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Subhamoy Bhowmik

Publications and source records attributed to Subhamoy Bhowmik.

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Quantum Computing Enabled ab initio Molecular Dynamics Simulations

We demonstrate a quantum-classical workflow for ab initio molecular dynamics (AIMD) in which quantum measurements from a chemistry-inspired LUCJ ansatz are post-processed using Sample-based Quantum Diagonalization (SQD) to recover determinant subspaces and deliver energies and analytical nuclear gradients for dynamics. As an exact benchmark, we use full configuration interaction (FCI) in the STO-3G basis, enabling a direct assessment of the accuracy of SQD. In gas-phase benchmarks, SQD reproduces FCI energies and gradients to within 1 kcal mol$^{-1}$ of the FCI reference and yields stable AIMD trajectories. In explicit-solvent QM/MM simulations, SQD retains this agreement, matching FCI energy fluctuations and RMS gradient profiles and reproducing solute-solvent structure as quantified by radial distribution functions. Overall, these benchmarks establish LUCJ+SQD as a practical route for integrating current quantum hardware into QM/MM molecular dynamics and provide an early demonstration of condensed-phase QM/MM dynamics driven by a quantum electronic-structure engine.

physics.chem-ph

Quantum Computations on Fusion Blanket Molten Salts

Molten salts such as FLiBe (2LiF--BeF$_2$) are leading blanket materials for breeding and recovering tritium in fusion reactors. Predicting tritium speciation requires accurate electronic ground-state energies for representative molten-salt clusters, a demanding task for correlated electronic-structure methods. Here we report the first application of heterogeneous quantum--classical computing to tritium binding in FLiBe. Clusters drawn from ab initio molecular dynamics are partitioned by an embedded-wavefunction (EWF) method into atom-centered fragments, and the largest fragments are solved on IBM quantum hardware using extended sample-based quantum diagonalization (ext-SQD). Across nine clusters, the heterogeneous quantum--classical workflow reproduces fragment ground-state energies with agreement to full configuration interaction within 0.7~kcal/mol and a mean absolute deviation of 0.3~kcal/mol. In contrast, fragmented and unfragmented conformational energy differences and tritium binding energies differ by 12~kcal/mol and 110~kcal/mol on average, respectively, identifying fragment construction rather than fragment solution as the dominant source of algorithmic bias. To the best of our knowledge, this is the first such demonstration for a charged ionic system and in particular an inorganic molten salt, where electrostatic and polarization effects make the accurate treatment of electronic correlation particularly challenging. These results also identify areas of future research towards an accurate and scalable quantum--classical workflow to compute free-energy estimates of tritium speciation in fusion blankets.

quant-ph

Protein-Ligand Free Energy Perturbation on Quantum Hardware

The use of free energy perturbation (FEP) methods to study protein-ligand complexes is one of the most important tools in structure-based drug design. Because FEP methods typically rely on force fields, they may suffer from force field parameter-related issues. Herein, we present a quantum mechanics/molecular mechanics (QM/MM) hybrid method to overcome deficiencies in force-field models by using QM bookending approaches on both classical and quantum hardware. In the MM part of this QM/MM FEP method, AMBER is used to simulate the protein receptor and the unperturbed moiety of the ligand, with the ff19SB and GAFF2 force fields. In the QM part, QUICK was used to conduct Hartree-Fock (HF) calculations, followed by heat-bath configuration interaction (HCI) as a benchmark on classical devices. To enable the HCI function in QUICK, we developed a Python-based interface to execute HCI from IBM's qiskit-addon-dice-solver. Moreover, the same interface also enabled this work to execute QM/MM FEP calculations on quantum hardware using the Local Unitary Cluster Jastrow (LUCJ) ansatz, followed by sample-based diagonalization (SQD) and extended-SQD (extSQD) post-processing. Using a series of thermolysis inhibitors as an example, we find reasonable agreement with experiment between the classical HCI method and the LUCJ-SQD/extSQD method, with the latter yielding a result closer to the experimental value. The execution time between the HCI-based FEP method and the LUCJ-SQD/extSQD-based FEP method is also comparable, indicating a high potential for utility in the noisy intermediate-scale quantum (NISQ) era.

quant-ph

Molecular Quantum Computations on a Protein

This work presents the implementation of a fragment-based, quantum-centric supercomputing workflow for computing molecular electronic structure using quantum hardware. The workflow is applied to predict the relative energies of two conformers of the 300-atom Trp-cage miniprotein. The methodology employs wave function-based embedding (EWF) as the underlying fragmentation framework, in which all atoms in the system are explicitly included in the CI treatment. CI calculations for individual fragments are performed using either sample-based quantum diagonalization (SQD) for challenging fragments or full configuration interaction (FCI) for trivial fragments. To assess the accuracy of SQD for fragment CI calculations, EWF-(FCI,SQD) results are compared against EWF-MP2 and EWF-CCSD benchmarks. Overall, the results demonstrate that large-scale electronic configuration interaction (CI) simulations of protein systems containing hundreds or even thousands of atoms can be realized through the combined use of quantum and classical computing resources.

quant-ph