2,812 research outputs found
An Efficient Algorithm for Haplotype Inference on Pedigrees with a Small Number of Recombinants
Pulsar Polarization Arrays
Pulsar timing arrays (PTAs) consisting of widely distributed and well-timed
millisecond pulsars can serve as a galactic interferometer to measure
gravitational waves. With the same data acquired for PTAs, we propose to
develop pulsar polarization arrays (PPAs), to explore astrophysics and
fundamental physics. As in the case of PTAs, PPAs are best suited to reveal
temporal and spatial correlations at large scales that are hard to mimic by
local noise. To demonstrate the physical potential of PPAs, we consider
detection of ultralight axion-like dark matter (ALDM), through cosmic
birefringence induced by its Chern-Simon coupling. Because of its tiny mass,
the ultralight ALDM can be generated as a Bose-Einstein condensate,
characterized by a strong wavy nature. Incorporating both temporal and spatial
correlations of the signal, we show that PPAs have a potential to probe the
Chern-Simon coupling up to GeV, with a mass
range eV.Comment: 8 pages, 2 figures; comments welcom
Thread of Thought Unraveling Chaotic Contexts
Large Language Models (LLMs) have ushered in a transformative era in the
field of natural language processing, excelling in tasks related to text
comprehension and generation. Nevertheless, they encounter difficulties when
confronted with chaotic contexts (e.g., distractors rather than long irrelevant
context), leading to the inadvertent omission of certain details within the
chaotic context. In response to these challenges, we introduce the "Thread of
Thought" (ThoT) strategy, which draws inspiration from human cognitive
processes. ThoT systematically segments and analyzes extended contexts while
adeptly selecting pertinent information. This strategy serves as a versatile
"plug-and-play" module, seamlessly integrating with various LLMs and prompting
techniques. In the experiments, we utilize the PopQA and EntityQ datasets, as
well as a Multi-Turn Conversation Response dataset (MTCR) we collected, to
illustrate that ThoT significantly improves reasoning performance compared to
other prompting techniques.Comment: 11 pages, 7 figures, 5 table
Borda Regret Minimization for Generalized Linear Dueling Bandits
Dueling bandits are widely used to model preferential feedback prevalent in
many applications such as recommendation systems and ranking. In this paper, we
study the Borda regret minimization problem for dueling bandits, which aims to
identify the item with the highest Borda score while minimizing the cumulative
regret. We propose a rich class of generalized linear dueling bandit models,
which cover many existing models. We first prove a regret lower bound of order
for the Borda regret minimization problem, where
is the dimension of contextual vectors and is the time horizon. To attain
this lower bound, we propose an explore-then-commit type algorithm for the
stochastic setting, which has a nearly matching regret upper bound
. We also propose an EXP3-type algorithm for the
adversarial linear setting, where the underlying model parameter can change at
each round. Our algorithm achieves an regret,
which is also optimal. Empirical evaluations on both synthetic data and a
simulated real-world environment are conducted to corroborate our theoretical
analysis.Comment: 33 pages, 5 figure. This version includes new results for dueling
bandits in the adversarial settin
Midgap States in Antiferromagnetic Heisenberg Chains with A Staggered Field
We study low-energy excitations in antiferromagnetic Heisenberg chains with a
staggered field which splits the spectrum into a longitudinal and a transverse
branch. Bound states are found to exist inside the field induced gap in both
branches. They originate from the edge effects and are inherent to spin-chain
materials. The sine-Gordon scaling (: the
staggered field) provides an accurate description for the gap and midgap
energies in the transverse branch for and the midgap energies in both
branches for over a wide range of magnetic field; however, it can fit
other low-energy excitations only at much lower field. Moreover, the
integer-spin S=1 chain displays scaling behavior that does not fit this scaling
law. These results reveal intriguing features of magnetic excitations in
spin-chain materials that deserve further investigation.Comment: 4 pages, 4figure
Minimizing L1 over L2 norms on the gradient
In this paper, we study the L1/L2 minimization on the gradient for imaging
applications. Several recent works have demonstrated that L1/L2 is better than
the L1 norm when approximating the L0 norm to promote sparsity. Consequently,
we postulate that applying L1/L2 on the gradient is better than the classic
total variation (the L1 norm on the gradient) to enforce the sparsity of the
image gradient. To verify our hypothesis, we consider a constrained formulation
to reveal empirical evidence on the superiority of L1/L2 over L1 when
recovering piecewise constant signals from low-frequency measurements.
Numerically, we design a specific splitting scheme, under which we can prove
subsequential and global convergence for the alternating direction method of
multipliers (ADMM) under certain conditions. Experimentally, we demonstrate
visible improvements of L1/L2 over L1 and other nonconvex regularizations for
image recovery from low-frequency measurements and two medical applications of
MRI and CT reconstruction. All the numerical results show the efficiency of our
proposed approach.Comment: 26 page
The Recovery of Weak Impulsive Signals Based on Stochastic Resonance and Moving Least Squares Fitting
In this paper a stochastic resonance (SR)-based method for recovering weak impulsive signals is developed for quantitative diagnosis of faults in rotating machinery. It was shown in theory that weak impulsive signals follow the mechanism of SR, but the SR produces a nonlinear distortion of the shape of the impulsive signal. To eliminate the distortion a moving least squares fitting method is introduced to reconstruct the signal from the output of the SR process. This proposed method is verified by comparing its detection results with that of a morphological filter based on both simulated and experimental signals. The experimental results show that the background noise is suppressed effectively and the key features of impulsive signals are reconstructed with a good degree of accuracy, which leads to an accurate diagnosis of faults in roller bearings in a run-to failure test
- …