Trapped-ion quantum computing: Progress and challenges

By C. Bruzewicz, J. Chiaverini, R. McConnell, J. Sage. Applied Physics Reviews, 2019

1,431 citations recorded by the source corpus.

Trapped ions are among the most promising systems for practical quantum computing (QC). The basic requirements for universal QC have all been demonstrated with ions, and quantum algorithms using few-ion-qubit systems have been implemented. We review the state of the field, covering the basics of how trapped ions are used for QC and their strengths and limitations as qubits. In addition, we discuss what is being done, and what may be required, to increase the scale of trapped ion quantum computers while mitigating decoherence and control errors. Finally, we explore the outlook for trapped-ion QC. In particular, we discuss near-term applications, considerations impacting the design of future systems of trapped ions, and experiments and demonstrations that may further inform these considerations.Trapped ions are among the most promising systems for practical quantum computing (QC). The basic requirements for universal QC have all been demonstrated with ions, and quantum algorithms using few-ion-qubit systems have been implemented. We review the state of the field, covering the basics of how trapped ions are used for QC and their strengths and limitations as qubits. In addition, we discuss what is being done, and what may be required, to increase the scale of trapped ion quantum computers while mitigating decoherence and control errors. Finally, we explore the outlook for trapped-ion QC. In particular, we discuss near-term applications, considerations impacting the design of future systems of trapped ions, and experiments and demonstrations that may further inform these considerations.

Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics

View Paper: https://www.semanticscholar.org/paper/eff6546819d25df0bccdc89f02554a43a4f1c464

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Citations in the corpus

Quantum simulation and computing with Rydberg-interacting qubits (2020, background): “999 (ions 16–18 )].”
Fusion-based quantum computation (2021, methodology): “In a matter-based system such as ion traps [20] or superconducting qubits [21], a projective measurement can be performed using a multi-qubit entangling gate followed by single qubit measurements [22].”
OpenQASM 3: A Broader and Deeper Quantum Assembly Language (2021, background): “This system model describes many quantum technologies such as ion traps, quantum dots, and neutral atoms [21, 72, 81].”
A Race-Track Trapped-Ion Quantum Processor (2023, background): “Several technology platforms are viable candidates for large-scale quantum computation, including trapped ions [1], neutral atoms [2], and superconducting circuits [3].”
Superconducting nanowire single-photon detectors for quantum information (2020, background): “[54] Bruzewicz C D, Chiaverini J, McConnell R & Sage J M.”
Entanglement certification from theory to experiment (2018, methodology): “Ion trap platforms have been designed primarily for the purpose of fault-tolerant quantum computation [241, 242] and quantum simulation [243].”
Fault-tolerant quantum error correction for Steane’s seven-qubit color code with few or no extra qubits (2018, background): “In an ion trap quantum computing experiment [11], gates can be applied between arbitrary qubits within the same trap; and with multiple traps, qubits can be moved between them.”
Materials challenges and opportunities for quantum computing hardware (2021, methodology): “Atomswith twoelectronsinthevalenceshell, whose singly ionized state thus has a single valence electron, are commonly used for QIP; these include isotopes of Be, Mg, Ca, Sr, Ba, and Yb, among others [see ( 282 ) for a discussion of possible qubit encodings within these ions].”