Microsoft Technology Licensing, LLC

Marcus Palmer Da Silva

Nicolas Guillaume Delfosse

Michael Edward Beverland

Christopher Anand Pattison

Adam Edward Paetznick

Mohamed Ayman El Mandouh

A method of probabilistically canceling noise in a measurement-based quantum device includes obtaining a sequence of ideal measurements included within a quantum algorithm and selecting a sequence of noisy measurements for emulating the sequence of ideal measurements. Each of the noisy measurements in the selected sequence approximates a corresponding one of the ideal measurements and is adjusted by a quantum correction, where the noisy measurements are selected according to a carefully chosen distribution to cancel known features of noise in those same noisy measurements in the sequence.

Probabilistic error cancellation for measurement-based quantum computation

A quantum computing system computes soft information quantifying an effect of soft noise on multiple rounds of a syndrome measurement that is output by a quantum measurement circuit. The soft noise arises due to imperfections in a readout device that introduce variability in repeated measurements of ancilla qubits and is distinct from quantum noise arising from bit-flips in data qubits that are indirectly measured by the ancilla qubits. The quantum computing system applying decoding logic to identify fault locations within the quantum measurement circuit based on the computed soft information.

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Marcus Palmer Da Silva