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Density estimation is a fundamental task in statistics and machine learning applications. Kernel density estimation is a powerful tool for non-parametric density estimation in low dimensions; however, its performance is poor in higher…

Machine Learning · Computer Science 2022-08-08 Joseph A. Gallego , Fabio A. González

We present a simple, perturbative approach for calculating spectral densities for random matrix ensembles in the thermodynamic limit we call the Perturbative Resolvent Method (PRM). The PRM is based on constructing a linear system of…

Disordered Systems and Neural Networks · Physics 2020-12-02 Wenping Cui , Jason W. Rocks , Pankaj Mehta

In recent years, machine learning potentials (MLP) for atomistic simulations have attracted a lot of attention in chemistry and materials science. Many new approaches have been developed with the primary aim to transfer the accuracy of…

Background: The quasiparticle random phase approximation (QRPA), within the framework of the nuclear density functional theory (DFT), has been a standard tool to access the collective excitations of the atomic nuclei. Recently, finite…

Nuclear Theory · Physics 2016-03-30 Tomohiro Oishi , Markus Kortelainen , Nobuo Hinohara

Starting from an independent-particle model with a finite and arbitrary set of single-particle energies, we develop an analytical approximation to the many-body level density $\rho_A(E)$ and to particle-hole densities. We use exact…

Nuclear Theory · Physics 2013-09-30 Adriana Pálffy , Hans A. Weidenmüller

We present a calculation of the properties of vibrational states in deformed, axially--symmetric even--even nuclei, within the framework of a fully self--consistent Quasparticle Random Phase Approximation (QRPA). The same Skyrme energy…

Nuclear Theory · Physics 2011-02-28 C. Losa , A. Pastore , T. Dossing , E. Vigezzi , R. A. Broglia

We generalize the Approximate Quantum Compiling algorithm into a new method for CNOT-depth reduction, which is apt to process wide target quantum circuits. Combining this method with state-of-the-art techniques for error mitigation and…

Density level sets can be estimated using plug-in methods, excess mass algorithms or a hybrid of the two previous methodologies. The plug-in algorithms are based on replacing the unknown density by some nonparametric estimator, usually the…

Statistics Theory · Mathematics 2016-11-26 A. Rodríguez-Casal , P. Saavedra-Nieves

This paper presents a general method for producing randomly perturbed density operators subject to different sets of constraints. The perturbed density operators are a specified "distance" away from the state described by the original…

Quantum Physics · Physics 2024-06-10 J. A. Montanez-Barrera , R. T. Holladay , G. P. Beretta , Michael R. von Spakovsky

We present the finite amplitude method (FAM) for superfluid systems. A Hartree-Fock-Bogoliubov code may be transformed into a code of the quasi-particle-random-phase approximation (QRPA) with simple modifications. This technique has…

Nuclear Theory · Physics 2011-08-08 Paolo Avogadro , Takashi Nakatsukasa

The estimation of the density matrix of a $k$-level quantum system is studied when the parametrization is given by the real and imaginary part of the entries and they are estimated by independent measurements. It is established that the…

Quantum Physics · Physics 2009-11-13 D. Petz , K. M. Hangos , A. Magyar

The level density is among the most important statistical nuclear properties. It appears in Fermi's golden rule for transition rates and is an important input to the Hauser-Feshbach theory of compound nucleus reactions. We discuss empirical…

Nuclear Theory · Physics 2022-01-05 Y. Alhassid

This paper presents a strategy for efficient quantum circuit design for density estimation. The strategy is based on a quantum-inspired algorithm for density estimation and a circuit optimisation routine based on memetic algorithms. The…

We proposed a novel dense line spectrum super-resolution algorithm, the DMRA, that leverages dynamical multi-resolution of atoms technique to address the limitation of traditional compressed sensing methods when handling dense point-source…

Signal Processing · Electrical Eng. & Systems 2024-09-04 Mingguang Han , Yi Zeng , Xiaoguang Li , Tiejun Li

We introduce a novel hybrid quantum-classical algorithm for the near-term computation of expectation values in quantum systems at finite temperatures. This is based on two stages: on the first one, a mixed state approximating a fiducial…

Quantum Physics · Physics 2024-01-31 Giuseppe Clemente

We describe and apply a version of the finite amplitude method for obtaining the charge-changing nuclear response in the quasiparticle random phase approximation. The method is suitable for calculating strength functions and beta-decay…

Nuclear Theory · Physics 2015-06-19 M. T. Mustonen , T. Shafer , Z. Zenginerler , J. Engel

We present a quantum algorithm to obtain the response of the atomic nucleus to a small external electromagnetic perturbation. The Hamiltonian of the system is presented by a harmonic oscillator, and the linear combination of unitaries (LCU)…

Quantum Physics · Physics 2022-10-18 Abhishek , Nifeeya Singh , Pooja Siwach , P. Arumugam

Impressive progress has been made in the past decade in the study of technological applications of varied types of quantum systems. With industry giants like IBM laying down their roadmap for scalable quantum devices with more than…

Quantum Physics · Physics 2021-09-15 Rishabh Gupta , Sabre Kais , Raphael D. Levine

Determining the vibrational structure of a molecule is central to fundamental applications in several areas, from atmospheric science to catalysis, fuel combustion modeling, biochemical imaging, and astrochemistry. However, when significant…

Quantum Physics · Physics 2021-12-22 Nicolas P. D. Sawaya , Francesco Paesani , Daniel P. Tabor

We propose a practical method to solve the random-phase approximation (RPA) in the self-consistent Hartree-Fock (HF) and density-functional theory. The method is based on numerical evaluation of the residual interactions utilizing finite…

Nuclear Theory · Physics 2010-11-26 Takashi Nakatsukasa , Tsunenori Inakura , Kazuhiro Yabana