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We present an efficient algorithm for calculating spectral properties of large sparse Hamiltonian matrices such as densities of states and spectral functions. The combination of Chebyshev recursion and maximum entropy achieves high energy…

Condensed Matter · Physics 2009-10-30 R. N. Silver , H. Roder

Efficient and stable algorithms for the calculation of spectral quantities and correlation functions are some of the key tools in computational condensed matter physics. In this article we review basic properties and recent developments of…

Other Condensed Matter · Physics 2007-05-23 Alexander Weisse , Gerhard Wellein , Andreas Alvermann , Holger Fehske

We present a spectral scheme for atomic structure calculations in pseudopotential Kohn-Sham density functional theory. In particular, after applying an exponential transformation of the radial coordinates, we employ global polynomial…

Computational Physics · Physics 2024-06-07 Sayan Bhowmik , John E. Pask , Andrew J. Medford , Phanish Suryanarayana

Quantum simulators, in which well controlled quantum systems are used to reproduce the dynamics of less understood ones, have the potential to explore physics that is inaccessible to modeling with classical computers. However, checking the…

Quantum Physics · Physics 2015-06-18 C. Senko , J. Smith , P. Richerme , A. Lee , W. C. Campbell , C. Monroe

We introduce a numerical method for computing spectral densities, and apply it to the evaluation of the local density of states (LDOS) of sparse Hamiltonians derived from tight-binding models. The approach, which we call the high-order…

Computational Physics · Physics 2025-12-04 Jinjing Yi , Daniel Massatt , Andrew Horning , Mitchell Luskin , J. H. Pixley , Jason Kaye

Quantum computing shows promise for addressing computationally intensive problems but is constrained by the exponential resource requirements of general quantum state tomography (QST), which fully characterizes quantum states through…

Quantum Physics · Physics 2025-09-12 Hao Su , Shiying Xiong , Yue Yang

We compute spectral function for $^4$He by combining coupled-cluster theory with an expansion of integral transforms into Chebyshev polynomials. Our method allows to estimate the uncertainty of spectral reconstruction. The properties of the…

Nuclear Theory · Physics 2024-02-16 J. E. Sobczyk , S. Bacca , G. Hagen , T. Papenbrock

We describe a novel end-to-end approach using Machine Learning to reconstruct the power spectrum of cosmological density perturbations at high redshift from observed quasar spectra. State-of-the-art cosmological simulations of structure…

Cosmology and Nongalactic Astrophysics · Physics 2021-07-21 Maria Han Veiga , Xi Meng , Oleg Y. Gnedin , Nickolay Y. Gnedin , Xun Huan

Response functions are a key quantity to describe the near-equilibrium dynamics of strongly-interacting many-body systems. Recent techniques that attempt to overcome the challenges of calculating these \emph{ab initio} have employed…

Quantum Physics · Physics 2025-01-22 Doga Murat Kurkcuoglu , Alessandro Roggero , Gabriel N. Perdue , Rajan Gupta

We propose an inverse-design approach for computational spectrometers in which the scattering media are topology-optimized to achieve better performance in inference of unknown spectra. Unlike traditional end-to-end approaches, our inverse…

Optics · Physics 2026-03-31 Wenchao Ma , Raphaël Pestourie , Zin Lin , Steven G. Johnson

Determining the properties of molecules and materials is one of the premier applications of quantum computing. A major question in the field is: how might we use imperfect near-term quantum computers to solve problems of practical value? We…

Quantum Physics · Physics 2023-08-29 Phillip W. K. Jensen , Peter D. Johnson , Alexander A. Kunitsa

We present a numerical method for calculating piecewise smooth spectral functions of correlated quantum systems in the thermodynamic limit from the spectra of finite systems computed using the dynamical or correction-vector density-matrix…

Strongly Correlated Electrons · Physics 2014-05-05 Martin Paech , Eric Jeckelmann

An inverse problem in spectroscopy is considered. The objective is to restore the discrete spectrum from observed spectrum data, taking into account the spectrometer's line spread function. The problem is reduced to solution of a system of…

Numerical Analysis · Mathematics 2017-01-23 Valery Sizikov , Denis Sidorov

Spectroscopy is an indispensable tool in understanding the structures and dynamics of molecular systems. However computational modelling of spectroscopy is challenging due to the exponential scaling of computational complexity with system…

Quantum Physics · Physics 2021-06-22 Chee-Kong Lee , Chang-Yu Hsieh , Shengyu Zhang , Liang Shi

Quantum computers hold promise to enable efficient simulations of the properties of molecules and materials; however, at present they only permit ab initio calculations of a few atoms, due to a limited number of qubits. In order to harness…

Materials Science · Physics 2020-07-07 He Ma , Marco Govoni , Giulia Galli

We develop a spectrally accurate numerical method to compute solutions of a model partial differential equation used in plasma physics to describe diffusion in velocity space due to Fokker-Planck collisions. The solution is represented as a…

Classical Analysis and ODEs · Mathematics 2015-03-18 Jon Wilkening , Antoine Cerfon

Accessing both amplitude and phase of nuclear response functions is central to fully characterizing light-matter interactions in the X-ray-nuclear regime. Recent work has demonstrated phase retrieval in two-dimensional time- and…

Traditionally, finite differences and finite element methods have been by many regarded as the basic tools for obtaining numerical solutions in a variety of quantum mechanical problems emerging in atomic, nuclear and particle physics,…

Quantum Physics · Physics 2008-11-26 A. Deloff

Reconstruction of density matrices is important in NMR quantum computing. An analysis is made for a 2-qubit system by using the error matrix method. It is found that the state tomography method determines well the parameters that are…

Quantum Physics · Physics 2009-11-06 G. L. Long , H. Y. Yan , Yang Sun

Classical approximation bases such as Chebyshev polynomials provide principled and interpretable representations, but their multivariate tensor-product constructions scale exponentially with dimension and impose axis-aligned structure that…

Machine Learning · Computer Science 2026-04-07 Milo Coombs
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