US 12,346,772 B2
Probabilistic error cancellation for measurement-based quantum computation
Adam Edward Paetznick, Bellevue, WA (US); Marcus Palmer da Silva, Redmond, WA (US); and Mohamed Ayman El Mandouh, Mississauga (CA)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed on Dec. 22, 2021, as Appl. No. 17/559,358.
Prior Publication US 2023/0196172 A1, Jun. 22, 2023
Int. Cl. G06N 10/70 (2022.01)
CPC G06N 10/70 (2022.01) 17 Claims
OG exemplary drawing
 
1. A method for removing noise from an expectation value of a quantum algorithm implemented by a noisy quantum circuit, the method comprising:
receiving, at a processor, a sequence of ideal quantum operations included within the quantum algorithm;
implementing each ideal quantum operation in the sequence of ideal quantum operations by a series of processing operations including:
selecting a noisy measurement instrument to emulate an operation corresponding to the ideal quantum operation;
observing a noisy outcome of a measurement operation performed using the selected noisy measurement instrument in the noisy quantum circuit;
sampling from a probability distribution to obtain an adjusted outcome for the measurement operation, the probability distribution representing a spread of possible outcomes given the observed noisy outcome and the selected noisy measurement instrument; and
determining and storing bias correction weights for the measurement operation, the bias correction weights being based on the observed noisy outcome, the selected noisy measurement instrument, and the sampled adjusted outcome; and
after each iteration of multiple iterations of the quantum algorithm in the noisy quantum circuit, removing noise from an output of the quantum algorithm by re-scaling the output by a scalar computed based on the bias correction weights.