Graphics processing unit-accelerated quantum simulation for molecular biology and drug discovery: algorithms, platforms, and emerging applications.

GPU-accelerated quantum simulation enables quantum algorithms to be developed, validated, and benchmarked on classical hardware at 30–40 noiseless qubits, bridging toward quantum-accurate molecular modeling.

• Why it matters: Quantum hardware is scarce and noisy, limiting direct experiments, while classical force fields and density functional theory alone cannot reach quantum-mechanical fidelity for molecular and biological processes.
• What they did: The review surveys simulation-layer methods—variational quantum eigensolver, quantum phase estimation, and sample-based hybrid schemes—plus GPU benchmarks, and maps where tensor-network approaches are adequate versus not.
• The result: It compiles GPU platform evidence, explains how GPUs accelerate error mitigation, and assesses 2023–6 advances such as hybrid quantum Monte Carlo and protein binding-site prediction, positioning GPU simulation as a near-term enabler.

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