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Abstract:
Quantum error correction remains the most promising path toward realizing promising applications at scale. Currently, error-corrected quantum computers are expected to use the surface code, which is considered the most promising error correction as its implementation details are all but resolved. Unfortunately, the surface code is not incredibly scalable: each logical qubit is expected to require >500 physical qubits. Thus, applications will require millions of physical qubits to achieve any meaningful quantum advantage, and designing systems at this scale presents a significant engineering hurdle that may take decades to overcome. Ideally, we would like to achieve unquestionable quantum advantage in the near-term (next decade or so), which will require reducing the resources of error correction. To this end, Quantum LDPC codes have emerged as an alternative to the surface code, and many of these codes are orders of magnitude more efficient than the surface code. In this talk, I will present a recently-published paper written in collaboration with researchers at IBM tackling implementation challenges for QLDPC codes. I will also discuss my ongoing research on designing error-corrected quantum systems that leverage both surface codes and QLDPC codes to execute programs.
Bio:
Suhas Vittal is a 2nd year PhD student at Georgia Tech advised by Moin Qureshi. His research has appeared at top computer architecture venues such as ISCA, MICRO, and ASPLOS. Currently, his interests are in architecting error-corrected quantum systems and hardware memory compression.