Matthias C. Caro

E-Mail: matthias.caro (at) fu-berlin.de

I am a postdoctoral researcher in the group of Jens Eisert at the Physics Department of the Freie Universität Berlin. I work at the intersection of quantum information theory and machine learning theory.

Before returning to FU Berlin, I was a postdoctoral visiting research fellow in the group of John Preskill at the Caltech Institute for Quantum Information and Matter funded by the DAAD PRIME program. And before becoming a postdoc, I did my PhD at the Chair of Mathematical Physics at the Mathematics Department of the Technical University of Munich, supervised by Michael M. Wolf. The topic of my PhD thesis was "Quantum Learning Theory".

In Fall 2024, I will join the Department of Computer Science at the University of Warwick as an Assistant Professor.

News

2024/06/06: We posted our work "Online learning of quantum channels" on the arXiv.
2024/05/08: Our work Information-theoretic generalization bounds for learning from quantum data was accepted at COLT 2024.
2024/04/15: Our works Classical Verification of Quantum Learning, Dissipation-enabled bosonic Hamiltonian learning via new information-propagation bounds, Hamiltonian Property Testing, and Information-theoretic generalization bounds for learning from quantum data were accepted at TQC 2024.
2024/03/19: I gave a talk on "Information-theoretic generalization bounds for learning from quantum data" at the DPG Spring Meeting 2024.
2024/03/05: We posted our work "Hamiltonian Property Testing" on the arXiv.
2024/03/05: Our work "Dynamical simulation via quantum machine learning with provable generalization" was published in Physical Review Research.
2024/02/14: I gave a talk on "Learning quantum states and unitaries of bounded gate complexity" in the University of Warwick Computer Science Colloquium.
2024/01/24: Our work "Classical Verification of Quantum Learning" was published in the ITCS 2024 proceedings.
2023/11/09: We posted our work "Information-theoretic generalization bounds for learning from quantum data" on the arXiv.
2023/11/08: Our work "Classical Verification of Quantum Learning" was accepted at ITCS 2024.
2023/11/07: I gave a talk on "Classical Verification of Quantum Learning" at IQC Quantum Innovators 2023.
2023/11/02: I gave a talk on "Classical Verification of Quantum Learning" at Harvard University.
2023/10/30: We posted our work "Learning quantum states and unitaries of bounded gate complexity" on the arXiv.
2023/10/17: I gave a talk on "Classical Verification of Quantum Learning" at the IPAM Workshop "Mathematical Aspects of Quantum Learning".
2023/09/19: I gave a talk on "Classical Verification of Quantum Learning" at QAISG's QML seminar.
2023/08/17: Our works Classical Verification of Quantum Learning and The power and limitations of learning quantum dynamics incoherently were accepted for Long Talks at QTML 2023!
2023/07/28: I gave a talk on "Out-of-distribution generalization for learning quantum dynamics and dynamical simulation" at TQC 2023.
2023/07/27: We posted our work "Dissipation-enabled bosonic Hamiltonian learning via new information-propagation bounds" on the arXiv.
2023/07/05: Our work "Out-of-distribution generalization for learning quantum dynamics" was published in Nature Communications and featured in press releases by EPFL and LANL.
2023/06/23: I was awarded the MCQST PhD Award 2022.
2023/06/08: We posted our work "Classical Verification of Quantum Learning" on the arXiv.
2023/04/03: "Our work Out-of-distribution generalization for learning quantum dynamics and dynamical simulation" was accepted for a talk at TQC 2023.
2023/03/28: Our work "On the Generators of Quantum Dynamical Semigroups with Invariant Subalgebras" was published in Open Systems & Information Dynamics.
2023/03/28: I presented a poster on "Out-of-distribution generalization for learning quantum dynamics and dynamical simulation" at The University of Chicago and Caltech Conference on AI+Science.
2023/03/23: We posted our work "The power and limitations of learning quantum dynamics incoherently" on the arXiv.
2023/03/10: I gave a talk on "Out-of-distribution generalization for learning quantum dynamics" at the APS March Meeting 2023.
2023/02/28: I was awarded a TopMath Award for exceptional research achievements during the PhD.
2023/02/24: I gave a talk on "Quantum Computing Meets Machine Learning - A Maths/TCS Perspective" in the University of Warwick Computer Science Colloquium.
2023/02/06: I presented a poster on "Out-of-distribution generalization for learning quantum dynamics and dynamical simulation" at QIP 2023.
2022/12/16: I was awarded a doctoral thesis award by the Freunde der TUM e.V.
2022/12/08: I posted my work "Learning Quantum Processes and Hamiltonians via the Pauli Transfer Matrix" on the arXiv.
2022/10/21: I gave a talk on "Out-of-distribution generalization for learning quantum dynamics and dynamical simulation" at SQuInT 2022.
2022/10/01: I started my new position as a postdoctoral visiting research fellow at Caltech.
2022/09/18: Our work Out-of-distribution generalization for learning quantum dynamics was accepted for an Extended Talk at QTML 2022!
2022/08/22: Our work "Generalization in quantum machine learning from few training data" was published in Nature Communications.
2022/08/02: I defended my doctoral dissertation (online) at TU Munich summa cum laude.
2022/07/15: I gave a talk on "Generalization guarantees for variational quantum machine learning" at TQC 2022.
2022/07/19: Our work "Quantum and classical dynamical semigroups of superchannels and semicausal channels" was published in the Journal of Mathematical Physics.
2022/06/15: I gave a talk on "Out-of-distribution generalization for learning quantum dynamics" at CQT Singapore.
2022/04/01: I started my new position as a postdoctoral researcher at FU Berlin.