Characterizing conical intersections of nucleobases on quantum computers

TL;DR

This paper demonstrates the first quantum simulation of conical intersections in a biomolecule using a superconducting quantum computer, advancing understanding of photostability in DNA and RNA.

Contribution

It introduces the application of the Contracted Quantum Eigensolver to simulate conical intersections in cytosine, showing promising results on noisy quantum hardware.

Findings

CQE and VQD methods accurately approximate CIs compared to exact solutions.

Quantum simulations on noisy hardware show potential for studying biological photochemical processes.

First quantum simulation of conical intersections in a biomolecule.

Abstract

Hybrid quantum-classical computing algorithms offer significant potential for accelerating the calculation of the electronic structure of strongly correlated molecules. In this work, we present the first quantum simulation of conical intersections (CIs) in a biomolecule, cytosine, using a superconducting quantum computer. We apply the Contracted Quantum Eigensolver (CQE) -- with comparisons to conventional Variational Quantum Deflation (VQD) -- to compute the near-degenerate ground and excited states associated with the conical intersection, a key feature governing the photostability of DNA and RNA. The CQE is based on an exact ansatz for many-electron molecules in the absence of noise -- a critically important property for resolving strongly correlated states at CIs. Both methods demonstrate promising accuracy when compared with exact diagonalization, even on noisy intermediate-scale quantum computers, highlighting their potential for advancing the understanding of photochemical and photobiological processes. The ability to simulate these intersections is critical for advancing our knowledge of biological processes like DNA repair and mutation, with potential implications for molecular biology and medical research.