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Reposted by Luis Mantilla

The Matter Lab @thematterlab.bsky.social · 30/04/2026

🚀Excited to share our latest work: “Optimizing ground state preparation protocols with autoresearch”. We explore how language-model coding agents can automate the optimization of ground-state preparation protocols in quantum computing & classical quantum simulation. 🔗 arxiv.org/abs/2604.25610 [1/4]

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Reposted by Luis Mantilla

The Matter Lab @thematterlab.bsky.social · 02/03/2026

Kudos to the authors: Raul Ortega Ochoa, @realmantilla.bsky.social, Juan Bernardo Pérez Sánchez, Mohsen Bagherimehrab, @an-aldossary.bsky.social, @tvegge.bsky.social, Tonio Buonassisi, and @aspuru.bsky.social. [5/5]

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Reposted by Luis Mantilla

The Matter Lab @thematterlab.bsky.social · 02/03/2026

Our perspective, Connecting the concepts of quantum state tomography and molecular representations for machine learning", is now published in Digital Discovery🎉 Here, we explore how ideas from quantum state tomography can inform representation learning in molecular ML 🔗 doi.org/10.1039/D5DD... [1/5]

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Luis Mantilla @realmantilla.bsky.social · 28/11/2025

The matter blotter is back :) This week we revisit the springs and sticks model—one of the projects I have enjoyed the most working on during my PhD! A universal regression model that learns using thermodynamics, and let’s us compute the minimum energy it requires to learn a function

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Reposted by Luis Mantilla

The Matter Lab @thematterlab.bsky.social · 30/09/2025

Excited to share our new article: “Quantum algorithm for vibronic dynamics: case study on singlet fission solar cell design”, now published in Quantum Science and Technology! 📜 Paper: doi.org/10.1088/2058... 📝 Blog post overview: pennylane.ai/blog/2025/02... [1/8]

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Reposted by Luis Mantilla

The Matter Lab @thematterlab.bsky.social · 19/09/2025

🎉Excited to share our new perspective: “Connecting the concepts of quantum state tomography and molecular representations for machine learning” — now on ChemRxiv! Link: doi.org/10.26434/che... [1/5]

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Reposted by Luis Mantilla

Alán Aspuru-Guzik @aspuru.bsky.social · 28/08/2025

With all the recent interest in physical machine learning, @realmantilla.bsky.social and I wondered what would be a mechanical machine learning system? We devised a simple springs and sticks model that leads to very interesting thermodynamics learning limits. #chemsky #physicssky #machinelearning

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Reposted by Luis Mantilla

The Matter Lab @thematterlab.bsky.social · 28/08/2025

Excited to share our most recent work: “Learning with springs and sticks” — now on arXiv! Paper link: arxiv.org/abs/2508.19015 Project page (with animations & code): bestquark.github.io/springs-and-... Authors: @realmantilla.bsky.social, @aspuru.bsky.social [1/4]

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Reposted by Luis Mantilla

The Matter Lab @thematterlab.bsky.social · 30/06/2025

⚛️ Curious about getting into quantum computing for quantum chemistry? Check out our new primer published in ACS InFocus. 📙 [1/4]

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Reposted by Luis Mantilla

The Matter Lab @thematterlab.bsky.social · 09/06/2025

👾Excited to share our most recent work: “Quantum circuits as a game: A reinforcement-learning compiler for reconfigurable neutral-atom arrays” — now live on arXiv! We explore how reconfigurable neutral-atom arrays can be controlled more efficiently using reinforcement learning. [1/5]

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Reposted by Luis Mantilla

The Matter Lab @thematterlab.bsky.social · 24/03/2025

⚛️🖥️Excited to share our work on simulating Hamiltonian evolution on quantum computers. Led by our group member Mohsen Bagherimehrab, we introduce Corrected Product Formulas (CPFs), which significantly improve the performance of standard product formulas. [1/4]

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