Alan Bidart | Searcharxiv

arXiv2026

The cost of quantum algorithms for biochemistry: A case study in metaphosphate hydrolysis

We evaluate the quantum resource requirements for ATP/metaphosphate hydrolysis, one of the most important reactions in all of biology with implications for metabolism, cellular signaling, and cancer therapeutics. In particular, we consider three algorithms for solving the ground state energy estimation problem: the variational quantum eigensolver, quantum Krylov, and quantum phase estimation. By utilizing exact classical simulation, numerical estimation, and analytical bounds, we provide a current and future outlook for using quantum computers to solve impactful biochemical and biological problems. Our results show that variational methods, while being the most heuristic, still require substantially fewer overall resources on quantum hardware, and could feasibly address such problems on current or near-future devices. We include our complete dataset of biomolecular Hamiltonians and code as benchmarks to improve upon with future techniques.

quant-ph↗

arXiv2025

Quantum Computing Beyond Ground State Electronic Structure: A Review of Progress Toward Quantum Chemistry Out of the Ground State

Quantum computing offers the promise of revolutionizing quantum chemistry by enabling the solution of chemical problems for substantially less computational cost. While most demonstrations of quantum computation to date have focused on resolving the energies of the electronic ground states of small molecules, the field of quantum chemistry is far broader than ground state chemistry; equally important to practicing chemists are chemical reaction dynamics and reaction mechanism prediction. Here, we review progress toward and the potential of quantum computation for understanding quantum chemistry beyond the ground state, including for reaction mechanisms, reaction dynamics, and finite temperature quantum chemistry. We discuss algorithmic and other considerations these applications share, as well as differences that make them unique. We also highlight the potential speedups these applications may realize and challenges they may face. We hope that this discussion stimulates further research into how quantum computation may better inform experimental chemistry in the future.

physics.chem-ph↗