Gabriel Matos

Hi! My name is Gabriel, and I am currently a Research Scientist at Quantinuum working on quantum algorithms and applications of artificial intelligence in quantum computing.

Before joining Quantinuum, I completed a PhD in Theoretical Physics at the University of Leeds supervised by Zlatko Papić and Jiannis Pachos. My research during that time was focused on quantum many-body physics and variational quantum algorithms. You can read my PhD thesis.

Before that, I completed a BSc and an MSc in Mathematics at the Instituto Superior Técnico, University of Lisbon. You can read my master's thesis.

Gabriel Matos

Publications & Preprints

2026

  • Quantum error correction well below the color code threshold
    Ali Lavasani, Adam P. Reed, Joan M. Dreiling, Annie J. Park, Michael Mills, Matteo Puviani, Gabriel Matos, M.S. Allman, Noah Berthusen, Natalie C. Brown, Victor E. Colussi, Brian Estey, Cameron Foltz, Daniel Gresh, Reza Haghshenas, Akhil Isanaka, Nikhil Kotibhaskar, Anthony Ransford, Ciarán Ryan-Anderson, Brian Neyenhuis, David Hayes, Tzvetan S. Metodi, Andrew C. Potter
    arXiv:2610.24077 (2026)
  • Stacking the Deck: Tunable Trainability in Stacked LCUs
    Nikhil Khatri, Stefan Zohren, Gabriel Matos
    arXiv:2607.24686 (2026)
  • Efficiently Simulable Pauli Correlation Encoding
    Daniele Lizzio Bosco, Gabriel Matos, Chen-Yu Liu, Frederic Rapp, Fabian Finger, Enrico Rinaldi, Konstantinos Meichanetzidis
    arXiv:2607.20409 (2026)
  • Exact log-depth preparation of highly entangled matrix product states
    Keisuke Murota, Frédéric Sauvage, Marco Ballarin, Gabriel Matos, Enrico Rinaldi
    arXiv:2606.24475 (2026)
  • Fast stabilizer state preparation via AI-optimized graph decimation
    Michael Doherty, Matteo Puviani, Jasmine Brewer, Gabriel Matos, David Amaro, Ben Criger, David T. Stephen
    arXiv:2603.17743 (2026)
  • Reinforcement Learning for Adaptive Composition of Quantum Circuit Optimisation Passes
    Daniel Mills, Ifan Williams, Jacob Swain, Gabriel Matos, Enrico Rinaldi, Alexander Koziell-Pipe
    Mach. Learn.: Sci. Technol. (2026) | arXiv:2601.21629

2025

  • You Only Measure Once: On Designing Single-Shot Quantum Machine Learning Models
    Chen-Yu Liu, Leonardo Placidi, Kuan-Cheng Chen, Samuel Yen-Chi Chen, Gabriel Matos
    arXiv:2509.20090 (2025)
  • Trainability of Parametrised Linear Combinations of Unitaries
    Nikhil Khatri, Stefan Zohren, Gabriel Matos
    arXiv:2506.22310 (2025)
  • Lindblad engineering for quantum Gibbs state preparation under the eigenstate thermalization hypothesis
    Eric Brunner, Luuk Coopmans, Gabriel Matos, Matthias Rosenkranz, Frederic Sauvage, Yuta Kikuchi
    Quantum 9, 1843 (2025) | arXiv:2412.17706

2024

2023

2022

  • Laughlin states change under large geometry deformations and imaginary time Hamiltonian dynamics
    Gabriel Matos, Bruno Mera, José M. Mourão, Paulo D. Mourão, João P. Nunes
    Commun. Math. Phys. (2022) | arXiv:2107.11360

2021

2020