Abstract
Quantum information processing is steadily progressing from a purely academic discipline towards applications throughout science and industry. Transitioning from lab-based, proof-of-concept experiments to robust, integrated realizations of quantum information processing hardware is an important step in this process. However, the nature of traditional laboratory setups does not offer itself readily to scaling up system sizes or allow for applications outside of laboratory-grade environments. This transition requires overcoming challenges in engineering and integration without sacrificing the state-of-the-art performance of laboratory implementations. Here, we present a 19-inch rack quantum computing demonstrator based on optical qubits in a linear Paul trap to address many of these challenges. We outline the mechanical, optical, and electrical subsystems. Furthermore, we describe the automation and remote access components of the quantum computing stack. We conclude by describing characterization measurements relevant to quantum computing including site-resolved single-qubit interactions, and entangling operations mediated by the Mølmer-Sørensen interaction delivered via two distinct addressing approaches. Using this setup, we produce maximally entangled Greenberger-Horne-Zeilinger states with up to 24 ions without the use of postselection or error mitigation techniques; on par with well-established conventional laboratory setups.
- Received 28 January 2021
- Revised 12 April 2021
- Accepted 7 May 2021
- Corrected 30 June 2021
DOI:https://doi.org/10.1103/PRXQuantum.2.020343
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)
Corrections
30 June 2021
Correction: Incorrect source information appeared in Ref. [20] and has been fixed.
synopsis
synopsisThe Smallest Quantum Computer Yet
Published 17 June 2021
A trapped-ion-based quantum computer that fits in two boxes, each the size of a studio apartment’s shower, can create a fully entangled 24-particle quantum state.
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Popular Summary
Quantum computers are anticipated to produce significant speed-ups relative to even the most powerful classical computers for problems relevant to science and industry. Many prototype implementations of quantum computers already exist, which are beginning to push beyond the computational capacity of classical computers. The next generation of quantum computers will have to be significantly scaled up to truly harness the advantage of the quantum computing paradigm. However, current implementations of quantum computing hardware are mainly laboratory-based, one-of-a-kind setups that do not offer themselves readily to scaling up in size. A significant challenge in the field is to realize this next generation of quantum computers in a scalable fashion while maintaining the performance quality of smaller systems.
Our work’s approach is to develop a heavily integrated hardware solution compatible with industry standards and minimal maintenance requirements. This is achieved in part by modularization and replaceable parts similar to classical server banks. Our implementation is a quantum computing demonstrator based on individual charged atoms stored in an ion trap, manipulated with lasers, housed inside two 19-inch industry racks, as found in data centers throughout the world. The entire setup requires only a single wall-mounted power plug and is otherwise self-contained. We show that this departure from typical laboratory setups does not have to come at the cost of performance by producing a fully entangled, 24-particle quantum state—the largest thus far.
Further upgrading the demonstrator’s hardware and software capabilities will be followed by opening this diverse platform to cloud access for testing quantum algorithms on a medium-scale, hardware-agnostic quantum computing language.
