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Fitting geometric models onto outlier contaminated data is provably intractable. Many computer vision systems rely on random sampling heuristics to solve robust fitting, which do not provide optimality guarantees and error bounds. It is…

Computer Vision and Pattern Recognition · Computer Science 2022-06-28 Anh-Dzung Doan , Michele Sasdelli , David Suter , Tat-Jun Chin

In quantum/classical (QM/CM) partitioning methods for multi-scale modeling, one is often forced to introduce uncontrolled phenomenological effects of the environment (CM) in the quantum (QM) domain as ab initio quantum calculations are…

Chemical Physics · Physics 2007-05-23 Aditi Mallik , Carlos E. Taylor , Keith Runge , James W. Dufty

The use of geometric and symmetry techniques in quantum and classical information processing has a long tradition across the physical sciences as a means of theoretical discovery and applied problem solving. In the modern era, the emergent…

Quantum Physics · Physics 2024-09-10 Elija Perrier

Quantum algorithms are of great interest for their possible use in optimization problems. In particular, variational algorithms that use classical counterparts to optimize parameters hold promise for use in currently existing devices.…

Quantum Physics · Physics 2026-05-13 Bruno Oziel Fernandez , Rodrigo Bloot , Marcelo Moret

We propose a new non-perturbative method for studying UV complete unitary quantum field theories (QFTs) with a mass gap in general number of spacetime dimensions. The method relies on unitarity formulated as positive semi-definiteness of…

High Energy Physics - Theory · Physics 2021-07-21 Denis Karateev , Simon Kuhn , Joao Penedones

We have developed a multi-orbital approach to compute the electronic structure of a quantum impurity using the non-crossing approximation. The calculation starts with a mean-field evaluation of the system's electronic structure using a…

Mesoscale and Nanoscale Physics · Physics 2015-05-27 Richard Korytár , Nicolás Lorente

We present a critical analysis of the popular fragment-orbital density-functional theory (FO-DFT) scheme for the calculation of electronic coupling values. We discuss the characteristics of different possible formulations or 'flavors' of…

Materials Science · Physics 2016-02-17 Christoph Schober , Karsten Reuter , Harald Oberhofer

We introduce the concept of embedding quantum simulators, a paradigm allowing the efficient quantum computation of a class of bipartite and multipartite entanglement monotones. It consists in the suitable encoding of a simulated quantum…

Quantum Physics · Physics 2015-06-16 R. Di Candia , B. Mejia , H. Castillo , J. S. Pedernales , J. Casanova , E. Solano

Quantum embedding theories are powerful tools for approximately solving large-scale strongly correlated quantum many-body problems. The main idea of quantum embedding is to glue together a highly accurate quantum theory at the local scale…

Computational Physics · Physics 2020-01-23 Lin Lin , Michael Lindsey

Recent improvements in control of quantum systems make it seem feasible to finally build a quantum computer within a decade. While it has been shown that such a quantum computer can in principle solve certain small electronic structure…

Quantum Physics · Physics 2016-09-27 Bela Bauer , Dave Wecker , Andrew J. Millis , Matthew B. Hastings , M. Troyer

We develop a systematic classical framework to accommodate canonical quantization of geometric and matter perturbations on a quantum homogeneous isotropic flat spacetime. The existing approach of standard cosmological perturbations is…

General Relativity and Quantum Cosmology · Physics 2013-06-05 Andrea Dapor , Jerzy Lewandowski , Jacek Puchta

Quantum computers can be used to address molecular structure, materials science and condensed matter physics problems, which currently stretch the limits of existing high-performance computing resources. Finding exact numerical solutions to…

Machine learning opens new avenues for modelling correlated materials. Quantum embedding approaches, such as the dynamical mean-field theory (DMFT), provide corrections to first-principles calculations for strongly correlated materials,…

Computational Physics · Physics 2021-12-01 Evan Sheridan , Christopher Rhodes , Francois Jamet , Ivan Rungger , Cedric Weber

One of the goals in the development of large scale electronic structure methods is to perform calculations explicitly for a localised region of a system, while still taking into account the rest of the system outside of this region. An…

Materials Science · Physics 2009-10-01 J. R. Trail , D. M. Bird

The task of estimating the ground state of Hamiltonians is an important problem in physics with numerous applications ranging from solid-state physics to combinatorial optimization. We provide a hybrid quantum-classical algorithm for…

Quantum Physics · Physics 2022-02-28 Kishor Bharti , Tobias Haug

The idea of using fragment embedding to circumvent the high computational scaling of accurate electronic structure methods while retaining high accuracy has been a long-standing goal for quantum chemists. Traditional fragment embedding…

Chemical Physics · Physics 2022-10-11 Hong-Zhou Ye , Matthew Welborn , Nathan D. Ricke , Troy Van Voorhis

Quantum harmonic oscillators, or qumodes, provide a promising and versatile framework for quantum computing. Unlike qubits, which are limited to two discrete levels, qumodes have an infinite-dimensional Hilbert space, making them…

We present a mixed basis-set approach to obtain optical absorption spectra within a generalized Kohn-Sham time-dependent density functional theory framework. All occupied valence molecular orbitals (MOs) are expanded in a plane-wave (PW)…

Chemical Physics · Physics 2025-08-13 Kyle Chen , Barry Y. Li , Tucker Allen , Daniel Neuhauser

In the framework of quantum thermodynamics, we propose a method to quantitatively describe thermodynamic quantities for out-of-equilibrium interacting many-body systems. The method is articulated in various approximation protocols which…

Quantum Physics · Physics 2018-02-22 Marcela Herrera , Roberto M. Serra , Irene D'Amico

This work develops a symplectic framework for quantum computing to be applied to classical Hamiltonian systems, exploiting the intrinsic geometric compatibility between unitary quantum evolution and symplectic phase-space dynamics in a…