Qubit Pharmaceuticals
@qubit-pharma.bsky.social
Bringing unparalleled #accuracy and precision to #drugdiscovery and design, using #quantumphysics to develop life-changing treatments for major diseases. Visit our website: https://www.qubit-pharmaceuticals.com/
Now in final form and #openaccess. "Quantum circuits for the Metropolis–Hastings algorithm" #quantumcomputing iopscience.iop.org/article/10.1...
Jean-Philip Piquemal@jppiquem.bsky.social · 3w agoFinally out in J. Phys. A: Math. Theor.: "Quantum Circuits for the Metropolis-Hastings Algorithm" With these quantum walks, the end-to-end quadratic speedup holds for MH Markov Chain Monte-Carlo simulations. Stellar work by B. Claudon. #quantumcomputing #compchem iopscience.iop.org/article/10.1...
#compchem #compbio New group paper in JCTC: "Faster Molecular Dynamics with Neural Network Potentials via Distilled Multiple Time-Stepping and Nonconservative Forces". No fine-tuning, easier to implement, high accuracy & maximum efficiency. @qubit-pharma.bsky.social pubs.acs.org/doi/10.1021/...
Just out: Dual-LAO for calculating fast and robust relative binding free energies of simple and complex transformations
Dual-LAO for calculating fast and robust relative binding free energies of simple and complex transformations
Communications Chemistry, Published online: 08 May 2026; doi:10.1038/s42004-026-02022-6Relative Binding Free Energy (RBFE) calculations are essential for drug discovery but are often hindered by high computational costs and limited reliability for complex transformations. Here, the authors introduce the Dual-LAO framework integrating Lambda-ABF-OPES, dual topology, and dual-DBC restraints, that accelerates RBFE calculations by 15 to 30 times, maintains high accuracy and tackles previously prohibitive molecular changes.
dlvr.it
We demonstrate that Dual-LAO, in combination with the AMOEBA polarizable force field, achieves an unprecedented acceleration factor of 15 to 30 times compared to current state-of-the-art methods on standard drug targets. #compchem #compchemsky #compbio #drugdesign
Jean-Philip Piquemal@jppiquem.bsky.social · 3mo agoNew paper with the @qubit-pharma.bsky.social team led by Narjes Ansari, just published @commschem.nature.com : "Dual-LAO for calculating fast and robust relative binding free energies of simple and complex transformations". #compchem #compchemsky #compbio www.nature.com/articles/s42...
New paper with the @qubit-pharma.bsky.social team led by Narjes Ansari, just published @commschem.nature.com : "Dual-LAO for calculating fast and robust relative binding free energies of simple and complex transformations". #compchem #compchemsky #compbio www.nature.com/articles/s42...
Dual-LAO for calculating fast and robust relative binding free energies of simple and complex transformations - Communications Chemistry
Relative Binding Free Energy (RBFE) calculations are essential for drug discovery but are often hindered by high computational costs and limited reliability for complex transformations. Here, the auth...
nature.com
Qubit Pharmaceuticals @qubit-pharma.bsky.social to collaborate with the Centre for Quantum Technologies @quantumlah.bsky.social in Singapore to Advance Quantum Algorithms for Drug Discovery. #quantumcomputing #compchem #compchemsky #compbio thequantuminsider.com/2026/04/30/q...
Qubit Pharmaceuticals to Collaborate with the Centre for Quantum Technologies in Singapore to Advance Quantum Algorithms for Drug Discovery
Qubit Pharmaceuticals and the Centre for Quantum Technologies have launched a two-year collaboration to develop and test quantum algorithms.
thequantuminsider.com
Will Quantum Computing actually transform #drug discovery? In the age of AI, why are we still betting on Quantum & GPU-accelerated HPC? We’ve just released our whitepaper detailing how the synergy of #QuantumComputing #MachineLearning & #HPC enables quantum-accurate simulations. #compbio #compchem
Jean-Philip Piquemal@jppiquem.bsky.social · 5mo ago#compchem #machinelearning #quantumcomputing #compbio New preprint: "The Convergence Frontier: Integrating Machine Learning and High Performance Quantum Computing for Next-Generation Drug Discovery". @qubit-pharma.bsky.social arxiv.org/abs/2603.17790
New #quantumcomputing preprint: quantum Markov Chain Monte Carlo on quantum computer!
Jean-Philip Piquemal@jppiquem.bsky.social · 5mo ago#quantumcomputing New preprint: "Experimental Realization of the Markov Chain Monte Carlo Algorithm on a Quantum Computer". We experimentally encoded & accurately ran a quantum MCMC on the H2 & Helios quantum computers. @qubit-pharma.bsky.social @quantumlah.bsky.social arxiv.org/abs/2603.08395
#compchem #compchemsky Our paper in J. Phys. Chem. Lett.: "Accelerating Molecular Dynamics Simulations with Foundation Neural Network Models using Multiple Time-Step and Distillation" made it to one of the covers! pubs.acs.org/doi/full/10....
Jean-Philip Piquemal@jppiquem.bsky.social · 7mo ago#compchem #machinelearning 1st of the year in J. Phys. Chem. Lett.: "Accelerating Molecular Dynamics Simulations with Foundation Neural Network Models using Multiple Time-Step and Distillation". pubs.acs.org/doi/full/10.... (see also the updated preprint: arxiv.org/abs/2510.06562)
🚀 Game-changing speed for drug discovery simulations without trading accuracy for Relative Binding Free Energy (RBFE) calculations. Dual-LAO delivers 15–30× faster simulations while maintaining industry-leading accuracy (~0.5–0.6 kcal/mol). #compchem t.co/dDLVqXKvZm
🤩 New year, new publication using the FeNNix-Bio1 foundation model ! 🚀« Accelerating Molecular Dynamics Simulations with Foundation Neural Network Models using Multiple Time-Step and Distillation» published in the Journal of Physical Chemistry Letters #compchemsky #biosky #machinelearning
Jean-Philip Piquemal@jppiquem.bsky.social · 7mo ago#compchem #machinelearning 1st of the year in J. Phys. Chem. Lett.: "Accelerating Molecular Dynamics Simulations with Foundation Neural Network Models using Multiple Time-Step and Distillation". pubs.acs.org/doi/full/10.... (see also the updated preprint: arxiv.org/abs/2510.06562)
#compchem #machinelearning 1st of the year in J. Phys. Chem. Lett.: "Accelerating Molecular Dynamics Simulations with Foundation Neural Network Models using Multiple Time-Step and Distillation". pubs.acs.org/doi/full/10.... (see also the updated preprint: arxiv.org/abs/2510.06562)
Accelerating Molecular Dynamics Simulations with Foundation Neural Network Models Using Multiple Time Steps and Distillation
We present a distilled multi-time-step (DMTS) strategy to accelerate molecular dynamics simulations using foundation neural network models. DMTS uses a dual-level neural network, where the target accurate potential is coupled to a simpler but faster model obtained via a distillation process. The 3.5 Å cutoff distilled model is sufficient to capture the fast-varying forces, i.e., mainly bonded interactions, from the accurate potential, allowing its use in a reversible reference system propagator algorithm (RESPA)-like formalism. The approach conserves accuracy, preserving both static and dynamic properties, while enabling us to evaluate the costly model only every 3 to 6 fs depending on the system. Consequently, large simulation speedups over standard 1 fs integration are observed: nearly 4-fold in homogeneous systems and 3-fold in large solvated proteins through leveraging active learning for enhanced stability. Such a strategy is applicable to any neural network potential and reduces the performance gap with classical force fields.
pubs.acs.org
Check it out!!! #compbio #drugdesign #AI4Science
Jean-Philip Piquemal@jppiquem.bsky.social · 7mo ago#hpc #supercomputing #machinelearning #compchem New Grand Challenges @gencifrance.bsky.social report dedicated to the Jean Zay 4 machine at IDRIS. Our work on the FeNNix-Bio1 machine learning foundation model can be found on pages 22-25. genci.fr/sites/defaul...
Speeding up accurate relative binding free energy computation: dual-LAO. #compchem
Jean-Philip Piquemal@jppiquem.bsky.social · 8mo ago#compchem #compbio Last preprint of the year: "Fast, systematic and robust relative binding free energies for simple and complex transformations : dual-LAO". arxiv.org/abs/2512.17624 Great work by N. Ansari. @qubit-pharma.bsky.social . Another nice collab with J. Hénin.
💫 We just released the weights of the #FeNNixBio1 foundation machine learning model for drug design! 💫 Weights: github.com/FeNNol-tools... FeNNol code: github.com/FeNNol-tools... The models are distributed under the open source ASL license (non-commercial academic research). #compchem #compbio
GitHub - FeNNol-tools/FeNNol-PMC: FeNNol Pretrained Models Collection
FeNNol Pretrained Models Collection. Contribute to FeNNol-tools/FeNNol-PMC development by creating an account on GitHub.
github.com
New paper in collaboration with Q-CTRL demonstrating the use of NISQ hardware for the water placement problem in drug design, up to 123 qubits on IBM's Heron QPU! #quantumcomputing #compchem #drugdesign
Jean-Philip Piquemal@jppiquem.bsky.social · 8mo ago#compchem #quantumcomputing I’m thrilled to share this new preprint: "Practical protein-pocket hydration-site prediction for drug discovery on a quantum computer". 👉Check it out: arxiv.org/abs/2512.08390 Great collab with D. Loco (@qubit-pharma.bsky.social ), K. Barkemeyer & A. Carvalho (Q-CTRL)
Quantum Zeitgeist @superposition.bsky.social highlighted our recent preprint: "An Optimal Framework for Constructing Lie-Algebra Generator Pools: Application to Variational Quantum Eigensolvers for Chemistry" #quantumcomputing #compchem quantumzeitgeist.com/variational-...
Optimal Framework Constructs Lie-Algebra Generator Pools, Enabling Efficient Variational Quantum Eigensolvers For Chemistry
Researchers have developed a new mathematical strategy that efficiently identifies the essential building blocks of complex systems, dramatically improving computational power for applications ranging...
quantumzeitgeist.com
Ce lundi 8/12, je représenterai @qubit-pharma.bsky.social à la journée "𝐐𝐮𝐚𝐧𝐭𝐮𝐦 & 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐞𝐥𝐥𝐞 - 𝐕𝐞𝐫𝐬 𝐮𝐧𝐞 𝐜𝐨𝐧𝐯𝐞𝐫𝐠𝐞𝐧𝐜𝐞 𝐝𝐞𝐬 𝐫𝐮𝐩𝐭𝐮𝐫𝐞𝐬 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐪𝐮𝐞𝐬 ?". evenium.events/quantum-inte... #quantumcomputing #AI #artificialintelligence #machinelearning
#quantumcomputing #compchem New preprint! The presented mathematical framework is general & applicable well beyond chemistry in fields including quantum error correction, quantum control, quantum machine learning, and more universally wherever compact Pauli basis are required. Congrats to the team!
Jean-Philip Piquemal@jppiquem.bsky.social · 8mo ago#compchem #compchemsky #quantumcomputing New group preprint: "An Optimal Framework for Constructing Lie-Algebra Generator Pools: Application to Variational Quantum Eigensolvers for Chemistry." 👉Check it out: arxiv.org/abs/2511.22593 @piquemalgroup.bsky.social @qubit-pharma.bsky.social
New preprint! The presented mathematical framework is general and applicable well beyond chemistry in fields including quantum error correction, quantum control, quantum machine learning, & more universally wherever compact Pauli basis are required! #quantumcomputing #compchem Confrats to the team.
#quantumcomputing Check our “Behind the paper” post on the @nature.com Physics community. @qubit-pharma.bsky.social @sorbonne-universite.fr @cnrs.fr communities.springernature.com/posts/quantu...
Quantum Speedup for Nonreversible Markov Chains
This work investigates two quantum methods for accelerating the mixing of nonreversible Markov chains on a quantum computer. The results extend the quadratic speedup in sampling from the stationary me...
communities.springernature.com
Jean-Philip Piquemal@jppiquem.bsky.social · 8mo ago#compchem #quantumcomputing New paper published @natcomms.nature.com "Quantum Speedup for Nonreversible Markov Chains". 👉Check it out #openaccess. Congrats to B. Claudon and another maths/chemistry collaboration with P. Monmarché. www.nature.com/articles/s41...
"Quantum speedup for nonreversible Markov Chains": just published in @natcomms.nature.com. #quantumcomputing
Jean-Philip Piquemal@jppiquem.bsky.social · 8mo ago#compchem #quantumcomputing New paper published @natcomms.nature.com "Quantum Speedup for Nonreversible Markov Chains". 👉Check it out #openaccess. Congrats to B. Claudon and another maths/chemistry collaboration with P. Monmarché. www.nature.com/articles/s41...
Un grand merci à @natachatriou.bsky.social pour nous avoir reçu dans l'émission #SciencesCQFD sur @franceculture.fr pour discuter des usages des supercalculateurs. @sorbonne-universite.fr / @cnrs.fr @qubit-pharma.bsky.social www.radiofrance.fr/francecultur...
Supercalculateurs : droit au bit
Depuis quelques années, on entend beaucoup parler de ”supercalculateurs”. Mais ces géants silencieux ont toujours fait partie de l’histoire de l’informatique, et la guerre de clochers à laquelle on as...
radiofrance.fr
🤩 We are immensely proud to be selected for the #FrenchTech2030 program for the second year in a row! ⚡ This continued support is a powerful validation of our mission: to accelerate new molecule discovery using quantum computing. #QuantumComputing #AI #DeepTech
New #preprint: Accelerating molecular dynamics simulations with foundation #machinelearning models
Jean-Philip Piquemal@jppiquem.bsky.social · 10mo ago#compchem #compbio New preprint: "𝐀𝐜𝐜𝐞𝐥𝐞𝐫𝐚𝐭𝐢𝐧𝐠 𝐌𝐨𝐥𝐞𝐜𝐮𝐥𝐚𝐫 𝐃𝐲𝐧𝐚𝐦𝐢𝐜𝐬 𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧𝐬 𝐰𝐢𝐭𝐡 𝐅𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐍𝐞𝐮𝐫𝐚𝐥 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐌𝐨𝐝𝐞𝐥𝐬 𝐮𝐬𝐢𝐧𝐠 𝐌𝐮𝐥𝐭𝐢𝐩𝐥𝐞 𝐓𝐢𝐦𝐞-𝐒𝐭𝐞𝐩 𝐚𝐧𝐝 𝐃𝐢𝐬𝐭𝐢𝐥𝐥𝐚𝐭𝐢𝐨𝐧" in link with our #FeNNix-Bio1 foundation #machinelearning model. 👉 Check it out: arxiv.org/abs/2510.06562
The paper is #openacces and you can check the associated blog: blog.qubit-pharmaceuticals.com/blog/unlocki...
Unlocking RNA Targets: Advancing Drug Discovery with Cutting-Edge Simulations
Qubit Pharmaceuticals accelerates and transforms drug discovery by publishing an unprecedentedly accurate computational approach combining their core technologies with exciting innovations: highest ac...
blog.qubit-pharmaceuticals.com
Jean-Philip Piquemal@jppiquem.bsky.social · 10mo ago#compchem #compbio Happy to be part of this new paper just published in @commsbio.nature.com : "Targeting RNA with Small Molecules using State-of-the-Art Methods Provides Highly Predictive Affinities of Riboswitch Inhibitors." www.nature.com/articles/s42... @qubit-pharma.bsky.social
Thank you @pennylaneai.bsky.social for selecting our work in your "𝐓𝐨𝐩 𝐪𝐮𝐚𝐧𝐭𝐮𝐦 𝐚𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 𝐩𝐚𝐩𝐞𝐫𝐬 — 𝐒𝐮𝐦𝐦𝐞𝐫 2025 𝐞𝐝𝐢𝐭𝐢𝐨𝐧". pennylane.ai/blog/2025/09... 👉 Check the paper (link in comment)
Top quantum algorithms papers — Summer 2025 edition | PennyLane Blog
We've selected our favourite papers from the third quarter of 2025. Read our takeaways from the top quantum algorithms papers that we admire and that have been influential to our research.
pennylane.ai