes the baseline performance of GPT-3 and GPT-4 at both zero-shot and
one-shot settings in eight BioNLP datasets across four applications: named
entity recognition, relation extraction, multi-label document classification,
and semantic similarity and reasoning, (2) examines the errors produced by the
LLMs and categorized the errors into three types: missingness, inconsistencies,
and unwanted artificial content, and (3) provides suggestions for using LLMs in
BioNLP applications. We make the datasets, baselines, and results publicly
available to the community via
https://github.com/qingyu-qc/gpt_bionlp_benchmark.
|
We investigate the validity of the assertion that eternal inflation populates
the landscape of string theory. We verify that bubble solutions do not satisfy
the Klein Gordon equation for the landscape potential. Solutions to the
landscape potential within the formalism of quantum cosmology are Anderson
localized wavefunctions. Those are inconsistent with inflating bubble
solutions. The physical reasons behind the failure of a relation between
eternal inflation and the landscape are rooted in quantum phenomena such as
interference between wavefunction concentrated around the various vacua in the
landscape.
|
The pair-correlation functions for fluid ionic mixtures in arbitrary spatial
dimensions are computed in hypernetted chain (HNC) approximation. In the
primitive model, all ions are approximated as non-overlapping hyperspheres with
Coulomb interactions. Our spectral HNC solver is based on a Fourier-Bessel
transform introduced by Talman [J. Comput. Phys., 29, 35 (1978)], with
logarithmically spaced computational grids. Numeric efficiency for arbitrary
spatial dimensions is a commonly exploited virtue of this transform method.
Here, we highlight another advantage of logarithmic grids, consisting in
efficient sampling of pair-correlation functions for highly asymmetric ionic
mixtures. For three-dimensional fluids, ion size- and charge-ratios larger than
one thousand can be treated, corresponding to hitherto computationally not
accessed micrometer-sized colloidal spheres in 1-1 electrolyte. Effective
colloidal charge numbers are extracted from our primitive model results. For
moderately large ion size- and charge-asymmetries, we present Molecular
Dynamics simulation results that agree well with the approximate HNC pair
correlations.
|
Multi-task learning (MTL) aims to improve the performance of multiple related
prediction tasks by leveraging useful information from them. Due to their
flexibility and ability to reduce unknown coefficients substantially, the
task-clustering-based MTL approaches have attracted considerable attention.
Motivated by the idea of semisoft clustering of data, we propose a semisoft
task clustering approach, which can simultaneously reveal the task cluster
structure for both pure and mixed tasks as well as select the relevant
features. The main assumption behind our approach is that each cluster has some
pure tasks, and each mixed task can be represented by a linear combination of
pure tasks in different clusters. To solve the resulting non-convex constrained
optimization problem, we design an efficient three-step algorithm. The
experimental results based on synthetic and real-world datasets validate the
effectiveness and efficiency of the proposed approach. Finally, we extend the
proposed approach to a robust task clustering problem.
|
We present a comparative network theoretic analysis of the two largest global
transportation networks: The worldwide air-transportation network (WAN) and the
global cargoship network (GCSN). We show that both networks exhibit striking
statistical similarities despite significant differences in topology and
connectivity. Both networks exhibit a discontinuity in node and link
betweenness distributions which implies that these networks naturally segragate
in two different classes of nodes and links. We introduce a technique based on
effective distances, shortest paths and shortest-path trees for strongly
weighted symmetric networks and show that in a shortest-path-tree
representation the most significant features of both networks can be readily
seen. We show that effective shortest-path distance, unlike conventional
geographic distance measures, strongly correlates with node centrality
measures. Using the new technique we show that network resilience can be
investigated more precisely than with contemporary techniques that are based on
percolation theory. We extract a functional relationship between node
characteristics and resilience to network disruption. Finally we discuss the
results, their implications and conclude that dynamic processes that evolve on
both networks are expected to share universal dynamic characteristics.
|
Suppose that we are given independent, identically distributed samples $x_l$
from a mixture $\mu$ of no more than $k$ of $d$-dimensional spherical gaussian
distributions $\mu_i$ with variance $1$, such that the minimum $\ell_2$
distance between two distinct centers $y_l$ and $y_j$ is greater than $\sqrt{d}
\Delta$ for some $c \leq \Delta $, where $c\in (0,1)$ is a small positive
universal constant. We develop a randomized algorithm that learns the centers
$y_l$ of the gaussians, to within an $\ell_2$ distance of $\delta <
\frac{\Delta\sqrt{d}}{2}$ and the weights $w_l$ to within $cw_{min}$ with
probability greater than $1 - \exp(-k/c)$. The number of samples and the
computational time is bounded above by $poly(k, d, \frac{1}{\delta})$. Such a
bound on the sample and computational complexity was previously unknown when
$\omega(1) \leq d \leq O(\log k)$. When $d = O(1)$, this follows from work of
Regev and Vijayaraghavan. These authors also show that the sample complexity of
learning a random mixture of gaussians in a ball of radius $\Theta(\sqrt{d})$
in $d$ dimensions, when $d$ is $\Theta( \log k)$ is at least $poly(k,
\frac{1}{\delta})$, showing that our result is tight in this case.
|
Symmetry Adapted Perturbation Theory (SAPT) has become an important tool when
predicting and analyzing intermolecular interactions. Unfortunately, DFT-SAPT,
which uses Density Functional Theory (DFT) for the underlying monomers, has
some arbitrariness concerning the exchange-correlation potential and the
exchange-correlation kernel involved. By using ab initio Brueckner Doubles
densities and constructing Kohn-Sham orbitals via the Zhao-Morrison-Parr (ZMP)
method, we are able to lift the dependence of DFT-SAPT on DFT
exchange-correlation potential models in first order. This way, we can compute
the monomers at the Coupled-Cluster level of theory and utilize SAPT for the
intermolecular interaction energy. The resulting ZMP-SAPT approach is tested
for small dimer systems involving rare gas atoms, cations, and anions and shown
to compare well with the Tang-Toennies model and coupled cluster results.
|
Let $\Bbb Z$ and $\Bbb N$ be the set of integers and the set of positive
integers, respectively. For $a_1,a_2,\ldots,a_k,n\in\Bbb N$ let
$N(a_1,a_2,\ldots,a_k;n)$ be the number of representations of $n$ by
$a_1x_1^2+a_2x_2^2+\cdots+a_kx_k^2$, and let $t(a_1,a_2,\ldots,a_k;n)$ be the
number of representations of $n$ by
$a_1\frac{x_1(x_1-1)}2+a_2\frac{x_2(x_2-1)}2+\cdots+a_k\frac{x_k(x_k-1)}2$
$(x_1,\ldots,x_k\in\Bbb Z$). In this paper, by using Ramanujan's theta
functions $\varphi(q)$ and $\psi(q)$ we reveal many relations between
$t(a_1,a_2,\ldots,a_k;n)$ and $N(a_1,a_2,\ldots,a_k;8n+a_1+\cdots+a_k)$ for
$k=3,4$.
|
Quantitative data is frequently represented using color, yet designing
effective color mappings is a challenging task, requiring one to balance
perceptual standards with personal color preference. Current design tools
either overwhelm novices with complexity or offer limited customization
options. We present ColorMaker, a mixed-initiative approach for creating
colormaps. ColorMaker combines fluid user interaction with real-time
optimization to generate smooth, continuous color ramps. Users specify their
loose color preferences while leaving the algorithm to generate precise color
sequences, meeting both designer needs and established guidelines. ColorMaker
can create new colormaps, including designs accessible for people with
color-vision deficiencies, starting from scratch or with only partial input,
thus supporting ideation and iterative refinement. We show that our approach
can generate designs with similar or superior perceptual characteristics to
standard colormaps. A user study demonstrates how designers of varying skill
levels can use this tool to create custom, high-quality colormaps. ColorMaker
is available at https://colormaker.org
|
We analyze the modular properties of the effective CFT description for paired
states, proposed in cond-mat/0003453, corresponding to the non-standard filling
nu =1/(p+1). We construct its characters for the twisted and the untwisted
sector and the diagonal partition function. We show that the degrees of freedom
entering our partition function naturally go to complete a Z_2-orbifold
construction of the CFT for the Halperin state. Different behaviours for the p
even and p odd cases are also studied. Finally it is shown that the tunneling
phenomenon selects out a twist invariant CFT which is identified with the
Moore-Read model.
|
In the present work, we provide results from specific heat, magnetic
susceptibility, dielectric constant, ac conductivity, and electrical
polarization measurements performed on the lacunar spinel GaV4Se8. With
decreasing temperature, we observe a transition from the paraelectric and
paramagnetic cubic state into a polar, probably ferroelectric state at 42 K
followed by magnetic ordering at 18 K. The polar transition is likely driven by
the Jahn-Teller effect due to the degeneracy of the V4 cluster orbitals. The
excess polarization arising in the magnetic phase indicates considerable
magnetoelectric coupling. Overall, the behavior of GaV4Se8 in many respects is
similar to that of the skyrmion host GaV4S8, exhibiting a complex interplay of
orbital, spin, lattice, and polar degrees of freedom. However, its dielectric
behavior at the polar transition markedly differs from that of the Jahn-Teller
driven ferroelectric GeV4S8, which can be ascribed to the dissimilar electronic
structure of the Ge compound.
|
Recent proposals by C.S. Unnikrishnan concerning locality and Bell's theorem
are critically analysed.
|
Bayesian analyses are often performed using so-called noninformative priors,
with a view to achieving objective inference about unknown parameters on which
available data depends. Noninformative priors depend on the relationship of the
data to the parameters over the sample space. Combining Bayesian updating -
multiplying an existing posterior density for parameters being estimated by a
likelihood function derived from independent new data that depend on those
parameters and renormalizing - with use of noninformative priors gives rise to
inconsistency where existing and new data depend on continuous parameters in
different ways. In such cases, noninformative priors for inference from only
the existing and from only the new data would differ, so Bayesian updating
would give different final posterior densities depending on which set of data
was used to derive an initial posterior and which was used to update that
posterior. I propose a revised Bayesian updating method, which resolves this
inconsistency by updating the prior as well as the likelihood function, and
involves only a single application of Bayes' theorem. The revised method is
also applicable where actual prior information as to parameter values exists
and inference that objectively reflects the existing information as well as new
data is sought. I demonstrate by numerical testing the probability-matching
superiority of the proposed revised updating method, in two cases.
|
Based on a variant of frequency function, we improve the vanishing order of
solutions for Schr\"{o}dinger equations which describes quantitative behavior
of strong uniqueness continuation property. For the first time, we investigate
the quantitative uniqueness of higher order elliptic equations and show the
vanishing order of solutions. Furthermore, strong unique continuation is
established for higher order elliptic equations using this variant of frequency
function.
|
We show that negative refraction with minimal absorption can be obtained by
means of quantum interference effects similar to electromagnetically induced
transparency. Coupling a magnetic dipole transition coherently with an electric
dipole transition leads to electromagnetically induced chirality, which can
provide negative refraction without requiring negative permeability, and also
suppresses absorption. This technique allows negative refraction in the optical
regime at densities where the magnetic susceptibility is still small and with
refraction/absorption ratios that are orders of magnitude larger than those
achievable previously. Furthermore, the value of the refractive index can be
fine-tuned via external laser fields, which is essential for practical
realization of sub-diffraction-limit imaging.
|
Temporally and spatially resolved measurements of protein transport inside
cells provide important clues to the functional architecture and dynamics of
biological systems. Fluorescence Recovery After Photobleaching (FRAP) technique
has been used over the past three decades to measure the mobility of
macromolecules and protein transport and interaction with immobile structures
inside the cell nucleus. A theoretical model is presented that aims to describe
protein transport inside the nucleus, a process which is influenced by the
presence of a boundary (i.e. membrane). A set of reaction-diffusion equations
is employed to model both the diffusion of proteins and their interaction with
immobile binding sites. The proposed model has been designed to be applied to
biological samples with a Confocal Laser Scanning Microscope (CLSM) equipped
with the feature to bleach regions characterised by a scanning beam that has a
radially Gaussian distributed profile. The proposed model leads to FRAP curves
that depend on the on- and off-rates. Semi-analytical expressions are used to
define the boundaries of on- (off-) rate parameter space in simplified cases
when molecules move within a bounded domain. The theoretical model can be used
in conjunction to experimental data acquired by CLSM to investigate the
biophysical properties of proteins in living cells.
|
Elastic stress concentration at tips of long slender objects moving in
viscoelastic fluids has been observed in numerical simulations, but despite the
prevalence of flagellated motion in complex fluids in many biological
functions, the physics of stress accumulation near tips has not been analyzed.
Here we theoretically investigate elastic stress development at tips of slender
objects by computing the leading order viscoelastic correction to the
equilibrium viscous flow around long cylinders, using the weak-coupling limit.
In this limit nonlinearities in the fluid are retained allowing us to study the
biologically relevant parameter regime of high Weissenberg number. We calculate
a stretch rate from the viscous flow around cylinders to predict when large
elastic stress develops at tips, find thresholds for large stress development
depending on orientation, and calculate greater stress accumulation near tips
of cylinders oriented parallel to motion over perpendicular.
|
We compare the quenched hadron spectrum on blocked and unblocked lattices for
the Wilson quark action, the clover action and the tadpole-improved clover
action. The latter gives a spectrum markedly closer to the original one, even
though the cutoff is 1/a ~ 500 Mev.
|
We revisit recent claims that there is a "cold spot" in both number counts
and brightness of radio sources in the NVSS survey, with location coincident
with the previously detected cold spot in WMAP. Such matching cold spots would
be difficult if not impossible to explain in the standard LCDM cosmological
model. Contrary to the claim, we find no significant evidence for the radio
cold spot, after including systematic effects in NVSS, and carefully accounting
for the effect of a posteriori choices when assessing statistical significance.
|
We explicitly show how the chiral superstring amplitudes can be obtained
through factorisation of the higher genus chiral measure induced by suitable
degenerations of Riemann surfaces. This powerful tool also allows to derive, at
any genera, consistency relations involving the amplitudes and the measure. A
key point concerns the choice of the local coordinate at the node on degenerate
Riemann surfaces that greatly simplifies the computations. As a first
application, starting from recent ansaetze for the chiral measure up to genus
five, we compute the chiral two-point function for massless Neveu-Schwarz
states at genus two, three and four. For genus higher than three, these
computations include some new corrections to the conjectural formulae appeared
so far in the literature. After GSO projection, the two-point function vanishes
at genus two and three, as expected from space-time supersymmetry arguments,
but not at genus four. This suggests that the ansatz for the superstring
measure should be corrected for genus higher than four.
|
We present the direct imaging discovery of a low-mass companion to the nearby
accelerating F star, HIP 5319, using SCExAO coupled with the CHARIS, VAMPIRES,
and MEC instruments in addition to Keck/NIRC2 imaging. CHARIS $JHK$ (1.1-2.4
$\mu$m) spectroscopic data combined with VAMPIRES 750 nm, MEC $Y$, and NIRC2
$L_{\rm p}$ photometry is best matched by an M3--M7 object with an effective
temperature of T=3200 K and surface gravity log($g$)=5.5. Using the relative
astrometry for HIP 5319 B from CHARIS and NIRC2 and absolute astrometry for the
primary from $Gaia$ and $Hipparcos$ and adopting a log-normal prior assumption
for the companion mass, we measure a dynamical mass for HIP 5319 B of
$31^{+35}_{-11}M_{\rm J}$, a semimajor axis of $18.6^{+10}_{-4.1}$ au, an
inclination of $69.4^{+5.6}_{-15}$ degrees, and an eccentricity of
$0.42^{+0.39}_{-0.29}$. However, using an alternate prior for our dynamical
model yields a much higher mass of 128$^{+127}_{-88}M_{\rm J}$. Using data
taken with the LCOGT NRES instrument we also show that the primary HIP 5319 A
is a single star in contrast to previous characterizations of the system as a
spectroscopic binary. This work underscores the importance of assumed priors in
dynamical models for companions detected with imaging and astrometry and the
need to have an updated inventory of system measurements.
|
We define a new algebra of noncommutative differential forms for any Hopf
algebra with an invertible antipode. We prove that there is a one to one
correspondence between anti-Yetter-Drinfeld modules, which serve as
coefficients for the Hopf cyclic (co)homology, and modules which admit a flat
connection with respect to our differential calculus. Thus we show that these
coefficient modules can be regarded as ``flat bundles'' in the sense of Connes'
noncommutative differential geometry.
|
Consider the following interacting particle system on the $d$-ary tree, known
as the frog model: Initially, one particle is awake at the root and i.i.d.
Poisson many particles are sleeping at every other vertex. Particles that are
awake perform simple random walks, awakening any sleeping particles they
encounter. We prove that there is a phase transition between transience and
recurrence as the initial density of particles increases, and we give the order
of the transition up to a logarithmic factor.
|
Because of the significant increase in size and complexity of the networks,
the distributed computation of eigenvalues and eigenvectors of graph matrices
has become very challenging and yet it remains as important as before. In this
paper we develop efficient distributed algorithms to detect, with higher
resolution, closely situated eigenvalues and corresponding eigenvectors of
symmetric graph matrices. We model the system of graph spectral computation as
physical systems with Lagrangian and Hamiltonian dynamics. The spectrum of
Laplacian matrix, in particular, is framed as a classical spring-mass system
with Lagrangian dynamics. The spectrum of any general symmetric graph matrix
turns out to have a simple connection with quantum systems and it can be thus
formulated as a solution to a Schr\"odinger-type differential equation. Taking
into account the higher resolution requirement in the spectrum computation and
the related stability issues in the numerical solution of the underlying
differential equation, we propose the application of symplectic integrators to
the calculation of eigenspectrum. The effectiveness of the proposed techniques
is demonstrated with numerical simulations on real-world networks of different
sizes and complexities.
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In 1992, Agache and Chaple introduced the concept of a semi-symmetric
non-metric connection([1]). The semi-symmetric non-metric connection does not
satisfy the Schur`s theorem. The purpose of the present paper is to study some
properties of a new semi-symmetric non-metric connection satisfying the Schur`s
theorem in a Riemannian manifold. And we considered necessary and sufficient
condition that a Riemannian manifold with a semi-symmetric non-metric
connection be a Riemannian manifold with constant curvature.
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We report the formation of bound star clusters in a sample of high-resolution
cosmological zoom-in simulations of z>5 galaxies from the FIRE project. We find
that bound clusters preferentially form in high-pressure clouds with gas
surface densities over 10^4 Msun pc^-2, where the cloud-scale star formation
efficiency is near unity and young stars born in these regions are
gravitationally bound at birth. These high-pressure clouds are compressed by
feedback-driven winds and/or collisions of smaller clouds/gas streams in highly
gas-rich, turbulent environments. The newly formed clusters follow a power-law
mass function of dN/dM~M^-2. The cluster formation efficiency is similar across
galaxies with stellar masses of ~10^7-10^10 Msun at z>5. The age spread of
cluster stars is typically a few Myrs and increases with cluster mass. The
metallicity dispersion of cluster members is ~0.08 dex in [Z/H] and does not
depend on cluster mass significantly. Our findings support the scenario that
present-day old globular clusters (GCs) were formed during relatively normal
star formation in high-redshift galaxies. Simulations with a stricter/looser
star formation model form a factor of a few more/fewer bound clusters per
stellar mass formed, while the shape of the mass function is unchanged.
Simulations with a lower local star formation efficiency form more stars in
bound clusters. The simulated clusters are larger than observed GCs due to
finite resolution. Our simulations are among the first cosmological simulations
that form bound clusters self-consistently in a wide range of high-redshift
galaxies.
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We test a model of inflation with a fast-rolling kinetic-dominated initial
condition against data from Planck using Markov chain Monte Carlo parameter
estimation. We test both an $m^2 \phi^2$ potential and the $R+R^2$ gravity
model and perform a full numerical calculation of both the scalar and tensor
primordial power spectra. We find a slight (though not significant) improvement
in fit for this model over the standard eternal slow-roll case.
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In many models of the Calvin cycle of photosynthesis it is observed that
there are solutions where concentrations of key substances belonging to the
cycle tend to zero at late times, a phenomenon known as overload breakdown. In
this paper we prove theorems about the existence and non-existence of solutions
of this type and obtain information on which concentrations tend to zero when
overload breakdown occurs. As a starting point we take a model of Pettersson
and Ryde-Pettersson which seems to be prone to overload breakdown and a
modification of it due to Poolman which was intended to avoid this effect.
|
A conceptual framework for variational formulations of physical theories is
proposed. Such a framework is displayed here just for statics, but it is
designed to be subsequently adapted to variational formulations of static field
theories and dynamics.
|
Power systems are growing rapidly, due to the ever-increasing demand for
electrical power. These systems require novel methodologies and modern tools
and technologies, to better perform, particularly for communication among
different parts. Therefore, power systems are facing new challenges such as
energy trading and marketing and cyber threats. Using blockchain in power
systems, as a solution, is one of the newest methods. Most studies aim to
investigate innovative approach-es of blockchain application in power systems.
Even though, many articles published to support the research activities, there
has not been any bibliometric analysis which specifies the research trends.
This paper aims to present a bibliographic analysis of the blockchain
application in power systems related literature, in the Web of Science (WoS)
database between January 2009 and July 2019. This paper discusses the research
activities and performed a detailed analysis by looking at the number of
articles published, citations, institutions, research areas, and authors. From
the analysis, it was concluded that there are several significant impacts of
research activities in China and the USA, in comparison to other countries.
|
We study the spherical collapse of an over-density of a barotropic fluid with
linear equation of state in a cosmological background. Fully relativistic
simulations are performed by using the Baumgarte-Shibata-Shapiro-Nakamura
formalism jointly with the Valencia formulation of the hydrodynamics. This
permits us to test the universality of the critical collapse with respect to
the matter type by considering the constant equation of state parameter
$\omega$ as a control parameter. We exhibit, for a fixed radial profile of the
energy-density contrast, the existence of a critical value $\omega^*$ for the
equation of state parameter under which the fluctuation collapses to a black
hole and above which it is diluting. It is shown numerically that the mass of
the formed black hole, for subcritical solutions, obeys a scaling law $M\propto
|\omega - \omega^*|^\gamma$ with a critical exponent $\gamma$ independent on
the matter type, revealing the universality. This universal scaling law is
shown to be verified in the empty Minkoswki and de Sitter space-times. For the
full matter Einstein-de Sitter universe, the universality is not observed if
conformally flat sub-horizon initial conditions are used. But when
super-horizon initial conditions computed from the long-wavelength
approximation are used, the universality appears to be true.
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Let g and p be non-negative integers.
Let A(g,p) denote the group consisting of all those automorphisms of the free
group on {t_1,...,t_p, x_1,...,x_g, y_1,...y_g} which fix the element
t_1t_2...t_p[x_1,y_1]...[x_g,y_g] and permute the set of conjugacy classes
{[t_1],....,[t_p]}. Labru\`ere and Paris, building on work of Artin, Magnus,
Dehn, Nielsen, Lickorish, Zieschang, Birman, Humphries, and others, showed that
A(g,p) is generated by a set that is called the ADLH set. We use methods of
Zieschang and McCool to give a self-contained, algebraic proof of this result.
Labru\`ere and Paris also gave defining relations for the ADLH set in A(g,p);
we do not know an algebraic proof of this for g > 1. Consider an orientable
surface S(g,p) of genus g with p punctures, such that (g,p) is not (0,0) or
(0,1). The algebraic mapping-class group of S(g,p), denoted M(g,p), is defined
as the group of all those outer automorphisms of the one-relator group with
generating set {t_1,...,t_p, x_1,...,x_g, y_1,...y_g} and relator
t_1t_2...t_p[x_1,y_1]...[x_g,y_g] which permute the set of conjugacy classes
{[t_1],....,[t_p]}. It now follows from a result of Nielsen that M(g,p) is
generated by the image of the ADLH set together with a reflection. This gives a
new way of seeing that M(g,p) equals the (topological) mapping-class group of
S(g,p), along lines suggested by Magnus, Karrass, and Solitar in 1966.
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In this work we improve existing calculations of radiative energy loss by
computing corrections that implement energy-momentum conservation, previously
only implemented a posteriori, in a rigorous way. Using the path-integral
formalism, we compute in-medium splittings allowing transverse motion of all
particles in the emission process, thus relaxing the assumption that only the
softest particle is permitted such movement. This work constitutes the
extension of the computation carried out for x$\rightarrow$1 in Phys. Lett.
B718 (2012) 160-168, to all values of x, the momentum fraction of the energy of
the parent parton carried by the emitted gluon. In order to accomplish a
general description of the whole in-medium showering process, in this work we
allow for arbitrary formation times for the emitted gluon. We provide general
expressions and their realisation in the path integral formalism within the
harmonic oscillator approximation.
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We investigate the birth and evolution of Galactic isolated radio pulsars. We
begin by estimating their birth space velocity distribution from proper motion
measurements of Brisken et al. (2002, 2003). We find no evidence for
multimodality of the distribution and favor one in which the absolute
one-dimensional velocity components are exponentially distributed and with a
three-dimensional mean velocity of 380^{+40}_{-60} km s^-1. We then proceed
with a Monte Carlo-based population synthesis, modelling the birth properties
of the pulsars, their time evolution, and their detection in the Parkes and
Swinburne Multibeam surveys. We present a population model that appears
generally consistent with the observations. Our results suggest that pulsars
are born in the spiral arms, with a Galactocentric radial distribution that is
well described by the functional form proposed by Yusifov & Kucuk (2004), in
which the pulsar surface density peaks at radius ~3 kpc. The birth spin period
distribution extends to several hundred milliseconds, with no evidence of
multimodality. Models which assume the radio luminosities of pulsars to be
independent of the spin periods and period derivatives are inadequate, as they
lead to the detection of too many old simulated pulsars in our simulations.
Dithered radio luminosities proportional to the square root of the spin-down
luminosity accommodate the observations well and provide a natural mechanism
for the pulsars to dim uniformly as they approach the death line, avoiding an
observed pile-up on the latter. There is no evidence for significant torque
decay (due to magnetic field decay or otherwise) over the lifetime of the
pulsars as radio sources (~100 Myr). Finally, we estimate the pulsar birthrate
and total number of pulsars in the Galaxy.
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Stellar-mass primordial black holes (PBHs) from the early Universe can
directly contribute to the gravitational wave (GW) events observed by LIGO, but
can only comprise a subdominant component of the dark matter (DM). The primary
DM constituent will generically form massive halos around seeding stellar-mass
PBHs. We demonstrate that gravitational lensing of sources at cosmological
($\gtrsim$Gpc) distances can directly explore DM halo dresses engulfing PBHs,
challenging for lensing of local sources in the vicinity of Milky Way. Strong
lensing analysis of fast radio bursts detected by CHIME survey already starts
to probe parameter space of dressed stellar-mass PBHs, and upcoming searches
can efficiently explore dressed PBHs over $\sim 10-10^5 M_{\odot}$ mass-range
and provide a stringent test of the PBH scenario for the GW events. Our
findings establish a general test for a broad class of DM models with
stellar-mass PBHs, including those where QCD axions or WIMP-like particles
comprise predominant DM. The results open a new route for exploring dressed
PBHs with various types of lensing events at cosmological distances, such as
supernovae and caustic crossings.
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Similarity search in high-dimentional spaces is a pivotal operation found a
variety of database applications. Recently, there has been an increase interest
in similarity search for online content-based multimedia services. Those
services, however, introduce new challenges with respect to the very large
volumes of data that have to be indexed/searched, and the need to minimize
response times observed by the end-users. Additionally, those users dynamically
interact with the systems creating fluctuating query request rates, requiring
the search algorithm to adapt in order to better utilize the underline hardware
to reduce response times. In order to address these challenges, we introduce
hypercurves, a flexible framework for answering approximate k-nearest neighbor
(kNN) queries for very large multimedia databases, aiming at online
content-based multimedia services. Hypercurves executes on hybrid CPU--GPU
environments, and is able to employ those devices cooperatively to support
massive query request rates. In order to keep the response times optimal as the
request rates vary, it employs a novel dynamic scheduler to partition the work
between CPU and GPU. Hypercurves was throughly evaluated using a large database
of multimedia descriptors. Its cooperative CPU--GPU execution achieved
performance improvements of up to 30x when compared to the single CPU-core
version. The dynamic work partition mechanism reduces the observed query
response times in about 50% when compared to the best static CPU--GPU task
partition configuration. In addition, Hypercurves achieves superlinear
scalability in distributed (multi-node) executions, while keeping a high
guarantee of equivalence with its sequential version --- thanks to the proof of
probabilistic equivalence, which supported its aggressive parallelization
design.
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We present a sample of 8321 candidate Field Horizontal-Branch (FHB) stars
selected by automatic spectral classification in the digital data base of the
Hamburg/ESO objective-prism survey. The stars are distributed over 8225 square
degrees of the southern sky, at |b| > 30 deg. The average distance of the
sample, assuming that they are all FHB stars, is 9.8 kpc, and distances of up
to ~30 kpc are reached. Moderate-resolution spectroscopic follow-up
observations and UBV photometry of 125 test sample stars demonstrate that the
contamination of the full candidate sample with main-sequence A-type stars is <
16%, while it would be up to 50% in a flux-limited sample at high galactic
latitudes. Hence more than ~6800 of our FHB candidates are expected to be
genuine FHB stars. The candidates are being used as distance probes for
high-velocity clouds and for studies of the structure and kinematics of the
Galactic halo.
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We propose a simple theory for the dynamics of model glass-forming fluids,
which should be solvable using a mean-field-like approach. The theory is based
on transparent physical assumptions, which can be tested in computer
simulations. The theory predicts an ergodicity-breaking transition that is
identical to the so-called dynamic transition predicted within the replica
approach. Thus, it can provide the missing dynamic component of the random
first order transition framework. In the large-dimensional limit the theory
reproduces the result of a recent exact calculation of Maimbourg et al. [PRL
116, 015902 (2016)]. Our approach provides an alternative, physically motivated
derivation of this result.
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We investigate the influence of the external fields on the stability of spin
helix states in a XXZ Heisenberg model. Exact diagonalization on finite system
shows that random transverse fields in x and y directions drive the transition
from integrability to nonintegrability. It results in the fast decay of a
static helix state, which is the eigenstate of an unperturbed XXZ Heisenberg
model. However, in the presence of uniform z field, the static helix state
becomes a dynamic helix state with a relatively long life as a quantum scar
state.
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We study polar coding for stochastic processes with memory. For example, a
process may be defined by the joint distribution of the input and output of a
channel. The memory may be present in the channel, the input, or both. We show
that $\psi$-mixing processes polarize under the standard Ar\i{}kan transform,
under a mild condition. We further show that the rate of polarization of the
\emph{low-entropy} synthetic channels is roughly $O(2^{-\sqrt{N}})$, where $N$
is the blocklength. That is, essentially the same rate as in the memoryless
case.
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PG 0014+067 is one of the most promising pulsating subdwarf B stars for
seismic analysis, as it has a rich pulsation spectrum. The richness of its
pulsations, however, poses a fundamental challenge to understanding the
pulsations of these stars, as the mode density is too complex to be explained
only with radial and nonradial low degree (l < 3) p-modes without rotational
splittings. One proposed solution, for the case of PG 0014+067 in particular,
assigns some modes with high degree (l=3). On the other hand, theoretical
models of sdB stars suggest that they may retain rapidly rotating cores, and so
the high mode density may result from the presence of a few rotationally-split
triplet (l=1), quintuplet (l=2) modes, along with radial (l=0) p-modes. To
examine alternative theoretical models for these stars, we need better
frequency resolution and denser longitude coverage. Therefore, we observed this
star with the Whole Earth Telescope for two weeks in October 2004. In this
paper we report the results of Whole Earth Telescope observations of the
pulsating subdwarf B star PG 0014+067. We find that the frequencies seen in PG
0014+067 do not appear to fit any theoretical model currently available;
however, we find a simple empirical relation that is able to match all of the
well-determined frequencies in this star.
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We study the response of a thin superconducting amorphous InO film with
variable oxygen content to a parallel magnetic field. A field-induced
superconductor-insulator transition (SIT) is observed that is very similar to
the one in normal magnetic fields. As the boson-vortex duality, which is the
key-stone of the theory of the field-induced SIT, is obviously absent in the
parallel configuration, we have to draw conclusion about the theory
insufficiency.
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Universe structure emerges in the unreduced, complex-dynamic interaction
process with the simplest initial configuration (two attracting homogeneous
fields, quant-ph/9902015). The unreduced interaction analysis gives
intrinsically creative cosmology, describing the real, explicitly emerging
world structure with dynamic randomness on each scale. Without imposing any
postulates or entities, we obtain physically real space, time, elementary
particles with their detailed structure and intrinsic properties, causally
complete and unified version of quantum and relativistic behaviour, the origin
and number of naturally unified fundamental forces, and classical behaviour
emergence in closed systems (gr-qc/9906077). Main problems of standard
cosmology and astrophysics are consistently solved in this extended picture
(without introduction of any additional entities), including those of quantum
cosmology and gravity, entropy growth and time, "hierarchy" of elementary
particles, "anthropic" difficulties, space-time flatness, and "missing"
("dark") mass and energy. The observed universe structure and laws can be
presented as manifestations of the universal symmetry (conservation) of
complexity providing the unified, irregular, but exact (never "broken") Order
of the World (physics/0404006).
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Let $G$~be a real Lie group and let $G^\circ$ be the identity component
of~$G$. Let $G$~act on a $C^\infty$ real manifold~$M$. Assume the action is
$C^\infty$. Assume that the fixpoint set of any nontrivial element of~$G^\circ$
has empty interior in~$M$. Let $n:=\dim G$. Assume $n\ge1$. Let $F$ be the
frame bundle of~$M$ of order $n-1$. We prove: there exists a $G$-invariant
dense open subset~$Q$ of~$F$ such that the $G$-action on $Q$ has discrete
stabilizers.
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We use the shear transformation zone (STZ) theory of dynamic plasticity to
study the necking instability in a two-dimensional strip of amorphous solid.
Our Eulerian description of large-scale deformation allows us to follow the
instability far into the nonlinear regime. We find a strong rate dependence;
the higher the applied strain rate, the further the strip extends before the
onset of instability. The material hardens outside the necking region, but the
description of plastic flow within the neck is distinctly different from that
of conventional time-independent theories of plasticity.
|
We applied computer analysis to classify the broad morphological type of
~3,000,000 SDSS galaxies. The catalog provides for each galaxy the DR8 object
ID, right ascension, declination, and the certainty of the automatic
classification to spiral or elliptical. The certainty of the classification
allows controlling the accuracy of a subset of galaxies by sacrificing some of
the least certain classifications. The accuracy of the catalog was tested using
galaxies that were classified by the manually annotated Galaxy Zoo catalog. The
results show that the catalog contains ~900,000 spiral galaxies and ~600,000
elliptical galaxies with classification certainty that has a statistical
agreement rate of ~98% with Galaxy Zoo debiased 'superclean' dataset. That also
demonstrates the ability of computers to turn large datasets of galaxy images
into structured catalogs of galaxy morphology. The catalog can be downloaded at
http://vfacstaff.ltu.edu/lshamir/data/morph_catalog , and can be accessed
through public tables on CAS: public.broadMorph.LargeGM,
public.broadMorph.LargeWnnGM, and public.broadMorph.SpectraGM. The image
analysis software that was used to create the catalog is also publicly
available.
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We derive the braid relations of the charged anyons interacting with a
magnetic field on Riemann surfaces. The braid relations are used to calculate
the quasiparticle's spin in the fractional quantum Hall states on Riemann
surfaces. The quasiparticle's spin is found to be topological independent and
satisfies physical restrictions.
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Active fire detection in satellite imagery is of critical importance to the
management of environmental conservation policies, supporting decision-making
and law enforcement. This is a well established field, with many techniques
being proposed over the years, usually based on pixel or region-level
comparisons involving sensor-specific thresholds and neighborhood statistics.
In this paper, we address the problem of active fire detection using deep
learning techniques. In recent years, deep learning techniques have been
enjoying an enormous success in many fields, but their use for active fire
detection is relatively new, with open questions and demand for datasets and
architectures for evaluation. This paper addresses these issues by introducing
a new large-scale dataset for active fire detection, with over 150,000 image
patches (more than 200 GB of data) extracted from Landsat-8 images captured
around the world in August and September 2020, containing wildfires in several
locations. The dataset was split in two parts, and contains 10-band spectral
images with associated outputs, produced by three well known handcrafted
algorithms for active fire detection in the first part, and manually annotated
masks in the second part. We also present a study on how different
convolutional neural network architectures can be used to approximate these
handcrafted algorithms, and how models trained on automatically segmented
patches can be combined to achieve better performance than the original
algorithms - with the best combination having 87.2% precision and 92.4% recall
on our manually annotated dataset. The proposed dataset, source codes and
trained models are available on Github
(https://github.com/pereira-gha/activefire), creating opportunities for further
advances in the field
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The fourth generation of cell phones, marketed as 4G/LTE (Long-Term
Evolution) is being quickly adopted worldwide. Given the mobile and wireless
nature of the involved communications, security is crucial. This paper includes
both a theoretical study and a practical analysis of the SNOW 3G generator,
included in such a standard for protecting confidentiality and integrity. From
its implementation and performance evaluation in mobile devices, several
conclusions about how to improve its efficiency are obtained.
|
While statisticians and quantitative social scientists typically study the
"effects of causes" (EoC), Lawyers and the Courts are more concerned with
understanding the "causes of effects" (CoE). EoC can be addressed using
experimental design and statistical analysis, but it is less clear how to
incorporate statistical or epidemiological evidence into CoE reasoning, as
might be required for a case at Law. Some form of counterfactual reasoning,
such as the "potential outcomes" approach championed by Rubin, appears
unavoidable, but this typically yields "answers" that are sensitive to
arbitrary and untestable assumptions. We must therefore recognise that a CoE
question simply might not have a well-determined answer. It is nevertheless
possible to use statistical data to set bounds within which any answer must
lie. With less than perfect data these bounds will themselves be uncertain,
leading to a compounding of different kinds of uncertainty. Still further care
is required in the presence of possible confounding factors. In addition, even
identifying the relevant "counterfactual contrast" may be a matter of Policy as
much as of Science. Defining the question is as non-trivial a task as finding a
route towards an answer. This paper develops some technical elaborations of
these philosophical points, and illustrates them with an analysis of a case
study in child protection.
Keywords: benfluorex, causes of effects, counterfactual, child protection,
effects of causes, Fre'chet bound, potential outcome, probability of causation
|
Dataflow matrix machines are self-referential generalized recurrent neural
nets. The self-referential mechanism is provided via a stream of matrices
defining the connectivity and weights of the network in question. A natural
question is: what should play the role of untyped lambda-calculus for this
programming architecture? The proposed answer is a discipline of programming
with only one kind of streams, namely the streams of appropriately shaped
matrices. This yields Pure Dataflow Matrix Machines which are networks of
transformers of streams of matrices capable of defining a pure dataflow matrix
machine.
|
We show that any element of the universal Teichm\"uller space is realized by
a unique minimal Lagrangian diffeomorphism from the hyperbolic plane to itself.
The proof uses maximal surfaces in the 3-dimensional anti-de Sitter space. We
show that, in $AdS^{n+1}$, any subset $E$ of the boundary at infinity which is
the boundary at infinity of a space-like hypersurface bounds a maximal
space-like hypersurface. In $AdS^3$, if $E$ is the graph of a quasi-symmetric
homeomorphism, then this maximal surface is unique, and it has negative
sectional curvature. As a by-product, we find a simple characterization of
quasi-symmetric homeomorphisms of the circle in terms of 3-dimensional
projective geometry.
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A long-duration gamma-ray burst (GRB) marks the violent end of a massive
star. GRBs are rare in the universe, and their progenitor stars are thought to
possess unique physical properties such as low metal content and rapid
rotation, while the supernovae (SNe) that are associated with GRBs are expected
to be highly aspherical. To date, it has been unclear whether GRB-SNe could be
used as standardizable candles, with contrasting conclusions found by different
teams. In this paper I present evidence that GRB-SNe have the potential to be
used as standardizable candles, and show that a statistically significant
relation exists between the brightness and width of their decomposed light
curves relative to a template supernova. Every single nearby spectroscopically
identified GRB-SN, for which the rest-frame and host contributions have been
accurately determined, follows this relation. Additionally, it is shown that
not only GRB-SNe, but perhaps all supernovae whose explosion is powered by a
central engine, may eventually be used as a standardizable candle. Finally, I
suggest that the use of GRB-SNe as standardizable candles likely arises from
from a combination of the viewing angle and similar explosion geometry in each
event, the latter which is influenced by the explosion mechanism of GRB-SNe.
|
We consider a problem of recovering a high-dimensional vector $\mu$ observed
in white noise, where the unknown vector $\mu$ is assumed to be sparse. The
objective of the paper is to develop a Bayesian formalism which gives rise to a
family of $l_0$-type penalties. The penalties are associated with various
choices of the prior distributions $\pi_n(\cdot)$ on the number of nonzero
entries of $\mu$ and, hence, are easy to interpret. The resulting Bayesian
estimators lead to a general thresholding rule which accommodates many of the
known thresholding and model selection procedures as particular cases
corresponding to specific choices of $\pi_n(\cdot)$. Furthermore, they achieve
optimality in a rather general setting under very mild conditions on the prior.
We also specify the class of priors $\pi_n(\cdot)$ for which the resulting
estimator is adaptively optimal (in the minimax sense) for a wide range of
sparse sequences and consider several examples of such priors.
|
Subsets and Splits
Filtered Text Samples
Retrieves 100 samples of text containing the specific phrase "You are a helpful assistant", providing limited insight into the dataset.
Helpful Assistant Text Samples
Returns a limited set of rows containing the phrase 'helpful assistant' in the text, providing basic filtering of relevant entries.