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DTSTART:20240310T070000
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DTSTART:20231105T060000
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DTSTART;TZID=America/Toronto:20240320T120000
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URL:https://uwaterloo.ca/institute-for-quantum-computing/events/iqc-student
 -seminar-featuring-sarah-li-1
LOCATION:QNC - Quantum Nano Centre 200 University Avenue West Room QNC 1201
  Waterloo ON N2L 3G1 Canada
SUMMARY:IQC Student Seminar Featuring Sarah Li
CLASS:PUBLIC
DESCRIPTION:IMPROVING THE FIDELITY OF CNOT CIRCUITS ON NISQ HARDWARE\n\nQua
 ntum-Nano Centre\, 200 University Ave West\, Room QNC 1201 Waterloo\,\nON 
 CA N2L 3G1\n\nWe introduce an improved CNOT synthesis algorithm that consi
 ders\nnearest-neighbour interactions and CNOT gate error rates in noisy\ni
 ntermediate-scale quantum (NISQ) hardware. Our contribution is\ntwofold. F
 irst\, we define a \\Cost function by approximating the\naverage gate fide
 lity Favg. According to the simulation results\, \\Cost\nfits the error pr
 obability of a noisy CNOT circuit\, Prob = 1 - Favg\,\nmuch tighter than t
 he commonly used cost functions. On IBM's fake\nNairobi backend\, it fits 
 Prob with an error at most 10^(-3). On other\nbackends\, it fits Prob with
  an error at most 10^(-1). \\Cost accounts\nfor the machine calibration da
 ta\, and thus accurately quantifies the\ndynamic error characteristics of 
 a NISQ-executable CNOT circuit.\nMoreover\, it circumvents the computation
  complexity of calculating\nFavg and shows remarkable scalability. \n\nSe
 cond\, we propose an architecture-aware CNOT synthesis algorithm\,\nNAPerm
 RowCol\, by adapting the leading Steiner-tree-based synthesis\nalgorithms.
  A weighted edge is used to encode a CNOT gate error rate\nand \\Cost-inst
 ructed heuristics are applied to each reduction step.\nCompared to IBM's Q
 iskit compiler\, it reduces \\Cost by a factor of 2\non average (and up to
  a factor of 8.8). It lowers the synthesized CNOT\ncount by a factor of 13
  on average (up to a factor of 162). Compared\nwith algorithms that are no
 ise-agnostic\, it is effective and scalable\nto improve the fidelity of CN
 OT circuits. Depending on the benchmark\ncircuit and the IBM backend selec
 ted\, it lowers the synthesized CNOT\ncount up to 56.95% compared to ROWCO
 L and up to 21.62% compared to\nPermRowCol. It reduces the synthesis \\Cos
 t up to 25.71% compared to\nROWCOL and up to 9.12% compared to PermRowCol.
  NAPermRowCol improves\nthe fidelity and execution time of a synthesized C
 NOT circuit across\nvaried NISQ hardware. It does not use ancillary qubits
  and is not\nrestricted to certain initial qubit maps. It could be general
 ized to\nroute a more complicated quantum circuit\, and eventually boost t
 he\noverall efficiency and accuracy of quantum computing on NISQ\ndevices.
  \n\nJoint-work with: Dohun Kim\, Minyoung Kim\, and Michele Mosca
DTSTAMP:20260419T135629Z
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