Qubit Pharmaceuticals

#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....

🚀 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

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.

#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)

Check it out!!! #compbio #drugdesign #AI4Science

Check it out! #compbio #drugdesign #ai4science

Speeding up accurate relative binding free energy computation: dual-LAO. #compchem

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.

💫 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

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

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...

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-...

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!

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": just published in @natcomms.nature.com.
#quantumcomputing

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...

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...

🤩 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

The paper is #openacces and you can check the associated blog: blog.qubit-pharmaceuticals.com/blog/unlocki...

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.

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)

Real-Space Chemistry on Quantum Computers: A Fault-Tolerant Algorithm with Adaptive Grids and Transcorrelated Extension First-quantized, real-space formulations of quantum chemistry on quantum computers are appealing: qubit count scales logarithmically with spatial resolution, and Coulomb operators achieve quadratic in...

A molecule-adaptive, non-uniform grid approach for first-quantized quantum chemistry enables efficient resolution of electron-nuclear cusps and eliminates Coulomb singularities, allowing accurate ground-state simulations on quantum hardware.
@jppiquem.bsky.social
arxiv.org/abs/2507.20583

Real-Space Chemistry on Quantum Computers: A Fault-Tolerant Algorithm with Adaptive Grids and Transcorrelated Extension First-quantized, real-space formulations of quantum chemistry on quantum computers are appealing: qubit count scales logarithmically with spatial resolution, and Coulomb operators achieve quadratic in...

New preprint: "Real-Space Chemistry on Quantum Computers: A Fault-Tolerant Algorithm with Adaptive Grids and Transcorrelated Extension".
arxiv.org/abs/2507.20583

#compchem #compchemsky #quantumcomputing

#compchem Our #quantumcomputing paper "Non-iterative disentangled unitary coupled-cluster based on lie-algebraic structure" published in Quantum Science and Technology @iopp-quantum.bsky.social just switched to #openaccess.
iopscience.iop.org/article/10.1...

#compchem Congrats to Nicolaï Gouraud who brilliantly defended his #applliedmathematics PhD thesis yesterday @sorbonne-universite.fr. @lct-umr7616.bsky.social @qubit-pharma.bsky.social

Methodological developments in electronic structure theory and chemical dynamics This Collection aims to highlight research that advances our understanding of electronic structure and chemical dynamics, as well as the application of ...

#compchem Our recent work "𝐒𝐡𝐨𝐫𝐭𝐜𝐮𝐭 𝐭𝐨 𝐜𝐡𝐞𝐦𝐢𝐜𝐚𝐥𝐥𝐲 𝐚𝐜𝐜𝐮𝐫𝐚𝐭𝐞 𝐪𝐮𝐚𝐧𝐭𝐮𝐦 𝐜𝐨𝐦𝐩𝐮𝐭𝐢𝐧𝐠 𝐯𝐢𝐚 𝐝𝐞𝐧𝐬𝐢𝐭𝐲-𝐛𝐚𝐬𝐞𝐝 𝐛𝐚𝐬𝐢𝐬-𝐬𝐞𝐭 𝐜𝐨𝐫𝐫𝐞𝐜𝐭𝐢𝐨𝐧 " has been selected in the following Nature collection ( #quantumcomputing for Quantum Chemistry section). www.nature.com/collections/...

I heard in some talks at #Watoc 2025 that #machinelearning Foundation models could not simulate well condensed-phase systems in Biology & Chemistry. Have a look at our recent papers! Lots of things are now possible with the #FENNIX-Bio1 model (check the post below). #compchem #drugdesign #GPU

Our #quantumcomputing work on the Metropolis-Hastings quantum speedup (see: arxiv.org/abs/2506.11576) highlighted on Quantum Zeitgeist. #compchemsky #compchem

#quantumcomputing New preprint: "Quantum Circuits for the Metropolis-Hastings Algorithm".
👉Check it out: arxiv.org/abs/2506.11576
Enabling the end-to-end quadratic speedup of Metropolis-Hastings simulations to hold.
Stellar work by B. CLaudon, P. Rodenas-Ruiz & nice collab with P. Monmarché.

Here is a short "Behind the Paper" blog on the Nature Physics Community about our recent #quantumcomputing paper published in Scientific Reports.

👉 Check it out: communities.springernature.com/posts/greedy...
#compchem #hpc

Greedy gradient-free adaptive variational quantum algorithms on a noisy intermediate scale quantum computer - Scientific Reports Scientific Reports - Greedy gradient-free adaptive variational quantum algorithms on a noisy intermediate scale quantum computer

#compchem #quantumcomputing New paper: "Greedy gradient-free adaptive variational quantum algorithms on a noisy intermediate scale quantum computer"
Great work by Cesar Feniou and nice collaboration with Y. Maday.
@qubit-pharma.bsky.social

www.nature.com/articles/s41...