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Self-consistent field theory (SCFT) has proven to be a powerful tool for modeling equilibrium microstructures of soft materials, particularly for multiblock polymers. A very successful approach to numerically solving the SCFT set of…

Soft Condensed Matter · Physics 2017-01-04 David M. Ackerman , Kris Delaney , Glenn H. Fredrickson , Baskar Ganapathysubramanian

Stochastic compositional optimization generalizes classic (non-compositional) stochastic optimization to the minimization of compositions of functions. Each composition may introduce an additional expectation. The series of expectations may…

Optimization and Control · Mathematics 2021-09-29 Tianyi Chen , Yuejiao Sun , Wotao Yin

This paper concerns models and convergence principles for dealing with stochasticity in a wide range of algorithms arising in nonlinear analysis and optimization in Hilbert spaces. It proposes a flexible geometric framework within which…

Optimization and Control · Mathematics 2026-02-17 Patrick L. Combettes , Javier I. Madariaga

The second-order Green's function method (GF2) was shown recently to be an accurate self-consistent approach for electronic structure of correlated systems since the self-energy accounts for both the weak and some of the strong correlation.…

Chemical Physics · Physics 2016-03-31 Daniel Neuhauser , Roi Baer , Dominika Zgid

This work analyzes the overall computational complexity of the stochastic Galerkin finite element method (SGFEM) for approximating the solution of parameterized elliptic partial differential equations with both affine and non-affine random…

Numerical Analysis · Mathematics 2020-01-22 Nick Dexter , Clayton Webster , Guannan Zhang

The self-consistent field (SCF) iteration, combined with its variants, is one of the most widely used algorithms in quantum chemistry. We propose a procedure to adapt the SCF iteration for the p-Laplacian eigenproblem, which is an important…

Numerical Analysis · Mathematics 2021-11-23 Parikshit Upadhyaya , Elias Jarlebring , Francesco Tudisco

The convergence of iterative schemes to achieve self-consistency in mean field problems such as the Schr\"odinger-Poisson equation is notoriously capricious. It is particularly difficult in regimes where the non-linearities are strong such…

Mesoscale and Nanoscale Physics · Physics 2026-05-14 Antonio Lacerda-Santos , Xavier Waintal

We consider and analyze applying a spectral inverse iteration algorithm and its subspace iteration variant for computing eigenpairs of an elliptic operator with random coefficients. With these iterative algorithms the solution is sought…

Numerical Analysis · Computer Science 2017-06-16 Harri Hakula , Mikael Laaksonen

It has recently been shown that configuration state functions (CSF) with local orbitals can provide a compact reference state for low-spin open-shell electronic structures, such as antiferromagnetic states. However, optimizing a low-spin…

Chemical Physics · Physics 2025-08-05 Hugh G. A. Burton

Total energy electronic structure calculations, based on density functional theory or on the more empirical tight binding approach, are generally believed to scale as the cube of the number of electrons. By using the localisaton property of…

Materials Science · Physics 2009-11-11 Florian R. Krajewski , Michele Parrinello

The recently developed localized orbital scaling correction (LOSC) method shows the ability to systematically and size-consistently reduce the delocalization error existing in conventional density functional approximations (DFAs). Applying…

Chemical Physics · Physics 2020-10-19 Yuncai Mei , Zehua Chen , Weitao Yang

A method of the self-consistent calculation of the thermodynamical and correlation functions is presented. This approach is based on the GRPA (generalized random phase approximation) scheme with the inclusion of the mean field corrections.…

Superconductivity · Physics 2016-08-31 I. V. Stasyuk , A. M. Shvaika , K. V. Tabunshchyk

Suppose that we are given an arbitrary graph $G=(V, E)$ and know that each edge in $E$ is going to be realized independently with some probability $p$. The goal in the stochastic matching problem is to pick a sparse subgraph $Q$ of $G$ such…

Data Structures and Algorithms · Computer Science 2020-02-28 Soheil Behnezhad , Mahsa Derakhshan , MohammadTaghi Hajiaghayi

This paper develops a framework for the error analysis in nonparametric model fitting of fractional stochastic differential equations based on discrete observations. We identify and quantify the main error sources -- time discretization,…

Probability · Mathematics 2026-05-07 Mahdi Dehshiri , Kerlyns Martinez , Lauri Viitasaari

Stochastic gradient methods for machine learning and optimization problems are usually analyzed assuming data points are sampled \emph{with} replacement. In practice, however, sampling \emph{without} replacement is very common, easier to…

Machine Learning · Computer Science 2016-10-18 Ohad Shamir

A self-consistent calculation scheme for correlated electron systems is created based on the density-functional theory (DFT). Our scheme is a multi-reference DFT (MR-DFT) calculation in which the electron charge density is reproduced by an…

Strongly Correlated Electrons · Physics 2009-11-13 Koichi Kusakabe , Naoshi Suzuki , Shusuke Yamanaka , Kizashi Yamaguchi

We consider conditional tests for non-negative discrete exponential families. We develop two Markov Chain Monte Carlo (MCMC) algorithms which allow us to sample from the conditional space and to perform approximated tests. The first…

Computation · Statistics 2017-07-27 Roberto Fontana , Francesca Romana Crucinio

The paper proposes a method to obtain the optimal basis set for solving the self consistent field (SCF) equations for large atomic systems in order to calculate the energy barriers in tunneling structures, with higher accuracy and speed.…

Mathematical Physics · Physics 2009-12-16 Sever Spanulescu

In this paper, we provide novel algorithms with identifiability guarantees for simplex-structured matrix factorization (SSMF), a generalization of nonnegative matrix factorization. Current state-of-the-art algorithms that provide…

Machine Learning · Computer Science 2021-05-12 Maryam Abdolali , Nicolas Gillis

We formulate the Kohn-Sham density functional theory (KS-DFT) as a statistical theory in which the electron density is deter-mined from an average of correlated stochastic densities in a trace formula. The key idea is that it is sufficient…

Materials Science · Physics 2015-06-15 Roi Baer , Daniel Neuhauser , Eran Rabani