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, W. D. Oliver

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

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.

Original languageEnglish
Article number011005
JournalPhysical Review X
Volume12
Issue number1
DOIs
StatePublished - 1 Mar 2022
Externally publishedYes

ASJC Scopus subject areas

  • General Physics and Astronomy

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