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An expectation-maximization algorithm for continuous-time hidden Markov models

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arXiv 2021年

作者： Wang, Qingcan Weinan, E. Program in Applied and Computational Mathematics Princeton University United States Department of Mathematics and Program in Applied and Computational Mathematics Princeton University United States

We propose a unified framework that extends the inference methods for classical hidden Markov models to continuous settings, where both the hidden states and observations occur in continuous time. Two different settings are analyzed: hidden jump process with a finite state space, and hidden diffusion process with a continuous state space. For each setting, we first estimate the hidden states given the observations and model parameters, showing that the posterior distribution of the hidden states can be described by differential equations in continuous time. We then consider the estimation of unknown model parameters, deriving the continuous-time formulas for the expectation-maximization algorithm. We also propose a Monte Carlo method based on the continuous formulation, sampling the posterior distribution of the hidden states and updating the parameter *** Codes 60J25, 65C40 Copyright © 2021, The Authors. All rights reserved.

关键词： Continuous time systems

Theoretical Prediction of the Effective Dynamic Dielectric Constant of Disordered Hyperuniform Anisotropic Composites Beyond the Long-Wavelength Regime

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arXiv 2023年

作者： Kim, Jaeuk Torquato, Salvatore Department of Chemistry Princeton University PrincetonNJ08544 United States Princeton Materials Institute Princeton University PrincetonNJ08544 United States Department of Physics Princeton University PrincetonNJ08544 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

Torquato and Kim [Phys. Rev. X 11, 296 021002 (2021)] derived exact nonlocal strong-contrast expansions of the effective dynamic dielectric constant tensor Εe(kq, ω) that treat general three-dimensional (3D) two-phase composite microstructures, which are valid well beyond the long-wavelength regime. Here, we demonstrate that truncating this general rapidly converging expansion at the two- and three-point levels is a powerful theoretical tool from which one can extract accurate approximations suited for various microstructural symmetries. Among other results, we show that such truncations yield closed-form formulas applicable to transverse polarization in layered media and transverse magnetic polarization in transversely isotropic media, respectively. We apply these formulas to estimate Εe(kq, ω) for models of 3D disordered hyperuniform layered and transversely isotropic media: nonstealthy hyperuniform media and stealthy hyperuniform media. In particular, we show that stealthy hyperuniform layered and transversely isotropic media are perfectly transparent (trivially implying no Anderson localization, in principle) within finite wave number intervals through the third-order terms. For all models considered here, we validate that the second-order formulas, which depend on the spectral density, are already very accurate well beyond the long-wavelength regime by showing very good agreement with the finite-difference time-domain (FDTD) simulations. The high predictive power of the second-order formula is due to the fact that higher-order contributions are negligibly small, implying that it very accurately approximates multiple scattering through all orders. This implies that there can be no Anderson localization within the predicted perfect transparency interval in stealthy hyperuniform layered and transversely isotropic media in practice because the localization length (associated with only possibly negligibly small higher-order contributions) should be very large compar

关键词： Spectral density

Modeling Neural Activity with Conditionally Linear Dynamical Systems

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arXiv 2025年

作者： Geadah, Victor Nejatbakhsh, Amin Lipshutz, David Pillow, Jonathan W. Williams, Alex H. Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Center for Computational Neuroscience Flatiron Institute New York CityNY United States Department of Neuroscience Baylor College of Medicine HoustonTX United States Princeton Neuroscience Institute PrincetonNJ United States Center for Neural Science New York University New York CityNY United States

Neural population activity exhibits complex, nonlinear dynamics, varying in time, over trials, and across experimental conditions. Here, we develop Conditionally Linear Dynamical System (CLDS) models as a general-purpose method to characterize these dynamics. These models use Gaussian Process (GP) priors to capture the nonlinear dependence of circuit dynamics on task and behavioral variables. Conditioned on these covariates, the data is modeled with linear dynamics. This allows for transparent interpretation and tractable Bayesian inference. We find that CLDS models can perform well even in severely data-limited regimes (e.g. one trial per condition) due to their Bayesian formulation and ability to share statistical power across nearby task conditions. In example applications, we apply CLDS to model thalamic neurons that nonlinearly encode heading direction and to model motor cortical neurons during a cued reaching task. © 2025, CC BY.

关键词： Neurons

Effective electromagnetic wave properties of disordered stealthy hyperuniform layered media beyond the quasistatic regime

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arXiv 2023年

Disordered stealthy hyperuniform dielectric composites exhibit novel electromagnetic wave transport properties in two and three dimensions. Here, we carry out the first study of the electromagnetic properties of one-dimensional (1D) disordered stealthy hyperuniform layered media. From an exact nonlocal theory, we derive an approximation formula for the effective dynamic dielectric constant tensor Εe(kq, ω) of general 1D media that is valid well beyond the quasistatic regime and apply it to 1D stealthy hyperuniform systems. We consider incident waves of transverse polarization, frequency ω, and wavenumber kq. Our formula for Εe(kq, ω), which is given in terms of the spectral density, leads to a closed-form relation for the transmittance T. Our theoretical predictions are in excellent agreement with finite-difference time-domain (FDTD) simulations. Stealthy hyperuniform layered media have perfect transparency intervals up to a finite wavenumber, implying no Anderson localization, but non-stealthy hyperuniform media are not perfectly transparent. Our predictive theory provides a new path for the inverse design of the wave characteristics of disordered layered media, which are readily fabricated, by engineering their spectral densities. © 2023 Optica Publishing Group © 2023, CC BY.

关键词： Spectral density

Characterization of void space, large-scale structure, and transport properties of maximally random jammed packings of superballs

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Physical Review Materials 2022年第2期6卷 025603-025603页

作者： Charles Emmett Maher Frank H. Stillinger Salvatore Torquato Department of Chemistry Princeton University Princeton New Jersey 08544 USA Department of Physics Princeton University Princeton New Jersey 08544 USA Princeton Institute for the Science and Technology of Materials Princeton University Princeton New Jersey 08544 USA Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA

Dense, disordered packings of particles are useful models of low-temperature amorphous phases of matter, biological systems, granular media, and colloidal systems. The study of dense packings of nonspherical particles enables one to ascertain how rotational degrees of freedom affect packing behavior. Here, we study superballs, a large family of deformations of the sphere, defined in three dimensions by |x1|2p+|x2|2p+|x3|2p≤1, where p∈(0,∞) is a deformation parameter indicating to what extent the shape deviates from a sphere. As p increases from the sphere point (p=1), the superball tends to a cuboidal shape and approaches a cube in the p→∞ limit. As p→0.5, it approaches an octahedron, becomes a concave body with octahedral symmetry for p<0.5, and approaches a three-dimensional cross in the limit p→0. Previous characterization of superball packings has shown that they have a maximally random jammed (MRJ) state, whose properties (e.g., packing fraction ϕ, average contact number Z¯) vary nonanalytically as p diverges from unity. Here, we use an event-driven molecular dynamics algorithm to produce MRJ superball packings with 0.85≤p≤1.50. To supplement the previous work on such packings, we characterize their large-scale structure by examining the behaviors of their structure factors S(Q) and spectral densities χ̃V(Q), as the wave number Q tends to zero, and find that these packings are effectively hyperuniform for all values of p examined. We show that the mean width w¯ is a useful length scale to make distances dimensionless in order to compare systematically superballs of different shape. Moreover, we compute the complementary cumulative pore-size distribution F(δ) and find that the pore sizes tend to decrease as |1−p| increases. From F(δ), we estimate how the fluid permeability, mean survival time, and principal diffusion relaxation time vary as a function of p. Additionally, we compute the diffusion “spreadability” S(t) [Torquato, Phys. Rev. E 104, 054102 (2021)] of

关键词： Granular packing

大气阻塞Charney-De Vore准地转方程的能量稳定性

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中国科学：数学 2022年第7期52卷 823-844页

作者：陈志敏熊向明深圳大学数学与统计学院深圳518060 The Program in Applied and Computational Mathematics Princeton UniversityrincetonJ08544USA

Charney和DeVore(1979)发现,由于地形的影响,β平面槽道中正压大气的准地转流动有多个平衡态.本文证明了这种流动的基本流在某个参数范围内(包括平坦地表的特殊情形)是渐近稳定的,因此排除了这一参数范围内存在多个平衡态的可能性.本文... 详细信息

Charney和DeVore(1979)发现,由于地形的影响,β平面槽道中正压大气的准地转流动有多个平衡态.本文证明了这种流动的基本流在某个参数范围内(包括平坦地表的特殊情形)是渐近稳定的,因此排除了这一参数范围内存在多个平衡态的可能性.本文作者还发现,为了使Charney-DeVore准地转方程适定,需要补充一个平均经向力或平均经向速度的条件.本文在不同的地表起伏幅度下,采用拟弧长延拓法证实至少存在3个平衡态;还通过高精度直接数值模拟研究了这些平衡态的稳定性.

关键词：准地转方程正压流动 β平面槽道模型地形效应非线性稳定性拟弧长延拓法

Transient rod-climbing in an Oldroyd-B fluid

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arXiv 2025年

作者： Ruangkriengsin, Tachin Brandão, Rodolfo Wu, Katie Hwang, Jonghyun Boyko, Evgeniy Stone, Howard A. Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States School of Mathematics University of Bristol Fry Building Woodland Road BristolBS8 1UG United Kingdom Department of Mechanical and Aerospace Engineering Princeton University PrincetonNJ08544 United States Faculty of Mechanical Engineering Technion – Israel Institute of Technology Haifa3200003 Israel

The Weissenberg effect, or rod-climbing phenomenon, occurs in non-Newtonian fluids where the fluid interface ascends along a rotating rod. Despite its prominence, theoretical insights into this phenomenon remain limited. In earlier work, Joseph & Fosdick (Arch. Rat. Mech. Anal., vol. 49, 1973, pp. 321–380) employed domain perturbation methods for second-order fluids to determine the equilibrium interface height by expanding solutions based on the rotation speed. In this work, we investigate the time-dependent interface height through asymptotic analysis with dimensionless variables and equations using the Oldroyd-B model. We begin by neglecting surface tension and inertia to focus on the interaction between gravity and viscoelasticity. In the small-deformation scenario, the governing equations indicate the presence of a boundary layer in time, where the interface rises rapidly over a short time scale before gradually approaching a steady state. By employing a stretched time variable, we derive the transient velocity field and corresponding interface profile on this short time scale and recover the steady-state profile on a longer time scale. Subsequently, we reintroduce small but finite inertial effects to investigate their interplay with viscoelasticity and propose a criterion for determining the conditions under which rod-climbing occurs. © 2025, CC BY.

关键词： Non Newtonian liquids

Empowering Optimal Control with Machine Learning: A Perspective from Model Predictive Control

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IFAC-PapersOnLine 2022年第30期55卷 121-126页

作者： E Weinan Jiequn Han Jihao Long AI for Science Institute Beijing Center for Machine Learning Research and School of Mathematical Sciences Peking University Beijing China Center for Computational Mathematics Flatiron Institute New York 10010 USA Program of Applied and Computational Mathematics Princeton University Princeton 08544 USA

Solving complex optimal control problems have confronted computational challenges for a long time. Recent advances in machine learning have provided us with new opportunities to address these challenges. This paper takes model predictive control, a popular optimal control method, as the primary example to survey recent progress that leverages machine learning techniques to empower optimal control solvers. We also discuss some of the main challenges encountered when applying machine learning to develop more robust optimal control algorithms.

关键词： Machine Learning Optimal Control Model Predictive Control

Low-Rank Decomposition of Plasma Kinetic Distributions in the Collisional Transition Regime

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Low-Rank Decomposition of Plasma Kinetic Distributions in th...

2022 IEEE International Conference on Plasma Science, ICOPS 2022

作者： Coughlin, J. Shumlak, U. Hu, J. University of Washington Applied Mathematics SeattleWA United States University of Washington Computational Plasma Dynamics Laboratory Aerospace and Energetics Research Program SeattleWA United States

ISBN: (纸本)9781665479257

The strength of collisional effects in a plasma can be summarized by the non-dimensional Knudsen number Kn. For very small values of Kn, plasma behavior is well-described by the 5N moment fluid model, including the Braginskii closure. When Kn is large, plasmas are best described by a fully kinetic model such as the Vlasov-Maxwell system. For intermediate values of the Knudsen number, i.e. 10-2 © 2022 IEEE.

关键词： Collisional plasmas