BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Memento EPFL// BEGIN:VEVENT SUMMARY:QSE Quantum Seminar: Mini algorithms-fest - John Martyn and Jonath an Lu DTSTART:20251113T120000 DTEND:20251113T140000 DTSTAMP:20260416T080624Z UID:0ad10b98b2af250372a430412134f6951ad6533abe8b97696f6c562a CATEGORIES:Conferences - Seminars DESCRIPTION:John Martyn Jonathan Lu\nPlease join us for the QSE Center  Quantum Seminar with John Martyn from Harvard University & Pacific Nor thwest National Lab (PNNL) who will give the talk "A Little Incoherence Goes a Long Way: Enhancing Quantum and Classical Algorithms with Randomiza tion" and Jonathan Lu from MIT who will give the talk "Hamiltonian Decod ed Quantum Interferometry" on Thursday November 13 from 12:00pm to 2:00pm \nLocation: BS 160\n\nPizzas will be available at 12:00pm. The first talk will start at 12:10pm. All PhDs\, postdocs\, students\, group leaders\, a nd PIs are welcome to join us.\n\nABSTRACT:\n1. "A Little Incoherence Goe s a Long Way: Enhancing Quantum and Classical Algorithms with Randomizatio n" - John Martyn\nIn studying quantum systems\, either with quantum algo rithms or classical methods\, we typically focus on coherent unitary dyna mics. Decoherence arising from randomness or environmental noise is often viewed as detrimental\, and sought to be suppressed. In this talk\, I wil l demonstrate the opposite: incoherence\, in small doses\, is beneficial  to both quantum and classical algorithms. I will illustrate this stat ement in two contexts. First\, in quantum algorithms based on quantum sign al processing\, I will show how using a randomized channel\, instead of th e standard deterministic one\, reduces costs (e.g.\, gate count) by 50%. Second\, in the context of neural-network quantum states\, I will prove how using a variational mixed state representation\, instead of a pure st ate\, provides more accurate estimates of ground state observables. In ag gregate\, these results reveal the surprising utility of incoherence in qu antum information\, and suggest wider applications in algorithm developme nt. \n\n2. "Hamiltonian Decoded Quantum Interferometry" - Jonathan Lu\nWe introduce Hamiltonian Decoded Quantum Interferometry (HDQI)\, a quantum a lgorithm that utilizes coherent Bell measurements and the symplectic repre sentation of the Pauli group to reduce Gibbs sampling and Hamiltonian opti mization to classical decoding. For a degree-d polynomial P and Hamilto nian H\, HDQI prepares a density matrix proportional to P^2(H) by solvi ng a combination of two tasks: decoding weight-d errors on a classical c ode defined by H\, and preparing a pilot state that encodes the anti-comm utation structure of H.     Choosing P(x) to approximate exponentia ls yields Gibbs states\; other choices prepare approximate ground states\ , microcanonical ensembles\, and other spectral filters.\nFor local Hamilt onians\, the corresponding decoding problem is that of LDPC codes. Prepari ng the pilot state is always efficient for commuting Hamiltonians\, but hi ghly non-trivial for non-commuting Hamiltonians. Nevertheless\, we prove t hat this state admits an efficient matrix product state representation for Hamiltonians whose anti-commutation graph decomposes into connected compo nents of logarithmic size. We show that HDQI efficiently prepares Gibbs st ates at arbitrary temperatures for a class of physically motivated commuti ng Hamiltonians—including the toric code and Haah's cubic code—but we also develop a matching efficient classical algorithm for this task. For a non-commuting semiclassical spin glass and commuting stabilizer Hamiltoni ans with quantum defects\, HDQI prepares Gibbs states up to a constant inv erse-temperature threshold using polynomial quantum resources and quasi-po lynomial classical pre-processing. These results position HDQI as a versat ile algorithmic primitive\, and as the first extension of Regev's reductio n to non-abelian groups.\n\nBIOS:\nJohn Martyn is a Quantum Initiative Fel low at Harvard University\, and a Staff Scientist of Pacific Northwest Na tional Laboratory. In his research\, he explores the theoretical side of quantum information\, with a focus on developing quantum and classical alg orithms for simulating physics and solving hard computational problems. H e recently received his PhD in physics from MIT\, advised by Isaac Chuan g\, during which he spent time interning at IBM Quantum and Google X. In t he beforetimes\, he received a BS in physics from the University of Maryla nd\, and worked as a student researcher at Caltech.\nJonathan Lu is a Ph.D . student in Applied Mathematics at MIT co-advised by Peter Shor and Misha Lukin. He works on algorithmic aspects of quantum coding theory\, especia lly in connection to quantum algorithms\, complexity\, and cryptography. R ecent work includes the use of error correction to devise new quantum phys ics algorithms\, and rigorous analyses of the average-case complexity of d ecoding quantum codes. LOCATION:BS 160 https://plan.epfl.ch/?room==BS%20160 STATUS:CONFIRMED END:VEVENT END:VCALENDAR