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The correct description of the ionic interaction and stable equilibrium of
the simulations of biomolecular structure, dynamics, folding, catalysis, and
function, an accurate model of the monovalent ions is very important. The force
field needs to reproduce coincident many properties of ions, like their
structure, solvation, and moreover both the interactions of these ions with
each other in the crystal and in solution and the interactions of ions with
other molecules. Using a similar strategy employed in the parameterization of
the NaCl/epsilon , in this paper, we first propose a force field for the
Potassium Bromide, the KBr/epsilon. This new model is compared with the
experimental values of cristal density and structure for the salt and the
density, the viscosity, the dielectric constant and the solubility in the water
solution for a range of concentrations. Next, the transferability, of this new
model KBr/epsilon and the NaCl/epsilon, is verified by creating the KCl/epsilon
and the NaBr/epsilon models. The strategy is to employ the same parameters
obtained for the NaCl/epsilon and for the KBr/epsilon force fields. The two new
models derived are also compared with the experimental values for the density,
the viscosity, the dielectric constant and the solubility in the water solution
for a range of concentrations.
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Association Rule mining is one of the most important fields in data mining
and knowledge discovery. This paper proposes an algorithm that combines the
simple association rules derived from basic Apriori Algorithm with the multiple
minimum support using maximum constraints. The algorithm is implemented, and is
compared to its predecessor algorithms using a novel proposed comparison
algorithm. Results of applying the proposed algorithm show faster performance
than other algorithms without scarifying the accuracy.
|
We investigate the motion of a sedimenting spherical drop in the presence of
an applied uniform electric field in an otherwise arbitrary direction in the
limit of low surface charge convection. We analytically solve the electric
potential in and around the leaky dielectric drop, and solve for the Stokesian
velocity and pressure fields. We obtain the drop velocity through perturbations
in powers of the electric Reynolds number which signifies the importance of the
charge relaxation time scale as compared to the convective time scale. We show
that in the presence of electric field either in the sedimenting direction or
orthogonal to it, there is a change in the drop velocity only in the direction
of sedimentation due to an asymmetric charge distribution in the same
direction. However, in the presence of an electric field applied in both the
directions, and depending on the permittivities and conductivities of the two
fluids, we obtain a non-intuitive lateral migration of drop in addition to the
buoyancy driven sedimentation. These dynamical features can be effectively used
for manipulating drops in a controlled electro-fluidic environment.
|
Surface reconstruction from a set of scattered points, or a point cloud, has
many applications ranging from computer graphics to remote sensing. We present
a new method for this task that produces an implicit surface (zero-level set)
approximation for an oriented point cloud using only information about
(approximate) normals to the surface. The technique exploits the fundamental
result from vector calculus that the normals to an implicit surface are
curl-free. By using a curl-free radial basis function (RBF) interpolation of
the normals, we can extract a potential for the vector field whose zero-level
surface approximates the point cloud. We use curl-free RBFs based on
polyharmonic splines for this task, since they are free of any shape or support
parameters. Furthermore, to make this technique efficient and able to better
represent local sharp features, we combine it with a partition of unity (PU)
method. The result is the curl-free partition of unity (CFPU) method. We show
how CFPU can be adapted to enforce exact interpolation of a point cloud and can
be regularized to handle noise in both the normal vectors and the point
positions. Numerical results are presented that demonstrate how the method
converges for a known surface as the sampling density increases, how
regularization handles noisy data, and how the method performs on various
problems found in the literature.
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Machine learning has been successfully applied to identify phases and phase
transitions in condensed matter systems. However, quantitative characterization
of the critical fluctuations near phase transitions is lacking. In this study
we propose a finite-size scaling approach based on a convolutional neural
network and analyze the critical behavior of a quantum Hall plateau transition.
The localization length critical exponent learned by the neural network is
consistent with the value obtained by conventional approaches. We show that the
general-purposed method can be used to extract critical exponents in models
with drastically different physics and input data, such as the two-dimensional
Ising model and 4-state Potts model.
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Computer vision applications are increasingly popular for wildlife monitoring
tasks. While some studies focus on the monitoring of a single species, such as
a particular endangered species, others monitor larger functional groups, such
as predators. In our study, we used camera trap images collected in
north-western New South Wales, Australia, to investigate how model results were
affected by combining multiple species in single classes, and whether the
addition of negative samples can improve model performance. We found that
species that benefited the most from merging into a single class were mainly
species that look alike morphologically, i.e. macropods. Whereas species that
looked distinctively different gave mixed results when merged, e.g. merging
pigs and goats together as non-native large mammals. We also found that adding
negative samples improved model performance marginally in most instances, and
recommend conducting a more comprehensive study to explore whether the marginal
gains were random or consistent. We suggest that practitioners could classify
morphologically similar species together as a functional group or higher
taxonomic group to draw ecological inferences. Nevertheless, whether to merge
classes or not will depend on the ecological question to be explored.
|
We use the mass-to-light gradients in early-type galaxies to infer the global
dark matter fraction, f_d=M_d/M_*, for these systems. We discuss implications
about the total star formation efficiency in dark-matter halos and show that
the trend of $f_{\rm d}$ with mass produces virial mass-to-light ratios which
are consistent with semi-analitical models. Preliminary kurtosis analysis of
the quasi-constant M/L galaxies in Romanowsky et al. seems at odd with Dekel et
al. simulations.
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Vehicular networks are exposed to various threats resulting from malicious
attacks. These threats compromise the security and reliability of
communications among road users, thereby jeopardizing road and traffic safety.
One of the main vectors of these attacks within vehicular networks is
misbehaving vehicles. To address this challenge, we propose deploying a
pretrained Large Language Model (LLM)-empowered Misbehavior Detection System
(MDS) within an edge-cloud detection framework. Specifically, we fine-tune
Mistral-7B, a state-of-the-art LLM, as the edge component to enable real-time
detection, whereas a larger LLM deployed in the cloud can conduct a more
comprehensive analysis. Our experiments conducted on the extended VeReMi
dataset demonstrate Mistral-7B's superior performance, achieving 98\% accuracy
compared to other LLMs such as LLAMA2-7B and RoBERTa. Additionally, we
investigate the impact of window size on computational costs to optimize
deployment efficiency. Leveraging LLMs in MDS shows interesting results in
improving the detection of vehicle misbehavior, consequently strengthening
vehicular network security to ensure the safety of road users.
|
Linear optical networks are devices that turn classical incident modes by a
linear transformation into outgoing ones. In general, the quantum version of
such transformations may mix annihilation and creation operators. We derive a
simple formula for the effective Hamiltonian of a general linear quantum
network, if such a Hamiltonian exists. Otherwise we show how the scattering
matrix of the network is decomposed into a product of three matrices that can
be generated by Hamiltonians.
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Neural signed distance functions (SDFs) are emerging as an effective
representation for 3D shapes. State-of-the-art methods typically encode the SDF
with a large, fixed-size neural network to approximate complex shapes with
implicit surfaces. Rendering with these large networks is, however,
computationally expensive since it requires many forward passes through the
network for every pixel, making these representations impractical for real-time
graphics. We introduce an efficient neural representation that, for the first
time, enables real-time rendering of high-fidelity neural SDFs, while achieving
state-of-the-art geometry reconstruction quality. We represent implicit
surfaces using an octree-based feature volume which adaptively fits shapes with
multiple discrete levels of detail (LODs), and enables continuous LOD with SDF
interpolation. We further develop an efficient algorithm to directly render our
novel neural SDF representation in real-time by querying only the necessary
LODs with sparse octree traversal. We show that our representation is 2-3
orders of magnitude more efficient in terms of rendering speed compared to
previous works. Furthermore, it produces state-of-the-art reconstruction
quality for complex shapes under both 3D geometric and 2D image-space metrics.
|
We have investigated the magnetic and transport properties of a ternary
intermetallic compound PrRuSi3 using dc magnetization, ac susceptibility,
specific heat, electrical resistivity, neutron diffraction, inelastic neutron
scattering and muSR measurements. The magnetic susceptibility and specific heat
data reveal the signatures of spin-glass behavior in PrRuSi3 with a freezing
temperature of 9.8 K. At low magnetic fields, we observe two sharp anomalies
(at 4.9 and 8.6 K) in magnetic susceptibility data. In contrast, the specific
heat data show only a broad Schottky-type anomaly centered around 10 K.
However, muSR reveals very low frequency coherent oscillations at 1.8 K with an
onset of fast relaxation below 12 K indicating a long range magnetically
ordered ground state with very small moment. On the other hand, no magnetic
Bragg peaks are observed in low temperature neutron diffraction data at 1.8 K.
These two contradictory ground states, spin-glass versus magnetic order, can be
explained if the spin-glass behavior in PrRuSi3 is considered due to the
dynamic fluctuations of the crystal field levels as has been proposed for
spin-glass behavior in PrAu2Si2. Two sharp inelastic excitations near 2.4 meV
and 14.7 meV are observed in the inelastic neutron scattering (INS) spectra
between 4 K and 50 K. Further, exchange coupling J_ex obtained from the
analysis of INS data with CEF model provides evidence for the spontaneously
induced magnetic order with a CEF-split singlet (Gamma_t4) ground state.
However, the exchange coupling seems to be close to the critical value for the
induced moment magnetism, therefore we tend to believe that the dynamic
fluctuations between the ground state singlet and excited doublet CEF levels is
responsible for spin-glass behavior in PrRuSi3.
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To cope with the growing demand for transportation on the railway system,
accurate, robust, and high-frequency positioning is required to enable a safe
and efficient utilization of the existing railway infrastructure. As a basis
for a localization system we propose a complete on-board mapping pipeline able
to map robust meaningful landmarks, such as poles from power lines, in the
vicinity of the vehicle. Such poles are good candidates for reliable and long
term landmarks even through difficult weather conditions or seasonal changes.
To address the challenges of motion blur and illumination changes in railway
scenarios we employ a Dynamic Vision Sensor, a novel event-based camera. Using
a sideways oriented on-board camera, poles appear as vertical lines. To map
such lines in a real-time event stream, we introduce Hough2Map, a novel
consecutive iterative event-based Hough transform framework capable of
detecting, tracking, and triangulating close-by structures. We demonstrate the
mapping reliability and accuracy of Hough2Map on real-world data in typical
usage scenarios and evaluate using surveyed infrastructure ground truth maps.
Hough2Map achieves a detection reliability of up to 92% and a mapping root mean
square error accuracy of 1.1518m.
|
Orthogonal polynomials of degree $n$ with respect to the weight function
$W_\mu(x) = (1-\|x\|^2)^\mu$ on the unit ball in $\RR^d$ are known to satisfy
the partial differential equation $$
[ \Delta - \la x, \nabla \ra^2 -
(2 \mu +d) \la x, \nabla \ra \right ] P = -n(n+2 \mu+d) P $$ for $\mu > -1$.
The singular case of $\mu = -1,-2, ...$ is studied in this paper. Explicit
polynomial solutions are constructed and the equation for $\nu = -2,-3,...$ is
shown to have complete polynomial solutions if the dimension $d$ is odd. The
orthogonality of the solution is also discussed.
|
Unlike the bewildering situation in the $\gamma\gamma^*\to \pi$ form factor,
a widespread view is that perturbative QCD can decently account for the recent
\textsc{BaBar} measurement of $\gamma\gamma^*\to \eta_c$ transition form
factor. The next-to-next-to-leading order (NNLO) perturbative correction to the
$\gamma\gamma^*\to \eta_{c,b}$ form factor, is investigated in the NRQCD
factorization framework for the first time. As a byproduct, we obtain by far
the most precise order-$\alpha_s^2$ NRQCD matching coefficient for the
$\eta_{c,b}\to \gamma\gamma$ process. After including the substantial negative
order-$\alpha_s^2$ correction, the good agreement between NRQCD prediction and
the measured $\gamma\gamma^*\to \eta_c$ form factor is completely ruined over a
wide range of momentum transfer squared. This eminent discrepancy casts some
doubts on the applicability of NRQCD approach to hard exclusive reactions
involving charmonium.
|
Unsupervised domain adaptation (UDA) has achieved remarkable success in fault
diagnosis, bringing significant benefits to diverse industrial applications.
While most UDA methods focus on cross-working condition scenarios where the
source and target domains are notably similar, real-world applications often
grapple with severe domain shifts. We coin the term `distant domain adaptation
problem' to describe the challenge of adapting from a labeled source domain to
a significantly disparate unlabeled target domain. This problem exhibits the
risk of negative transfer, where extraneous knowledge from the source domain
adversely affects the target domain performance. Unfortunately, conventional
UDA methods often falter in mitigating this negative transfer, leading to
suboptimal performance. In response to this challenge, we propose a novel
Online Selective Adversarial Alignment (OSAA) approach. Central to OSAA is its
ability to dynamically identify and exclude distant source samples via an
online gradient masking approach, focusing primarily on source samples that
closely resemble the target samples. Furthermore, recognizing the inherent
complexities in bridging the source and target domains, we construct an
intermediate domain to act as a transitional domain and ease the adaptation
process. Lastly, we develop a class-conditional adversarial adaptation to
address the label distribution disparities while learning domain invariant
representation to account for potential label distribution disparities between
the domains. Through detailed experiments and ablation studies on two
real-world datasets, we validate the superior performance of the OSAA method
over state-of-the-art methods, underscoring its significant utility in
practical scenarios with severe domain shifts.
|
We develop techniques for describing the derived moduli spaces of solutions
to the equations of motion in twists of supersymmetric gauge theories as
derived algebraic stacks. We introduce a holomorphic twist of N=4
supersymmetric gauge theory and compute the derived moduli space. We then
compute the moduli spaces for the Kapustin-Witten topological twists as its
further twists. The resulting spaces for the A- and B-twist are closely related
to the de Rham stack of the moduli space of algebraic bundles and the de Rham
moduli space of flat bundles, respectively. In particular, we find the
unexpected result that the moduli spaces following a topological twist need not
be entirely topological, but can continue to capture subtle algebraic
structures of interest for the geometric Langlands program.
|
We study the effect of gradual symmetry breaking in a non-integrable system
on the level fluctuation statistics. We consider the case when the symmetry is
represented by a quantum number that takes one of two possible values, so that
the unperturbed system has a spectrum composed of two independent sequences.
When symmetry-breaking perturbation is represented by a random matrix with an
adjustable strength, the shape of the spectrum monotonously evolves towards the
Wigner distribution as the strength parameter increases. This contradicts the
observed behaviour of the acoustic resonance spectra in quartz blocks during
the breaking of a point-group symmetry that has two eigenvalues, where the
system changes in the beginning towards the Poisson statistics then turns back
to the GOE statistics. This behaviour is explained by assuming that the
symmetry breaking perturbation removes the degeneracy of a limited number of
levels, thus creating a third chaotic sequence. As symmetry breaking increases,
the new sequence grows at the expense of the initial pair until it overwhelms
the whole spectrum when the symmetry completely disappears. The calculated
spacing distribution and spectral rigidity are able to describe the evolution
of the observed acoustic resonance spectra.
|
It is argued that quantum theory is best understood as requiring an
ontological duality of res extensa and res potentia, where the latter is
understood per Heisenberg's original proposal, and the former is roughly
equivalent to Descartes' 'extended substance.' However, this is not a dualism
of mutually exclusive substances in the classical Cartesian sense, and
therefore does not inherit the infamous 'mind-body' problem. Rather, res
potentia and res extensa are proposed as mutually implicative ontological
extants that serve to explain the key conceptual challenges of quantum theory;
in particular, nonlocality, entanglement, null measurements, and wave function
collapse. It is shown that a natural account of these quantum perplexities
emerges, along with a need to reassess our usual ontological commitments
involving the nature of space and time.
|
Towards conversational agents that are capable of handling more complex
questions on contractual conditions, formalizing contract statements in a
machine readable way is crucial. However, constructing a formal model which
captures the full scope of a contract proves difficult due to the overall
complexity its set of rules represent. Instead, this paper presents a top-down
approach to the problem. After identifying the most relevant contract
statements, we model their underlying rules in a novel knowledge engineering
method. A user-friendly tool we developed for this purpose allows to do so
easily and at scale. Then, we expose the statements as service so they can get
smoothly integrated in any chatbot framework.
|
The process $e^+e^- \to K^0_L K^0_S$ has been studied with the CMD-2 detector
using about 950 events detected in the center-of-mass energy range from 1.05 to
1.38 GeV. The cross section exceeds the expectation based on the contributions
of the rho(770), omega(782) and phi(1020) mesons only.
|
Over the past years, experiments accumulated intriguing hints for new physics
(NP) in flavor observables, namely in the anomalous magnetic moment of the muon
($a_\mu$), in $R(D^{(*)})={\rm Br}(B\to D^{(*)}\tau\nu)/{\rm Br}(B\to
D^{(*)}\ell\nu)$ and in $b\to s\mu^+\mu^-$ transitions, which are all at the
$3-4\,\sigma$ level. In this article we point out that one can explain the
$R(D^{(*)})$ anomaly using two scalar leptoquarks (LQs) with the same mass and
coupling to fermions related via a discrete symmetry: an $SU(2)$ singlet and an
$SU(2)$ triplet, both with hypercharge $Y=-2/3$. In this way, potentially
dangerous contributions to $b\to s\nu\nu$ are avoided and non-CKM suppressed
effects in $R(D^{(*)})$ can be generated. This allows for smaller overall
couplings to fermions weakening the direct LHC bounds. In our model,
$R(D^{(*)})$ is directly correlated to $b\to s\tau^+\tau^-$ transitions where
an enhancement by orders of magnitude compared to the standard model (SM) is
predicted, such that these decay modes are in the reach of LHCb and BELLE II.
Furthermore, one can also naturally explain the $b\to s\mu^+\mu^-$ anomalies
(including $R(K)$) by a $C_9=-C_{10}$ like contribution without spoiling
$\mu-e$ universality in charged current decays. In this case sizable effects in
$b\to s\tau\mu$ transitions are predicted which are again well within the
experimental reach. One can even address the longstanding anomaly in $a_\mu$,
generating a sizable decay rate for $\tau\to\mu\gamma$. However, we find that
out of the three anomalies $R(D^{(*)})$, $b\to s\mu^+\mu^-$ and $a_{\mu}$ only
two (but any two) can be explained simultaneously.
|
We discuss the application of the Agapito Curtarolo and Buongiorno Nardelli
(ACBN0) pseudo-hybrid Hubbard density functional to several transition metal
oxides. ACBN0 is a fast, accurate and parameter-free alternative to traditional
DFT+$U$ and hybrid exact exchange methods. In ACBN0, the Hubbard energy of
DFT+$U$ is calculated via the direct evaluation of the local Coulomb and
exchange integrals in which the screening of the bare Coulomb potential is
accounted for by a renormalization of the density matrix. We demonstrate the
success of the ACBN0 approach for the electronic properties of a series
technologically relevant mono-oxides (MnO, CoO, NiO, FeO, both at equilibrium
and under pressure). We also present results on two mixed valence compounds,
Co$_3$O$_4$ and Mn$_3$O$_4$. Our results, obtained at the computational cost of
a standard LDA/PBE calculation, are in excellent agreement with hybrid
functionals, the GW approximation and experimental measurements.
|
A potential flow model is derived for a large flap-type oscillating wave
energy converter in the open ocean. Application of the Green's integral theorem
in the fluid domain yields a hypersingular integral equation for the jump in
potential across the flap. Solution is found via a series expansion in terms of
the Chebyshev polynomials of the second kind and even order. Several
relationships are then derived between the hydrodynamic parameters of the
system. Comparison is made between the behaviour of the converter in the open
ocean and in a channel. The degree of accuracy of wave tank experiments aiming
at reproducing the performance of the device in the open ocean is quantified.
Parametric analysis of the system is then undertaken. It is shown that
increasing the flap width has the beneficial effect of broadening the bandwidth
of the capture factor curve. This phenomenon can be exploited in random seas to
achieve high levels of efficiency.
|
We investigate the renormalizability of the classical $\phi^4$ theory at
finite temperature. We calculate the time-dependent two point function to two
loop order and show that it can be rendered finite by the counterterms of the
classical static theory. As an application the classical plasmon damping rate
is found to be $\gamma = \lambda^2 T^2/1536 \pi m$. When we use the high
temperature expression for $m$ given by dimensional reduction, the rate is
found to agree with the quantum mechanical result.
|
For the Heyting Arithmetic HA, HA* is defined as the theory $\{A\mid {\sf
HA}\vdash A^{\Box}\}$, where $A^{\Box}$ is called the box translation of $A$.
We characterize the $\Sigma_1$-provability logic of HA* as a modal theory ${\sf
iH}_\sigma^*$.
|
Working memory (WM), denoting the information temporally stored in the mind,
is a fundamental research topic in the field of human cognition.
Electroencephalograph (EEG), which can monitor the electrical activity of the
brain, has been widely used in measuring the level of WM. However, one of the
critical challenges is that individual differences may cause ineffective
results, especially when the established model meets an unfamiliar subject. In
this work, we propose a cross-subject deep adaptation model with spatial
attention (CS-DASA) to generalize the workload classifications across subjects.
First, we transform EEG time series into multi-frame EEG images incorporating
spatial, spectral, and temporal information. First, the Subject-Shared module
in CS-DASA receives multi-frame EEG image data from both source and target
subjects and learns the common feature representations. Then, in the
subject-specific module, the maximum mean discrepancy is implemented to measure
the domain distribution divergence in a reproducing kernel Hilbert space, which
can add an effective penalty loss for domain adaptation. Additionally, the
subject-to-subject spatial attention mechanism is employed to focus on the
discriminative spatial features from the target image data. Experiments
conducted on a public WM EEG dataset containing 13 subjects show that the
proposed model is capable of achieving better performance than existing
state-of-the-art methods.
|
Interactions between electrons can strongly affect the shape and
functionality of multi-electron quantum dots. The resulting charge
distributions can be localized, as in the case of Wigner molecules, with
consequences for the energy spectrum and tunneling to states outside the dot.
The situation is even more complicated for silicon dots, due to the interplay
between valley, orbital, and interaction energy scales. Here, we study
two-electron wavefunctions in electrostatically confined quantum dots formed in
a SiGe/Si/SiGe quantum well at zero magnetic field, using a combination of
tight-binding and full-configuration-interaction (FCI) methods, and taking into
account atomic-scale disorder at the quantum well interface. We model dots
based on recent qubit experiments, which straddle the boundary between strongly
interacting and weakly interacting systems, and display a rich and diverse
range of behaviors. Our calculations show that strong electron-electron
interactions, induced by weak confinement, can significantly suppress the
low-lying, singlet-triplet (ST) excitation energy. However, when the
valley-orbit interactions caused by interfacial disorder are weak, the ST
splitting can approach its noninteracting value, even when the
electron-electron interactions are strong and Wigner-molecule behavior is
observed. These results have important implications for the rational design and
fabrication of quantum dot qubits with predictable properties.
|
We show that the diameter of the directed configuration model with $n$
vertices rescaled by $\log n$ converges in probability to a constant. Our
assumptions are the convergence of the in- and out-degree of a uniform random
vertex in distribution, first and second moment. Our result extends previous
results on the diameter of the model and applies to many other random directed
graphs.
|
Large pre-trained vision language models (VLMs) have shown impressive
zero-shot ability on downstream tasks with manually designed prompt. To further
adapt VLMs to downstream tasks, soft prompt is proposed to replace manually
designed prompt, which undergoes fine-tuning based on specific domain data.
Prior prompt learning methods primarily learn a fixed prompt or residuled
prompt from training samples. However, the learned prompts lack diversity and
ignore information about unseen domains. In this paper, we reframe the prompt
learning framework from a generative perspective and propose a simple yet
efficient method for the Domain Generalization (DG) task, namely Soft Prompt
Generation (SPG). Specifically, SPG consists of a two-stage training phase and
an inference phase. During the training phase, we introduce soft prompt label
for each domain, aiming to incorporate the generative model domain knowledge.
During the inference phase, the generator of the generative model is employed
to obtain instance-specific soft prompts for the unseen target domain.
Extensive experiments on five domain generalization benchmarks of three DG
tasks demonstrate that SPG achieves state-of-the-art performance. The code is
available at https://github.com/renytek13/Soft-Prompt-Generation-with-CGAN.
|
We consider a free-standing metallic nanofilm with a predominant intersubband
paring which emerges as a result of the confinement in the growth direction. We
show that the Fermi wave vector mismatch between the subbands, detrimental to
the intersubband pairing, can be compensated by the non-zero center of mass
momentum of the Cooper pairs. This leads to the spontaneous appearance of the
intersubband Fulde-Ferrell (IFF) state, even in the absence of an external
magnetic field. Our study of the intrasubband pairing channel on the stability
of the IFF phase shows that the former strongly competes with the intersubband
pairing, which prohibits the coexistence of the two superconducting phases.
Interestingly, upon application of the magnetic field we find a transition to
an exotic mixed spin-singlet subband-triplet and spin-triplet subband-singlet
paired state. Finally, we discuss the possibility of existence of the IFF
pairing in novel superconducting materials.
|
In this article, we propose tree edit distance with variables, which is an
extension of the tree edit distance to handle trees with variables and has a
potential application to measuring the similarity between mathematical
formulas, especially, those appearing in mathematical models of biological
systems. We analyze the computational complexities of several variants of this
new model. In particular, we show that the problem is NP-complete for ordered
trees. We also show for unordered trees that the problem of deciding whether or
not the distance is 0 is graph isomorphism complete but can be solved in
polynomial time if the maximum outdegree of input trees is bounded by a
constant. This distance model is then extended for measuring the
difference/similarity between two systems of differential equations, for which
results of preliminary computational experiments using biological models are
provided.
|
The accurate reconstruction of surgical scenes from surgical videos is
critical for various applications, including intraoperative navigation and
image-guided robotic surgery automation. However, previous approaches, mainly
relying on depth estimation, have limited effectiveness in reconstructing
surgical scenes with moving surgical tools. To address this limitation and
provide accurate 3D position prediction for surgical tools in all frames, we
propose a novel approach called SAMSNeRF that combines Segment Anything Model
(SAM) and Neural Radiance Field (NeRF) techniques. Our approach generates
accurate segmentation masks of surgical tools using SAM, which guides the
refinement of the dynamic surgical scene reconstruction by NeRF. Our
experimental results on public endoscopy surgical videos demonstrate that our
approach successfully reconstructs high-fidelity dynamic surgical scenes and
accurately reflects the spatial information of surgical tools. Our proposed
approach can significantly enhance surgical navigation and automation by
providing surgeons with accurate 3D position information of surgical tools
during surgery.The source code will be released soon.
|
We prove a strong form of the quantitative Sobolev inequality in
$\mathbb{R}^n$ for $p\geq 2$, where the deficit of a function $u\in \dot
W^{1,p} $ controls $\| \nabla u -\nabla v\|_{L^p}$ for an extremal function $v$
in the Sobolev inequality.
|
In this article, the approximation properties of the Szasz-Mirakjan type
operators are studied for the function of two variables, and the rate of
convergence of the bivariate operators is determined in terms of total and
partial modulus of continuity. An associated GBS (Generalized Boolean Sum)-form
of the bivariate Szasz-Mirakjan type operators are considered for the function
of two variables to find an approximation of B-continuous and B-differentiable
function in the Bogel's space. Further, the degree of approximation of the GBS
type operators is found in terms of mixed modulus of smoothness and functions
belonging to the Lipschitz class as well as a pioneering result is obtained in
terms of Peetre K-functional. Finally, the rate of convergence of the bivariate
Szasz-Mirakjan type operators and the associated GBS type operators are
examined through graphical representation for the finite and infinite sum which
shows that the rate of convergence of the associated GBS type operators is
better than the bivariate Szasz-Mirakjan type operators.
|
In the Standard Model (SM) of particle physics, the branching ratio for Higgs
boson decays to a final state which is invisible to collider detectors, $H
\rightarrow ZZ^{\star} \rightarrow \nu \bar{\nu} \nu \bar{\nu}$, is order
0.10%. In theories beyond the SM (BSM), this branching ratio can be enhanced by
decays to undiscovered particles like dark matter (DM). At the Large Hadron
Collider (LHC), the current best upper limit on the branching ratio of
invisible Higgs boson decays is 11% at 95% confidence level. We investigate the
expected sensitivity to invisible Higgs decays with the Silicon Detector (SiD)
at the International Linear Collider (ILC). We conclude that at $\sqrt{s}=250$
GeV with 900 fb$^{-1}$ integrated luminosity each for $e_{L}^-e_{R}^+$ and
$e_{R}^-e_{L}^+$ at nominal beam polarization fractions, the expected upper
limit is 0.16% at 95% confidence level.
|
Convolutional neural networks with spatio-temporal 3D kernels (3D CNNs) have
an ability to directly extract spatio-temporal features from videos for action
recognition. Although the 3D kernels tend to overfit because of a large number
of their parameters, the 3D CNNs are greatly improved by using recent huge
video databases. However, the architecture of 3D CNNs is relatively shallow
against to the success of very deep neural networks in 2D-based CNNs, such as
residual networks (ResNets). In this paper, we propose a 3D CNNs based on
ResNets toward a better action representation. We describe the training
procedure of our 3D ResNets in details. We experimentally evaluate the 3D
ResNets on the ActivityNet and Kinetics datasets. The 3D ResNets trained on the
Kinetics did not suffer from overfitting despite the large number of parameters
of the model, and achieved better performance than relatively shallow networks,
such as C3D. Our code and pretrained models (e.g. Kinetics and ActivityNet) are
publicly available at https://github.com/kenshohara/3D-ResNets.
|
Mirror matter is a dark matter candidate. In this paper, we re-examine the
linear regime of density perturbation growth in a universe containing mirror
dark matter. Taking adiabatic scale-invariant perturbations as the input, we
confirm that the resulting processed power spectrum is richer than for the more
familiar cases of cold, warm and hot dark matter. The new features include a
maximum at a certain scale $\lambda_{max}$, collisional damping below a smaller
characteristic scale $\lambda'_S$, with oscillatory perturbations between the
two. These scales are functions of the fundamental parameters of the theory. In
particular, they decrease for decreasing $x$, the ratio of the mirror plasma
temperature to that of the ordinary. For $x \sim 0.2$, the scale
$\lambda_{max}$ becomes galactic. Mirror dark matter therefore leads to
bottom-up large scale structure formation, similar to conventional cold dark
matter, for $x \stackrel{<}{\sim} 0.2$. Indeed, the smaller the value of $x$,
the closer mirror dark matter resembles standard cold dark matter during the
linear regime. The differences pertain to scales smaller than $\lambda'_S$ in
the linear regime, and generally in the non-linear regime because mirror dark
matter is chemically complex and to some extent dissipative. Lyman-$\alpha$
forest data and the early reionisation epoch established by WMAP may hold the
key to distinguishing mirror dark matter from WIMP-style cold dark matter.
|
ART-XC (Astronomical Roentgen Telescope - X-ray Concentrator) is the hard
X-ray instrument with grazing incidence imaging optics on board the
Spektr-Roentgen-Gamma (SRG) observatory. The SRG observatory is the flagship
astrophysical mission of the Russian Federal Space Program, which was
successively launched into orbit around the second Lagrangian point (L2) of the
Earth-Sun system with a Proton rocket from the Baikonur cosmodrome on 13 July
2019. The ART-XC telescope will provide the first ever true imaging all-sky
survey performed with grazing incidence optics in the 4-30 keV energy band and
will obtain the deepest and sharpest map of the sky in the energy range of 4-12
keV. Observations performed during the early calibration and performance
verification phase as well as during the on-going all-sky survey that started
on 12 Dec. 2019 have demonstrated that the in-flight characteristics of the
ART-XC telescope are very close to expectations based on the results of ground
calibrations. Upon completion of its 4-year all-sky survey, ART-XC is expected
to detect ~5000 sources (~3000 active galactic nuclei, including heavily
obscured ones, several hundred clusters of galaxies, ~1000 cataclysmic
variables and other Galactic sources), and to provide a high-quality map of the
Galactic background emission in the 4-12 keV energy band. ART-XC is also well
suited for discovering transient X-ray sources. In this paper, we describe the
telescope, results of its ground calibrations, major aspects of the mission,
the in-flight performance of ART-XC and first scientific results.
|
The spectra of quantum dots of different geometry (``quantum ring'',
``quantum cylinder'', ``spherical square-well'' and ``parabolic confinement'')
are studied. The stochastic variational method on correlated Gaussian basis
functions and a large scale shell-model approach have been used to investigate
these ``artificial'' atoms and their properties in magnetic field. Accurate
numerical results are presented for $N$=2-8 electron systems.
|
In the present work, a hyperelastic constitutive model based on neural
networks is proposed which fulfills all common constitutive conditions by
construction, and in particular, is applicable to compressible material
behavior. Using different sets of invariants as inputs, a hyperelastic
potential is formulated as a convex neural network, thus fulfilling symmetry of
the stress tensor, objectivity, material symmetry, polyconvexity, and
thermodynamic consistency. In addition, a physically sensible stress behavior
of the model is ensured by using analytical growth terms, as well as
normalization terms which ensure the undeformed state to be stress free and
with zero energy. In particular, polyconvex, invariant-based stress
normalization terms are formulated for both isotropic and transversely
isotropic material behavior. By fulfilling all of these conditions in an exact
way, the proposed physics-augmented model combines a sound mechanical basis
with the extraordinary flexibility that neural networks offer. Thus, it
harmonizes the theory of hyperelasticity developed in the last decades with the
up-to-date techniques of machine learning. Furthermore, the non-negativity of
the hyperelastic neural network-based potentials is numerically examined by
sampling the space of admissible deformations states, which, to the best of the
authors' knowledge, is the only possibility for the considered nonlinear
compressible models. For the isotropic neural network model, the sampling space
required for that is reduced by analytical considerations. In addition, a proof
for the non-negativity of the compressible Neo-Hooke potential is presented.
The applicability of the model is demonstrated by calibrating it on data
generated with analytical potentials, which is followed by an application of
the model to finite element simulations. In addition, an adaption of the model
to noisy data is shown and its [...]
|
Monopartite projections of bipartite networks are useful tools for modeling
indirect interactions in complex systems. The standard approach to identify
significant links is statistical validation using a suitable null network
model, such as the popular configuration model (CM) that constrains node
degrees and randomizes everything else. However different CM formulations
exist, depending on how the constraints are imposed and for which sets of
nodes. Here we systematically investigate the application of these formulations
in validating the same network, showing that they lead to different results
even when the same significance threshold is used. Instead a much better
agreement is obtained for the same density of validated links. We thus propose
a meta-validation approach that allows to identify model-specific significance
thresholds for which the signal is strongest, and at the same time to obtain
results independent of the way in which the null hypothesis is formulated. We
illustrate this procedure using data on scientific production of world
countries.
|
We study the solid-on-solid interface model above a horizontal wall in three
dimensional space, with an attractive interaction when the interface is in
contact with the wall, at low temperatures. The system presents a sequence of
layering transitions, whose levels increase with the temperature, before the
complete wetting above a certain value of this quantity.
|
A recent study showed that commonly (vanilla) studied implementations of
accelerometer-based gait authentication systems ($v$ABGait) are susceptible to
random-vector attack. The same study proposed a beta noise-assisted
implementation ($\beta$ABGait) to mitigate the attack. In this paper, we assess
the effectiveness of the random-vector attack on both $v$ABGait and
$\beta$ABGait using three accelerometer-based gait datasets. In addition, we
propose $i$ABGait, an alternative implementation of ABGait, which uses a
Conditional Tabular Generative Adversarial Network. Then we evaluate
$i$ABGait's resilience against the traditional zero-effort and random-vector
attacks. The results show that $i$ABGait mitigates the impact of the
random-vector attack to a reasonable extent and outperforms $\beta$ABGait in
most experimental settings.
|
Given $n$ polynomials $p_1, \dots, p_n$ of degree at most $n$ with
$\|p_i\|_\infty \le 1$ for $i \in [n]$, we show there exist signs $x_1, \dots,
x_n \in \{-1,1\}$ so that \[\Big\|\sum_{i=1}^n x_i p_i\Big\|_\infty <
30\sqrt{n}, \] where $\|p\|_\infty := \sup_{|x| \le 1} |p(x)|$. This result
extends the Rudin-Shapiro sequence, which gives an upper bound of $O(\sqrt{n})$
for the Chebyshev polynomials $T_1, \dots, T_n$, and can be seen as a
polynomial analogue of Spencer's "six standard deviations" theorem.
|
We study a natural combinatorial pricing problem for sequentially arriving
buyers with equal budgets. Each buyer is interested in exactly one pair of
items and purchases this pair if and only if, upon arrival, both items are
still available and the sum of the item prices does not exceed the budget. The
goal of the seller is to set prices to the items such that the number of
transactions is maximized when buyers arrive in adversarial order.
Formally, we are given an undirected graph where vertices represent items and
edges represent buyers. Once prices are set to the vertices, edges with a total
price exceeding the buyers' budgets are evicted. Any arrival order of the
buyers leads to a set of transactions that forms a maximal matching in this
subgraph, and an adversarial arrival order results in a minimum maximal
matching. In order to measure the performance of a pricing strategy, we compare
the size of such a matching to the size of a maximum matching in the original
graph. It was shown by Correa et al. [IPCO 2022] that the best ratio any
pricing strategy can guarantee lies within $[1/2, 2/3]$. Our contribution to
the problem is two-fold: First, we provide several characterizations of
subgraphs that may result from pricing schemes. Second, building upon these, we
show an improved upper bound of $3/5$ and a lower bound of $1/2 + 2/n$, where
$n$ is the number of items.
|
If we want to understand planetesimal formation, the only data set we have is
our own Solar System. It is particularly interesting as it is so far the only
planetary system we know of that developed life. Understanding the conditions
under which the Solar Nebula evolved is crucial in order to understand the
different processes in the disk and the subsequent dynamical interaction
between (proto-)planets, once the gas disk is gone. Protoplanetary disks
provide a plethora of different parameters to explore. The question is whether
this parameter space can be constrained, allowing simulations to reproduce the
Solar System. Models and observations of planet formation provide constraints
on the initial planetesimal mass in certain regions of the Solar Nebula. By
making use of pebble flux-regulated planetesimal formation, we perform a
parameter study with nine different disk parameters like the initial disk mass,
initial disk size, initial dust-to-gas ratio, turbulence level, and more. We
find that the distribution of mass in planetesimals in the disk depends on the
planetesimal formation timescale and the pebbles' drift timescale. Multiple
disk parameters can influence pebble properties and thus planetesimal
formation. However, it is still possible to draw some conclusions on potential
parameter ranges. Pebble flux-regulated planetesimal formation seems to be very
robust, allowing simulations with a wide range of parameters to meet the
initial planetesimal constraints for the Solar Nebula. I.e., it does not
require a lot of fine tuning.
|
It is shown in this paper that, almost all current prevalent iterative
\mbox{methods} for solving linear system of equations can be classified as what
we called extended Krylov subspace methods. In this paper a new type of
iterative methods are introduced which do not depend on any Krylov subspaces.
This type of methods are based on the so-called accumulated projection
technique proposed by authors. It overcomes some shortcomings of classical
Row-Projection technique and takes full advantages of the linear system.
Comparing with traditional Krylov subspace methods which always depend on the
matrix-vector multiplication with some fixed matrix, the newly introduced
method (SAP) uses different projection matrices which differ in each step in
the iteration process to form an approximate solution. More importantly some
particular accelerative schemes (named as MSAP1 and MSAP2) are introduced to
improve the convergence of the SAP method. Numerical experiments show some
surprisingly improved convergence behavior; some superior experimental behavior
of MSAP methods over GMRES and block-Jacobi are demonstrated in some
situations.
|
We study the SZ-effect-induced non-Gaussianity in the cosmic microwave
background (CMB) fluctuation maps. If a CMB map is contaminated by the SZ
effect of galaxies or galaxy clusters, the CMB maps should have similar
non-Gaussian features as the galaxy and cluster fields. Using the WMAP data and
2MASS galaxy catalog we show that the non-Gaussianity of the 2MASS galaxies is
imprinted on WMAP maps. The signature of non-Gaussianity can be seen with the
4^{th} order cross correlation between the wavelet variables of the WMAP maps
and 2MASS clusters. The intensity of the 4^{th} order non-Gaussian features is
found to be consistent with the contamination of the SZ effect of 2MASS
galaxies. We also show that this non-Gaussianity can not be seen by the high
order auto-correlation of the WMAP. This is because the SZ signals in the
auto-correlations of the WMAP data generally is weaker than the WMAP-2MASS
cross correlations by a factor f^2, which is the ratio between the powers of SZ
effect map and the CMB fluctuations on the scale considered. Therefore, the
ratio of high order auto-correlations of CMB maps to cross-correlations of the
CMB maps and galaxy field would be effective to constrain the powers of SZ
effect on various scales.
|
A well-isolated system often shows relaxation to a quasi-stationary state
before reaching thermal equilibrium. Such a prethermalization has attracted
considerable interest recently in association with closely related fundamental
problems of relaxation and thermalization of isolated quantum systems.
Motivated by the recent experiment in ultracold atoms, we study the dynamics of
a one-dimensional Bose gas which is split into two subsystems, and find that
individual subsystems relax to Gibbs states, yet the entire system does not due
to quantum entanglement. In view of recent experimental realization on a small
well-defined number of ultracold atoms, our prediction based on exact few-body
calculations is amenable to experimental test.
|
A series of Ni0.6-x/2Zn0.4-x/2SnxFe2O4 (x = 0.0, 0.05, 0.1, 0.15, 0.2 and
0.3) (NZSFO) ferrite composites have been synthesized from nano powders using
standard solid state reaction technique. The spinel cubic structure of the
investigated samples has been observed by the X-ray diffraction (XRD). The
magnetic properties such as saturation magnetization (Ms), remanent
magnetization (Mr), coercive field (Hc) and Bohr magneton (B) are calculated
from the hysteresis loops. The value of Ms is found to decrease with increasing
Sn content in the samples. This change has been successfully explained by the
variation of A-B interaction strength due to Sn substitution in different
sites. The compositional stability and quality of the prepared ferrite
composites have also been endorsed by the fairly constant initial permeability
(/) over a wide range of frequency region. The decreasing trend of / with
increasing Sn content has been observed. Curie temperature (TC) has found to
increase with the increase in Sn content. Wide spread frequency utility zone
indicates that the NZSFO can be considered as a good candidate for use in
broadband pulse transformer and wide band read-write heads for video recording.
The abnormal behavior for x = 0.05 has been explained with existing theory.
|
In this work, we propose an algorithm to price American options by directly
solving the dual minimization problem introduced by Rogers. Our approach relies
on approximating the set of uniformly square integrable martingales by a finite
dimensional Wiener chaos expansion. Then, we use a sample average approximation
technique to efficiently solve the optimization problem. Unlike all the
regression based methods, our method can transparently deal with path dependent
options without extra computations and a parallel implementation writes easily
with very little communication and no centralized work. We test our approach on
several multi--dimensional options with up to 40 assets and show the impressive
scalability of the parallel implementation.
|
Granular flows through pipes show interesting phenomena, e.g. clogging and
density waves, 1/f-noise. These things are fairly good studied by
computer-experiments, but there is a lack in theoretical and analytical
consideration. We introduce a simple "minimal" model describing such a flow of
granular particles and examine the stability of an initially homogeneous system
against perturbations. In order to define the collisions between the granular
particles we use two different approaches. For both, the simple and the more
advanced collision definition, the model shows the qualitative same behaviour.
|
We demonstrate that electrons can be efficiently accelerated to high energy
in spatially non-uniform, intense laser fields. Laser non-uniformities occur
when a perfect plane wave reflects off a randomly perturbed surface. By solving
for three-dimensional particle trajectories in the electromagnetic field of a
randomly perturbed laser, we are able to generate electron energy spectra with
temperatures well above the ponderomotive scaling, as observed in many
experiments. The simulations show that high electron energies can be achieved
by the laser fields alone, without the need for plasma fields. The
characteristic temperatures of the electron spectra are determined by the
characteristic features of the laser field turbulence. The process is very
rapid, occurring on 10-50fs timescales, indicating it is likely a dominant
acceleration mechanism in short-pulse laser-solid interactions when the
intensity is at or below the relativistic threshold. A simple analytic model
shows how electrons can reach high energy by undergoing repeated acceleration
in laser wavelets for short periods of time.
|
A classic result in extremal graph theory, known as Mantel's theorem, states
that every non-bipartite graph of order $n$ with size $m>\lfloor
\frac{n^{2}}{4}\rfloor$ contains a triangle. Lin, Ning and Wu [Comb. Probab.
Comput. 30 (2021) 258-270] proved a spectral version of Mantel's theorem for
given order $n.$ Zhai and Shu [Discrete Math. 345 (2022) 112630] investigated a
spectral version for fixed size $m.$ In this paper, we prove $Q$-spectral
versions of Mantel's theorem.
|
The viscous flow of polymer chains in dense melts is dominated by topological
constraints whenever the single chain contour length, N, becomes larger than
the characteristic scale Ne, defining comprehensively the macroscopic
rheological properties of the highly entangled polymer systems. Even though the
latter are naturally connected to the presence of hard constraints like knots
and links within the polymer chains, the difficulty of integrating the rigorous
language of mathematical topology with the physics of polymer melts has limited
somehow a genuine topological approach to the problem of classifying these
constraints and to how they are related to the rheological entanglements. In
this work, we tackle this problem by studying the occurrence of knots and links
in lattice melts of randomly knotted and randomly concatenated ring polymers of
various bending stiffness. Specifically, by introducing an algorithm which
shrinks the chains to their minimal shapes which do not violate topological
constraints and by analyzing those in terms of suitable topological invariants,
we provide a detailed characterization of the topological properties at the
intra-chain level (knots) and of links between pairs and triplets of distinct
chains. Then, by employing the Z1-algorithm on the minimal conformations in
order to extract the entanglement length $N_e$, we show that the ratio $N/N_e$,
the number of entanglements per chain, can be remarkably well reconstructed in
terms of 2-chain links solely.
|
We have carried out 2D and 3D general relativistic magnetohydrodynamic
simulations of jets launched self-consistently from accretion disks orbiting
Kerr black holes and applied the results to the inner engine of the collapsar
model of gamma-ray bursts. The accretion flow launches energetic jets in the
axial funnel region of the disk/jet system, as well as a substantial coronal
wind. The jets feature knot-like structures of extremely hot,
ultra-relativistic gas; the gas in these knots begins at moderate velocities
near the inner engine, and is accelerated to ultra-relativistic velocities
(Lorentz factors of 50, and higher) by the Lorentz force in the axial funnel.
The increase in jet velocity takes place in an acceleration zone extending to
at least a few hundred gravitational radii from the inner engine. The overall
energetics of the jets are strongly spin-dependent, with high-spin black holes
producing the highest energy and mass fluxes. In addition, with high-spin black
holes, the ultra-relativistic outflow is cylindrically collimated within a few
hundred gravitational radii of the black hole, whereas in the zero- spin case
the jet retains a constant opening angle of approximately 16 degrees. The
simulations also show that the coronal wind, though considerably slower and
colder than the jets, also carries a significant amount of mass and energy.
When simulation data is scaled to the physical dimensions of a collapsar the
jets operate for a period ranging from 0.1 to 1.4 seconds, until the accretion
disk is depleted, delivering $10^{48}$ to $10^{49}$ erg.
|
The behavior of artificially grown CVD diamond films under intense
electromagnetic radiation has been studied. The properties of irradiated
diamond samples have been investigated using the method of thermally stimulated
current and by studying their charge collection properties. Diamonds have been
found to remain unaffected after doses of 6.8 MGy of 10 keV photons and 10 MGy
of MeV-range photons. This observation makes diamond an attractive detector
material for a calorimeter in the very forward region of the proposed TESLA
detector.
|
In this paper we report the occurrence of sliding bifurcations admitted by
the memristive Murali-Lakshmanan-Chua circuit \cite{icha13} and the memristive
driven Chua oscillator \citep{icha11}. Both of these circuits have a
flux-controlled active memristor designed by the authors in 2011, as their
non-linear element. The three segment piecewise-linear characteristic of this
memristor bestows on the circuits two discontinuity boundaries, dividing their
phase spaces into three sub-regions. For proper choice of parameters, these
circuits take on a degree of smoothness equal to one at each of their two
discontinuities, thereby causing them to behave as \textit{Filippov} systems.
Sliding bifurcations, which are characteristic of Filippov systems, arise when
the periodic orbits in each of the sub-regions, interact with the discontinuity
boundaries, giving rise to many interesting dynamical phenomena. The numerical
simulations are carried out after incorporating proper zero time discontinuity
mapping (ZDM) corrections. These are found to agree well with the experimental
observations which we report here appropriately.
|
A non-Hermitian topological insulator with real spectrum is interesting in
the theory of non-Hermitian extension of topological systems. We find an
experimentally realizable example of a two dimensional non-Hermitian
topological insulator with real spectrum. We consider two-dimensional
Su-Schrieffer-Heeger (SSH) model with gain and loss. We introduce non-Hermitian
polarization vector to explore topological phase and show that topological edge
states in the band gap exist in the system.
|
An algorithm for an improved description of final-state QCD radiation is
introduced. It is matched to the first-order matrix elements for gluon emission
in a host of decays, for processes within the Standard Model and the Minimal
Supersymmetric extension thereof.
|
Most non-safety applications deployed in Vehicular Ad-hoc Network (VANET) use
vehicle-to-infrastructure (V2I) and I2V communications to receive various forms
of content such as periodic traffic updates, advertisements from adjacent
road-side units (RSUs). In case of heavy traffic on highways and urban areas,
content delivery time (CDT) can be significantly affected. Increase in CDT can
be attributed to high load on the RSU or high volume of broadcasted content
which can flood the network. Therefore, this paper suggests a novel caching
strategy to improve CDT in high traffic areas and three major contributions
have been made: (1) Design and simulation of a caching strategy to decrease the
average content delivery time; (2) Evaluation and comparison of caching
performance in both urban scenario and highway scenario; (3) Evaluation and
comparison of caching performance in single RSU and multiple RSUs. The
simulation results show that caching effectively reduces the CDT by 50% in
urban scenario and 60-70% in highway scenario.
|
Horn recursion is a term used to describe when non-vanishing products of
Schubert classes in the cohomology of complex flag varieties are characterized
by inequalities parameterized by similar non-vanishing products in the
cohomology of "smaller" flag varieties. We consider the type A partial flag
variety and find that its cohomology exhibits a Horn recursion on a certain
deformation of the cup product defined by Belkale and Kumar in \cite{BK06}. We
also show that if a product of Schubert classes is non-vanishing on this
deformation, then the associated structure constant can be written in terms of
structure constants coming from induced Grassmannians.
|
We use the analytical solution of the quantum Rabi model to obtain absolutely
convergent series expressions of the exact eigenstates and their scalar
products with Fock states. This enables us to calculate the numerically exact
time evolution of <\sigma_x(t)> and <\sigma_z(t)> for all regimes of the
coupling strength, without truncation of the Hilbert space. We find a
qualitatively different behavior of both observables which can be related to
their representations in the invariant parity subspaces.
|
Modeling of the self-consistent formation and evolution of disks as a result
of prestellar core collapse reveals an intense early phase of recurrent
gravitational instability and clump formation. These clumps generally migrate
inward due to gravitational interaction with trailing spiral arms, and can be
absorbed into the central object. However, in situations of multiple clump
formation, gravitational scattering of clumps can result in the ejection of a
low mass clump. These clumps can then give rise to free-floating low mass
stars, brown dwarfs, or even giant planets. Detailed modeling of this process
in the context of present-day star formation reveals that these clumps start
out essentially as Larson first cores and grow subsequently by accretion. In
the context of Pop III star formation, preliminary indications are that the
disk clumps may also be of low mass. This mechanism of clump formation and
possible ejection provides a channel for the formation of low mass objects in
the first generation of stars.
|
Given two pairs of quantum states, a fundamental question in the resource
theory of asymmetric distinguishability is to determine whether there exists a
quantum channel converting one pair to the other. In this work, we reframe this
question in such a way that a catalyst can be used to help perform the
transformation, with the only constraint on the catalyst being that its reduced
state is returned unchanged, so that it can be used again to assist a future
transformation. What we find here, for the special case in which the states in
a given pair are commuting, and thus quasi-classical, is that this catalytic
transformation can be performed if and only if the relative entropy of one pair
of states is larger than that of the other pair. This result endows the
relative entropy with a fundamental operational meaning that goes beyond its
traditional interpretation in the setting of independent and identical
resources. Our finding thus has an immediate application and interpretation in
the resource theory of asymmetric distinguishability, and we expect it to find
application in other domains.
|
To construct a robot that can walk as efficiently and steadily as humans or
other legged animals, we develop an enhanced elitist-mutated ant colony
optimization~(EACO) algorithm with genetic and crossover operators in real-time
applications to humanoid robotics or other legged robots. This work presents
promoting global search capability and convergence rate of the EACO applied to
humanoid robots in real-time by estimating the expected convergence rate using
Markov chain. Furthermore, we put a special focus on the EACO algorithm on a
wide range of problems, from ACO, real-coded GAs, GAs with neural
networks~(NNs), particle swarm optimization~(PSO) to complex robotics systems
including gait synthesis, dynamic modeling of parameterizable trajectories and
gait optimization of humanoid robotics. The experimental results illustrate the
capability of this method to discover the premature convergence probability,
tackle successfully inherent stagnation, and promote the convergence rate of
the EACO-based humanoid robotics systems and demonstrated the applicability and
the effectiveness of our strategy for solving sophisticated optimization tasks.
We found reliable and fast walking gaits with a velocity of up to 0.47m/s using
the EACO optimization strategy. These findings have significant implications
for understanding and tackling inherent stagnation and poor convergence rate of
the EACO and provide new insight into the genetic architectures and control
optimization of humanoid robotics.
|
We propose a holographic description of $\mathcal{N}=4$ super Yang-Mills on
the four-dimensional real projective space $\mathbb{RP}^4$. We first construct
the dual background in the framework of five-dimensional $\mathcal{N}=8$ gauged
supergravity, and then uplift it to a new one-half BPS solution of type IIB
supergravity. A salient feature of our solution is the presence of a bulk naked
singularity whose local behavior resembles that of an O1$_{-}$ plane in flat
space.
|
In this paper we prove by induction on $n$ that any positive real number has
$n$th root.
|
The COMPASS experiment at the CERN SPS features good charged particle
tracking and coverage by electromagnetic calorimetry, and our data provide
excellent opportunity for simultaneous observation of new states in two
different decay modes within the same experiment. The existence of the
spin-exotic $\pi_1(1600)$ resonance in the $\rho\pi$ decay channel is studied
for the first time in COMPASS in both decay modes of the diffractively produced
$(3\pi)^{-}$ system: $\pi^{-}p \rightarrow \pi^{-}\pi^{0}\pi^{0}p$ and
$\pi^{-}p \rightarrow \pi^{-}\pi^{+}\pi^{-}p$. A preliminary partial-wave
analysis (PWA) performed on the 2008 proton target data allows for a first
conclusive comparison of both $(3\pi)^{-}$ decay modes not only for main waves
but also for small ones, including the spin-exotic $1^{-+}$ wave. We find the
neutral versus charged mode results in good agreement with expectations from
isospin symmetry. Both, the intensities and the relative phases to well-known
resonances, are consistent for the neutral and the charged decay modes of the
$(3\pi)^{-}$ system. The status on the search for the spin-exotic $\pi_1(1600)$
resonance produced on a proton target is discussed.
|
Soft, quasilocalized excitations (QLEs) are known to generically emerge in a
broad class of disordered solids, and to govern many facets of the physics of
glasses, from wave attenuation to plastic instabilities. In view of this key
role of QLEs, shedding light upon several open questions in glass physics
depends on the availability of computational tools that allow to study QLEs'
statistical mechanics. The latter is a formidable task since harmonic analyses
are typically contaminated by hybridizations of QLEs with phononic excitations
at low frequencies, obscuring a clear picture of QLEs' abundance, typical
frequencies and other important micromechanical properties. Here we present an
efficient algorithm to detect the field of quasilocalized excitations in
structural computer glasses. The algorithm introduced takes a computer-glass
sample as input, and outputs a library of QLEs embedded in that sample. We
demonstrate the power of the new algorithm by reporting the spectrum of glassy
excitations in two-dimensional computer glasses featuring a huge range of
mechanical stability, which is inaccessible using conventional harmonic
analyses due to phonon-hybridizations. Future applications are finally
discussed.
|
We describe some regular behavior in the motivic wedge, which is a subalgebra
of the cohomology Ext$_{\mathbf{A}}(\mathbb{M}_2,\mathbb{M}_2)$ of the
$\mathbb{C}$-motivic Steenrod algebra. The key tool is to compare motivic
computations to classical computations, to
Ext$_{\mathbf{A}(2)}(\mathbb{M}_2,\mathbb{M}_2)$, or to $h_1$-localization of
Ext$_{\mathbf{A}}(\mathbb{M}_2,\mathbb{M}_2)$. We also give a conjecture on the
behavior of the family $e_0^tg^k$ in
Ext$_{\mathbf{A}}(\mathbb{M}_2,\mathbb{M}_2)$ which raises naturally from the
study of the motivic wedge.
|
A novel oxygen evolution reaction (OER) catalyst (3D S235-P steel) based on
steel S235 substrate has been successfully prepared via a facile one-step
surface modification. The standard Carbon Manganese steel was phosphorizated
superficially leading to the formation of a unique 3D interconnected nanoporous
surface with high specific area which facilitates the electrocatalytically
initiated oxygen evolution reaction. The prepared 3D S235-P steel exhibits
enhanced electrocatalytic OER activities in alkaline regime confirmed by a low
overpotential ({\eta}=326 mV at j=10 mA cm-2) and a small Tafel slope of 68.7
mV dec-1. Moreover, the catalyst was found to be stable under long-term usage
conditions functioning as oxygen evolving electrode at pH 13 as evidenced by
the sufficient charge to oxygen conversion rate (Faradaic efficiency: 82.11%
and 88.34% at 10 mA cm-2 and 5 mA cm-2, respectively). In addition, it turned
out that the chosen surface modification renders steel S235 into an OER
electrocatalyst sufficiently and stable to work in neutral pH condition. Our
investigation revealed that the high catalytic activities are likely to stem
from the generated Fe/(Mn) hydroxide/oxo-hydroxides generated during the OER
process. The phosphorization treatment is therefore not only an efficient way
to optimize the electrocatalytic performance of standard Carbon-Manganese
steel, but also enables for the development of low cost and abundant steels in
the field of energy conversion.
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A recent analysis of the "Einstein" sample of early-type galaxies has
revealed that at any fixed optical luminosity Lb S0 galaxies have lower mean
X-ray luminosity Lx per unit Lb than ellipticals. Following a previous
analytical investigation of this problem (Ciotti & Pellegrini 1996), we have
performed 2D numerical simulations of the gas flows inside S0 galaxies in order
to ascertain the effectiveness of rotation and/or galaxy flattening in reducing
the Lx/Lb ratio. The flow in models without SNIa heating is considerably
ordered, and essentially all the gas lost by the stars is cooled and
accumulated in the galaxy center. If rotation is present, the cold material
settles in a disk on the galactic equatorial plane. Models with a time
decreasing SNIa heating host gas flows that can be much more complex. After an
initial wind phase, gas flows in energetically strongly bound galaxies tend to
reverse to inflows. This occurs in the polar regions, while the disk is still
in the outflow phase. In this phase of strong decoupling, cold filaments are
created at the interface between inflowing and outflowing gas. Models with more
realistic values of the dynamical quantities are preferentially found in the
wind phase with respect to their spherical counterparts of equal Lb. The
resulting Lx of this class of models is lower than in spherical models with the
same Lb and SNIa heating. At variance with cooling flow models, rotation is
shown to have only a marginal effect in this reduction, while the flattening is
one of the driving parameters for such underluminosity, in accordance with the
analytical investigation.
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Deciphering the underpinnings of the dynamical processes leading to
information transmission, processing, and storing in the brain is a crucial
challenge in neuroscience. An inspiring but speculative theoretical idea is
that such dynamics should operate at the brink of a phase transition, i.e., at
the edge between different collective phases, to entail a rich dynamical
repertoire and optimize functional capabilities. In recent years, research
guided by the advent of high-throughput data and new theoretical developments
has contributed to making a quantitative validation of such a hypothesis. Here
we review recent advances in this field, stressing our contributions. In
particular, we use data from thousands of individually recorded neurons in the
mouse brain and tools such as a phenomenological renormalization group
analysis, theory of disordered systems, and random matrix theory. These
combined approaches provide novel evidence of quasi-universal scaling and
near-critical behavior emerging in different brain regions. Moreover, we design
artificial neural networks under the reservoir-computing paradigm and show that
their internal dynamical states become near critical when we tune the networks
for optimal performance. These results not only open new perspectives for
understanding the ultimate principles guiding brain function but also towards
the development of brain-inspired, neuromorphic computation.
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In this paper we present preliminary work examining the relationship between
the formation of expectations and the realization of musical performances,
paying particular attention to expressive tempo and dynamics. To compute
features that reflect what a listener is expecting to hear, we employ a
computational model of auditory expectation called the Information Dynamics of
Music model (IDyOM). We then explore how well these expectancy features -- when
combined with score descriptors using the Basis-Function modeling approach --
can predict expressive tempo and dynamics in a dataset of Mozart piano sonata
performances. Our results suggest that using expectancy features significantly
improves the predictions for tempo.
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Software developers often submit questions to technical Q&A sites like Stack
Overflow (SO) to resolve code-level problems. In practice, they include example
code snippets with questions to explain the programming issues. Existing
research suggests that users attempt to reproduce the reported issues using
given code snippets when answering questions. Unfortunately, such code snippets
could not always reproduce the issues due to several unmet challenges that
prevent questions from receiving appropriate and prompt solutions. One previous
study investigated reproducibility challenges and produced a catalog. However,
how the practitioners perceive this challenge catalog is unknown.
Practitioners' perspectives are inevitable in validating these challenges and
estimating their severity. This study first surveyed 53 practitioners to
understand their perspectives on reproducibility challenges. We attempt to (a)
see whether they agree with these challenges, (b) determine the impact of each
challenge on answering questions, and (c) identify the need for tools to
promote reproducibility. Survey results show that - (a) about 90% of the
participants agree with the challenges, (b) "missing an important part of code"
most severely hurt reproducibility, and (c) participants strongly recommend
introducing automated tool support to promote reproducibility. Second, we
extract \emph{nine} code-based features (e.g., LOC, compilability) and build
five Machine Learning (ML) models to predict issue reproducibility. Early
detection might help users improve code snippets and their reproducibility. Our
models achieve 84.5% precision, 83.0% recall, 82.8% F1-score, and 82.8% overall
accuracy, which are highly promising. Third, we systematically interpret the ML
model and explain how code snippets with reproducible issues differ from those
with irreproducible issues.
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One of the important issues in nanomagnetism is to lower the current needed
for a technologically useful domain wall (DW) propagation speed. Based on the
modified Landau-Lifshitz-Gilbert (LLG) equation with both Slonczewski
spin-transfer torque and the field-like torque, we derive the optimal spin
current pattern for fast DW propagation along nanowires. Under such conditions,
the DW velocity in biaxial wires can be enhanced as much as ten times compared
to the velocities achieved in experiments so far. Moreover, the fast variation
of spin polarization can help DW depinning. Possible experimental realizations
are discussed.
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Dynamical friction (DF) against stars and gas is thought to be an important
mechanism for orbital evolution of massive black holes (MBHs) in merger remnant
galaxies. Recent theoretical investigations however show that DF does not
always lead to MBH inspiral. For MBHs evolving in gas-rich backgrounds, the
ionizing radiation that emerges from the innermost parts of their accretion
flow can affect the surrounding gas in such a way to cause the MBHs to
accelerate and gain orbital energy. This effect was dubbed "negative DF". We
use a semi-analytic model to study the impact of negative DF on pairs of MBHs
in merger remnant galaxies evolving under the combined influence of stellar and
gaseous DF. Our results show that for a wide range of merger galaxy and MBH
properties negative DF reduces the MBH pairing probability by $\sim 46\%$. The
suppression of MBH pairing is most severe in galaxies with one or more of these
properties: (1) a gas fraction of $f_g \geq 0.1$; (2) a galactic gas disk
rotating close to the circular velocity; (3) MBH pairs in prograde, low
eccentricity orbits, and (4) MBH pairs with mass $< 10^8\,$M$_\odot$. The last
point is of importance because MBH pairs in this mass range are direct
progenitors of merging binaries targeted by the future space-based
gravitational wave observatory LISA.
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Neutrino-induced recoil events may constitute a background to direct dark
matter searches, particularly for those detectors that strive to reach the
ton-scale and beyond. This paper discusses the expected neutrino-induced
background spectrum due to several of the most important sources, including
solar, atmospheric, and diffuse supernova neutrinos. The largest rate arises
from $^8$B produced solar neutrinos, providing upwards of $\sim 10^3$ events
per ton-year over all recoil energies for the heaviest nuclear targets. However
the majority of these $^8$B events are expected to be below the recoil
threshold of modern detectors. The remaining neutrino sources are found to
constitute a background to the WIMP-induced recoil rate only if the
WIMP-nucleon cross section is less than $10^{-12}$ pb. Finally the sensitivity
to diffuse supernova neutrino flux for non-electron neutrino flavors is
discussed, and projected flux limits are compared with existing flux limits.
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We investigate challenges and possibilities of formal reasoning for
encoder-only transformers (EOT), meaning sound and complete methods for
verifying or interpreting behaviour. In detail, we condense related formal
reasoning tasks in the form of a naturally occurring satisfiability problem
(SAT). We find that SAT is undecidable if we consider EOT, commonly considered
in the expressiveness community. Furthermore, we identify practical scenarios
where SAT is decidable and establish corresponding complexity bounds. Besides
trivial cases, we find that quantized EOT, namely those restricted by some
fixed-width arithmetic, lead to the decidability of SAT due to their limited
attention capabilities. However, the problem remains difficult, as we establish
those scenarios where SAT is NEXPTIME-hard and those where we can show that it
is solvable in NEXPTIME for quantized EOT. To complement our theoretical
results, we put our findings and their implications in the overall perspective
of formal reasoning.
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We present an object-oriented Python library for computation of properties of
highly-excited Rydberg states of alkali atoms. These include single-body
effects such as dipole matrix elements, excited-state lifetimes (radiative and
black-body limited) and Stark maps of atoms in external electric fields, as
well as two-atom interaction potentials accounting for dipole and quadrupole
coupling effects valid at both long and short range for arbitrary placement of
the atomic dipoles. The package is cross-referenced to precise measurements of
atomic energy levels and features extensive documentation to facilitate rapid
upgrade or expansion by users. This library has direct application in the field
of quantum information and quantum optics which exploit the strong Rydberg
dipolar interactions for two-qubit gates, robust atom-light interfaces and
simulating quantum many-body physics, as well as the field of metrology using
Rydberg atoms as precise microwave electrometers.
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We present \emph{c} axis infrared optical data on a number of Ba, Sr and
Nd-doped cuprates of the La$_{2}$CuO$_{4}$ (La214) series in which we observe
significant deviations from the universal Josephson relation linking the normal
state transport (DC conductivity $\sigma_{DC}$ measured at $T_{c}$) with the
superfluid density ($\rho_{s}$): $\rho_{s}\propto\sigma_{DC}(T_{c})$. We find
the violation of Josephson scaling is associated with striking enhancement of
the anisotropy in the superfluid density. The data allows us to link the
breakdown of Josephson interlayer physics with the development of magnetic
order in the CuO$_2$ planes.
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Models are increasing in size and complexity in the hunt for SOTA. But what
if those 2\% increase in performance does not make a difference in a production
use case? Maybe benefits from a smaller, faster model outweigh those slight
performance gains. Also, equally good performance across languages in
multilingual tasks is more important than SOTA results on a single one. We
present the biggest, unified, multilingual collection of sentiment analysis
datasets. We use these to assess 11 models and 80 high-quality sentiment
datasets (out of 342 raw datasets collected) in 27 languages and included
results on the internally annotated datasets. We deeply evaluate multiple
setups, including fine-tuning transformer-based models for measuring
performance. We compare results in numerous dimensions addressing the imbalance
in both languages coverage and dataset sizes. Finally, we present some best
practices for working with such a massive collection of datasets and models
from a multilingual perspective.
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The research effort prompted by the prediction that SmB$_6$ could be the
first topological Kondo insulator has produced a wealth of new results, though
not all of these seem compatible. A major discrepancy exists between scanning
tunneling microscopy / spectroscopy (STM/S) and angle-resolved photoemission
spectroscopy (ARPES), because the two experimental methods suggest a very
different number of terminations of the (100) surface with different
properties. Here we tackle this issue in a combined STM/S and ARPES study. We
find that two of the well-ordered topographies reported in earlier STM studies
can be associated with the crystal terminations identified using photoemission.
We further observe a reversal of the STM contrast with bias voltage for one of
the topographies. We ascribe this result to a different energy dependence of Sm
and B-derived states, and show that it can be used to obtain element specific
images of SmB$_6$ and identify which topography belongs to which termination.
We finally find STS results to support a modification of the low-energy
electronic structure at the surface that has been proposed as the trivial
origin of surface metallicity in this material.
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In this paper, we provide necessary and sufficient conditions for a
column-weight-three LDPC code to correct three errors when decoded using
Gallager A algorithm. We then provide a construction technique which results in
a code satisfying the above conditions. We also provide numerical assessment of
code performance via simulation results.
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We consider the problem of whether, for a given virtually torsionfree
discrete group $\Gamma$, there exists a cocompact proper topological
$\Gamma$-manifold, which is equivariantly homotopy equivalent to the
classifying space for proper actions. This problem is related to Nielsen
Realization. We will make the assumption that the expected manifold model has a
zero-dimensional singular set. Then we solve the problem in the case, for
instance, that $\Gamma$ contains a normal torsionfree subgroup $\pi$ such that
$\pi$ is hyperbolic and $\pi$ is the fundamental group of an aspherical closed
manifold of dimension greater or equal to five and $\Gamma/\pi$ is a finite
cyclic group of odd order.
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It is well known that conventional pairing fluctuation theory at the Hartree
level leads to a normal state pseudogap in the fermionic spectrum. Our goal is
to extend this Hartree approximated scheme to arrive at a generalized mean
field theory of pseudogapped superconductors for all temperatures $T$. While an
equivalent approach to the pseudogap has been derived elsewhere using a more
formal Green's function decoupling scheme, in this paper we re-interpret this
mean field theory and BCS theory as well, and demonstrate how they naturally
relate to ideal Bose gas condensation. Here we recast the Hartree approximated
Ginzburg-Landau self consistent equations in a T-matrix form. This recasting
makes it possible to consider arbitrarily strong attractive coupling, where
bosonic degrees of freedom appear at $ T^*$ considerably above $T_c$. The
implications for transport both above and below $T_c$ are discussed. Below
$T_c$ we find two types of contributions. Those associated with fermionic
excitations have the usual BCS functional form. That they depend on the
magnitude of the excitation gap, nevertheless, leads to rather atypical
transport properties in the strong coupling limit, where this gap (as distinct
from the order parameter) is virtually $T$-independent. In addition, there are
bosonic terms arising from non-condensed pairs whose transport properties are
shown here to be reasonably well described by an effective time-dependent
Ginzburg-Landau theory.
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We define and investigate versions of Silver and Mathias forcing with respect
to lower and upper density. We focus on properness, Axiom A, chain conditions,
preservation of cardinals and adding Cohen reals. We find rough forcings that
collapse 2^\omega to \omega, while others are surprisingly gentle. We also
study connections between regularity properties induced by these parametrized
forcing notions and the Baire property.
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Let $k$ be a field and let $A=\bigoplus_{n\ge 1}A_n$ be a positively graded
$k$-algebra. We recall that $A$ is graded nilpotent if for every $d\ge 1$, the
subalgebra of $A$ generated by elements of degree $d$ is nilpotent. We give a
method of producing grading nilpotent algebras and use this to prove that over
any base field $k$ there exists a finitely generated graded nilpotent algebra
that contains a free $k$-subalgebra on two generators.
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Based on a variant of the frequency function approach of Almgren([Al]), we
establish an optimal upper bound on the vanishing order of solutions to
stationary Schr\"odinger equations associated to sub-Laplacian on Carnot groups
of arbitrary step. Such bound provides a quantitative form of strong unique
continuation and can be thought of as an analogue of the recent results of
Bakri and Zhu for the standard Laplacian.
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Heteroepitaxial growth of selected group IV-VI nitrides on various
orientations of sapphire (\alpha-Al2O3) is demonstrated using atomic layer
deposition. High quality, epitaxial films are produced at significantly lower
temperatures than required by conventional deposition methods. Characterization
of electrical and superconducting properties of epitaxial films reveals a
reduced room temperature resistivity and increased residual resistance ratio
(RRR) for films deposited on sapphire compared to polycrystalline samples
deposited concurrently on fused quartz substrates.
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The socle of a group $G$ is the subgroup generated by all minimal normal
subgroups of $G$. In this short note, we determine the socle of a Hamiltonian
group explicitly.
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An explanation is given for the observed magnetic-field dependence of the
low-temperature specific heat coefficient of Yb(4)As(3). It is based on a
recently developed model for that material which can explain the observed
heavy-fermion behaviour. According to it the Yb(3+)-ions are positioned in a
net of parallel chains with an effective spin coupling of the order of J = 25
K. The magnetic-field dependence can be understood by including a weak magnetic
coupling J' between adjacent chains. The data require a ratio J'/J of about
10^{-4}. In that case the experimental results can be reproduced very well by
the theory.
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Let $\Omega\subset\mathbb{R}^{N}$, $N\geq1$, be a smooth bounded domain, and
let $m:\Omega\rightarrow\mathbb{R}$ be a possibly sign-changing function. We
investigate the existence of positive solutions for the semipositone problem
$-\Delta u=\lambda m(x)(f(u)-k)$ in $\Omega$, $u=0$ on $\partial\Omega$, where
$\lambda,k>0$ and $f$ is either sublinear at infinity with $f(0)=0$, or $f$ has
a singularity at $0$. We prove the existence of a positive solution for certain
ranges of $\lambda$ provided that the negative part of $m$ is suitably small.
Our main tool is the sub-supersolutions method, combined with some rescaling
properties.
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Entity resolution (ER) is about identifying and merging records in a database
that represent the same real-world entity. Matching dependencies (MDs) have
been introduced and investigated as declarative rules that specify ER policies.
An ER process induced by MDs over a dirty instance leads to multiple clean
instances, in general. General "answer sets programs" have been proposed to
specify the MD-based cleaning task and its results. In this work, we extend MDs
to "relational MDs", which capture more application semantics, and identify
classes of relational MDs for which the general ASP can be automatically
rewritten into a stratified Datalog program, with the single clean instance as
its standard model.
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We present preliminary results of a follow-up survey which aims to
characterise in detail those galaxies which hosted Type Ia supernovae found by
the Supernova Cosmology Project (SCP). Our survey has two components: Hubble
Space Telescope imaging with STIS and Keck spectroscopy with ESI, the goal
being to classify each host galaxy into one of three broad
morphological/spectral classes and hence to investigate the dependence of
supernovae properties on host galaxy type over a large range in redshift. Of
particular interest is the supernova Hubble diagram characterised by host
galaxy class which suggests that most of the scatter arises from those
occurring in late-type irregulars. Supernovae hosted by (presumed dust-free)
E/S0 galaxies closely follow the adopted SCP cosmological model. Although
larger datasets are required, we cannot yet find any significant difference in
the light curves of distant supernovae hosted in different galaxy types.
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I employ methods from derived algebraic geometry to give a uniform
moduli-theoretic construction of special cycle classes on integral models many
Shimura varieties of Hodge type, including unitary, quaternionic, and
orthogonal Shimura varieties. All desired properties of these cycles, even for
those corresponding to degenerate Fourier coefficients under the Kudla
correspondence, follow naturally from the construction. I formulate Kudla's
modularity conjectures in this general framework, and give some preliminary
evidence towards their validity.
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Temperature difference-induced mist adhered to the glass, such as windshield,
camera lens, is often inhomogeneous and obscure, easily obstructing the vision
and severely degrading the image. Together with adherent raindrops, they bring
considerable challenges to various vision systems but without enough attention.
Recent methods for other similar problems typically use hand-crafted priors to
generate spatial attention maps. In this work, we newly present a problem of
image degradation caused by adherent mist and raindrops. An attentive
convolutional network is adopted to visually remove the adherent mist and
raindrop from a single image. A baseline architecture with general channel-wise
attention, spatial attention, and multilevel feature fusion is used.
Considering the variations and regional characteristics of adherent mist and
raindrops, we apply interpolation-based pyramid-attention blocks to perceive
spatial information at different scales. Experiments show that the proposed
method can improve severely degraded images' visibility, both qualitatively and
quantitatively. More applied experiments show that this underrated practical
problem is critical to high-level vision scenes. Our method also achieves
state-of-the-art performance on conventional dehazing and pure de-raindrop
problems, in addition to our task of handling adherent mist and raindrops.
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We extend to Segal-Piatetski-Shapiro sequences previous results on the
Luca-Schinzel question over integral valued polynomial sequences. Namely, we
prove that for any real $c$ larger than $1$ the sequence $(\sum_{m\le n}
\varphi(\lfloor m^c \rfloor) /\lfloor m^c \rfloor)_n$ is dense modulo $1$,
where $\varphi$ denotes Euler's totient function. The main part of the proof
consists in showing that when $R$ is a large integer, the sequence of the
residues of $\lfloor m^c \rfloor$ modulo $R$ contains blocks of consecutive
values which are in an arithmetic progression.
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We prove that the mapping class group of a closed surface acts ergodically on
connected components of the representation variety corresponding to a connected
compact Lie group.
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Subsets and Splits