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Multi-frequency matched filters (MMFs) are routinely used to detect galaxy
clusters from CMB data through the thermal Sunyaev-Zeldovich (tSZ) effect,
leading to cluster catalogues that can be used for cosmological inference. In
order to be applied, MMFs require knowledge of the cross-frequency power
spectra of the noise in the maps. This is typically estimated from the data and
taken to be equal to the power spectra of the data, assuming the contribution
from the tSZ signal of the detections to be negligible. Using both analytical
arguments and \textit{Planck}-like mock observations, we show that doing so
causes the MMF noise to be overestimated, inducing a loss of signal-to-noise.
Furthermore, the MMF cluster observable (the amplitude $\hat{y}_0$ or the
signal-to-noise $q$) does not behave as expected, which can potentially bias
cosmological inference. In particular, the observable becomes biased with
respect to its theoretical prediction and displays a variance that also differs
from its predicted value. We propose an iterative MMF (iMMF) approach designed
to mitigate these effects. In this approach, after a first standard MMF step,
the noise power spectra are reestimated by masking the detections from the
data, delivering an updated iterative cluster catalogue. Applying our iMMF to
our \textit{Planck}-like mock observations, we find that the aforementioned
effects are completely suppressed. This leads to a signal-to-noise gain
relative to the standard MMF, with more significant detections and a higher
number of them, and to a cluster observable with the expected theoretical
properties, thus eliminating any potential biases in the cosmological
constraints.
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A selfcontained proof of the KAM theorem in the Thirring model is discussed.
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The possibility for detuned spins to display synchronous oscillations in
local observables is analyzed in the presence of collective dissipation and
incoherent pumping. We show that there exist two distinct mechanisms that can
give rise to synchronization, that is, non-degenerate subradiance and
coalescence. The former, known as transient synchronization, is here
generalized in the presence of pumping. It is due to long-lasting coherences
leading to a progressive frequency selection. In the same set-up, even if under
different conditions, coalescence and exceptional points are found which can
lead to regimes where a single oscillation frequency is present in the relevant
quantities. Still, we show that synchronization can be established only after
steady phase-locking occurs. Distinctive spectral features of synchronization
by these two different mechanisms are reported for two-time correlations.
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Graphical representations of classical Friedmann's models are often
misleading when one considers the age of the universe. Most textbooks disregard
conceptual differences in the representations, as far as ages are concerned. We
discuss the details of the scale-factor versus time function for Friedmann's
solutions in the time range that includes the ages of model universes.
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Topology establishes a unifying framework for a diverse range of scientific
areas including particle physics, cosmology, and condensed matter physics. One
of the most fascinating manifestations of topology in the context of condensed
matter is the topological Hall effect, and its relative: the Skyrmion Hall
effect. Skyrmions are stable vortex-like spin configurations in certain chiral
magnets, and when subject to external electric currents can drift in the
transverse direction to the current. These quasi-particles are characterised by
a conserved topological charge which in the Skyrmion Hall effect plays the role
of electric charges in the ordinary Hall effect. Recently, it has been shown
that liquid crystals endowed with chiral properties serve as an ideal testbed
for the fundamental investigation of topological solitons, including their two-
and three-dimensional realisations. Here, we show experimentally and
numerically that three-dimensional solitons aka "torons" exhibit a Hall-like
effect when driven by shear flows: the torons are deflected in the direction
perpendicular to the shear plane. The experimental results are rationalised in
terms of the dynamic Ericksen-Leslie equations, which predict the emergence of
the transverse component of the net mass flow, the magnitude of which scales as
the 3rd power of the shear rate. The perturbation analysis highlights an
interplay of the viscous and chiral elastic torques as the mechanism for the
emergence of net transverse currents. Numerical simulations demonstrate,
however, that torons are not merely dragged by the flow but move with their own
transverse speed, much larger than the average flow velocity in the transverse
direction. Our findings may enable responsive microfluidic applications relying
on soft topological solitons.
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This paper identifies the homotopy theories of topological stacks and
orbispaces with unstable global homotopy theory. At the same time, we provide a
new perspective by interpreting it as the homotopy theory of `spaces with an
action of the universal compact Lie group'. The upshot is a novel way to
construct and study genuine cohomology theories on stacks, orbifolds, and
orbispaces, defined from stable global homotopy types represented by orthogonal
spectra.
The universal compact Lie group (which is neither compact nor a Lie group) is
a well known object, namely the topological monoid $\mathcal L$ of linear
isometric self-embeddings of $\mathbb R^\infty$. The underlying space of
$\mathcal L$ is contractible, and the homotopy theory of $\mathcal L$-spaces
with respect to underlying weak equivalences is just another model for the
homotopy theory of spaces. However, the monoid $\mathcal L$ contains copies of
all compact Lie groups in a specific way, and we define global equivalences of
$\mathcal L$-spaces by testing on corresponding fixed points. We establish a
global model structure on the category of $\mathcal L$-spaces and prove it to
be Quillen equivalent to the global model category of orthogonal spaces, and to
the category of orbispaces, i.e., presheaves of spaces on the global orbit
category.
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We propose a monotonic logic of internalised non-monotonic or instant
interactive proofs (LiiP) and reconstruct an existing monotonic logic of
internalised monotonic or persistent interactive proofs (LiP) as a minimal
conservative extension of LiiP. Instant interactive proofs effect a fragile
epistemic impact in their intended communities of peer reviewers that consists
in the impermanent induction of the knowledge of their proof goal by means of
the knowledge of the proof with the interpreting reviewer: If my peer reviewer
knew my proof then she would at least then (in that instant) know that its
proof goal is true. Their impact is fragile and their induction of knowledge
impermanent in the sense of being the case possibly only at the instant of
learning the proof. This accounts for the important possibility of
internalising proofs of statements whose truth value can vary, which, as
opposed to invariant statements, cannot have persistent proofs. So instant
interactive proofs effect a temporary transfer of certain propositional
knowledge (knowable ephemeral facts) via the transmission of certain individual
knowledge (knowable non-monotonic proofs) in distributed systems of multiple
interacting agents.
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A short review is given of the simplified differential equations approach to
Master Integrals, which was recently proposed by one of the authors. We show
its applicability by calculating some non-trivial two-loop planar Master
Integrals, namely those contributing to amplitudes of massive diboson VV'
production at the LHC with massless internal lines.
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Feature transformation aims to reconstruct an effective representation space
by mathematically refining the existing features. It serves as a pivotal
approach to combat the curse of dimensionality, enhance model generalization,
mitigate data sparsity, and extend the applicability of classical models.
Existing research predominantly focuses on domain knowledge-based feature
engineering or learning latent representations. However, these methods, while
insightful, lack full automation and fail to yield a traceable and optimal
representation space. An indispensable question arises: Can we concurrently
address these limitations when reconstructing a feature space for a
machine-learning task? Our initial work took a pioneering step towards this
challenge by introducing a novel self-optimizing framework. This framework
leverages the power of three cascading reinforced agents to automatically
select candidate features and operations for generating improved feature
transformation combinations. Despite the impressive strides made, there was
room for enhancing its effectiveness and generalization capability. In this
extended journal version, we advance our initial work from two distinct yet
interconnected perspectives: 1) We propose a refinement of the original
framework, which integrates a graph-based state representation method to
capture the feature interactions more effectively and develop different
Q-learning strategies to alleviate Q-value overestimation further. 2) We
utilize a new optimization technique (actor-critic) to train the entire
self-optimizing framework in order to accelerate the model convergence and
improve the feature transformation performance. Finally, to validate the
improved effectiveness and generalization capability of our framework, we
perform extensive experiments and conduct comprehensive analyses.
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We provide an integral formula for the Maslov index of a pair $(E,F)$ over a
surface $\Sigma$, where $E\rightarrow\Sigma$ is a complex vector bundle and
$F\subset E_{|\partial\Sigma}$ is a totally real subbundle. As in Chern-Weil
theory, this formula is written in terms of the curvature of $E$ plus a
boundary contribution.
When $(E,F)$ is obtained via an immersion of $(\Sigma,\partial\Sigma)$ into a
pair $(M,L)$ where $M$ is K\"ahler and $L$ is totally real, the formula allows
us to control the Maslov index in terms of the geometry of $(M,L)$. We exhibit
natural conditions on $(M,L)$ which lead to bounds and monotonicity results.
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Here, we report the unusual behaviour shown by the (BiFeO3)1-x-(PbTiO3)x
(BF-xPT) films prepared using a multilayer deposition approach by chemical
solution deposition method. Thin film samples of various compositions were
prepared by depositing several bilayers of BF and PT precursors by varying the
BF or PT layer thicknesses. X-ray diffraction showed that final samples of all
compositions show mixing of the two compounds resulting in a single phase
mixture, also confirmed by transmission electron microscopy. In contrast to
bulk equilibrium compositions, our samples show a monoclinic (MA type)
structure suggesting disappearance of morphotropic phase boundary (MPB) about x
= 0.30 as observed in the bulk. This is accompanied by the lack of any
enhancement of remnant polarization at MPB as shown by the ferroelectric
measurements. Magnetic measurements show that the magnetization of the samples
increases with increasing BF content. Significant magnetization of the samples
indicates melting of spin spirals in the BF-xPT arising from random
distribution of iron atoms across the film. Absence of Fe2+ ions in the films
was corroborated by X-ray photoelectron spectroscopy measurements. The results
illustrate that used thin film processing methodology significantly changes the
structural evolution in contrast to predictions from the equilibrium phase
diagram as well as modify the functional characteristics of BP-xPT system
dramatically.
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In previous work, we presented a novel information-theoretic privacy
criterion for query forgery in the domain of information retrieval. Our
criterion measured privacy risk as a divergence between the user's and the
population's query distribution, and contemplated the entropy of the user's
distribution as a particular case. In this work, we make a twofold
contribution. First, we thoroughly interpret and justify the privacy metric
proposed in our previous work, elaborating on the intimate connection between
the celebrated method of entropy maximization and the use of entropies and
divergences as measures of privacy. Secondly, we attempt to bridge the gap
between the privacy and the information-theoretic communities by substantially
adapting some technicalities of our original work to reach a wider audience,
not intimately familiar with information theory and the method of types.
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We introduce a new technique to calculate perturbative corrections to
neutron-deuteron ($nd$) scattering that does not require calculation of the
full off-shell scattering amplitude. Its relation to the more familiar
partial-resummation technique is explained. Also included is a calculation of
the SD-mixing term that occurs at next-to-next-to-leading-order (NNLO) in
pionless effective field theory $\mathrm{EFT}_{\not{\pi}}$\xspace. Using the
new technique with the SD-mixing term a complete strictly perturbative
phase-shift analysis of $nd$ scattering is performed up to NNLO including
eigen-phases and mixing angles. This is compared to potential model
calculations and good agreement is found with the eigen-phases and some of the
mixing angles at low energies.
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We analyze the long-time evolution of open quantum many-body systems using a
variational approach. For the dissipative Ising model, where mean-field theory
predicts a wide region of bistable behavior, we find genuine bistability only
at a singular point, confirming the previously suggested picture of a first
order transition. The situation is dramatically different when considering a
majority-voter model including three-body interactions, where we find bistable
behavior in an extended region, owing to the breaking of detailed balance in
the the effective description of the system. In this model, genuine bistability
persists even when quantum fluctuations are added.
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In this comment on "The Markov blanket trick: On the scope of the free energy
principle and active inference" by Raja and colleagues (2021) in Physics of
Life Reviews, I argue that the argument presented by the authors is valid;
however, I claim that the argument contains a flawed premise, which undermines
their conclusions. In addition, I argue that work on the FEP that has appeared
since the target paper was published underwrites a cogent response to the
issues that are raised by Raja and colleagues.
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Tutte initiated the study of nowhere-zero flows and proved the following
fundamental theorem: For every graph $G$ there is a polynomial $f$ so that for
every abelian group $\Gamma$ of order $n$, the number of nowhere-zero
$\Gamma$-flows in $G$ is $f(n)$. For signed graphs (which have bidirected
orientations), the situation is more subtle. For a finite group $\Gamma$, let
$\epsilon_2(\Gamma)$ be the largest integer $d$ so that $\Gamma$ has a subgroup
isomorphic to $\mathbb{Z}_2^d$. We prove that for every signed graph $G$ and $d
\ge 0$ there is a polynomial $f_d$ so that $f_d(n)$ is the number of
nowhere-zero $\Gamma$-flows in $G$ for every abelian group $\Gamma$ with
$\epsilon_2(\Gamma) = d$ and $|\Gamma| = 2^d n$. Beck and Zaslavsky had
previously established the special case of this result when $d=0$ (i.e., when
$\Gamma$ has odd order).
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We study how the presence of world-sheet currents affects the evolution of
cosmic string networks, and their impact on predictions for the cosmic
microwave background (CMB) anisotropies generated by these networks. We provide
a general description of string networks with currents and explicitly
investigate in detail two physically motivated examples: wiggly and
superconducting cosmic string networks. By using a modified version of the
CMBact code, we show quantitatively how the relevant network parameters in both
of these cases influence the predicted CMB signal. Our analysis suggests that
previous studies have overestimated the amplitude of the anisotropies for
wiggly strings. For superconducting strings the amplitude of the anisotropies
depends on parameters which presently are not well known - but which can be
measured in future high-resolution numerical simulations.
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The periodic standing wave approach to binary inspiral assumes rigid rotation
of gravitational fields and hence helically symmetric solutions. To exploit the
symmetry, numerical computations must solve for ``helical scalars,'' fields
that are functions only of corotating coordinates, the labels on the helical
Killing trajectories. Here we present the formalism for describing linearized
general relativity in terms of helical scalars and we present solutions to the
mixed partial differential equations of the linearized gravity problem (and to
a toy nonlinear problem) using the adapted coordinates and numerical techniques
previously developed for scalar periodic standing wave computations. We argue
that the formalism developed may suffice for periodic standing wave
computations for post-Minkowskian computations and for full general relativity.
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We present the galaxy luminosity function (LF) of the Abell 119 cluster down
to $M_r\sim-14$ mag based on deep images in the $u$-, $g$-, and $r$-bands taken
by using MOSAIC II CCD mounted on the Blanco 4m telescope at the CTIO. The
cluster membership was accurately determined based on the radial velocity
information as well as on the color-magnitude relation for bright galaxies and
the scaling relation for faint galaxies. The overall LF exhibits a bimodal
behavior with a distinct dip at $r\sim18.5$ mag ($M_r\sim-17.8$ mag), which is
more appropriately described by a two-component function. The shape of the LF
strongly depends on the cluster-centric distance and on the local galaxy
density. The LF of galaxies in the outer, low-density region exhibits a steeper
slope and more prominent dip compared with that of counterparts in the inner,
high-density region. We found evidence for a substructure in the projected
galaxy distribution in which several overdense regions in the Abell 119 cluster
appear to be closely associated with the surrounding, possible filamentary
structure. The combined LF of the overdense regions exhibits a two-component
function with a distinct dip, while the LF of the central region is well
described by a single Schechter function. We suggest that, in the context of
the hierarchical cluster formation scenario, the observed overdense regions are
the relics of galaxy groups, retaining their two-component LFs with a dip,
which acquired their shapes through galaxy merging process in group
environments, before they fall into a cluster.
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We introduce Inference-Time Intervention (ITI), a technique designed to
enhance the "truthfulness" of large language models (LLMs). ITI operates by
shifting model activations during inference, following a set of directions
across a limited number of attention heads. This intervention significantly
improves the performance of LLaMA models on the TruthfulQA benchmark. On an
instruction-finetuned LLaMA called Alpaca, ITI improves its truthfulness from
32.5% to 65.1%. We identify a tradeoff between truthfulness and helpfulness and
demonstrate how to balance it by tuning the intervention strength. ITI is
minimally invasive and computationally inexpensive. Moreover, the technique is
data efficient: while approaches like RLHF require extensive annotations, ITI
locates truthful directions using only few hundred examples. Our findings
suggest that LLMs may have an internal representation of the likelihood of
something being true, even as they produce falsehoods on the surface.
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We present the effect of adapting to human preferences on trust in a
human-robot teaming task. The team performs a task in which the robot acts as
an action recommender to the human. It is assumed that the behavior of the
human and the robot is based on some reward function they try to optimize. We
use a new human trust-behavior model that enables the robot to learn and adapt
to the human's preferences in real-time during their interaction using Bayesian
Inverse Reinforcement Learning. We present three strategies for the robot to
interact with a human: a non-learner strategy, in which the robot assumes that
the human's reward function is the same as the robot's, a non-adaptive learner
strategy that learns the human's reward function for performance estimation,
but still optimizes its own reward function, and an adaptive-learner strategy
that learns the human's reward function for performance estimation and also
optimizes this learned reward function. Results show that adapting to the
human's reward function results in the highest trust in the robot.
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The angular momentum of galaxies is routinely ascribed to a process of tidal
torques acting during the early stages of gravitational collapse, and is
predicted from the initial mass distribution using second-order perturbation
theory and the Zel'dovich approximation. We have tested this theory for a flat
hierarchical cosmogony using a large N-body simulation with sufficient dynamic
range to include tidal fields, allow resolution of individual galaxies, and
thereby expand on previous studies. We find relatively good correlation between
the predictions of linear theory and actual galaxy evolution. While structure
formation from early times is a complex history of hierarchical merging,
salient features are well described by the simple spherical-collapse model.
Most notably, we test several methods for determining the turnaround epoch, and
find that turnaround is succesfully described by the spherical collapse model.
The angular momentum of collapsing structures grows linearly until turnaround,
as predicted, and continues quasi-linearly until shell crossing. The predicted
angular momentum for well-resolved galaxies at turnaround overestimates the
true turnaround and final values by a factor of ~3 with a scatter of ~70
percent, and only marginally yields the correct direction of the angular
momentum vector. We recover the prediction that final angular momentum scales
as mass to the 5/3 power. We find that mass and angular momentum also vary
proportionally with peak height.
|
We consider three-dimensional gravity based on torsion. Specifically, we
consider an extension of the so-called Teleparallel Equivalent of General
Relativity in the presence of a scalar field with a self-interacting potential,
where the scalar field is non-minimally coupled with the torsion scalar. Then,
we find asymptotically AdS hairy black hole solutions, which are characterized
by a scalar field with a power-law behavior, being regular outside the event
horizon and null at spatial infinity and by a self-interacting potential, which
tends to an effective cosmological constant at spatial infinity.
|
Reed showed that, if two graphs are $P_4$-isomorphic, then either both are
perfect or none of them is. In this note we will derive an analogous result for
perfect digraphs.
|
We investigate a spin-boson model with two boson baths that are coupled to
two perpendicular components of the spin by employing the density matrix
renormalization group method with an optimized boson basis. It is revealed that
in the deep sub-Ohmic regime there exists a novel second-order phase transition
between two types of doubly degenerate states, which is reduced to one of the
usual type for nonzero tunneling. In addition, it is found that expectation
values of the spin components display jumps at the phase boundary in the
absence of bias and tunneling.
|
We investigate the nonequilibrium dynamics of spherical active Brownian
particles in three spatial dimensions that interact via a pair potential. The
investigation is based on a predictive local field theory that is derived by a
rigorous coarse-graining starting from the overdamped Langevin dynamics of the
particles. This field theory is highly accurate and applicable even for the
highest activities. It includes configurational order parameters and
derivatives up to infinite orders. We present also three finite reduced models
that result from the general field theory by suitable approximations and are
easier to apply. Furthermore, we use the general field theory and the simplest
one of the reduced models to derive analytic expressions for the
density-dependent mean swimming speed and the spinodal corresponding to the
onset of motility-induced phase separation of the particles, respectively. Both
of these results show a good agreement with recent findings described in the
literature. The analytic result for the spinodal yields also a prediction for
the associated critical point whose position has not been determined before.
|
Multi-frequency radio polarimetric observations of the diffuse Galactic
synchrotron background enable us to study the structure of the diffuse ionized
gas via rotation measure maps. However, depolarization will introduce artifacts
in the resulting rotation measure, most notably in the form of narrow,
elongated ``depolarization canals''. We use numerical models of a non-emitting
Faraday rotating medium to study the RM distribution needed to create
depolarization canals by depolarization due to a finite beam width, and to
estimate the influence of this depolarization mechanism on the determination of
RM. We argue that the depolarization canals indeed can be caused by beam
depolarization, which in turn is a natural consequence when observing a
turbulent medium with limited resolution. Furthermore, we estimate that beam
depolarization can induce an additional error of about 20% in RM
determinations, and considerably less in regions that are not affected by
depolarization canals.
|
This paper explores the recently proposed Graph Convolutional Network
architecture proposed in (Kipf & Welling, 2016) The key points of their work is
summarized and their results are reproduced. Graph regularization and
alternative graph convolution approaches are explored. I find that explicit
graph regularization was correctly rejected by (Kipf & Welling, 2016). I
attempt to improve the performance of GCN by approximating a k-step transition
matrix in place of the normalized graph laplacian, but I fail to find positive
results. Nonetheless, the performance of several configurations of this GCN
variation is shown for the Cora, Citeseer, and Pubmed datasets.
|
Chaotic eigenstates of quantum systems are known to localize on either side
of a classical partial transport barrier if the flux connecting the two sides
is quantum mechanically not resolved due to Heisenberg's uncertainty.
Surprisingly, in open systems with escape chaotic resonance states can localize
even if the flux is quantum mechanically resolved. We explain this using the
concept of conditionally invariant measures from classical dynamical systems by
introducing a new quantum mechanically relevant class of such fractal measures.
We numerically find quantum-to-classical correspondence for localization
transitions depending on the openness of the system and on the decay rate of
resonance states.
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Kinematical and luminosity relations for black-hole jet sources are reviewed.
If the TeV flares observed from PKS 2155-304 in 2006 July are assumed to
originate from a black hole with mass $\approx 10^8 M_8 M_\odot$, then the
$\sim 5$ minute variability timescale is consistent with the light-travel time
across the Schwarzschild radius of the black hole if $M_8\sim 1$. The absolute
jet power in a synchrotron/SSC model exceeds, however, the Eddington luminosity
for a black hole with $M_8\sim 1$ unless the jet is highly efficient. The
maximum Blandford-Znajek power is $\sim 10^{46}M_8$ ergs s$^{-1}$ if the
magnetic-field energy density threading the horizon is equated with the
luminous energy density in the vicinity of the black hole. An external Compton
component can relax power requirements, so a black hole with mass $\sim 10^8
M_\odot$ could explain the observed flaring behavior. For the Swift and HESS
data taken in 2006 July, relativistic outflows with bulk Lorentz factor $\Gamma
\gtrsim 30$ satisfy $\gamma$-$\gamma$ attenuation limits. If this system
harbors a binary black hole, then the accretion disk from a more massive, $\sim
10^9 M_\odot$ black-hole primary would make an additional external radiation
component. Dual thermal accretion disk signatures would confirm this scenario.
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We employ numerical simulations and finite-size scaling techniques to
investigate the properties of the dynamic phase transition that is encountered
in the Blume-Capel model subjected to a periodically oscillating magnetic
field. We mainly focus on the study of the two-dimensional system for various
values of the crystal-field coupling in the second-order transition regime. Our
results indicate that the present non-equilibrium phase transition belongs to
the universality class of the equilibrium Ising model and allow us to construct
a dynamic phase diagram, in analogy to the equilibrium case, at least for the
range of parameters considered. Finally, we present some complementary results
for the three-dimensional model, where again the obtained estimates for the
critical exponents fall into the universality class of the corresponding
three-dimensional equilibrium Ising ferromagnet.
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In the first part of this paper we review a mathematical model for the onset
and progression of Alzheimer's disease (AD) that was developed in subsequent
steps over several years. The model is meant to describe the evolution of AD in
vivo. In [Y. Achdou et al., 2013] we treated the problem at a microscopic
scale, where the typical length scale is a multiple of the size of the soma of
a single neuron. Subsequently, in [M. Bertsch at al., 2016] we concentrated on
the macroscopic scale, where brain neurons are regarded as a continuous medium,
structured by their degree of malfunctioning.
In the second part of the paper we consider the relation between the
microscopic and the macroscopic models. In particular we show under which
assumptions the kinetic transport equation, which in the macroscopic model
governs the evolution of the probability measure for the degree of
malfunctioning of neurons, can be derived from a particle-based setting.
In the microscopic model we consider basically mechanism i), modelling it by
a system of Smoluchowski equations for the amyloid concentration (describing
the agglomeration phenomenon), with the addition of a diffusion term as well as
of a source term on the neuronal membrane. At the macroscopic level instead we
model processes i) and ii) by a system of Smoluchowski equations for the
amyloid concentration, coupled to a kinetic-type transport equation for the
distribution function of the degree of malfunctioning of the neurons. The
second equation contains an integral term describing the random onset of the
disease as a jump process localized in particularly sensitive areas of the
brain.
Even though we deliberately neglected many aspects of the complexity of the
brain and the disease, numerical simulations are in both cases (microscopic and
macroscopic) in good qualitative agreement with clinical data.
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Existing Simultaneous Localization and Mapping (SLAM) approaches are limited
in their scalability due to growing map size in long-term robot operation.
Moreover, processing such maps for localization and planning tasks leads to the
increased computational resources required onboard. To address the problem of
memory consumption in long-term operation, we develop a novel real-time SLAM
algorithm, MeSLAM, that is based on neural field implicit map representation.
It combines the proposed global mapping strategy, including neural networks
distribution and region tracking, with an external odometry system. As a
result, the algorithm is able to efficiently train multiple networks
representing different map regions and track poses accurately in large-scale
environments. Experimental results show that the accuracy of the proposed
approach is comparable to the state-of-the-art methods (on average, 6.6 cm on
TUM RGB-D sequences) and outperforms the baseline, iMAP$^*$. Moreover, the
proposed SLAM approach provides the most compact-sized maps without details
distortion (1.9 MB to store 57 m$^3$) among the state-of-the-art SLAM
approaches.
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In this paper, we use the latest Higgs measurements from ATLAS and CMS to
constrain the parameter space of the model of Schmaltz, Stolarski and Thaler, a
Little Higgs model with two Higgs doublets, which we will refer to as the BLH
model. We account for all production and decay modes explored at ATLAS and CMS
in two scenarios: a general case, which assumes the $h_0$ state is light
($m_{h_0} \approx 125$ GeV) and the masses of the other neutral scalars ($H_0$
and $A_0$) are allowed to vary, and a case with a near-degeneracy between the
masses of the $h_0$ and $A_0$ and, for some choices of parameters, the $H_0$
states. The near-degeneracy scenario can result in an enhanced diphoton rate,
as measured by ATLAS, but is largely ruled out by a combination of the $h_0
\rightarrow \tau^+\tau^-$ and the heavy $H_0 \rightarrow W^+W^-$ measurements.
In the general case, we find large regions of parameter space that are in
better agreement with either the ATLAS or CMS results than is the SM. However,
a significantly enhanced diphoton rate is only possible through large
contributions to the $h_0 \gamma \gamma$ effective coupling from charged Higgs
bosons in a region of parameter space that borders on violation of
perturbativity in the scalar sector.
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We connect two key concepts in quantum information: compatibility and
divisibility of quantum channels. Two channels are compatible if they can be
both obtained via marginalization from a third channel. A channel divides
another channel if it reproduces its action by sequential composition with a
third channel. (In)compatibility is of central importance for studying the
difference between classical and quantum dynamics. The relevance of
divisibility stands in its close relationship with the onset of Markovianity.
We emphasize the simulability character of compatibility and divisibility, and,
despite their structural difference, we find a set of channels --
self-degradable channels -- for which the two notions coincide. We also show
that, for degradable channels, compatibility implies divisibility, and that,
for anti-degradable channels, divisibility implies compatibility. These results
motivate further research on these classes of channels and shed new light on
the meaning of these two largely studied notions.
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We investigate the implications of the model with a SU(2)-singlet up-type
quark, heavy enough not to be produced at the LHC, namely, the contribution of
the new quark to the branching ratios of the K to \pi \nu \bar{\nu}, B to \pi
\nu \bar{\nu} and B to K \nu \bar{\nu} decays. We show that the deviation from
the Standard Model can be up to 10% in the case of a 5 TeV quark. Precise
measurements of these branching ratios at the future experiments will allow to
observe the contributions of the new quark or to impose stronger constraints on
its mass.
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Recent remarkable advances in the experimental techniques have provided a
background for inferring neuronal couplings from point process data that
includes a great number of neurons. Here, we propose a systematic procedure for
pre- and post-processing generic point process data in an objective manner, to
handle data in the framework of a binary simple statistical model, the Ising or
generalized McCulloch--Pitts model. The procedure involves two steps: (1)
determining time-bin size for transforming the point-process data into
discrete-time binary data and (2) screening relevant couplings from the
estimated couplings. For the first step, we decide the optimal time-bin size by
introducing the null hypothesis that all neurons would fire independently, then
choosing a time-bin size so that the null hypothesis is rejected with the most
strict criterion. The likelihood associated with the null hypothesis is
analytically evaluated and used for the rejection process. For the second
post-processing step, after a certain estimator of coupling is obtained based
on the pre-processed dataset, the estimate is compared with many other
estimates derived from datasets obtained by randomizing the original dataset in
the time direction. We accept the original estimate as relevant only if its
absolute value is sufficiently larger than them of randomized datasets. These
manipulations suppress false positive couplings induced by statistical noise.
We apply this inference procedure to spiking data from synthetic and in vitro
neuronal networks. The results show that the proposed procedure identifies the
presence/absence of synaptic couplings fairly well including their signs, for
the synthetic and experimental data. In particular, the results support that we
can infer the physical connections of underlying systems in favorable
situations, even when using the simple statistical model.
|
Spilling tea or coffee leads to a tell-tale circular stain after the drying
of the droplet. This phenomenon was termed after the latter example as the
"coffee ring effect". The evaporation of suspension droplets is a complex
physical process, and prediction and control over particle deposit patterns
obtained from sessile droplet evaporation are essential for many industrial
processes such as ink-jet printing or crop-care applications. In this article,
we present a systematic investigation of the effect of surface wettability on
the evaporation dynamics of a particle-laden droplet, including the effect on
the contact line stick-slip, the hydrodynamic flow of the suspended particles
and the resulting particle deposit after evaporation. We tune the wettability
of glass slides using silanisation and quantify the internal flow during the
evaporation by tracking fluorescent tracer particles. We find that the internal
flow shifts from a predominantly outward flow towards the contact line for low
contact angles to an inward flow for large contact angles. Additionally, the
corresponding deposit gradually changes from the typical coffee-ring to a
central stain upon increasing the hydrophobicity of the substrate. Last, we
corroborate these experimental findings with dynamic density functional theory,
modelling the droplet evaporation process and stick-slip behaviour of the
contact line. Our investigation suggests that the wettability of the substrate
can substantially alter hydrodynamic flow within drying droplets and therefore
the resulting particle deposit.
|
We use the process of quantum hamiltonian reduction of SU(2)_k, at rational
level k, to study explicitly the correlators of the h_{1,s} fields in the
c_{p,q} models. We find from direct calculation of the correlators that we have
the possibility of extra, chiral and non-chiral, multiplet structure in the
h_{1,s} operators beyond the `minimal' sector. At the level of the vacuum null
vector h_{1,2p-1}=(p-1)(q-1) we find that there can be two extra non-chiral
fermionic fields. The extra indicial structure present here permeates
throughout the entire theory. In particular we find we have a chiral triplet of
fields at h_{1,4p-1}=(2p-1)(2q-1). We conjecture that this triplet algebra may
produce a rational extended c_{p,q} model. We also find a doublet of fields at
h_{1,3p-1}=(\f{3p}{2}-1)(\f{3q}{2}-1). These are chiral fermionic operators if
p and q are not both odd and otherwise parafermionic.
|
We suggest a new model for the structure of a magnetic field embedded high
$\beta$ turbulent plasma, based on the popular notion that the magnetic field
will tend to separate into individual flux tubes. We point out that
interactions between the flux tubes will be dominated by coherent effects
stemming from the turbulent wakes created as the fluid streams by the flux
tubes. Balancing the attraction caused by shielding effects with turbulent
diffusion we find that flux tubes have typical radii comparable to the local
Mach number squared times the large scale eddy length, are arranged in a one
dimensional fractal pattern, have a radius of curvature comparable to the
largest scale eddies in the turbulence, and have an internal magnetic pressure
comparable to the ambient pressure. When the average magnetic energy density is
much less than the turbulent energy density the radius, internal magnetic field
and curvature scale of the flux tubes will be smaller than these estimates.
Realistic resistivity does not alter the macroscopic properties of the fluid or
the large scale magnetic field. In either case we show that the Sweet-Parker
reconnection rate is much faster than an eddy turnover time. Realistic stellar
plasmas are expected to either be in the ideal limit (e.g. the solar
photosphere) or the resistive limit (most of the solar convection zone). All
current numerical simulations of three dimensional MHD turbulence are in the
viscous regime and are inapplicable to stars or accretion disks.
|
In this paper we are interested in extending Bailey's identity to other
classical hypergeometric functions. Bailey's identity states that under a
suitable choice of parameters, Appell's $F_4$ decomposes into a product of two
${}_2F_1$'s. We will show how Bailey-type factorizations can be found for
Horn's hypergeometric functions $H_1, H_4$ and $H_5$.
|
The UN-Habitat estimates that over one billion people live in slums around
the world. However, state-of-the-art techniques to detect the location of slum
areas employ high-resolution satellite imagery, which is costly to obtain and
process. As a result, researchers have started to look at utilising free and
open-access medium resolution satellite imagery. Yet, there is no clear
consensus on which data preparation and machine learning approaches are the
most appropriate to use with such imagery data. In this paper, we evaluate two
techniques (multi-spectral data and grey-level co-occurrence matrix feature
extraction) on an open-access dataset consisting of labelled Sentinel-2 images
with a spatial resolution of 10 meters. Both techniques were paired with a
canonical correlation forests classifier. The results show that the grey-level
co-occurrence matrix performed better than multi-spectral data for all four
cities. It had an average accuracy for the slum class of 97% and a mean
intersection over union of 94%, while multi-spectral data had 75% and 64% for
the respective metrics. These results indicate that open-access satellite
imagery with a resolution of at least 10 meters may be suitable for keeping
track of development goals such as the detection of slums in cities.
|
Coset diagrams have been used to study quotients, orbits, subgroups and
structure of the finitely generated groups. In this paper we use coset diagrams
and modular arithmetic to determine the $G$-orbits of $\QQ^*(\sqrt{p^k})$,
$\QQ^*(\sqrt{2p^k})$, $\QQ^*(\sqrt{2^2p^k})$, and in general
$\QQ^*(\sqrt{2^lp^k})$, for each $l\geq3$ and $k=2h+1\geq3$, for each odd prime
$p$.
|
We present a rapid design methodology that combines automated hyper-parameter
tuning with semi-supervised training to build highly accurate and robust models
for voice commands classification. Proposed approach allows quick evaluation of
network architectures to fit performance and power constraints of available
hardware, while ensuring good hyper-parameter choices for each network in
real-world scenarios. Leveraging the vast amount of unlabeled data with a
student/teacher based semi-supervised method, classification accuracy is
improved from 84% to 94% in the validation set. For model optimization, we
explore the hyper-parameter space through population based training and obtain
an optimized model in the same time frame as it takes to train a single model.
|
We perform Monte Carlo simulations of cosmic ray-induced hard X-ray radiation
from the Earth's atmosphere. We find that the shape of the spectrum emergent
from the atmosphere in the energy range 25-300 keV is mainly determined by
Compton scatterings and photoabsorption, and is almost insensitive to the
incident cosmic-ray spectrum. We provide a fitting formula for the hard X-ray
surface brightness of the atmosphere as would be measured by a satellite-born
instrument, as a function of energy, solar modulation level, geomagnetic cutoff
rigidity and zenith angle. A recent measurement by the INTEGRAL observatory of
the atmospheric hard X-ray flux during the occultation of the cosmic X-ray
background by the Earth agrees with our prediction within 10%. This suggests
that Earth observations could be used for in-orbit calibration of future hard
X-ray telescopes. We also demonstrate that the hard X-ray spectra generated by
cosmic rays in the crusts of the Moon, Mars and Mercury should be significantly
different from that emitted by the Earth's atmosphere.
|
We demonstrate simultaneous detection of current driven antidamping-like and
field-like spin-orbit torques in heavy metal/ferromagnetic metal bilayers by
measuring all three magnetization components m_(x,) m_y, and m_z using the
vector magneto-optic Kerr effect. We have also implemented a self-calibration
method to accurately determine the effective fields of spin-orbit torques. With
this technique, we investigate the magnitude and direction of spin-orbit
torques in a series of platinum/permalloy samples. The values found are in
excellent agreement with results obtained via quadratic magneto-optic Kerr
effect, planar Hall effect, and spin transfer ferromagnetic resonance
measurements.
|
We study the dynamics of a two-degrees-of-freedom (two DOF) nonlinear
oscillator representing a quartercar model excited by a road roughness profile.
Modelling the road profile by means of a harmonic function we derive the
Melnikov criterion for a system transition to chaos or escape. The analytically
obtained estimations are confirmed by numerical simulations. To analyze the
transient vibrations we used recurrences.
|
The most common way to listen to recorded music nowadays is via streaming
platforms which provide access to tens of millions of tracks. To assist users
in effectively browsing these large catalogs, the integration of Music
Recommender Systems (MRSs) has become essential. Current real-world MRSs are
often quite complex and optimized for recommendation accuracy. They combine
several building blocks based on collaborative filtering and content-based
recommendation. This complexity can hinder the ability to explain
recommendations to end users, which is particularly important for
recommendations perceived as unexpected or inappropriate. While pure
recommendation performance often correlates with user satisfaction,
explainability has a positive impact on other factors such as trust and
forgiveness, which are ultimately essential to maintain user loyalty.
In this article, we discuss how explainability can be addressed in the
context of MRSs. We provide perspectives on how explainability could improve
music recommendation algorithms and enhance user experience. First, we review
common dimensions and goals of recommenders' explainability and in general of
eXplainable Artificial Intelligence (XAI), and elaborate on the extent to which
these apply -- or need to be adapted -- to the specific characteristics of
music consumption and recommendation. Then, we show how explainability
components can be integrated within a MRS and in what form explanations can be
provided. Since the evaluation of explanation quality is decoupled from pure
accuracy-based evaluation criteria, we also discuss requirements and strategies
for evaluating explanations of music recommendations. Finally, we describe the
current challenges for introducing explainability within a large-scale
industrial music recommender system and provide research perspectives.
|
The temperature dependent resistivity of two Pr1-xCaxMnO3 (x=0.5 and 0.4)
thin films grown on LaAlO3 has been studied as a function of hydrostatic
pressure (up to 2.5 GPa) and magnetic field (up to 9T). Both samples show a
monotonic decrease in the resistivity with an increase in pressure,
corresponding to a change of -35% at 2.5 GPa. No pressure induced
metal-to-insulator transition was observed in the temperature-dependent
resistivity. The non-trivial interaction between high pressure and magnetic
field reveals that the effect of pressure cannot be simply rescaled to that of
a specific field, as has been reported for the corresponding bulk material. We
propose an interpretation of the data based on phase separation, where two
different insulating phases coexist: the charge ordered phase, which is
sensitive to both magnetic field and pressure, and a second insulating phase
that can be tuned by magnetic field. Such a result demonstrates that phase
separation can be manipulated in thin films by independent application of
magnetic field and/or external pressure.
|
We report a proof-of-principle experimental demonstration of a
turbulence-resistant quantum Lidar system. As a key technology for sensing and
ranging, Lidar has drawn considerable attention for a study from quantum
perspective, in search of proven advantages complementary to the capabilities
of conventional Lidar technologies. Environmental factors such as strong
atmospheric turbulence can have detrimental effects on the performance of these
systems. We demonstrate the possibility of turbulence-resistant operation of a
quantum Lidar system via two-photon interference of entangled photon pairs.
Additionally, the reported quantum Lidar also demonstrates the expected noise
resistance. This study suggests a potential high precision timing-positioning
technology operable under turbulence and noise.
|
We present new radio continuum observations of NGC253 from the Murchison
Widefield Array at frequencies between 76 and 227 MHz. We model the broadband
radio spectral energy distribution for the total flux density of NGC253 between
76 MHz and 11 GHz. The spectrum is best described as a sum of central starburst
and extended emission. The central component, corresponding to the inner 500pc
of the starburst region of the galaxy, is best modelled as an internally
free-free absorbed synchrotron plasma, with a turnover frequency around 230
MHz. The extended emission component of the NGC253 spectrum is best described
as a synchrotron emission flattening at low radio frequencies. We find that 34%
of the extended emission (outside the central starburst region) at 1 GHz
becomes partially absorbed at low radio frequencies. Most of this flattening
occurs in the western region of the SE halo, and may be indicative of
synchrotron self-absorption of shock re-accelerated electrons or an intrinsic
low-energy cut off of the electron distribution. Furthermore, we detect the
large-scale synchrotron radio halo of NGC253 in our radio images. At 154 - 231
MHz the halo displays the well known X-shaped/horn-like structure, and extends
out to ~8kpc in z-direction (from major axis).
|
In his recent article [arXiv:1604.04950], Adler questions the usefulness of
the bound found in our experimental search for genuine effects of hyper-complex
quantum mechanics [arXiv:1602.01624]. Our experiment was performed using a
black-box (instrumentalist) approach to generalized probabilistic theories;
therefore, it does not assume a priori any particular underlying mechanism.
From that point of view our experimental results do indeed place meaningful
bounds on possible effects of "post-quantum theories", including quaternionic
quantum mechanics. In his article, Adler compares our experiment to
non-relativistic and M\"oller formal scattering theory within quaternionic
quantum mechanics. With a particular set of assumptions, he finds that
quaternionic effects would likely not manifest themselves in general. Although
these assumptions are justified in the non-relativistic case, a proper
calculation for relativistic particles is still missing. Here, we provide a
concrete relativistic example of Klein-Gordon scattering wherein the
quaternionic effects persist. We note that when the Klein-Gordon equation is
formulated using a Hamiltonian formalism it displays a so-called "indefinite
metric", a characteristic feature of relativistic quantum wave equations. In
Adler's example this is directly forbidden by his assumptions, and therefore
our present example is not in contradiction to his work. In complex quantum
mechanics this problem of an indefinite metric is solved in second
quantization. Unfortunately, there is no known algorithm for canonical field
quantization in quaternionic quantum mechanics.
|
We present a method of constructing generic single-centered and
multi-centered extremal black hole solutions in a large class of 4D N=2
supergravities coupled to vector-multiplets with cubic prepotentials. The
method is applicable to models for which the 3D moduli spaces obtained via
c*-map are symmetric coset spaces. The attractor solutions are generated by
certain nilpotent elements in the coset algebra. We present explicit
computations in 4D N=2 supergravity coupled to one vector-multiplet, whose 3D
moduli space is the symmetric coset space G_{2(2)}/SL(2,R)^2. The
non-supersymmetric multi-centered black holes in this model are found to lack
the intricate moduli space of bound configurations that are typical of the
supersymmetric case.
|
The Krylov--Safonov theory for fully nonlinear nonlocal operators on
hyperbolic spaces of dimension three is established. Since the operators on
hyperbolic spaces exhibit qualitatively different behavior than those on
manifolds with nonnegative curvature, new scale functions are introduced which
take the effect of negative curvature into account.
The regularity theory in this work provides unified regularity results for
fractional-order and second-order operators in the sense that the regularity
estimates stay uniform as the fractional-order approaches 2. In the unified
regularity theory, the asymptotic behavior of the normalizing constant for the
fractional Laplacian plays a fundamental role. The dimension restriction has
been imposed to compute the explicit value of this constant by using the
Fourier analysis on hyperbolic spaces.
|
Objects in the Edgeworth-Kuiper belt and the main asteroid belt should emit
microwaves that may give rise to extra anisotropy signals in the multipole of
the cosmic microwave background (CMB) experiment. Constraints are derived from
the absence of positive detection of such anisotropies for ell < 50, giving the
total mass of Edgeworth-Kuiper belt objects to be smaller than 0.2 earth mass.
This limit is consistent with the mass extrapolated from the observable
population with the size of a > 15 km, assuming that the small-object
population follows the power law in size dN/da ~ a^{-q} with the canonical
index expected for collisional equilibrium, q ~ 3.5, with which 23% of the mass
is ascribed to objects smaller than are observationally accessible down to
grains. A similar argument applied to the main asteroid belt indicates that the
grain population should not increase faster than q ~ 3.6 towards smaller radii,
if it follows the power law continued to observed asteroids with larger radii.
It is underlined that both cases are at or only slightly above the limit that
can be physically significant, implying the importance of tightening further
the CMB anisotropy limit, which may be attained with the observation at higher
radio frequencies.
|
We present ObjBlur, a novel curriculum learning approach to improve
layout-to-image generation models, where the task is to produce realistic
images from layouts composed of boxes and labels. Our method is based on
progressive object-level blurring, which effectively stabilizes training and
enhances the quality of generated images. This curriculum learning strategy
systematically applies varying degrees of blurring to individual objects or the
background during training, starting from strong blurring to progressively
cleaner images. Our findings reveal that this approach yields significant
performance improvements, stabilized training, smoother convergence, and
reduced variance between multiple runs. Moreover, our technique demonstrates
its versatility by being compatible with generative adversarial networks and
diffusion models, underlining its applicability across various generative
modeling paradigms. With ObjBlur, we reach new state-of-the-art results on the
complex COCO and Visual Genome datasets.
|
The stochastic quantization of the fermion field is performed starting from
Dirac equations. The statistical properties of stochastic terms in Langevin
equations are described by explicit formulae of a Markov process. The
interaction of the field is introduced as correlation of the stochastic terms.
In the long time limit free fermions disappear and proper combinations of field
components propagate as a scalar boson field. The existence and uniqueness of
the long time limit is proved in the first order approximation of stochastic
Liouville equation.
|
We show that an in-plane Zeeman field applied to non-centrosymmetric Ising
superconductors converts singlet $s$-wave Cooper pairs to equal-spin triplet
$if$ pairs, leading to an enhancement of the critical transition line beyond
expected from Ising spin-orbit coupling. Singlet to triplet conversion relates
to a phase transformation due to spin rotation by the Zeeman field and has a
geometric origin. The discussion is especially relevant, but not limited to
monolayer transition metal dichalcogenides.
|
It has been suggested by Sorkin that a three-slit Young experiment could
reveal the validity a fundamental ingredient in the foundations of one of the
cornerstones in modern physics namely quantum mechanics. In terms of a certain
parameter $\kappa_S$, it was argued that a non-zero value could imply a
breakdown of the fundamental Born's rule as well as the superposition
principle. Here we argue that a physical realization of such arguments could
lead to an erroneous conclusion and contradict the basic rules of quantum
mechanics. In fact, we argue that a proper interpretation of the procedures
involved in a physical determination of $\kappa_S$ does not necessarily lead to
$\kappa_S=0$. In order to show this we consider a mono-chromatic source of
photons prepared in an {\it arbitrary} quantum state and a simple version of
the well-established photon detection theory of Glauber which, by construction,
obeys all the rules of quantum mechanics. It is, however, also argued that
after a proper identification of the relevant quantum-mechanical probability
amplitudes one can be reach $\kappa_S=0$. As long as one only consider a single
photon detector, it is verified that, in this context, there is no fundamental
difference between quantum-mechanical interference and interference as
expressed in terms of classical electro-magnetic waves.
|
Galaxy clusters contain a diffuse stellar component outside the cluster's
galaxies, which is observed as faint intracluster light (ICL). Using
Gemini/GMOS-N deep imaging and multi-object spectroscopy of a massive fossil
cluster at a redshift of $z=0.47$, RX J105453.3+552102 (J1054), we improve the
observational constraints on the formation mechanism of the ICL. We extract the
ICL surface brightness and colour profiles out to 155 kpc from the brightest
cluster galaxy (BCG) with a detection limit of 28.7 mag/arcsec$^2$ (1$\sigma$,
4.8" x 4.8"; i-band). The colour of the diffuse light is similar to that of the
BCG and central bright galaxies out to $\sim$ 70 kpc, becoming slightly bluer
toward the outside. We find that the ICL distribution shows better agreement
with the spatial distribution of member galaxies than with the BCG-dominated
cluster luminosity distribution. We report the ICL fraction of J1054 as $15.07
\pm 4.57 \%$ in the range of $60 \sim 155$ kpc from the BCG, which appears to
be higher than the ICL fraction-redshift trend in previous studies. Our
findings suggest that intracluster stars seems not to be explained by one
dominant production mechanism. However, a significant fraction of the ICL of
J1054 may have been generated from the outskirts of infalling/satellite
galaxies more recently rather than by the BCG at the early stage of the
cluster.
|
We use leading-order anisotropic hydrodynamics to study an
azimuthally-symmetric boost-invariant quark-gluon plasma. We impose a realistic
lattice-based equation of state and perform self-consistent anisotropic
freeze-out to hadronic degrees of freedom. We then compare our results for the
full spatiotemporal evolution of the quark-gluon plasma and its subsequent
freeze-out to results obtained using 1+1d Israel-Stewart second-order viscous
hydrodynamics. We find that for small shear viscosities, 4 pi eta/s ~ 1, the
two methods agree well for nucleus-nucleus collisions, however, for large shear
viscosity to entropy density ratios or proton-nucleus collisions we find
important corrections to the Israel-Stewart results for the final particle
spectra and the total number of charged particles. Finally, we demonstrate that
the total number of charged particles produced is a monotonically increasing
function of 4 pi eta/s in Israel-Stewart viscous hydrodynamics whereas in
anisotropic hydrodynamics it has a maximum at 4 pi eta/s ~ 10. For all 4 pi
eta/s > 0, we find that for Pb-Pb collisions Israel-Stewart viscous
hydrodynamics predicts more dissipative particle production than anisotropic
hydrodynamics.
|
Categorizing music files according to their genre is a challenging task in
the area of music information retrieval (MIR). In this study, we compare the
performance of two classes of models. The first is a deep learning approach
wherein a CNN model is trained end-to-end, to predict the genre label of an
audio signal, solely using its spectrogram. The second approach utilizes
hand-crafted features, both from the time domain and the frequency domain. We
train four traditional machine learning classifiers with these features and
compare their performance. The features that contribute the most towards this
multi-class classification task are identified. The experiments are conducted
on the Audio set data set and we report an AUC value of 0.894 for an ensemble
classifier which combines the two proposed approaches.
|
Pure de Sitter, anti de Sitter, and orthogonal gauge theories in
four-dimensional Euclidean spacetime are studied. It is shown that, if the
theory is asymptotically free and a dynamical mass is generated, then an
effective geometry may be induced and a gravity theory emerges. The asymptotic
freedom and the running of the mass might account for an In\"on\"u-Wigner
contraction which induces a breaking of the gauge group to the Lorentz group,
while the mass itself is responsible for the coset sector of the gauge field to
be identified with the effective vierbein. Furthermore, the resulting local
isometries are Lorentzian for the anti de Sitter group and Euclidean for the de
Sitter and orthogonal groups.
|
With this paper we provide a mathematical review on the initial-value problem
of the one-particle Dirac equation on space-like Cauchy hypersurfaces for
compactly supported external potentials. We, first, discuss the physically
relevant spaces of solutions and initial values in position and mass shell
representation; second, review the action of the Poincar\'e group as well as
gauge transformations on those spaces; third, introduce generalized Fourier
transforms between those spaces and prove convenient Paley-Wiener- and
Sobolev-type estimates. These generalized Fourier transforms immediately allow
the construction of a unitary evolution operator for the free Dirac equation
between the Hilbert spaces of square-integrable wave functions of two
respective Cauchy surfaces. With a Picard-Lindel\"of argument this evolution
map is generalized to the Dirac evolution including the external potential. For
the latter we introduce a convenient interaction picture on Cauchy surfaces.
These tools immediately provide another proof of the well-known existence and
uniqueness of classical solutions and their causal structure.
|
We present three new methods for determining the age of groups of
pre-main-sequence stars. The first, creating empirical isochrones allows us to
create a robust age ordering, but not to derive actual ages. The second, using
the width of the gap in colour-magnitude space between the pre-main-sequence
and main-sequence (the radiative convective gap) has promise as a distance and
extinction independent measure of age, but is as yet uncalibrated. Finally we
discuss tau-squared fitting of the main sequence as the stars approach the
terminus of the main sequence. This method suggests that there is a factor two
difference between these "nuclear" ages, and more conventional
pre-main-sequence contraction ages.
|
Perturbative calculations in field theory at finite temperature involve sums
over the Matsubara frequencies. Besides the usual difficulties that appear in
perturbative computations, these sums give rise to some new obstacles that are
carefully analized here. I present a fast and realible recipe to work out sums
over the Matsubara frequencies. As this algorithm leads to deal with very
cumbersome algebraic expressions, it has been written for computers by using
the symbolic manipulation program Mathematica. It is also shown this algorithm
to be self-consistent when it is applied to more than one loop computations.
|
We present ALMA Band-3/7 observations towards "the Heart" of a massive
hub-filament system (HFS) SDC335, to investigate its fragmentation and
accretion. At a resolution of $\sim0.03$ pc, 3 mm continuum emission resolves
two massive dense cores MM1 and MM2, with $383(^{+234}_{-120})$ $M_\odot$
(10-24% mass of "the Heart") and $74(^{+47}_{-24})$ $M_\odot$, respectively.
With a resolution down to 0.01 pc, 0.87 mm continuum emission shows MM1 further
fragments into six condensations and multi-transition lines of H$_2$CS provide
temperature estimation. The relation between separation and mass of
condensations at a scale of 0.01 pc favors turbulent Jeans fragmentation where
the turbulence seems to be scale-free rather than scale-dependent. We use the
H$^{13}$CO$^+$ (1-0) emission line to resolve the complex gas motion inside
"the Heart" in position-position-velocity space. We identify four major gas
streams connected to large-scale filaments, inheriting the anti-clockwise
spiral pattern. Along these streams, gas feeds the central massive core MM1.
Assuming an inclination angle of $45(\pm15)^{\circ}$ and a H$^{13}$CO$^+$
abundance of $5(\pm3)\times10^{-11}$, the total mass infall rate is estimated
to be $2.40(\pm0.78)\times10^{-3}$ $M_\odot$ yr$^{-1}$, numerically consistent
with the accretion rates derived from the clump-scale spherical infall model
and the core-scale outflows. The consistency suggests a continuous, near
steady-state, and efficient accretion from global collapse, therefore ensuring
core feeding. Our comprehensive study of SDC335 showcases the detailed gas
kinematics in a prototypical massive infalling clump and calls for further
systematic and statistical analyses in a large sample.
|
Recent theoretical developments for observing the Epoch of Reionization (EOR)
have concentrated on the power spectrum signature of redshifted 21 cm emission.
These studies have demonstrated the great potential of statistical EOR
observations, however, the sensitivity calculations for proposed low frequency
radio arrays have been highly approximate. The formalism developed for
interferometric measurements of the cosmic microwave background can be extended
to three dimensions to naturally incorporate the line-of-sight information
inherent in the EOR signal. In this paper we demonstrate how to accurately
calculate the EOR power spectrum sensitivity of an array, and develop scaling
relationships which can be used to guide the design of EOR observatories. The
implications for antenna distribution, antenna size, and correlator
requirements on the EOR sensitivity are detailed.
|
A by-no-means-complete collection of references for those interested in
intonational meaning, with other miscellaneous references on intonation
included. Additional references are welcome, and should be sent to
<EMAIL_ADDRESS>
|
Anomalous motional heating is a major obstacle to scalable quantum
information processing with trapped ions. While the source of this heating is
not yet understood, several previous studies suggest that surface contaminants
may be largely responsible. We demonstrate an improvement by a factor of four
in the room-temperature heating rate of a niobium surface electrode trap by in
situ plasma cleaning of the trap surface. This surface treatment was performed
with a simple homebuilt coil assembly and commercially-available matching
network and is considerably gentler than other treatments, such as ion milling
or laser cleaning, that have previously been shown to improve ion heating
rates. We do not see an improvement in the heating rate when the trap is
operated at cryogenic temperatures, pointing to a role of thermally-activated
surface contaminants in motional heating whose activity may freeze out at low
temperatures.
|
Split learning (SL) is a promising approach for training artificial
intelligence (AI) models, in which devices collaborate with a server to train
an AI model in a distributed manner, based on a same fixed split point.
However, due to the device heterogeneity and variation of channel conditions,
this way is not optimal in training delay and energy consumption. In this
paper, we design an adaptive split learning (ASL) scheme which can dynamically
select split points for devices and allocate computing resource for the server
in wireless edge networks. We formulate an optimization problem to minimize the
average training latency subject to long-term energy consumption constraint.
The difficulties in solving this problem are the lack of future information and
mixed integer programming (MIP). To solve it, we propose an online algorithm
leveraging the Lyapunov theory, named OPEN, which decomposes it into a new MIP
problem only with the current information. Then, a two-layer optimization
method is proposed to solve the MIP problem. Extensive simulation results
demonstrate that the ASL scheme can reduce the average training delay and
energy consumption by 53.7% and 22.1%, respectively, as compared to the
existing SL schemes.
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The main task of Multimodal Emotion Recognition in Conversations (MERC) is to
identify the emotions in modalities, e.g., text, audio, image and video, which
is a significant development direction for realizing machine intelligence.
However, many data in MERC naturally exhibit an imbalanced distribution of
emotion categories, and researchers ignore the negative impact of imbalanced
data on emotion recognition. To tackle this problem, we systematically analyze
it from three aspects: data augmentation, loss sensitivity, and sampling
strategy, and propose the Class Boundary Enhanced Representation Learning
(CBERL) model. Concretely, we first design a multimodal generative adversarial
network to address the imbalanced distribution of {emotion} categories in raw
data. Secondly, a deep joint variational autoencoder is proposed to fuse
complementary semantic information across modalities and obtain discriminative
feature representations. Finally, we implement a multi-task graph neural
network with mask reconstruction and classification optimization to solve the
problem of overfitting and underfitting in class boundary learning, and achieve
cross-modal emotion recognition. We have conducted extensive experiments on the
IEMOCAP and MELD benchmark datasets, and the results show that CBERL has
achieved a certain performance improvement in the effectiveness of emotion
recognition. Especially on the minority class fear and disgust emotion labels,
our model improves the accuracy and F1 value by 10% to 20%.
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The entropy of a hierarchical network topology in an ensemble of sparse
random networks with "hidden variables" associated to its nodes, is the
log-likelihood that a given network topology is present in the chosen
ensemble.We obtain a general formula for this entropy,which has a clear simple
interpretation in some simple limiting cases. The results provide new keys with
which to solve the general problem of "fitting" a given network with an
appropriate ensemble of random networks.
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In this paper we present the "Small Bodies: Near and Far" Infrared Database,
an easy-to-use tool intended to facilitate the modeling of thermal emission of
small Solar System bodies. Our database collects thermal emission measurements
of small Solar Systems targets that are otherwise available in scattered
sources and gives a complete description of the data, with all information
necessary to perform direct scientific analyses and without the need to access
additional, external resources. This public database contains representative
data of asteroid observations of large surveys (e.g. AKARI, IRAS and WISE) as
well as a collection of small body observations of infrared space telescopes
(e.g. the Herschel Space Observatory) and provides a web interface to access
this data (https://ird.konkoly.hu). We also provide an example for the direct
application of the database and show how it can be used to estimate the thermal
inertia of specific populations, e.g. asteroids within a given size range. We
show how different scalings of thermal inertia with heliocentric distance (i.e.
temperature) may affect our interpretation of the data and discuss why the
widely-used radiative conductivity exponent ($\alpha$=-3/4) might not be
adequate in general, as hinted by previous studies.
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In this paper, we introduce the bi-periodic Lucas matrix sequence and present
some fundamental properties of this generalized matrix sequence. Moreover, we
investigate the important relationships between the bi-periodic Fibonacci and
Lucas matrix sequences. We express that some behaviours of bi-periodic Lucas
numbers also can be obtained by considering properties of this new matrix
sequence. Finally, we say that the matrix sequences as Lucas, $k$-Lucas and
Pell-Lucas are special cases of this generalized matrix sequence.
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We review the case for the photon having a tiny mass compatible with the
experimental limits. We go over some possible experimental tests for such a
photon mass including the violation of Lorentz symmetry. We point out that such
violations may already have been witnessed in tests involving high energy gamma
rays from outer space as also ultra high energy cosmic rays.
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We demonstrate the use of the Unified Transform Method or Method of Fokas for
boundary value problems for systems of constant-coefficient linear partial
differential equations. We discuss how the apparent branch singularities
typically appearing in the global relation are removable, allowing the method
to proceed, in essence, as for scalar problems. We illustrate the use of the
method with boundary value problems for the Klein-Gordon equation and the
linearized Fitzhugh-Nagumo system. The case of wave equations is treated
separately in an appendix.
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The Trojan asteroids remain quite poorly understood, yet their physical
properties provide unique perspective on chemical and dynamical processes that
shaped the Solar System. The current study was undertaken to investigate
surface compositions of these objects. We present 66 new near-infrared (NIR;
0.7 to 2.5 microns) spectra of 58 Trojans, including members of both the
leading and trailing swarms. We also include in the analysis previously
published NIR spectra of 13 Trojans (3 of which overlap with the new sample).
This data set permits not only a direct search for compositional signatures,
but also a search for patterns that may reveal clues to the origin of the
Trojans. We do not report any confirmed absorption features in the new spectra.
Analysis of the spectral slopes, however, reveals an interesting bimodality
among the NIR data. The two spectral groups identified appear to be equally
abundant in the leading and trailing swarms. The spectral groups are not a
result of family membership; they occur in the background, non-family
population. The average albedos of the two groups are the same within
uncertainties (0.051\pm0.016 and 0.055\pm0.016). No correlations between
spectral slope and any other physical or orbital parameter are detected, with
the exception of a possible weak correlation with inclination among the
less-red spectral group. Synthesizing these results with previously published
properties, we conclude that the two spectral groups represent objects with
different intrinsic compositions. We further suggest that while the less-red
group originated near Jupiter or in the main asteroid belt, the redder spectral
group originated farther out in the Solar System. If correct, the Trojan swarms
offer the most readily accessible large reservoir of Kuiper Belt material as
well as a unique reservoir for the study of material from the middle part of
the solar nebula.
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The success of neural architecture search (NAS) has historically been limited
by excessive compute requirements. While modern weight-sharing NAS methods such
as DARTS are able to finish the search in single-digit GPU days, extracting the
final best architecture from the shared weights is notoriously unreliable.
Training-Speed-Estimate (TSE), a recently developed generalization estimator
with a Bayesian marginal likelihood interpretation, has previously been used in
place of the validation loss for gradient-based optimization in DARTS. This
prevents the DARTS skip connection collapse, which significantly improves
performance on NASBench-201 and the original DARTS search space. We extend
those results by applying various DARTS diagnostics and show several unusual
behaviors arising from not using a validation set. Furthermore, our experiments
yield concrete examples of the depth gap and topology selection in DARTS having
a strongly negative impact on the search performance despite generally
receiving limited attention in the literature compared to the operations
selection.
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We prove a generalization of the author's work to show that any subset of the
primes which is `well-distributed' in arithmetic progressions contains many
primes which are close together. Moreover, our bounds hold with some uniformity
in the parameters. As applications, we show there are infinitely many intervals
of length $(\log{x})^{\epsilon}$ containing $\gg_\epsilon \log\log{x}$ primes,
and show lower bounds of the correct order of magnitude for the number of
strings of $m$ congruent primes with $p_{n+m}-p_n\le \epsilon\log{x}$.
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This paper provides an overview of NVIDIA NeMo's neural machine translation
systems for the constrained data track of the WMT21 News and Biomedical Shared
Translation Tasks. Our news task submissions for English-German (En-De) and
English-Russian (En-Ru) are built on top of a baseline transformer-based
sequence-to-sequence model. Specifically, we use a combination of 1) checkpoint
averaging 2) model scaling 3) data augmentation with backtranslation and
knowledge distillation from right-to-left factorized models 4) finetuning on
test sets from previous years 5) model ensembling 6) shallow fusion decoding
with transformer language models and 7) noisy channel re-ranking. Additionally,
our biomedical task submission for English-Russian uses a biomedically biased
vocabulary and is trained from scratch on news task data, medically relevant
text curated from the news task dataset, and biomedical data provided by the
shared task. Our news system achieves a sacreBLEU score of 39.5 on the WMT'20
En-De test set outperforming the best submission from last year's task of 38.8.
Our biomedical task Ru-En and En-Ru systems reach BLEU scores of 43.8 and 40.3
respectively on the WMT'20 Biomedical Task Test set, outperforming the previous
year's best submissions.
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We have obtained Hubble Space Telescope/STIS low-resolution ultraviolet
spectra of the X-ray pulsar 4U 1626-67 (=KZ TrA); 4U 1626-67 is unusual even
among X-ray pulsars due to its ultra-short binary period (P=41.4 min) and
remarkably low mass-function (<1.3e-6 Msun). The far-UV spectrum was exposed
for a total of 32ks and has sufficient signal-to-noise to reveal numerous broad
emission and prominent narrower absorption lines. Most of the absorption lines
are consistent in strength with a purely interstellar origin. However, there is
evidence that both CI and CIV require additional absorbing gas local to the
system. In emission, the usual prominent lines of NV and HeII are absent,
whilst both OIV and OV are relatively strong. We further identify a rarely seen
feature at ~1660A as the OIII] multiplet. Our ultraviolet spectra therefore
provide independent support for the recent suggestion that the mass donor is
the chemically fractionated core of either a C-O-Ne or O-Ne-Mg white dwarf;
this was put forward to explain the results of Chandra high-resolution X-ray
spectroscopy. The velocity profiles of the ultraviolet lines are in all cases
broad and/or flat-topped, or perhaps even double-peaked for the highest
ionization cases of O; in either case the ultraviolet line profiles are in
broad agreement with the Doppler pairs found in the X-ray spectra. Both the
X-ray and far-UV lines are plausibly formed in (or in an corona just above) a
Keplerian accretion disc; the combination of ultraviolet and X-ray spectral
data may provide a rich data set for follow-on detailed models of the disk
dynamics and ionization structure in this highly unusual low-mass X-ray pulsar
system.
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Transformer large language models (LLMs) have sparked admiration for their
exceptional performance on tasks that demand intricate multi-step reasoning.
Yet, these models simultaneously show failures on surprisingly trivial
problems. This begs the question: Are these errors incidental, or do they
signal more substantial limitations? In an attempt to demystify transformer
LLMs, we investigate the limits of these models across three representative
compositional tasks -- multi-digit multiplication, logic grid puzzles, and a
classic dynamic programming problem. These tasks require breaking problems down
into sub-steps and synthesizing these steps into a precise answer. We formulate
compositional tasks as computation graphs to systematically quantify the level
of complexity, and break down reasoning steps into intermediate sub-procedures.
Our empirical findings suggest that transformer LLMs solve compositional tasks
by reducing multi-step compositional reasoning into linearized subgraph
matching, without necessarily developing systematic problem-solving skills. To
round off our empirical study, we provide theoretical arguments on abstract
multi-step reasoning problems that highlight how autoregressive generations'
performance can rapidly decay with\,increased\,task\,complexity.
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In this paper we present a particle-number-conserving (PNC) functional
formalism to describe the dynamics of a cold bosonic gas. Treating the total
number of particles as a constraint, whereby the phase invariance of the theory
becomes local in time, we study this U(1) gauge theory using DeWitt's "gauge
invariant effective action" techniques. Our functional formulation and earlier
PNC proposals are shown to yield equivalent results to next-to-leading order in
an expansion in the inverse powers of the total number of particles. In this
more general framework we also show that earlier PNC proposals can be seen as
different gauge (and gauge fixing condition) choices within the same physical
theory.
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Honeycomb structure has a natural extension to the three dimensions. Simple
examples are hyperhoneycomb and stripy-honeycomb lattices, which are realized
in $\beta $-Li$_{2}$IrO$_{3}$ and $\gamma $-Li$_{2}$IrO$_{3}$, respectively. We
propose a wide class of three-dimensional (3D) honeycomb lattices which are
loop-nodal semimetals. Their edge states have intriguing properties similar to
the two-dimensional honeycomb lattice in spite of dimensional difference.
Partial flat bands emerge at the zigzag or beard edge of the 3D honeycomb
lattice, whose boundary is given by the Fermi loop in the bulk spectrum.
Analytic solutions are explicitly constructed for them. On the other hand,
perfect flat bands emerge in the zigzag-beard edge or when the anisotropy is
large. All these 3D honeycomb lattices become strong topological insulators
with the inclusion of the spin-orbit interaction. Furthermore, point-nodal
semimetals may be realized in the presence of both the antiferromagnetic order
and the spin-orbit interaction.
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Computer vision applications such as visual relationship detection and human
object interaction can be formulated as a composite (structured) set detection
problem in which both the parts (subject, object, and predicate) and the sum
(triplet as a whole) are to be detected in a hierarchical fashion. In this
paper, we present a new approach, denoted Part-and-Sum detection Transformer
(PST), to perform end-to-end visual composite set detection. Different from
existing Transformers in which queries are at a single level, we simultaneously
model the joint part and sum hypotheses/interactions with composite queries and
attention modules. We explicitly incorporate sum queries to enable better
modeling of the part-and-sum relations that are absent in the standard
Transformers. Our approach also uses novel tensor-based part queries and
vector-based sum queries, and models their joint interaction. We report
experiments on two vision tasks, visual relationship detection and human object
interaction and demonstrate that PST achieves state of the art results among
single-stage models, while nearly matching the results of custom designed
two-stage models.
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This paper proposes a new method to drastically speed up deep reinforcement
learning (deep RL) training for problems that have the property of state-action
permissibility (SAP). Two types of permissibility are defined under SAP. The
first type says that after an action $a_t$ is performed in a state $s_t$ and
the agent has reached the new state $s_{t+1}$, the agent can decide whether
$a_t$ is permissible or not permissible in $s_t$. The second type says that
even without performing $a_t$ in $s_t$, the agent can already decide whether
$a_t$ is permissible or not in $s_t$. An action is not permissible in a state
if the action can never lead to an optimal solution and thus should not be
tried (over and over again). We incorporate the proposed SAP property and
encode action permissibility knowledge into two state-of-the-art deep RL
algorithms to guide their state-action exploration together with a virtual
stopping strategy. Results show that the SAP-based guidance can markedly speed
up RL training.
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Many forecasts consist not of point predictions but concern the evolution of
quantities. For example, a central bank might predict the interest rates during
the next quarter, an epidemiologist might predict trajectories of infection
rates, a clinician might predict the behaviour of medical markers over the next
day, etc. The situation is further complicated since these forecasts sometimes
only concern the approximate "shape of the future evolution" or "order of
events". Formally, such forecasts can be seen as probability measures on spaces
of equivalence classes of paths modulo time-parametrization. We leverage the
statistical framework of proper scoring rules with classical mathematical
results to derive a principled approach to decision making with such forecasts.
In particular, we introduce notions of gradients, entropy, and divergence that
are tailor-made to respect the underlying non-Euclidean structure.
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The stationary points of the total scalar curvature functional on the space
of unit volume metrics on a given closed manifold are known to be precisely the
Einstein metrics. One may consider the modified problem of finding stationary
points for the volume functional on the space of metrics whose scalar curvature
is equal to a given constant. In this paper, we localize a condition satisfied
by such stationary points to smooth bounded domains. The condition involves a
generalization of the static equations, and we interpret solutions (and their
boundary values) of this equation variationally. On domains carrying a metric
that does not satisfy the condition, we establish a local deformation theorem
that allows one to achieve simultaneously small prescribed changes of the
scalar curvature and of the volume by a compactly supported variation of the
metric. We apply this result to obtain a localized gluing theorem for constant
scalar curvature metrics in which the total volume is preserved. Finally, we
note that starting from a counterexample of Min-Oo's conjecture such as that of
Brendle-Marques-Neves, counterexamples of arbitrarily large volume and
different topological types can be constructed.
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A system of three point vortices in an unbounded plane has a special family
of self-similarly contracting or expanding solutions: during the motion, vortex
triangle remains similar to the original one, while its area decreases (grows)
at a constant rate. A contracting configuration brings three vortices to a
single point in a finite time; this phenomenon known as vortex collapse is of
principal importance for many-vortex systems. Dynamics of close-to-collapse
vortex configurations depends on the way the collapse conditions are violated.
Using an effective potential representation, a detailed quantitative analysis
of all the different types of near-collapse dynamics is performed when two of
the vortices are identical. We discuss time and length scales, emerging in the
problem, and their behavior as the initial vortex triangle is approaching to an
exact collapse configuration. Different types of critical behaviors, such as
logarithmic or power-law divergences are exhibited, which emphasizes the
importance of the way the collapse is approached. Period asymptotics for all
singular cases are presented as functions of the initial vortices
configurations. Special features of passive particle mixing by a near-collapse
flows are illustrated numerically.
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Neural parameter allocation search (NPAS) automates parameter sharing by
obtaining weights for a network given an arbitrary, fixed parameter budget.
Prior work has two major drawbacks we aim to address. First, there is a
disconnect in the sharing pattern between the search and training steps, where
weights are warped for layers of different sizes during the search to measure
similarity, but not during training, resulting in reduced performance. To
address this, we generate layer weights by learning to compose sets of
SuperWeights, which represent a group of trainable parameters. These
SuperWeights are created to be large enough so they can be used to represent
any layer in the network, but small enough that they are computationally
efficient. The second drawback we address is the method of measuring similarity
between shared parameters. Whereas prior work compared the weights themselves,
we argue this does not take into account the amount of conflict between the
shared weights. Instead, we use gradient information to identify layers with
shared weights that wish to diverge from each other. We demonstrate that our
SuperWeight Networks consistently boost performance over the state-of-the-art
on the ImageNet and CIFAR datasets in the NPAS setting. We further show that
our approach can generate parameters for many network architectures using the
same set of weights. This enables us to support tasks like efficient ensembling
and anytime prediction, outperforming fully-parameterized ensembles with 17%
fewer parameters.
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We show how temperature-induced disorder can be combined in a direct way with
first-principles scattering theory to study diffusive transport in real
materials. Excellent (good) agreement with experiment is found for the
resistivity of Cu, Pd, Pt (and Fe) when lattice (and spin) disorder are
calculated from first principles. For Fe, the agreement with experiment is
limited by how well the magnetization (of itinerant ferromagnets) can be
calculated as a function of temperature. By introducing a simple Debye-like
model of spin disorder parameterized to reproduce the experimental
magnetization, the temperature dependence of the average resistivity, the
anisotropic magnetoresistance and the spin polarization of a Ni$_{80}$Fe$_{20}$
alloy are calculated and found to be in good agreement with existing data.
Extension of the method to complex, inhomogeneous materials as well as to the
calculation of other finite-temperature physical properties within the
adiabatic approximation is straightforward.
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The electromagnetic transition of two-level atomic systems in a waveguide is
calculated. Compared with the result in free space, the spontaneous emission
rate decrease because the phase space is smaller, and meanwhile, some resonance
appears in some cases. Moreover, the influence of non-uniform electromagnetic
field in a waveguide on absorption and stimulated emission is considered.
Applying the results to lasers, a method to enhance the laser power is
proposed.
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We discuss the iron and nickel properties in the nuclear X-ray reflecting
region of the Circinus Galaxy, studied with XMM-Newton. The main results are:
a) from the depth of the Fe Kalpha edge, a value of A_Fe=1.7 in number with
respect to the cosmic value (as for Anders & Grevesse 1989) is measured, if the
(not directly visible) illuminating spectrum is assumed to be that measured by
BeppoSAX. If the slope of the primary power law is left free to vary, a steeper
spectrum and a lower iron abundance (about 1.2) are found. b) From the Ni to Fe
Kalpha lines flux ratio, a nickel-to-iron abundance ratio of 0.055-0.075 is
found. c) The Fe Kbeta/Kalpha flux ratio is slightly lower than expected,
possibly due to a mild ionization of iron (which however cannot be much more
ionized than X). d) The presence of the Fe Kalpha Compton Shoulder, already
discovered by Chandra, is confirmed, its relative flux implying Compton-thick
matter. This further supports the identification of the reflecting region with
the absorber.
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The performance of stochastic gradient descent (SGD), which is the simplest
first-order optimizer for training deep neural networks, depends on not only
the learning rate but also the batch size. They both affect the number of
iterations and the stochastic first-order oracle (SFO) complexity needed for
training. In particular, the previous numerical results indicated that, for SGD
using a constant learning rate, the number of iterations needed for training
decreases when the batch size increases, and the SFO complexity needed for
training is minimized at a critical batch size and that it increases once the
batch size exceeds that size. Here, we study the relationship between batch
size and the iteration and SFO complexities needed for nonconvex optimization
in deep learning with SGD using constant or decaying learning rates and show
that SGD using the critical batch size minimizes the SFO complexity. We also
provide numerical comparisons of SGD with the existing first-order optimizers
and show the usefulness of SGD using a critical batch size. Moreover, we show
that measured critical batch sizes are close to the sizes estimated from our
theoretical results.
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Due to their inherent compliance, soft robots are more versatile than rigid
linked robots when they interact with their environment, such as object
manipulation or biomimetic motion, and considered the key element in
introducing robots to everyday environments. Although various soft robotic
actuators exist, past research has focused primarily on designing and analyzing
single components. Limited effort has been made to combine each component to
create an overall capable, integrated soft robot. Ideally, the behavior of such
a robot can be accurately modeled, and its motion within an environment uses
its proprioception, without requiring external sensors. This work presents a
design and modeling process for a Soft continuum Proprioceptive Arm (SoPrA)
actuated by pneumatics. The integrated design is suitable for an analytical
model due to its internal capacitive flex sensor for proprioceptive
measurements and its fiber-reinforced fluidic elastomer actuators. The proposed
analytical dynamical model accounts for the inertial effects of the actuator's
mass and the material properties, and predicts in real-time the soft robot's
behavior. Our estimation method integrates the analytical model with
proprioceptive sensors to calculate external forces, all without relying on an
external motion capture system. SoPrA is validated in a series of experiments
demonstrating the model's and sensor's accuracy in estimation. SoPrA will
enable soft arm manipulation including force sensing while operating in
obstructed environments that disallows exteroceptive measurements.
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In this paper we present a combinatorial proof of a relation between the
generating functions of unicellular and bicellular maps. This relation is a
consequence of the Schwinger-Dyson equation of matrix theory. Alternatively it
can be proved using representation theory of the symmetric group. Here we give
a bijective proof by rewiring unicellular maps of topological genus $(g+1)$
into bicellular maps of genus $g$ and pairs of unicellular maps of lower
topological genera. Our result has immediate consequences for the folding of
RNA interaction structures, since the time complexity of folding the
transformed structure is $O((n+m)^5)$, where $n,m$ are the lengths of the
respective backbones, while the folding of the original structure has $O(n^6)$
time complexity, where $n$ is the length of the longer sequence.
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There is a growing interest in social robots to be considered in the therapy
of children with autism due to their effectiveness in improving the outcomes.
However, children on the spectrum exhibit challenging behaviors that need to be
considered when designing robots for them. A child could involuntarily throw a
small social robot during meltdown and that could hit another person's head and
cause harm (e.g. concussion). In this paper, the application of soft materials
is investigated for its potential in attenuating head's linear acceleration
upon impact. The thickness and storage modulus of three different soft
materials were considered as the control factors while the noise factor was the
impact velocity. The design of experiments was based on Taguchi method. A total
of 27 experiments were conducted on a developed dummy head setup that reports
the linear acceleration of the head. ANOVA tests were performed to analyze the
data. The findings showed that the control factors are not statistically
significant in attenuating the response. The optimal values of the control
factors were identified using the signal-to-noise (S/N) ratio optimization
technique. Confirmation runs at the optimal parameters (i.e. thickness of 3 mm
and 5 mm) showed a better response as compared to other conditions. Designers
of social robots should consider the application of soft materials to their
designs as it help in reducing the potential harm to the head.
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We investigate the dynamics of clumps that coexisted with/in
advection-dominated accretion flows by considering thermal conductivity.
Thermal conduction can be one of the effective factors in the energy
transportation of ADAFs; hence it may indirectly affect the dynamics of clumps
by means of a contact force between them and their host medium. We first study
the ensemble of clumps by assuming them as collision-less particles and
secondly we find the orbital motion of these clouds as individuals. For both
parts, clumps are subject to the gravity of the central object and a drag
force. The strong coupling between clumps and ADAF leads to equality between
the average treatment of the clumps and the dynamics of their background. By
employing the collision-less Boltzmann equation we calculate the velocity
dispersion of the clumps which turns out approximately one order of magnitude
higher than the ADAF. In fact, involving drag force in such a system causes the
angular momentum of the clumps can be transported outwards by the ADAF, and
hence the clouds eventually will be captured at the tidal radius. The results
show that the presence of thermal conduction increases the root of the averaged
radial velocity square and this in turn speeds up the process of capturing the
clouds through the tidal force. In the end, we focus on a typical individual
cloud, the spiral orbits appear thanks to only the toroidal component of
friction force. The parametric study again proves that the operation of thermal
conduction helps for decreasing the lifetime of clumps.
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Three-dimensional (3D) magnetic nulls are abundant in the solar atmosphere,
as been firmly established through contemporary observations. They are
established to be important magnetic structures in, for example, jets and
circular ribbon flares. While simulations and extrapolations support this, the
mechanisms behind 3D null generation remain an open question. Recent
magnetohydrodynamics (MHD) simulations propose that magnetic reconnection is
responsible for both generating and annihilating 3D nulls, a novel concept.
However, these simulations began with initial magnetic fields already
supporting pre-existing nulls, raising the question of whether magnetic
reconnection can create nulls in fields initially devoid of them. Previously,
this question was briefly explored in a simulation with an initial chaotic
magnetic field. However, the study failed to precisely identify locations,
topological degrees, and natures (spiral or radial) of nulls, and it
approximated magnetic reconnection without fully tracking field line in time.
In this paper these findings are revisited in light of recent advancements and
tools used to locate and trace nulls, along with the tracing of field lines,
through which the concept of generation/annihilation of 3D nulls from chaotic
fields is established in a precise manner.
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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.