Prospects of Quantum Computing for Molecular Sciences

2021/02/28 by Hongbin Liu, Guang Hao Low, Damian S. Steiger +3 · 1 citation
Computer Science · Mathematics · Physics and Astronomy · #Computer science #Field (mathematics) #Materials science #Mathematics #Nanotechnology #Physics #Pure mathematics #Quantum #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Mechanics and Applications #Quantum computer #Quantum mechanics #Qubit #Representation (politics) #Statistical physics #Theoretical physics #quant-ph

paper · pdf · doi:10.1186/s41313-021-00039-z

published as Materials Theory 6, article number: 11 (2022)

arxiv created 2021/05/17 · openalex publication_date 2022/03/07 · arxiv updated 2022/03/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

Molecular science is governed by the dynamics of electrons, atomic nuclei, and their interaction with electromagnetic fields. A reliable physicochemical understanding of these processes is crucial for the design and synthesis of chemicals and materials of economic value. Although some problems in this field are adequately addressed by classical mechanics, many require an explicit quantum mechanical description. Such quantum problems represented by exponentially large wave function should naturally benefit from quantum computation on a number of logical qubits that scales only linearly with system size. In this perspective, we focus on the potential of quantum computing for solving relevant problems in the molecular sciences -- molecular physics, chemistry, biochemistry, and materials science.

Citations

• Ab initio quantum chemistry using the density matrix renormalization group
• Nonphysical sampling distributions in Monte Carlo free-energy estimation: Umbrella sampling
• Density Functional Theory of Electronic Structure
• Exponential algorithmic speedup by a quantum walk
• Ab Initio Multiple Spawning: Photochemistry from First Principles Quantum Molecular Dynamics
• Configuration interaction calculations on the nitrogen molecule
• Simulated Quantum Computation of Molecular Energies
• Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer
• Quantum algorithms: an overview
• Self-Consistent Equations Including Exchange and Correlation Effects
• Solving the Quantum Many-Body Problem with Artificial Neural Networks
• Quantum Machine Learning
• Quantum Computing in the NISQ era and beyond
• Quantum Computation and Quantum Information
• Quantum computational advantage using photons
• Demonstration of the trapped-ion quantum CCD computer architecture
• Optimizing Electronic Structure Simulations on a Trapped-ion Quantum Computer using Problem Decomposition
• Noisy intermediate-scale quantum (NISQ) algorithms

Cited by

• Preconditioning Natural and Second Order Gradient Descent in Quantum Optimization: A Performance Benchmark