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Related papers: O(N) algorithms for disordered systems

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In this work we discuss the problem of selecting suitable approximators from families of parameterized elementary functions that are known to be dense in a Hilbert space of functions. We consider and analyze published procedures, both…

Numerical Analysis · Computer Science 2016-09-01 Alexander N. Gorban , Ivan Yu. Tyukin , Danil V. Prokhorov , Konstantin I. Sofeikov

An expansion method for perturbation of the zero temperature grand canonical density matrix is introduced. The method achieves quadratically convergent recursions that yield the response of the zero temperature density matrix upon variation…

Materials Science · Physics 2009-11-10 Anders M. N. Niklasson , Matt Challacombe

We investigate the problem of sequential linear data prediction for real life big data applications. The second order algorithms, i.e., Newton-Raphson Methods, asymptotically achieve the performance of the "best" possible linear data…

Data Structures and Algorithms · Computer Science 2017-01-20 Burak C. Civek , Suleyman S. Kozat

We examine the onset of Anderson localization in three-dimensional systems with structural disorder in the form of lattice irregularities and in the absence of any on-site disordered potential. Analyzing two models with distinct types of…

Disordered Systems and Neural Networks · Physics 2025-05-29 Sourav Bhattacharjee , Piotr Sierant , Marek Dudyński , Jan Wehr , Jakub Zakrzewski , Maciej Lewenstein

We represent low dimensional quantum mechanical Hamiltonians by moderately sized finite matrices that reproduce the lowest O(10) boundstate energies and wave functions to machine precision. The method extends also to Hamiltonians that are…

Quantum Physics · Physics 2015-06-03 Johann Foerster , Alejandro Saenz , Ulli Wolff

We present selected results from combined analytical and numerical studies of the Anderson-impurity model within the framework of infinite order perturbation theory with respect to the hybridization. Our approximation goes considerably…

Condensed Matter · Physics 2009-10-22 F. B. Anders , N. Grewe

The matrix scaling problem, particularly the Sinkhorn-Knopp algorithm, has been studied for over 60 years. In practice, the algorithm often yields high-quality approximations within just a few iterations. Theoretically, however, the…

Data Structures and Algorithms · Computer Science 2025-08-12 Kun He

We study the conformal bootstrap for 3D CFTs with O(N) global symmetry. We obtain rigorous upper bounds on the scaling dimensions of the first O(N) singlet and symmetric tensor operators appearing in the $\phi_i \times \phi_j$ OPE, where…

High Energy Physics - Theory · Physics 2015-10-16 Filip Kos , David Poland , David Simmons-Duffin

An extended Holstein-Primakoff mapping which incorporates both single- and double boson mappings is used in the context of O(N+1) anharmonic oscillator with the global symmetry broken down to O(N) to study the next-to-leading order of the…

High Energy Physics - Phenomenology · Physics 2007-05-23 Alan Dzhioev , J. Wambach , A. Vdovin , Z. Aouissat

Density matrix perturbation theory [Phys. Rev. Lett. Vol. 92, 193001 (2004)] provides an efficient framework for the linear scaling computation of response properties [Phys. Rev. Lett. Vol. 92, 193002 (2004)]. In this article, we generalize…

Computational Physics · Physics 2009-11-11 Anders M. N. Niklasson , Valery Weber , Matt Challacombe

Neural oscillators, originating from second-order ordinary differential equations (ODEs), have demonstrated strong performance in stably learning causal mappings between long-term sequences or continuous temporal functions, as well as in…

Machine Learning · Computer Science 2026-04-21 Zifeng Huang , Konstantin M. Zuev , Yong Xia , Michael Beer

We analyze the problem of determining the electronic ground state within O(N) schemes, focusing on methods in which the total energy is minimized with respect to the density matrix. We note that in such methods a crucially important…

Condensed Matter · Physics 2007-05-23 D. R. Bowler , M. J. Gillan

The Anderson model in one dimension is a quantum particle on a discrete chain of sites with nearest-neighbor hopping and random on-site potentials. It is a progenitor of many further models of disordered systems, and it has spurred numerous…

Disordered Systems and Neural Networks · Physics 2025-11-27 Oleg Evnin

We consider the problem of reconstructing a rank-$k$ $n \times n$ matrix $M$ from a sampling of its entries. Under a certain incoherence assumption on $M$ and for the case when both the rank and the condition number of $M$ are bounded, it…

Machine Learning · Statistics 2017-08-23 David Gamarnik , Quan Li , Hongyi Zhang

It is a well known fact that sequential algorithms which exhibit a strong "local" nature can be adapted to the distributed setting given a legal graph coloring. The running time of the distributed algorithm will then be at least the number…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-05-15 Ken-ichi Kawarabayashi , Gregory Schwartzman

Using a supersymmetry formalism, we reduce exactly the problem of electron motion in an external potential to a new supermatrix model valid at all distances. All approximate nonlinear sigma models obtained previously for disordered systems…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 K. B. Efetov , G. Schwiete , K. Takahashi

Motivated by current interest in disordered systems of interacting electrons, the effectiveness of the geometrically averaged density of states, $\rho_g(\omega)$, as an order parameter for the Anderson transition is examined. In the context…

Strongly Correlated Electrons · Physics 2009-11-11 Yun Song , W. A. Atkinson , R. Wortis

Density Functional Theory (DFT) is widely used for atomistic simulations. However, its reach stays limited due to several limitations such as lack of accurate exchange-correlation functional, requirement of costly O(N 3) diagonalization…

Quantum Physics · Physics 2026-05-18 Namrata Manglani , Samrit Kumar Maity , Shashank Sharma , Soham Phulare , Sanjay Wandhekar

In this paper, we study the tradeoff between the approximation guarantee and adaptivity for the problem of maximizing a monotone submodular function subject to a cardinality constraint. The adaptivity of an algorithm is the number of…

Data Structures and Algorithms · Computer Science 2018-11-01 Alina Ene , Huy L. Nguyen

By employing Random Matrix Theory (RMT) and first-principle calculations, we investigated the behavior of Anderson localization in 1D, 2D and 3D systems characterized by a varying disorder. In particular, we considered random binary layer…

Optics · Physics 2012-08-23 D. Molinari , A. Fratalocchi