Soon Hoe Lim

@su.se

Nordic Institute for Theoretical Physics
UNIVERSITY OF STOCKHOLM



           

https://researchid.co/soonhoe
13

Scopus Publications

331

Scholar Citations

11

Scholar h-index

12

Scholar i10-index

Scopus Publications

  • Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent


  • NOISY FEATURE MIXUP



  • Noisy Recurrent Neural Networks


  • Understanding recurrent neural networks using nonequilibrium response theory


  • Predicting critical transitions in multiscale dynamical systems using reservoir computing
    Soon Hoe Lim, Ludovico Theo Giorgini, Woosok Moon, and J. S. Wettlaufer

    AIP Publishing
    We study the problem of predicting rare critical transition events for a class of slow-fast nonlinear dynamical systems. The state of the system of interest is described by a slow process, whereas a faster process drives its evolution and induces critical transitions. By taking advantage of recent advances in reservoir computing, we present a data-driven method to predict the future evolution of the state. We show that our method is capable of predicting a critical transition event at least several numerical time steps in advance. We demonstrate the success as well as the limitations of our method using numerical experiments on three examples of systems, ranging from low dimensional to high dimensional. We discuss the mathematical and broader implications of our results.

  • Homogenization for Generalized Langevin Equations with Applications to Anomalous Diffusion
    Soon Hoe Lim, Jan Wehr, and Maciej Lewenstein

    Springer Science and Business Media LLC
    AbstractWe study homogenization for a class of generalized Langevin equations (GLEs) with state-dependent coefficients and exhibiting multiple time scales. In addition to the small mass limit, we focus on homogenization limits, which involve taking to zero the inertial time scale and, possibly, some of the memory time scales and noise correlation time scales. The latter are meaningful limits for a class of GLEs modeling anomalous diffusion. We find that, in general, the limiting stochastic differential equations for the slow degrees of freedom contain non-trivial drift correction terms and are driven by non-Markov noise processes. These results follow from a general homogenization theorem stated and proven here. We illustrate them using stochastic models of particle diffusion.

  • Precursors to rare events in stochastic resonance
    L. T. Giorgini, S. H. Lim, W. Moon, and J. S. Wettlaufer

    IOP Publishing
    In stochastic resonance, a periodically forced Brownian particle in a double-well potential jumps between minima at rare increments, the prediction of which pose a major theoretical challenge. Here, we use a path-integral method to predict these transitions by determining the most probable (or "{optimal}") space-time path of a particle. We characterize the optimal path using a direct comparison principle between the Langevin and Hamiltonian dynamical descriptions, allowing us to express the jump condition in terms of the accumulation of noise around the stable periodic path. In consequence, as a system approaches a rare event these fluctuations approach one of the deterministic minimizers, thereby providing a precursor for predicting the stochastic transition. We demonstrate the method numerically, which allows us to determine whether a state is following a stable periodic path or will experience an incipient jump. The vast range of systems that exhibit stochastic resonance behavior insures broad relevance of our framework, which allows one to extract precursor fluctuations from data.

  • Functionals in stochastic thermodynamics: How to interpret stochastic integrals
    Stefano Bo, Soon Hoe Lim, and Ralf Eichhorn

    IOP Publishing
    In stochastic thermodynamics standard concepts from macroscopic thermodynamics, such as heat, work, and entropy production, are generalized to small fluctuating systems by defining them on a trajec ...

  • Homogenization for a Class of Generalized Langevin Equations with an Application to Thermophoresis
    Soon Hoe Lim and Jan Wehr

    Springer Science and Business Media LLC
    We study a class of systems whose dynamics are described by generalized Langevin equations with state-dependent coefficients. We find that in the limit, in which all the characteristic time scales vanish at the same rate, the position variable of the system converges to a homogenized process, described by an equation containing additional drift terms induced by the noise. The convergence results are obtained using the main result in Hottovy et al. (Commun Math Phys 336(3):1259–1283, 2015), whose version is proven here under a weaker spectral assumption on the damping matrix. We apply our results to study thermophoresis of a Brownian particle in a non-equilibrium heat bath.

  • On the Small Mass Limit of Quantum Brownian Motion with Inhomogeneous Damping and Diffusion
    Soon Hoe Lim, Jan Wehr, Aniello Lampo, Miguel Ángel García-March, and Maciej Lewenstein

    Springer Science and Business Media LLC
    We study the small mass limit (or: the Smoluchowski–Kramers limit) of a class of quantum Brownian motions with inhomogeneous damping and diffusion. For Ohmic bath spectral density with a Lorentz–Drude cutoff, we derive the Heisenberg–Langevin equations for the particle’s observables using a quantum stochastic calculus approach. We set the mass of the particle to equal $$m = m_{0} \\epsilon $$m=m0ϵ, the reduced Planck constant to equal $$\\hbar = \\epsilon $$ħ=ϵ and the cutoff frequency to equal $$\\varLambda = E_{\\varLambda }/\\epsilon $$Λ=EΛ/ϵ, where $$m_0$$m0 and $$E_{\\varLambda }$$EΛ are positive constants, so that the particle’s de Broglie wavelength and the largest energy scale of the bath are fixed as $$\\epsilon \\rightarrow 0$$ϵ→0. We study the limit as $$\\epsilon \\rightarrow 0$$ϵ→0 of the rescaled model and derive a limiting equation for the (slow) particle’s position variable. We find that the limiting equation contains several drift correction terms, the quantum noise-induced drifts, including terms of purely quantum nature, with no classical counterparts.

  • Bose polaron as an instance of quantum Brownian motion
    Aniello Lampo, Soon Hoe Lim, Miguel Ángel García-March, and Maciej Lewenstein

    Verein zur Forderung des Open Access Publizierens in den Quantenwissenschaften
    We study the dynamics of a quantum impurity immersed in a Bose-Einstein condensate as an open quantum system in the framework of the quantum Brownian motion model. We derive a generalized Langevin equation for the position of the impurity. The Langevin equation is an integrodifferential equation that contains a memory kernel and is driven by a colored noise. These result from considering the environment as given by the degrees of freedom of the quantum gas, and thus depend on its parameters, e.g. interaction strength between the bosons, temperature, etc. We study the role of the memory on the dynamics of the impurity. When the impurity is untrapped, we find that it exhibits a super-diffusive behavior at long times. We find that back-flow in energy between the environment and the impurity occurs during evolution. When the particle is trapped, we calculate the variance of the position and momentum to determine how they compare with the Heisenberg limit. One important result of this paper is that we find position squeezing for the trapped impurity at long times. We determine the regime of validity of our model and the parameters in which these effects can be observed in realistic experiments.

  • Lindblad model of quantum Brownian motion
    Aniello Lampo, Soon Hoe Lim, Jan Wehr, Pietro Massignan, and Maciej Lewenstein

    American Physical Society (APS)
    Programa Masters d'Excel-lencia of the Fundacio Catalunya-La Pedrera; ERC; EU [323714]; Fundacio Cellex; Spanish MINECO [SEV-2015-0522, FIS2013-46768]; Generalitat de Catalunya [SGR 874]; "Ramon y Cajal" fellowship; NSF [MS 131271]

RECENT SCHOLAR PUBLICATIONS

  • NoisyMix: Boosting Model Robustness to Common Corruptions
    NB Erichson, SH Lim, W Xu, F Utrera, Z Cao, MW Mahoney
    Proc. of the 27th International Conference on AISTATS 2024

  • Gated Recurrent Neural Networks with Weighted Time-Delay Feedback
    NB Erichson, SH Lim, MW Mahoney
    arXiv preprint arXiv:2212.00228 2022

  • Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent
    SH Lim, Y Wan, U Şimşekli
    Advances in Neural Information Processing Systems 35 2022

  • Noisy Feature Mixup
    SH Lim, NB Erichson, F Utrera, W Xu, MW Mahoney
    Proc. of the 2022 ICLR Conference 2021

  • Anomalous thermodynamics in homogenized generalized Langevin systems
    SH Lim
    Journal of Physics A: Mathematical and Theoretical 54 (15), 155001 2021

  • Noisy Recurrent Neural Networks
    SH Lim, NB Erichson, L Hodgkinson, MW Mahoney
    Advances in Neural Information Processing Systems 34 2021

  • Modeling the El Nino Southern Oscillation with Neural Differential Equations
    LT Giorgini, SH Lim, W Moon, N Chen, JS Wettlaufer
    ICML 2021 Time Series Workshop 2021

  • Understanding Recurrent Neural Networks Using Nonequilibrium Response Theory
    SH Lim
    Journal of Machine Learning Research 22, 47:1-47:48 2021

  • Predicting critical transitions in multiscale dynamical systems using reservoir computing
    SH Lim, LT Giorgini, W Moon, JS Wettlaufer
    Chaos: An Interdisciplinary Journal of Nonlinear Science 30 (12) 2020

  • Precursors to rare events in stochastic resonance
    LT Giorgini, SH Lim, W Moon, JS Wettlaufer
    Europhysics letters 129 (4), 40003 2020

  • Homogenization for generalized Langevin equations with applications to anomalous diffusion
    SH Lim, J Wehr, M Lewenstein
    Annales Henri Poincar 21, 1813–1871 2020

  • Stochastic Processes: From Classical to Quantum
    SH Lim
    2020

  • Stochastic Lorenz Systems are Generalized Langevin Systems
    SH Lim
    2020

  • A Short Introduction to Concentration Inequalities
    SH Lim
    2020

  • A Primer on Multiscale Method for Slow-Fast SDE Systems
    SH Lim
    2020

  • Functionals in stochastic thermodynamics: how to interpret stochastic integrals
    S Bo, SH Lim, R Eichhorn
    Journal of Statistical Mechanics: Theory and Experiment 2019 (8), 084005 2019

  • Homogenization for a class of generalized Langevin equations with an application to thermophoresis
    SH Lim, J Wehr
    Journal of Statistical Physics 174 (3), 656-691 2019

  • On the small mass limit of quantum Brownian motion with inhomogeneous damping and diffusion
    SH Lim, J Wehr, A Lampo, M Garca-March, M Lewenstein
    Journal of Statistical Physics 170 (2), 351-377 2018

  • Bose polaron as an instance of quantum Brownian motion
    A Lampo, SH Lim, M Garca-March, M Lewenstein
    Quantum 1, 30 2017

  • M Garc a-March, M. Lewenstein
    A Lampo, SH Lim
    Quantum 1, 30 2017

MOST CITED SCHOLAR PUBLICATIONS

  • Bose polaron as an instance of quantum Brownian motion
    A Lampo, SH Lim, M Garca-March, M Lewenstein
    Quantum 1, 30 2017
    Citations: 89

  • Noisy Recurrent Neural Networks
    SH Lim, NB Erichson, L Hodgkinson, MW Mahoney
    Advances in Neural Information Processing Systems 34 2021
    Citations: 43

  • Noisy Feature Mixup
    SH Lim, NB Erichson, F Utrera, W Xu, MW Mahoney
    Proc. of the 2022 ICLR Conference 2021
    Citations: 28

  • Predicting critical transitions in multiscale dynamical systems using reservoir computing
    SH Lim, LT Giorgini, W Moon, JS Wettlaufer
    Chaos: An Interdisciplinary Journal of Nonlinear Science 30 (12) 2020
    Citations: 26

  • Lindblad model of quantum Brownian motion
    A Lampo, SH Lim, J Wehr, P Massignan, M Lewenstein
    Physical Review A 94 (4), 042123 2016
    Citations: 23

  • Functionals in stochastic thermodynamics: how to interpret stochastic integrals
    S Bo, SH Lim, R Eichhorn
    Journal of Statistical Mechanics: Theory and Experiment 2019 (8), 084005 2019
    Citations: 20

  • NoisyMix: Boosting Model Robustness to Common Corruptions
    NB Erichson, SH Lim, W Xu, F Utrera, Z Cao, MW Mahoney
    Proc. of the 27th International Conference on AISTATS 2024
    Citations: 19

  • Homogenization for a class of generalized Langevin equations with an application to thermophoresis
    SH Lim, J Wehr
    Journal of Statistical Physics 174 (3), 656-691 2019
    Citations: 18

  • Understanding Recurrent Neural Networks Using Nonequilibrium Response Theory
    SH Lim
    Journal of Machine Learning Research 22, 47:1-47:48 2021
    Citations: 17

  • Homogenization for generalized Langevin equations with applications to anomalous diffusion
    SH Lim, J Wehr, M Lewenstein
    Annales Henri Poincar 21, 1813–1871 2020
    Citations: 13

  • On the small mass limit of quantum Brownian motion with inhomogeneous damping and diffusion
    SH Lim, J Wehr, A Lampo, M Garca-March, M Lewenstein
    Journal of Statistical Physics 170 (2), 351-377 2018
    Citations: 12

  • Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent
    SH Lim, Y Wan, U Şimşekli
    Advances in Neural Information Processing Systems 35 2022
    Citations: 11

  • Precursors to rare events in stochastic resonance
    LT Giorgini, SH Lim, W Moon, JS Wettlaufer
    Europhysics letters 129 (4), 40003 2020
    Citations: 4

  • M Garc a-March, M. Lewenstein
    A Lampo, SH Lim
    Quantum 1, 30 2017
    Citations: 3

  • Anomalous thermodynamics in homogenized generalized Langevin systems
    SH Lim
    Journal of Physics A: Mathematical and Theoretical 54 (15), 155001 2021
    Citations: 2

  • Modeling the El Nino Southern Oscillation with Neural Differential Equations
    LT Giorgini, SH Lim, W Moon, N Chen, JS Wettlaufer
    ICML 2021 Time Series Workshop 2021
    Citations: 2

  • Gated Recurrent Neural Networks with Weighted Time-Delay Feedback
    NB Erichson, SH Lim, MW Mahoney
    arXiv preprint arXiv:2212.00228 2022
    Citations: 1