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Events on Wednesday, August 12th, 2020

Physics Meets ML
Discovering new phases of matter with unsupervised and interpretable support vector machines
Time: 11:00 am - 12:00 pm
Place: Please register for this online event:
Speaker: Lode Pollet, LMU Munich
Abstract: I present the Tensorial Kernel Support Vector Machine (TK-SVM) as a tool to automate the classification of complicated phase diagrams for classical systems, which is a complicated task when multiple phases coexist and orders compete, as is frequently the case in frustrated magnetism. The key property is the interpretability of the decision function, from which the physical local order parameter can be deduced irrespective of its rank. Furthermore, we discuss a second intrinsic parameter of TK-SVM, the bias, which can be given a distinct physical meaning and which allows one to make an unsupervised graph analysis of the topology of the phase diagram. We illustrate our tool for the classical XXZ model on the frustrated pyrochlore lattice. Unexpectedly, TK-SVM could also learn local constraints hinting at various types of spin liquids resulting in a complete classification of all types of behavior for this model. TK-SVM was subsequently applied to the Kitaev materials where we found a new type of magnetic order as well as new explicit formula’s for the local constraints of certain spin liquids, proving the usefulness of TK-SVM in going beyond the state of the art.


Phys. Rev. B 99, 060404 (2019)
Phys. Rev. B 99, 104410 (2019)
Phys. Rev. B 100, 174408 (2019)
preprint arXiv:2004.14415 (2020)
Host: Shiu
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Thesis Defense
Role of Stable Eigenmodes in Shear-flow Instability Saturation and Turbulence
Time: 12:00 pm - 2:00 pm
Place: virtual
Speaker: Adrian Fraser, Physics PhD Graduate Student
Abstract: Join Zoom Meeting Meeting ID: 510 013 3208 Passcode: 53706 One tap mobile +13126266799,,5100133208# US (Chicago) +16468769923,,5100133208# US (New York) Dial by your location +1 312 626 6799 US (Chicago) +1 646 876 9923 US (New York) +1 301 715 8592 US (Germantown) +1 253 215 8782 US (Tacoma) +1 346 248 7799 US (Houston) +1 408 638 0968 US (San Jose) +1 669 900 6833 US (San Jose) Meeting ID: 510 013 3208 Find your local number:
Host: Paul Terry, Faculty Advisor
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Thesis Defense
Identifying and Exploiting Structure in Cosmological and String Theoretic Data
Time: 1:00 pm - 2:00 pm
Place: Virtual
Speaker: Alex Cole, Physics PhD Graduate Student
Abstract: Meeting ID: 979 7763 2946 Passcode: email for passcode
Host: Gary Shiu, Faculty Advisor
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Academic Calendar
Masters in Learning Analytics Webinar
Time: 4:00 pm - 4:30 pm
Abstract: Informational session to learn about the program. Join the Masters in Learning Analytics program director to learn more about the 24-month online program and get your questions answered. Simply sign up for this free event on the program's home page. CONTACT: 858-337-5858, URL:
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