High-Quality Protein Force Fields with Noisy Quantum Processors
arXiv:1907.07128
Abstract
A central problem in biophysics and computational drug design is accurate modeling of biomolecules. The current molecular dynamics simulation methods can answer how a molecule inhibits a cancerous cell signaling pathway, or the role of protein misfolding in neurodegenerative diseases. However, the accuracy of current force fields (interaction potential) limits the reliability of computer simulations. Fundamentally a quantum chemistry problem, here we discuss optimizing force fields using scalable ab initio quantum chemistry calculations on quantum computers and estimate the quantum resources required for this task. For a list of dipeptides for local parameterizations, we estimate the required number of qubits to be 1576 to 3808 with cc-pVTZ(-f) orbital basis and 88 to 276 with active space reduction. Using a linear depth ansatz with active-space reduction, we estimate a quantum circuit with a circuit depth of few thousands can be used to simulate these dipeptides. The estimated number of 100s of qubits and a few thousand long circuit depth puts the pharmaceutical application of near-term quantum processors in a realistic perspective.
8 pages of main text, 5 page appendix. Added circuit depth and gate count discussion, reduced Appendix size
References in corpus (10)
- Quantum Computing in the NISQ era and beyond
- Supplementary information for "Quantum supremacy using a programmable superconducting processor"
- ANI-1: An extensible neural network potential with DFT accuracy at force field computational cost
- Generalized Unitary Coupled Cluster Wavefunctions for Quantum Computation
- Quantum Simulation of Electronic Structure with Linear Depth and Connectivity
- Cloud Quantum Computing of an Atomic Nucleus
- Quantum Error Correction
- Tapering off qubits to simulate fermionic Hamiltonians
- Increasing the representation accuracy of quantum simulations of chemistry without extra quantum resources
- Accuracy and Resource Estimations for Quantum Chemistry on a Near-term Quantum Computer