Quantum-Centric Alchemical Free Energy Calculations

• URL: http://arxiv.org/abs/2506.20825v1
• Date: Wed, 25 Jun 2025 20:50:40 GMT
• Title: Quantum-Centric Alchemical Free Energy Calculations
• Authors: Milana Bazayeva, Zhen Li, Danil Kaliakin, Fangchun Liang, Akhil Shajan, Susanta Das, Kenneth M. Merz Jr,
• Abstract summary: This work aims at improving the accuracy of alchemical free energy (AFE) predictions by incorporating configuration interaction (CI) simulations using the book-ending correction method.<n>We introduce a novel interface to QUICK, via sander, that enables CI simulations, and can operate in two ways: A) via PySCF backend to perform full configuration interaction (FCI) using conventional computing resources, B) quantum-centric sample-based quantum diagonalization (SQD) workflow via Qiskit.
• Score: 1.6741394365746018
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In the present work, we present a hybrid quantum-classical workflow aimed at improving the accuracy of alchemical free energy (AFE) predictions by incorporating configuration interaction (CI) simulations using the book-ending correction method. This approach applies the Multistate Bennett Acceptance Ratio (MBAR) over a coupling parameter {\lambda} to smoothly transition the system from molecular mechanics (MM) ({\lambda} = 0) to a quantum mechanics (QM) ({\lambda} = 1) description. The resulting correction is then applied to the classically (MM) computed AFE to account for the more accurate QM treatment. The standard book-ending procedure uses AMBER to simulate the MM region, and QUICK, AMBER's default QM engine, to handle the QM region with either the Hartree-Fock (HF) method or density functional theory (DFT). In this work, we introduce a novel interface to QUICK, via sander, that enables CI simulations, and can operate in two ways: A) via PySCF backend to perform full configuration interaction (FCI) using conventional computing resources, B) quantum-centric sample-based quantum diagonalization (SQD) workflow via Qiskit which leverages both quantum hardware and post-processing on conventional computing resources for CI simulations. In this workflow QUICK performs most steps of the calculations, but at user-defined intervals, it redirects the computation to either FCI or SQD backend to get the CI result. We computed the book-end corrections for the hydration free energy (HFE) of three small organic molecules (ammonia, methane, and water) to benchmark the proposed approach and demonstrate how quantum-computers can be used in AFE calculations. We believe that this approach can be scaled to more complex systems like drug-receptor interactions in future studies.

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