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Related papers: Adaptive Basis Sets for Practical Quantum Computin…

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Quantum computational chemistry has emerged as an important application of quantum computing. Hybrid quantum-classical computing methods, such as variational quantum eigensolvers (VQE), have been designed as promising solutions to quantum…

Decoherence, resulting from unwanted interaction between a qubit and its environment, poses a serious challenge towards the development of quantum technologies. Recently, researchers have started analysing how real-time Hamiltonian learning…

Quantum Physics · Physics 2020-06-24 Eleanor Scerri , Erik M. Gauger , Cristian Bonato

We present a quantum-classical hybrid algorithm for calculating the ground state and its energy of the quantum many-body Hamiltonian by proposing an adaptive construction of a quantum state for the quantum-selected configuration interaction…

Quantum Physics · Physics 2024-12-12 Yuya O. Nakagawa , Masahiko Kamoshita , Wataru Mizukami , Shotaro Sudo , Yu-ya Ohnishi

Hybrid quantum-classical algorithms have begun to leverage quantum devices to efficiently represent many-electron wavefunctions, enabling early demonstrations of molecular simulations on real hardware. A key prerequisite for scalable…

Quantum Physics · Physics 2026-04-28 Noah Garrett , Michael Rose , David A. Mazziotti

Approximating the ground states of strongly interacting electron systems in quantum chemistry and condensed matter physics is expected to be one of the earliest applications of quantum computers. In this paper, we prepare highly accurate…

Quantum Physics · Physics 2022-11-09 Gaurav Gyawali , Michael J. Lawler

The exact solution of the Schrodinger equation for atoms, molecules and extended systems continues to be a "Holy Grail" problem for the field of atomic and molecular physics since inception. Recently, breakthroughs have been made in the…

Quantum Physics · Physics 2017-06-02 Rongxin Xia , Teng Bian , Sabre Kais

We present high-precision quantum computing simulations of three-body atoms (He, H$^-$) and molecules (H$_2^+$, HD$^+$), the latter being studied beyond the Born-Oppenheimer approximation. The Non-Iterative Disentangled Unitary Coupled…

Quantum Physics · Physics 2025-10-22 Mohammad Haidar , Hugo D. Nogueira , J. -Ph. Karr

A simple yet general method for constructing basis sets for molecular electronic structure calculations is presented. These basis sets consist of atomic natural orbitals from a multi-configurational self-consistent field calculation…

Materials Science · Physics 2015-05-19 F. R. Petruzielo , Julien Toulouse , C. J. Umrigar

The rapidly growing interest in simulating condensed-phase materials using quantum chemistry methods calls for a library of high-quality Gaussian basis sets suitable for periodic calculations. Unfortunately, most standard Gaussian basis…

Chemical Physics · Physics 2022-06-07 Hong-Zhou Ye , Timothy C. Berkelbach

A major obstacle towards realizing a practical quantum computer is the noise that arises due to system-environment interactions. While it is very well known that quantum error correction (QEC) provides a way to protect against errors that…

Quantum Physics · Physics 2023-02-24 Akshaya Jayashankar

Owing to the computational complexity of electronic structure algorithms running on classical digital computers, the range of molecular systems amenable to simulation remains tightly circumscribed even after many decades of work. Quantum…

Quantum Physics · Physics 2022-05-18 Alexis Ralli , Michael I. Williams , Peter V. Coveney

Determining the exponentially scaled ground state wavefunction and the associated molecular properties remains one of the central challenges in quantum chemistry. Hybrid quantum-classical algorithms implemented on quantum computers offer a…

Quantum Physics · Physics 2026-04-22 Dibyendu Mondal , Ashish Kumar Patra , Rahul Maitra

Quantum phase estimation (QPE) is a promising quantum algorithm for obtaining molecular ground-state energies with chemical accuracy. However, its computational cost, dominated by the Hamiltonian 1-norm $\lambda$ and the cost of the block…

We show how to adapt the quasi-Newton method to the electronic-structure calculations using systematic basis sets. Our implementation requires less iterations than the conjugate gradient method, while the computational cost per iteration is…

Materials Science · Physics 2009-11-07 Eiji Tsuchida

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…

Quantum machine learning algorithms, the extensions of machine learning to quantum regimes, are believed to be more powerful as they leverage the power of quantum properties. Quantum machine learning methods have been employed to solve…

Computational Physics · Physics 2021-06-01 Shree Hari Sureshbabu , Manas Sajjan , Sangchul Oh , Sabre Kais

Electronic structure simulation is an anticipated application for quantum computers. Due to high-dimensional quantum entanglement in strongly correlated systems, the quantum resources required to perform such simulations are far beyond the…

Quantum Physics · Physics 2022-01-25 Jie Liu , Zhenyu Li , Jinlong Yang

In the noisy intermediate-scale quantum era, ab initio computation of the electronic structure problems has become one of the major benchmarks for identifying the boundary between classical and quantum computational power. Basis sets play a…

Quantum Physics · Physics 2024-11-06 Weishi Wang , James D. Whitfield

Whether it is at the fabrication stage or during the course of the quantum computation, e.g. because of high-energy events like cosmic rays, the qubits constituting an error correcting code may be rendered inoperable. Such defects may…

Quantum Physics · Physics 2023-07-26 Adam Siegel , Armands Strikis , Thomas Flatters , Simon Benjamin

Quantum hardware suffers from intrinsic device heterogeneity and environmental drift, forcing practitioners to choose between suboptimal non-adaptive controllers or costly per-device recalibration. We derive a scaling law lower bound for…

Machine Learning · Computer Science 2026-05-21 Nima Leclerc , Chris Miller , Nicholas Brawand