Theory Seminar: Dimensionality reduction of quantum stochastic models for complex systems

Marta Florido, Theory Group MPQ
Theory Seminar at MPQ Herbert-Walther-Hörsaal (G0.25) and Zoom
Wednesday, January 25th, 2022, 11:30 am (MEZ)

Abstract:

Systems displaying complex stochastic behaviors are ubiquitous in nature and society, which means that building models that are capable of making faithful predictions about their future evolution is an essential task. However, this usually involves tracking prohibitively large amounts of information for complex systems, so it is necessary to develop effective tools to cut down on the amount of memory needed. In my talk, I will first present a classical approach to this problem: the so-called ‘ϵ-machines’, which lie at the heart of a branch in complexity science known as computational mechanics [1]. Then, I will proceed to explain how introducing quantum mechanics into the picture can yield significant advantages [2]. Finally, I will go through my master’s thesis project, in which I studied MPS-based methods to further reduce the memory of these quantum stochastic models.

[1]: J. Crutchfield. Nature Phys 8, 17–24 (2012). (link: https://doi.org/10.1038/nphys2190)
[2]: M. Gu, K. Wiesner, E. Rieper, et al. Nat Commun 3, 762 (2012). (link: https://doi.org/10.1038/ncomms1761)