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Matthias Christandl

Matthias Christandl

Professor

Medlem af:

    About me

    I am Professor in the Department of Mathematical Sciences at the University of Copenhagen and co-PI of the research centre QMATH, the Centre for the Mathematics of Quantum Theory.

    Previously, I was Assistant Professor at ETH Zurich (2010–2014) and at the University of Munich (2008–2010), and Postdoctoral Fellow at the University of Cambridge (2005–2008). I hold a PhD from the University of Cambridge (2006) and a Diploma from ETH Zurich (2002). 

    In 2013, I was awarded an ERC Starting Grant and in 2018 an ERC Consolidator Grant. In 2016 I was elected to the Royal Danish Academy of Sciences and Letters. In 2018, I was on sabbatical at MIT for one semester while serving as programme committee chair for QIP 2019, the premier conference in the field of quantum information processing.

     

    My research 

    My research aims to understand the way quantum mechanics impacts on information processing. To this end, I have made contributions of an algorithmic, cryptographic, information-theoretical and foundational nature, drawing on techniques and concepts from mathematics, computer science, physics and engineering. 

    Excited by recent experimental breakthroughs in the building of quantum devices, I continue this theoretical line of research with a focus on the near-term facilitation and long-term benefits of quantum computing.

    You find all my publications (including preprints) here and all recent presentations here.

     

    Key results

     

    I am hiring!

    If you are interested in working with me as a PhD student or postdoc, please send me an email. Positions are available within the European Project Quantalgo - Quantum Algorithms and Applications, my ERC Grant on Quantum Information, or the VILLUM Centre Grant on the Mathematics of Quantum Theory.

     

    Further research on quantum mechanics, tensors, and complexity

    The quantum states of several particles can be described mathematically with the help of tensors (higher-dimensional arrays of numbers, generalising matrices). Through this connection, I have obtained fundamental results in the theory of tensors, as well as applications to condensed matter physics (via tensor networks) and algebraic complexity theory. Algebraic complexity is a topic in classical computer science that includes the famous problem of deciding whether matrices can be multiplied in quadratic time. My work here may be regarded as quantum-inspired classical algorithmic research. 

     

    Some recent results

    • Reducing the bond dimension in tensor networks (preprint)
    • Universal obstructions to tensor transformations (FOCS 2018)
    • Efficient algorithm for multiplicities occurring in approach to solving P versus NP (STOC 2012), implemented here.

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