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Machine learning models for the potential energy of multi-atomic systems, such as the deep potential (DP) model, make possible molecular simulations with the accuracy of quantum mechanical density functional theory, at a cost only…

We present a real-space method for computing the random phase approximation (RPA) correlation energy within Kohn-Sham density functional theory, leveraging the low-rank nature of the frequency-dependent density response operator. In…

Computational Physics · Physics 2025-04-03 Boqin Zhang , Shikhar Shah , John E. Pask , Edmond Chow , Phanish Suryanarayana

Simulating liquid water to an accuracy that matches its wealth of available experimental data requires both precise electronic structure methods and reliable sampling of nuclear (quantum) motion. This is challenging because applying the…

Error mitigation is essential for the practical implementation of quantum algorithms on noisy intermediate-scale quantum (NISQ) devices. This work explores and extends Clifford Data Regression (CDR) to mitigate noise in quantum chemistry…

Tensor-network methods enable probing dynamics of strongly interacting quantum many-body systems, including gauge theories, via Hamiltonian simulation, hence bypassing sign problems. They also have the potential to inform efficient…

High Energy Physics - Lattice · Physics 2025-02-18 Emil Mathew , Navya Gupta , Saurabh V. Kadam , Aniruddha Bapat , Jesse Stryker , Zohreh Davoudi , Indrakshi Raychowdhury

We address the task of estimating the ground-state energy of Hamiltonians coming from chemistry. We study numerically the behavior of a digital-analog variational quantum eigensolver for the H2, LiH and BeH2 molecules, and we observe that…

Quantum Physics · Physics 2023-04-25 Antoine Michel , Sebastian Grijalva , Loïc Henriet , Christophe Domain , Antoine Browaeys

Modeling chemical reactions and complicated molecular systems has been proposed as the `killer application' of a future quantum computer. Accurate calculations of derivatives of molecular eigenenergies are essential towards this end,…

Highly accurate methods such as coupled cluster (CC) techniques can be used for periodic systems within the framework of the method of increments. Its extension to low-dimensional conducting system is considered. To demonstrate the…

Materials Science · Physics 2012-01-31 Elena Voloshina

Computer-aided engineering techniques are indispensable in modern engineering developments. In particular, partial differential equations are commonly used to simulate the dynamics of physical phenomena, but very large systems are often…

Quantum Physics · Physics 2022-04-26 Yuki Sato , Ruho Kondo , Satoshi Koide , Hideki Takamatsu , Nobuyuki Imoto

We introduce a theoretical approach to study the quantum-dissipative dynamics of electronic excitations in macromolecules, which enables to perform calculations in large systems and cover long time intervals. All the parameters of the…

Mesoscale and Nanoscale Physics · Physics 2016-07-20 S. A Beccara , F. Mascherpa , E. Schneider , P. Faccioli

We calculate rovibrational energy levels of H$_2$O using a trapped-ion quantum computer. We first derive the qubit form of Watson's Hamiltonian, including the rovibrational coupling terms. In a second step, we employ a variant of the…

Quantum Physics · Physics 2026-03-09 Erik Lötstedt , Tamás Szidarovszky

Dyson--Schwinger equations are an established, powerful non-perturbative tool for QCD. In the Hamiltonian formulation of a quantum field theory they can be used to perform variational calculations with non-Gaussian wave functionals. By…

High Energy Physics - Theory · Physics 2017-04-05 Davide R. Campagnari , Hugo Reinhardt , Markus Q. Huber , Peter Vastag , Ehsan Ebadati

Quantum chemistry simulations of some industrially relevant molecules are reported, employing variational quantum algorithms for near-term quantum devices. The energies and dipole moments are calculated along the dissociation curves for…

Coupled cluster methods based exclusively on double excitations are comparatively "cheap" and interesting model chemistries, as they are typically able to capture the bulk of the dynamical electron correlation effects. The trade-off in such…

Quantum Physics · Physics 2024-06-14 Zachary W. Windom , Daniel Claudino , Rodney J. Bartlett

In this work, we study the pairing Hamiltonian with four particles at finite temperatures on a quantum simulator and a superconducting quantum computer. The excited states are obtained by the variational quantum deflation (VQD). The…

Nuclear Theory · Physics 2023-04-26 Chongji Jiang , Junchen Pei

While quantum computing algorithms have been widely applied for electronic structure calculations, applications to molecular dynamics remain scarce. Complex and varied landscapes of molecular potential energy surfaces give rise to…

Quantum Physics · Physics 2026-04-02 K. Asnaashari , D. Bondarenko , R. V. Krems

While the treatment of chemically relevant systems containing hundreds or even thousands of electrons remains beyond the reach of quantum devices, the development of quantum-classical hybrid algorithms to resolve electronic correlation…

We show that from the point of view of the generalized pairing Hamiltonian, the atomic nucleus is a system with small entanglement and can thus be described efficiently using a 1D tensor network (matrix-product state) despite the presence…

Nuclear Theory · Physics 2024-03-07 Roman Rausch , Cassian Plorin , Matthias Peschke , Christoph Karrasch

We devise and examine two procrustean entanglement concentration schemes using Quantum Non- Demolition (QND) interaction Hamiltonians in the continuous variable regime, applicable for light, for atomic ensembles or in a hybrid setting. We…

Quantum Physics · Physics 2011-11-22 Richard Tatham , Natalia Korolkova

Many-body techniques based on the double unitary coupled cluster ansatz (DUCC) can be used to downfold electronic Hamiltonians into low-dimensional active spaces. It can be shown that the resulting dimensionality reduced Hamiltonians are…

Quantum Physics · Physics 2020-01-29 Nicholas P. Bauman , Guang Hao Low , Karol Kowalski