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]

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]

Kudos to the amazing team from UofT and NVIDIA for making this happen! Luca Anthony Thiede, @an-aldossary.bsky.social, @andreasburger.bsky.social, Jorge Campos, Ning Wang, Alexander Zook, Melisa Alkan, Kouhei Nakaji, Taylor Patti, Jérôme Gonthier, Mohammad Ghazi Vakili, @aspuru.bsky.social [7/7]

Kudos to the team who made this happen: Jiaru Bai, @an-aldossary.bsky.social, Thomas Swanick, Marcel Müller, Yeonghun Kang, Zijian Zhang, Jin Won Lee, Tsz Wai Ko, Mohammad Ghazi Vakili, @variniabernales.bsky.social, @aspuru.bsky.social [7/7]

Brought to you by the Matter Lab at the University of Toronto: Philipp Schleich, @realmantilla.bsky.social, @an-aldossary.bsky.social, @aspuru.bsky.social, together with Chong Sun at Rutgers University and @kottmann.bsky.social at the University of Augsburg. [4/4]

We’re excited to welcome a new member to the Matter Lab: El AgenteQ Specialty: Quantum Chemistry Operating mode: 24/7. No coffee. No ego. Just results and electrons. Contributions: arxiv.org/abs/2505.02484 [1/6]

⚛️🖥️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]