Qiskit Quantum Seminar

Stay up to date with the latest academic and research topics in the quantum community by joining our live discussions every Friday at 12PM EDT. Tune in to gain insights from experts and engage with a community of quantum enthusiasts!

Curated by: Qiskit (180 videos)


Currently Playing: Neural Error Mitigation of Near-Term Quantum Simulations | Seminar Series w/ Elizabeth Bennewitz

Neural Error Mitigation of Near-Term Quantum Simulations Seminar Series with Elizabeth Bennewitz Your formal invite to weekly Qiskit videos ► https://ibm.biz/q-subscribe Speaker: Elizabeth Bennewitz Host: Zlatko Minev, PhD. Abstract: Near-term quantum computers provide a promising platform for finding ground states of quantum systems, which is an essential task in physics, chemistry, and materials science. Near-term approaches, however, are constrained by the effects of noise as well as the limited resources of near-term quantum hardware. We introduce neural error mitigation, which uses neural networks to improve estimates of ground states and ground-state observables obtained using near-term quantum simulations. To demonstrate our method’s broad applicability, we employ neural error mitigation to find the ground states of the H2 and LiH molecular Hamiltonians, as well as the lattice Schwinger model, prepared via the variational quantum eigensolver (VQE). Our results show that neural error mitigation improves numerical and experimental VQE computations to yield low energy errors, high fidelities, and accurate estimations of more-complex observables like order parameters and entanglement entropy, without requiring additional quantum resources. Furthermore, neural error mitigation is agnostic with respect to the quantum state preparation algorithm used, the quantum hardware it is implemented on, and the particular noise channel affecting the experiment, contributing to its versatility as a tool for quantum simulation. Bio: Elizabeth Bennewitz is an Advisor at 1QBit's Hardware Innovation Lab and a physics PhD student at the University of Maryland advised by Alexey Gorshkov. Her research focuses on using classical and quantum computational tools to study large, interacting quantum systems. Her work includes applying machine learning techniques to the study of quantum systems as well as designing protocols to study quantum field theory on quantum devices. Elizabeth is an incoming fellow for the Department of Energy Computational Science Graduate Fellowship and was a finalist for the 2022 Hertz Fellowship. Prior to pursuing her PhD, she received her Master’s degree in physics in 2020 from the Perimeter Institute through the Perimeter Scholars International (PSI) program, and in 2019 graduated with a BA in physics from Bowdoin College. -- The Qiskit Seminar Series is a deep dive into various academic and research topics within the quantum community. It will feature community members and leaders every Friday, 12 PM EDT.


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