BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Maciej Koch-J8anusz (University of Zurich) DTSTART:20210222T170000Z DTEND:20210222T180000Z DTSTAMP:20260423T003247Z UID:MPML/38 DESCRIPTION:Title: St atistical physics through the lens of real-space mutual information\nb y Maciej Koch-J8anusz (University of Zurich) as part of Mathematics\, Phys ics and Machine Learning (IST\, Lisbon)\n\n\nAbstract\nIdentifying the rel evant coarse-grained degrees of freedom in a complex physical system is a key stage in developing effective theories. The renormalization group (RG) provides a framework for this task\, but its practical execution in unfam iliar systems is fraught with ad hoc choices. Machine learning approaches\ , on the other hand\, though promising\, often lack formal interpretabilit y: it is unclear what relation\, if any\, the architecture- and training-d ependent learned "relevant" features bear to standard objects of physical theory.\n\nI will present recent results addressing both issues. We develo p a fast algorithm\, the RSMI-NE\, employing state-of-art results in machi ne-learning-based estimation of information-theoretic quantities to constr uct the optimal coarse-graining. We use it to develop a new approach to id entifying the most relevant field theory operators describing a statistica l system\, which we validate on the example of interacting dimer model. I will also discuss formal results underlying the method: we establish equiv alence between the information-theoretic notion of relevance defined in th e Information Bottleneck (IB) formalism of compression theory\, and the fi eld-theoretic relevance of the RG. We show analytically that for statistic al physical systems the "relevant" degrees of freedom found using IB compr ession indeed correspond to operators with the lowest scaling dimensions\, providing a dictionary connecting two distinct theoretical toolboxes.\n LOCATION:https://researchseminars.org/talk/MPML/38/ END:VEVENT END:VCALENDAR