English
Related papers

Related papers: Inverse Transform Sampling for Efficient Doppler-A…

200 papers

Inverse problems involve making inference about unknown parameters of a physical process using observational data. This paper investigates an important class of inverse problems -- the estimation of the initial condition of a…

Methodology · Statistics 2023-02-09 Xiao Liu , Kyongmin Yeo

This paper proposes a direct sampling method for the inverse problem of magnetic induction tomography (MIT). Our approach defines a class of point spread functions with explicit expressions, which are computed via inner products, leading to…

Numerical Analysis · Mathematics 2026-01-29 Junqing Chen , Chengzhe Jiang

The rare-event sampling problem has long been the central limiting factor in molecular dynamics (MD), especially in biomolecular simulation. Recently, diffusion models such as BioEmu have emerged as powerful equilibrium samplers that…

In traditional QCD sum rules, the simple hadron spectral density model of ``delta-function-type ground state + theta-function-type continuous spectrum" determines that there is no perfect parameter selection. In recent years, inverse…

High Energy Physics - Phenomenology · Physics 2024-07-16 Zhen-Xing Zhao , Yi-Peng Xing , Run-Hui Li

Since the mass of the electron is very small relative to atomic masses, Thomson scattering of low-energy photons ($h\nu \ll m_ec^2$) produces thermal Doppler frequency shifts that are much larger than atomic Doppler widths. A method is…

Astrophysics · Physics 2011-05-23 G. B. Rybicki , D. G. Hummer

Normalizing flows are a promising tool for modeling probability distributions in physical systems. While state-of-the-art flows accurately approximate distributions and energies, applications in physics additionally require smooth energies…

Machine Learning · Statistics 2021-12-01 Jonas Köhler , Andreas Krämer , Frank Noé

We derive a novel efficient scheme to measure the rate constant of transitions between stable states separated by high free energy barriers in a complex environment within the framework of transition path sampling. The method is based on…

Statistical Mechanics · Physics 2009-11-07 Titus S. van Erp , Daniele Moroni , Peter G. Bolhuis

In this paper, we have established a new framework of truncated inverse sampling for estimating mean values of non-negative random variables such as binomial, Poisson, hyper-geometrical, and bounded variables. We have derived explicit…

Statistics Theory · Mathematics 2013-11-05 Xinjia Chen

The development of enhanced sampling methods has greatly extended the scope of atomistic simulations, allowing long-time phenomena to be studied with accessible computational resources. Many such methods rely on the identification of an…

Computational Physics · Physics 2022-06-08 Luigi Bonati , GiovanniMaria Piccini , Michele Parrinello

Even in low dimensions, sampling from multi-modal distributions is challenging. We provide the first sampling algorithm for a broad class of distributions -- including all Gaussian mixtures -- with a query complexity that is polynomial in…

Computation · Statistics 2025-10-24 Adrien Vacher , Omar Chehab , Anna Korba

Doppler-broadening thermometry (DBT) can be used as a calibration-free primary reference suitable for practical applications, e.g. reliably measuring temperatures over long periods of time in environments where sensor retrieval is…

Atomic Physics · Physics 2026-01-14 Nicola Agnew , Veronika Vohníková , Erling Riis , Graham Machin , Aidan S. Arnold

Biased enhanced sampling methods utilizing collective variables (CVs) are powerful tools for sampling conformational ensembles. Due to high intrinsic dimensions, efficiently generating conformational ensembles for complex systems requires…

Machine Learning · Computer Science 2023-12-19 Yikai Liu , Tushar K. Ghosh , Guang Lin , Ming Chen

The method of Doppler - free comb - spectroscopy for dipole transitions was proposed. The calculations for susceptibility spectrum for moving two-level atoms driving by strong counter propagating combs have been done. The used theoretical…

Optics · Physics 2014-03-07 S. A. Pulkin , A. Kalinichev , V. Arnautov , S. V. Uvarova , S. Savel'eva

In the note we consider an iterative generalisation of the rejection sampling method. In high energy physics, this sampling is frequently used for event generation, i.e. preparation of phase space points distributed according to a matrix…

High Energy Physics - Phenomenology · Physics 2008-07-18 A. Sherstnev

A simple numerical method for loading of a relativistic Maxwellian-type distribution is proposed based on inverse transform sampling. The relativistic Maxwellian energy distribution is introduced as an alternative to the Maxwell-J\"{u}ttner…

Plasma Physics · Physics 2026-03-05 Takayuki Umeda

A new measuring technique dedicated to bubble velocity and size measurements in complex bubbly flows such as those occurring in bubble columns is proposed. This sensor combines the phase detection capability of a conical optical fiber, with…

Fluid Dynamics · Physics 2021-09-17 Anthony Lefebvre , Yann Mezui , Martin Obligado , Stéphane Gluck , Alain Cartellier

In this paper, we derive a Sampling Method to solve the inverse shape problem of recovering an inclusion with a generalized impedance condition from electrostatic Cauchy data. The generalized impedance condition is a second-order…

Analysis of PDEs · Mathematics 2019-05-30 Isaac Harris

We present a mechanism to steer the sampling diversity of denoising diffusion and flow matching models, allowing users to sample from a sharper or broader distribution than the training distribution. We build on the observation that these…

Machine Learning · Computer Science 2026-05-26 Yanbo Xu , Yu Wu , Sungjae Park , Zhizhuo Zhou , Shubham Tulsiani

A new inversion method for determining near-surface shear currents from a measured wave spectrum is introduced. The method is straightforward to implement and starts from the existing state-of-the-art technique of assigning effective depths…

Atmospheric and Oceanic Physics · Physics 2020-02-19 Benjamin K. Smeltzer , Eirik Æsøy , Anna Ådnøy , Simen Å. Ellingsen

This work introduces a new approximate proximal sampler that operates solely with zeroth-order information of the potential function. Prior theoretical analyses have revealed that proximal sampling corresponds to alternating forward and…

Machine Learning · Computer Science 2026-03-23 Hirohane Takagi , Atsushi Nitanda
‹ Prev 1 3 4 5 6 7 10 Next ›