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BEGIN:VEVENT
SUMMARY:QSE Seminar - Tongyang Li
DTSTART:20250703T120000
DTEND:20250703T133000
DTSTAMP:20260313T054347Z
UID:7d0bac250edf6a5a60b705187dd55808bbce80f3f31ea432d6f17cec
CATEGORIES:Conferences - Seminars
DESCRIPTION:Tongyang Li\nPlease join us for the QSE Center Quantum Semi
 nar with Tongyang Li from the Center on Frontiers of Computing Studies\
 , Peking University\, who will speak Thursday July 3rd on "Quantum singul
 ar value transformation without block encodings: Near-optimal complexity w
 ith minimal ancilla". \nLocation: BS 270\n\nPizzas will be available bef
 ore the seminar at 12:00. All PhDs\, postdocs\, students\, and PIs are wel
 come to join us.\n\nTITLE: "Quantum singular value transformation without 
 block encodings: Near-optimal complexity with minimal ancilla"\n\n​​
 ​​​​​ABSTRACT:\nQuantum singular value transformation (QSVT) is 
 a unifying framework that encapsulates most known quantum algorithms. Howe
 ver\, existing implementations rely on block encoding\, incurring an intri
 nsic O(log L) ancilla overhead when there are L terms. In this talk\, I wi
 ll introduce some methods for implementing QSVT without block encodings\, 
 based on our recent work [arXiv:2504.02385]. We propose algorithms that ac
 hieve near-optimal complexity using only a single ancilla qubit. One appro
 ach utilizes Trotter and Richardson extrapolation. Furthermore\, we propos
 e randomized QSVT algorithms for cases where only sampling access to the H
 amiltonian terms is available. We also establish a fundamental lower bound
  of Ω(d^2) for any randomized method implementing polynomial transformati
 ons within this model.\n\nBIO:\nTongyang Li is currently an assistant pr
 ofessor at the Center on Frontiers of Computing Studies\, Peking Universit
 y. Previously he was a postdoctoral associate at the Center for Theoretica
 l Physics\, Massachusetts Institute of Technology during 2020-2021. He rec
 eived Ph.D. degree from the Department of Computer Science\, University of
  Maryland in 2020. His research investigates interdisciplinary subjects am
 ong quantum computing\, machine learning\, and theoretical computer scienc
 e\, with the focus on designing quantum algorithms for optimization and ma
 chine learning. He is also interested in performing quantum algorithms on 
 current noisy\, intermediate-scale quantum devices (NISQ)\, as well as app
 lying AI for better quantum algorithm design.\n 
LOCATION:BS 270 https://plan.epfl.ch/?room==BS%20270
STATUS:CONFIRMED
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