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A systematically improvable wave function is proposed for the numerical solution of strongly correlated systems. With a stochastic optimization method, based on the auxiliary field quantum Monte Carlo technique, an effective temperature…

Strongly Correlated Electrons · Physics 2022-03-22 Sandro Sorella

Based on Smirnov's decomposition theorem we prove that every rectifiable $1$-current $T$ with finite mass $\mathbb{M}(T)$ and finite mass $\mathbb{M}(\partial T)$ of its boundary $\partial T$ can be approximated in mass by a sequence of…

Functional Analysis · Mathematics 2018-10-22 Andrea Marchese , Benedikt Wirth

This paper shows that the semi-dual formulation of the optimal transport problem has a degenerate saddle-point structure, and that its numerical solution is equivalent to solving a constrained optimization problem. We derive necessary and…

Optimization and Control · Mathematics 2026-05-20 Anton Selitskiy , David Millard

In recent years efficient algorithms have been developed for the numerical computation of relativistic single-particle path integrals in quantum field theory. Here, we adapt this "worldline Monte Carlo" approach to the standard problem of…

Assuming power travels instantaneously, can be steered by us, and is lost quadratically in each power line, the dynamic optimal power flow problem simplifies to a min-cost dynamic generalized flow with quadratic losses (MCDGFWQL) problem.…

Optimization and Control · Mathematics 2024-04-08 Jacob H. Rothschild

The well-posedness of a phase-field approximation to the Willmore flow with area and volume constraints is established when the functional approximating the area has no critical point satisfying the two constraints. The existence proof…

Analysis of PDEs · Mathematics 2012-12-27 Pierluigi Colli , Philippe Laurencot

We introduce a new non-linear optimal transport formulation for a pair of probability measures on $\mathbb{R}^d$ sharing a common barycentre, in which admissible transference plans satisfy two martingale-type constraints. This bi-martingale…

Probability · Mathematics 2025-11-03 Karol Bołbotowski

A new Monte Carlo scheme based on the system of Tsallis's generalized statistical mechanics is applied to a simple double well potential to calculate the canonical thermal average of potential energy. Although we observed serious…

Statistical Mechanics · Physics 2009-10-31 Masao Iwamatsu , Yutaka Okabe

Charge transport is well understood in both highly ordered materials (band conduction) or highly disordered ones (hopping conduction). In moderately disordered materials -- including many organic semiconductors -- the approximations valid…

Chemical Physics · Physics 2021-06-16 Daniel Balzer , Thijs J. A. M. Smolders , David Blyth , Samantha N. Hood , Ivan Kassal

The Diffusion Monte Carlo method is devoted to the computation of electronic ground-state energies of molecules. In this paper, we focus on implementations of this method which consist in exploring the configuration space with a {\bf fixed}…

Numerical Analysis · Mathematics 2007-05-23 Tony Lelievre , Mohamed El Makrini , Benjamin Jourdain

We prove a pointwise $C^{2,\,\alpha}$ estimate for the potential of the optimal transport map in the case that the densities are only close to constant in a certain $L^p$ sense.

Analysis of PDEs · Mathematics 2025-05-02 Arghya Rakshit

In order to find the equilibrium geometries of molecules and solids and to perform ab initio molecular dynamics, it is necessary to calculate the forces on the nuclei. We present a correlated sampling method to efficiently calculate…

Condensed Matter · Physics 2009-10-31 Claudia Filippi , C. J. Umrigar

We study an approximate controllability problem for the continuity equation and its application to constructing transport maps with normalizing flows. Specifically, we construct time-dependent controls $\theta=(w, a, b)$ in the vector field…

Optimization and Control · Mathematics 2025-08-19 Antonio Álvarez-López , Borjan Geshkovski , Domènec Ruiz-Balet

We provide theoretical convergence bounds for the variational Monte Carlo (VMC) method as applied to optimize neural network wave functions for the electronic structure problem. We study both the energy minimization phase and the supervised…

Machine Learning · Computer Science 2025-03-07 Nilin Abrahamsen , Zhiyan Ding , Gil Goldshlager , Lin Lin

We consider the conjecture proposed in Matsumoto, Zhang and Schiebinger (2022) suggesting that optimal transport with quadratic regularisation can be used to construct a graph whose discrete Laplace operator converges to the…

Analysis of PDEs · Mathematics 2022-12-02 Gilles Mordant , Stephen Zhang

Weak optimal transport generalizes the classical theory of optimal transportation to nonlinear cost functions and covers a range of problems that lie beyond the traditional theory - including entropic transport, martingale transport, and…

Probability · Mathematics 2025-07-16 Filip Pramenković

Approximate natural orbitals are investigated as a way to improve a Monte Carlo configuration interaction (MCCI) calculation. We introduce a way to approximate the natural orbitals in MCCI and test these and approximate natural orbitals…

Chemical Physics · Physics 2013-04-12 J. P. Coe , M. J. Paterson

The Riccati-type nonlinear differential equation, also known as the Variable Phase Approach or Phase Function Method, is used to construct local inverse potentials for the \( ^3S_1 \) and \( ^1S_0 \) states of the deuteron. The Morse…

Nuclear Theory · Physics 2024-07-08 Anil Khachi , Gabor Balassa

In this paper, we develop a theory of new classes of discrete convex functions, called L-extendable functions and alternating L-convex functions, defined on the product of trees. We establish basic properties for optimization: a…

Optimization and Control · Mathematics 2016-01-19 Hiroshi Hirai

This paper studies a variant of the minimum-cost flow problem in a graph with convex cost function where the demands at the vertices are functions depending on a one-dimensional parameter $\lambda$. We devise two algorithmic approaches for…

Data Structures and Algorithms · Computer Science 2022-03-25 Per Joachims , Max Klimm , Philipp Warode
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