DMTS-NC Boosts Neural MD Speed 3‑5
New group preprint: "Faster Molecular Dynamics with Neural Network Potentials via Distilled Multiple Time-Stepping and Non-Conservative Forces”, which introduces the DMTS-NC approach - a strategy designed to further accelerate atomistic molecular dynamics simulations using foundation neural network models. https://t.co/SIbycvoca7 Significant Speedups: using the FeNNix-Bio1 foundation model, DMTS-NC is 15–30% faster than its conservative DMTS counterpart making it 3 to 4 time faster overall than single-stime-step (STS) .When applied to the somewhat more computationnaly MACE-OFF23, we observed speedups ranging from 3.66 to 5.64 compared to STS. No Fine-Tuning and Enhanced Stability: unlike many acceleration methods, DMTS-NC requires no system-specific fine-tuning, making it much easier to implement across different chemical spaces. Pushing the Limits: by combining Hydrogen Mass Repartitioning (HMR) and High Hydrogen Friction (HHF), we successfully extended external timesteps up to 10fs while maintaining accuracy. This framework is model-agnostic and can be applied to any neural network potential. We’ve validated it on systems ranging from bulk water to solvated proteins like DHFR. For those interested in the technical details or implementation, the code is available via the FeNNol library and Tinker-HP. Great work by @NicolaiGouraud @qubit_pharma #MachineLearning #compchem #Biophysics #DrugDesign #AI
ML and Quantum Computing Unite for Next‑Gen Drug Discovery
#compchem #machinelearning #quantumcomputing New preprint: "The Convergence Frontier: Integrating Machine Learning and High Performance Quantum Computing for Next-Generation Drug Discovery". @qubit_pharma https://t.co/4D23DV0uAk
Logarithmic-Depth Quantum Circuits Efficiently Prepare Polynomial States
New #quantumcomputing preprint with @qubit_pharma team and CERFACS: "Logarithmic-depth quantum state preparation of polynomials" Check it out: https://t.co/DWGkoTImjK
Quantum MCMC Achieved on NISQ Hardware with Accurate Results
#quantumcomputing New group preprint: "Experimental Realization of the Markov Chain Monte Carlo Algorithm on a Quantum Computer". https://t.co/NSGNw3gTin In this work, we experimentally use encodings of Markov chains to prepare quantum states and run a quantum Markov Chain Monte Carlo...
FeNNix-Bio1 Delivers Quantum‑Accurate MD, Open for Academia
#compchem #compbio 🚀 𝐅𝐞𝐍𝐍𝐢𝐱-𝐁𝐢𝐨1 enables to perform extremely fast molecular dynamics simulations at hashtag#quantum accuracy under various #GPU-accelerated frameworks. 🚀 As some people asked me, the 𝐅𝐞𝐍𝐍𝐢𝐱-𝐁𝐢𝐨1 #machinelearning foundation model is fully available for academic groups (ASL licence) at various places: - 👉...
