Quantum Readout Error Mitigation By Stochastic Matrix Inversion
A method of mitigating quantum readout errors by stochastic matrix inversion includes performing a plurality of quantum measurements on a plurality of qubits having predetermined plurality of states to obtain a plurality of measurement outputs; selecting a model for a matrix linking the predetermined plurality of states to the plurality of measurement outputs, the model having a plurality of model parameters, wherein a number of the plurality of model parameters grows less than exponentially with a number of the plurality of qubits; training the model parameters to minimize a loss function that compares predictions of the model with the matrix; computing an inverse of the model based on the trained model parameters; and providing the computed inverse of the model to a noise prone quantum readout of the plurality of qubits to obtain a substantially noise free quantum readout.
Claim CLM-00001. 1. A method of mitigating quantum readout errors by stochastic matrix inversion, comprising:
performing a plurality of quantum measurements on a plurality of qubits having predetermined plurality of states to obtain a plurality of measurement outputs; selecting a model for a matrix linking the predetermined plurality of states to the plurality of measurement outputs, the model having a plurality of model parameters, wherein a number of the plurality of model parameters grows less than exponentially with a number of the plurality of qubits; training the plurality of model parameters to minimize a loss function that compares predictions of the model with the matrix; computing an inverse of the model representing an inverse of the matrix based on the trained model parameters; and providing the computed inverse of the model to a noise prone quantum readout of the plurality of qubits to obtain a substantially noise free quantum readout.
Claim CLM-00015. 15. A computer readable medium on which is stored non-transitory computer-executable code, which when executed by a classical computer causes a quantum computer to:
perform a plurality of quantum measurements on plurality of qubits having predetermined plurality of states to obtain a plurality of measurement outputs; select a model for a matrix linking the predetermined plurality of states to the plurality of measurement outputs, the model having a plurality of model parameters, wherein a number of the plurality of model parameters grows less than exponentially with a number of the plurality of states; train the plurality of model parameters to minimize a loss function that compares predictions of the model with the matrix; compute an inverse of the model representing an inverse of the matrix based on the trained model parameters; and apply the computed inverse of the model to a noise prone quantum readout of the plurality of qubits of the quantum computer to obtain a substantially noise free quantum readout from the quantum computer.
Claim CLM-00025. 25. A classical computer configured to execute a non-transitory computer-executable code, the code when executed by the classical computer causes a quantum computer to:
perform a plurality of quantum measurements on plurality of qubits having predetermined plurality of states to obtain a plurality of measurement outputs; select a model for a matrix linking the predetermined plurality of states to the plurality of measurement outputs, the model having a plurality of model parameters, wherein a number of the plurality of model parameters grows less than exponentially with a number of the plurality of states; train the plurality of model parameters to minimize a loss function that compares predictions of the model with the matrix; compute an inverse of the model representing an inverse of the matrix based on the trained model parameters; and apply the computed inverse of the model to a noise prone quantum readout of the plurality of qubits of the quantum computer to obtain a substantially noise free quantum readout from the quantum computer.
