Deep-Neural-Network Discrimination of Multiplexed Superconducting-Qubit States

Benjamin Lienhard, Antti Vepsäläinen, Luke C.G. Govia, Cole R. Hoffer, Jack Y. Qiu, Diego Ristè, Matthew Ware, David Kim, Roni Winik, Alexander Melville, Bethany Niedzielski, Jonilyn Yoder, Guilhem J. Ribeill, Thomas A. Ohki, Hari K. Krovi, Terry P. Orlando, Simon Gustavsson, and William D. Oliver

Phys. Rev. Applied 17, 014024 – Published 20 January 2022

Abstract

Demonstrating a quantum computational advantage will require high-fidelity control and readout of multiqubit 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 multiqubit 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.

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Received 11 March 2021
Revised 8 September 2021
Accepted 11 November 2021

DOI:https://doi.org/10.1103/PhysRevApplied.17.014024

Physics Subject Headings (PhySH)

Machine learning Measurement-based quantum computing Optoelectronics Quantum control Quantum information with solid state qubits

Superconducting qubits

Artificial neural networks Microwave techniques

Quantum Information, Science & Technology

Authors & Affiliations

Benjamin Lienhard ^1,2,*, Antti Vepsäläinen², Luke C.G. Govia ^3,†, Cole R. Hoffer^1,2, Jack Y. Qiu^1,2, Diego Ristè ³, Matthew Ware ³, David Kim⁴, Roni Winik², Alexander Melville ⁴, Bethany Niedzielski ⁴, Jonilyn Yoder⁴, Guilhem J. Ribeill ³, Thomas A. Ohki³, Hari K. Krovi ³, Terry P. Orlando^1,2, Simon Gustavsson², and William D. Oliver ^1,2,4

¹Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
²Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
³Quantum Engineering and Computing Group, Raytheon BBN Technologies, Cambridge, Massachusetts 02138, USA
⁴MIT Lincoln Laboratory, Lexington, Massachusetts 02421, USA