activity
20172026
most citedTinker-HP : Accelerating Molecular Dynamics Simulations of Large Complex Systems with Advanced Point Dipole Polarizable Force Fields using GPUs and Multi-GPUs systems

92 citations · 665 across the 45 of their papers we have counts for

collaborators

54 papers

physics.chem-ph2026

Probing Extended Recognition Sites in Zn-Metalloproteins via Quantum Chemistry and Polarizable Molecular Dynamics

Nohad Gresh, Jean-Philip Piquemal

Zn-metalloproteins play vital roles in numerous metabolic processes, making them high-value targets for structure-based drug design. To advance these efforts, it is useful to unrav…

quant-ph2026

The Convergence Frontier: Integrating Machine Learning and High Performance Quantum Computing for Next-Generation Drug Discovery

Narjes Ansari, César Feniou, Nicolaï Gouraud +13

Integrating quantum mechanics into drug discovery marks a decisive shift from empirical trial-and-error toward quantitative precision. However, the prohibitive cost of ab initio mo…

quant-ph2026

High Performance Quantum Emulation for Chemistry Applications with Hyperion

Olivier Adjoua, Siwar Badreddine, César Feniou +4

The strategic demand for quantum hardware currently outpaces the availability of near-term devices, necessitating high-performance software emulators to validate novel protocols. W…

quant-ph2026

Logarithmic-depth quantum state preparation of polynomials

Baptiste Claudon, Alexis Lucas, Jean-Philip Piquemal +2

Quantum state preparation is a central primitive in many quantum algorithms, yet it is generally resource intensive, with efficient constructions known only for structured families…

quant-ph2026

Experimental Realization of the Markov Chain Monte Carlo Algorithm on a Quantum Computer

Baptiste Claudon, Sergi Ramos-Calderer, Jean-Philip Piquemal

Quantum algorithms present a quadratically improved complexity over classical ones for certain sampling tasks. For instance, the Quantum Amplitude Estimation (QAE) algorithm promis…

physics.chem-ph2026

Faster Molecular Dynamics with Neural Network Potentials via Distilled Multiple Time-Stepping and Non-Conservative Forces

Nicolaï Gouraud, Côme Cattin, Thomas Plé +3

Following our previous work (J. Phys. Chem. Lett., 2026, 17, 5, 1288-1295), we propose the DMTS-NC approach, a distilled multi-time-step (DMTS) strategy using non-conservative (NC)…