Large-scale quantum computers will require error correction in order to reliably perform computations. However, the hardware overhead for error correction remains dauntingly large, with each logical qubit potentially requiring thousands of physical qubits for reliable operation. One promising approach to reducing the overheads of error correction is to tailor quantum error correcting codes to the dominant noise in the qubit hardware.
In this talk, I’ll present recent work on tailoring measurement-based quantum computing for photonic quantum computers. Building a quantum computer out of photons allows one to avoid many sources of error, but introduces a new photonic error known as“fusion failure,” which occurs at a very high rate. Existing schemes for error correction can tolerate a fusion failure rate of 24%, but experimentally feasible fusions fail at least 25% of the time. We introduce new tailored designs for error correction in photonic quantum computers that allows for the correction of a surprisingly high rate of fusion failures; in one of our schemes, we can tolerate a failure rate of over 34%. This surpasses a key barrier in building a photonic quantum computer.
Bio: Jahan Claes received his PhD from the University of Illinois at Urbana Champaign in condensed matter physics. As a graduate student, he was a Feynman Intern at NASA’s Quantum Artificial Intelligence Lab, where he researched methods for characterizing errors in experimental quantum computers, as well as a Quantum Algorithms Intern at QC Ware, where he researched quantum optimization algorithms. Jahan is currently the YQI Postdoctoral Fellow at Yale University, where he researches tailored error correction and error characterization for quantum computers.
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