• Open Access

Demonstration of Density Matrix Exponentiation Using a Superconducting Quantum Processor

M. Kjaergaard, M. E. Schwartz, A. Greene, G. O. Samach, A. Bengtsson, M. O’Keeffe, C. M. McNally, J. Braumüller, D. K. Kim, P. Krantz, M. Marvian, A. Melville, B. M. Niedzielski, Y. Sung, R. Winik, J. Yoder, D. Rosenberg, K. Obenland, S. Lloyd, T. P. Orlando, I. Marvian, S. Gustavsson, and W. D. Oliver
Phys. Rev. X 12, 011005 – Published 7 January 2022

Abstract

Density matrix exponentiation (DME) is a general technique for using a quantum state ρ to enact the quantum operation eiρθ on a target system. It was first proposed in the context of quantum machine learning, but has since been shown to have broad applications in quantum metrology and computation. No experimental demonstration of DME has been performed thus far due to its demanding circuit depths and the need to efficiently generate multiple identical copies of ρ during the finite lifetime of the target system. In this work, we describe the first demonstration of the DME algorithm, which we accomplish using a superconducting quantum processor. Our demonstration relies on a 99.7% fidelity controlled-phase gate implemented using two tunable superconducting transmon qubits. We achieve a fidelity surpassing 90% at circuit depths exceeding 70 when comparing the output of the circuit executed on our quantum processor to a simulation assuming perfect operations and measurements.

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  • Received 1 March 2021
  • Revised 1 October 2021
  • Accepted 4 November 2021

DOI:https://doi.org/10.1103/PhysRevX.12.011005

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

Published by the American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & Technology

Authors & Affiliations

M. Kjaergaard1,*, M. E. Schwartz2,†, A. Greene1,3, G. O. Samach1,2,3, A. Bengtsson1,4, M. O’Keeffe2, C. M. McNally1,3, J. Braumüller1, D. K. Kim2, P. Krantz1,‡, M. Marvian1,5, A. Melville2, B. M. Niedzielski2, Y. Sung1,3, R. Winik1, J. Yoder2, D. Rosenberg2, K. Obenland2, S. Lloyd1,5, T. P. Orlando1,3, I. Marvian6, S. Gustavsson1, and W. D. Oliver1,2,7,3

  • 1Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
  • 2MIT Lincoln Laboratory, Lexington, Massachusetts 02421, USA
  • 3Department of Electrical Engineering & Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
  • 4Microtechnology and Nanoscience, Chalmers University of Technology, Göteborg 412 96, Sweden
  • 5Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
  • 6Departments of Physics & Electrical and Computer Engineering, Duke University, Durham, North Carolina 27708, USA
  • 7Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA

  • *mortenk@mit.edu
  • These authors contributed equally to this work.
  • Present address: Microtechnology and Nanoscience, Chalmers University of Technology, Göteborg, Sweden.

Popular Summary

Quantum computers hold the potential to outperform classical supercomputers at certain tasks. To implement algorithms on a quantum computer, programmers use conventional computers and hardware to create a set of classical control signals that implement a desired quantum algorithm. However, feeding the quantum information forward requires an inefficient conversion: extraction of quantum information, conversion to classical control signals, and reinjection of those signals into the system to implement quantum operations. Here, we demonstrate a more natively quantum strategy to programming quantum computers.

Our approach uses the density matrix exponentiation (DME) protocol, a general technique for using a quantum state to enact a quantum operation. It can be thought of as a subroutine with which programmers can turn multiple copies of a quantum state into instructions for next steps in a quantum algorithm.

We implement DME using two qubits in a superconducting quantum processor. Our implementation relies on a high-fidelity two-qubit gate and a novel technique called quantum measurement emulation to approximately reset a known quantum state. These developments enable us to demonstrate the DME protocol for the first time on a small-scale quantum processor and benchmark its performance.

While DME was originally proposed in the context of a specific quantum machine-learning algorithm, it may also represent a fundamentally different approach to quantum programming. It allows the possibility of encoding quantum algorithms directly into quantum states and executing those algorithms on other quantum states, enabling a new class of efficient quantum algorithms.

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Vol. 12, Iss. 1 — January - March 2022

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