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The $t$-channel contribution to the difference of electromagnetic
polarizabilities of the nucleon, $(\alpha-\beta)^t$, can be quantitatively
understood in terms of a $\sigma$-meson pole in the complex $t$-plane of the
invariant scattering amplitude $A_1(s,t)$ with properties of the $\sigma$ meson
as given by the quark-level Nambu--Jona-Lasinio model (NJL). Equivalently, this
quantity may be understood in terms of a cut in the complex $t$-plane where the
properties of the $\sigma$ meson are taken from the $\pi\pi -> \sigma ->
\pi\pi$, $\gamma\gamma -> \sigma -> \pi\pi$ and $N\bar{N} -> \sigma -> \pi\pi$
reactions. This equivalence may be understood as a sum rule where the
properties of the $\sigma$ meson as predicted by the NJL model are related to
the $f_0(600)$ particle observed in the three reactions. In the following we
describe details of the derivation of $(\alpha-\beta)^t$ making use of
predictions of the quark-level NJL model for the $\sigma$-meson mass.
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Temporal grounding entails establishing a correspondence between natural
language event descriptions and their visual depictions. Compositional modeling
becomes central: we first ground atomic descriptions "girl eating an apple,"
"batter hitting the ball" to short video segments, and then establish the
temporal relationships between the segments. This compositional structure
enables models to recognize a wider variety of events not seen during training
through recognizing their atomic sub-events. Explicit temporal modeling
accounts for a wide variety of temporal relationships that can be expressed in
language: e.g., in the description "girl stands up from the table after eating
an apple" the visual ordering of the events is reversed, with first "eating an
apple" followed by "standing up from the table." We leverage these observations
to develop a unified deep architecture, CTG-Net, to perform temporal grounding
of natural language event descriptions to videos. We demonstrate that our
system outperforms prior state-of-the-art methods on the DiDeMo, Tempo-TL, and
Tempo-HL temporal grounding datasets.
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We propose Easymark, a family of embarrassingly simple yet effective
watermarks. Text watermarking is becoming increasingly important with the
advent of Large Language Models (LLM). LLMs can generate texts that cannot be
distinguished from human-written texts. This is a serious problem for the
credibility of the text. Easymark is a simple yet effective solution to this
problem. Easymark can inject a watermark without changing the meaning of the
text at all while a validator can detect if a text was generated from a system
that adopted Easymark or not with high credibility. Easymark is extremely easy
to implement so that it only requires a few lines of code. Easymark does not
require access to LLMs, so it can be implemented on the user-side when the LLM
providers do not offer watermarked LLMs. In spite of its simplicity, it
achieves higher detection accuracy and BLEU scores than the state-of-the-art
text watermarking methods. We also prove the impossibility theorem of perfect
watermarking, which is valuable in its own right. This theorem shows that no
matter how sophisticated a watermark is, a malicious user could remove it from
the text, which motivate us to use a simple watermark such as Easymark. We
carry out experiments with LLM-generated texts and confirm that Easymark can be
detected reliably without any degradation of BLEU and perplexity, and
outperform state-of-the-art watermarks in terms of both quality and
reliability.
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Modern convolutional networks such as ResNet and NASNet have achieved
state-of-the-art results in many computer vision applications. These
architectures consist of stages, which are sets of layers that operate on
representations in the same resolution. It has been demonstrated that
increasing the number of layers in each stage improves the prediction ability
of the network. However, the resulting architecture becomes computationally
expensive in terms of floating point operations, memory requirements and
inference time. Thus, significant human effort is necessary to evaluate
different trade-offs between depth and performance. To handle this problem,
recent works have proposed to automatically design high-performance
architectures, mainly by means of neural architecture search (NAS). Current NAS
strategies analyze a large set of possible candidate architectures and, hence,
require vast computational resources and take many GPUs days. Motivated by
this, we propose a NAS approach to efficiently design accurate and low-cost
convolutional architectures and demonstrate that an efficient strategy for
designing these architectures is to learn the depth stage-by-stage. For this
purpose, our approach increases depth incrementally in each stage taking into
account its importance, such that stages with low importance are kept shallow
while stages with high importance become deeper. We conduct experiments on the
CIFAR and different versions of ImageNet datasets, where we show that
architectures discovered by our approach achieve better accuracy and efficiency
than human-designed architectures. Additionally, we show that architectures
discovered on CIFAR-10 can be successfully transferred to large datasets.
Compared to previous NAS approaches, our method is substantially more
efficient, as it evaluates one order of magnitude fewer models and yields
architectures on par with the state-of-the-art.
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Elliptic partial differential equations are important both from application
and analysis points of views. In this paper we apply the Closest Point Method
to solving elliptic equations on general curved surfaces. Based on the closest
point representation of the underlying surface, we formulate an embedding
equation for the surface elliptic problem, then discretize it using standard
finite differences and interpolation schemes on banded, but uniform Cartesian
grids. We prove the convergence of the difference scheme for the Poisson's
equation on a smooth closed curve. In order to solve the resulting large sparse
linear systems, we propose a specific geometric multigrid method in the setting
of the Closest Point Method. Convergence studies both in the accuracy of the
difference scheme and the speed of the multigrid algorithm show that our
approaches are effective.
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We study if eternal inflation is realized while satisfying the recently
proposed string Swampland criteria concerning the range of scalar field
excursion, $|\Delta \phi| < \mathcal{D} \cdot M_{\rm P}$, and the potential
gradient, $|\nabla V| > c \cdot V/M_{\rm P}$, where $\mathcal{D}$ and $c$ are
constants of order unity, and $M_{\rm P}$ is the reduced Planck mass. We find
that only the eternal inflation of chaotic type is possible for $c \sim {\cal
O}(0.01)$ and $1/\mathcal{D} \sim {\cal O}(0.01)$, and that the Hubble
parameter during the eternal inflation is parametrically close to the Planck
scale, and is in the range of $2 \pi c \lesssim H_{\rm inf}/M_{\rm P} <
1/\sqrt{3}$.
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We prove a shape theorem for rotor-router aggregation on the comb, for a
specific initial rotor configuration and clockwise rotor sequence for all
vertices. Furthermore, as an application of rotor-router walks, we describe the
harmonic measure of the rotor-router aggregate and related shapes, which is
useful in the study of other growth models on the comb. We also identify the
shape for which the harmonic measure is uniform. This gives the first known
example where the rotor-router cluster has non-uniform harmonic measure, and
grows with different speeds in different directions.
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We investigate the nonlinear dynamics underlying the evolution of a 2-D
nanoscale ferromagnetic film with uniaxial anisotropy in the presence of
perpendicular pumping. Considering the associated Landau-Lifshitz spin
evolution equation with Gilbert damping together with Maxwell equation for the
demagnetization field, we study the dynamics in terms of the stereographic
variable. We identify several new fixed points for suitable choice of external
field in a rotating frame of reference. In particular, we identify explicit
equatorial and related fixed points of the spin vector in the plane transverse
to the anisotropy axis when the pumping frequency coincides with the amplitude
of the static parallel field. We then study the linear stability of these novel
fixed points under homogeneous and spin wave perturbations and obtain a
generalized Suhl's instability criterion, giving the condition for exponential
growth of P-modes under spin wave perturbations. Two parameter phase diagrams
(in terms of amplitudes of static parallel and oscillatory perpendicular
magnetic fields) for stability are obtained, which differ qualitatively from
those for the conventional ferromagnetic resonance near thermal equilibrium and
are amenable to experimental tests.
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Cloud computing, undoubtedly, has become the buzzword in the IT industry
today. Looking at the potential impact it has on numerous business applications
as well as in our everyday life, it can certainly be said that this disruptive
technology is here to stay. Many of the features that make cloud computing
attractive, have not just challenged the existing security system, but have
also revealed new security issues. This paper provides an insightful analysis
of the existing status on cloud computing security issues based on a detailed
survey carried by the author. It also makes an attempt to describe the security
challenges in Software as a Service (SaaS) model of cloud computing and also
endeavors to provide future security research directions.
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Counting integer solutions of linear constraints has found interesting
applications in various fields. It is equivalent to the problem of counting
lattice points inside a polytope. However, state-of-the-art algorithms for this
problem become too slow for even a modest number of variables. In this paper,
we propose a new framework to approximate the lattice counts inside a polytope
with a new random-walk sampling method. The counts computed by our approach has
been proved approximately bounded by a $(\epsilon, \delta)$-bound. Experiments
on extensive benchmarks show that our algorithm could solve polytopes with
dozens of dimensions, which significantly outperforms state-of-the-art
counters.
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We propose a new integrated phase I/II trial design to identify the most
efficacious dose combination that also satisfies certain safety requirements
for drug-combination trials. We first take a Bayesian copula-type model for
dose finding in phase I. After identifying a set of admissible doses, we
immediately move the entire set forward to phase II. We propose a novel
adaptive randomization scheme to favor assigning patients to more efficacious
dose-combination arms. Our adaptive randomization scheme takes into account
both the point estimate and variability of efficacy. By using a moving
reference to compare the relative efficacy among treatment arms, our method
achieves a high resolution to distinguish different arms. We also consider
groupwise adaptive randomization when efficacy is late-onset. We conduct
extensive simulation studies to examine the operating characteristics of the
proposed design, and illustrate our method using a phase I/II melanoma clinical
trial.
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We compute the total cross-section for Higgs boson production in bottom-quark
fusion using the so-called FONLL method for the matching of a scheme in which
the $b$-quark is treated as a massless parton to that in which it is treated as
a massive final-state particle, and extend our previous results to the case in
which the next-to-next-to-leading-log five-flavor scheme result is combined
with the next-to-leading-order O(as^3) four-flavor scheme computation.
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The present paper investigates state space analysis of memristor based series
and parallel RLCM circuits. The stability analysis is carried out with the help
of eigenvalues formulation method, pole-zero plot and transient response of
system. The state space analysis is successfully applied and eigenvalues of the
two circuits are calculated. It is found that the, system follows negative real
part of eigenvalues. The result clearly shows that addition of memristor in
circuits will not alter the stability of system. It is found that systems poles
located at left hand side of the S plane, which indicates stable performance of
system. It clearly evident that eigenvalues has negative real part hence two
systems are internally stable.
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When vehicle routing decisions are intertwined with higher-level decisions,
the resulting optimization problems pose significant challenges for
computation. Examples are the multi-depot vehicle routing problem (MDVRP),
where customers are assigned to depots before delivery, and the capacitated
location routing problem (CLRP), where the locations of depots should be
determined first. A simple and straightforward approach for such hierarchical
problems would be to separate the higher-level decisions from the complicated
vehicle routing decisions. For each higher-level decision candidate, we may
evaluate the underlying vehicle routing problems to assess the candidate. As
this approach requires solving vehicle routing problems multiple times, it has
been regarded as impractical in most cases. We propose a novel
deep-learning-based approach called Genetic Algorithm with Neural Cost
Predictor (GANCP) to tackle the challenge and simplify algorithm developments.
For each higher-level decision candidate, we predict the objective function
values of the underlying vehicle routing problems using a pre-trained graph
neural network without actually solving the routing problems. In particular,
our proposed neural network learns the objective values of the HGS-CVRP
open-source package that solves capacitated vehicle routing problems. Our
numerical experiments show that this simplified approach is effective and
efficient in generating high-quality solutions for both MDVRP and CLRP and has
the potential to expedite algorithm developments for complicated hierarchical
problems. We provide computational results evaluated in the standard benchmark
instances used in the literature.
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Let $p$ be a prime and $n$ be a positive integer, and consider
$f_b(X)=X+(X^p-X+b)^{-1}\in \Bbb F_p(X)$, where $b\in\Bbb F_{p^n}$ is such that
$\text{Tr}_{p^n/p}(b)\ne 0$. It is known that (i) $f_b$ permutes $\Bbb F_{p^n}$
for $p=2,3$ and all $n\ge 1$; (ii) for $p>3$ and $n=2$, $f_b$ permutes $\Bbb
F_{p^2}$ if and only if $\text{Tr}_{p^2/p}(b)=\pm 1$; and (iii) for $p>3$ and
$n\ge 5$, $f_b$ does not permute $\Bbb F_{p^n}$. It has been conjectured that
for $p>3$ and $n=3,4$, $f_b$ does not permute $\Bbb F_{p^n}$. We prove this
conjecture for sufficiently large $p$.
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The focus of this paper is on topology optimization of continuum structures
subject to thermally induced buckling. Popular strategies for solving such
problems include Solid Isotropic Material with Penalization (SIMP) and Rational
Approximation of Material Properties (RAMP). Both methods rely on material
parameterization, and can sometimes exhibit pseudo buckling modes in regions
with low pseudo-densities. Here we consider a level-set approach that relies on
the concept of topological sensitivity. Topological sensitivity analysis for
thermo-elastic buckling is carried out via direct and adjoint formulations.
Then, an augmented Lagrangian formulation is presented that exploits these
sensitivities to solve a buckling constrained problem. Numerical experiments in
3D illustrate the robustness and efficiency of the proposed method.
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Generalized permutohedra are deformations of regular permutohedra, and arise
in many different fields of mathematics. One important characterization of
generalized permutohedra is the Submodular Theorem, which is related to the
deformation cone of the Braid fan. We lay out general techniques for
determining deformation cones of a fixed polytope and apply it to the Braid fan
to obtain a natural combinatorial proof for the Submodular Theorem.
We also consider a refinement of the Braid fan, called the nested Braid fan,
and construct usual (respectively, generalized) nested permutohedra which have
the nested Braid fan as (respectively, refining) their normal fan. We extend
many results on generalized permutohedra to this new family of polytopes,
including a one-to-one correspondence between faces of nested permutohedra and
chains in ordered partition posets, and a theorem analogous to the Submodular
Theorem. Finally, we show that the nested Braid fan is the barycentric
subdivision of the Braid fan, which gives another way to construct this new
combinatorial object.
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This paper surveys some of the known results on $\delta$-ideal CR
submanifolds in complex space forms, the nearly K\"{a}hler $6$-sphere and odd
dimensional unit spheres. In addition, the relationship between $\delta$-ideal
CR submanifolds and critical points of the $\lambda$-bienergy is mentioned.
Some topics on variational problem for the $\lambda$-bienergy are also
presented.
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With a vast domain of applications and now having quantum computing hardware
available for commercial use, an education challenge arises in getting people
of various background to become quantum literate. Quantum Odyssey is a new
piece of computer software that promises to be a medium where people can learn
quantum computing without any previous requirements. It aims to achieve this
through visual cues and puzzle play, without requiring the user to possess a
background in computer coding or even linear algebra, which are traditionally a
must to work on quantum algorithms. In this paper we report our findings on an
UKRI Citizen Science grant that involves using Quantum Odyssey to teach how to
construct quantum computing algorithms. Sessions involved 30 minutes of play,
with 10 groups of 5 students, ranging between 11 to 18 years old, in two
schools in the UK. Results show the Quantum Odyssey visual methods are
efficient in portraying counterintuitive quantum computational logic in a
visual and interactive form. This enabled untrained participants to quickly
grasp difficult concepts in an intuitive way and solve problems that are
traditionally given today in Masters level courses in a mathematical form. The
results also show an increased interest in quantum physics after play, a higher
openness and curiosity to learn the mathematics behind computing on quantum
systems. Participants developed a visual, rather than mathematical intuition,
that enabled them to understand and correctly answer entry level technical
quantum information science.
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Non-orthogonal multiple access (NOMA) has been widely recognized as a
promising way to scale up the number of users, enhance the spectral efficiency,
and improve the user fairness in wireless networks, by allowing more than one
user to share one wireless resource. NOMA can be flexibly combined with many
existing wireless technologies and emerging ones including multiple-input
multiple-output (MIMO), massive MIMO, millimeter wave communications, cognitive
and cooperative communications, visible light communications, physical layer
security, energy harvesting, wireless caching, and so on. Combination of NOMA
with these technologies can further increase scalability, spectral efficiency,
energy efficiency, and greenness of future communication networks. This paper
provides a comprehensive survey of the interplay between NOMA and the above
technologies. The emphasis is on how the above techniques can benefit from NOMA
and vice versa. Moreover, challenges and future research directions are
identified.
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The growing proliferation of distributed information systems, allows
organizations to offer their business processes to a worldwide audience through
Web services. Semantic Web services have emerged as a means to achieve the
vision of automatic discovery, selection, composition, and invocation of Web
services by encoding the specifications of these software components in an
unambiguous and machine-interpretable form. Several frameworks have been
devised as enabling technologies for Semantic Web services. In this paper, we
survey the prominent Semantic Web service frameworks. In addition, a set of
criteria is identified and the discussed frameworks are evaluated and compared
with respect to these criteria. Knowing the strengths and weaknesses of the
Semantic Web service frameworks can help researchers to utilize the most
appropriate one according to their needs.
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Optical refrigeration using anti-Stokes photoluminescence is now well
established, especially for rare-earth-doped solids where cooling to cryogenic
temperatures has recently been achieved. The cooling efficiency of optical
refrigeration is constrained by the requirement that the increase in entropy of
the photon field must be greater than the decrease in entropy of the sample.
Laser radiation has been used in all demonstrated cases of optical
refrigeration with the intention of minimizing the entropy of the absorbed
photons. Here, we show that as long as the incident radiation is
unidirectional, the loss of coherence does not significantly affect the cooling
efficiency. Using a general formulation of radiation entropy as the von Neumann
entropy of the photon field, we show how the cooling efficiency depends on the
properties of the light source such as wavelength, coherence, and
directionality. Our results suggest that the laws of thermodynamics permit
optical cooling of materials with incoherent sources such as light emitting
diodes and filtered sunlight almost as efficiently as with lasers. Our findings
have significant and immediate implications for design of compact,
all-solid-state devices cooled via optical refrigeration.
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Understanding human behavior fundamentally relies on accurate 3D human pose
estimation. Graph Convolutional Networks (GCNs) have recently shown promising
advancements, delivering state-of-the-art performance with rather lightweight
architectures. In the context of graph-structured data, leveraging the
eigenvectors of the graph Laplacian matrix for positional encoding is
effective. Yet, the approach does not specify how to handle scenarios where
edges in the input graph are missing. To this end, we propose a novel
positional encoding technique, PerturbPE, that extracts consistent and regular
components from the eigenbasis. Our method involves applying multiple
perturbations and taking their average to extract the consistent and regular
component from the eigenbasis. PerturbPE leverages the Rayleigh-Schrodinger
Perturbation Theorem (RSPT) for calculating the perturbed eigenvectors.
Employing this labeling technique enhances the robustness and generalizability
of the model. Our results support our theoretical findings, e.g. our
experimental analysis observed a performance enhancement of up to $12\%$ on the
Human3.6M dataset in instances where occlusion resulted in the absence of one
edge. Furthermore, our novel approach significantly enhances performance in
scenarios where two edges are missing, setting a new benchmark for
state-of-the-art.
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Current methods to determine the energy efficiency of buildings require
on-site visits of certified energy auditors which makes the process slow,
costly, and geographically incomplete. To accelerate the identification of
promising retrofit targets on a large scale, we propose to estimate building
energy efficiency from widely available and remotely sensed data sources only,
namely street view, aerial view, footprint, and satellite-borne land surface
temperature (LST) data. After collecting data for almost 40,000 buildings in
the United Kingdom, we combine these data sources by training multiple
end-to-end deep learning models with the objective to classify buildings as
energy efficient (EU rating A-D) or inefficient (EU rating E-G). After
evaluating the trained models quantitatively as well as qualitatively, we
extend our analysis by studying the predictive power of each data source in an
ablation study. We find that the end-to-end deep learning model trained on all
four data sources achieves a macro-averaged F1 score of 64.64% and outperforms
the k-NN and SVM-based baseline models by 14.13 to 12.02 percentage points,
respectively. Thus, this work shows the potential and complementary nature of
remotely sensed data in predicting energy efficiency and opens up new
opportunities for future work to integrate additional data sources.
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We study the behavior of self avoiding polymers in a background of vertically
aligned rods that are either frozen into random positions or free to move
horizontally. We find that in both cases the polymer chains are highly
elongated, with vertical and horizontal size exponents that differ by a factor
of 3. Though these results are different than previous predictions, our results
are confirmed by detailed computer simulations.
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A new diluted ferromagnetic semiconductor (Sr,Na)(Zn,Mn)2As2 is reported, in
which charge and spin doping are decoupled via Sr/Na and Zn/Mn substitutions,
respectively, being distinguished from classic (Ga,Mn)As where charge & spin
doping are simultaneously integrated. Different from the recently reported
ferromagnetic (Ba,K)(Zn,Mn)2As2, this material crystallizes into the hexagonal
CaAl2Si2-type structure. Ferromagnetism with a Curie temperature up to 20 K has
been observed from magnetization. The muon spin relaxation measurements suggest
that the exchange interaction between Mn moments of this new system could be
different to the earlier DMS systems. This system provides an important means
for studying ferromagnetism in diluted magnetic semiconductors.
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Quantum computation based on nonadiabatic geometric phases has attracted a
broad range of interests, due to its fast manipulation and inherent noise
resistance. However, it is limited to some special evolution paths, and the
gate-times are typically longer than conventional dynamical gates, resulting in
weakening of robustness and more infidelities of the implemented geometric
gates. Here, we propose a path-optimized scheme for geometric quantum
computation on superconducting transmon qubits, where high-fidelity and robust
universal nonadiabatic geometric gates can be implemented, based on
conventional experimental setups. Specifically, we find that, by selecting
appropriate evolution paths, the constructed geometric gates can be superior to
their corresponding dynamical ones under different local errors. Numerical
simulations show that the fidelities for single-qubit geometric Phase, $\pi/8$
and Hadamard gates can be obtained as $99.93\%$, $99.95\%$ and $99.95\%$,
respectively. Remarkably, the fidelity for two-qubit control-phase gate can be
as high as $99.87\%$. Therefore, our scheme provides a new perspective for
geometric quantum computation, making it more promising in the application of
large-scale fault-tolerant quantum computation.
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Grounded Situation Recognition (GSR) is capable of recognizing and
interpreting visual scenes in a contextually intuitive way, yielding salient
activities (verbs) and the involved entities (roles) depicted in images. In
this work, we focus on the application of GSR in assisting people with visual
impairments (PVI). However, precise localization information of detected
objects is often required to navigate their surroundings confidently and make
informed decisions. For the first time, we propose an Open Scene Understanding
(OpenSU) system that aims to generate pixel-wise dense segmentation masks of
involved entities instead of bounding boxes. Specifically, we build our OpenSU
system on top of GSR by additionally adopting an efficient Segment Anything
Model (SAM). Furthermore, to enhance the feature extraction and interaction
between the encoder-decoder structure, we construct our OpenSU system using a
solid pure transformer backbone to improve the performance of GSR. In order to
accelerate the convergence, we replace all the activation functions within the
GSR decoders with GELU, thereby reducing the training duration. In quantitative
analysis, our model achieves state-of-the-art performance on the SWiG dataset.
Moreover, through field testing on dedicated assistive technology datasets and
application demonstrations, the proposed OpenSU system can be used to enhance
scene understanding and facilitate the independent mobility of people with
visual impairments. Our code will be available at
https://github.com/RuipingL/OpenSU.
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Emerging real-time multi-model ML (RTMM) workloads such as AR/VR and drone
control involve dynamic behaviors in various granularity; task, model, and
layers within a model. Such dynamic behaviors introduce new challenges to the
system software in an ML system since the overall system load is not completely
predictable, unlike traditional ML workloads. In addition, RTMM workloads
require real-time processing, involve highly heterogeneous models, and target
resource-constrained devices. Under such circumstances, developing an effective
scheduler gains more importance to better utilize underlying hardware
considering the unique characteristics of RTMM workloads. Therefore, we propose
a new scheduler, DREAM, which effectively handles various dynamicity in RTMM
workloads targeting multi-accelerator systems. DREAM quantifies the unique
requirements for RTMM workloads and utilizes the quantified scores to drive
scheduling decisions, considering the current system load and other inference
jobs on different models and input frames. DREAM utilizes tunable parameters
that provide fast and effective adaptivity to dynamic workload changes. In our
evaluation of five scenarios of RTMM workload, DREAM reduces the overall
UXCost, which is an equivalent metric of the energy-delay product (EDP) for
RTMM defined in the paper, by 32.2% and 50.0% in the geometric mean (up to
80.8% and 97.6%) compared to state-of-the-art baselines, which shows the
efficacy of our scheduling methodology.
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This paper proposes efficient multiple-access schemes for large wireless
networks based on the transmitters' buffer state information and their
transceivers' duplex transmission capability. First, we investigate the case of
half-duplex nodes where a node can either transmit or receive in a given time
instant. The network is said to be naturally sparse if the number of
nonempty-queue transmitters in a given frame is much smaller than the number of
users, which is the case when the arrival rates to the queues are very small
and the number of users is large. If the network is not naturally sparse, we
design the user requests to be sparse such that only few requests are sent to
the destination. We refer to the detected nonempty-queue transmitters in a
given frame as frame owners. Our design goal is to minimize the nodes' total
transmit power in a given frame. In the case of unslotted-time data
transmission, the optimization problem is shown to be a convex optimization
program. We propose an approximate formulation to simplify the problem and
obtain a closed-form expression for the assigned time durations to the nodes.
The solution of the approximate optimization problem demonstrates that the time
duration assigned to a node in the set of frame owners is the ratio of the
square-root of the buffer occupancy of that node to the sum of the square-roots
of each occupancy of all the frame owners. We then investigate the slotted-time
data transmission scenario, where the time durations assigned for data
transmission are slotted. In addition, we show that the full-duplex capability
of a node increases the data transmission portion of the frame and enables a
distributed implementation of the proposed schemes.
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This paper has been withdrawn by the author due to a crucial sign error in
equation 1
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This article examines the Dirichlet boundary control problem governed by the
Poisson equation, where the control variables are square integrable functions
defined on the boundary of a two dimensional bounded, convex, polygonal domain.
It employs an ultra weak formulation and utilizes Crouzeix-Raviart finite
elements to discretize the state variable, while employing piecewise constants
for the control variable discretization. The study demonstrates that the energy
norm of an enriched discrete optimal control is uniformly bounded with respect
to the discretization parameter. Furthermore, it establishes an optimal order a
priori error estimate for the control variable.
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The number of known PWNe has recently increased considerably, and the
majority of them are now middle-age objects. Recent studies have shown a clear
correlation of both X-ray luminosity and size with the PWN age, but fail in
providing a thorough explanation of the observed trends. Here I propose a
different approach to these effects, based on the hypothesis that the observed
trends do not simply reproduce the evolution of a "typical" PWN, but are a
combined effect of PWNe evolving under different ambient conditions, the
leading parameter being the ambient medium density. Using a simple analytic
approach, I show that most middle-age PWNe are more likely observable during
the reverberation phase, and I succeed in reproducing trends consistent with
those observed, provided that the evolution of the X-ray emitting electrons
keeps adiabatic over the whole reverberation phase. As a direct consequence, I
show that the X-ray spectra of older PWNe should be harder: also this is
consistent with observations.
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The last decade has seen a strong increase of research into flows in
fractured porous media, mainly related to subsurface processes, but also in
materials science and biological applications. Connected fractures totally
dominate flow-patterns, and their representation is therefore a critical part
in model design. Due to the fracture's characteristics as approximately planar
discontinuities with an extreme size to width ratio, they challenge standard
macroscale mathematical and numerical modeling of flow based on averaging.
Thus, over the last decades, various, and also fundamentally different,
approaches have been developed. This paper reviews common conceptual models and
discretization approaches for flow in fractured porous media, with an emphasis
on the dominating effects the fractures have on flow processes. In this
context, the paper discuss the tight connection between physical and
mathematical modeling and simulation approaches. Extensions and research
challenges related to transport, multi-phase flow and fluid-solid interaction
are also commented on.
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We present an extensive catalogue of BY Draconis (BY Dra)-type variables and
their stellar parameters. BY Dra are main-sequence FGKM-type stars. They
exhibit inhomogeneous starspots and bright faculae in their photospheres. These
features are caused by stellar magnetic fields, which are carried along with
the stellar disc through rotation and which produce gradual modulations in
their light curves (LCs). Our main objective is to characterise the properties
of BY Dra variables over a wide range of stellar masses, temperatures and
rotation periods. A recent study categorised 84,697 BY Dra variables from Data
Release 2 of the Zwicky Transient Facility based on their LCs. We have
collected additional photometric data from multiple surveys and performed
broad-band spectral energy distribution fits to estimate stellar parameters. We
found that more than half of our sample objects are of K spectral type,
covering an extensive range of stellar parameters in the low-mass regime
(0.1-1.3 M$_{\odot}$ ). Compared with previous studies, most of the sources in
our catalogue are rapid rotators, and so most of them must be young stars for
which a spin-down has not yet occurred. We subdivided our catalogue based on
convection zone depth and found that the photospheric activity index, $S_{\rm
ph}$, is lower for higher effective temperatures, i.e., for thinner convective
envelopes. We observe a broad range of photospheric magnetic activity for
different spectral classes owing to the presence of stellar populations of
different ages. We found a higher magnetically active fraction for K- than
M-type stars.
|
Modeling the rotation history of solar-type stars is still an unsolved
problem in modern astrophysics. One of the main challenges is to explain the
dispersion in the distribution of stellar rotation rate for young stars.
Previous works have advocated dynamo saturation or magnetic field localization
to explain the presence of fast rotators and star-disk coupling in pre-main
sequence to account for the existence of slow rotators. Here, we present a new
model that can account for the presence of both types of rotators by
incorporating fluctuations in the solar wind. This renders the spin-down
problem probabilistic in nature, some stars experiencing more braking on
average than others. We show that random fluctuations in the loss of angular
momentum enhance the population of both fast and slow rotators compared to the
deterministic case. Furthermore, the distribution of rotational speed is
severely skewed towards large values in agreement with observations.
|
Let M be a 1-motive defined over a field of characteristic 0. To M we can
associate its motivic Galois group, G_mot(M), which is the geometrical
interpretation of the Munford-Tate group of M. We prove that the unipotent
radical of the Lie algebra of G_mot(M) is the semi-abelian variety defined by
the adjoint action of the semi-simplified of the Lie algebra of G_mot(M) on
itself.
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We study the finite frequency (F.F.) noise properties of edge states in the
Laughlin state. We investigate the model of a resonant detector coupled to a
quantum point contact in the weak-backscattering limit. In particular we
discuss the impact of possible renormalization of the Luttinger exponent, due
to environmental effects, on the measured quantities and we propose a simple
way to extract such non-universal parameters from noise measurements.
|
A la Pontecorvo when one defines electroweak flavour states of neutrinos as a
linear superposition of mass eigenstates one ignores the associated spin. If,
however, there is a significant rotation between the neutrino source, and the
detector, a negative helicity state emitted by the former acquires a non-zero
probability amplitude to be perceived as a positive helicity state by the
latter. Both of these states are still in the left-Weyl sector of the Lorentz
group. The electroweak interaction cross sections for such helicity-flipped
states are suppressed by a factor of $(m_\nu/E_\nu)^2$, where $m_\nu$ is the
expectation value of the neutrino mass, and $E_\nu$ is the associated energy.
Thus, if the detecting process is based on electroweak interactions, and the
neutrino source is a highly rotating object, the rotation-induced helicity flip
becomes very significant in interpreting the data. The effect immediately
generalizes to anti-neutrinos. Motivated by these observations we present a
generalization of the Pontecorvo formalism and discuss its relevance in the
context of recent data obtained by the IceCube neutrino telescope.
|
An important question concerning in-medium high-energy parton showers in a
quark-gluon plasma or other QCD medium is whether consecutive splittings of the
partons in a given shower can be treated as quantum mechanically independent,
or whether the formation times for two consecutive splittings instead have
significant overlap. Various previous calculations of the effect of overlapping
formation times have either (i) restricted attention to a soft bremsstrahlung
limit, or else (ii) used the large-$N_c$ limit (where $N_c{=}3$ is the number
of quark colors). In this paper, we make a first study of the accuracy of the
large-$N_c$ limit used by those calculations of overlap effects that avoid a
soft bremsstrahlung approximation. Specifically, we calculate the $1/N_c^2$
correction to previous $N_c{=}\infty$ results for overlap $g \to gg \to ggg$ of
two consecutive gluon splittings $g \to gg$. At order $1/N_c^2$, there is
interesting and non-trivial color dynamics that must be accounted for during
the overlap of the formation times.
|
We prove without appeal to the Axiom of Choice that for any sets A and B, if
there is a one-to-one correspondence between 3 cross A and 3 cross B then there
is a one-to-one correspondence between A and B. The first such proof, due to
Lindenbaum, was announced by Lindenbaum and Tarski in 1926, and subsequently
`lost'; Tarski published an alternative proof in 1949. We argue that the proof
presented here follows Lindenbaum's original.
|
We consider the Landau-de Gennes variational problem on a bound\-ed, two
dimensional domain, subject to Dirichlet smooth boundary conditions. We prove
that minimizers are maximally biaxial near the singularities, that is, their
biaxiality parameter reaches the maximum value $1$. Moreover, we discuss the
convergence of minimizers in the vanishing elastic constant limit. Our
asymptotic analysis is performed in a general setting, which recovers the
Landau-de Gennes problem as a specific case.
|
Phase spaces with nontrivial geometry appear in different approaches to
quantum gravity and can also play a role in e.g. condensed matter physics.
However, so far such phase spaces have only been considered for particles or
strings. We propose an extension of the usual field theories to the framework
of fields with nonlinear phase space of field values, which generally means
nontrivial topology or geometry. In order to examine this idea we construct a
prototype scalar field with the spherical phase space and then study its
quantized version with the help of perturbative methods. As the result we
obtain a variety of predictions that are known from the quantum gravity
research, including algebra deformations, generalization of the uncertainty
relation and shifting of the vacuum energy.
|
Knowledge-based question answering (KBQA) is widely used in many scenarios
that necessitate domain knowledge. Large language models (LLMs) bring
opportunities to KBQA, while their costs are significantly higher and absence
of domain-specific knowledge during pre-training. We are motivated to combine
LLMs and prior small models on knowledge graphs (KGMs) for both inferential
accuracy and cost saving. However, it remains challenging since accuracy and
cost are not readily combined in the optimization as two distinct metrics. It
is also laborious for model selection since different models excel in diverse
knowledge. To this end, we propose Coke, a novel cost-efficient strategy for
KBQA with LLMs, modeled as a tailored multi-armed bandit problem to minimize
calls to LLMs within limited budgets. We first formulate the accuracy
expectation with a cluster-level Thompson Sampling for either KGMs or LLMs. A
context-aware policy is optimized to further distinguish the expert model
subject to the question semantics. The overall decision is bounded by the cost
regret according to historical expenditure on failures. Extensive experiments
showcase the superior performance of Coke, which moves the Pareto frontier with
up to 20.89% saving of GPT-4 fees while achieving a 2.74% higher accuracy on
the benchmark datasets.
|
We show the results in [1,2] for computing the QCD contributions to the scale
evolution of average gluon and quark jet multiplicities. The new results came
due a recent progress in timelike small-x resummation obtained in the MSbar
factorization scheme. They depend on two nonperturbative parameters with clear
and simple physical interpretations. A global fit of these two quantities to
all available experimental data sets demonstrates by its goodness how our
results solve a longstandig problem of QCD. Including all the available
theoretical input within our approach, alphas(Mz)=0.1199 +- 0.0026 has been
obtained in the MSbar scheme in an approximation equivalent to
next-to-next-to-leading order enhanced by the resummations of ln x terms
through the NNLL level and of ln Q2 terms by the renormalization group. This
result is in excellent agreement with the present world average.
|
Following the standardization and deployment of fifth generation (5G)
network, researchers have shifted their focus to beyond 5G communication.
Existing technologies have brought forth a plethora of applications that could
not have been imagined in the past years. Beyond 5G will enable us to rethink
the capability, it will offer in various sectors including agriculture, search
and rescue and more specifically in the delivery of health care services.
Unobtrusive and non-invasive measurements using radio frequency (RF) sensing,
monitoring and control of wearable medical devices are the areas that would
potentially benefit from beyond 5G. Applications such as RF sensing, device
charging and remote patient monitoring will be a key challenge using millimetre
(mmWave) communication. The mmWaves experience multi-path induced fading, where
the rate of attenuation is larger as compared to the microwaves. Eventually,
mmWave communication systems would require range extenders and guided surfaces.
A proposed solution is the use of intelligent reflective surfaces, which will
have the ability to manipulate electromagnetic (EM) signals. These intelligent
surfaces mounted and/or coated on walls aka - Intelligent Walls are planar and
active surfaces, which will be a key element in beyond 5G and 6G communication.
These intelligent walls equipped with machine learning algorithm and
computation power would have the ability to manipulate EM waves and act as
gateways in the heterogeneous network environment. The article presents the
application and vision of intelligent walls for next-generation healthcare in
the era of beyond 5G.
|
We use the semiclassical formalism based on singular solutions in complex
time to compute scattering rates for multiparticle production at high energies.
In a weakly coupled $\lambda \phi^4$ scalar field theory in four dimensions, we
consider scattering processes where the number of particles $n$ in the final
state approaches its maximal value $n \to E/m \gg 1$, where $m$ is the particle
mass. Quantum corrections to the known tree-level amplitudes in this regime are
characterised by the parameter $\lambda n$ and we show that they become large
at sufficiently high multiplicities. We compute full amplitudes in the large
$\lambda n$ limit on multiparticle mass thresholds using the thin-wall
realisation of the singular solutions in the WKB approach. We show that the
scalar theory with spontaneous symmetry breaking, used here as a simplified
model for the Higgs sector, leads to exponentially growing multi-particle rates
within our regime which is likely to realise the high-energy Higgsplosion
phenomenon. We also comment on realisation of Higgsplosion in dimensions lower
than four.
|
The present paper is a continuation of our work [11], where we introduced a
fractional operator calculus related to a fractional ${\psi}-$Fueter operator
in the one-dimensional Riemann-Liouville derivative sense in each direction of
the quaternionic structure, that depends on an additional vector of complex
parameters with fractional real parts.
This allowed us also to study a pair of lower order fractional operators and
prove the associated analogues of both Stokes and Borel-Pompieu formulas for
holomorphic functions in two complex variables.
|
We prove a variety of results on the existence of automorphic Galois
representations lifting a residual automorphic Galois representation. We prove
a result on the structure of deformation rings of local Galois representations,
and deduce from this and the method of Khare and Wintenberger a result on the
existence of modular lifts of specified type for Galois representations
corresponding to Hilbert modular forms of parallel weight 2. We discuss some
conjectures on the weights of $n$-dimensional mod $p$ Galois representations.
Finally, we use recent work of Taylor to prove level raising and lowering
results for $n$-dimensional automorphic Galois representations.
|
Our ability to use deep learning approaches to decipher neural activity would
likely benefit from greater scale, in terms of both model size and datasets.
However, the integration of many neural recordings into one unified model is
challenging, as each recording contains the activity of different neurons from
different individual animals. In this paper, we introduce a training framework
and architecture designed to model the population dynamics of neural activity
across diverse, large-scale neural recordings. Our method first tokenizes
individual spikes within the dataset to build an efficient representation of
neural events that captures the fine temporal structure of neural activity. We
then employ cross-attention and a PerceiverIO backbone to further construct a
latent tokenization of neural population activities. Utilizing this
architecture and training framework, we construct a large-scale multi-session
model trained on large datasets from seven nonhuman primates, spanning over 158
different sessions of recording from over 27,373 neural units and over 100
hours of recordings. In a number of different tasks, we demonstrate that our
pretrained model can be rapidly adapted to new, unseen sessions with
unspecified neuron correspondence, enabling few-shot performance with minimal
labels. This work presents a powerful new approach for building deep learning
tools to analyze neural data and stakes out a clear path to training at scale.
|
The classical Steinitz theorem states that if the origin belongs to the
interior of the convex hull of a set $S \subset \mathbb{R}^d$, then there are
at most $2d$ points of $S$ whose convex hull contains the origin in the
interior. B\'ar\'any, Katchalski, and Pach proved the following quantitative
version of Steinitz's theorem. Let $Q$ be a convex polytope in $\mathbb{R}^d$
containing the standard Euclidean unit ball $\mathbf{B}^d$. Then there exist at
most $2d$ vertices of $Q$ whose convex hull $Q^\prime$ satisfies \[ r
\mathbf{B}^d \subset Q^\prime \] with $r\geq d^{-2d}$. They conjectured that
$r\geq c d^{-1/2}$ holds with a universal constant $c>0$. We prove $r \geq
\frac{1}{5d^2}$, the first polynomial lower bound on $r$. Furthermore, we show
that $r$ is not be greater than $\frac{2}{\sqrt{d}}$.
|
Preliminary results concerning non-quadratic (and non-bijective)
transformations that exibit a degree of parentage with the well known
Levi-Civita, Kustaanheimo-Stiefel, and Fock transformations are reported in
this article. Some of the new transformations are applied to non-relativistic
quantum dynamical systems in two dimensions.
|
We introduce several methods of decomposition for two player normal form
games. Viewing the set of all games as a vector space, we exhibit explicit
orthonormal bases for the subspaces of potential games, zero-sum games, and
their orthogonal complements which we call anti-potential games and
anti-zero-sum games, respectively. Perhaps surprisingly, every anti-potential
game comes either from the Rock-Paper-Scissors type games (in the case of
symmetric games) or from the Matching Pennies type games (in the case of
asymmetric games). Using these decompositions, we prove old (and some new)
cycle criteria for potential and zero-sum games (as orthogonality relations
between subspaces). We illustrate the usefulness of our decomposition by (a)
analyzing the generalized Rock-Paper-Scissors game, (b) completely
characterizing the set of all null-stable games, (c) providing a large class of
strict stable games, (d) relating the game decomposition to the decomposition
of vector fields for the replicator equations, (e) constructing Lyapunov
functions for some replicator dynamics, and (f) constructing Zeeman games
-games with an interior asymptotically stable Nash equilibrium and a pure
strategy ESS.
|
The increasing precision of spacecraft radiometric tracking data experienced
in the last number of years, coupled with the huge amount of data collected and
the long baselines of the available datasets, has made the direct observation
of Solar System dynamics possible, and in particular relativistic effects,
through the measurement of some key parameters as the post-Newtonian
parameters, the Nordtvedt parameter "eta" and the graviton mass. In this work
we investigate the potentialities of the datasets provided by the most
promising past, present and future interplanetary missions to draw a realistic
picture of the knowledge that can be reached in the next 10-15 years. To this
aim, we update the semi-analytical model originally developed for the
BepiColombo mission, to take into account planet-planet relativistic
interactions and eccentricity-induced effects and validate it against
well-established numerical models to assess the precision of the retrieval of
the parameters of interest. Before the analysis of the results we give a review
of some of the hypotheses and constrained analysis schemes that have been
proposed until now to overcome geometrical weaknessess and model degeneracies,
proving that these strategies introduce model inconsistencies. Finally we apply
our semi-analytical model to perform a covariance analysis on three samples of
interplanetary missions: 1) those for which data are available now (e.g.
Cassini, MESSENGER, MRO, Juno), 2) in the next years (BepiColombo) and 3) still
to be launched as JUICE and VERITAS (this latter is waiting for the approval).
|
This paper considers the use of routerless networks-on-chip as an alternative
on-chip interconnect for multiprocessor systems requiring hard real-time
guarantees for inter-processor communication. It presents a novel analytical
framework that can provide latency upper bounds to real-time packet flows sent
over routerless networks-on-chip, and it uses that framework to evaluate the
ability of such networks to provide real-time guarantees. Extensive comparative
analysis is provided, considering different architectures for routerless
networks and a state-of-the-art wormhole network based on priority-preemptive
routers as a baseline.
|
We introduce a new family of orthogonal polynomials on the disk that has
emerged in the context of wave propagation in layered media. Unlike known
examples, the polynomials are orthogonal with respect to a measure all of whose
even moments are infinite.
|
Living cells exhibit an important out-of-equilibrium mechanical activity,
mainly due to the forces generated by molecular motors. These motor proteins,
acting individually or collectively on the cytoskeleton, contribute to the
violation of the fluctuation-dissipation theorem in living systems. In this
work we probe the cytoskeletal out-of-equilibrium dynamics by performing
simultaneous active and passive microrheology experiments, using the same
micron-sized probe specifically bound to the actin cortex. The free motion of
the probe exhibits a constrained, subdiffusive behavior at short time scales (t
< 2s), and a directed, superdiffusive behavior at larger time scales, while, in
response to a step force, its creep function presents the usual weak power law
dependence with time. Combining the results of both experiments, we precisely
measure for the first time the power spectrum of the force fluctuations exerted
on this probe, which lies more than one order of magnitude above the spectrum
expected at equilibrium, and greatly depends on frequency. We retrieve an
effective temperature Teff of the system, as an estimate of the departure from
thermal equilibrium. This departure is especially pronounced on long time
scales, where Teff bears the footprint of the cooperative activity of motors
pulling on the actin network. ATP depletion reduces the fluctuating force
amplitude and results in a sharp decrease of Teff towards equilibrium.
|
Simulations predict that hot super-Earth sized exoplanets can have their
envelopes stripped by photo-evaporation, which would present itself as a lack
of these exoplanets. However, this absence in the exoplanet population has
escaped a firm detection. Here we demonstrate, using asteroseismology on a
sample of exoplanets and exoplanet candidates observed during the Kepler
mission that, while there is an abundance of super-Earth sized exoplanets with
low incident fluxes, none are found with high incident fluxes. We do not find
any exoplanets with radii between 2.2 and 3.8 Earth radii with incident flux
above 650 times the incident flux on Earth. This gap in the population of
exoplanets is explained by evaporation of volatile elements and thus supports
the predictions. The confirmation of a hot-super-Earth desert caused by
evaporation will add an important constraint on simulations of planetary
systems, since they must be able to reproduce the dearth of close-in
super-Earths.
|
In this paper we study the minimum dilatation pseudo-Anosov mapping classes
coming from fibrations over the circle of a single 3-manifold, the mapping
torus for the "simplest pseudo-Anosov braid". The dilatations that arise
include the minimum dilatations for orientable mapping classes for genus
g=2,3,4,5,8 as well as Lanneau and Thiffeault's conjectural minima for
orientable mapping classes, when g = 2,4 (mod 6). Our examples also show that
the minimum dilatation for orientable mapping classes is strictly greater than
the minimum dilatation for non-orientable ones when g = 4,6,8.
|
We propose a novel method for discovering shape regions that strongly
correlate with user-prescribed tags. For example, given a collection of chairs
tagged as either "has armrest" or "lacks armrest", our system correctly
highlights the armrest regions as the main distinctive parts between the two
chair types. To obtain point-wise predictions from shape-wise tags we develop a
novel neural network architecture that is trained with tag classification loss,
but is designed to rely on segmentation to predict the tag. Our network is
inspired by U-Net, but we replicate shallow U structures several times with new
skip connections and pooling layers, and call the resulting architecture
"WU-Net". We test our method on segmentation benchmarks and show that even with
weak supervision of whole shape tags, our method can infer meaningful semantic
regions, without ever observing shape segmentations. Further, once trained, the
model can process shapes for which the tag is entirely unknown. As a bonus, our
architecture is directly operational under full supervision and performs
strongly on standard benchmarks. We validate our method through experiments
with many variant architectures and prior baselines, and demonstrate several
applications.
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We present NEAMER -- Named Entity Augmented Multi-word Expression Recognizer.
This system is inspired by non-compositionality characteristics shared between
Named Entity and Idiomatic Expressions. We utilize transfer learning and
locality features to enhance idiom classification task. This system is our
submission for SemEval Task 2: Multilingual Idiomaticity Detection and Sentence
Embedding Subtask A OneShot shared task. We achieve SOTA with F1 0.9395 during
post-evaluation phase. We also observe improvement in training stability.
Lastly, we experiment with non-compositionality knowledge transfer,
cross-lingual fine-tuning and locality features, which we also introduce in
this paper.
|
Early analyses revealed that dark web marketplaces (DWMs) started offering
COVID-19 related products (e.g., masks and COVID-19 tests) as soon as the
COVID-19 pandemic started, when these goods were in shortage in the traditional
economy. Here, we broaden the scope and depth of previous investigations by
analysing 194 DWMs until July 2021, including the crucial period in which
vaccines became available, and by considering the wider impact of the pandemic
on DWMs. First, we focus on vaccines. We find 250 listings offering approved
vaccines, like Pfizer/BioNTech and AstraZeneca, as well as vendors offering
fabricated proofs of vaccination and COVID-19 passports. Second, we consider
COVID-19 related products. We reveal that, as the regular economy has become
able to satisfy the demand of these goods, DWMs have decreased their offer.
Third, we analyse the profile of vendors of COVID-19 related products and
vaccines. We find that most of them are specialized in a single type of
listings and are willing to ship worldwide. Finally, we consider a broader set
of listings mentioning COVID-19 as proxy for the general impact of the pandemic
on these DWMs . Among 10,330 such listings, we show that recreational drugs are
the most affected among traditional DWMs product, with COVID-19 mentions
steadily increasing since March 2020. We anticipate that our effort is of
interest to researchers, practitioners, and law enforcement agencies focused on
the study and safeguard of public health.
|
The extension of Boltzmann-Gibbs thermostatistics, proposed by Tsallis,
introduces an additional parameter $q$ to the inverse temperature $\beta$.
Here, we show that a previously introduced generalized Metropolis dynamics to
evolve spin models is not local and does not obey the detailed energy balance.
In this dynamics, locality is only retrieved for $q=1$, which corresponds to
the standard Metropolis algorithm. Non-locality implies in very time consuming
computer calculations, since the energy of the whole system must be
reevaluated, when a single spin is flipped. To circumvent this costly
calculation, we propose a generalized master equation, which gives rise to a
local generalized Metropolis dynamics that obeys the detailed energy balance.
To compare the different critical values obtained with other generalized
dynamics, we perform Monte Carlo simulations in equilibrium for Ising model. By
using the short time non-equilibrium numerical simulations, we also calculate
for this model: the critical temperature, the static and dynamical critical
exponents as function of $q$. Even for $q\neq 1$, we show that suitable time
evolving power laws can be found for each initial condition. Our numerical
experiments corroborate the literature results, when we use non-local dynamics,
showing that short time parameter determination works also in this case.
However, the dynamics governed by the new master equation leads to different
results for critical temperatures and also the critical exponents affecting
universality classes. We further propose a simple algorithm to optimize
modeling the time evolution with a power law considering in a log-log plot two
successive refinements.
|
The previous link adaptation algorithms on ofdm based systems use equal
modulation order for all sub carrier index within a block. For multimedia
transmission using ofdm as the modulation technique, unequal constellation is
used within one ofdm subcarrier block, a set of subcarriers for audio and
another set for video transmissions. A generic model has been shown for such a
transmission and link adaptation algorithm has been proposed using EESM
(Effective Exponential SNR mapping) method as basic method. Mathematical model
has been derived for the channel based on bivariate Gaussian distribution in
which the amplitude varies two dimensionally in the same envelope. From the
Moment generating function of bivariate distribution, Probability of error has
been theoretically derived. Results have been shown for BER performance of an
ofdm system using unequal constellation. BER performances have been shown for
different values of correlation parameter and fading figure.
|
Si nanopillars of less than 50 nm diameter have been irradiated in a helium
ion microscope with a focused Ne$^+$ beam. The morphological changes due to ion
beam irradiation at room temperature and elevated temperatures have been
studied with the transmission electron microscope. We found that the shape
changes of the nanopillars depend on irradiation-induced amorphization and
thermally driven dynamic annealing. While at room temperature, the nanopillars
evolve to a conical shape due to ion-induced plastic deformation and viscous
flow of amorphized Si, simultaneous dynamic annealing during the irradiation at
elevated temperatures prevents amorphization which is necessary for the viscous
flow. Above the critical temperature of ion-induced amorphization, a steady
decrease of the diameter was observed as a result of the dominating forward
sputtering process through the nanopillar sidewalls. Under these conditions the
nanopillars can be thinned down to a diameter of 10 nm in a well-controlled
manner. A deeper understanding of the pillar thinning process has been achieved
by a comparison of experimental results with 3D computer simulations based on
the binary collision approximation.
|
we study on compact Riemannian manifolds with boundary, the problems of
existence and multiplicity of solutions to a Neumann problem involving the
p-Laplacian operator and critical Sobolev exponents.
|
Let $\F\subset 2^{[n]}$ be a family of subsets of $\{1,2,..., n\}$. For any
poset $H$, we say $\F$ is $H$-free if $\F$ does not contain any subposet
isomorphic to $H$. Katona and others have investigated the behavior of
$\La(n,H)$, which denotes the maximum size of $H$-free families $\F\subset
2^{[n]}$. Here we use a new approach, which is to apply methods from extremal
graph theory and probability theory to identify new classes of posets $H$, for
which $\La(n,H)$ can be determined asymptotically as $n\to\infty$ for various
posets $H$, including two-end-forks, up-down trees, and cycles $C_{4k}$ on two
levels.
|
We report the appearance of superconductivity under hydrostatic pressure
(0.35 to 2.5GPa) in Sr0.5RE0.5FBiS2 with RE = Ce, Nd, Pr and Sm. The studied
compounds, synthesized by solid state reaction route, are crystallized in
tetragonal P4/nmm space group. At ambient pressure though the RE = Ce exhibit
the onset of superconductivity below 2.5K, the Nd, Pr and Sm samples are not
superconducting down to 2K. With application of hydrostatic pressure (up to
2.5GPa), superconducting transition temperature is increased to around 10K for
all the studied samples. The magneto-transport measurements are carried out on
all the samples with maximum Tc i.e., at under 2.5GPa pressure and their upper
critical fields are determined. The new superconducting compounds appear to be
quite robust against magnetic field but within Pauli paramagnetic limit. The
new superconducting compounds with various RE (Ce, Nd, Pr and Sm) belonging to
Sr0.5La0.5FBiS2 family are successfully synthesized for the first time and
superconductivity is induced in them under hydrostatic pressure.
|
A structure $\mathcal{A}=\left(A;E_i\right)_{i\in n}$ where each $E_i$ is an
equivalence relation on $A$ is called an $n$-grid if any two equivalence
classes coming from distinct $E_i$'s intersect in a finite set. A function
$\chi: A \to n$ is an acceptable coloring if for all $i \in n$, the set
$\chi^{-1}(i)$ intersects each $E_i$-equivalence class in a finite set. If $B$
is a set, then the $n$-cube $B^n$ may be seen as an $n$-grid, where the
equivalence classes of $E_i$ are the lines parallel to the $i$-th coordinate
axis. We use elementary submodels of the universe to characterize those
$n$-grids which admit an acceptable coloring. As an application we show that if
an $n$-grid $\mathcal{A}$ does not admit an acceptable coloring, then every
finite $n$-cube is embeddable in $\mathcal{A}$.
|
We show a relation between a quantum channel $\Phi$ and its conjugate
$\Phi^C$, which implies that the $p\to p$ Schatten norm of the channel is the
same as the $1\to p$ completely bounded norm of the conjugate. This relation is
used to give an alternative proof of the multiplicativity of both norms.
|
The ubiquity of smartphones has led to an increase in on demand healthcare
being supplied. For example, people can share their illness-related experiences
with others similar to themselves, and healthcare experts can offer advice for
better treatment and care for remediable, terminal and mental illnesses. As
well as this human-to-human communication, there has been an increased use of
human-to-computer digital health messaging, such as chatbots. These can prove
advantageous as they offer synchronous and anonymous feedback without the need
for a human conversational partner. However, there are many subtleties involved
in human conversation that a computer agent may not properly exhibit. For
example, there are various conversational styles, etiquettes, politeness
strategies or empathic responses that need to be chosen appropriately for the
conversation. Encouragingly, computers are social actors (CASA) posits that
people apply the same social norms to computers as they would do to people. On
from this, previous studies have focused on applying conversational strategies
to computer agents to make them embody more favourable human characteristics.
However, if a computer agent fails in this regard it can lead to negative
reactions from users. Therefore, in this dissertation we describe a series of
studies we carried out to lead to more effective human-to-computer digital
health messaging.
In our first study, we use the crowd [...]
Our second study investigates the effect of a health chatbot's conversational
style [...]
In our final study, we investigate the format used by a chatbot when [...]
In summary, we have researched how to create more effective digital health
interventions starting from generating health messages, to choosing an
appropriate formality of messaging, and finally to formatting messages which
reference a user's previous utterances.
|
The payload of communications satellites must go through a series of tests to
assert their ability to survive in space. Each test involves some equipment of
the payload to be active, which has an impact on the temperature of the
payload. Sequencing these tests in a way that ensures the thermal stability of
the payload and minimizes the overall duration of the test campaign is a very
important objective for satellite manufacturers. The problem can be decomposed
in two sub-problems corresponding to two objectives: First, the number of
distinct configurations necessary to run the tests must be minimized. This can
be modeled as packing the tests into configurations, and we introduce a set of
implied constraints to improve the lower bound of the model. Second, tests must
be sequenced so that the number of times an equipment unit has to be switched
on or off is minimized. We model this aspect using the constraint Switch, where
a buffer with limited capacity represents the currently active equipment units,
and we introduce an improvement of the propagation algorithm for this
constraint. We then introduce a search strategy in which we sequentially solve
the sub-problems (packing and sequencing). Experiments conducted on real and
random instances show the respective interest of our contributions.
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Active learning seeks to reduce the amount of data required to fit the
parameters of a model, thus forming an important class of techniques in modern
machine learning. However, past work on active learning has largely overlooked
latent variable models, which play a vital role in neuroscience, psychology,
and a variety of other engineering and scientific disciplines. Here we address
this gap by proposing a novel framework for maximum-mutual-information input
selection for discrete latent variable regression models. We first apply our
method to a class of models known as "mixtures of linear regressions" (MLR).
While it is well known that active learning confers no advantage for
linear-Gaussian regression models, we use Fisher information to show
analytically that active learning can nevertheless achieve large gains for
mixtures of such models, and we validate this improvement using both
simulations and real-world data. We then consider a powerful class of
temporally structured latent variable models given by a Hidden Markov Model
(HMM) with generalized linear model (GLM) observations, which has recently been
used to identify discrete states from animal decision-making data. We show that
our method substantially reduces the amount of data needed to fit GLM-HMM, and
outperforms a variety of approximate methods based on variational and amortized
inference. Infomax learning for latent variable models thus offers a powerful
for characterizing temporally structured latent states, with a wide variety of
applications in neuroscience and beyond.
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We claim that any approach neglecting the spin-orbit coupling and the orbital
magnetism is not physically adequate for 3d oxides, including NiO, and that in
reaching "excellent agreement" in a Phys. Rev. Lett. 93, 126406 (2004) paper
too small experimental value of 1.9 muB has been taken for the Ni magnetic
moment despite publication of a new experimental value of 2.2 muB, at 300 K
yielding 2.6 muB at T = 0 K, already in a year of 1998.
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Nonequilibrium dynamics of a nonintegrable system without the eigenstate
thermalization hypothesis is studied. It is shown that, in the thermodynamic
limit, this model thermalizes after an arbitrary quantum quench at finite
temperature, although it does not satisfy the eigenstate thermalization
hypothesis. In contrast, when the system size is finite and the temperature is
low enough, the system may not thermalize. In this case, the steady state is
well described by the generalized Gibbs ensemble constructed by using highly
nonlocal conserved quantities. We also show that this model exhibits
prethermalization, in which the prethermalized state is characterized by
nonthermal energy eigenstates.
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A scheme of universal quantum computation on a chain of qubits is described
that does not require local control. All the required operations, an Ising-type
interaction and spatially uniform simultaneous one-qubit gates, are
translation-invariant.
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In this paper we present a first-principles analysis of the nonequilibrium
work distribution and the free energy difference of a quantum system
interacting with a general environment (with arbitrary spectral density and for
all temperatures) based on a well-understood micro-physics (quantum Brownian
motion) model under the conditions stipulated by the Jarzynski equality [C.
Jarzynski, Phys. Rev. Lett. 78, 2690 (1997)] and Crooks' fluctuation theorem
[G. E. Crooks, Phys. Rev. E 60, 2721 (1999)] (in short FTs). We use the
decoherent history conceptual framework to explain how the notion of
trajectories in a quantum system can be made viable and use the
environment-induced decoherence scheme to assess the strength of noise which
could provide sufficient decoherence to warrant the use of trajectories to
define work in open quantum systems. From the solutions to the Langevin
equation governing the stochastic dynamics of such systems we were able to
produce formal expressions for these quantities entering in the FTs, and from
them prove explicitly the validity of the FTs at the high temperature limit. At
low temperatures our general results would enable one to identify the range of
parameters where FTs may not hold or need be expressed differently. We explain
the relation between classical and quantum FTs and the advantage of this
micro-physics open-system approach over the phenomenological modeling and
energy-level calculations for substitute closed quantum systems.
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Around year 2000 the centenary of Planck's thermal radiation formula awakened
interest in the origins of quantum theory, traditionally traced back to the
Planck's conference on 14 December 1900 at the Berlin Academy of Sciences. A
lot of more accurate historical reconstructions, conducted under the stimulus
of that recurrence, placed the birth date of quantum theory in March 1905 when
Einstein advanced his light quantum hypothesis. Both interpretations are yet
controversial, but science historians agree on one point: the emergence of
quantum theory from a presumed "crisis" of classical physics is a myth with
scarce adherence to the historical truth. This article, written in Italian
language, was originally presented in connection with the celebration of the
World Year of Phyics 2005 with the aim of bringing these scholarly theses to a
wider audience.
---
Tradizionalmente la nascita della teoria quantistica viene fatta risalire al
14 dicembre 1900, quando Planck present\`o all'Accademia delle Scienze di
Berlino la dimostrazione della formula della radiazione termica. Numerose
ricostruzioni storiche pi\`u accurate, effettuate nel periodo intorno al 2000
sotto lo stimolo dell'interesse per il centenario di quell'avvenimento,
collocano invece la nascita della teoria quantistica nel marzo del 1905, quando
Einstein avanz\`o l'ipotesi dei quanti di luce. Entrambe le interpretazioni
sono tuttora controverse, ma gli storici della scienza concordano su un punto:
l'emergere della teoria quantistica da una presunta "crisi" della fisica
classica \`e un mito con scarsa aderenza alla verit\`a storica. Con questo
articolo in italiano, presentato originariamente in occasione delle
celebrazioni per il World Year of Phyics 2005, si \`e inteso portare a un pi\`u
largo pubblico queste tesi gi\`a ben note agli specialisti.
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We investigate the evolution of globular clusters using N-body calculations
and anisotropic Fokker-Planck (FP) calculations. The models include a mass
spectrum, mass loss due to stellar evolution, and the tidal field of the parent
galaxy. Recent N-body calculations have revealed a serious discrepancy between
the results of N-body calculations and isotropic FP calculations. The main
reason for the discrepancy is an oversimplified treatment of the tidal field
employed in the isotropic FP models. In this paper we perform a series of
calculations with anisotropic FP models with a better treatment of the tidal
boundary and compare these with N-body calculations. The new tidal boundary
condition in our FP model includes one free parameter. We find that a single
value of this parameter gives satisfactory agreement between the N-body and FP
models over a wide range of initial conditions.
Using the improved FP model, we carry out an extensive survey of the
evolution of globular clusters over a wide range of initial conditions varying
the slope of the mass function, the central concentration, and the relaxation
time. The evolution of clusters is followed up to the moment of core collapse
or the disruption of the clusters in the tidal field of the parent galaxy. In
general, our model clusters, calculated with the anisotropic FP model with the
improved treatment for the tidal boundary, live longer than isotropic models.
The difference in the lifetime between the isotropic and anisotropic models is
particularly large when the effect of mass loss via stellar evolution is rather
significant. On the other hand the difference is small for relaxation-
dominated clusters which initially have steep mass functions and high central
concentrations.
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Br\"and\'en and Claesson introduced mesh patterns to provide explicit
expansions for certain permutation statistics as linear combinations of
(classical) permutation patterns. The first systematic study of avoidance of
mesh patterns was conducted by Hilmarsson et al., while the first systematic
study of the distribution of mesh patterns was conducted by the first two
authors.
In this paper, we provide far-reaching generalizations for 8 known
distribution results and 5 known avoidance results related to mesh patterns by
giving distribution or avoidance formulas for certain infinite families of mesh
patterns in terms of distribution or avoidance formulas for smaller patterns.
Moreover, as a corollary to a general result, we find the distribution of one
more mesh pattern of length 2.
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We study the kinetics of domain growth of fluid mixtures quenched from a
disordered to a lamellar phase. At low viscosities, in two dimensions, when
hydrodynamic modes become important, dynamical scaling is verified in the form
$C(\vec k, t) \sim L^{\alpha} f[(k-k_M)L]$ where $C$ is the structure factor
with maximum at $k_M$ and
$L$ is a typical length changing from power law to logarithmic growth at late
times. The presence of extended defects can explain the behavior of $L$.
Three-dimensional simulations confirm that diffuse grain boundaries inhibit
complete ordering of lamellae. Applied shear flow alleviates frustration and
gives power-law growth at all times.
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This paper concerns the Cauchy problem of the two-dimensional (2D)
nonhomogeneous incompressible Magnetohydrodynamic (MHD) equations with vacuum
as far field density. We establish the global existence and uniqueness of
strong solutions to the 2D Cauchy problem on the whole space $\mathbb{R}^2$,
provided that the initial density and the initial magnetic decay not too slow
at infinity. In particular, the initial data can be arbitrarily large and the
initial density can contain vacuum states and even have compact support.
Furthermore, we also obtain the large time decay rates of the gradients of
velocity, magnetic and pressure.
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It is known that neither immersions nor maps with a fixed finite set of
multisingularities are enough to realize all mod 2 homology classes in
manifolds. In this paper we define the notion of realizing a homology class up
to cobordism; it is shown that for realization in this weaker sense immersions
are sufficient, but maps with a fixed finite set of multisingularities are
still insufficient.
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The United States of America has been the worst affected country in terms of
the number of cases and deaths on account of the severe acute respiratory
syndrome coronavirus 2 (SARS-CoV-2) or COVID-19, a highly transmissible and
pathogenic coronavirus that started spreading globally in late 2019. On account
of the surge of infections, accompanied by hospitalizations and deaths due to
COVID-19, and lack of a definitive cure at that point, a national emergency was
declared in the United States on March 13, 2020. To prevent the rapid spread of
the virus, several states declared stay at home and remote work guidelines
shortly after this declaration of an emergency. Such guidelines caused schools,
colleges, and universities, both private and public, in all the 50-United
States to switch to remote or online forms of teaching for a significant period
of time. As a result, Google, the most widely used search engine in the United
States, experienced a surge in online shopping of remote learning-based
software, systems, applications, and gadgets by both educators and students
from all the 50-United States, due to both these groups responding to the
associated needs and demands related to switching to remote teaching and
learning. This paper aims to investigate, analyze, and interpret these trends
of Google Shopping related to remote learning that emerged since March 13,
2020, on account of COVID-19 and the subsequent remote learning adoption in
almost all schools, colleges, and universities, from all the 50-United States.
The study was performed using Google Trends, which helps to track and study
Google Shopping-based online activity emerging from different geolocations. The
results and discussions show that the highest interest related to Remote
Learning-based Google Shopping was recorded from Oregon, which was followed by
Illinois, Florida, Texas, California, and the other states.
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Host load prediction is the basic decision information for managing the
computing resources usage on the cloud platform, its accuracy is critical for
achieving the servicelevel agreement. Host load data in cloud environment is
more high volatility and noise compared to that of grid computing, traditional
data-driven methods tend to have low predictive accuracy when dealing with host
load of cloud computing, Thus, we have proposed a host load prediction method
based on Bidirectional Long Short-Term Memory (BiLSTM) in this paper. Our
BiLSTM-based apporach improve the memory capbility and nonlinear modeling
ability of LSTM and LSTM Encoder-Decoder (LSTM-ED), which is used in the recent
previous work, In order to evaluate our approach, we have conducted experiments
using a 1-month trace of a Google data centre with more than twelve thousand
machines. our BiLSTM-based approach successfully achieves higher accuracy than
other previous models, including the recent LSTM one and LSTM-ED one.
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The notion of Turing kernelization investigates whether a polynomial-time
algorithm can solve an NP-hard problem, when it is aided by an oracle that can
be queried for the answers to bounded-size subproblems. One of the main open
problems in this direction is whether k-Path admits a polynomial Turing kernel:
can a polynomial-time algorithm determine whether an undirected graph has a
simple path of length k, using an oracle that answers queries of size poly(k)?
We show this can be done when the input graph avoids a fixed graph H as a
topological minor, thereby significantly generalizing an earlier result for
bounded-degree and $K_{3,t}$-minor-free graphs. Moreover, we show that k-Path
even admits a polynomial Turing kernel when the input graph is not
H-topological-minor-free itself, but contains a known vertex modulator of size
bounded polynomially in the parameter, whose deletion makes it so. To obtain
our results, we build on the graph minors decomposition to show that any
H-topological-minor-free graph that does not contain a k-path, has a separation
that can safely be reduced after communication with the oracle.
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We prove the law of large numbers for the drift of random walks on the
two-dimensional lamplighter group, under the assumption that the random walk
has finite $(2+\epsilon)$-moment. This result is in contrast with classical
examples of abelian groups, where the displacement after $n$ steps, normalised
by its mean, does not concentrate, and the limiting distribution of the
normalised $n$-step displacement admits a density whose support is
$[0,\infty)$. We study further examples of groups, some with random walks
satisfying LLN for drift and other examples where such concentration phenomenon
does not hold, and study relation of this property with asymptotic geometry of
groups.
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The density perturbations generated when the inflaton decay rate is perturbed
by a light scalar field $\chi$ are studied. By explicitly solving the
perturbation equations for the system of two scalar fields and radiation, we
show that even in low energy-scale inflation nearly scale-invariant spectra of
scalar perturbations with an amplitude set by observations are obtained through
the conversion of $\chi$ fluctuations into adiabatic density perturbations. We
demonstrate that the spectra depend on the average decay rate of the inflaton &
on the inflaton fluctuations. We then apply this new mechanism to string
cosmologies & generalized Einstein theories and discuss the conditions under
which scale-invariant spectra are possible.
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In this paper we study a broad class of non-local advection-diffusion models
describing the behaviour of an arbitrary number of interacting species, each
moving in response to the non-local presence of others. Our model allows for
different non-local interaction kernels for each species and arbitrarily many
spatial dimensions. We prove the global existence of both non-negative weak
solutions in any spatial dimension and positive classical solutions in one
spatial dimension. These results generalise and unify various existing results
regarding existence of non-local advection-diffusion equations. We also prove
that solutions can blow up in finite time when the detection radius becomes
zero, i.e. when the system is local, thus showing that nonlocality is essential
for the global existence of solutions. We verify our results with some
numerical simulations on 2D spatial domains.
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We present a solution to the problem of reflection/refraction of a polarized
Gaussian beam on the interface between two transparent media. The transverse
shifts of the beams' centers of gravity are calculated. They always satisfy the
total angular momentum conservation law for beams, however, in general, do not
satisfy the conservation laws for individual photons in consequence of the lack
of the ``which path'' information in a two-channel wave scattering. The field
structure for the reflected/refracted beam is analyzed. In the scattering of a
linearly-polarized beam, photons of opposite helicities are accumulated at the
opposite edges of the beam: this is the spin Hall effect for photons, which can
be registered in the cross-polarized component of the scattered beam.
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In the present paper a plastic-damage model for concrete is discussed. Based
on the fact that for isotropic materials the elastic trial stress and the
projected plastic stress states have the same eigenvec-tors, the loading
surface is formulated in the principal stress space rather than using the
invariants of stress tensor. The model assumes that the directions of
orthotropic damage coincide with principal directions of elastic predictor
stress state (motivated by coaxial rotated crack model). Due to this
assumption, the load-ing surface and the closest point projection algorithm can
still be formulated in the principal directions. The evolution of the inelastic
strain is determined using minimization principle. Damage and plastic parts of
the inelastic strain are separated using a scalar parameter, which is assumed
to be stress dependent. The paper also discusses an effective numerical
implementation. The performance of the model is demonstrated on one
illustrative example.
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The delicate balance of spin-screening and spin-aligning interactions
determines many of the peculiar properties of dilute magnetic systems. We study
a surface-supported all-organic multi-impurity Kondo spin system at the atomic
scale by low-temperature scanning tunnelling microscopy and -spectroscopy. The
model system consists of spin-1/2 radicals that are aligned in one-dimensional
chains and interact via a ferromagnetic RKKY interaction mediated by the 2DEG
of the supporting substrate. Due to the RKKY-induced enhanced depopulation of
one spin-subband in the 2DEG, we finally succeeded to detect the so far
unobserved 'Kondo state' as opposed to the well-established Kondo resonance.
Its cloud of screening electrons, that are virtually bound to the radicals
below the Kondo temperature, represents the extended exchange hole of the
ferromagnetically polarized spin chain imaged here in real space.
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We consider a system of differential equations and obtain its solutions with
exponential asymptotics and analyticity with respect to the spectral parameter.
Solutions of such type have importance in studying spectral properties of
differential operators. Here, we consider the system of first-order
differential equations on a half-line with summable coefficients, containing a
nonlinear dependence on the spectral parameter. We obtain fundamental systems
of solutions with analyticity in certain sectors, in which it is possible to
apply the method of successive approximations. We also construct
non-fundamental systems of solutions with analyticity in a large sector,
including two previously considered neighboring sectors. The obtained results
admit applications in studying inverse spectral problems for the higher-order
differential operators with distribution coefficients.
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In this article, new wormhole solutions in the framework of General
Relativity are presented. Taking advantage of gravitational decoupling by means
of minimal geometric deformation approach and, the so-called noncommutative
geometry Gaussian and Lorentzian density profiles, the seminal Morris-Thorne
space-time is minimally deformed providing new asymptotically wormhole
solutions. Constraining the signature of some parameters, the dimensionless
constant $\alpha$ is bounded using the flare-out and energy conditions. In both
cases, this results in an energy-momentum tensor that violates energy
conditions, thus the space-time is threading by exotic matter. However, it is
possible to obtain a positive defined density at the wormhole throat and its
neighborhood. To further support the study a thoroughly graphical analysis has
been performed.
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The eikonal approximation (EA) is widely used in various high-energy
scattering problems. In this work we generalize this approximation from the
scattering problems with time-independent Hamiltonian to the ones with
periodical Hamiltonians, {\it i.e.}, the Floquet scattering problems. We
further illustrate the applicability of our generalized EA via the scattering
problem with respect to a shaking spherical square-well potential,
by comparing the results given by this approximation and the exact ones. The
generalized EA we developed is helpful for the research of manipulation of
high-energy scattering processes with external field, {\it e.g.}, the
manipulation of atom, molecule or nuclear collisions or reactions via strong
laser fields.
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Radiative corrections to the parity-violating asymmetry measured in elastic
electron-proton scattering are analyzed in the framework of the Standard Model.
We include the complete set of one-loop contributions to one quark current
amplitudes. The contribution of soft photon emission to the asymmetry is also
calculated, giving final results free of infrared divergences. The one quark
radiative corrections, when combined with previous work on many quark effects
and recent SAMPLE experimental data, are used to place some new constraints on
electroweak form factors of the nucleon.
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Distinct entropy definitions have been used to obtain an inverse correlation
between the residual size and entropy for Heavy Ion Collisions. This explains
the existence of several temperatures for different residual size bins, as
reported elsewhere (Natowitz et. al., 2002). HIC collisions were simulated
using binary interaction LATINO model where Pandharipande potential replicates
internucleonic interaction. System temperature is defined as the temperature
obtained when Kinetic Gas Theory is applied to the nucleons in the participant
region. Fragments are detected with an Early Cluster Recognition Algorithm that
optimizes the partitions in energy space.
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The formation of monolayer and multilayer ice with a square lattice structure
has recently been reported on the basis of transmission electron microscopy
experiments, renewing interest in confined two dimensional ice. Here we report
a systematic density functional theory study of double-layer ice in
nano-confinement. A phase diagram as a function of confinement width and
lateral pressure is presented. Included in the phase diagram are honeycomb
hexagonal, square-tube, hexagonal-close-packed and buckled-rhombic structures.
However, contrary to experimental observations, square structures do not
feature: our most stable double-layer square structure is predicted to be
metastable. This study provides general insight into the phase transitions of
double-layer confined ice and a fresh theoretical perspective on the stability
of square ice in graphene nanocapillary experiments.
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The Large Area Telescope (LAT), one of two instruments on the Gamma-ray Large
Area Space Telescope (GLAST) mission, scheduled for launch by NASA in 2007, is
an imaging, wide field-of-view, high-energy gamma-ray telescope, covering the
approximate energy range from 20 MeV to more than 300 GeV. Annihilation of
Weakly Interacting Massive Particles (WIMP), predicted in many extensions of
the Standard Model of Particle Physics, may give rise to a signal in gamma-ray
spectra from many cosmic sources. In this contribution we give an overview of
the searches for WIMP Dark Matter performed by the GLAST-LAT collaboration.
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The inherent network of nanopores and voids in silicon dioxide (SiO2) is
generally undesirable for aspects of film quality, electrical insulation and
dielectric performance. However, if we view these pores as natural
nano-patterns embedded in a dielectric matrix then that opens up new vistas for
exploration. The nano-pattern platform can be used to tailor electrical,
optical, magnetic and mechanical properties of the carrier film. In this
article we report the tunable electrical properties of thermal SiO2 thin-film
achieved through utilization of the metal-nanopore network where the pores are
filled with metallic Titanium (Ti). Without any intentional chemical doping, we
have shown that the electrical resistivity of the oxide film can be controlled
through physical filling up of the intrinsic oxide nanopores with Ti. The
electrical resistance of the composite film remains constant even after
complete removal of the metal from the film surface except the pores. Careful
morphological, electrical and structural analyses are carried out to establish
that the presence of Ti in the nanopores play a crucial role in the observed
conductive nature of the nanoporous film.
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