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We perform a data-driven dimensionality reduction of the scale-dependent 4-point vertex function characterizing the functional Renormalization Group (fRG) flow for the widely studied two-dimensional $t - t'$ Hubbard model on the square…

We analyze the one-dimensional (1D) and the two-dimensional (2D) repulsive Hubbard models (HM) for densities slightly away from half-filling through the behavior of two central quantities of a system: the uniform charge and spin…

Strongly Correlated Electrons · Physics 2009-11-11 Hermann Freire , Eberth Correa , Alvaro Ferraz

A method for finding reduced-order approximations of turbulent flow models is presented. The method preserves bounds on the production of turbulent energy in the sense of the $\curly{L}_2$ norm of perturbations from a notional laminar…

Fluid Dynamics · Physics 2013-01-22 A S Sharma

We introduce a diagrammatic multi-scale approach to the Hubbard model based on the interaction-irreducible (multi-boson) vertex of a small cluster embedded in a self-consistent medium. The vertex captures short-ranged correlations up to the…

Strongly Correlated Electrons · Physics 2024-06-25 Dominik Kiese , Nils Wentzell , Igor Krivenko , Olivier Parcollet , Karsten Held , Friedrich Krien

In this work, we analyze the Born, Bogoliubov, Green, Kirkwood and Yvon (BBGKY) hierarchy of equations for describing the full time-evolution of a many-body fermionic system in terms of its reduced density matrices (at all orders). We…

Materials Science · Physics 2012-06-26 Ali Akbari , Mohammad Javad Hashemi , Risto M. Nieminen , Robert van Leeuwen , Angel Rubio

In the search for accurate approximate solutions of the many-body Schr\"odinger equation, reduced density matrices play an important role, as they allow to formulate approximate methods with polynomial scaling in the number of particles.…

Quantum Physics · Physics 2024-12-19 Elias Pescoller , Marie Eder , Iva Březinová

Bilevel optimization has been recently revisited for designing and analyzing algorithms in hyperparameter tuning and meta learning tasks. However, due to its nested structure, evaluating exact gradients for high-dimensional problems is…

Machine Learning · Computer Science 2019-04-09 Amirreza Shaban , Ching-An Cheng , Nathan Hatch , Byron Boots

We analyze a variety of integration schemes for the momentum space functional renormalization group calculation with the goal of finding an optimized scheme. Using the square lattice $t-t'$ Hubbard model as a testbed we define and benchmark…

Strongly Correlated Electrons · Physics 2023-01-27 Jacob Beyer , Florian Goth , Tobias Müller

In this work, we introduce an original self-consistent scheme based on the one-body reduced density matrix ($\gamma$) formalism. A significant feature of this methodology is the utilization of an optimal unitary transformation of the…

Strongly Correlated Electrons · Physics 2023-11-10 Quentin Marécat , Benjamin Lasorne , Emmanuel Fromager , Matthieu Saubanère

The main goal of this paper is to reconsider a phenomenon which was treated in earlier work of the authors' on several truncated matricial moment problems. Using a special kind of Schur complement we obtain a more transparent insight into…

Classical Analysis and ODEs · Mathematics 2017-12-20 Bernd Fritzsche , Bernd Kirstein , Conrad Mädler

We consider the low-energy particle-particle scattering properties in a periodic simple cubic crystal. In particular, we investigate the relation between the two-body scattering length and the energy shift experienced by the lowest-lying…

Quantum Gases · Physics 2016-05-25 Manuel Valiente , Nikolaj Thomas Zinner

This paper introduces a novel ansatz-based technique for solution of the Hubbard model over two length scales. Short range correlations are treated exactly using a dynamical cluster approximation QMC simulation, while longer-length-scale…

Strongly Correlated Electrons · Physics 2009-11-10 J. P. Hague , Mark Jarrell , T. C. Schulthess

We consider a class of adaptive multilevel domain decomposition-like algorithms, built from a combination of adaptive multilevel finite element, domain decomposition, and partition of unity methods. These algorithms have several interesting…

Numerical Analysis · Mathematics 2010-01-12 Michael Holst

The development of numerical methods capable of simulating realistic materials with strongly correlated electrons, with controllable errors, is a central challenge in quantum many-body physics. Here we describe how a hybrid between…

Strongly Correlated Electrons · Physics 2015-04-23 Alexei A. Kananenka , Emanuel Gull , Dominika Zgid

Ground state properties of the Hubbard model on a two-dimensional square lattice are studied by the auxiliary-field quantum Monte Carlo method. Accurate results for energy, double occupancy, effective hopping, magnetization, and momentum…

Strongly Correlated Electrons · Physics 2016-08-10 Mingpu Qin , Hao Shi , Shiwei Zhang

In this thesis the variational optimisation of the density matrix is discussed as a method in many-body quantum mechanics. This is a relatively unknown technique in which one tries to obtain the two-particle reduced density matrix directly…

Quantum Physics · Physics 2012-03-27 Brecht Verstichel

We present an adaptive reduced-order model for the efficient time-resolved simulation of fluid-structure interaction problems with complex and non-linear deformations. The model is based on repeated linearizations of the structural balance…

Fluid Dynamics · Physics 2020-04-13 Ali Thari , Vito Pasquariello , Niels Aage , Stefan Hickel

The second-order reduced density matrix method (the RDM method) has performed well in determining energies and properties of atomic and molecular systems, achieving coupled-cluster singles and doubles with perturbative triples (CC SD(T))…

Strongly Correlated Electrons · Physics 2012-07-23 James S. M. Anderson , Maho Nakata , Ryo Igarashi , Katsuki Fujisawa , Makoto Yamashita

An adaptive finite element method is presented for the elastic scattering of a time-harmonic plane wave by a periodic surface. First, the unbounded physical domain is truncated into a bounded computational domain by introducing the…

Numerical Analysis · Mathematics 2016-05-30 Xue Jiang , Peijun Li , Junliang Lv , Weiying Zheng

Randomized matrix compression techniques, such as the Johnson-Lindenstrauss transform, have emerged as an effective and practical way for solving large-scale problems efficiently. With a focus on computational efficiency, however, forsaking…

Machine Learning · Statistics 2015-10-19 Stephen Becker , Ban Kawas , Marek Petrik , Karthikeyan N. Ramamurthy