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We report the properties of two new isostructural compounds, U3Bi4Ni3 and
U3Bi4Rh3. The first of these compounds is non-metallic, and the second is a
nearly ferromagnetic metal, both as anticipated from their electron count
relative to other U-based members of the larger 3-4-3 family. For U3Bi4Rh3, a
logarithmic increase of C/T below 3 K, a resistivity proportional to T^4/3, and
the recovery of Fermi-liquid behavior in both properties with applied fields
greater than 3T, suggest that U3Bi4Rh3 may be a new example of a material
displaying ferromagnetic quantum criticality.
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Electricity consumption forecasting has vital importance for the energy
planning of a country. Of the enabling machine learning models, support vector
regression (SVR) has been widely used to set up forecasting models due to its
superior generalization for unseen data. However, one key procedure for the
predictive modeling is feature selection, which might hurt the prediction
accuracy if improper features were selected. In this regard, a modified
discrete particle swarm optimization (MDPSO) was employed for feature selection
in this study, and then MDPSO-SVR hybrid mode was built to predict future
electricity consumption. Compared with other well-established counterparts,
MDPSO-SVR model consistently performs best in two real-world electricity
consumption datasets, which indicates that MDPSO for feature selection can
improve the prediction accuracy and the SVR equipped with the MDPSO can be a
promised alternative for electricity consumption forecasting.
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In this paper, we consider a device-to-device communication network in which
$K$ transmitter-receiver pairs are sharing spectrum with each other. We propose
a novel but simple binary scheduling scheme for this network to maximize the
average sum rate of the pairs. According to the scheme, each receiver predicts
its Signal-to-Interference-plus-Noise Ratio (SINR), assuming \emph{all} other
user pairs are active, and compares it to a preassigned threshold to decide
whether its corresponding transmitter to be activated or not. For our proposed
scheme, the optimal threshold that maximizes the expected sum rate is obtained
analytically for the two user-pair case and empirically in the general $K$
user-pair case. Simulation results reveal that our proposed SINR-threshold
scheduling scheme outperforms ITLinQ \cite{navid}, FlashLinQ \cite{flash} and
the method presented in \cite{G} in terms of the expected sum rate (network
throughput). In addition, the computational complexity of the proposed scheme
is $O(K)$, outperforming both ITLinQ and FlashLinQ that have $O(K^2)$
complexity requirements. Moreover, we also discuss the application of our
proposed new scheme into an operator-assisted cellular D2D heterogeneous
network.
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I prefer taking off this paper for the moment because of a mistake in the
lemma 2.1 of the secund version. Precisely, in the proof of this lemma, it is
not clear that the morphism $r\_j$ is flat, that I claim it.
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We demonstrate detection of broadband intense terahertz electromagnetic
pulses by Zeeman-torque sampling (ZTS). Our approach is based on magneto-optic
probing of the Zeeman torque the terahertz magnetic field exerts on the
magnetization of a ferromagnet. Using an 8 nm thick iron film as sensor, we
detect pulses from a silicon-based spintronic terahertz emitter with bandwidth
0.1-11 THz and peak field >0.1 MV/cm. Static calibration provides access to
absolute transient THz field strengths. We show relevant added values of ZTS
compared to electro-optic sampling (EOS): an absolute and echo-free transfer
function with simple frequency dependence, linearity even at high terahertz
field amplitudes, the straightforward calibration of EOS response functions and
the modulation of the polarization-sensitive direction by an external AC
magnetic field. Consequently, ZTS has interesting applications even beyond the
accurate characterization of broadband high-field terahertz pulses for
nonlinear terahertz spectroscopy.
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The correlation energies for two interacting electrons in a parabolic quantum
dot are studied via a pseudo-perturbation recipe. It is shown that the central
spike term, ($m^2-1/4)/r^2$, plays a distinctive role in determining the
spectral properties of the above problem. The study is carried out for a wide
range of the Coulomb coupling strength $\lambda$ relative to the confinement.
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The performance of a quantum information processing protocol is ultimately
judged by distinguishability measures that quantify how distinguishable the
actual result of the protocol is from the ideal case. The most prominent
distinguishability measures are those based on the fidelity and trace distance,
due to their physical interpretations. In this paper, we propose and review
several algorithms for estimating distinguishability measures based on trace
distance and fidelity. The algorithms can be used for distinguishing quantum
states, channels, and strategies (the last also known in the literature as
"quantum combs"). The fidelity-based algorithms offer novel physical
interpretations of these distinguishability measures in terms of the maximum
probability with which a single prover (or competing provers) can convince a
verifier to accept the outcome of an associated computation. We simulate many
of these algorithms by using a variational approach with parameterized quantum
circuits. We find that the simulations converge well in both the noiseless and
noisy scenarios, for all examples considered. Furthermore, the noisy
simulations exhibit a parameter noise resilience. Finally, we establish a
strong relationship between various quantum computational complexity classes
and distance estimation problems.
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Demonstration of how matter effects can result into non-oscillating neutrinos
in vacuum, after they have passed through an appropriate distribution of
matter.
A brief discussion about matter effects in neutrinos oscillation is also
made.
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In this paper, we characterize the rigidity of umbilical hypersurfaces by a
Serrin-type partially overdetermined problem in space forms, which generalizes
the similar results in Euclidean half-space and Euclidean half-ball. Guo-Xia
first obtained these rigidity results when the Robin boundary condition on the
support hypersurface is homogeneous, at this time the target umbilical
hypersurface has orthogonal contact angle with the support. However, in this
paper we can obtain any contact angle $\theta\in (0,\pi)$ by changing the Robin
boundary condition to be inhomogeneous.
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We show how an experimentally realized set of operations on a single trapped
ion is sufficient to simulate a wide class of Hamiltonians of a spin-1/2
particle in an external potential. This system is also able to simulate other
physical dynamics. As a demonstration, we simulate the action of an $n$-th
order nonlinear optical beamsplitter. Two of these beamsplitters can be used to
construct an interferometer sensitive to phase shifts in one of the
interferometer beam paths. The sensitivity in determining these phase shifts
increases linearly with $n$, and the simulation demonstrates that the use of
nonlinear beamsplitters ($n$=2,3) enhances this sensitivity compared to the
standard quantum limit imposed by a linear beamsplitter ($n$=1).
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Entity Linking is one of the essential tasks of information extraction and
natural language understanding. Entity linking mainly consists of two tasks:
recognition and disambiguation of named entities. Most studies address these
two tasks separately or focus only on one of them. Moreover, most of the
state-of-the -art entity linking algorithms are either supervised, which have
poor performance in the absence of annotated corpora or language-dependent,
which are not appropriate for multi-lingual applications. In this paper, we
introduce an Unsupervised Language-Independent Entity Disambiguation (ULIED),
which utilizes a novel approach to disambiguate and link named entities.
Evaluation of ULIED on different English entity linking datasets as well as the
only available Persian dataset illustrates that ULIED in most of the cases
outperforms the state-of-the-art unsupervised multi-lingual approaches.
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We investigate properties of material ejected dynamically in the merger of
black hole-neutron star binaries by numerical-relativity simulations. We
systematically study the dependence of ejecta properties on the mass ratio of
the binary, spin of the black hole, and equation of state of the neutron-star
matter. Dynamical mass ejection is driven primarily by tidal torque, and the
ejecta is much more anisotropic than that from binary neutron star mergers. In
particular, the dynamical ejecta is concentrated around the orbital plane with
a half opening angle of 10--20deg and often sweeps out only a half of the
plane. The ejecta mass can be as large as ~0.1M_sun, and the velocity is
subrelativistic with ~0.2--0.3c for typical cases. The ratio of the ejecta mass
to the bound mass (disk and fallback components) is larger, and the ejecta
velocity is larger, for larger values of the binary mass ratio, i.e., for
larger values of the black-hole mass. The remnant black hole-disk system
receives a kick velocity of O(100)km/s due to the ejecta linear momentum, and
this easily dominates the kick velocity due to gravitational radiation.
Structures of postmerger material, velocity distribution of the dynamical
ejecta, fallback rates, and gravitational waves are also investigated. We also
discuss the effect of ejecta anisotropy on electromagnetic counterparts,
specifically a macronova/kilonova and synchrotron radio emission, developing
analytic models.
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The evolution of the weather can be described by deterministic numerical
weather forecasting models. Multiple runs of these models with different
initial conditions and/or model physics result in forecast ensembles which are
used for estimating the distribution of future atmospheric variables. However,
these ensembles are usually under-dispersive and uncalibrated, so
post-processing is required.
In the present work we compare different versions of Bayesian Model Averaging
(BMA) and Ensemble Model Output Statistics (EMOS) post-processing methods in
order to calibrate 2m temperature and 10m wind speed forecasts of the
operational ALADIN Limited Area Model Ensemble Prediction System of the
Hungarian Meteorological Service. We show that compared to the raw ensemble
both post-processing methods improve the calibration of probabilistic and
accuracy of point forecasts and that the best BMA method slightly outperforms
the EMOS technique.
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We evaluate the local variance of the Hubble Constant $H_0$ with low-z Type
Ia Supernovae (SNe). Our analyses are performed using a hemispherical
comparison method in order to test whether taking the bulk flow motion into
account can reconcile the measurement of the Hubble Constant $H_0$ from
standard candles ($H_0 = 73.8 \pm 2.4 \; \mathrm{km \; s}^{-1}\;
\mathrm{Mpc}^{-1}$) with that of the Planck's Cosmic Microwave Background data
($H_0 = 67.8 \pm 0.9 \; \mathrm{km \; s}^{-1} \mathrm{Mpc}^{-1}$). We obtaina
Hubble Constant maximal variance of $\delta H_0 = (2.30 \pm 0.86) \; \mathrm{km
\; s}^{-1} \mathrm{Mpc}^{-1}$ towards the $(l,b) = (315^{\circ},27^{\circ})$
direction. Interestingly, this result agrees with the bulk flow direction
estimates found in the literature, as well as previous evaluations of the $H_0$
variance due to the presence of nearby inhomogeneities. We assess the
statistical significance of this result with different prescriptions of Monte
Carlo simulations, obtaining moderate statistical significance, i.e., $68.7$\%
confidence level (CL) for such variance. Furthermore, we test the hypothesis of
a higher $H_0$ value in the presence of a bulk flow velocity dipole, finding
some evidence for this result which, however, cannot be claimed to be
significant due to the current large uncertainty in the SNe distance modulus.
Then, we conclude that the tension between different $H_0$ determinations can
plausibly be caused to the bulk flow motion of the local Universe, even though
the current incompleteness of the SNe data set, both in terms of celestial
coverage and distance uncertainties, does not allow a high statistical
significance for these results or a definitive conclusion about this issue.
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We study the suppression of the conductance quantization in quantum spin Hall
systems by a combined effect of electronic interactions and edge disorder, that
is ubiquitous in exfoliated and CVD grown 2D materials. We show that the
interplay between the electronic localized states due to edge defects and
electron-electron interactions gives rise to local magnetic moments, that break
time-reversal symmetry and the topological protection of the edge states in 2D
topological systems. Our results suggest that edge disorder leads to small
deviations of a perfect quantized conductance in short samples and to a strong
conductance suppression in long ones. Our analysis is based on on the Kane-Mele
model, an unrestricted Hubbard mean field Hamiltonian and on a self-consistent
recursive Green's functions technique to calculate the transport quantities.
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In this paper we study the existence, uniqueness and asymptotic stability of
the periodic solutions for a Lipschitz system with a small right hand side.
Classical hypotheses in the periodic case of second Bogolyubov's theorem imply
our ones. By means of the results established we construct the curves of
dependence of the amplitude of asymptotically stable $2\pi$--periodic solutions
of the nonsmooth van der Pol oscillator on the detuning parameter and the
amplitude of the perturbation. After, we compare the resonance curves obtained,
with the resonance curves of the classical van der Pol oscillator which were
first constructed by Andronov and Witt.
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In present paper a spherically symmetric stellar configuration has been
analyzed by assuming the matter distribution of the stellar configuration is
anisotropic in nature and compared with the realistic objects, namely, the low
mass X-ray binaries (LMXBs) and X-ray pulsars. The analytic solution has been
obtained by utilizing the dark energy equation of state for the interior
solution corresponding to the Schwarzschild exterior vacuum solution at the
junction interface. Several physical properties like energy conditions,
stability, mass-radius ratio, and surface redshift are described through
mathematical calculations as well as graphical plots. It is found that obtained
mass-radius ration of the compact stars candidates like 4U 1820-30, PSR J
1614-2230, Vela X-1 and Cen X-3 are very much consistent with the observed data
by Gangopadhyay et al. (Mon. Not. R. Astron. Soc. 431, 3216 (2013)). So our
proposed model would be useful in the investigation of the possible clustering
of dark energy.
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The success of many machine learning (ML) methods depends crucially on having
large amounts of labeled data. However, obtaining enough labeled data can be
expensive, time-consuming, and subject to ethical constraints for many
applications. One approach that has shown tremendous value in addressing this
challenge is semi-supervised learning (SSL); this technique utilizes both
labeled and unlabeled data during training, often with much less labeled data
than unlabeled data, which is often relatively easy and inexpensive to obtain.
In fact, SSL methods are particularly useful in applications where the cost of
labeling data is especially expensive, such as medical analysis, natural
language processing (NLP), or speech recognition. A subset of SSL methods that
have achieved great success in various domains involves algorithms that
integrate graph-based techniques. These procedures are popular due to the vast
amount of information provided by the graphical framework and the versatility
of their applications. In this work, we propose an algebraic topology-based
semi-supervised method called persistent Laplacian-enhanced graph MBO (PL-MBO)
by integrating persistent spectral graph theory with the classical
Merriman-Bence- Osher (MBO) scheme. Specifically, we use a filtration procedure
to generate a sequence of chain complexes and associated families of simplicial
complexes, from which we construct a family of persistent Laplacians. Overall,
it is a very efficient procedure that requires much less labeled data to
perform well compared to many ML techniques, and it can be adapted for both
small and large datasets. We evaluate the performance of the proposed method on
data classification, and the results indicate that the proposed technique
outperforms other existing semi-supervised algorithms.
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This paper is concerned with superconvergence properties of the direct
discontinuous Galerkin (DDG) method for two-dimensional nonlinear
convection-diffusion equations. By using the idea of correction function, we
prove that, for any piecewise tensor-product polynomials of degree $k\geq 2$,
the DDG solution is superconvergent at nodes and Lobatto points, with an order
of ${\cal O}(h^{2k})$ and ${\cal O}(h^{k+2})$, respectively. Moreover,
superconvergence properties for the derivative approximation are also studied
and the superconvergence points are identified at Gauss points, with an order
of ${\cal O}(h^{k+1})$. Numerical experiments are presented to confirm the
sharpness of all the theoretical findings.
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In this paper, we consider how to formulate semiclassical problems in the
context of the AdS/CFT correspondence, based on the proposal of Compere and
Marolf. Our prescription involves the effective action with self-action term
for boundary dynamical fields, which can be viewed as imposing mixed boundary
conditions for the gravity dual. We derive the semiclassical Einstein equations
sourced by boundary CFT stress-energy tensor. Analyzing perturbations of the
holographic semiclassical Einstein equations, we find a universal parameter
$\gamma_d$ which controls the contribution from boundary CFTs and specifies
dynamics on the AdS boundary. As a simple example, we examine the semiclassical
Einstein equations in $3$-dimensions with $4$-dimensional AdS gravity dual, and
show that the boundary BTZ black hole with vanishing expectation value of the
stress-energy tensor becomes unstable due to the backreaction from quantum
stress-energy tensor when the parameter $\gamma_d$ exceeds a certain critical
value.
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Despite the success of adaptive time-stepping in ODE simulation, it has so
far seen few applications for Stochastic Differential Equations (SDEs). To
simulate SDEs adaptively, methods such as the Virtual Brownian Tree (VBT) have
been developed, which can generate Brownian motion (BM) non-chronologically.
However, in most applications, knowing only the values of Brownian motion is
not enough to achieve a high order of convergence; for that, we must compute
time-integrals of BM such as $\int_s^t W_r \, dr$. With the aim of using high
order SDE solvers adaptively, we extend the VBT to generate these integrals of
BM in addition to the Brownian increments. A JAX-based implementation of our
construction is included in the popular Diffrax library
(https://github.com/patrick-kidger/diffrax).
Since the entire Brownian path produced by VBT is uniquely determined by a
single PRNG seed, previously generated samples need not be stored, which
results in a constant memory footprint and enables experiment repeatability and
strong error estimation. Based on binary search, the VBT's time complexity is
logarithmic in the tolerance parameter $\varepsilon$. Unlike the original VBT
algorithm, which was only precise at some dyadic times, we prove that our
construction exactly matches the joint distribution of the Brownian motion and
its time integrals at any query times, provided they are at least $\varepsilon$
apart.
We present two applications of adaptive high order solvers enabled by our new
VBT. Using adaptive solvers to simulate a high-volatility CIR model, we achieve
more than twice the convergence order of constant stepping. We apply an
adaptive third order underdamped or kinetic Langevin solver to an MCMC problem,
where our approach outperforms the No U-Turn Sampler, while using only a tenth
of its function evaluations.
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Let T be a compact complex torus, dim T>2. We show that the category of
coherent sheaves on T is independent of the choice of the complex structure, if
this complex structure is generic. The proof is independent of math.AG/0205210,
where the same result was proven for K3 surfaces and even-dimensional tori.
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In Frequency Modulated Continuous Waveform (FMCW) radar systems, the phase
noise from the Phase-Locked Loop (PLL) can increase the noise floor in the
Range-Doppler map. The adverse effects of phase noise on close targets can be
mitigated if the transmitter (Tx) and receiver (Rx) employ the same chirp, a
phenomenon known as the range correlation effect.
In the context of a multi-static radar network, sharing the chirp between
distant radars becomes challenging. Each radar generates its own chirp, leading
to uncorrelated phase noise. Consequently, the system performance cannot
benefit from the range correlation effect.
Previous studies show that selecting a suitable code sequence for a Phase
Modulated Continuous Waveform (PMCW) radar can reduce the impact of
uncorrelated phase noise in the range dimension. In this paper, we demonstrate
how to leverage this property to exploit both the mono- and multi-static
signals of each radar in the network without having to share any signal at the
carrier frequency. The paper introduces a detailed signal model for PMCW radar
networks, analyzing both correlated and uncorrelated phase noise effects in the
Doppler dimension. Additionally, a solution for compensating uncorrelated phase
noise in Doppler is presented and supported by numerical results.
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Analytical investigations are made on BML two-dimensional traffic flow model
with alternative movement and exclude-volume effect. Several exact results are
obtained, including the upper critical density above which there are only
jamming configurations asymptotically, and the lower critical density below
which there are only moving configurations asymptotically. The jamming
transition observed in the ensemble average velocity takes place at another
critical density $p_{c}(N)$, which is dependent on the lattice size $N$ and is
in the intermediate region between the lower and upper critical densities. It
is suggested that $p_{c}(N)$ is proportional to a power of $N$, in good
agreement with the numerical simulation. The order parameter of this jamming
transition is identified.
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The search for non-centrosymmetric superconductors that may exhibit unusual
physical properties and unconventional superconductivity has yielded the
synthesis of a non-centrosymmetric phosphide Mg$_2$Rh$_3$P with an
Al$_2$Mo$_3$C-type structure. Although stoichiometric Mg$_2$Rh$_3$P does not
exhibit superconductivity at temperatures above 2 K, we found that an Mg
deficiency of approximately 5 at.% in the Mg$_2$Rh$_3$P induced
superconductivity at 3.9 K. Physical properties such as the lattice parameter a
= 0.70881 nm, Sommerfeld constant $\gamma_n$ = 5.36 mJ mol$^{-1}$ K$^{-2}$,
specific heat jump $\Delta$C$_{el}$/$\gamma_n$Tc = 0.72, electron-phonon
coupling constant $\lambda$$_{e-p}$ = 0.58, upper critical field H$_{c2}$(0) =
24.3 kOe, and pressure effect dTc/dP = -0.34 K/GPa were measured for the
superconducting Mg$_{2-\delta}$Rh$_3$P ($\delta$ $\sim$ 0.1). Band-structure
calculations indicate that exotic fermions, which are not present in
high-energy physics, exist in Mg$_2$Rh$_3$P. Since Mg, Rh, and P are the first
elements used at each crystal site of Al$_2$Mo$_3$C-type compounds, the
discovery of Mg$_2$Rh$_3$P may guide the search for new related materials.
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We introduce the notion of discrete Baker-Akhiezer (DBA) modules, which are
modules over the ring of difference operators, as a certain discretization of
Baker-Akhiezer modules which are modules over the ring of differential
operators. We use it to construct commuting difference operators with matrix
coefficients in several discrete variables.
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The one-dimensional reaction diffusion process AA->A and A0A->AAA is exactly
solvable through the empty interval method if the diffusion rate equals the
coagulation rate. Independently of the particle production rate, the model is
always in the universality class of diffusion-annihilation. This allows us to
check analytically the universality of finite-size scaling in a non-equilibrium
critical point.
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In this paper, we study the problem of uniqueness of tangent cone for
minimizing extrinsic biharmonic maps. Following the celebrated result of Simon,
we prove that if the target manifold is a compact analytic submanifold in R p
and if there is one tangent map whose singularity set consists of the origin
only, then this tangent map is unique.
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We show that in generic supergravity theories the mass of the moduli during
inflation is larger (or at least of the same order of magnitude) than the
Hubble constant. This fact does not depends on the details of the inflation and
on the value of the Hubble parameter during it. The reason is that inflationary
universe is dominated by large F-term (or D-term) density which is higher than
the SUSY breaking scale in the present minimum and stabilizes the flat
directions of the supersymmetric vacua. Therefore, in general even standard
inflationary scenarios (with large H) may solve the cosmological moduli
problem.
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Decision trees are machine learning models commonly used in various
application scenarios. In the era of big data, traditional decision tree
induction algorithms are not suitable for learning large-scale datasets due to
their stringent data storage requirement. Online decision tree learning
algorithms have been devised to tackle this problem by concurrently training
with incoming samples and providing inference results. However, even the most
up-to-date online tree learning algorithms still suffer from either high memory
usage or high computational intensity with dependency and long latency, making
them challenging to implement in hardware. To overcome these difficulties, we
introduce a new quantile-based algorithm to improve the induction of the
Hoeffding tree, one of the state-of-the-art online learning models. The
proposed algorithm is light-weight in terms of both memory and computational
demand, while still maintaining high generalization ability. A series of
optimization techniques dedicated to the proposed algorithm have been
investigated from the hardware perspective, including coarse-grained and
fine-grained parallelism, dynamic and memory-based resource sharing, pipelining
with data forwarding. Following this, we present Hard-ODT, a high-performance,
hardware-efficient and scalable online decision tree learning system on a
field-programmable gate array (FPGA) with system-level optimization techniques.
Performance and resource utilization are modeled for the complete learning
system for early and fast analysis of the trade-off between various design
metrics. Finally, we propose a design flow in which the proposed learning
system is applied to FPGA run-time power monitoring as a case study.
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Answering a question left open in \cite{MZ2}, we show for general symmetric
hyperbolic boundary problems with constant coefficients, including in
particular systems with characteristics of variable multiplicity, that the
uniform Lopatinski condition implies strong $L^2$ well-posedness, with no
further structural assumptions. The result applies, more generally, to any
system that is strongly $L^2$ well-posed for at least one boundary condition.
The proof is completely elementary, avoiding reference to Kreiss symmetrizers
or other specific techniques. On the other hand, it is specific to the
constant-coefficient case; at least, it does not translate in an obvious way to
the variable-coefficient case. The result in the hyperbolic case is derived
from a more general principle that can be applied, for example, to parabolic or
partially parabolic problems like the Navier-Stokes or viscous MHD equations
linearized about a constant state or even a viscous shock.
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We consider scattering by short range perturbations of the semi-classical
Laplacian. We prove that when a polynomial bound on the resolvent holds, the
scattering amplitude is a semi-classical Fourier integral operator associated
to the scattering relation. Compared to previous work, we allow the scattering
relation to have more general structure.
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This paper studies the sliced nearby cycle functor and its commutation with
duality. Over a Henselian discrete valuation ring, we show that this
commutation holds, confirming a prediction of Deligne. As an application we
give a new proof of Beilinson's theorem that the vanishing cycle functor
commutes with duality up to twist. Over an excellent base scheme, we show that
the sliced nearby cycle functor commutes with duality up to modification of the
base. We deduce that duality preserves universal local acyclicity over an
excellent regular base. We also present Gabber's theorem that local acyclicity
implies universal local acyclicity over a Noetherian base.
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We study the spin Hall effect in the kagom\'{e} lattice with Rashba
spin-orbit coupling. The conserved spin Hall conductance $\sigma_{xy}^{s}$ (see
text) and its two components, i.e., the conventional term $\sigma_{xy}^{s0}$
and the spin-torque-dipole term $\sigma_{xy}^{s\tau}$, are numerically
calculated, which show a series of plateaus as a function of the electron Fermi
energy $\epsilon_{F}$. A consistent two-band analysis, as well as a Berry-phase
interpretation, is also given. We show that these plateaus are a consequence of
the various Fermi-surface topologies when tuning $\epsilon_{F}$. In particular,
we predict that compared to the case with the Fermi surface encircling the
$\mathbf{\Gamma}$ point in the Brillouin zone, the amplitude of the spin Hall
conductance with the Fermi surface encircling the $\mathbf{K}$ points is twice
enhanced, which makes it highly meaningful in the future to systematically
carry out studies of the $\mathbf{K}$-valley spintronics.
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We investigate the problem of multi-party private set intersection (MP-PSI).
In MP-PSI, there are $M$ parties, each storing a data set $\mathcal{p}_i$ over
$N_i$ replicated and non-colluding databases, and we want to calculate the
intersection of the data sets $\cap_{i=1}^M \mathcal{p}_i$ without leaking any
information beyond the set intersection to any of the parties. We consider a
specific communication protocol where one of the parties, called the leader
party, initiates the MP-PSI protocol by sending queries to the remaining
parties which are called client parties. The client parties are not allowed to
communicate with each other. We propose an information-theoretic scheme that
privately calculates the intersection $\cap_{i=1}^M \mathcal{p}_i$ with a
download cost of $D = \min_{t \in \{1, \cdots, M\}} \sum_{i \in \{1, \cdots
M\}\setminus {t}} \left\lceil \frac{|\mathcal{p}_t|N_i}{N_i-1}\right\rceil$.
Similar to the 2-party PSI problem, our scheme builds on the connection between
the PSI problem and the multi-message symmetric private information retrieval
(MM-SPIR) problem. Our scheme is a non-trivial generalization of the 2-party
PSI scheme as it needs an intricate design of the shared common randomness.
Interestingly, in terms of the download cost, our scheme does not incur any
penalty due to the more stringent privacy constraints in the MP-PSI problem
compared to the 2-party PSI problem.
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Let G=GL(n,q), SL(n,q) or PGL(n,q) where q is a power of some prime number p,
let U denote a Sylow p-subgroup of G and let R be a commutative ring in which p
is invertible. Let D(U) denote the derived subgroup of U and let e be the
central primitive idempotent of the group algebra RD(U) corresponding to the
projection on the invariant RD(U)-submodule. The aim of this note is to prove
that the R-algebras RG and eRGe are Morita equivalent (through the natural
functor sending an RG-module M to the eRGe-module eM).
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Let $X$ be an analytic space over a non-Archimedean, complete field $k$ and
let $(f_1,..., f_n)$ be a family of invertible functions on $X$. Let $\phi$ the
morphism $X\to G_m^n$ induced by the $f_i$'s, and let $t$ be the map $X\to
(R^*_+)^n$ induced by the norms of the $f_i$'s. Let us recall two results.
1) The compact set $t(X)$ is a polytope of the $R$-vector space $(R^*_+)^n$
(we use the multiplicative notation) ; this is due to Berkovich in the locally
algebraic case, and has been extended to the general case by the author.
2) If moreover $X$ is Hausdorff and $n$-dimensional, then the pre-image under
$\phi$ of the skeleton $S_n$ of $G_m^n$ has a piecewise-linear structure making
$\phi^{-1}(S_n)\to S_n$ a piecewise immersion ; this is due to the author.
In this article, we improve 1) and 2), and give new proofs of both of them.
Our proofs are based upon the model theory of algebraically closed,
non-trivially valued fields.
Let us quickly explain what we mean by improving 1) and 2).
- Concerning 1), we also prove that if $x\in X$, there exists a compact
analytic neighborhood $U$ of $x$, such that for every compact analytic
neighborhood $V$ of $x$ in $X$, the germs of polytopes $(t(U),t(x))$ and
$(t(V),t(x))$ coincide.
- Concerning 2), we prove that the piecewise linear structure on
$\phi^{-1}(S_n)$ is canonical, that is, doesn't depend on the map we choose to
write it as a pre-image of the skeleton; we thus answer a question which was
asked to us by Temkin. Moreover, we prove that the pre-image of the skeleton
'stabilizes after a finite, separable ground field extension', and that if
$\phi_1,..., \phi_m$ are finitely many morphisms from $X\to G_m^n$, the union
$\bigcup \phi_j(S_n)$ also inherits a canonical piecewise-linear structure.
|
We define pseudo-Hermitian magnetic curves in Sasakian manifolds endowed with
the Tanaka-Webster connection. After we give a complete classification theorem,
we construct parametrizations of pseudo-Hermitian magnetic curves in
$\mathbb{R}^{2n+1}(-3)$.
|
The relationships between solar flare parameters (total importance, time
duration, flare index, and flux) and sunspot activity (Rz) as well as those
between geomagnetic activity (aa index) and the flare parameters can be well
described by an integral response model with the response time scales of about
eight and thirteen months, respectively. Compared with linear relationships,
the correlation coefficients of the flare parameters with Rz, of aa with the
flare parameters, and of aa with Rz based on this model have increased about
6%, 17%, and 47% on average, respectively. The time delays of the flare
parameters to Rz, of aa to the flare parameters, and of aa to Rz at their peaks
in solar cycle can be predicted in part by this model (82%, 47%, and 78%,
respectively). These results may be further improved when using a cosine filter
with a wider window. It implies that solar flares are related to the
accumulation of solar magnetic energies in the past through a time decay
factor. The above results may help to understand the mechanism of the solar
cycle and to improve the solar flare prediction.
|
High-temperature cuprate superconductors have been known to exhibit
significant pressure effects. In order to fathom the origin of why and how Tc
is affected by pressure, we have recently studied the pressure effects on Tc
adoptig a model that contains two cupper d-orbitals derived from
first-principles band calculations, where the dz2 orbital is considere on top
of the usually considered dx2-y2 orbital. In that paper, we have identified two
origins for the Tc enhancement under hydrostatic pressure: (i) while at ambient
pressure the smaller the hybridization of other orbital components the higher
the Tc, an application of pressure acts to reduce the multiorbital mxing on the
Fermi surface, which we call the orbital distillation effects, and (ii) the
increase of the band width with pressure also contributes to the enhancement.
In the present paper, we further elabolrate the two points. As for point (i),
while the reduction of the apical oxygen height under pressure tends to
increase the dz2 mixture, hence to lower Tc, here we show that this effect is
strongly reduced in bi-layer materials due to the pyramidal coordination of
oxygen atoms. As for point (ii), we show that the enhancement of Tc due to the
increase in the band width is caused by the effect that the many-body
renormalization arising from the self-energy is reduced.
|
A set $S\subset \mathbb{N}$ is a Sidon set if all pairwise sums $s_1+s_2$
(for $s_1, s_2\in S$, $s_1\leq s_2$) are distinct. A set $S\subset \mathbb{N}$
is an asymptotic basis of order 3 if every sufficiently large integer $n$ can
be written as the sum of three elements of $S$. In 1993, Erd\H{o}s,
S\'{a}rk\"{o}zy and S\'{o}s asked whether there exists a set $S$ with both
properties. We answer this question in the affirmative. Our proof relies on a
deep result of Sawin on the $\mathbb{F}_q[t]$-analogue of Montgomery's
conjecture for convolutions of the von Mangoldt function.
|
Study of astrophysical objects with strong dipolar magnetic fields show that
the spectrum of the accelerated charged particles leaving the sources has a
power law form with exponent -2.5, where the exponent is calculated on purely
geometrical bases and is independent on the particle species.
|
Carbon stars are known to exhibit systematically redder near-infrared colours
with respect to M-type stars. In the near-infrared colour-magnitude diagrams
provided by the 2MASS and DENIS surveys, the LMC C-type stars draw a striking
red tail, well separated from the sequences of O-rich giants. So far, this
conspicuous feature has been absent from any set of available isochrones, even
the few existing ones that include the TP-AGB evolution of low- and
intermediate-mass stars. To investigate such issue we simulate the complete
2MASS Ks vs.(J-Ks) data towards the LMC by means of a population synthesis
approach, that relies on extended libraries of published stellar evolutionary
tracks, including the TP-AGB phase. The simulations provide quite a detailed
description of the several vertical fingers and inclined sequences seen in
2MASS data, due to both Galactic foreground and LMC O-rich stars. Instead, as
mentioned, the red tail of C-stars sets a major difficulty: we find that TP-AGB
models with solar-scaled molecular opacities, the usual assumption of existing
AGB calculations, do not succeed in reproducing this feature. Our tests
indicate that the main reason for this failure should not be ascribed to
empirical Teff - (J-K) transformations for C-type stars. Instead, the
discrepancy is simply removed by adopting new evolutionary models that account
for the changes in molecular opacities as AGB stars get enriched in carbon via
the third dredge-up (Marigo 2002). In fact, simulations that adopt these models
are able to reproduce, for the first time, the red tail of C-stars in
near-infrared CMDs. Finally, we point out that these simulations also provide
useful indications about the efficiency of the third dredge-up process, and the
pulsation modes of long-period variables.
|
The origin of cosmic magnetism is an issue of fundamental importance in
astrophysics. We review here some of the ideas of how large scale magnetic
fields in the universe, particularly in galaxies and galaxy clusters could
arise. The popular paradigm involves the generation of a seed magnetic field
followed by turbulent dynamo amplification of the seed field. We first outline
various seed field generation mechanisms including Biermann batteries. These in
general give a field much smaller than the observed field and so they require
further amplification by dynamo action. The basic idea behind fluctuation
dynamos, as applied to cluster magnetism and the mean-field helical dynamo as
applied to disk galaxies, are outlined. Major difficulties with the dynamo
paradigm are considered. It is particularly important to understand the
nonlinear saturation of dynamos, and whether the fields produced are coherent
enough on large-scales to explain the observed fields in galaxies and clusters.
At the same time the alternative possibility of a primordial field lacks firm
theoretical support but can have very interesting observational consequences.
|
Polyp segmentation is still known as a difficult problem due to the large
variety of polyp shapes, scanning and labeling modalities. This prevents deep
learning model to generalize well on unseen data. However, Transformer-based
approach recently has achieved some remarkable results on performance with the
ability of extracting global context better than CNN-based architecture and yet
lead to better generalization. To leverage this strength of Transformer, we
propose a new model with encoder-decoder architecture named LAPFormer, which
uses a hierarchical Transformer encoder to better extract global feature and
combine with our novel CNN (Convolutional Neural Network) decoder for capturing
local appearance of the polyps. Our proposed decoder contains a progressive
feature fusion module designed for fusing feature from upper scales and lower
scales and enable multi-scale features to be more correlative. Besides, we also
use feature refinement module and feature selection module for processing
feature. We test our model on five popular benchmark datasets for polyp
segmentation, including Kvasir, CVC-Clinic DB, CVC-ColonDB, CVC-T, and
ETIS-Larib
|
Modern robotics often involves the use of web technologies as a means to cope
with the complexity of design and operation. Many of these technologies have
been formalized into standards, which are often avoided by those in robotics
and controls because of a sometimes warranted fear that "the web" is too slow,
or too uncertain for meaningful control applications.
In this work we argue that while web technologies may not be applicable for
all control, they should not be dismissed outright because they can provide
critical help with system integration. Web technologies have also advanced
significantly over the past decade. We present the details of an application of
a web server to perform open and close-loop control (between 3Hz and 1kHz) over
a variety of different network topologies. In our study we also consider the
impact of a web browser to implement the control of the plant. Our results
confirm that meaningful control can be performed using web technologies, and
also highlight design choices that can limit their applicability.
|
We study the UV properties of Type I AGN from the ROSAT All-Sky Survey that
have been selected to show unusually soft X-ray continua. We examine a sample
of 54 Seyfert 1 galaxies with detections in both Near-UV and Far-UV bands of
the Galaxy Evolution Explorer (GALEX) satellite. Our sample is systematically
fainter in the UV than galaxies studied in similar work by previous authors. We
look for correlations between their UV and X-ray properties as well as
correlations of these properties with either black hole mass or Eddington
ratio. The shape of the Big Blue Bump(BBB) in the GALEX regime does not appear
to correlate with its strength relative to the power law continuum, which
conflicts with results reported by previous authors. The strength of the BBB is
correlated with the shape of the X-ray continuum, in agreement with previous
work, but the slope of the correlation is different than previously reported.
The properties of the accretion disks of Type I AGN in the GALEX regime are
relatively independent of black hole mass and Eddington ratio. We compare our
measurements to the predictions of alternative theories for the origin of the
soft excess, but we are unable to distinguish between Comptonization of BBB
photons by a hot plasma and absorption in relativistic winds as the most likely
origins for the soft X-ray excess.
|
We consider the 3-dimensional gravitational $n$-body problem, $n\ge 2$, in
spaces of constant Gaussian curvature $\kappa\ne 0$, i.e.\ on spheres ${\mathbb
S}_\kappa^3$, for $\kappa>0$, and on hyperbolic manifolds ${\mathbb
H}_\kappa^3$, for $\kappa<0$. Our goal is to define and study relative
equilibria, which are orbits whose mutual distances remain constant in time. We
also briefly discuss the issue of singularities in order to avoid impossible
configurations. We derive the equations of motion and define six classes of
relative equilibria, which follow naturally from the geometric properties of
${\mathbb S}_\kappa^3$ and ${\mathbb H}_\kappa^3$. Then we prove several
criteria, each expressing the conditions for the existence of a certain class
of relative equilibria, some of which have a simple rotation, whereas others
perform a double rotation, and we describe their qualitative behaviour. In
particular, we show that in ${\mathbb S}_\kappa^3$ the bodies move either on
circles or on Clifford tori, whereas in ${\mathbb H}_\kappa^3$ they move either
on circles or on hyperbolic cylinders. Then we construct concrete examples for
each class of relative equilibria previously described, thus proving that these
classes are not empty. We put into the evidence some surprising orbits, such as
those for which a group of bodies stays fixed on a great circle of a great
sphere of ${\mathbb S}_\kappa^3$, while the other bodies rotate uniformly on a
complementary great circle of another great sphere, as well as a large class of
quasiperiodic relative equilibria, the first such non-periodic orbits ever
found in a 3-dimensional $n$-body problem. Finally, we briefly discuss other
research directions and the future perspectives in the light of the results we
present here.
|
Exosomes are significant facilitators of inter-cellular communication that
can unveil cell-cell interactions, signaling pathways, regulatory mechanisms
and disease diagnostics. Nonetheless, current analysis required large amount of
data for exosome identification that it hampers efficient and timely mechanism
study and diagnostics. Here, we used a machine-learning assisted
Surface-enhanced Raman spectroscopy (SERS) method to detect exosomes derived
from six distinct cell lines (HepG2, Hela, 143B, LO-2, BMSC, and H8) with small
amount of data. By employing sodium borohydride-reduced silver nanoparticles
and sodium borohydride solution as an aggregating agent, 100 SERS spectra of
the each types of exosomes were collected and then subjected to multivariate
and machine learning analysis. By integrating Principal Component Analysis with
Support Vector Machine (PCA-SVM) models, our analysis achieved a high accuracy
rate of 94.4% in predicting exosomes originating from various cellular sources.
In comparison to other machine learning analysis, our method used small amount
of SERS data to allow a simple and rapid exosome detection, which enables a
timely subsequent study of cell-cell interactions, communication mechanisms,
and disease mechanisms in life sciences.
|
Using a groundstate transformation, we give a new proof of the optimal
Stein-Weiss inequality of Herbst [\int_{\R^N} \int_{\R^N} \frac{\varphi
(x)}{\abs{x}^\frac{\alpha}{2}} I_\alpha (x - y) \frac{\varphi
(y)}{\abs{y}^\frac{\alpha}{2}}\dif x \dif y \le \mathcal{C}_{N,\alpha,
0}\int_{\R^N} \abs{\varphi}^2,] and of its combinations with the Hardy
inequality by Beckner [\int_{\R^N} \int_{\R^N} \frac{\varphi
(x)}{\abs{x}^\frac{\alpha + s}{2}} I_\alpha (x - y) \frac{\varphi
(y)}{\abs{y}^\frac{\alpha + s}{2}}\dif x \dif y \le \mathcal{C}_{N, \alpha, 1}
\int_{\R^N} \abs{\nabla \varphi}^2,] and with the fractional Hardy inequality
[\int_{\R^N} \int_{\R^N} \frac{\varphi (x)}{\abs{x}^\frac{\alpha + s}{2}}
I_\alpha (x - y) \frac{\varphi (y)}{\abs{y}^\frac{\alpha + s}{2}}\dif x \dif y
\le \mathcal{C}_{N, \alpha, s} \mathcal{D}_{N, s} \int_{\R^N} \int_{\R^N}
\frac{\bigabs{\varphi (x) - \varphi (y)}^2}{\abs{x-y}^{N+s}}\dif x \dif y]
where (I_\alpha) is the Riesz potential, (0 < \alpha < N) and (0 < s < \min(N,
2)). We also prove the optimality of the constants. The method is flexible and
yields a sharp expression for the remainder terms in these inequalities.
|
We complement a previous work \cite{Fortuna:2020wwx} using an EFT framework
of dark matter and standard model interactions, with spin-one mediators,
exploring a wider dark matter mass range, up to $6.4$ TeV. We use again bounds
from different experiments: relic density, direct detection experiments and
indirect detection limits from the search of gamma-ray emissions and positron
fluxes. Besides, in this paper we add collider constraints by the ATLAS
Collaboration in monojet analysis. Moreover, here we tested our previous
results in the light of the aforementioned ATLAS data, which turn out to be the
most restrictive forlight dark matter masses (as expected), $m_{\rm DM}<M_Z/2$.
We obtain a larger range of solutions for the operators of dimension 5, OP1 and
OP4, where masses above $43$ GeV and $30$ GeV (but for the $Z$ resonance
region, $\sim (M_Z\pm\Gamma_Z)/2$), respectively, are allowed. In contrast, the
operator of dimension 6, OP3, has viable solutions for masses $\gtrsim 190$
GeV. For the combination of OP1\&OP3 we obtain solutions (for masses larger
than $140$ or $325$ GeV) that depend on the relative sign between the
operators.
|
We explain how to achieve the traceless gauge for the spatial part of the
spin connection in the framework of the recently proposed correspondence
between the (appropriately truncated) bosonic sectors of maximal supergravities
and the `geodesic' sigma-model over E10/K(E10) at low levels. After making this
gauge choice, the residual symmetries on both sides of this correspondence
match precisely. The gauge choice also allows us to give a physical
interpretation to the multiplicity of certain primitive affine null roots of
E10.
|
The zero-temperature Glauber dynamics is used to investigate the persistence
probability $P(t)$ in the Potts model with $Q=3,4,5,7,9,12,24,64, 128$, $256,
512, 1024,4096,16384 $,..., $2^{30}$ states on {\it directed} and {\it
undirected} Barab\'asi-Albert networks and Erd\"os-R\'enyi random graphs. In
this model it is found that $P(t)$ decays exponentially to zero in short times
for {\it directed} and {\it undirected} Erd\"os-R\'enyi random graphs. For {\it
directed} and {\it undirected} Barab\'asi-Albert networks, in contrast it
decays exponentially to a constant value for long times, i.e, $P(\infty)$ is
different from zero for all $Q$ values (here studied) from $Q=3,4,5,...,
2^{30}$; this shows "blocking" for all these $Q$ values. Except that for
$Q=2^{30}$ in the {\it undirected} case $P(t)$ tends exponentially to zero;
this could be just a finite-size effect since in the other "blocking" cases you
may have only a few unchanged spins.
|
We prove the existence of global solutions to the focusing
energy-supercritical semilinear wave equation in R^{3+1} for arbitrary outgoing
large initial data, after we modify the equation by projecting the nonlinearity
on outgoing states.
|
Improved EM strategies, based on the idea of efficient data augmentation
(Meng and van Dyk 1997, 1998), are presented for ML estimation of mixture
proportions. The resulting algorithms inherit the simplicity, ease of
implementation, and monotonic convergence properties of EM, but have
considerably improved speed. Because conventional EM tends to be slow when
there exists a large overlap between the mixture components, we can improve the
speed without sacrificing the simplicity or stability, if we can reformulate
the problem so as to reduce the amount of overlap. We propose simple
"squeezing" strategies for that purpose. Moreover, for high-dimensional
problems, such as computing the nonparametric MLE of the distribution function
with censored data, a natural and effective remedy for conventional EM is to
add exchange steps (based on improved EM) between adjacent mixture components,
where the overlap is most severe. Theoretical considerations show that the
resulting EM-type algorithms, when carefully implemented, are globally
convergent. Simulated and real data examples show dramatic improvement in speed
in realistic situations.
|
We study quantum critical phenomena in the microwave scattering of the
subohmic spin-boson system, which exhibits a quantum phase transition at a
critical system-reservoir coupling. By relating the reflection coefficient of a
microwave with the dynamic susceptibility of the subohmic spin-boson system, we
clarify the appearance of quantum critical phenomena in microwave scattering.
Further, we propose experimental setups to realize the subohmic spin-boson
system in a superconducting circuit composed of a charge qubit and a
dissipative transmission line.
|
We add 9 new observations of NY Vir and identify four others from AASVO
database. Our results indicste that the one and two exo-planet predictions made
by earlier authors do not match these new results.
|
Dynamical behavior of steady granular flow is investigated numerically in the
inelastic hard sphere limit of the soft sphere model. We find distinctively
different limiting behaviors for the two flow regimes, i.e., the collisional
flow and the frictional flow. In the collisional flow, the hard sphere limit is
straightforward; the number of collisions per particle per unit time converges
to a finite value and the total contact time fraction with other particles goes
to zero. For the frictional flow, however, we demonstrate that the collision
rate diverges as the power of the particle stiffness so that the time fraction
of the multiple contacts remains finite even in the hard sphere limit although
the contact time fraction for the binary collisions tends to zero.
|
We present a new method for calculating linear cosmic microwave background
(CMB) anisotropy spectra based on integration over sources along the photon
past light cone. In this approach the temperature anisotropy is written as a
time integral over the product of a geometrical term and a source term. The
geometrical term is given by radial eigenfunctions which do not depend on the
particular cosmological model. The source term can be expressed in terms of
photon, baryon and metric perturbations, all of which can be calculated using a
small number of differential equations. This split clearly separates between
the dynamical and geometrical effects on the CMB anisotropies. More
importantly, it allows to significantly reduce the computational time compared
to standard methods. This is achieved because the source term, which depends on
the model and is generally the most time consuming part of calculation, is a
slowly varying function of wavelength and needs to be evaluated only in a small
number of points. The geometrical term, which oscillates much more rapidly than
the source term, does not depend on the particular model and can be precomputed
in advance. Standard methods that do not separate the two terms and require a
much higher number of evaluations. The new method leads to about two orders of
magnitude reduction in CPU time when compared to standard methods and typically
requires a few minutes on a workstation for a single model. The method should
be especially useful for accurate determinations of cosmological parameters
from CMB anisotropy and polarization measurements that will become possible
with the next generation of experiments. A programm implementing this method
can be obtained from the authors.
|
We present a novel idea to compute square roots over finite fields, without
being given any quadratic nonresidue, and without assuming any unproven
hypothesis. The algorithm is deterministic and the proof is elementary. In some
cases, the square root algorithm runs in $\tilde{O}(\log^2 q)$ bit operations
over finite fields with $q$ elements. As an application, we construct a
deterministic primality proving algorithm, which runs in $\tilde{O}(\log^3 N)$
for some integers $N$.
|
We report the first realization of a biomolecular AND gate function with
double-sigmoid response (sigmoid in both inputs). Two enzyme biomarker inputs
activate the gate output signal which can then be used as indicating liver
injury, but only when both of these inputs have elevated pathophysiological
concentrations, effectively corresponding to logic-1 of the binary gate
functioning. At lower, normal physiological concentrations, defined as logic-0
inputs, the liver-injury output levels are not obtained. High-quality gate
functioning in handling of various sources of noise, on time scales of
relevance to potential applications is enabled by utilizing "filtering"
effected by a simple added biocatalytic process. The resulting gate response is
sigmoid in both inputs when proper system parameters are chosen, and the gate
properties are theoretically analyzed within a model devised to evaluate its
noise-handling properties.
|
Molecular dynamics has been widely used to numerically solve equation of
motion of classical many-particle system. It can be used to simulate many
systems including biophysics, whose complexity level is determined by the
involved elements. Based on this method, a numerical model had been constructed
to mimic the behaviour of malaria-infected red blood cells within capillary
vessel. The model was governed by three forces namely Coulomb force, normal
force, and Stokes force. By utilizing two dimensional four-cells scheme,
theoretical observation was carried out to test its capability. Although the
parameters were chosen deliberately, all of the quantities were given arbitrary
value. Despite this fact, the results were quite satisfactory. Combined with
the previous results, it can be said that the proposed model were sufficient
enough to mimic the malaria-infected red blood cells motion within obstructed
capillary vessel.
Keywords: molecular dynamics, two-dimensional model, red-blood cell motion,
malaria
|
The discovery of novel experimental techniques often lags behind contemporary
theoretical understanding. In particular, it can be difficult to establish
appropriate measurement protocols without analytic descriptions of the
underlying system-of-interest. Here we propose a statistical learning framework
that avoids the need for such descriptions for ergodic systems. We validate
this framework by using Monte Carlo simulation and deep neural networks to
learn a mapping between low-field nuclear magnetic resonance spectra and proton
exchange rates in ethanol-water mixtures. We found that trained networks
exhibited normalized-root-mean-square errors of less than 1% for exchange rates
under 150 s-1 but performed poorly for rates above this range. This
differential performance occurred because low-field measurements are
indistinguishable from one another at fast exchange. Nonetheless, where a
discoverable relationship between indirect measurements and emergent dynamics
exists, we demonstrate the possibility of approximating it without the need for
precise analytic descriptions, allowing experimental science to flourish in the
midst of ongoing theoretical work
|
Molecular or condensed matter systems are often well approximated by hybrid
quantum-classical models: the electrons retain their quantum character, whereas
the ions are considered to be classical particles. We discuss various
alternative approaches for the computation of equilibrium (canonical) ensemble
averages for observables of these hybrid quantum-classical systems through the
use of molecular dynamics (MD), i.e. by performing dynamics in the presence of
a thermostat and computing time averages over the trajectories. Often, in
classical or ab initio MD, the temperature of the electrons is ignored and they
are assumed to remain at the instantaneous ground state given by each ionic
configuration during the evolution. Here, however, we discuss the general case
that considers both classical and quantum subsystems at finite temperature
canonical equilibrium. Inspired by a recent formal derivation for the canonical
ensemble for quantum classical hybrids, we discuss previous approaches found in
the literature, and provide some new formulas.
|
Layered van der Waals magnets have attracted much recent attention as a
promising and versatile platform for exploring intrinsic two-dimensional
magnetism. Within this broader class, the transition metal phosphorous
trichalcogenides $M$P$X_3$ stand out as particularly interesting, as they
provide a realization of honeycomb lattice magnetism and are known to display a
variety of magnetic ordering phenomena as well as superconductivity under
pressure. One example, found in a number of different materials, is
commensurate single-$Q$ zigzag antiferromagnetic order, which spontaneously
breaks the spatial threefold $(C_3)$ rotation symmetry of the honeycomb
lattice. The breaking of multiple distinct symmetries in the magnetic phase
suggests the possibility of a sequence of distinct transitions as a function of
temperature, and a resulting intermediate $\mathbb{Z}_3$-nematic phase which
exists as a paramagnetic vestige of zigzag magnetic order -- a scenario known
as vestigial ordering. Here, we report the observation of key signatures of
vestigial Potts-nematic order in rhombohedral FePSe$_3$. By performing linear
dichroism imaging measurements -- an ideal probe of rotational symmetry
breaking -- we find that the $C_3$ symmetry is already broken above the N\'eel
temperature. We show that these observations are explained by a general
Ginzburg-Landau model of vestigial nematic order driven by magnetic
fluctuations and coupled to residual strain. An analysis of the domain
structure as temperature is lowered and a comparison with zigzag-ordered
monoclinic FePS$_3$ reveals a broader applicability of the Ginzburg-Landau
model in the presence of external strain, and firmly establishes the $M$P$X_3$
magnets as a new experimental venue for studying the interplay between
Potts-nematicity, magnetism and superconductivity.
|
The symmetry properties, order parameters, and magnetoelectric phase diagrams
of multiferroics are discussed. After brief reviews of Ni$_3$V$_2$O$_8$,
TbMnO$_3$, and RbFe(MoO$_4$)$_2$, we present a detailed analysis of
RMn$_2$O$_5$ (with R=Y, Ho, Dy, Er, Tb, Tm).
|
Broad iron emission lines are observed in many accreting systems from black
holes in AGN and X-ray binaries to neutron star low-mass X-ray binaries. The
origin of the line broadening is often interpreted as due to dynamical
broadening and relativistic effects. However, alternative interpretations have
been proposed, included broadening due to Compton scattering in a wind or
accretion disk atmosphere. Here we explore the observational signatures
expected from broadening in a wind, in particular that the iron line width
should increase with an increase in the column density of the absorber (due to
an increase in the number of scatterings). We study the data from three neutron
star low-mass X-ray binaries where both a broad iron emission line and
absorption lines are seen simultaneously, and show that there is no significant
correlation between line width and column density. This favors an inner disk
origin for the line broadening rather than scattering in a wind.
|
We report on Bayesian estimation of the radius, mass, and hot surface regions
of the massive millisecond pulsar PSR J0740$+$6620, conditional on
pulse-profile modeling of Neutron Star Interior Composition Explorer X-ray
Timing Instrument (NICER XTI) event data. We condition on informative pulsar
mass, distance, and orbital inclination priors derived from the joint NANOGrav
and CHIME/Pulsar wideband radio timing measurements of arXiv:2104.00880. We use
XMM European Photon Imaging Camera spectroscopic event data to inform our X-ray
likelihood function. The prior support of the pulsar radius is truncated at 16
km to ensure coverage of current dense matter models. We assume conservative
priors on instrument calibration uncertainty. We constrain the equatorial
radius and mass of PSR J0740$+$6620 to be $12.39_{-0.98}^{+1.30}$ km and
$2.072_{-0.066}^{+0.067}$ M$_{\odot}$ respectively, each reported as the
posterior credible interval bounded by the 16% and 84% quantiles, conditional
on surface hot regions that are non-overlapping spherical caps of fully-ionized
hydrogen atmosphere with uniform effective temperature; a posteriori, the
temperature is $\log_{10}(T$ [K]$)=5.99_{-0.06}^{+0.05}$ for each hot region.
All software for the X-ray modeling framework is open-source and all data,
model, and sample information is publicly available, including analysis
notebooks and model modules in the Python language. Our marginal likelihood
function of mass and equatorial radius is proportional to the marginal joint
posterior density of those parameters (within the prior support) and can thus
be computed from the posterior samples.
|
Many methods have been proposed to detect communities, not only in plain, but
also in attributed, directed or even dynamic complex networks. In its simplest
form, a community structure takes the form of a partition of the node set. From
the modeling point of view, to be of some utility, this partition must then be
characterized relatively to the properties of the studied system. However, if
most of the existing works focus on defining methods for the detection of
communities, only very few try to tackle this interpretation problem. Moreover,
the existing approaches are limited either in the type of data they handle, or
by the nature of the results they output. In this work, we propose a method to
efficiently support such a characterization task. We first define a
sequence-based representation of networks, combining temporal information,
topological measures, and nodal attributes. We then describe how to identify
the most emerging sequential patterns of this dataset, and use them to
characterize the communities. We also show how to detect unusual behavior in a
community, and highlight outliers. Finally, as an illustration, we apply our
method to a network of scientific collaborations.
|
The ``fast iterative shrinkage-thresholding algorithm'', a.k.a. FISTA, is one
of the most widely used algorithms in the literature. However, despite its
optimal theoretical $O(1/k^2)$ convergence rate guarantee, oftentimes in
practice its performance is not as desired owing to the (local) oscillatory
behaviour. Over the years, various approaches are proposed to overcome this
drawback of FISTA, in this paper, we propose a simple yet effective
modification to the algorithm which has two advantages: 1) it enables us to
prove the convergence of the generated sequence; 2) it shows superior practical
performance compared to the original FISTA. Numerical experiments are presented
to illustrate the superior performance of the proposed algorithm.
|
The interlayer exchange coupling (IEC) of two local moment ferromagnetic
layers separated by a non-magnetic spacer layer (M/N/M multilayer) is studied
using the modified RKKY method along with the s-f model. The IEC exhibits
oscillatory behaviour with respect to the spacer layer thickness and it
oscillates between ferro- and antiferromagnetic configurations. The
conventional RKKY method is also used to obtain the IEC and the results are
compared with those obtained from the modified RKKY method which incorporates
the electron correlation effects. We find significant correlation effects on
the IEC and in fact the correlations alter the nature and magnitude of the
magnetic coupling.
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Gamma-ray Bursts (GRBs) are relativistic cosmological beacons of transient
high energy radiation whose afterglows span the electromagnetic spectrum.
Theoretical expectations of correlated neutrino emission position GRBs at an
astrophysical nexus for a metamorphosis in our understanding of the Cosmos.
This new dawn in the era of experimental (particle) astrophysics and cosmology
is afforded by current facilities enabling the novel astronomy of high energy
neutrinos, in concert with unprecedented electromagnetic coverage. In that
regard, GRBs represent a compelling scientific theme that may facilitate
fundamental breakthroughs in the context of Swift, Fermi and IceCube.
Scientific synergy will be achieved by leveraging the combined sensitivity of
contemporaneous ground-based and satellite observatories, thus optimizing their
collective discovery potential. Hence, the advent of GRB multi-messenger
astronomy may cement an explicit connection to fundamental physics, via nascent
cosmic windows, throughout the next decade.
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Positron beams, both polarized and unpolarized, are identified as essential
ingredients for the experimental program at the next generation of lepton
accelerators. In the context of the Hadronic Physics program at the Jefferson
Laboratory (JLab), positron beams are complementary, even essential, tools for
a precise understanding of the electromagnetic structure of the nucleon, in
both the elastic and the deep-inelastic regimes. For instance, elastic
scattering of (un)polarized electrons and positrons off the nucleon allows for
a model independent determination of the electromagnetic form factors of the
nucleon. Also, the deeply virtual Compton scattering of (un)polarized electrons
and positrons allows us to separate unambiguously the different contributions
to the cross section of the lepto-production of photons, enabling an accurate
determination of the nucleon Generalized Parton Distributions (GPDs), and
providing an access to its Gravitational Form Factors. Furthermore, positron
beams offer the possibility of alternative tests of the Standard Model through
the search of a dark photon or the precise measurement of electroweak
couplings. This letter proposes to develop an experimental positron program at
JLab to perform unique high impact measurements with respect to the two-photon
exchange problem, the determination of the proton and the neutron GPDs, and the
search for the $A^{\prime}$ dark photon.
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This technical report presents the modeling approaches used in our submission
to the ICML Expressive Vocalizations Workshop & Competition multitask track
(ExVo-MultiTask). We first applied image classification models of various sizes
on mel-spectrogram representations of the vocal bursts, as is standard in sound
event detection literature. Results from these models show an increase of
21.24% over the baseline system with respect to the harmonic mean of the task
metrics, and comprise our team's main submission to the MultiTask track. We
then sought to characterize the headroom in the MultiTask track by applying a
large pre-trained Conformer model that previously achieved state-of-the-art
results on paralinguistic tasks like speech emotion recognition and mask
detection. We additionally investigated the relationship between the sub-tasks
of emotional expression, country of origin, and age prediction, and discovered
that the best performing models are trained as single-task models, questioning
whether the problem truly benefits from a multitask setting.
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In this paper, we focus on the pattern reconfigurable multiple-input
multiple-output (PR-MIMO), a technique that has the potential to bridge the gap
between electro-magnetics and communications towards the emerging
Electro-magnetic Information Theory (EIT). Specifically, we focus on the
pattern design problem aimed at maximizing the channel capacity for
reconfigurable MIMO communication systems, where we firstly introduce the
matrix representation of PR-MIMO and further formulate a pattern design
problem. We decompose the pattern design into two steps, i.e., the correlation
modification process to optimize the correlation structure of the channel,
followed by the power allocation process to improve the channel quality based
on the optimized channel structure. For the correlation modification process,
we propose a sequential optimization framework with eigenvalue decomposition to
obtain near-optimal solutions. For the power allocation process, we provide a
closed-form power allocation scheme to redistribute the transmission power
among the modified subchannels. Numerical results show that the proposed
pattern design scheme offers significant improvements over legacy MIMO systems,
which motivates the application of PR-MIMO in wireless communication systems.
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Due to the superiority and noteworthy progress of Quantum Computing (QC) in a
lot of applications such as cryptography, chemistry, Big data, machine
learning, optimization, Internet of Things (IoT), Blockchain, communication,
and many more. Fully towards to combine classical machine learning (ML) with
Quantum Information Processing (QIP) to build a new field in the quantum world
is called Quantum Machine Learning (QML) to solve and improve problems that
displayed in classical machine learning (e.g. time and energy consumption,
kernel estimation). The aim of this paper presents and summarizes a
comprehensive survey of the state-of-the-art advances in Quantum Machine
Learning (QML). Especially, recent QML classification works. Also, we cover
about 30 publications that are published lately in Quantum Machine Learning
(QML). we propose a classification scheme in the quantum world and discuss
encoding methods for mapping classical data to quantum data. Then, we provide
quantum subroutines and some methods of Quantum Computing (QC) in improving
performance and speed up of classical Machine Learning (ML). And also some of
QML applications in various fields, challenges, and future vision will be
presented.
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Accountability is a recent paradigm in security protocol design which aims to
eliminate traditional trust assumptions on parties and hold them accountable
for their misbehavior. It is meant to establish trust in the first place and to
recognize and react if this trust is violated. In this work, we discuss a
protocol agnostic definition of accountability: a protocol provides
accountability (w.r.t. some security property) if it can identify all
misbehaving parties, where misbehavior is defined as a deviation from the
protocol that causes a security violation. We provide a mechanized method for
the verification of accountability and demonstrate its use for verification and
attack finding on various examples from the accountability and causality
literature, including Certificate Transparency and Kroll Accountable Algorithms
protocol. We reach a high degree of automation by expressing accountability in
terms of a set of trace properties and show their soundness and completeness.
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We construct new M-theory solutions of M5 branes that are a realization of
the fully localized ten dimensional NS5/D6 and NS5/D5 brane intersections.
These solutions are obtained by embedding self-dual geometries lifted to
M-theory. We reduce these solutions down to ten dimensions, obtaining new
D-brane systems in type IIA/IIB supergravity. The worldvolume theories of the
NS5-branes are new non-local, non-gravitational, six dimensional, T-dual little
string theories with eight supersymmetries.
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The relative velocity between baryons and dark matter in the early Universe
can suppress the formation of small-scale baryonic structure and leave an
imprint on the baryon acoustic oscillation (BAO) scale at low redshifts after
reionization. This "streaming velocity" affects the post-reionization gas
distribution by directly reducing the abundance of pre-existing mini-halos
($\lesssim 10^7 M_{\bigodot}$) that could be destroyed by reionization and
indirectly modulating reionization history via photoionization within these
mini-halos. In this work, we investigate the effect of streaming velocity on
the BAO feature in HI 21 cm intensity mapping after reionization, with a focus
on redshifts $3.5\lesssim z\lesssim5.5$. We build a spatially modulated halo
model that includes the dependence of the filtering mass on the local
reionization redshift and thermal history of the intergalactic gas. In our
fiducial model, we find isotropic streaming velocity bias coefficients $b_v$
ranging from $-0.0043$ at $z=3.5$ to $-0.0273$ at $z=5.5$, which indicates that
the BAO scale is stretched (i.e., the peaks shift to lower $k$). In particular,
streaming velocity shifts the transverse BAO scale between 0.121% ($z=3.5$) and
0.35% ($z=5.5$) and shifts the radial BAO scale between 0.167% ($z=3.5$) and
0.505% ($z=5.5$). These shifts exceed the projected error bars from the more
ambitious proposed hemispherical-scale surveys in HI (0.13% at $1\sigma$ per
$\Delta z = 0.5$ bin).
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Any finite state automaton gives rise to a Boolean one-dimensional TQFT with
defects and inner endpoints of cobordisms. This paper extends the
correspondence to Boolean TQFTs where defects accumulate toward inner
endpoints, relating such TQFTs and topological theories to sofic systems and
$\omega$-automata.
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In the real world, documents are organized in different formats and varied
modalities. Traditional retrieval pipelines require tailored document parsing
techniques and content extraction modules to prepare input for indexing. This
process is tedious, prone to errors, and has information loss. To this end, we
propose Document Screenshot Embedding} (DSE), a novel retrieval paradigm that
regards document screenshots as a unified input format, which does not require
any content extraction preprocess and preserves all the information in a
document (e.g., text, image and layout). DSE leverages a large vision-language
model to directly encode document screenshots into dense representations for
retrieval. To evaluate our method, we first craft the dataset of Wiki-SS, a
1.3M Wikipedia web page screenshots as the corpus to answer the questions from
the Natural Questions dataset. In such a text-intensive document retrieval
setting, DSE shows competitive effectiveness compared to other text retrieval
methods relying on parsing. For example, DSE outperforms BM25 by 17 points in
top-1 retrieval accuracy. Additionally, in a mixed-modality task of slide
retrieval, DSE significantly outperforms OCR text retrieval methods by over 15
points in nDCG@10. These experiments show that DSE is an effective document
retrieval paradigm for diverse types of documents. Model checkpoints, code, and
Wiki-SS collection will be released.
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We analyze the structure of the set of limiting Carleman weights in all
conformally flat manifolds, 3-manifolds, and 4-manifolds. In particular we give
a new proof of the classification of Euclidean limiting Carleman weights, and
show that there are only three basic such weights up to the action of the
conformal group. In dimension three we show that if the manifold is not
conformally flat, there could be one or two limiting Carleman weights. We also
characterize the metrics that have more than one limiting Carleman weight. In
dimension four we obtain a complete spectrum of examples according to the
structure of the Weyl tensor. In particular, we construct unimodular Lie groups
whose Weyl or Cotton-York tensors have the symmetries of conformally
transversally anisotropic manifolds, but which do not admit limiting Carleman
weights.
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One of the most difficult problems difficult problem in systems biology is to
discover protein-protein interactions as well as their associated functions.
The analysis and alignment of protein-protein interaction networks (PPIN),
which are the standard model to describe protein-protein interactions, has
become a key ingredient to obtain functional orthologs as well as evolutionary
conserved pathways and protein complexes. Several methods have been proposed to
solve the PPIN alignment problem, aimed to match conserved subnetworks or
functionally related proteins. However, the right balance between considering
network topology and biological information is one of the most difficult and
key points in any PPIN alignment algorithm which, unfortunately, remains
unsolved. Therefore, in this work, we propose AligNet, a new method and
software tool for the pairwise global alignment of PPIN that produces
biologically meaningful alignments and more efficient computations than
state-of-the-art methods and tools, by achieving a good balance between
structural matching and protein function conservation as well as reasonable
running times.
|
A set $A$ is an $(r,\ell)$-approximate group in the additive abelian group
$G$ if $A$ is a nonempty subset of $G$ and there exists a subset $X$ of $G$
such that $|X| \leq \ell$ and $rA \subseteq X+A$. The set $A$ is an asymptotic
$(r,\ell)$-approximate group if the sumset $hA$ is an $(r,\ell)$-approximate
group for all sufficiently large integers $h$. It is proved that every finite
set of integers is an asymptotic $(r,r+1)$-approximate group for every integer
$r \geq 2$.
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Coloring is used in wireless networks to improve communication efficiency,
mainly in terms of bandwidth, energy and possibly end-to-end delays. In this
paper, we define the h-hop node coloring problem, with h any positive integer,
adapted to two types of applications in wireless networks. We specify both
general mode for general applications and strategic mode for data gathering
applications.We prove that the associated decision problem is NP-complete. We
then focus on grid topologies that constitute regular topologies for large or
dense wireless networks. We consider various transmission ranges and identify a
color pattern that can be reproduced to color the whole grid with the optimal
number of colors. We obtain an optimal periodic coloring of the grid for the
considered transmission range. We then present a 3-hop distributed coloring
algorithm, called SERENA. Through simulation results, we highlight the impact
of node priority assignment on the number of colors obtained for any network
and grids in particular. We then compare these optimal results on grids with
those obtained by SERENA and identify directions to improve SERENA.
|
Existing research on music recommendation systems primarily focuses on
recommending similar music, thereby often neglecting diverse and distinctive
musical recordings. Musical outliers can provide valuable insights due to the
inherent diversity of music itself. In this paper, we explore music outliers,
investigating their potential usefulness for music discovery and recommendation
systems. We argue that not all outliers should be treated as noise, as they can
offer interesting perspectives and contribute to a richer understanding of an
artist's work. We introduce the concept of 'Genuine' music outliers and provide
a definition for them. These genuine outliers can reveal unique aspects of an
artist's repertoire and hold the potential to enhance music discovery by
exposing listeners to novel and diverse musical experiences.
|
This paper introduces the notion of a Galois point for a finite graph, using
the theory of linear systems of divisors for graphs discovered by Baker and
Norine. We present a new characterization of complete graphs in terms of Galois
points.
|
In both natural and engineered systems, communication often occurs
dynamically over networks ranging from highly structured grids to largely
disordered graphs. To use, or comprehend the use of, networks as efficient
communication media requires understanding of how they propagate and transform
information in the face of noise. Here, we develop a framework that enables us
to examine how network structure, noise, and interference between consecutive
packets jointly determine transmission performance in networks with linear
dynamics at single nodes and arbitrary topologies. Mathematically normal
networks, which can be decomposed into separate low-dimensional information
channels, suffer greatly from readout and interference noise. Interestingly,
most details of their wiring have no impact on transmission quality. Non-normal
networks, however, can largely cancel the effect of noise by transiently
amplifying select input dimensions while ignoring others, resulting in higher
net information throughput. Our theory could inform the design of new
communication networks, as well as the optimal use of existing ones.
|
Facial action units (AUs) recognition is essential for emotion analysis and
has been widely applied in mental state analysis. Existing work on AU
recognition usually requires big face dataset with AU labels; however, manual
AU annotation requires expertise and can be time-consuming. In this work, we
propose a semi-supervised approach for AU recognition utilizing a large number
of web face images without AU labels and a relatively small face dataset with
AU annotations inspired by the co-training methods. Unlike traditional
co-training methods that require provided multi-view features and model
re-training, we propose a novel co-training method, namely multi-label
co-regularization, for semi-supervised facial AU recognition. Two deep neural
networks are utilized to generate multi-view features for both labeled and
unlabeled face images, and a multi-view loss is designed to enforce the two
feature generators to get conditional independent representations. In order to
constrain the prediction consistency of the two views, we further propose a
multi-label co-regularization loss by minimizing the distance of the predicted
AU probability distributions of two views. In addition, prior knowledge of the
relationship between individual AUs is embedded through a graph convolutional
network (GCN) for exploiting useful information from the big unlabeled dataset.
Experiments on several benchmarks show that the proposed approach can
effectively leverage large datasets of face images without AU labels to improve
the AU recognition accuracy and outperform the state-of-the-art semi-supervised
AU recognition methods.
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Web portals are nowadays very popular. This type of web sites let users to
share information, request advice or help in a particular field, and
furthermore allow them to create and extend sites content. Combined with
instant messaging systems, used to send messages or files instantaneously to a
user or a group of users, and with various kinds of chat programs, which
connect two or more individuals simulating a conversation, it is now possible
to create "web communities". In this paper we present the opensource tools used
to create the "Grid Support Community" of the National Institute for Nuclear
Physics in Italy.
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This paper addresses the problem that designing the transmit waveform and
receive beamformer aims to maximize the receive radar SINR for secure
dual-functional radar-communication (DFRC) systems, where the undesired
multi-user interference (MUI) is transformed to useful power. In this system,
the DFRC base station (BS) serves communication users (CUs) and detects the
target simultaneously, where the radar target is regarded to be malicious since
it might eavesdrop the transmitted information from BS to CUs. Inspired by the
constructive interference (CI) approach, the phases of received signals at CUs
are rotated into the relaxed decision region, and the undesired MUI is designed
to contribute in useful power. Then, the convex approximation method (SCA) is
adopted to tackle the optimization problem. Finally, numerical results are
given to validate the effectiveness of the proposed method, which shows that it
is viable to ensure the communication data secure adopting the techniques that
we propose.
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We study the problem of the existence of unconditional basic sequences in
Banach spaces of high density. We show, in particular, the relative consistency
with GCH of the statement that every Banach space of density $\aleph_\omega$
contains an unconditional basic sequence.
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By using the inverse spectral transform, the SRS equations are solved and the
explicit output data is given for arbitrary laser pump and Stokes seed profiles
injected on a vacuum of optical phonons. For long duration laser pulses, this
solution is modified such as to take into account the damping rate of the
optical phonon wave. This model is used to interprete the experiments of Druhl,
Wenzel and Carlsten (Phys. Rev. Lett., (1983) vol. 51, p. 1171), in particular
the creation of a spike of (anomalous) pump radiation. The related nonlinear
Fourier spectrum does not contain discrete eigenvalue, hence this Raman spike
is not a soliton.
|
We consider the problem of inferring the causal structure from observational
data, especially when the structure is sparse. This type of problem is usually
formulated as an inference of a directed acyclic graph (DAG) model. The linear
non-Gaussian acyclic model (LiNGAM) is one of the most successful DAG models,
and various estimation methods have been developed. However, existing methods
are not efficient for some reasons: (i) the sparse structure is not always
incorporated in causal order estimation, and (ii) the whole information of the
data is not used in parameter estimation. To address {these issues}, we propose
a new estimation method for a linear DAG model with non-Gaussian noises. The
proposed method is based on the log-likelihood of independent component
analysis (ICA) with two penalty terms related to the sparsity and the
consistency condition. The proposed method enables us to estimate the causal
order and the parameters simultaneously. For stable and efficient optimization,
we propose some devices, such as a modified natural gradient. Numerical
experiments show that the proposed method outperforms existing methods,
including LiNGAM and NOTEARS.
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Let G be a finitely generated discrete group. In this paper we establish
vanishing results for rho-invariants associated to
(i) the spin-Dirac operator of a spin manifold with positive scalar curvature
(ii) the signature operator of the disjoint union of a pair of homotopy
equivalent oriented manifolds with fundamental group G.
The invariants we consider are more precisely
- the Atiyah-Patodi-Singer rho-invariant associated to a pair of finite
dimensional unitary representations.
- the L2-rho invariant of Cheeger-Gromov
- the delocalized eta invariant of Lott for a finite conjugacy class of G.
We prove that all these rho-invariants vanish if the group G is torsion-free
and the Baum-Connes map for the maximal group C^*-algebra is bijective. For the
delocalized invariant we only assume the validity of the Baum-Connes conjecture
for the reduced C^*-algebra.
In particular, the three rho-invariants associated to the signature operator
are, for such groups, homotopy invariant. For the APS and the Cheeger-Gromov
rho-invariants the latter result had been established by Navin Keswani. Our
proof re-establishes this result and also extends it to the delocalized
eta-invariant of Lott. Our method also gives some information about the
eta-invariant itself (a much more saddle object than the rho-invariant).
|
We calculate the phase diagram of the SU($N$) Hubbard model describing
fermionic alkaline earth atoms in a square optical lattice with on-average one
atom per site, using a slave-rotor mean-field approximation. We find that the
chiral spin liquid predicted for $N\ge5$ and large interactions passes through
a fractionalized state with a spinon Fermi surface as interactions are
decreased before transitioning to a weakly interacting metal. We also show that
by adding an artificial uniform magnetic field with flux per plaquette
$2\pi/N$, the chiral spin liquid becomes the ground state for all $N\ge 3$ at
large interactions, persists to weaker interactions, and its spin gap
increases, suggesting that the spin liquid physics will persist to higher
temperatures. We discuss potential methods to realize the artificial gauge
fields and detect the predicted phases.
|
Rod bundle flows are commonplace in nuclear engineering, and are present in
light water reactors (LWRs) as well as other more advanced concepts.
Inhomogeneities in the bundle cross section can lead to complex flow phenomena,
including varying local conditions of turbulence. Despite the decades of
numerical and experimental investigations regarding this topic, and the
importance of elucidating the physics of the flow field, to date there are few
publicly available direct numerical simulations (DNS) of the flow in
multiple-pin rod bundles. Thus a multiple-pin DNS study can provide significant
value toward reaching a deeper understanding of the flow physics, as well as a
reference simulation for development of various reduced-resolution analysis
techniques. To this end, DNS of the flow in a square 5x5 rod bundle at Reynolds
number of 19,000 has been performed using the highly-parallel spectral element
code Nek5000. The geometrical dimensions were representative of typical LWR
fuel designs. The DNS was designed using microscales estimated from an advanced
Reynolds-Averaged Navier-Stokes (RANS) model. Characteristics of the velocity
field, Reynolds stresses, and anisotropy are presented in detail for various
regions of the bundle. The turbulent kinetic energy budget is also presented
and discussed
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We introduce new families of pure quantum states that are constructed on top
of the well-known Gilmore-Perelomov group-theoretic coherent states. We do this
by constructing unitaries as the exponential of operators quadratic in Cartan
subalgebra elements and by applying these unitaries to regular group-theoretic
coherent states. This enables us to generate entanglement not found in the
coherent states themselves, while retaining many of their desirable properties.
Most importantly, we explain how the expectation values of physical observables
can be evaluated efficiently. Examples include generalized spin-coherent states
and generalized Gaussian states, but our construction can be applied to any Lie
group represented on the Hilbert space of a quantum system. We comment on their
applicability as variational families in condensed matter physics and quantum
information.
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Automating enterprise workflows could unlock $4 trillion/year in productivity
gains. Despite being of interest to the data management community for decades,
the ultimate vision of end-to-end workflow automation has remained elusive.
Current solutions rely on process mining and robotic process automation (RPA),
in which a bot is hard-coded to follow a set of predefined rules for completing
a workflow. Through case studies of a hospital and large B2B enterprise, we
find that the adoption of RPA has been inhibited by high set-up costs (12-18
months), unreliable execution (60% initial accuracy), and burdensome
maintenance (requiring multiple FTEs). Multimodal foundation models (FMs) such
as GPT-4 offer a promising new approach for end-to-end workflow automation
given their generalized reasoning and planning abilities. To study these
capabilities we propose ECLAIR, a system to automate enterprise workflows with
minimal human supervision. We conduct initial experiments showing that
multimodal FMs can address the limitations of traditional RPA with (1)
near-human-level understanding of workflows (93% accuracy on a workflow
understanding task) and (2) instant set-up with minimal technical barrier
(based solely on a natural language description of a workflow, ECLAIR achieves
end-to-end completion rates of 40%). We identify human-AI collaboration,
validation, and self-improvement as open challenges, and suggest ways they can
be solved with data management techniques. Code is available at:
https://github.com/HazyResearch/eclair-agents
|
Two prominent methods for integer factorization are those based on general
integer sieve and elliptic curve. The general integer sieve method can be
specialized to quadratic integer sieve method. In this paper, a probability
analysis for the success of these methods is described, under some reasonable
conditions. The estimates presented are specialized for the elliptic curve
factorization. These methods are compared through heuristic estimates. It is
shown that the elliptic curve method is a probabilistic polynomial time
algorithm under the assumption of uniform probability distribution for the
arising group orders and clearly more likely to succeed, faster asymptotically.
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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.