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To improve the usability of a revision history, change untangling, which
reconstructs the history to ensure that changes in each commit belong to one
intentional task, is important. Although there are several untangling
approaches based on the clustering of fine-grained editing operations of source
code, they often produce unsuitable result for a developer, and manual
tailoring of the result is necessary. In this paper, we propose
ChangeBeadsThreader (CBT), an interactive environment for splitting and merging
change clusters to support the manual tailoring of untangled changes. CBT
provides two features: 1) a two-dimensional space where fine-grained change
history is visualized to help users find the clusters to be merged and 2) an
augmented diff view that enables users to confirm the consistency of the
changes in a specific cluster for finding those to be split. These features
allow users to easily tailor automatically untangled changes.
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The linear Navier-Stokes equations in three dimensions are given by:
$u_{it}(x,t)-\rho \triangle u_i(x,t)-p_{x_i}(x,t)=$ $w_i(x,t)$ , $div
\textbf{u}(x,t)=0,i=1,2,3$ with initial conditions:
$\textbf{u}|_{(t=0)\bigcup\partial\Omega}=0$. The Green function to the
Dirichlet problem $\textbf{u}|_{(t=0)\bigcup\partial\Omega}=0$ of the equation
$u_{it}(x,t)-\rho\triangle u_i(x,t)=f_i(x,t)$ present as:
$G(x,t;\xi,\tau)=Z(x,t;\xi,\tau)+V(x,t;\xi,\tau).$ Where
$Z(x,t;\xi,\tau)=\frac{1}{8\pi^{3/2}(t-\tau)^{3/2}}\cdot
e^{-\frac{(x_1-\xi_1)^2+(x_2-\xi_2)^2+(x_3-\xi_3)^2}{4(t-\tau)}}$ is the
fundamental solution to this equation and $V(x,t;\xi,\tau)$ is the smooth
function of variables $(x,t;\xi,\tau)$. The construction of the function
$G(x,t;\xi,\tau)$ is resulted in the book [1 p.106]. By the Green function we
present the Navier-Stokes equation as:
$u_i(x,t)=\int_0^t\int_{\Omega}\Big(Z(x,t;\xi,\tau)+V(x,t;\xi,\tau)\Big)\frac{dp(\xi,\tau)}{d\xi}d\xi
d\tau +\int_0^t\int_{\Omega}G(x,t;\xi,\tau)w_i(\xi,\tau)d\xi d\tau$. But $div
\textbf{u}(x,t)=\sum_1^3 \frac{du_i(x,t)}{dx_i}=0.$ Using these equations and
the following properties of the fundamental function: $Z(x,t;\xi,\tau)$:
$\frac{dZ(x,t;\xi,\tau)}{d x_i}=-\frac{d Z(x,t; \xi,\tau)}{d \xi_i},$ for the
definition of the unknown pressure p(x,t) we shall receive the integral
equation. From this integral equation we define the explicit expression of the
pressure: $p(x,t)=-\frac{d}{dt}\triangle^{-1}\ast\int_0^t\int_{\Omega}\sum_1^3
\frac{dG(x,t;\xi,\tau)}{dx_i}w_i(\xi,\tau)d\xi
d\tau+\rho\cdot\int_0^t\int_{\Omega}\sum_1^3\frac{dG(x,t;\xi,\tau)}{dx_i}w_i(\xi,\tau)d\xi
d\tau.$ By this formula the following estimate:
$\int_0^t\sum_1^3\Big\|\frac{\partial p(x,\tau)}{\partial
x_i}\Big\|_{L_2(\Omega)}^2 d
\tau<c\cdot\int_0^t\sum_1^3\|w_i(x,\tau)\|_{L_2(\Omega)}^2 d\tau$ holds.
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We find it is common for consumers who are not in financial distress to make
credit card payments at or close to the minimum. This pattern is difficult to
reconcile with economic factors but can be explained by minimum payment
information presented to consumers acting as an anchor that weighs payments
down. Building on Stewart (2009), we conduct a hypothetical credit card payment
experiment to test an intervention to de-anchor payment choices. This
intervention effectively stops consumers selecting payments at the contractual
minimum. It also increases their average payments, as well as shifting the
distribution of payments. By de-anchoring choices from the minimum, consumers
increasingly choose the full payment amount - which potentially seems to act as
a target payment for consumers. We innovate by linking the experimental
responses to survey responses on financial distress and to actual credit card
payment behaviours. We find that the intervention largely increases payments
made by less financially-distressed consumers. We are also able to evaluate the
potential external validity of our experiment and find that hypothetical
responses are closely related to consumers' actual credit card payments.
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This is the construction proposal for the STAR Event Plane Detector (EPD). It
discusses design considerations, simulations, and physics motivations for the
device. It also covers other important details such as connector construction,
cost schedule and radiation hardness of the epoxy. This proposal was submitted
to STAR in May 2016 and approved shortly thereafter. The device was
subsequently constructed and installed into STAR. The design evolved somewhat
between the proposal and final construction, but this document contains useful
details not found elsewhere. A manuscript detailing the device as constructed
has been posted at arXiv:1912.05243.
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Thanks to its capability of classifying complex phenomena without explicit
modeling, deep learning (DL) has been demonstrated to be a key enabler of
Wireless Signal Classification (WSC). Although DL can achieve a very high
accuracy under certain conditions, recent research has unveiled that the
wireless channel can disrupt the features learned by the DL model during
training, thus drastically reducing the classification performance in
real-world live settings. Since retraining classifiers is cumbersome after
deployment, existing work has leveraged the usage of carefully-tailored Finite
Impulse Response (FIR) filters that, when applied at the transmitter's side,
can restore the features that are lost because of the the channel actions,
i.e., waveform synthesis. However, these approaches compute FIRs using offline
optimization strategies, which limits their efficacy in highly-dynamic channel
settings. In this paper, we improve the state of the art by proposing Chares, a
Deep Reinforcement Learning (DRL)-based framework for channel-resilient
adaptive waveform synthesis. Chares adapts to new and unseen channel conditions
by optimally computing through DRL the FIRs in real-time. Chares is a DRL agent
whose architecture is-based upon the Twin Delayed Deep Deterministic Policy
Gradients (TD3), which requires minimal feedback from the receiver and explores
a continuous action space. Chares has been extensively evaluated on two
well-known datasets. We have also evaluated the real-time latency of Chares
with an implementation on field-programmable gate array (FPGA). Results show
that Chares increases the accuracy up to 4.1x when no waveform synthesis is
performed, by 1.9x with respect to existing work, and can compute new actions
within 41us.
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In this paper we consider the problem of packing a symplectic manifold with
integral Lagrangian tori, that is Lagrangian tori whose area homomorphsims take
only integer values. We prove that the Clifford torus in $S^2 \times S^2$ is a
maximal integral packing, in the sense that any other integral Lagranian torus
must intersect it. In the other direction, we show that in any symplectic
polydisk $P(a,b)$ with $a,b>2$, there is at least one integral Lagrangian torus
in the complement of the collection of standard product integral Lagrangian
tori.
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We present a chemical-composition analysis of 77 red-giant stars in Omega
Centauri. We have measured abundances for carbon and nitrogen, and combined our
results with abundances of O, Na, La, and Fe that we determined in our previous
work. Our aim is to better understand the peculiar chemical-enrichment history
of this cluster, by studying how the total C+N+O content varies among the
different-metallicity stellar groups, and among stars at different places along
the Na-O anticorrelation. We find the (anti)correlations among the light
elements that would be expected on theoretical ground for matter that has been
nuclearly processed via high-temperature proton captures. The overall
[(C+N+O)/Fe] increases by 0.5 dex from [Fe/H] -2.0 to [Fe/H] -0.9. Our results
provide insight into the chemical-enrichment history of the cluster, and the
measured CNO variations provide important corrections for estimating the
relative ages of the different stellar populations.
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In this paper, we propose an ensemble learning algorithm named \textit{bagged
$k$-distance for mode-based clustering} (\textit{BDMBC}) by putting forward a
new measurement called the \textit{probability of localized level sets}
(\textit{PLLS}), which enables us to find all clusters for varying densities
with a global threshold. On the theoretical side, we show that with a properly
chosen number of nearest neighbors $k_D$ in the bagged $k$-distance, the
sub-sample size $s$, the bagging rounds $B$, and the number of nearest
neighbors $k_L$ for the localized level sets, BDMBC can achieve optimal
convergence rates for mode estimation. It turns out that with a relatively
small $B$, the sub-sample size $s$ can be much smaller than the number of
training data $n$ at each bagging round, and the number of nearest neighbors
$k_D$ can be reduced simultaneously. Moreover, we establish optimal convergence
results for the level set estimation of the PLLS in terms of Hausdorff
distance, which reveals that BDMBC can find localized level sets for varying
densities and thus enjoys local adaptivity. On the practical side, we conduct
numerical experiments to empirically verify the effectiveness of BDMBC for mode
estimation and level set estimation, which demonstrates the promising accuracy
and efficiency of our proposed algorithm.
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We introduce in this article a new method to estimate the minimum distance of
codes from algebraic surfaces. This lower bound is generic, i.e. can be applied
to any surface, and turns out to be ``liftable'' under finite morphisms, paving
the way toward the construction of good codes from towers of surfaces. In the
same direction, we establish a criterion for a surface with a fixed finite set
of closed points $\mathcal P$ to have an infinite tower of $\ell$--\'etale
covers in which $\mathcal P$ splits totally. We conclude by stating several
open problems. In particular, we relate the existence of asymptotically good
codes from general type surfaces with a very ample canonical class to the
behaviour of their number of rational points with respect to their $K^2$ and
coherent Euler characteristic.
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In this note, with the help of the boundary classification of diffusions, we
derive a criterion of the convergence of perpetual integral functionals of
transient real-valued diffusions. In the particular case of transient Bessel
processes, we note that this criterion agrees with the one obtained via
Jeulin's convergence lemma.
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We calculate the leading power corrections to the decay rates, distributions
and hadronic spectral moments in rare inclusive \bxsll decays in the standard
model, using heavy quark expansion (HQE) in $(1/m_b)$ and a phenomenological
model implementing the Fermi motion effects of the b-quark bound in the
B-hadron. We include next-to-leading order perturbative QCD corrections and
work out the dependences of the spectra, decay rates and hadronic moments on
the model parameters in either HQE and the Fermi motion model. In the latter,
we take into account long-distance effects via $B \to X_s +(J/\psi,
\psi^\prime,...) \to X_s \ell^+ \ell^- $ with a vector meson dominance ansatz
and study the influence of kinematical cuts in the dilepton and hadronic
invariant masses on branching ratios, hadron spectra and hadronic moments. We
present leading logarithmic QCD corrections to the $b \to s \gamma\gamma$
amplitude. The QCD perturbative improved $B_{s}\to\gamma\gamma$ branching ratio
is given in the standard model including our estimate of long-distance effects
via $B_s \to \phi \gamma \to \gamma \gamma$ and $B_s \to \phi \psi \to \phi
\gamma \to \gamma \gamma$ decays. The uncertainties due to the renormalization
scale and the parameters of the HQE inspired bound state model are worked out.
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The prevalent use of Large Language Models (LLMs) has necessitated studying
their mental models, yielding noteworthy theoretical and practical
implications. Current research has demonstrated that state-of-the-art LLMs,
such as ChatGPT, exhibit certain theory of mind capabilities and possess
relatively stable Big Five and/or MBTI personality traits. In addition,
cognitive process features form an essential component of these mental models.
Research in cultural psychology indicated significant differences in the
cognitive processes of Eastern and Western people when processing information
and making judgments. While Westerners predominantly exhibit analytical
thinking that isolates things from their environment to analyze their nature
independently, Easterners often showcase holistic thinking, emphasizing
relationships and adopting a global viewpoint. In our research, we probed the
cultural cognitive traits of ChatGPT. We employed two scales that directly
measure the cognitive process: the Analysis-Holism Scale (AHS) and the Triadic
Categorization Task (TCT). Additionally, we used two scales that investigate
the value differences shaped by cultural thinking: the Dialectical Self Scale
(DSS) and the Self-construal Scale (SCS). In cognitive process tests (AHS/TCT),
ChatGPT consistently tends towards Eastern holistic thinking, but regarding
value judgments (DSS/SCS), ChatGPT does not significantly lean towards the East
or the West. We suggest that the result could be attributed to both the
training paradigm and the training data in LLM development. We discuss the
potential value of this finding for AI research and directions for future
research.
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The nonlinear evolution of the m=1 internal kink mode is studied numerically
in a setting where the tokamak core plasma is surrounded by a turbulent region
with low magnetic shear. As a starting point we choose configurations with
three nearby q=1 surfaces where triple tearing modes (TTMs) with high poloidal
mode numbers m are unstable. While the amplitudes are still small, the fast
growing high-m TTMs enhance the growth of the m=1 instability. This is
interpreted as a fast sawtooth trigger mechanism. The TTMs lead to a partial
collapse, leaving behind a turbulent belt with q ~= 1 around the unreconnected
core plasma. Although, full reconnection can occur if the core displacement
grows large enough, it is shown that the turbulence may actively prevent
further reconnection. This is qualitatively similar to experimentally observed
partial sawtooth crashes with post-cursor oscillations due to a saturated
internal kink.
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We calculate the spectrum of the scattered light from quantum degenerate
atomic gases obeying Bose-Einstein statistics. The atoms are assumed to occupy
two ground states which are optically coupled through a common excited state by
two low intensity off-resonant light beams. In the presence of a Bose
condensate in both ground states, the atoms may exhibit light induced
oscillations between the two condensates analogous to the Josephson effect. The
spectrum of the scattered light is calculated in the limit of a low oscillation
frequency. In the spectrum we are able to observe qualitative features
depending on the phase difference between the macroscopic wave functions of the
two condensates. Thus, our optical scheme could possibly be used as an
experimental realization of the spontaneous breakdown of the U(1) gauge
symmetry in the Bose-Einstein condensation.
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We solve the Euclidean Einstein equations with non-Abelian gauge fields of
sufficiently large symmetry in various dimensions. In higher-dimensional
spaces, we find the solutions which are similar to so-called scalar wormholes.
In four-dimensional space-time, we find singular wormhole solutions with
infinite Euclidean action. Wormhole solutions in the three-dimensional
Einstein-Yang-Mills theory with a Chern-Simons term are also constructed.
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We reinvestigate the recently discovered bifurcation phase transition in
Causal Dynamical Triangulations (CDT) and provide further evidence that it is a
higher order transition. We also investigate the impact of introducing matter
in the form of massless scalar fields to CDT. We discuss the impact of scalar
fields on the measured spatial volumes and fluctuation profiles in addition to
analysing how the scalar fields influence the position of the bifurcation
transition.
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Most research into anti-phishing defence assumes that the mal-actor is
attempting to harvest end-users' personally identifiable information or login
credentials and, hence, focuses on detecting phishing websites. The defences
for this type of attack are usually activated after the end-user clicks on a
link, at which point the link is checked. This is known as after-the-click
detection. However, more sophisticated phishing attacks (such as spear-phishing
and whaling) are rarely designed to get the end-user to visit a website.
Instead, they attempt to get the end-user to perform some other action, for
example, transferring money from their bank account to the mal-actors account.
These attacks are rarer, and before-the-click defence has been investigated
less than after-the-click defence. To better integrate and contextualize these
studies in the overall anti-phishing research, this paper presents a systematic
literature review of proposed anti-phishing defences. From a total of 6330
papers, 21 primary studies and 335 secondary studies were identified and
examined. The current research was grouped into six primary categories,
blocklist/allowlist, heuristics, content, visual, artificial
intelligence/machine learning and proactive, with an additional category of
"other" for detection techniques that do not fit into any of the primary
categories. It then discusses the performance and suitability of using these
techniques for detecting phishing emails before the end-user even reads the
email. Finally, it suggests some promising areas for further research.
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Using the full data sample collected with the Belle detector at the KEKB
asymmetric-energy $e^+e^-$ collider, we present CP violation in charm decays.
The $D^0-\bar{D}^0$ mixing parameter
$y_{CP}$ and indirect CP violation parameter $A_{\Gamma}$ in
$D^0\rightarrow h^+h^-$ decays are reported, where $h$ denotes $K$ and $\pi$.
The preliminary results are
$y_{CP}=(1.11\pm0.22\pm0.11)%$ and
$A_{\Gamma}=(-0.03\pm0.20\pm0.08)%$. We also report searches for
CP violation in $D^0\rightarrow h^+h^-$ and $D^+\rightarrow K^0_S
K^+$ decays. No evidence for CP violation in $D^0\rightarrow h^+h^-$ is
observed with $A^{KK}_{CP}=(-0.32\pm0.21\pm0.09)%$ and
$A^{\pi\pi}_{CP}=(+0.55\pm0.36\pm0.09)%$. The CP asymmetry difference between
$D^0\rightarrow K^+K^-$ and
$D^0\rightarrow\pi^+\pi^-$ decays is measured with $\Delta
A^{hh}_{CP}=(-0.87\pm0.41\pm0.06)%$. The CP asymmetry in
$D^+\rightarrow K^0_S K^+$ decay is measured to be
$(-0.25\pm0.28\pm0.14)%$. After subtracting CP violation due to
$K^0-\bar{K}^0$ mixing, the CP asymmetry in
$D^+\rightarrow\bar{K}^0 K^+$ decay is found to be
$(+0.08\pm0.28\pm0.14)%$.
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The nature of subproton scale fluctuations in the solar wind is an open
question, partly because two similar types of electromagnetic turbulence can
occur: kinetic Alfven turbulence and whistler turbulence. These two
possibilities, however, have one key qualitative difference: whistler
turbulence, unlike kinetic Alfven turbulence, has negligible power in density
fluctuations. In this Letter, we present new observational data, as well as
analytical and numerical results, to investigate this difference. The results
show, for the first time, that the fluctuations well below the proton scale are
predominantly kinetic Alfven turbulence, and, if present at all, the whistler
fluctuations make up only a small fraction of the total energy.
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Although neural sequence-to-sequence models have been successfully applied to
semantic parsing, they fail at compositional generalization, i.e., they are
unable to systematically generalize to unseen compositions of seen components.
Motivated by traditional semantic parsing where compositionality is explicitly
accounted for by symbolic grammars, we propose a new decoding framework that
preserves the expressivity and generality of sequence-to-sequence models while
featuring lexicon-style alignments and disentangled information processing.
Specifically, we decompose decoding into two phases where an input utterance is
first tagged with semantic symbols representing the meaning of individual
words, and then a sequence-to-sequence model is used to predict the final
meaning representation conditioning on the utterance and the predicted tag
sequence. Experimental results on three semantic parsing datasets show that the
proposed approach consistently improves compositional generalization across
model architectures, domains, and semantic formalisms.
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We demonstrate that in photonic gap antennas composed of an epsilon-near-zero
(ENZ) layer embedded within a high-index dielectric, hybrid modes emerge from
the strong coupling between the ENZ thin film and the photonic modes of the
dielectric antenna. These hybrid modes show giant electric field enhancements,
large enhancements of the far-field spontaneous emission rate and a
unidirectional radiation response. We analyze both parent and hybrid modes
using quasinormal mode theory and find that the hybridization can be well
understood using a coupled oscillator model. Under plane wave illumination,
hybrid ENZ antennas can concentrate light with an electric field amplitude
$\sim$100 times higher than that of the incident wave, which places them on par
with the best plasmonic antennas. In addition, the far-field spontaneous
emission rate of a dipole embedded at the antenna hotspot reaches up to
$\sim$2300 that in free space, with nearly perfect unidirectional emission.
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Particle therapy is an established method to treat deep-seated tumours using
accelerator-produced ion beams. For treatment planning, the precise knowledge
of the relative stopping power (RSP) within the patient is vital. Conversion
errors from x-ray computed tomography (CT) measurements to RSP introduce
uncertainties in the applied dose distribution. Using a proton computed
tomography (pCT) system to measure the SP directly could potentially increase
the accuracy of treatment planning. A pCT demonstrator, consisting of
double-sided silicon strip detectors (DSSD) as tracker and plastic scintillator
slabs coupled to silicon photomultipliers (SiPM) as a range telescope, was
developed. After a significant hardware upgrade of the range telescope, a 3D
tomogram of an aluminium stair phantom was recorded at the MedAustron facility
in Wiener Neustadt, Austria. In total, 80 projections with 6.5x10^5 primary
events were acquired and used for the reconstruction of the RSP distribution in
the phantom. After applying a straight-line approximation for the particle path
inside the phantom, the most probable value (MPV) of the RSP distribution could
be measured with an accuracy of 0.59%. The RSP resolution inside the phantom
was only 9.3% due to a limited amount of projections and measured events per
projection.
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Nonlinear Schr\"odinger equation (with the Schwarzian initial data) is
important in nonlinear optics, Bose condensation and in the theory of strongly
correlated electrons. The asymptotic solutions in the region $x/t={\cal O}(1)$,
$t\to\infty$, can be represented as a double series in $t^{-1}$ and $\ln t$.
Our current purpose is the description of the asymptotics of the coefficients
of the series.
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We predict hyper-entanglement generation during binary scattering of
mesoscopic bound states, solitary waves in Bose-Einstein condensates containing
thousands of identical Bosons. The underlying many-body Hamiltonian must not be
integrable, and the pre-collision quantum state of the solitons fragmented.
Under these conditions, we show with pure state quantum field simulations that
the post-collision state will be hyper-entangled in spatial degrees of freedom
and atom number within solitons, for realistic parameters. The effect links
aspects of non-linear systems and quantum-coherence and the entangled
post-collision state challenges present entanglement criteria for identical
particles. Our results are based on simulations of colliding quantum solitons
in a quintic interaction model beyond the mean-field, using the truncated
Wigner approximation.
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Observations by the Large Area Telescope (LAT) on the \textit{Fermi} mission
of diffuse $\gamma$-rays in a mid-latitude region in the third quadrant
(Galactic longitude $l$ from $200\arcdeg$ to $260\arcdeg$ and latitude $| b |$
from $22\arcdeg$ to $60\arcdeg$) are reported. The region contains no known
large molecular cloud and most of the atomic hydrogen is within 1 kpc of the
solar system. The contributions of $\gamma$-ray point sources and inverse
Compton scattering are estimated and subtracted. The residual $\gamma$-ray
intensity exhibits a linear correlation with the atomic gas column density in
energy from 100 MeV to 10 GeV. The measured integrated $\gamma$-ray emissivity
is $(1.63 \pm 0.05) \times 10^{-26} {\rm photons s^{-1} sr^{-1}
H\mathchar`-atom^{-1}}$ and $(0.66 \pm 0.02) \times 10^{-26} {\rm photons
s^{-1} sr^{-1} H\mathchar`-atom^{-1}}$ above 100 MeV and above 300 MeV,
respectively, with additional systematic error of $\sim 10%$. The differential
emissivity in 100 MeV--10 GeV agrees with calculations based on cosmic ray
spectra consistent with those directly measured, at the 10% level. The results
obtained indicate that cosmic ray nuclei spectra within 1 kpc from the solar
system in regions studied are close to the local interstellar spectra inferred
from direct measurements at the Earth within $\sim 10%$.
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The TREC 2017 Common Core Track aimed at gathering a diverse set of
participating runs and building a new test collection using advanced pooling
methods.
In this paper, we describe the participation of the IlpsUvA team at the TREC
2017 Common Core Track. We submitted runs created using two methods to the
track: (1) BOIR uses Bayesian optimization to automatically optimize retrieval
model hyperparameters. (2) NVSM is a latent vector space model where
representations of documents and query terms are learned from scratch in an
unsupervised manner.
We find that BOIR is able to optimize hyperparameters as to find a system
that performs competitively amongst track participants. NVSM provides rankings
that are diverse, as it was amongst the top automated unsupervised runs that
provided the most unique relevant documents.
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From pressure and surface dilation measurements, we show that a
solid-liquid-type transition occurs at low excitation frequencies in vertically
vibrated granular layers. This transition precedes subharmonic bifurcations
from flat surface to standing wave patterns, indicating that these waves are in
fact associated with the fluid like behavior of the layer. In the limit of high
excitation frequencies, we show that a new kind of subharmonic waves can be
distinguished. These waves do not involve any lateral transfer of grains within
the layer and correspond to excitations for which the layer slightly bends
alternately in time and space. These bending waves have very low amplitude and
we observe them in a vibrated two-dimensional layer of photoelastic particles.
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The overall aim of the software industry is to ensure delivery of high
quality software to the end user. To ensure high quality software, it is
required to test software. Testing ensures that software meets user
specifications and requirements. However, the field of software testing has a
number of underlying issues like effective generation of test cases,
prioritisation of test cases etc which need to be tackled. These issues demand
on effort, time and cost of the testing. Different techniques and methodologies
have been proposed for taking care of these issues. Use of evolutionary
algorithms for automatic test generation has been an area of interest for many
researchers. Genetic Algorithm (GA) is one such form of evolutionary
algorithms. In this research paper, we present a survey of GA approach for
addressing the various issues encountered during software testing.
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Explainable artificial intelligence has rapidly emerged since lawmakers have
started requiring interpretable models for safety-critical domains.
Concept-based neural networks have arisen as explainable-by-design methods as
they leverage human-understandable symbols (i.e. concepts) to predict class
memberships. However, most of these approaches focus on the identification of
the most relevant concepts but do not provide concise, formal explanations of
how such concepts are leveraged by the classifier to make predictions. In this
paper, we propose a novel end-to-end differentiable approach enabling the
extraction of logic explanations from neural networks using the formalism of
First-Order Logic. The method relies on an entropy-based criterion which
automatically identifies the most relevant concepts. We consider four different
case studies to demonstrate that: (i) this entropy-based criterion enables the
distillation of concise logic explanations in safety-critical domains from
clinical data to computer vision; (ii) the proposed approach outperforms
state-of-the-art white-box models in terms of classification accuracy and
matches black box performances.
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An analytical model is derived for the probability of failure (P-fail) to
spatially acquire an optical link with a jittering search beam. The analytical
model accounts for an arbitrary jitter spectrum and considers the associated
correlations between jitter excursions on adjacent tracks of the search spiral.
An expression of P-fail in terms of basic transcendental functions is found by
linearizing the exact analytical model with respect to the correlation
strength. Predictions from the models indicate a strong decrease of P-fail with
increasing correlation-strength, which is found to be in excellent agreement to
results from Monte Carlo simulations. The dependency of P-fail on track-width
and scan speed is investigated, confirming previous assumptions on the impact
of correlations. Expressions and applicable constraints are derived for the
limits of full and no correlations, and the optimal track width to minimize the
acquisition time is computed for a range of scan speeds. The model is
applicable to optical terminals equipped with a fast beam steering mirror, as
often found for optical communication missions in space.
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Scanning tunneling spectroscopy was performed on single crystals of
superconducting 2H-NbSe2, at 300 mK and in a magnetic field, up to 5 T, applied
parallel to the ab-plane. This novel field geometry allows the quasiparticle
density-of-states spectrum to be measured under finite superfluid momentum,
while avoiding contributions from the vortex-core bound states. At zero field,
we observed a fully-gapped conductance spectrum with both gap-edge peaks and
sub-gap kinks. These spectral features show a systematic evolution with the
applied field: the kinks close in while the peaks move apart in low fields, and
the zero-bias conductance has a two-sloped behavior over the entire field
range, though dipping anomalously at 0.7 T. Our data was analyzed with recent
theoretical models for quasiparticle tunneling into a current-carrying
superconductor, and yielded distinct evidence for multiple superconducting gaps
coming from various Fermi-surface sheets of different topologies, as well as
possible implications on the origin of the coexisting charge-density-wave
order.
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In many areas of physics, the Kramers-Kronig (KK) relations are used to
extract information about the real part of the optical response of a medium
from its imaginary counterpart. In this paper we discuss an alternative but
mathematically equivalent approach based on the Hilbert transform. We apply the
Hilbert transform to transmission spectra to find the group and refractive
indices of a Cs vapor, and thereby demonstrate how the Hilbert transform allows
indirect measurement of the refractive index, group index and group delay
whilst avoiding the use of complicated experimental set ups.
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In this paper we develop new methods of study of generalized normal
homogeneous Riemannian manifolds. In particular, we obtain a complete
classification of generalized normal homogeneous Riemannian metrics on spheres.
We prove that for any connected (almost effective) transitive on $S^n$ compact
Lie group $G$, the family of $G$-invariant Riemannian metrics on $S^n$ contains
generalized normal homogeneous but not normal homogeneous metrics if and only
if this family depends on more than one parameters. Any such family (that
exists only for $n=2k+1$) contains a metric $g_{\can}$ of constant sectional
curvature 1 on $S^n$. We also prove that $(S^{2k+1}, g_{\can})$ is
Clifford-Wolf homogeneous, and therefore generalized normal homogeneous, with
respect to $G$ (excepting the groups $G=SU(k+1)$ with odd $k+1$). The space of
unit Killing vector fields on $(S^{2k+1}, g_{\can})$ from Lie algebra
$\mathfrak{g}$ of Lie group $G$ is described as some symmetric space (excepting
the case $G=U(k+1)$ when one obtains the union of all complex Grassmannians in
$\mathbb{C}^{k+1}$).
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Seal in classical information is simply impossible. Since classical
information can be easily copied any number of times. Based on quantum
information, esp. quantum unclonable theorem, quantum seal maybe constructed
perfectly. But it is shown that perfect quantum seal is impossible, and the
success probability is bounded. In this paper, we show how to exceed the
optimal bound by using the TCF (Trapdoor Claw Free) functions, which can be
constructed based on LWE assumption. Hence it is post-quantum secure.
|
In this work, the relation between input-to-state stability and integral
input-to-state stability is studied for linear infinite-dimensional systems
with an unbounded control operator. Although a special focus is laid on the
case $L^{\infty}$, general function spaces are considered for the inputs. We
show that integral input-to-state stability can be characterized in terms of
input-to-state stability with respect to Orlicz spaces. Since we consider
linear systems, the results can also be formulated in terms of admissibility.
For parabolic diagonal systems with scalar inputs, both stability notions with
respect to $L^\infty$ are equivalent.
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A crossover between logarithmic and exponential temperature dependence of the
conductance (weak and strong localization) has been observed in ultrathin films
of metals deposited onto substrates held at liquid helium temperatures. The
resistance at the crossover is well defined by the onset of a nearly linear
dependence of conductance on thickness at fixed temperature in a sequence of in
situ evaporated films. The results of a finite size scaling analysis treating
thickness as a control parameter suggest the existence of a T=0 quantum
critical point which we suggest is a charge, or electron glass melting
transition.
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This paper proposes a strategy for detecting the presence of a
gravito-magnetic field due to the rotation of the galactic dark halo. Visible
matter in galaxies rotates and dark matter, supposed to form a halo
incorporating barionic matter, rotates also, since it interacts gravitationally
with the rest. Pursuing the same line of reasoning, dark matter should produce
all gravitational effects predicted by general relativity, including a
gravito-magnetic field. I discuss a possible strategy for measuring that field.
The idea recovers the old Sagnac effect and proposes to use a triangle having
three Lagrange points of the Sun-Earth pair at its vertices. The asymmetry in
the times of flight along the loop in opposite directions is proportional to
the gravito-magnetic galactic field.
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Classical T Tauri stars (CTTS) are young (< 10 Myr), cool stars that actively
accrete matter from a disk. They show strong, broad and asymmetric, atomic FUV
emission lines. Neither the width, nor the line profile is understood. Likely,
different mechanisms influence the line profile; the best candidates are
accretion, winds and stellar activity. We monitored the C IV 1548/1550 Ang
doublet in the nearby, bright CTTS TW Hya with the Hubble Space Telescope
Cosmic Origin Spectrograph (HST/COS) to correlate it with i) the cool wind, as
seen in COS NUV Mg II line profiles, ii) the photometric period from joint
ground-based monitoring, iii) the accretion rate as determined from the UV
continuum, and iv) the Ha line profile from independent ground-based
observations. The observations span 10 orbits distributed over a few weeks to
cover the typical time scales of stellar rotation, accretion and winds. Here we
describe a model with intrinsically asymmetric C IV lines.
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In unparticle dark matter (unmatter) models the equation of state of the
unmatter is given by $p=\rho/(2d_U+1)$, where $d_U$ is the scaling factor.
Unmatter with such equations of state would have a significant impact on the
expansion history of the universe. Using type Ia supernovae (SNIa), the baryon
acoustic oscillation (BAO) measurements and the shift parameter of the cosmic
microwave background (CMB) to place constraints on such unmatter models we find
that if only the SNIa data is used the constraints are weak. However, with the
BAO and CMB shift parameter data added strong constraints can be obtained. For
the $\Lambda$UDM model, in which unmatter is the sole dark matter, we find that
$d_U > 60$ at 95% C.L. For comparison, in most unparticle physics models it is
assumed $d_U<2$. For the $\Lambda$CUDM model, in which unmatter co-exists with
cold dark matter, we found that the unmatter can at most make up a few percent
of the total cosmic density if $d_U<10$, thus it can not be the major component
of dark matter.
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Suppose agents can exert costly effort that creates nonrival, heterogeneous
benefits for each other. At each possible outcome, a weighted, directed network
describing marginal externalities is defined. We show that Pareto efficient
outcomes are those at which the largest eigenvalue of the network is 1. An
important set of efficient solutions, Lindahl outcomes, are characterized by
contributions being proportional to agents' eigenvector centralities in the
network. The outcomes we focus on are motivated by negotiations. We apply the
results to identify who is essential for Pareto improvements, how to
efficiently subdivide negotiations, and whom to optimally add to a team.
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The CLEO-c experiment, running at charm threshold, has measured many charmed
meson properties. Here I summarize results on leptonic and semileptonic decays
of D mesons, as well as measurements hadronic decay strong phases that are
relevant to the extraction of the CKM angle gamma from B decays.
|
The impact of atomic parity violation experiments on determination of the
weak mixing parameter $\sin^2 \theta$ and the Peskin-Takeuchi parameters $S$
and $T$ is reassessed in the light of recent electroweak measurements at LEP,
SLAC, and Fermilab. Since the weak charge $Q_W$ provides unique information on
$S$, its determination with a factor of four better accuracy than present
levels can have a noticeable effect on global fits. However, the measurement of
$\Delta Q_W / Q_W$ for two different isotopes provides primarily information on
$\sin^2 \theta$. To specify this quantity to an accuracy of $\pm 0.0004$,
comparable to that now provided by other electroweak experiments, one would
have to determine $\Delta Q_W/Q_W$ in cesium to about 0.1\% of its value, with
comparable demands for other nuclei. The relative merits of absolute
measurements of $Q_W$ and isotope ratios for discovering effects of new gauge
bosons are noted briefly.
|
We review the theory and phenomenology of heavy-quark symmetry, exclusive
weak decays of B mesons, inclusive decay rates and lifetimes of b hadrons.
|
In assistive robots, compliant actuator is a key component in establishing
safe and satisfactory physical human-robot interaction (pHRI). The performance
of compliant actuators largely depends on the stiffness of the elastic element.
Generally, low stiffness is desirable to achieve low impedance, high fidelity
of force control and safe pHRI, while high stiffness is required to ensure
sufficient force bandwidth and output force. These requirements, however, are
contradictory and often vary according to different tasks and conditions. In
order to address the contradiction of stiffness selection and improve
adaptability to different applications, we develop a reconfigurable rotary
series elastic actuator with nonlinear stiffness (RRSEAns) for assistive
robots. In this paper, an accurate model of the reconfigurable rotary series
elastic element (RSEE) is presented and the adjusting principles are
investigated, followed by detailed analysis and experimental validation. The
RRSEAns can provide a wide range of stiffness from 0.095 Nm/deg to 2.33 Nm/deg,
and different stiffness profiles can be yielded with respect to different
configuration of the reconfigurable RSEE. The overall performance of the
RRSEAns is verified by experiments on frequency response, torque control and
pHRI, which is adequate for most applications in assistive robots.
Specifically, the root-mean-square (RMS) error of the interaction torque
results as low as 0.07 Nm in transparent/human-in-charge mode, demonstrating
the advantages of the RRSEAns in pHRI.
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Radiation exposure in positron emission tomography (PET) imaging limits its
usage in the studies of radiation-sensitive populations, e.g., pregnant women,
children, and adults that require longitudinal imaging. Reducing the PET
radiotracer dose or acquisition time reduces photon counts, which can
deteriorate image quality. Recent deep-neural-network (DNN) based methods for
image-to-image translation enable the mapping of low-quality PET images
(acquired using substantially reduced dose), coupled with the associated
magnetic resonance imaging (MRI) images, to high-quality PET images. However,
such DNN methods focus on applications involving test data that match the
statistical characteristics of the training data very closely and give little
attention to evaluating the performance of these DNNs on new
out-of-distribution (OOD) acquisitions. We propose a novel DNN formulation that
models the (i) underlying sinogram-based physics of the PET imaging system and
(ii) the uncertainty in the DNN output through the per-voxel heteroscedasticity
of the residuals between the predicted and the high-quality reference images.
Our sinogram-based uncertainty-aware DNN framework, namely, suDNN, estimates a
standard-dose PET image using multimodal input in the form of (i) a
low-dose/low-count PET image and (ii) the corresponding multi-contrast MRI
images, leading to improved robustness of suDNN to OOD acquisitions. Results on
in vivo simultaneous PET-MRI, and various forms of OOD data in PET-MRI, show
the benefits of suDNN over the current state of the art, quantitatively and
qualitatively.
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Common meadows are fields expanded with a total inverse function. Division by
zero produces an additional value denoted with "a" that propagates through all
operations of the meadow signature (this additional value can be interpreted as
an error element). We provide a basis theorem for so-called common cancellation
meadows of characteristic zero, that is, common meadows of characteristic zero
that admit a certain cancellation law.
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A self-consistent non-minimal non-Abelian Einstein-Yang-Mills model,
containing three phenomenological coupling constants, is formulated. The ansatz
of a vanishing Yang-Mills induction is considered as a particular case of the
self-duality requirement for the gauge field. Such an ansatz is shown to allow
obtaining an exact solution of the self-consistent set of equations when the
space-time has a constant curvature. An example describing a pure magnetic
gauge field in the de Sitter cosmological model is discussed in detail.
|
A classic result by Bass says that the class of all projective modules is
covering, if and only if it is closed under direct limits. Enochs extended the
if-part by showing that every class of modules $\mathcal C$, which is
precovering and closed under direct limits, is covering, and asked whether the
converse is true. We employ the tools developed in [18] and give a positive
answer when $\mathcal C = \mathcal A$, or $\mathcal C$ is the class of all
locally $\mathcal A ^{\leq \omega}$-free modules, where $\mathcal A$ is any
class of modules fitting in a cotorsion pair $(\mathcal A, \mathcal B)$ such
that $\mathcal B$ is closed under direct limits. This setting includes all
cotorsion pairs and classes of locally free modules arising in
(infinite-dimensional) tilting theory. We also consider two particular
applications: to pure-semisimple rings, and artin algebras of infinite
representation type.
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Unsupervised anomalous sound detection aims to detect unknown abnormal sounds
of machines from normal sounds. However, the state-of-the-art approaches are
not always stable and perform dramatically differently even for machines of the
same type, making it impractical for general applications. This paper proposes
a spectral-temporal fusion based self-supervised method to model the feature of
the normal sound, which improves the stability and performance consistency in
detection of anomalous sounds from individual machines, even of the same type.
Experiments on the DCASE 2020 Challenge Task 2 dataset show that the proposed
method achieved 81.39\%, 83.48\%, 98.22\% and 98.83\% in terms of the minimum
AUC (worst-case detection performance amongst individuals) in four types of
real machines (fan, pump, slider and valve), respectively, giving 31.79\%,
17.78\%, 10.42\% and 21.13\% improvement compared to the state-of-the-art
method, i.e., Glow\_Aff. Moreover, the proposed method has improved AUC
(average performance of individuals) for all the types of machines in the
dataset. The source codes are available at
https://github.com/liuyoude/STgram_MFN
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In this paper we analyze so-called Parisian ruin probability that happens
when surplus process stays below zero longer than fixed amount of time
$\zeta>0$. We focus on general spectrally negative L\'{e}vy insurance risk
process. For this class of processes we identify expression for ruin
probability in terms of some other quantities that could be possibly calculated
explicitly in many models. We find its Cram\'{e}r-type and
convolution-equivalent asymptotics when reserves tends to infinity. Finally, we
analyze few explicit examples.
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We show a general method to solve 2+1 dimensional dilatonic Maxwell-Einstein
equation with a positive or negative cosmological constant. All the physical
solutions are listed with assumptions that they are static, rotationally
symmetric, and has a nonzero magnetic field and a nonzero dilaton field. On the
contrary to the magnetic solution without a dilaton field, some of the present
solutions with a dilaton field possess a horizon.
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Recently the Ihara zeta function for the finite graph was extended to
infinite one by Clair and Chinta et al. In this paper, we obtain the same
expressions by a different approach from their analytical method. Our new
approach is to take a suitable limit of a sequence of finite graphs via the
Konno-Sato theorem. This theorem is related to explicit formulas of
characteristic polynomials for the evolution matrix of the Grover walk. The
walk is one of the most well-investigated quantum walks which are quantum
counterpart of classical random walks. We call the relation between the Grover
walk and the zeta function based on the Konno-Sato theorem "Grover/Zeta
Correspondence" here.
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Titanium dioxide (TiO$_2$) plays a central role in the study of artificial
photosynthesis, owing to its ability to perform photocatalytic water splitting.
Despite over four decades of intense research efforts in this area, there is
still some debate over the nature of the first water monolayer on the
technologically-relevant anatase TiO$_2$ (101) surface. In this work we use
first-principles calculations to reverse-engineer the experimental
high-resolution X-ray photoelectron spectra measured for this surface in [Walle
et al., J. Phys. Chem. C 115, 9545 (2011)], and find evidence supporting the
existence of a mix of dissociated and molecular water in the first monolayer.
Using both semilocal and hybrid functional calculations we revise the current
understanding of the adsorption energetics by showing that the energetic cost
of water dissociation is reduced via the formation of a hydrogen-bonded
hydroxyl-water complex. We also show that such a complex can provide an
explanation of an unusual superstructure observed in high-resolution scanning
tunneling microscopy experiments.
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In this paper, we initiate the study of a triple $(X,\Delta,D)$ which
consists of a pair $(X,\Delta)$ and a polarizing pseudoeffective divisor $D$.
The adjoint asymptotic multiplier ideal sheaf $\mathcal{J}(X,\Delta;\lVert D
\rVert)$ associated to the triple gives a simultaneous generalization of the
multiplier ideal sheaf $\mathcal{J}(D)$ and asymptotic multiplier ideal sheaf
$\mathcal{J}(\lVert D \rVert)$. We describe the closed set defined by the ideal
sheaf $\mathcal{J}(X,\Delta;\lVert D \rVert)$ in terms of the minimal model
program. We also characterize the case where $\mathcal{J}(X,\Delta;\lVert D
\rVert)=\mathcal{O}_X$. Lastly, we also prove a Nadel type vanishing theorem of
cohomology using $\mathcal{J}(X,\Delta;\lVert D \rVert)$.
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Despite having the simplest atomic structure, bulk FeSe has an observed
electronic structure with the largest deviation from the band theory
predictions among all Fe-based superconductors and exhibits a low temperature
nematic electronic state without intervening magnetic order. We show that the
Fe-Fe interatomic Coulomb repulsion $V$ offers a natural explanation for the
puzzling electron correlation effects in FeSe superconductors. It produces a
strongly renormalized low-energy band structure where the van Hove singularity
sits remarkably close to Fermi level in the high-temperature electron liquid
phase as observed experimentally. This proximity enables the quantum
fluctuations in $V$ to induce a rotational symmetry breaking electronic bond
order in the $d$-wave channel. We argue that this emergent low-temperature
$d$-wave bond nematic state, different from the commonly discussed
ferro-orbital order and spin-nematicity, has been observed recently by several
angle resolved photoemission experiments detecting the lifting of the band
degeneracies at high symmetry points in the Brillouin zone. We present a
symmetry analysis of the space group and identify the hidden antiunitary
$T$-symmetry that protects the band degeneracy and the electronic
order/interaction that can break the symmetry and lift the degeneracy. We show
that the $d$-wave nematic bond order, together with the spin-orbit coupling,
provide a unique explanation of the temperature dependence, momentum space
anisotropy, and domain effects observed experimentally. We discuss the
implications of our findings on the structural transition, the absence of
magnetic order, and the intricate competition between nematicity and
superconductivity in FeSe superconductors.
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In this paper, we study the homology of the coloring complex and the cyclic
coloring complex of a complete $k$-uniform hypergraph. We show that the
coloring complex of a complete $k$-uniform hypergraph is shellable, and we
determine the rank of its unique nontrivial homology group in terms of its
chromatic polynomial. We also show that the dimension of the $(n-k-1)^{st}$
homology group of the cyclic coloring complex of a complete $k$-uniform
hypergraph is given by a binomial coefficient. Further, we discuss a complex
whose $r$-faces consist of all ordered set partitions $[B_1, \hdots, B_{r+2}]$
where none of the $B_i$ contain a hyperedge of the complete $k$-uniform
hypergraph $H$ and where $1 \in B_1$. It is shown that the dimensions of the
homology groups of this complex are given by binomial coefficients. As a
consequence, this result gives the dimensions of the multilinear parts of the
cyclic homology groups of $\C[x_1, \hdots, x_n]/ \{x_{i_1} \hdots x_{i_k} \mid
i_{1} \hdots i_{k}$ is a hyperedge of $H \}$.
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Using high-resolution hydrodynamical simulations of galaxy clusters, we study
the interaction between the brightest cluster galaxy, its supermassive black
hole (BH) and the intracluster medium (ICM). We create initial conditions for
which the ICM is in hydrostatic equilibrium within the gravitational potential
from the galaxy and an NFW dark matter halo. Two free parameters associated
with the thermodynamic profiles determine the cluster gas fraction and the
central temperature, where the latter can be used to create cool-core or
non-cool-core systems. Our simulations include radiative cooling, star
formation, BH accretion, and stellar and active galactic nucleus (AGN)
feedback. Even though the energy of AGN feedback is injected thermally and
isotropically, it leads to anisotropic outflows and buoyantly rising bubbles.
We find that the BH accretion rate (BHAR) is highly variable and only
correlates strongly with the star formation rate (SFR) and the ICM when it is
averaged over more than $1~\rm Myr$. We generally find good agreement with the
theoretical precipitation framework. In $10^{13}~\rm M_\odot$ haloes, AGN
feedback quenches the central galaxy and converts cool-core systems into
non-cool-core systems. In contrast, higher-mass, cool-core clusters evolve
cyclically. Episodes of high BHAR raise the entropy of the ICM out to the
radius where the ratio of the cooling time and the local dynamical time $t_{\rm
cool}/t_{\rm dyn} > 10$, thus suppressing condensation and, after a delay, the
BHAR. The corresponding reduction in AGN feedback allows the ICM to cool and
become unstable to precipitation, thus initiating a new episode of high SFR and
BHAR.
|
In [10] the third author of this paper presented two conjectures on the
additive decomposability of the sequence of ''smooth'' (or ''friable'')
numbers. Elsholtz and Harper [4] proved (by using sieve methods) the second
(less demanding) conjecture. The goal of this paper is to extend and sharpen
their result in three directions by using a different approach (based on the
theory of $S$-unit equations).
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In this Letter we report on the results of our search for photons from a U(1)
gauge factor in the hidden sector of the full theory. With our experimental
setup we observe the single spectrum in a HPGe detector arising as a result of
the photoelectric-like absorption of hidden photons emitted from the Sun on
germanium atoms inside the detector. The main ingredient of the theory used in
our analysis, a severely constrained kinetic mixing from the two U(1) gauge
factors and massive hidden photons, entails both photon into hidden state
oscillations and a minuscule coupling of hidden photons to visible matter, of
which the latter our experimental setup has been designed to observe. On a
theoretical side, full account was taken of the effects of refraction and
damping of photons while propagating in Sun's interior as well as in the
detector. We exclude hidden photons with kinetic couplings chi > (2.2 x
10^{-13}- 3 x 10^{-7}) in the mass region 0.2 eV < m_gamma' < 30 keV. Our
constraints on the mixing parameter chi in the mass region from 20 eV up to 15
keV prove even slightly better then those obtained recently by using data from
the CAST experiment, albeit still somewhat weaker than those obtained from
solar and HB stars lifetime arguments.
|
We devise a novel neural network-based universal denoiser for the
finite-input, general-output (FIGO) channel. Based on the assumption of known
noisy channel densities, which is realistic in many practical scenarios, we
train the network such that it can denoise as well as the best sliding window
denoiser for any given underlying clean source data. Our algorithm, dubbed as
Generalized CUDE (Gen-CUDE), enjoys several desirable properties; it can be
trained in an unsupervised manner (solely based on the noisy observation data),
has much smaller computational complexity compared to the previously developed
universal denoiser for the same setting, and has much tighter upper bound on
the denoising performance, which is obtained by a theoretical analysis. In our
experiments, we show such tighter upper bound is also realized in practice by
showing that Gen-CUDE achieves much better denoising results compared to other
strong baselines for both synthetic and real underlying clean sequences.
|
We study maximal clades in random phylogenetic trees with the Yule-Harding
model or, equivalently, in binary search trees. We use probabilistic methods to
reprove and extend earlier results on moment asymptotics and asymptotic
normality. In particular, we give an explanation of the curious phenomenon
observed by Drmota, Fuchs and Lee (2014) that asymptotic normality holds, but
one should normalize using half the variance.
|
Pulsar positions can be measured with high precision using both pulsar timing
methods and very-long-baseline interferometry (VLBI). Pulsar timing positions
are referenced to a solar-system ephemeris, whereas VLBI positions are
referenced to distant quasars. Here we compare pulsar positions from published
VLBI measurements with those obtained from pulsar timing data from the Nanshan
and Parkes radio telescopes in order to relate the two reference frames. We
find that the timing positions differ significantly from the VLBI positions
(and also differ between different ephemerides). A statistically significant
change in the obliquity of the ecliptic of $2.16\pm0.33$\,mas is found for the
JPL ephemeris DE405, but no significant rotation is found in subsequent JPL
ephemerides. The accuracy with which we can relate the two frames is limited by
the current uncertainties in the VLBI reference source positions and in
matching the pulsars to their reference source. Not only do the timing
positions depend on the ephemeris used in computing them, but also different
segments of the timing data lead to varying position estimates. These
variations are mostly common to all ephemerides, but slight changes are seen at
the 10$\mu$as level between ephemerides.
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Estimating the structure of directed acyclic graphs (DAGs, also known as
Bayesian networks) is a challenging problem since the search space of DAGs is
combinatorial and scales superexponentially with the number of nodes. Existing
approaches rely on various local heuristics for enforcing the acyclicity
constraint. In this paper, we introduce a fundamentally different strategy: We
formulate the structure learning problem as a purely \emph{continuous}
optimization problem over real matrices that avoids this combinatorial
constraint entirely. This is achieved by a novel characterization of acyclicity
that is not only smooth but also exact. The resulting problem can be
efficiently solved by standard numerical algorithms, which also makes
implementation effortless. The proposed method outperforms existing ones,
without imposing any structural assumptions on the graph such as bounded
treewidth or in-degree. Code implementing the proposed algorithm is open-source
and publicly available at https://github.com/xunzheng/notears.
|
The CMS Collaboration has released the results of its search for
supersymmetry, by applying an alphaT method to 1.1/fb of data at 7 TeV. The
null result excludes (at 95% CL) a low-mass region of the Constrained MSSM's
parameter space that was previously favored by other experiments. Additionally,
the negative result of the XENON100 dark matter search has excluded (at 90% CL)
values of the spin-independent scattering cross sections sigma^SI_p as low as
10^-8 pb. We incorporate these improved experimental constraints into a global
Bayesian fit of the Constrained MSSM by constructing approximate likelihood
functions. In the case of the alphaT limit, we simulate detector efficiency for
the CMS alphaT 1.1/fb and validate our method against the official 95% CL
contour. We identify the 68% and 95% credible posterior regions of the CMSSM
parameters, and also find the best-fit point. We find that the credible regions
change considerably once a likelihood from alphaT is included, in particular
the narrow light Higgs resonance region becomes excluded, but the focus
point/horizontal branch region remains allowed at the 1sigma level. Adding the
limit from XENON100 has a weaker additional effect, in part due to large
uncertainties in evaluating sigma^SI_p, which we include in a conservative way,
although we find that it reduces the posterior probability of the focus point
region to the 2sigma level. The new regions of high posterior favor squarks
lighter than the gluino and all but one Higgs bosons heavy. The dark matter
neutralino mass is found in the range 250 GeV <~ m_Chi1 <~ 343 GeV (at 1sigma)
while, as the result of improved limits from the LHC, the favored range of
sigma^SI_p is pushed down to values below 10^{-9} pb. We highlight tension
between (g-2)_mu and BR(b->sg), which is exacerbated by including the alphaT
limit; each constraint favors a different region of the CMSSM's mass
parameters.
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Microcanonical description is characterized by the presence of an internal
symmetry closely related with the dynamical origin of this ensemble: the
reparametrization invariance. Such symmetry possibilities the development of a
non Riemannian geometric formulation within the microcanonical description of
an isolated system, which leads to an unexpected generalization of the Gibbs
canonical ensemble and the classical fluctuation theory for the open systems
(where the inverse temperature and the total energy E behave as complementary
thermodynamical quantities), the improvement of Monte Carlo simulations based
on the canonical ensemble, as well as a reconsideration of any classification
scheme of the phase transitions based on the concavity of the microcanonical
entropy.
|
In this work, we investigate the bosonic chiral string in the sectorized
interpretation, computing its spectrum, kinetic action and $3$-point
amplitudes. As expected, the bosonic ambitwistor string is recovered in the
tensionless limit.
We also consider an extension of the bosonic model with current algebras. In
that case, we compute the effective action and show that it is essentially the
same as the action of the mass-deformed $(DF)^{2}$ theory found by Johansson
and Nohle. Aspects which might seem somewhat contrived in the original
construction --- such as the inclusion of a scalar transforming in some real
representation of the gauge group --- are shown to follow very naturally from
the worldsheet formulation of the theory.
|
The (homogeneous) Essentially Isolated Determinantal Variety is the natural
generalization of generic determinantal variety, and is fundamental example to
study non-isolated singularities. In this paper we study the characteristic
classes on these varieties. We give explicit formulas of their
Chern-Schwartz-MacPherson classes and Chern-Mather classes via standard
Schubert calculus. As corollaries we obtain formulas for their (generic)
sectional Euler characteristics, characteristic cycles and polar classes.
|
In this article we study a nonlocal Nambu--Jona-Lasinio (nNJL) model with a
Gaussian regulator in presence of a uniform magnetic field. We take a mixed
approach to the incorporation of temperature in the model, and consider aspects
of both real and imaginary time formalisms. We include confinement in the model
through the quasiparticle interpretation of the poles of the propagator. The
effect of the magnetic field in the deconfinement phase transition is then
studied. It is found that, like with chiral symmetry restoration, magnetic
catalysis occurs for the deconfinement phase transition. It is also found that
the magnetic field enhances the thermodynamical instability of the system. We
work in the weak field limit, i.e. $(eB)<5m_\pi^2$. At this level there is no
splitting of the critical temperatures for chiral and deconfinement phase
transitions.
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We say that a $q$-ary length $n$ code is \emph{non-overlapping} if the set of
non-trivial prefixes of codewords and the set of non-trivial suffices of
codewords are disjoint. These codes were first studied by Levenshtein in 1964,
motivated by applications in synchronisation. More recently these codes were
independently invented (under the name \emph{cross-bifix-free} codes) by
Baji\'c and Stojanovi\'c.
We provide a simple construction for a class of non-overlapping codes which
has optimal cardinality whenever $n$ divides $q$. Moreover, for all parameters
$n$ and $q$ we show that a code from this class is close to optimal, in the
sense that it has cardinality within a constant factor of an upper bound due to
Levenshtein from 1970. Previous constructions have cardinality within a
constant factor of the upper bound only when $q$ is fixed.
Chee, Kiah, Purkayastha and Wang showed that a $q$-ary length $n$
non-overlapping code contains at most $q^n/(2n-1)$ codewords; this bound is
weaker than the Levenshtein bound. Their proof appealed to the application in
synchronisation: we provide a direct combinatorial argument to establish the
bound of Chee \emph{et al}.
We also consider codes of short length, finding the leading term of the
maximal cardinality of a non-overlapping code when $n$ is fixed and
$q\rightarrow \infty$. The largest cardinality of non-overlapping codes of
lengths $3$ or less is determined exactly.
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Let $H(\hbar)=-\hbar^2d^2/dx^2+V(x)$ be a Schr\"odinger operator on the real
line, $W(x)$ be a bounded observable depending only on the coordinate and $k$
be a fixed integer. Suppose that an energy level $E$ intersects the potential
$V(x)$ in exactly two turning points and lies below
$V_\infty=\liminf_{|x|\to\infty} V(x)$. We consider the semiclassical limit
$n\to\infty$, $\hbar=\hbar_n\to0$ and $E_n=E$ where $E_n$ is the $n$th
eigen-energy of $H(\hbar)$. An asymptotic formula for $<{}n|W(x)|n+k>$, the
non-diagonal matrix elements of $W(x)$ in the eigenbasis of $H(\hbar)$, has
been known in the theoretical physics for a long time. Here it is proved in a
mathematically rigorous manner.
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Two-dimensional lattices of coupled micropillars etched in a planar
semiconductor microcavity offer a workbench to engineer the band structure of
polaritons. We report experimental studies of honeycomb lattices where the
polariton low-energy dispersion is analogous to that of electrons in graphene.
Using energy-resolved photoluminescence we directly observe Dirac cones, around
which the dynamics of polaritons is described by the Dirac equation for
massless particles. At higher energies, we observe p orbital bands, one of them
with the nondispersive character of a flatband. The realization of this
structure which holds massless, massive and infinitely massive particles opens
the route towards studies of the interplay of dispersion, interactions, and
frustration in a novel and controlled environment.
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A variant of the U-Net convolutional neural network architecture is proposed
to estimate linear elastic compatibility stresses in a-Zr (hcp) polycrystalline
grain structures. Training data was generated using VGrain software with a
regularity alpha of 0.73 and uniform random orientation for the grain
structures and ABAQUS to evaluate the stress welds using the finite element
method. The initial dataset contains 200 samples with 20 held from training for
validation. The network gives speedups of around 200x to 6000x using a CPU or
GPU, with signifcant memory savings, compared to finite element analysis with a
modest reduction in accuracy of up to 10%. Network performance is not
correlated with grain structure regularity or texture, showing generalisation
of the network beyond the training set to arbitrary Zr crystal structures.
Performance when trained with 200 and 400 samples was measured, finding an
improvement in accuracy of approximately 10% when the size of the dataset was
doubled.
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J/Psi and eta_c above the QCD critical temperature T_c are studied in
anisotropic quenched lattice QCD, considering whether the c\bar c systems above
T_c are spatially compact (quasi-)bound states or scattering states. We adopt
the standard Wilson gauge action and O(a)-improved Wilson quark action with
renormalized anisotropy a_s/a_t =4.0 at \beta=6.10 on 16^3\times (14-26)
lattices, which correspond to the spatial lattice volume V\equiv
L^3\simeq(1.55{\rm fm})^3 and temperatures T\simeq(1.11-2.07)T_c. We
investigate the c\bar c system above T_c from the temporal correlators with
spatially-extended operators, where the overlap with the ground state is
enhanced. To clarify whether compact charmonia survive in the deconfinement
phase, we investigate spatial boundary-condition dependence of the energy of
c\bar c systems above T_c. In fact, for low-lying S-wave c \bar c scattering
states, it is expected that there appears a significant energy difference
\Delta E \equiv E{\rm (APBC)}-E{\rm (PBC)}\simeq2\sqrt{m_c^2+3\pi^2/L^2}-2m_c
(m_c: charm quark mass) between periodic and anti-periodic boundary conditions
on the finite-volume lattice. In contrast, for compact charmonia, there is no
significant energy difference between periodic and anti-periodic boundary
conditions. As a lattice QCD result, almost no spatial boundary-condition
dependence is observed for the energy of the c\bar c system in J/\Psi and
\eta_c channels for T\simeq(1.11-2.07)T_c. This fact indicates that J/\Psi and
\eta_c would survive as spatially compact c\bar c (quasi-)bound states below
2T_c. We also investigate a $P$-wave channel at high temperature with maximally
entropy method (MEM) and find no low-lying peak structure corresponding to
\chi_{c1} at 1.62T_c.
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Optical bottle beams can be used to trap atoms and small low-index particles.
We introduce a figure of merit for optical bottle beams, specifically in the
context of optical traps, and use it to compare optical bottle-beam traps
obtained by three different methods. Using this figure of merit and an
optimization algorithm, we identified optical bottle-beam traps based on a
Gaussian beam illuminating a metasurface that are superior in terms of power
efficiency than existing approaches. We numerically demonstrate a silicon
metasurface for creating an optical bottle-beam trap.
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In Part I, we studied the communication for omniscience (CO) problem and
proposed a parametric (PAR) algorithm to determine the minimum sum-rate at
which a set of users indexed by a finite set $V$ attain omniscience. The
omniscience in CO refers to the status that each user in $V$ recovers the
observations of a multiple random source. It is called the global omniscience
in this paper in contrast to the study of the successive omniscience (SO),
where the local omniscience is attained subsequently in user subsets. By
inputting a lower bound on the minimum sum-rate for CO, we apply the PAR
algorithm to search a complimentary subset $X_* \subsetneq V$ such that if the
local omniscience in $X_*$ is reached first, the global omniscience whereafter
can still be attained with the minimum sum-rate. We further utilize the outputs
of the PAR algorithm to outline a multi-stage SO approach that is characterized
by $K \leq |V| - 1$ complimentary subsets $X_*^{(k)}, \forall k \in
\{1,\dotsc,K\}$ forming a nesting sequence $X_*^{(1)} \subsetneq \dotsc
\subsetneq X_*^{(K)} = V$. Starting from stage $k = 1$, the local omniscience
in $X_*^{(k)}$ is attained at each stage $k$ until the final global omniscience
in $X_*^{(K)} = V$. A $|X_*{(k)}|$-dimensional local omniscience achievable
rate vector is also derived for each stage $k$ designating individual users
transmitting rates. The sum-rate of this rate vector in the last stage $K$
coincides with the minimized sum-rate for the global omniscience.
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Counter reachability games are played by two players on a graph with labelled
edges. Each move consists in picking an edge from the current location and
adding its label to a counter vector. The objective is to reach a given counter
value in a given location. We distinguish three semantics for counter
reachability games, according to what happens when a counter value would become
negative: the edge is either disabled, or enabled but the counter value becomes
zero, or enabled. We consider the problem of deciding the winner in counter
reachability games and show that, in most cases, it has the same complexity
under all semantics. Surprisingly, under one semantics, the complexity in
dimension one depends on whether the objective value is zero or any other
integer.
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In this paper we adhere to the definition of infra-topological space as it
was introduced by Al-Odhari. Namely, we speak about families of subsets which
contain empty set and the whole universe X, being at the same time closed under
finite intersections (but not necessarily under arbitrary or even finite
unions). This slight modification allows us to distinguish between new classes
of subsets (infra-open, ps-infra-open and i-genuine). Analogous notions are
discussed in the language of closures. The class of minimal infra-open sets is
studied too, as well as the idea of generalized infra-spaces. Finally, we
obtain characterization of infra-spaces in terms of modal logic, using some of
the notions introduced above.
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We propose a method to extract predictions from quantum cosmology for
inflation that can be confronted with observations. Employing the tunneling
boundary condition in quantum geometrodynamics, we derive a probability
distribution for the inflaton field. A sharp peak in this distribution can be
interpreted as setting the initial conditions for the subsequent phase of
inflation. In this way, the peak sets the energy scale at which the
inflationary phase has started. This energy scale must be consistent with the
energy scale found from the inflationary potential and with the scale found
from a potential observation of primordial gravitational waves. Demanding a
consistent history of the universe from its quantum origin to its present
state, which includes decoherence, we derive a condition that allows one to
constrain the parameter space of the underlying model of inflation. We
demonstrate our method by applying it to two models: Higgs inflation and
natural inflation.
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Small 3He-rich solar energetic particle (SEP) events with their anomalous
abundances, markedly different from solar system, provide evidence for a unique
acceleration mechanism that operates routinely near solar active regions.
Although the events are sometimes accompanied by coronal mass ejections (CMEs)
it is believed that mass and isotopic fractionation is produced directly in the
flare sites on the Sun. We report on a large-scale extreme ultraviolet (EUV)
coronal wave observed in association with 3He-rich SEP events. In the two
examples discussed, the observed waves were triggered by minor flares and
appeared concurrently with EUV jets and type III radio bursts but without CMEs.
The energy spectra from one event are consistent with so-called class-1
(characterized by power laws) while the other with class-2 (characterized by
rounded 3He and Fe spectra) 3He-rich SEP events, suggesting different
acceleration mechanisms in the two. The observation of EUV waves suggests that
large-scale disturbances, in addition to more commonly associated jets, may be
responsible for the production of 3He-rich SEP events.
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Historically, multiple populations in Globular Clusters (GCs) have been
mostly studied from ultraviolet and optical filters down to stars that are more
massive than ~0.6 solar masses. Here we exploit deep near-infrared (NIR)
photometry from the Hubble Space Telescope to investigate multiple populations
among M-dwarfs in the GC NGC6752. We discovered that the three main populations
(A, B and C), previously observed in the brightest part of the color-magnitude
diagram, define three distinct sequences that run from the main-sequence (MS)
knee towards the bottom of the MS (~0.15 solar masses). These results, together
with similar findings on NGC2808, M4, and omega Centauri, demonstrate that
multiple sequences of M-dwarfs are common features of the color-magnitude
diagrams of GCs. The three sequences of low-mass stars in NGC6752 are
consistent with stellar populations with different oxygen abundances. The range
of [O/Fe] needed to reproduce the NIR CMD of NGC6752 is similar to the oxygen
spread inferred from high-resolution spectroscopy of red-giant branch (RGB)
stars. The relative numbers of stars in the three populations of M-dwarfs are
similar to those derived among RGB and MS stars more massive than ~0.6 solar
masses. As a consequence, the evidence that the properties of multiple
populations do not depend on stellar mass is a constraint for the formation
scenarios.
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Multimodal machine translation (MMT) systems have been shown to outperform
their text-only neural machine translation (NMT) counterparts when visual
context is available. However, recent studies have also shown that the
performance of MMT models is only marginally impacted when the associated image
is replaced with an unrelated image or noise, which suggests that the visual
context might not be exploited by the model at all. We hypothesize that this
might be caused by the nature of the commonly used evaluation benchmark, also
known as Multi30K, where the translations of image captions were prepared
without actually showing the images to human translators. In this paper, we
present a qualitative study that examines the role of datasets in stimulating
the leverage of visual modality and we propose methods to highlight the
importance of visual signals in the datasets which demonstrate improvements in
reliance of models on the source images. Our findings suggest the research on
effective MMT architectures is currently impaired by the lack of suitable
datasets and careful consideration must be taken in creation of future MMT
datasets, for which we also provide useful insights.
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The gap equation with dressed propagators is solved in symmetric nuclear
matter. Nucleon self-energies are obtained within the self-consistent in medium
T matrix approximation. The off-shell gap equation is compared to an effective
quasiparticle gap equation with reduced interaction. At normal density, we find
a reduction of the superfluid gap from 6.5MeV to .45MeV when self-energy
effects are included.
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We construct an unbounded strictly pseudoconvex Kobayashi hyperbolic and
complete domain in $\mathbb{C}^2$, which also possesses complete Bergman
metric, but has no nonconstant bounded holomorphic functions.
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Two different physical phenomena, described by the bias flow aperture theory
and the Coriolis flowmeter "bubble theory", are compared. The bubble theory is
simplified and analogies with the bias flow aperture theory are appraised.
|
We have theoretically investigated Su-Schrieffer-Heeger chains modelled as
optical lattices (OL) loaded with exciton-polaritons. The chains have been
subject to the resonant pumping of the edge site and shaken in either adiabatic
or high-frequency regime. The topological state has been controlled by the
relative phases of the lasers constructing the OL. The dynamic problem of the
occupation of the lattice sites and eigenstates has been semi-classically
solved. Finally, the analysis of the occupation numbers evolution has revealed
that gapless, topologically trivial and non-trivial chain configurations
demonstrate perceptible behaviour from both qualitative (occupation pattern)
and quantitative (total occupation) points of view.
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We use the Hubble Space Telescope ACS camera to obtain the first spatially
resolved, nebular imaging in the light of C IV 1548,1551 by using the F150LP
and F165LP filters. These observations of the local starburst Mrk 71 in NGC
2366 show emission apparently originating within the interior cavity around the
dominant super star cluster (SSC), Knot A. Together with imaging in He II 4686
and supporting STIS FUV spectroscopy, the morphology and intensity of the C IV
nebular surface brightness and the C IV / He II ratio map provide direct
evidence that the mechanical feedback is likely dominated by catastrophic
radiative cooling, which strongly disrupts adiabatic superbubble evolution. The
implied extreme mass loading and low kinetic efficiency of the cluster wind are
reasonably consistent with the wind energy budget, which is probably enhanced
by radiation pressure. In contrast, the Knot B SSC lies within a well-defined
superbubble with associated soft X-rays and He II 1640 emission, which are
signatures of adiabatic, energy-driven feedback from a supernova-driven
outflow. This system lacks clear evidence of C IV from the limb-brightened
shell, as expected for this model, but the observations may not be deep enough
to confirm its presence. We also detect a small C IV-emitting object that is
likely an embedded compact H II region. Its C IV emission may indicate the
presence of very massive stars (> 100 M_sun) or strongly pressure-confined
stellar feedback.
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Affine iterations of the form x(n+1) = Ax(n) + b converge, using real
arithmetic, if the spectral radius of the matrix A is less than 1. However,
substituting interval arithmetic to real arithmetic may lead to divergence of
these iterations, in particular if the spectral radius of the absolute value of
A is greater than 1. We will review different approaches to limit the
overestimation of the iterates, when the components of the initial vector x(0)
and b are intervals. We will compare, both theoretically and experimentally,
the widths of the iterates computed by these different methods: the naive
iteration, methods based on the QR-and SVD-factorization of A, and Lohner's
QR-factorization method. The method based on the SVD-factorization is
computationally less demanding and gives good results when the matrix is poorly
scaled, it is superseded either by the naive iteration or by Lohner's method
otherwise.
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It is widely accepted that blockchain systems cannot execute calls to
external systems or services due to each node having to reach a deterministic
state. However, in this paper we show that this belief is preconceived by
demonstrating a method that enables blockchain and distributed ledger
technologies to perform calls to external systems initiated from the
blockchain/DLT itself.
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Let $V$ be a set of cardinality $v$ (possibly infinite). Two graphs $G$ and
$G'$ with vertex set $V$ are {\it isomorphic up to complementation} if $G'$ is
isomorphic to $G$ or to the complement $\bar G$ of $G$. Let $k$ be a
non-negative integer, $G$ and $G'$ are {\it $k$-hypomorphic up to
complementation} if for every $k$-element subset $K$ of $V$, the induced
subgraphs $G\_{\restriction K}$ and $G'\_{\restriction K}$ are isomorphic up to
complementation. A graph $G$ is {\it $k$-reconstructible up to complementation}
if every graph $G'$ which is $k$-hypomorphic to $G$ up to complementation is in
fact isomorphic to $G$ up to complementation. We give a partial
characterisation of the set $\mathcal S$ of pairs $(n,k)$ such that two graphs
$G$ and $G'$ on the same set of $n$ vertices are equal up to complementation
whenever they are $k$-hypomorphic up to complementation. We prove in particular
that $\mathcal S$ contains all pairs $(n,k)$ such that $4\leq k\leq n-4$. We
also prove that 4 is the least integer $k$ such that every graph $G$ having a
large number $n$ of vertices is $k$-reconstructible up to complementation; this
answers a question raised by P. Ille
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One problem to solve in the context of information fusion, decision-making,
and other artificial intelligence challenges is to compute justified beliefs
based on evidence. In real-life examples, this evidence may be inconsistent,
incomplete, or uncertain, making the problem of evidence fusion highly
non-trivial. In this paper, we propose a new model for measuring degrees of
beliefs based on possibly inconsistent, incomplete, and uncertain evidence, by
combining tools from Dempster-Shafer Theory and Topological Models of Evidence.
Our belief model is more general than the aforementioned approaches in two
important ways: (1) it can reproduce them when appropriate constraints are
imposed, and, more notably, (2) it is flexible enough to compute beliefs
according to various standards that represent agents' evidential demands. The
latter novelty allows the users of our model to employ it to compute an agent's
(possibly) distinct degrees of belief, based on the same evidence, in
situations when, e.g, the agent prioritizes avoiding false negatives and when
it prioritizes avoiding false positives. Finally, we show that computing
degrees of belief with this model is #P-complete in general.
|
A number of interesting properties of graphene and graphite are postulated to
derive from the peculiar bandstructure of graphene. This bandstructure consists
of conical electron and hole pockets that meet at a single point in momentum
(k) space--the Dirac crossing, at energy $E_{D} = \hbar \omega_{D}$. Direct
investigations of the accuracy of this bandstructure, the validity of the
quasiparticle picture, and the influence of many-body interactions on the
electronic structure have not been addressed for pure graphene by experiment to
date. Using angle resolved photoelectron spectroscopy (ARPES), we find that the
expected conical bands are distorted by strong electron-electron,
electron-phonon, and electron-plasmon coupling effects. The band velocity at
$E_{F}$ and the Dirac crossing energy $E_{D}$ are both renormalized by these
many-body interactions, in analogy with mass renormalization by electron-boson
coupling in ordinary metals. These results are of importance not only for
graphene but also graphite and carbon nanotubes which have similar
bandstructures.
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The increase in parameter size of multimodal large language models (MLLMs)
introduces significant capabilities, particularly in-context learning, where
MLLMs enhance task performance without updating pre-trained parameters. This
effectiveness, however, hinges on the appropriate selection of in-context
examples, a process that is currently biased towards visual data, overlooking
textual information. Furthermore, the area of supervised retrievers for MLLMs,
crucial for optimal in-context example selection, continues to be
uninvestigated. Our study offers an in-depth evaluation of the impact of
textual information on the unsupervised selection of in-context examples in
multimodal contexts, uncovering a notable sensitivity of retriever performance
to the employed modalities. Responding to this, we introduce a novel supervised
MLLM-retriever MSIER that employs a neural network to select examples that
enhance multimodal in-context learning efficiency. This approach is validated
through extensive testing across three distinct tasks, demonstrating the
method's effectiveness. Additionally, we investigate the influence of
modalities on our supervised retrieval method's training and pinpoint factors
contributing to our model's success. This exploration paves the way for future
advancements, highlighting the potential for refined in-context learning in
MLLMs through the strategic use of multimodal data.
|
Visible Light Communication (VLC) technology using light emitting diodes
(LEDs) has been gaining increasing attention in recent years as it is appealing
for a wide range of applications such as indoor positioning. Orthogonal
frequency division multiplexing (OFDM) has been applied to indoor wireless
optical communications in order to mitigate the effect of multipath distortion
of the optical channel as well as increasing data rate. In this paper, we
investigate the indoor positioning accuracy of optical based OFDM techniques
used in VLC systems. A positioning algorithm based on power attenuation is used
to estimate the receiver coordinates. We further calculate the positioning
errors in all the locations of a room and compare them with those of single
carrier modulation scheme, i.e., on-off keying (OOK) modulation. We demonstrate
that OFDM positioning system outperforms its conventional counterpart.
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Using first-principles calculations, we explore the electronic and magnetic
properties of graphene nanomesh (GNM), a regular network of large vacancies,
produced either by lithography or nanoimprint. When removing an equal number of
A and B sites of the graphene bipartite lattice, the nanomesh made mostly of
zigzag (armchair) type edges exhibit antiferromagnetic (spin unpolarized)
states. In contrast, in situation of sublattice symmetry breaking, stable
ferri(o)magnetic states are obtained. For hydrogen-passivated nanomesh, the
formation energy is dramatically decreased, and ground state is found to
strongly depend on the vacancies shape and size. For triangular shaped holes,
the obtained net magnetic moments increase with the number difference of
removed A and B sites in agreement with Lieb's theorem for even A+B. For odd
A+B triangular meshes and all cases of non-triangular nanomeshes including the
one with even A+B, Lieb's theorem does not hold anymore which can be partially
attributed to introduction of armchair edges. In addition, large triangular
shaped GNM could be as robust as non-triangular GNMs, providing possible
solution to overcome one of crucial challenges for the sp-magnetism. Finally,
significant exchange splitting values as large as $\sim 0.5$ eV can be obtained
for highly asymmetric structures evidencing the potential of GNM for room
temperature carbon based spintronics. These results demonstrate that a turn
from 0-dimensional graphene nanoflakes throughout 1-dimensional graphene
nanoribbons with zigzag edges to GNM breaks localization of unpaired electrons
and provides deviation from the rules based on Lieb's theorem. Such
delocalization of the electrons leads the switch of the ground state of system
from antiferromagnetic narrow gap insulator discussed for graphene nanoribons
to ferromagnetic or nonmagnetic metal.
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Networked systems display complex patterns of interactions between a large
number of components. In physical networks, these interactions often occur
along structural connections that link components in a hard-wired connection
topology, supporting a variety of system-wide dynamical behaviors such as
synchronization. While descriptions of these behaviors are important, they are
only a first step towards understanding the relationship between network
topology and system behavior, and harnessing that relationship to optimally
control the system's function. Here, we use linear network control theory to
analytically relate the topology of a subset of structural connections (those
linking driver nodes to non-driver nodes) to the minimum energy required to
control networked systems. As opposed to the numerical computations of control
energy, our accurate closed-form expressions yield general structural features
in networks that require significantly more or less energy to control,
providing topological principles for the design and modification of network
behavior. To illustrate the utility of the mathematics, we apply this approach
to high-resolution connectomes recently reconstructed from drosophila, mouse,
and human brains. We use these principles to show that connectomes of
increasingly complex species are wired to reduce control energy. We then use
the analytical expressions we derive to perform targeted manipulation of the
brain's control profile by removing single edges in the network, a manipulation
that is accessible to current clinical techniques in patients with neurological
disorders. Cross-species comparisons suggest an advantage of the human brain in
supporting diverse network dynamics with small energetic costs, while remaining
unexpectedly robust to perturbations. Our results ground the expectation of a
system's dynamical behavior in its network architecture.
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In the light of the recent LHC data, we study precision tests sensitive to
the violation of lepton universality, in particular the violation of unitarity
in neutrino mixing. Keeping all data we find no satisfatory fit, even allowing
for violations of unitarity in neutrino mixing. Leaving out sin$^2
\theta_{\scriptsize \mbox{eff}}$ from the hadronic forward-backward asymmetry
at LEP, we find a good fit to the data with some evidence of lepton
universality violation at the $\mathcal{O}(10^{-3})$ level.
|
Large Language Models (LLMs) (e.g., ChatGPT) have shown impressive
performance in code generation. LLMs take prompts as inputs, and
Chain-of-Thought (CoT) prompting is the state-of-the-art prompting technique.
CoT prompting asks LLMs first to generate CoTs (i.e., intermediate natural
language reasoning steps) and then output the code. However, CoT prompting is
designed for natural language generation and has low accuracy in code
generation.
In this paper, we propose Structured CoTs (SCoTs) and present a novel
prompting technique for code generation, named SCoT prompting. Our motivation
is source code contains rich structural information and any code can be
composed of three program structures (i.e., sequence, branch, and loop
structures). Intuitively, structured intermediate reasoning steps make for
structured source code. Thus, we ask LLMs to use program structures to build
CoTs, obtaining SCoTs. Then, LLMs generate the final code based on SCoTs.
Compared to CoT prompting, SCoT prompting explicitly constrains LLMs to think
about how to solve requirements from the view of source code and further the
performance of LLMs in code generation. We apply SCoT prompting to two LLMs
(i.e., ChatGPT and Codex) and evaluate it on three benchmarks (i.e., HumanEval,
MBPP, and MBCPP). (1) SCoT prompting outperforms the state-of-the-art baseline
- CoT prompting by up to 13.79% in Pass@1. (2) Human evaluation shows human
developers prefer programs from SCoT prompting. (3) SCoT prompting is robust to
examples and achieves substantial improvements.
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The Linked Data Benchmark Council's Financial Benchmark (LDBC FinBench) is a
new effort that defines a graph database benchmark targeting financial
scenarios such as anti-fraud and risk control. The benchmark has one workload,
the Transaction Workload, currently. It captures OLTP scenario with complex,
simple read queries and write queries that continuously insert or delete data
in the graph. Compared to the LDBC SNB, the LDBC FinBench differs in
application scenarios, data patterns, and query patterns. This document
contains a detailed explanation of the data used in the LDBC FinBench, the
definition of transaction workload, a detailed description for all queries, and
instructions on how to use the benchmark suite.
|
We study the effects of disorder on long-range antiferromagnetic correlations
in the half-filled, two dimensional, repulsive Hubbard model at T=0. A mean
field approach is first employed to gain a qualitative picture of the physics
and to guide our choice for a trial wave function in a constrained path quantum
Monte Carlo (CPQMC) method that allows for a more accurate treatment of
correlations. Within the mean field calculation, we observe both Anderson and
Mott insulating antiferromagnetic phases. There are transitions to a paramagnet
only for relatively weak coupling, U < 2t in the case of bond disorder, and U <
4t in the case of on-site disorder. Using ground-state CPQMC we demonstrate
that this mean field approach significantly overestimates magnetic order. For
U=4t, we find a critical bond disorder of Vc = (1.6 +- 0.4)t even though within
mean field theory no paramagnetic phase is found for this value of the
interaction. In the site disordered case, we find a critical disorder of Vc =
(5.0 +- 0.5)t at U=4t.
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More than 50 years ago, Laszlo Fuchs asked which abelian groups can be the
group of units of a ring. Though progress has been made, the question remains
open. One could equally well pose the question for various classes of
nonabelian groups. In this paper, we prove that D_2, D_4, D_6, D_8, and D_12
are the only dihedral groups that appear as the group of units of a ring of
positive characteristic (or, equivalently, of a finite ring), and D_2 and D_4k,
where k is odd, are the only dihedral groups that appear as the group of units
of a ring of characteristic 0.
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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.