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DTSTAMP:20230124T171527Z
LOCATION:C140-142
DTSTART;TZID=America/Chicago:20221113T161000
DTEND;TZID=America/Chicago:20221113T163000
UID:submissions.supercomputing.org_SC22_sess423_ws_qcs123@linklings.com
SUMMARY:Stochastic Approach for Simulating Quantum Noise Using Tensor Netw
 orks
DESCRIPTION:Workshop\n\nStochastic Approach for Simulating Quantum Noise U
 sing Tensor Networks\n\nBerquist, Lykov, Liu, Alexeev\n\nNoisy quantum sim
 ulation is challenging since one has to take into account the stochastic n
 ature of the process. The dominating method for it is the density matrix a
 pproach. In this paper, we evaluate conditions for which this method is in
 ferior to a substantially simpler way of simulation. Our approach uses sto
 chastic ensembles of quantum circuits, where random Kraus operators are ap
 plied to original  quantum gates to represent random errors for modeling q
 uantum channels. We show that our stochastic simulation error is relativel
 y low, even for large numbers of qubits. We implemented this approach as a
  part of the QTensor package. While usual density matrix simulations on av
 erage hardware are challenging at n>15, we show that for up to n<30, it is
  possible to run embarrassingly parallel simulations with <1% error. By us
 ing the tensor slicing technique, we can simulate up to 100 qubit QAOA cir
 cuits with high depth using supercomputers.\n\nSession Format: Recorded\n\
 nTag: Quantum Computing\n\nRegistration Category: Workshop Reg Pass
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