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Ab-initio two-dimensional digital twin for quantum computer benchmarking

Alice Pagano · CERN

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About

Large-scale numerical simulations of the Hamiltonian dynamics of a Noisy Intermediate Scale Quantum (NISQ) computer - a digital twin - could play a major role in developing efficient and scalable strategies for tuning quantum algorithms for specific hardware. Via a two-dimensional tensor network digital twin of a Rydberg atom quantum computer, we demonstrate the feasibility of such a program. In particular, we quantify the effects of gate crosstalks induced by the van der Waals interaction between Rydberg atoms: according to an 8x8 digital twin simulation based on the current state-of-the-art experimental setups, the initial state of a five-qubit repetition code can be prepared with a high fidelity, a first indicator for a compatibility with fault-tolerant quantum computing. The preparation of a 64-qubit Greenberger-Horne-Zeilinger (GHZ) state with about 700 gates yields a 99.9% fidelity in a closed system while achieving a speedup of 35% via parallelization.

About the speaker Alice Pagano completed her Master's degree in Physics at the University of Padova in 2021, and she is currently pursuing a PhD at the same institution. Her research interests involve quantum machine learning, tensor network methods, and quantum optimal control techniques for quantum devices. She is actively collaborating with the QRydDemo project based in Stuttgart, which aims to develop a 500-qubit Rydberg atom quantum computer within the next few years.

Collaborators Daniel Jaschke (University of Ulm and INFN), Sebastian Weber (University of Stuttgart), Simone Montangero (University of Padova)

The talk

  1. Ab-initio two-dimensional digital twin for quantum computer benchmarking 2023-04-19 · 49 min · CERN's player

Credits and licence

Institution
CERN
Department
QTI Lectures
Speaker
Alice Pagano
Year
2023
Language
English
Subjects
Physics, Computer science
Source
CERN
Licence
CERN, as CERN states it. CERN's terms
Attribution
© CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
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