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This paper discusses fluctuations of linear spectral statistics of
high-dimensional sample covariance matrices when the underlying population
follows an elliptical distribution. Such population often possesses high order
correlations among their coordinates, which have great impact on the asymptotic
behaviors of linear spectral statistics. Taking such kind of dependency into
consideration, we establish a new central limit theorem for the linear spectral
statistics in this paper for a class of elliptical populations. This general
theoretical result has wide applications and, as an example, it is then applied
to test the sphericity of elliptical populations.
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We consider the thermoelectric properties of a double-quantum-dot molecule
coupled in parallel to metal electrodes with a magnetic flux threading the
ring. By means of the Sommerfeld expansion we obtain analytical expressions for
the electric and thermal conductances, thermopower and figure of merit for
arbitrary values of the magnetic flux. We neglect electronic correlations. The
Fano antiresonances in transmission demand that terms usually discarded in the
Sommerfeld expansion are taken into account. We also explore the behavior of
the Lorenz ratio L=\kappa/\sigma T, where \kappa\ and \sigma\ are the thermal
and electrical conductances and T the absolute temperature, and we discuss the
reasons why the Wiedemann-Franz law fails in presence of Fano antiresonances.
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The main thermodynamical properties of the first order phase transition of
the relativistic mean-field (RMF) hadronic model were explored in the isobaric,
the canonical and the grand canonical ensembles on the basis of the method of
the thermodynamical potentials and their first derivatives. It was proved that
the first order phase transition of the RMF model is the liquid-gas type one
associated with the Gibbs free energy $G$. The thermodynamical potential $G$ is
the piecewise smooth function and its first order partial derivatives with
respect to variables of state are the piecewise continuous functions. We have
found that the energy in the caloric curve is discontinuous in the isobaric and
the grand canonical ensembles at fixed values of the pressure and the chemical
potential, respectively, and it is continuous, i.e. it has no plateau, in the
canonical and microcanonical ensembles at fixed values of baryon density, while
the baryon density in the isotherms is discontinuous in the isobaric and the
canonical ensembles at fixed values of the temperature. The general criterion
for the nuclear liquid-gas phase transition in the canonical ensemble was
identified.
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The contribution contains the preface to the Proceedings to the 14th Workshop
What Comes Beyond the Standard Models, Bled, July 11 - 21, 2011, published in
Bled workshops in physics, Vol.12, No. 2, DMFA-Zaloznistvo, Ljubljana, Dec.
2011, and links to the published contributions.
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A robotic feeding system must be able to acquire a variety of foods. Prior
bite acquisition works consider single-arm spoon scooping or fork skewering,
which do not generalize to foods with complex geometries and deformabilities.
For example, when acquiring a group of peas, skewering could smoosh the peas
while scooping without a barrier could result in chasing the peas on the plate.
In order to acquire foods with such diverse properties, we propose stabilizing
food items during scooping using a second arm, for example, by pushing peas
against the spoon with a flat surface to prevent dispersion. The added
stabilizing arm can lead to new challenges. Critically, this arm should
stabilize the food scene without interfering with the acquisition motion, which
is especially difficult for easily breakable high-risk food items like tofu.
These high-risk foods can break between the pusher and spoon during scooping,
which can lead to food waste falling out of the spoon. We propose a general
bimanual scooping primitive and an adaptive stabilization strategy that enables
successful acquisition of a diverse set of food geometries and physical
properties. Our approach, CARBS: Coordinated Acquisition with Reactive Bimanual
Scooping, learns to stabilize without impeding task progress by identifying
high-risk foods and robustly scooping them using closed-loop visual feedback.
We find that CARBS is able to generalize across food shape, size, and
deformability and is additionally able to manipulate multiple food items
simultaneously. CARBS achieves 87.0% success on scooping rigid foods, which is
25.8% more successful than a single-arm baseline, and reduces food breakage by
16.2% compared to an analytical baseline. Videos can be found at
https://sites.google.com/view/bimanualscoop-corl22/home .
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We have numerically simulated the ideal-gas models of trading markets, where
each agent is identified with a gas molecule and each trading as an elastic or
money-conserving two-body collision. Unlike in the ideal gas, we introduce
(quenched) saving propensity of the agents, distributed widely between the
agents ($0 \le \lambda < 1$). The system remarkably self-organizes to a
critical Pareto distribution of money $P(m) \sim m^{-(\nu + 1)}$ with $\nu
\simeq 1$. We analyse the robustness (universality) of the distribution in the
model. We also argue that although the fractional saving ingredient is a bit
unnatural one in the context of gas models, our model is the simplest so far,
showing self-organized criticality, and combines two century-old distributions:
Gibbs (1901) and Pareto (1897) distributions.
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A new detection scheme capable of acquiring the entire spatiotemporal profile
of terahertz radiation in a single laser shot is being demonstrated. The design
allows temporal resolution of the order of transform-limited pulse duration of
the probe, which is an absolute benefit over the compromised resolution of
otherwise prevalent single-shot detection schemes based on spectral encoding of
terahertz waveform on a temporally chirped readout pulse. This makes the
technique perfectly suitable for sensitive spectroscopy studies. The single
shot detection technique presented here relies on space-to-time mapping of
terahertz temporal profile by use of a converging probe intensity front. The
present approach does not require any specialized optics and is implemented
using very straightforward alignment procedure. It has shown to reproduce the
temporal waveform of terahertz radiation faithfully.
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Magneto-electric multiferroics exemplified by TbMnO3 possess both magnetic
and ferroelectric long-range order. The magnetic order is mostly understood,
whereas the nature of the ferroelectricity has remained more elusive. Competing
models proposed to explain the ferroelectricity are associated respectively
with charge transfer and ionic displacements. Exploiting the magneto-electric
coupling, we use an electric field to produce a single magnetic domain state,
and a magnetic field to induce ionic displacements. Under these conditions,
interference charge-magnetic X-ray scattering arises, encoding the amplitude
and phase of the displacements. When combined with a theoretical analysis, our
data allow us to resolve the ionic displacements at the femtoscale, and show
that such displacements make a significant contribution to the zero-field
ferroelectric moment.
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We investigate an interfacial spin-transfer torque and $\beta$-term torque
with alternating current (AC) parallel to a magnetic interface. We find that
both torques are resonantly enhanced as the AC frequency approaches to the
exchange splitting energy. We show that this resonance allows us to estimate
directly the interfacial exchange interaction strength from the domain wall
motion. We also find that the $\beta$-term includes an unconventional
contribution which is proportional to the time derivative of the current and
exists even in absence of any spin relaxation processes.
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In this paper, we show that multiplicity spectra of direct photons in A+A and
d+Au collisions at different centrality classes and different energies exhibit
geometrical scaling, {\em i.e.}, they depend on a specific combination of
number of participants $N_{\rm part}$, collisions energy $W$, and transverse
momentum $p_{T}$ -- called saturation scale -- rather than on all these three
variables separately. In particular, the dependence on the geometry of
collisions encoded in the dependence on $N_{\rm part}$ is in agreement with the
expectations based on the Color Glass Condensate theory.
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In this paper we examine which Brownian Subordination with drift exhibits the
symmetry property introduced by Fajardo and Mordecki (2006). We obtain that
when the subordination results in a L\'evy process, a necessary and sufficient
condition for the symmetry to hold is that drift must be equal to -1/2.
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We excite ion acoustic waves in ultracold neutral plasmas by imprinting
density modulations during plasma creation. Laser-induced fluorescence is used
to observe the density and velocity perturbations created by the waves. The
effect of expansion of the plasma on the evolution of the wave amplitude is
described by treating the wave action as an adiabatic invariant. After
accounting for this effect, we determine that the waves are weakly damped, but
the damping is significantly faster than expected for Landau damping.
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We experimentally study a one-dimensional uncompressed granular chain
composed of a finite number of identical spherical beads with Hertzian
interactions. The chain is harmonically excited by an amplitude- and
frequency-dependent boundary drive at its left end and has a fixed boundary at
its right end. Such ordered granular media represent an interesting new class
of nonlinear acoustic metamaterials, since they exhibit essentially nonlinear
acoustics and have been designated as 'sonic vacua' due to the fact that their
corresponding speed of sound (as defined in classical acoustics) is zero.This
paves the way for essentially nonlinear and energy-dependent acoustics with no
counterparts in linear theory. We experimentally detect time-periodic, strongly
nonlinear resonances whereby the particles (beads) of the granular chain
respond at integer multiples of the excitation period, and which correspond to
local peaks of the maximum transmitted force at the chain's right, fixed end.In
between these resonances we detect a local minimum of the maximum transmitted
forces corresponding to an anti-resonance in the stationary-state dynamics. The
experimental results of this work confirm previous theoretical predictions, and
verify the existence of strongly nonlinear resonance responses in a system with
a complete absence of any linear spectrum; as such, the experimentally detected
nonlinear resonance spectrum is passively tunable with energy and sensitive to
dissipative effects such as internal structural damping in the beads, and
friction or plasticity effects. The experimental results are verified by direct
numerical simulations and by numerical stability analysis.
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Within the framework of a low-energy effective field theory we consider the
procedure of extraction of the S-wave kaon-nucleon scattering lengths a0 and a1
from a combined fit to the kaonic hydrogen and kaonic deuterium data. It is
demonstrated that, if the present DEAR central values for the kaonic hydrogen
ground-state energy and width are used in the analysis of the data, a solution
for a0 and a1 exists only in a restricted domain of input values for the
kaon-deuteron scattering length. We therefore conclude that forthcoming
measurement of this scattering length imposes stringent constraints on the
theoretical description of the kaon-deuteron interactions at low energies.
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We study theoretically the current-induced spin polarization effect in a
two-terminal mesoscopic structure which is composed of a semiconductor
two-dimensional electron gas (2DEG) bar with Rashba spin-orbit (SO) interaction
and two attached ideal leads. The nonequilibrium spin density is calculated by
solving the scattering wave functions explicitly within the ballistic transport
regime. We found that for a Rashba SO system the electrical current can induce
spin polarization in the SO system as well as in the ideal leads. The induced
polarization in the 2DEG shows some qualitative features of the intrinsic spin
Hall effect. On the other hand, the nonequilibrium spin density in the ideal
leads, after being averaged in the transversal direction, is independent of the
distance measured from the lead/SO system interface, except in the vicinity of
the interface. Such a lead polarization effect can even be enhanced by the
presence of weak impurity scattering in the SO system and may be detectable in
real experiments.
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Low-loss microwave components are used in many superconducting resonant
circuits from multiplexed readouts of low-temperature detector arrays to
quantum bits. Two-level system defects in amorphous dielectric materials cause
excess energy loss. In an effort to improve capacitor components, we have used
optical lithography and micromachining techniques to develop superconducting
parallel-plate capacitors in which lossy dielectrics are replaced by vacuum
gaps. Resonance measurements at 50 mK on lumped LC circuits that incorporate
these vacuum-gap capacitors (VGCs) reveal loss tangents at low powers as low as
4x10^{-5}, significantly lower than with capacitors using amorphous
dielectrics. VGCs are structurally robust, small, and easily scaled to
capacitance values above 100 pF.
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We discuss some mathematical conjectures which have come out of the Dirichlet
branes in superstring theory, focusing on the case of supersymmetric branes in
Calabi-Yau compactification. This has led to the formulation of a notion of
stability for objects in a derived category, contact with Kontsevich's
homological mirror symmetry conjecture, and "physics proofs" for many of the
subsequent conjectures based on it, such as the representation of Calabi-Yau
monodromy by autoequivalences of the derived category.
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Virtual reality labs for hearing research are commonly designed to achieve
maximal acoustical accuracy of virtual environments. For a high immersion, 3D
video systems are applied, that ideally do not influence the acoustical
conditions. In labs with projection systems, the video screens have a
potentially strong influence depending on their size, their acoustical
transmittance and their acoustical reflectance. In this study, the acoustical
transmittance and reflectance of six professional acoustic screen fabrics and
13 general purpose fabrics were measured considering two tension conditions.
Additionally, the influence of a black backing was tested, which is needed to
reduce the optical transparency of fabrics. The measured transmission losses
range from -5 dB to -0.1 dB and the reflected sound pressure levels from -32 dB
to -4 dB. The best acoustical properties were measured for a chiffon fabric.
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The combined inductive and coulombic coupling of an orbitally quantized
two-dimensional electron gas to a one-dimensional charge-density wave (CDW) is
shown to give rise to an anisotropic quantum fluid in which the Hall electric
field, current and gradient of the CDW phase are all exponentially screened
from within the bulk. The characteristic penetration depth is similar to the
London penetration depth of relevance to superconductivity.
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This computer science master thesis aims at modelling the nonlinearities of a
loudspeaker. A piecewise linear approximation is initially explored and then we
present a nonlinear Volterra model to simulate the behavior of the system. The
general theory of continuous and discrete Volterra series is summarised. A
Normalized Least Mean Square algorithm is used to determine the Volterra series
to third order. We also present as inverted system which is trained with the
same algorithm. Training data for the models were collected measuring a
physical speaker using a laser interferometer. Results indicate a decrease in
Mean Squared Error compared to the linear model with a dependency on the
particular test signal, the order and the parameters of the model.
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We discuss the possibilities of the BaSeL models in its lowest temperature
boundary (Teff ~ 2500 K for cool giants) to provide the Teff of AGB stars. We
present the first step of our work, by comparing our predictions for the AGB
star R Fornacis with the results of Lorenz-Martins & Lefevre (1994) based on
the dust spectral energy distribution.
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The functionals on an ordered semigroup S in the category Cu--a category to
which the Cuntz semigroup of a C*-algebra naturally belongs--are investigated.
After appending a new axiom to the category Cu, it is shown that the
"realification" S_R of S has the same functionals as S and, moreover, is
recovered functorially from the cone of functionals of S. Furthermore, if S has
a weak Riesz decomposition property, then S_R has refinement and interpolation
properties which imply that the cone of functionals on S is a complete
distributive lattice. These results apply to the Cuntz semigroup of a
C*-algebra. At the level of C*-algebras, the operation of realification is
matched by tensoring with a certain stably projectionless C*-algebra.
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The recent Fermilab measurement of the muon anomalous magnetic moment yields
$4.2 \sigma$ deviations from the SM prediction when combined with the BNL E821
experiment results. In the Type-X two Higgs doublet model, we study the
consequence of imposing the observed muon $g-2$, along with the constraints
from theoretical stabilities, electroweak oblique parameters, Higgs precision
data, and direct searches. For a comprehensive study, we scan the whole
parameter space in two scenarios, the normal scenario where $h_{\rm SM} = h$
and the inverted scenario where $h_{\rm SM}=H$, where $h$ ($H$) is the light
(heavy) CP-even Higgs boson. We found that large $\tan\beta$ (above 100) and
light pseudoscalar mass $M_A$ are required to explain the muon $g-2$ anomaly.
This breaks the theoretical stability unless the scalar masses satisfy $M_A^2
\simeq M_{H^\pm}^2 \simeq m_{12}^2 \tan\beta \approx M_{H/h}^2$. The direct
search bounds at the LEP and LHC exclude the light $A$ window with $M_A
\lesssim 62.5~$GeV. We also show that the observed electron anomalous magnetic
moment is consistent with the model prediction, but the lepton flavor
universality data in the $\tau$ and $Z$ decays are not. For a separate
exploration of the model, we propose the golden mode $pp \to A h/AH \to 4 \tau$
at the HL-LHC.
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We examine heating and cooling in protostellar disks using 3-D radiation-MHD
calculations of a patch of the Solar nebula at 1 AU, employing the shearing-box
and flux-limited radiation diffusion approximations. The disk atmosphere is
ionized by stellar X-rays, well-coupled to magnetic fields, and sustains a
turbulent accretion flow driven by magneto-rotational instability, while the
interior is resistive and magnetically dead.
The turbulent layers heat by absorbing the light from the central star and by
dissipating the magnetic fields. They are optically-thin to their own radiation
and cool inefficiently. The optically-thick interior in contrast is heated only
weakly, by re-emission from the atmosphere. The interior is colder than a
classical viscous model, and isothermal.
The magnetic fields support an extended atmosphere that absorbs the starlight
1.5 times higher than the hydrostatic viscous model. The disk thickness thus
measures not the internal temperature, but the magnetic field strength.
Fluctuations in the fields move the starlight-absorbing surface up and down.
The height ranges between 13% and 24% of the radius over timescales of several
orbits, with implications for infrared variability.
The fields are buoyant, so the accretion heating occurs higher in the
atmosphere than the stresses. The heating is localized around current sheets,
caused by magneto-rotational instability at lower elevations and by Parker
instability at higher elevations. Gas in the sheets is heated above the stellar
irradiation temperature, even though accretion is much less than irradiation
power when volume-averaged. The hot optically-thin current sheets might be
detectable through their line emission.
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The $\Lambda(1405)$ baryon is difficult to detect in experiment, absent in
many quark model calculations, and supposedly manifested through a two-pole
structure. Its uncommon properties made it subject to numerous experimental and
theoretical studies in recent years. Lattice-QCD eigenvalues for different
quark masses were recently reported by the Adelaide group. We compare these
eigenvalues to predictions of a model based on Unitary Chiral Perturbation
Theory. The UCHPT calculation predicts the quark mass dependence remarkably
well. It also explains the overlap pattern with different meson-baryon
components, mainly $\pi\Sigma$ and $\bar KN$, at different quark masses. More
accurate lattice QCD data are required to draw definite conclusions on the
nature of the $\Lambda(1405)$.
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Extensive measurements of the microwave conductivity of highly pure and
oxygen-ordered \YBCO single crystals have been performed as a means of
exploring the intrinsic charge dynamics of a d-wave superconductor. Broadband
and fixed-frequency microwave apparatus together provide a very clear picture
of the electrodynamics of the superconducting condensate and its thermally
excited nodal quasiparticles. The measurements reveal the existence of very
long-lived excitations deep in the superconducting state, as evidenced by sharp
cusp-like conductivity spectra with widths that fall well within our
experimental bandwidth. We present a phenomenological model of the microwave
conductivity that captures the physics of energy-dependent quasiparticle
dynamics in a d-wave superconductor which, in turn, allows us to examine the
scattering rate and oscillator strength of the thermally excited quasiparticles
as functions of temperature. Our results are in close agreement with the
Ferrell-Glover-Tinkham sum rule, giving confidence in both our experiments and
the phenomenological model. Separate experiments for currents along the $\hat
a$ and $\hat b$ directions of detwinned crystals allow us to isolate the role
of the CuO chain layers in \YBCO, and a model is presented that incorporates
both one-dimensional conduction from the chain electrons and two-dimensional
transport associated with the \cuplane plane layers.
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We consider impact parameter dependence of the polarized and unpolarized
structure functions. Unitarity does not allow factorization of the structure
functions over the Bjorken x and the impact parameter b variables. On the basis
of the particular geometrical model approach we conclude that spin of
constituent quark may have a significant orbital angular momentum component
which can manifest itself through the peripherality of the spin dependent
structure functions.
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We show a theorem proving that a non-local bosonic field upon a covariant
interaction with a confining gauge field undergoes the confinement of its
degrees of freedom present in the free theory changing completely the physical
mass spectrum following Kugo-Ojima criterion. This is applicable to an infinite
number of excitations of the bosonic field including ghosts whereas we pay
special attention to the modes with the complex conjugate masses, states
appearing in the string field theory motivated infinite-derivative models. The
same recipe will obviously work for the Lee-Wick models.
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We report the detection of As V resonance lines observed in the Far
Ultraviolet Spectroscopic Explorer (FUSE) spectra of three hot DA white dwarfs:
G191-B2B, WD0621-376, and WD2211-495. The stars have effective temperatures
ranging from 60,000 K to 64,000 K and are among the most metal-rich white
dwarfs known. We measured the arsenic abundances not only in these stars, but
also in three DO stars in which As has been detected before: HD149499B, HZ21,
and RE0503-289. The arsenic abundances observed in the DA stars are very
similar. This suggests that radiative levitation may be the mechanism that
supports arsenic. The arsenic abundance in HZ21 is significantly lower than
that observed in HD149499B, even though the stars have similar atmospheric
parameters. An additional mechanism may be at play in the atmospheres of these
two DO stars.
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The scattering cancellation technique (SCT) has proved to be an effective way
to render static objects invisible to electromagnetic and acoustic waves.
However, rotating cylindrical or spherical objects possess additional peculiar
scattering features that cannot be cancelled by regular SCT-based cloaks. Here,
a generalized SCT theory to cloak spinning objects, and hide them from static
observers, based on rotating shells with different angular velocity is
discussed. This concept is analytically and numerically demonstrated in the
case of cylinders, showing that generalized SCT operates efficiently in making
rotating objects appear static to an external observer. Our proposal extends
the realm of SCT, and brings it one step closer to its practical realization
that involves moving objects.
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Time-irreversible stochastic processes are frequently used in natural
sciences to explain non-equilibrium phenomena and to design efficient
stochastic algorithms. Our main goal in this thesis is to analyse their
dynamics by means of large deviation theory. We focus on processes that become
deterministic in a certain limit, and characterize their fluctuations around
that deterministic limit by Lagrangian rate functions. Our main techniques for
establishing these characterizations rely on the connection between large
deviations and Hamilton-Jacobi equations. We sketch this connection with
examples in the introductory parts of this thesis.
The second part of the thesis is devoted to irreversible processes that are
motivated from molecular motors, Markov chain Monte Carlo (MCMC) methods and
stochastic slow-fast systems. We characterize the asymptotic dynamics of
molecular motors by Hamiltonians defined in terms of principal-eigenvalue
problems. From our results about the zig-zag sampler used in MCMCs, we learn
that maximal irreversibility corresponds to an optimal rate of convergence. In
stochastic slow-fast systems, our main theoretical contributions are techniques
to work with the variational formulas of Hamiltonians that one encounters in
mean-field systems coupled to fast diffusions.
In the final part of the thesis, we study a family of Fokker-Planck equations
whose solutions become singular in a certain limit. The associated
gradient-flow structures do not converge since the relative entropies diverge
in the limit. To remedy this, we propose to work with a different variational
formulation that takes fluxes into account, which is motivated by density-flux
large deviations.
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Vandiver's conjecture states that any prime p does not divide the class
number $h(R)$ of the maximal real subfield R of the p-th cyclotomic field. The
aim of this paper is to prove Vandiver's conjecture, which has several
consequences including the first case of Fermat's Great Theorem. The main idea
lies in using relations of the algebraic K-theory and the Iwasawa theory,
discovered by M.Kervaire and M.P.Murthy in 1977.
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We define a natural conceptual framework in which a generalization of the
Lov\'{a}sz Local Lemma can be established in quantum probability theory.
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A systematic study of 160 heavy and super-heavy nuclei is performed in the
Hartree-Fock-Bogoliubov approach with the finite range and density dependent
Gogny force with the D1S parameter set. We show calculations in several
approximations: with axially symmetric and reflexion symmetric wave functions,
with axially symmetric and non-reflexion symmetric wave functions and finally
some representative examples with triaxial wave functions are also discussed.
Relevant properties of the ground state and along the fission path are
thoroughly analyzed. Fission barriers, Q$_\alpha$-factors and lifetimes with
respect to fission and $\alpha$-decay as well as other observables are
discussed. Larger configuration spaces and more general HFB wave functions as
compared to previous studies provide a very good agreement with the
experimental data.
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Configurations capable of maximizing both absorptance and polarization
contrast were determined for 1550 nm polarized light illumination of different
plasmonic structure integrated superconducting nanowire single-photon detectors
(SNSPDs) consisting of p=264 nm and P=792 nm periodic niobium-nitride (NbN)
patterns on silica substrate. Global NbN absorptance maxima appear in case of
p/s-polarized light illumination in S/P-orientation (gamma=90 azimuthal angle)
and the highest polarization contrast is attained in S-orientation of all
devices. Common nanophotonical origin of absorptance enhancement is collective
resonance on nano-cavity-gratings with different profiles, which is promoted by
coupling between localized modes in quarter wavelength MIM nano-cavities and
laterally synchronized Brewster-Zenneck-type surface waves in integrated SNSPDs
possessing a three-quarter-wavelength-scaled periodicity. The spectral
sensitivity and dispersion characteristics reveal that device design specific
optimal configurations exist.
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Clinical text is rich in information, with mentions of treatment, medication
and anatomy among many other clinical terms. Multiple terms can refer to the
same core concepts which can be referred as a clinical entity. Ontologies like
the Unified Medical Language System (UMLS) are developed and maintained to
store millions of clinical entities including the definitions, relations and
other corresponding information. These ontologies are used for standardization
of clinical text by normalizing varying surface forms of a clinical term
through Biomedical entity linking. With the introduction of transformer-based
language models, there has been significant progress in Biomedical entity
linking. In this work, we focus on learning through synonym pairs associated
with the entities. As compared to the existing approaches, our approach
significantly reduces the training data and resource consumption. Moreover, we
propose a suite of context-based and context-less reranking techniques for
performing the entity disambiguation. Overall, we achieve similar performance
to the state-of-the-art zero-shot and distant supervised entity linking
techniques on the Medmentions dataset, the largest annotated dataset on UMLS,
without any domain-based training. Finally, we show that retrieval performance
alone might not be sufficient as an evaluation metric and introduce an article
level quantitative and qualitative analysis to reveal further insights on the
performance of entity linking methods.
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A formal consideration in this paper is given for the essential notations to
characterize the object that is distinguished in a problem domain. The distinct
object is represented by another idealized object, which is a schematic
element. When the existence of an element is significant, then a class of these
partial elements is dropped down into actual, potential and virtual objects.
The potential objects are gathered into the variable domains which are the
extended ranges for unbound variables. The families of actual objects are shown
to be parameterized with the types and events. The transitions between events
are shown to be driven by the scripts. A computational framework arises which
is described by the commutative diagrams.
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Time Delay Neural Networks (TDNNs) are widely used in both DNN-HMM based
hybrid speech recognition systems and recent end-to-end systems. Nevertheless,
the receptive fields of TDNNs are limited and fixed, which is not desirable for
tasks like speech recognition, where the temporal dynamics of speech are varied
and affected by many factors. This paper proposes to use deformable TDNNs for
adaptive temporal dynamics modeling in end-to-end speech recognition. Inspired
by deformable ConvNets, deformable TDNNs augment the temporal sampling
locations with additional offsets and learn the offsets automatically based on
the ASR criterion, without additional supervision. Experiments show that
deformable TDNNs obtain state-of-the-art results on WSJ benchmarks
(1.42\%/3.45\% WER on WSJ eval92/dev93 respectively), outperforming standard
TDNNs significantly. Furthermore, we propose the latency control mechanism for
deformable TDNNs, which enables deformable TDNNs to do streaming ASR without
accuracy degradation.
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The muon transverse polarization in the $K^+ \leftarrow \pi^0 \mu^+ \nu_\mu$
decay will be measured at the $10^{-4}$ level in forthcoming experiments. We
compare the phenomenological perspectives with the theoretical predictions in
supersymmetric extensions of the standard model. In the minimal extension,
CP-violating phases lead to a non-zero transverse polarization, that however is
too small to account for a positive experimental signal. The problems that one
encounters when departing from minimal assumptions are discussed. An observable
effect is possible if the hypothesis of R-parity conservation is relaxed, but
only at the price of assuming a very special pattern for the R-parity breaking
couplings.
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While most approaches to the problem of Inverse Reinforcement Learning (IRL)
focus on estimating a reward function that best explains an expert agent's
policy or demonstrated behavior on a control task, it is often the case that
such behavior is more succinctly represented by a simple reward combined with a
set of hard constraints. In this setting, the agent is attempting to maximize
cumulative rewards subject to these given constraints on their behavior. We
reformulate the problem of IRL on Markov Decision Processes (MDPs) such that,
given a nominal model of the environment and a nominal reward function, we seek
to estimate state, action, and feature constraints in the environment that
motivate an agent's behavior. Our approach is based on the Maximum Entropy IRL
framework, which allows us to reason about the likelihood of an expert agent's
demonstrations given our knowledge of an MDP. Using our method, we can infer
which constraints can be added to the MDP to most increase the likelihood of
observing these demonstrations. We present an algorithm which iteratively
infers the Maximum Likelihood Constraint to best explain observed behavior, and
we evaluate its efficacy using both simulated behavior and recorded data of
humans navigating around an obstacle.
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Cooperative inter-vehicular applications rely on the exchange of broadcast
single-hop status messages among vehicles, called beacons. The aggregated load
on the wireless channel due to periodic beacons can prevent the transmission of
other types of messages, what is called channel congestion due to beaconing
activity. In this paper we approach the problem of controlling the beaconing
rate on each vehicle by modeling it as a Network Utility Maximization (NUM)
problem. This allows us to formally apply the notion of fairness of a beaconing
rate allocation in vehicular networks and to control the trade-off between
efficiency and fairness. The NUM methodology provides a rigorous framework to
design a broad family of simple and decentralized algorithms, with proved
convergence guarantees to a fair allocation solution. In this context, we focus
exclusively in beaconing rate control and propose the Fair Adaptive Beaconing
Rate for Intervehicular Communications (FABRIC) algorithm, which uses a
particular scaled gradient projection algorithm to solve the dual of the NUM
problem. The desired fairness notion in the allocation can be established with
an algorithm parameter. Simulation results validate our approach and show that
FABRIC converges to fair rate allocations in multi-hop and dynamic scenarios.
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We study the notion of non-trivial elementary embeddings $j : V \rightarrow
V$ under the assumption that $V$ satisfies $ZFC$ without Power Set but with the
Collection Scheme. We show that no such embedding can exist under the
additional assumption that it is cofinal and either $V_{\textrm{crit}(j)}$ is a
set or that the Dependent Choice Schemes holds. We then study failures of
instances of collection in symmetric submodels of class forcings.
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IoT devices are increasingly being implicated in cyber-attacks, driving
community concern about the risks they pose to critical infrastructure,
corporations, and citizens. In order to reduce this risk, the IETF is pushing
IoT vendors to develop formal specifications of the intended purpose of their
IoT devices, in the form of a Manufacturer Usage Description (MUD), so that
their network behavior in any operating environment can be locked down and
verified rigorously.
This paper aims to assist IoT manufacturers in developing and verifying MUD
profiles, while also helping adopters of these devices to ensure they are
compatible with their organizational policies. Our first contribution is to
develop a tool that takes the traffic trace of an arbitrary IoT device as input
and automatically generates a MUD profile for it. We contribute our tool as
open source, apply it to 28 consumer IoT devices, and highlight insights and
challenges encountered in the process. Our second contribution is to apply a
formal semantic framework that not only validates a given MUD profile for
consistency, but also checks its compatibility with a given organizational
policy. Finally, we apply our framework to representative organizations and
selected devices, to demonstrate how MUD can reduce the effort needed for IoT
acceptance testing.
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For a hyperbolic $3$-orbifold with underlying space the $3$-sphere, we obtain
a lower bound on its volume in the case that it contains an essential
$2$-suborbifold with underlying space the $2$-sphere with four cone points. Our
techniques involve computing the guts of the orbifold split along the
$2$-suborbifold via a careful analysis of its topology. We also characterize
the orbifolds of this type that have empty guts.
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People have probably been watching the sky since the beginning of human
history. Observers in pre-telescopic ages recorded anomalous events and these
astronomical records in the historical documents provide uniquely valuable
information for modern scientists. Records with drawings are particularly
useful, as the verbal expressions recorded by pre-telescopic observers, who did
not know the physical nature of the phenomena, are often ambiguous. However,
drawings for specific datable events in the historical documents are much fewer
than the verbal records. Therefore, in this paper, we show the possible
earliest drawings of datable auroras and a two-tail comet in a manuscript of
the Chronicle of Z\=uqn\=in, a Syriac chronicle up to 775/776 CE to interpret
their nature. They provide not only the historical facts in the realm around
Amida but also information about low-latitude aurora observations due to
extreme space weather events and the existence of sun-grazing comets.
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We present a system for generating song lyrics lines conditioned on the style
of a specified artist. The system uses a variational autoencoder with artist
embeddings. We propose the pre-training of artist embeddings with the
representations learned by a CNN classifier, which is trained to predict
artists based on MEL spectrograms of their song clips. This work is the first
step towards combining audio and text modalities of songs for generating lyrics
conditioned on the artist's style. Our preliminary results suggest that there
is a benefit in initializing artists' embeddings with the representations
learned by a spectrogram classifier.
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We present a mean field theory of the Pomeranchuk instability in two
dimensions, starting from a generic central interaction potential described in
terms of a few microscopic parameters. For a significant range of parameters,
the instability is found to be pre-empted by a first-order quantum phase
transition. We provide the ground state phase diagram in terms of our generic
parameters.
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Pulsed plasmas in liquids exhibit complex interaction between three phases of
matter (liquids, gas, plasmas) and are currently used in a wide range of
applications across several fields, however significant knowledge gaps in our
understanding of plasma initiation in liquids hinder additional application and
control; this area of research currently lacks a comprehensive predictive
model. To aid progress in this area experimentally, here we present the
first-known ultrafast (50 ps) X-ray images of pulsed plasma initiation
processes in water (+25 kV, 10 ns, 5 mJ), courtesy of the X-ray imaging
techniques available at Argonne National Laboratory's Advanced Photon Source
(APS), with supporting nanosecond optical imaging and a computational X-ray
diffraction model. These results clearly resolve narrow (~10 micron)
low-density plasma channels during initiation timescales typically obscured by
optical emission (<100 ns), a well-known and difficult problem to plasma
experiments without access to state-of-the-art X-ray sources such as the APS
synchrotron. Images presented in this work speak to several of the prevailing
plasma initiation hypotheses, supporting electrostriction and bubble
deformation as dominant initiation phenomena. We also demonstrate the plasma
setup used in this work as a cheap ($<$US\$100k), compact, and repeatable
benchmark imaging target (29.1 km/s, 1 TW/cm$^2$) useful for the development of
next-generation ultrafast imaging of high-energy-density physics (HEDP), as
well as easier integration of HEDP research into synchrotron-enabled
facilities.
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Phonon transmission across interfaces of dissimilar materials has been
studied intensively in the recent years by using atomistic simulation tools
owing to its importance in determining the effective thermal conductivity of
nanostructured materials. Atomistic Green's function (AGF) method with
interatomic force constants from the first-principles (FP) calculations has
evolved to be a promising approach to study phonon transmission in many not
well-studied material systems. However, the direct FP calculation for
interatomic force constants becomes infeasible when the system involves atomic
disorder. Mass approximation is usually used, but its validity has not been
tested. In this paper, we employ the higher-order force constant model to
extract harmonic force constants from the FP calculations, which originates
from the virtual crystal approximation but considers the local force-field
difference. As a feasibility demonstration of the proposed method that
integrates higher-order force constant model from the FP calculations with the
AGF, we study the phonon transmission in the Mg2Si/Mg2Si1-xSnx systems. When
integrated with the AGF, the widely-used mass approximation is found to
overpredict phonon transmission across Mg2Si/Mg2Sn interface. The difference
can be attributed to the absence of local strain field-induced scattering in
the mass approximation, which makes the high-frequency phonons less scattered.
The frequency-dependent phonon transmission across an interface between a
crystal and an alloy, which often appears in high efficiency "nanoparticle in
alloy" thermoelectric materials, is studied. The interfacial thermal resistance
across Mg2Si/Mg2Si1-xSnx interface is found to be weakly dependent on the
composition of Sn when the composition x is less than 40%, but increases
rapidly when it is larger than 40% due to the transition of high-frequency
phonon DOS in Mg2Si1-xSnx alloys.
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We present observations of the dark Gamma-Ray Burst GRB 051008 provided by
Swift/BAT, Swift/XRT, Konus-WIND, INTEGRAL/SPI-ACS in the high-energy domain
and the Shajn, Swift/UVOT, Tautenburg, NOT, Gemini and Keck I telescopes in the
optical and near-infrared bands. The burst was detected only in gamma- and
X-rays and neither a prompt optical nor a radio afterglow were detected down to
deep limits. We identified the host galaxy of the burst, which is a typical
Lyman-break Galaxy (LBG) with R-magnitude of 24.06 +/- 0.10. A redshift of the
galaxy of z = 2.77 (-0.20,+0.15) is measured photometrically due to the
presence of a clear, strong Lyman-break feature. The host galaxy is a small
starburst galaxy with moderate intrinsic extinction (A_V = 0.3 mag) and has a
SFR of ~ 60 M_Sun / yr typical for LBGs. It is one of the few cases where a GRB
host has been found to be a classical Lyman-break galaxy. Using the redshift we
estimate the isotropic-equivalent radiated energy of the burst to be E_iso =
(1.15 +/- 0.20) x 10^54 erg. We also provide evidence in favour of the
hypothesis that the darkness of GRB 051008 is due to local absorption resulting
from a dense circumburst medium.
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A vast majority of electrical devices have integrated magnetic units, which
generate constant magnetic fields with noticeable vibrations. The majority of
existing nanogenerators acquire energy through friction/mechanical forces and
most of these instances overlook acoustic vibrations and magnetic fields.
Magnetic two-dimensional (2D) tellurides present a wide range of possibilities
for devising a potential flexible energy harvester. We have synthesized
two-dimensional chromium telluride (2D CrTe3) which exhibits ferromagnetic (FM)
nature with a Tc of 224 K. The structure exhibits stable high remnant
magnetization, making 2D CrTe3 flakes a potential material for harvesting of
magneto-acoustic waves at room temperature. A magneto-acoustic nanogenerator
(MANG) was fabricated composing of 2D CrTe3 dispersed in a polymer matrix.
Basic mechanical stability and sensitivity of the device with change in load
conditions were tested. A high surface charge density of 2.919 mC m-2 was
obtained for the device. The thermal strain created in the lattice structure
was examined using in-situ Raman spectroscopic measurements. The magnetic
anisotropy energy (MAE) responsible for long-range FM ordering was calculated
with the help of theoretical modelling. The theoretical calculations also
showed opening of electronic bandgap which enhances the flexoelectric effects.
The MANG can be a potential energy harvester to synergistically tap into the
magneto-acoustic vibrations generated from the frequency changes of a vibrating
device such as loudspeakers.
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Consider quasianalytic local rings of germs of smooth functions closed under
composition, implicit equation, and monomial division. We show that if the
Weierstrass Preparation Theorem holds in such a ring then all elements of it
are germs of analytic functions. .
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In this paper we present a result which establishes a connection between the
theory of compact operators and the theory of iterated function systems. For a
Banach space X, S and T bounded linear operators from X to X such that
\parallel S \parallel, \parallel T \parallel <1 and w \in X, let us consider
the IFS S_{w}=(X,f_1,f_2), where f_1,f_2:X \rightarrow X are given by
f_1(x)=S(x) and f_2(x)=T(x)+w, for all x \in X. On one hand we prove that if
the operator S is compact, then there exists a family (K_{n})_{n \in N} of
compact subsets of X such that A_{S_{w}} is not connected, for all w \in H-
\cup K_{n}. One the other hand we prove that if H is an infinite dimensional
Hilbert space, then a bounded linear operator S:H \rightarrow H having the
property that \parallel S \parallel <1 is compact provided that for every
bounded linear operator T:H\rightarrow H such that \parallel T \parallel <1
there exists a sequence (K_{T,n})_{n} of compact subsets of H such that
A_{S_{w}} is not connected for all w \in H- \cup K_{T,n}. Consequently, given
an infinite dimensional Hilbert space H, there exists a complete
characterization of the compactness of an operator S:H \rightarrow H by means
of the non-connectedness of the attractors of a family of IFSs related to the
given operator.
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Let G be a split connected reductive group over a finite field F_q, and N its
maximal unipotent subgroup. V. Drinfeld has introduced a remarkable partial
compactification of the moduli stack of N-bundles on a smooth projective curve
X over F_q. In this paper we study Drinfeld's moduli space and a certain
category of perverse sheaves on it. The definition of this category is
motivated by the study of the Whittaker functions on the group G(K), where
K=F_q((t)). We prove that our category is semi-simple, and that irreducible
objects of this category are "clean", i.e., they are extenstions by 0 of local
systems supported on the strata. As an application of these results, we obtain
a purely geometric proof of the Casselman-Shalika formula for the Whittaker
functions.
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Based on first-principle calculations and $k\cdot p$ model analysis, we show
that the quantum anomalous Hall (QAH) insulating phase can be realized in the
functionalized hematite (or $\alpha$-Fe$_2$O$_3$) nanosheet and the obtained
topological gap can be as large as $\sim$300 meV. The driving force of the
topological phase is the strong interactions of localized Fe 3$d$ electrons
operating on the quadratic band crossing point of the non-interacting band
structures. Such interaction driven QAH insulator is different from the single
particle band topology mechanism in experimentally realized QAH insulator, the
magnetic ion doped topological insulator film. Depending on the thickness of
the nanosheet, topological insulating state with helical-like or chiral edge
states can be realized. Our work provides a realization of the
interaction-driven QAH insulating state in a realistic material.
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In this paper we provide a complete analogy between the Cauchy-Lipschitz and
the DiPerna-Lions theories for ODE's, by developing a local version of the
DiPerna-Lions theory. More precisely, we prove existence and uniqueness of a
maximal regular flow for the DiPerna-Lions theory using only local regularity
and summability assumptions on the vector field, in analogy with the classical
theory, which uses only local regularity assumptions. We also study the
behaviour of the ODE trajectories before the maximal existence time. Unlike the
Cauchy-Lipschitz theory, this behaviour crucially depends on the nature of the
bounds imposed on the spatial divergence of the vector field. In particular, a
global assumption on the divergence is needed to obtain a proper blow-up of the
trajectories.
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We develop a way of improving complex Langevin dynamics motivated by the
Lefschetz-thimble decomposition of integrals. In our method, arbitrary
observables of an original model with multiple Lefschetz thimbles are computed
by a modified model with a single thimble. We apply our modification method to
a one dimensional integral in which the naive implementation of the complex
Langevin dynamics fails to reproduce the exact results due to the severe sign
problem. We show that the toy model can be modified so that the new model
consists of a single Lefschetz thimble. We find that correct results can be
obtained by the improved complex Langevin dynamics.
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We find lower and upper bounds for the first eigenvalue of a nonlocal
diffusion operator of the form $ T(u) = - \int_{\rr^d} K(x,y) (u(y)-u(x)) \,
dy$. Here we consider a kernel $K(x,y)=\psi (y-a(x))+\psi(x-a(y))$ where $\psi$
is a bounded, nonnegative function supported in the unit ball and $a$ means a
diffeomorphism on $\rr^d$. A simple example being a linear function $a(x)= Ax$.
The upper and lower bounds that we obtain are given in terms of the Jacobian of
$a$ and the integral of $\psi$. Indeed, in the linear case $a(x) = Ax$ we
obtain an explicit expression for the first eigenvalue in the whole $\rr^d$ and
it is positive when the the determinant of the matrix $A$ is different from
one. As an application of our results, we observe that, when the first
eigenvalue is positive, there is an exponential decay for the solutions to the
associated evolution problem. As a tool to obtain the result, we also study the
behaviour of the principal eigenvalue of the nonlocal Dirichlet problem in the
ball $B_R$ and prove that it converges to the first eigenvalue in the whole
space as $R\to \infty$.
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The complete next-to-next-to leading order (NNLO) QCD correction matched with
next-to-next-to leading logarithm (NNLL) has been studied for Drell-Yan
production through spin-2 particle at the Large hadron collider (LHC). We
consider generic spin-2 particle which couples differently to the quarks and
the gluons (non-universal scenario). The threshold enhanced analytical
coefficient has been obtained up to third order exploiting the universality of
the soft function as well as the process dependent form factors at the same
order. We performed a detailed phenomenological analysis and give prediction
for the 13 TeV LHC for the search of such BSM signature. We found that the
matched correction at the second order gives sizeable corrections over wide
range of invariant mass of the lepton pair. The scale variation also stabilizes
at this order and reduces to 4%. As a by-product we also provide ingredients
for third order soft-virtual (SV) prediction as well as resummation and study
the impact on LHC searches.
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In this paper we study a family of algebraic deformations of regular
coadjoint orbits of compact semisimple Lie groups with the Kirillov Poisson
bracket. The deformations are restrictions of deformations on the dual of the
Lie algebra. We prove that there are non isomorphic deformations in the family.
The star products are not differential, unlike the star products considered in
other approaches. We make a comparison with the differential star product
canonically defined by Kontsevich's map.
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By scaling isothermal magnetization data measured at different temperatures
in the mixed state of high-Tc superconductors, we show that in some cases the
sample magnetization, measured in increasing magnetic field below the
irreversibility line, is identical with the equilibrium magnetization even in
magnetic fields well within the irreversible regime. This surprising behavior
can hardly be explained in terms of traditional models of vortex pinning in the
bulk of the sample.
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A class of multivariate mixed survival models for continuous and discrete
time with a complex covariance structure is introduced in a context of
quantitative genetic applications. The methods introduced can be used in many
applications in quantitative genetics although the discussion presented
concentrates on longevity studies. The framework presented allows to combine
models based on continuous time with models based on discrete time in a joint
analysis. The continuous time models are approximations of the frailty model in
which the hazard function will be assumed to be piece-wise constant. The
discrete time models used are multivariate variants of the discrete relative
risk models. These models allow for regular parametric likelihood-based
inference by exploring a coincidence of their likelihood functions and the
likelihood functions of suitably defined multivariate generalized linear mixed
models. The models include a dispersion parameter, which is essential for
obtaining a decomposition of the variance of the trait of interest as a sum of
parcels representing the additive genetic effects, environmental effects and
unspecified sources of variability; as required in quantitative genetic
applications. The methods presented are implemented in such a way that large
and complex quantitative genetic data can be analyzed.
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Efficient deterministic algorithms to construct representations of lattice
path matroids over finite fields are presented. They are built on known
constructions of hierarchical secret sharing schemes, a recent characterization
of hierarchical matroid ports, and the existence of isolating weight functions
for lattice path matroids whose values are polynomial on the size of the ground
set.
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In this work, some of the parameters influencing the cooling capacity of a
liquid jet impinging onto Inconel 718 and C45 plates were experimentally
investigated. The experiment included a high-speed camera to record the dynamic
of the jet during the cooling process while an infrared camera was used to
record the temperature field at the opposite surface. Jets made of water and
oil-in-water emulsion were analysed as well as the influence of the oil
concentration. Other parameters studied here include initial temperature of the
plate, nozzle-to-plate distance, nozzle diameter, jet velocity, and impinging
angle. The cooling performance was analysed by solving a full 3D inverse heat
transfer problem (IHTP) with the Conjugate Gradient Method (CGM) implemented in
a new solver in OpenFoam. The basic organization and implementation of the
solver is shown, followed by its validation with a made-up case. Finally, the
growth of the wetting front was analysed for different oil concentrations and a
combination of nozzle diameters and jet velocities for the same flow rate. For
the latest, unexpected results emerged when comparing the wetting growth for
the two plate materials.
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In this research, we propose a series of methodologies to mine transit riders
travel pattern and behavioral preferences, and then we use these knowledges to
adjust and optimize the transit systems. Contributions are: 1) To increase the
data validity: a) we propose a novel approach to rectify the time discrepancy
of data between the AFC (Automated Fare Collection) systems and AVL (Automated
Vehicle Location) system, our approach transforms data events into signals and
applies time domain correlation the detect and rectify their relative
discrepancies. b) By combining historical data and passengers ticketing time
stamps, we induct and compensate missing information in AVL datasets. 2) To
infer passengers alighting point, we introduce a maximum probabilistic model
incorporating passengers home place to recover their complete transit
trajectory from semi-complete boarding records.Then we propose an enhance
activity identification algorithm which is capable of specifying passengers
short-term activity from ordinary transfers. Finally, we analyze the
temporal-spatial characteristic of transit ridership. 3) To discover passengers
travel demands. We integrate each passengers trajectory data in multiple days
and construct a Hybrid Trip Graph (HTG). We then use a depth search algorithm
to derive the spatially closed transit trip chains; Finally, we use closed
transit trip chains of passengers to study their travel pattern from various
perspectives. Finally, we analyze urban transit corridors by aggregating the
passengers critical transit chains.4) We derive eight influential factors, and
then construct passengers choice models under various scenarios. Next, we
validate our model using ridership re-distribute simulations. Finally, we
conduct a comprehensive analysis on passengers temporal choice preference and
use this information to optimize urban transit systems.
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Nonsmooth sparsity constrained optimization encompasses a broad spectrum of
applications in machine learning. This problem is generally non-convex and
NP-hard. Existing solutions to this problem exhibit several notable
limitations, including their inability to address general nonsmooth problems,
tendency to yield weaker optimality conditions, and lack of comprehensive
convergence analysis. This paper considers Smoothing Proximal Gradient Methods
(SPGM) as solutions to nonsmooth sparsity constrained optimization problems.
Two specific variants of SPGM are explored: one based on Iterative Hard
Thresholding (SPGM-IHT) and the other on Block Coordinate Decomposition
(SPGM-BCD). It is shown that the SPGM-BCD algorithm finds stronger stationary
points compared to previous methods. Additionally, novel theories for analyzing
the convergence rates of both SPGM-IHT and SPGM-BCD algorithms are developed.
Our theoretical bounds, capitalizing on the intrinsic sparsity of the
optimization problem, are on par with the best-known error bounds available to
date. Finally, numerical experiments reveal that SPGM-IHT performs comparably
to current IHT-style methods, while SPGM-BCD consistently surpasses them.
Keywords: Sparsity Recovery, Nonsmooth Optimization, Nonconvex Optimization,
Proximal Gradient Method, Block Coordinate Decomposition, Iterative Hard
Thresholding, Convergence Analysis
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Detection and mitigation of radio frequency interference (RFI) is the first
and also the key step for data processing in radio observations, especially for
ongoing low frequency radio experiments towards the detection of the cosmic
dawn and epoch of reionization (EoR). In this paper we demonstrate the
technique and efficiency of RFI identification and mitigation for the 21
Centimeter Array (21CMA), a radio interferometer dedicated to the statistical
measurement of EoR. For terrestrial, man-made RFI, we concentrate mainly on a
statistical approach by identifying and then excising non-Gaussian signatures,
in the sense that the extremely weak cosmic signal is actually buried under
thermal and therefore Gaussian noise. We also introduce the so-called
visibility correlation coefficient instead of conventional visibility, which
allows a further suppression of rapidly time-varying RFI. Finally, we briefly
discuss removals of the sky RFI, the leakage of sidelobes from off-field strong
radio sources with time-invariant power and a featureless spectrum. It turns
out that state of the art technique should allow us to detect and mitigate RFI
to a satisfactory level in present low frequency interferometer observations
such as those acquired with the 21CMA, and the accuracy and efficiency can be
greatly improved with the employment of low-cost, high-speed computing
facilities for data acquisition and processing.
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We report the design, operation, and performance of a next generation
high-speed data acquisition system for multi-channel infrared and optical
photometry based on the modern technologies of Field Programmable Gate Arrays,
the Peripheral Component Interconnect bus, and the Global Positioning System.
This system allows either direct recording of photon arrival times or binned
photon counting with time resolution up to 1-$\mu$s precision in Universal
Time, as well as real-time data monitoring and analysis. The system also allows
simultaneous recording of multi-channel observations with very flexible,
reconfigurable observational modes. We present successful 20-$\mu$s resolution
simultaneous observations of the Crab Nebula Pulsar in the infrared (H-band)
and optical (V-band) wavebands obtained with this system and 100-$\mu$s
resolution V-band observations of the dwarf nova IY Uma with the 5-m Hale
telescope at the Palomar Observatory.
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Reasoning encompasses two typical types: deductive reasoning and inductive
reasoning. Despite extensive research into the reasoning capabilities of Large
Language Models (LLMs), most studies have failed to rigorously differentiate
between inductive and deductive reasoning, leading to a blending of the two.
This raises an essential question: In LLM reasoning, which poses a greater
challenge - deductive or inductive reasoning? While the deductive reasoning
capabilities of LLMs, (i.e. their capacity to follow instructions in reasoning
tasks), have received considerable attention, their abilities in true inductive
reasoning remain largely unexplored. To investigate into the true inductive
reasoning capabilities of LLMs, we propose a novel framework, SolverLearner.
This framework enables LLMs to learn the underlying function (i.e., $y =
f_w(x)$), that maps input data points $(x)$ to their corresponding output
values $(y)$, using only in-context examples. By focusing on inductive
reasoning and separating it from LLM-based deductive reasoning, we can isolate
and investigate inductive reasoning of LLMs in its pure form via SolverLearner.
Our observations reveal that LLMs demonstrate remarkable inductive reasoning
capabilities through SolverLearner, achieving near-perfect performance with ACC
of 1 in most cases. Surprisingly, despite their strong inductive reasoning
abilities, LLMs tend to relatively lack deductive reasoning capabilities,
particularly in tasks involving ``counterfactual'' reasoning.
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MANET is a collection of mobile nodes operated by battery source with limited
energy reservoir. The dynamic topology and absence of pre-existing
infrastructure in MANET makes routing technique more thought-provoking. The
arbitrary movement of nodes may lead towards more packet drop, routing overhead
and end-to-end delay. Moreover power deficiency in nodes affects the packet
forwarding ability and thus reduces network lifetime. So a power aware stable
routing strategy is in demand in MANET. In this manuscript we have proposed a
novel multipath routing strategy that could select multiple stable routes
between source and destination during data transmission depending on two
factors residual energy and link expiration time (LET) of nodes. Our proposed
energy aware stable multipath routing strategy could attain the reliability,
load balancing, and bandwidth aggregation in order to increase the network
lifetime.
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Extreme skin depth engineering (e-skid) can be applied to integrated
photonics to manipulate the evanescent field of a waveguide. Here we
demonstrate that e-skid can be implemented in two directions in order to
deterministically engineer the evanescent wave allowing for dense integration
with enhanced functionalities. In particular, by increasing the skin depth, we
enable the creation of large gap, bendless directional couplers with large
operational bandwidth. Here we experimentally validate two-dimensional e-skid
for integrated photonics in a CMOS photonics foundry and demonstrate strong
coupling with a gap of 1.44 {\mu}m.
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Exploring the potential of GANs for unsupervised disentanglement learning,
this paper proposes a novel GAN-based disentanglement framework with One-Hot
Sampling and Orthogonal Regularization (OOGAN). While previous works mostly
attempt to tackle disentanglement learning through VAE and seek to implicitly
minimize the Total Correlation (TC) objective with various sorts of
approximation methods, we show that GANs have a natural advantage in
disentangling with an alternating latent variable (noise) sampling method that
is straightforward and robust. Furthermore, we provide a brand-new perspective
on designing the structure of the generator and discriminator, demonstrating
that a minor structural change and an orthogonal regularization on model
weights entails an improved disentanglement. Instead of experimenting on simple
toy datasets, we conduct experiments on higher-resolution images and show that
OOGAN greatly pushes the boundary of unsupervised disentanglement.
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Compartmental epidemic models are among the most popular ones in
epidemiology. For the parameters (e.g., the transmission rate) characterizing
these models, the majority of researchers simplify them as constants, while
some others manage to detect their continuous variations. In this paper, we aim
at capturing, on the other hand, discontinuous variations, which better
describe the impact of many noteworthy events, such as city lockdowns, the
opening of field hospitals, and the mutation of the virus, whose effect should
be instant. To achieve this, we balance the model's likelihood by total
variation, which regulates the temporal variations of the model parameters. To
infer these parameters, instead of using Monte Carlo methods, we design a novel
yet straightforward optimization algorithm, dubbed Iterated Nelder--Mead, which
repeatedly applies the Nelder--Mead algorithm. Experiments conducted on the
simulated data demonstrate that our approach can reproduce these
discontinuities and precisely depict the epidemics.
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A thin ferromagnetic layer on a bulk equal-spin-pairing triplet
superconductor is shown to mediate a Josephson coupling between the spin
$\uparrow$ and $\downarrow$ condensates of the superconductor. By deriving
analytic expressions for the bound states at the triplet
superconductor-ferromagnet interface, we show that this spin Josephson effect
establishes an effective anisotropy axis in the ferromagnetic layer. The
associated Josephson spin current is predicted to cause a measurable precession
of the magnetization about the vector order parameter of the triplet
superconductor.
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A very common problem in science is the numerical diagonalization of
symmetric or hermitian 3x3 matrices. Since standard "black box" packages may be
too inefficient if the number of matrices is large, we study several
alternatives. We consider optimized implementations of the Jacobi, QL, and
Cuppen algorithms and compare them with an analytical method relying on
Cardano's formula for the eigenvalues and on vector cross products for the
eigenvectors. Jacobi is the most accurate, but also the slowest method, while
QL and Cuppen are good general purpose algorithms. The analytical algorithm
outperforms the others by more than a factor of 2, but becomes inaccurate or
may even fail completely if the matrix entries differ greatly in magnitude.
This can mostly be circumvented by using a hybrid method, which falls back to
QL if conditions are such that the analytical calculation might become too
inaccurate. For all algorithms, we give an overview of the underlying
mathematical ideas, and present detailed benchmark results. C and Fortran
implementations of our code are available for download from
http://www.mpi-hd.mpg.de/~globes/3x3/ .
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Cellular Automata (CA) have long been foundational in simulating dynamical
systems computationally. With recent innovations, this model class has been
brought into the realm of deep learning by parameterizing the CA's update rule
using an artificial neural network, termed Neural Cellular Automata (NCA). This
allows NCAs to be trained via gradient descent, enabling them to evolve into
specific shapes, generate textures, and mimic behaviors such as swarming.
However, a limitation of traditional NCAs is their inability to exhibit
sufficiently complex behaviors, restricting their potential in creative and
modeling tasks. Our research explores enhancing the NCA framework by
incorporating multiple neighborhoods and introducing structured noise for seed
states. This approach is inspired by techniques that have historically
amplified the expressiveness of classical continuous CA. All code and example
videos are publicly available on https://github.com/MagnusPetersen/MNNCA.
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We present an algorithm to test whether a given graphical degree sequence is
forcibly connected or not and prove its correctness. We also outline the
extensions of the algorithm to test whether a given graphical degree sequence
is forcibly $k$-connected or not for every fixed $k\ge 2$. We show through
experimental evaluations that the algorithm is efficient on average, though its
worst case run time is probably exponential. We also adapt Ruskey et al's
classic algorithm to enumerate zero-free graphical degree sequences of length
$n$ and Barnes and Savage's classic algorithm to enumerate graphical partitions
of even integer $n$ by incorporating our testing algorithm into theirs and then
obtain some enumerative results about forcibly connected graphical degree
sequences of given length $n$ and forcibly connected graphical partitions of
given even integer $n$. Based on these enumerative results we make some
conjectures such as: when $n$ is large, (1) almost all zero-free graphical
degree sequences of length $n$ are forcibly connected; (2) almost none of the
graphical partitions of even $n$ are forcibly connected.
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The optical properties of thin films of the heavy-fermion compound CeCoIn5,
which were deposited by molecular beam epitaxy onto MgF2 substrates, have been
studied at frequencies 7 to 45 cm^{-1} (corresponding to 0.2 to 1.3 THz) and
temperatures 2 to 300 K. We observe an electrodynamic behavior which is typical
for heavy fermions, namely Drude-like conductivity with a relaxation rate at
rather low frequencies. This relaxation rate increases almost linearly with
temperature up to at least 30 K. The coherent heavy-fermion state,
characterized by an increase of the effective mass, continuously evolves upon
cooling and is not fully developed for temperatures as low as 5 K.
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This article reviews the so-called "axioms" of origami (paper folding), which
are elementary single-fold operations to achieve incidences between points and
lines in a sheet of paper. The geometry of reflections is applied, and
exhaustive analysis of all possible incidences reveals a set of eight
elementary operations. The set includes the previously known seven "axioms",
plus the operation of folding along a given line. This operation has been
ignored in past studies because it does not create a new line. However,
completeness of the set and its regular application in practical origami
dictate its inclusion. Formal definitions and conditions of existence of
solutions are given for all the operations.
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The definition of stable models for propositional formulas with infinite
conjunctions and disjunctions can be used to describe the semantics of answer
set programming languages. In this note, we enhance that definition by
introducing a distinction between intensional and extensional atoms. The
symmetric splitting theorem for first-order formulas is then extended to
infinitary formulas and used to reason about infinitary definitions. This note
is under consideration for publication in Theory and Practice of Logic
Programming.
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We study the perpendicular transport characteristics of small
superconductor/ferromagnetic insulator/superconductor
(YBa$_2$Cu$_3$O$_{7-x}$/LaMnO$_{3+\delta}$/YBa$_2$Cu$_3$O$_{7-x}$) tunnel
junctions. At a large bias voltage $V\sim 1$ V we observe a step-like onset of
excess current that occurs below the superconducting transition temperature
$T<T_c$ and is easily suppressed by a magnetic field. The phenomenon is
attributed to a novel type of the superconducting proximity effect of
non-equilibrium electrons injected into the conduction band of the
ferromagnetic insulator via a Fowler-Nordheim tunneling process. The occurrence
of a strongly non-equilibrium population is confirmed by the detection of
photon emission at large bias voltage. Since the conduction band in our
ferromagnetic insulator is strongly spin polarized, the long-range (20 nm) of
the observed proximity effect provides evidence for an unconventional
spin-triplet superconducting state.
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The design of reliable circuits has received a lot of attention in the past,
leading to the definition of several design techniques introducing fault
detection and fault tolerance properties in systems for critical
applications/environments. Such design methodologies tackled the problem at
different abstraction levels, from switch-level to logic, RT level, and more
recently to system level. Aim of this paper is to introduce a novel
system-level technique based on the redefinition of the operators functionality
in the system specification. This technique provides reliability properties to
the system data path, transparently with respect to the designer. Feasibility,
fault coverage, performance degradation and overheads are investigated on a FIR
circuit.
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In this article we extend a euclidean result of David and Semmes to the
Heisenberg group by giving a sufficient condition for a $k$-Ahlfors-regular
subset to have big pieces of bilipschitz images of subsets of $\R^k$. This
Carleson type condition measures how well the set can be approximated by the
Heisenberg $k$-planes at different scales and locations. The proof given here
follow the paper of David and Semmes.
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In this paper, we evaluate determinants of some families of
Toeplitz-Hessenberg matrices having tribonacci number entries. These
determinant formulas may also be expressed equivalently as identities that
involve sums of products of multinomial coefficients and tribonacci numbers. In
particular, we establish a connection between the tribonacci and the Fibonacci
and Padovan sequences via Toeplitz-Hessenberg determinants. We then obtain, by
combinatorial arguments, extensions of our determinant formulas in terms of
generalized tribonacci sequences satisfying an r-th order recurrence of a more
general form with the appropriate initial conditions, where r>2 is arbitrary.
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In this paper we consider the class $\mathcal{A}$ of those solutions $u(x,t)$
to the conjugate heat equation $\frac{d}{dt}u = -\Delta u + Ru$ on compact
K\"ahler manifolds $M$ with $c_1 > 0$ (where $g(t)$ changes by the unnormalized
K\"ahler Ricci flow, blowing up at $T < \infty$), which satisfy Perelman's
differential Harnack inequality on $[0,T)$. We show $\mathcal{A}$ is nonempty.
If $|\ric(g(t))| \le \frac{C}{T-t}$, which is alaways true if we have type I
singularity, we prove the solution $u(x,t)$ satisfies the elliptic type Harnack
inequlity, with the constants that are uniform in time. If the flow $g(t)$ has
a type I singularity at $T$, then $\mathcal{A}$ has excatly one element.
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Logs are an essential source of information for people to understand the
running status of a software system. Due to the evolving modern software
architecture and maintenance methods, more research efforts have been devoted
to automated log analysis. In particular, machine learning (ML) has been widely
used in log analysis tasks. In ML-based log analysis tasks, converting textual
log data into numerical feature vectors is a critical and indispensable step.
However, the impact of using different log representation techniques on the
performance of the downstream models is not clear, which limits researchers and
practitioners' opportunities of choosing the optimal log representation
techniques in their automated log analysis workflows. Therefore, this work
investigates and compares the commonly adopted log representation techniques
from previous log analysis research. Particularly, we select six log
representation techniques and evaluate them with seven ML models and four
public log datasets (i.e., HDFS, BGL, Spirit and Thunderbird) in the context of
log-based anomaly detection. We also examine the impacts of the log parsing
process and the different feature aggregation approaches when they are employed
with log representation techniques. From the experiments, we provide some
heuristic guidelines for future researchers and developers to follow when
designing an automated log analysis workflow. We believe our comprehensive
comparison of log representation techniques can help researchers and
practitioners better understand the characteristics of different log
representation techniques and provide them with guidance for selecting the most
suitable ones for their ML-based log analysis workflow.
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We classify embedded blowups of the real affine plane up to oriented
isomorphy. We show that two blowups in the same isomorphism class are isotopic,
using a matrix deformation argument similar to an idea given by Shastri. This
answers two questions which were motivated by the interactive visualizations of
such blowups (see the work of the first author in [Elemente der Mathematik 50
(1995) 149-163] and the second author and Stussak in [IEEE Transactions on
Visualization and Computer Graphics 19 (2013) 978-990] and the references
there).
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The Yamabe problem concerns finding a conformal metric on a given closed
Riemannian manifold so that it has constant scalar curvature. This paper
concerns mainly a fully nonlinear version of the Yamabe problem and the
corresponding Liouville type problem.
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We consider diffusive lattice gases on a ring and analyze the stability of
their density profiles conditionally to a current deviation. Depending on the
current, one observes a phase transition between a regime where the density
remains constant and another regime where the density becomes time dependent.
Numerical data confirm this phase transition. This time dependent profile
persists in the large drift limit and allows one to understand on physical
grounds the results obtained earlier for the totally asymmetric exclusion
process on a ring.
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We study the quantum query complexity of constant-sized subgraph containment.
Such problems include determining whether an $ n $-vertex graph contains a
triangle, clique or star of some size. For a general subgraph $ H $ with $ k $
vertices, we show that $ H $ containment can be solved with quantum query
complexity $ O(n^{2-\frac{2}{k}-g(H)}) $, with $ g(H) $ a strictly positive
function of $ H $. This is better than $ \tilde{O}\s{n^{2-2/k}} $ by Magniez et
al. These results are obtained in the learning graph model of Belovs.
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Perturbed-angular correlation, x-ray absorption, and small-angle x-ray
scattering spectroscopies were suitably combined to elucidate the local
structure of highly diluted and dispersed InOx species confined in porous of
ZSM5 zeolite. These novel approach allow us to determined the structure of
extremely nanosized In-O species exchanged inside the 10-atom-ring channel of
the zeolite, and to quantify the amount of In2O3 crystallites deposited onto
the external zeolite surface.
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We consider an arbitrary Gaussian Stationary Process X(T) with known
correlator C(T), sampled at discrete times T_n = n \Delta T. The probability
that (n+1) consecutive values of X have the same sign decays as P_n \sim
\exp(-\theta_D T_n). We calculate the discrete persistence exponent \theta_D as
a series expansion in the correlator C(\Delta T) up to 14th order, and
extrapolate to \Delta T = 0 using constrained Pad\'e approximants to obtain the
continuum persistence exponent \theta. For the diffusion equation our results
are in exceptionally good agreement with recent numerical estimates.
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In this paper, we propose different algorithms for the solution of a tensor
linear discrete ill-posed problem arising in the application of the meshless
method for solving PDEs in three-dimensional space using multiquadric radial
basis functions. It is well known that the truncated singular value
decomposition (TSVD) is the most common effective solver for ill-conditioned
systems, but unfortunately the operation count for solving a linear system with
the TSVD is computationally expensive for large-scale matrices. In the present
work, we propose algorithms based on the use of the well known Einstein product
for two tensors to define the tensor global Arnoldi and the tensor Gloub Kahan
bidiagonalization algorithms. Using the so-called Tikhonov regularization
technique, we will be able to provide computable approximate regularized
solutions in a few iterations.
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In this article we improve the known Kazhdan constant for $SL_n(Z)$ with
respect to the generating set of the elementary matrices. We prove that the
Kazhdan constant is bounded from below by $[42\sqrt{n}+860]^{-1}$, which gives
the exact asymptotic behavior of the Kazhdan constant, as $n$ goes to infinity,
since $\sqrt{2/n}$ is an upper bound.
We can use this bound to improve the bounds for the spectral gap of the
Cayley graph of $SL_n(F_p)$ and for the working time of the product replacement
algorithm for abelian groups.
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We consider black-box global optimization of time-consuming-to-evaluate
functions on behalf of a decision-maker (DM) whose preferences must be learned.
Each feasible design is associated with a time-consuming-to-evaluate vector of
attributes and each vector of attributes is assigned a utility by the DM's
utility function, which may be learned approximately using preferences
expressed over pairs of attribute vectors. Past work has used a point estimate
of this utility function as if it were error-free within single-objective
optimization. However, utility estimation errors may yield a poor suggested
design. Furthermore, this approach produces a single suggested "best" design,
whereas DMs often prefer to choose from a menu. We propose a novel
multi-attribute Bayesian optimization with preference learning approach. Our
approach acknowledges the uncertainty in preference estimation and implicitly
chooses designs to evaluate that are good not just for a single estimated
utility function but a range of likely ones. The outcome of our approach is a
menu of designs and evaluated attributes from which the DM makes a final
selection. We demonstrate the value and flexibility of our approach in a
variety of experiments.
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Protocols of quantum information processing are the foundation of quantum
technology, allowing to share secrets at a distance for secure communication
(quantum key distribution), to teleport quantum states, and to implement
quantum computation. While various protocols have already been realized, and
even commercialized, the throughput and processing speed of standard protocols
is generally low, limited by the narrow electronic bandwidth of the measurement
apparatus in the MHz-to-GHz range, which is orders-of-magnitude lower than the
optical bandwidth of available quantum optical sources (10-100 THz). We present
a general concept and methods to process quantum information in parallel over
multiplexed frequency channels using parametric homodyne detection for
measurement of all the channels simultaneously, thereby harnessing the optical
bandwidth for quantum information in an efficient manner. We exemplify the
concept through two basic protocols: Multiplexed Continuous-Variable Quantum
Key Distribution (CV-QKD) and multiplexed continuous-variable quantum
teleportation. We demonstrate the multiplexed CV-QKD protocol in a
proof-of-principle experiment, where we successfully carry out QKD over 23
uncorrelated spectral channels, with capability to detect eavesdropping in any
channel. These multiplexed methods (and similar) will enable to carry out
quantum processing in parallel over hundreds of channels, potentially
increasing the throughput of quantum protocols by orders of magnitude.
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We show that a violation of the Clauser-Horne-Shimony-Holt (CHSH) inequality
can be demonstrated in a certain kind of Bell experiment for all bipartite
entangled states. Our protocol allows local filtering measurements and involves
shared ancilla states that do not themselves violate CHSH. Our result follows
from two main steps. We first provide a simple characterization of the states
that violate the CHSH-inequality after local filtering operations in terms of
witness-like operators. Second, we prove that for each entangled state
$\sigma$, there exists another state $\rho$ not violating CHSH, such that
$\rho\otimes\sigma$ violates CHSH. Hence, in this scenario, $\sigma$ cannot be
substituted by classical correlations without changing the statistics of the
experiment; we say that $\sigma$ is not simulable by classical correlations and
our result is that entanglement is equivalent to non-simulability.
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We propose a possible scenario for the new metallic conductivity of
underdoped and optimally doped cuprates. Charge carriers are assumed to be
large polarons which form a Fermi-liquid and Cooper-like pairs below a
crossover tempurature $T^{\ast}$. We use the Boltzmann equation to calculate
the conductivity of self-trapped carriers and the resistivity $\rho$ as a
function of temperature and doping for different cuprates. We show that various
anomalies in $\rho(T)$ below $T^{\ast}$ are caused by the competing
Fermi-liquid and BCS-like precursor pairing effects. Our results for $\rho$ fit
well with existing experiments and characterize high-$T_c$ cuprates with an
intermediate-coupling.
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Equip each point $x$ of a homogeneous Poisson process $\mathcal{P}$ on
$\mathbb{R}$ with $D_x$ edge stubs, where the $D_x$ are i.i.d. positive
integer-valued random variables with distribution given by $\mu$. Following the
stable multi-matching scheme introduced by Deijfen, H\"aggstrom and Holroyd
(2012), we pair off edge stubs in a series of rounds to form the edge set of an
infinite component $G$ on the vertex set $\mathcal{P}$. In this note, we answer
questions of Deijfen, Holroyd and Peres (2011) and Deijfen, H\"aggstr\"om and
Holroyd (2012) on percolation (the existence of an infinite connected
component) in $G$. We prove that percolation may occur a.s. even if $\mu$ has
support over odd integers. Furthermore, we show that for any $\varepsilon>0$
there exists a distribution $\mu$ such that $\mu(\{1\})>1-\varepsilon$ such
that percolation still occurs a.s..
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In community question-answering platforms, tags play essential roles in
effective information organization and retrieval, better question routing,
faster response to questions, and assessment of topic popularity. Hence,
automatic assistance for predicting and suggesting tags for posts is of high
utility to users of such platforms. To develop better tag prediction across
diverse communities and domains, we performed a thorough analysis of users'
tagging behavior in 17 StackExchange communities. We found various common
inherent properties of this behavior in those diverse domains. We used the
findings to develop a flexible neural tag prediction architecture, which
predicts both popular tags and more granular tags for each question. Our
extensive experiments and obtained performance show the effectiveness of our
model
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Subsets and Splits
Filtered Text Samples
Retrieves 100 samples of text containing the specific phrase "You are a helpful assistant", providing limited insight into the dataset.
Helpful Assistant Text Samples
Returns a limited set of rows containing the phrase 'helpful assistant' in the text, providing basic filtering of relevant entries.