Deep Neural Network Discrimination of Multiplexed Superconducting Qubit States

Abstract

Demonstrating the quantum computational advantage will require high-fidelity control and readout of multi-qubit systems. As system size increases, multiplexed qubit readout becomes a practical necessity to limit the growth of resource overhead. Many contemporary qubit-state discriminators presume single-qubit operating conditions or require considerable computational effort, limiting their potential extensibility. Here, we present multi-qubit readout using neural networks as state discriminators. We compare our approach to contemporary methods employed on a quantum device with five superconducting qubits and frequency-multiplexed readout. We find that fully-connected feedforward neural networks increase the qubit-state-assignment fidelity for our system. Relative to contemporary discriminators, the assignment error rate is reduced by up to 25 % due to the compensation of system-dependent nonidealities such as readout crosstalk which is reduced by up to one order of magnitude. Our work demonstrates a potentially extensible building block for high-fidelity readout relevant to both near-term devices and future fault-tolerant systems.

Quantum-tailored machine-learning characterization of a superconducting qubit

“…Below, we refer to these as the true parameters {Ω R , Γ d , η} of our physical model given by Eqs. (1) to (3). Using only realistic data allows us to transparently extend the machine-learning improvements drawn from the synthetic results to actual experimental settings.…”

“…Machine learning (ML) has recently been applied to solve problems in numerous areas of physics, including quantum-information science [1,2]. For example, ML models have been used to tackle quantumcomputing tasks including qubit readout [3][4][5], quantum control [6,7] and quantum state tomography [8][9][10] among others. These "black-box" models enjoy wide applicability to different problems, as their structure is agnostic to the physical processes involved in the targeted task.…”

Mitigation of Crosstalk Errors in a Quantum Measurement and Its Applications

“…It holds that for separable states σ sep , the lower and upper bounds are given by, see Eq. ( 30), B L = 0.1250 and B U = 0.3750 (20) where the lower bound detects |φ + and the upper one |ψ − , i.e., tr…”

“…It turns out that crosstalk errors also exist in measurement readout [16,20,21]. It is clear that quantum error-correcting codes that ultimately fix all types of errors appearing in a circuit do not work for measurement errors.…”