Drug design on quantum computers

Abstract

Quantum computers promise to impact industrial applications, for which quantum chemical calculations are required, by virtue of their high accuracy. This perspective explores the challenges and opportunities of applying quantum computers to drug design, discusses where they could transform industrial research and elaborates on what is needed to reach this goal.

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• High ground state overlap via quantum embedding methods
• Quantum-machine-assisted Drug Discovery
• Calculating the energy profile of an enzymatic reaction on a quantum computer
• Quantum Dynamics Simulation of the Advection-Diffusion Equation
• On the Impact of Classical and Quantum Communication Networks Upon Modular Quantum Computing Architecture System Performance
• Extending Quantum Computing through Subspace, Embedding and Classical Molecular Dynamics Techniques
• Efficient Learning of Long-Range and Equivariant Quantum Systems
• Optimal Particle-Conserved Linear Encoding for Practical Fermionic Simulation
• A recipe for local simulation of strongly-correlated fermionic matter on quantum computers: the 2D Fermi-Hubbard model
• Hyperfine Coupling Constants on Quantum Computers: Performance, Errors, and Future Prospects
• Compilation Techniques for Spin Qubits in a Shuttling Bus Architecture
• Topology-Aware Block Coordinate Descent for Qubit Frequency Allocation of Superconducting Quantum Processors
• Data Efficient Prediction of excited-state properties using Quantum Neural Networks
• Performance evaluation of variational quantum eigensolver and quantum dynamics algorithms on the advection-diffusion equation
• Matrix Product State on a Quantum Computer
• Qubit frugal entanglement determination with the deep multi-scale entanglement renormalization ansatz
• Energy Spectra of Compressed Quantum States