Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

IEEE National Aerospace and Electronics Conference (NAECON)

Physically Unclonable Characteristics for Trapped Ion Quantum Processors

Karli E. Wallace, Michael K. Roberts, Leleia A. Hsia, Laurence D. Merkle

Published Jul 15, 2024• 0 citations
Publisher

Abstract

At the forefront of quantum technology, trapped ion quantum computing offers unparalleled prospects for computation and data processing. This paper proposes securing trapped ion computing hardware with physically unclonable characteristics (PUCs), leveraging fabrication-induced device variations. We review Sandia's High Optical Access trap and IonQ's Iris trap processors, suggesting potential PUC characteristics for evaluation. We also present our experimental methodology and preliminary results using calibration data (SPAM error, 1Q, and 2Q errors) and results from benchmarking algorithms (Single Qubit State Fidelity and Hadamard Quantum Walks) as characteristics. Our findings indicate that, except for 2Q errors, calibration data characteristics lack promise as PUCs due to low variation. In contrast, benchmarking algorithms, particularly the Single Qubit State Fidelity, the 2-, 3-, and 5-qubit, 1-step Hadamard Walk, and the 5-qubit, 10-step Hadamard Walk show potential as PUC characteristics due to their high variation.

DOI
10.1109/naecon61878.2024.10670676

Related papers

Benchmarking a trapped-ion quantum computer with 30 qubits

Jwo-Sy Chen, Erik Nielsen, Matthew Ebert +8 more

Quantum computers are rapidly becoming more capable, with dramatic increases in both qubit count \cite{kim2023evidence} and quality \cite{moses2023race}. Among different hardware approaches, trapped-ion quantum processors are a leading technology for quantum computing, with established high-fidelity operations and architectures with promising scaling. Here, we demonstrate and thoroughly benchmark the IonQ Forte system: configured as a single-chain 30-qubit trapped-ion quantum computer with all-to-all operations. We assess the performance of our quantum computer operation at the component level via direct randomized benchmarking (DRB) across all 30 choose 2 = 435 gate pairs. We then show the results of application-oriented \cite{IonQ_AQ20_2022}\cite{qedcPeerReviewed} benchmarks and show that the system passes the suite of algorithmic qubit (AQ) benchmarks up to #AQ 29. Finally, we use our component-level benchmarking to build a system-level model to predict the application benchmarking data through direct simulation. While we find that the system-level model correlates with the experiment in predicting application circuit performance, we note quantitative discrepancies indicating significant out-of-model errors, leading to higher predicted performance than what is observed. This highlights that as quantum computers move toward larger and higher-quality devices, characterization becomes more challenging, suggesting future work required to push performance further.

arXiv:2308.05071•Quantum•Nov 7, 2024•103 citations

Benchmarking an 11-qubit quantum computer

Kenneth Wright, Kristin M. Beck, Shantanu Debnath +21 more

Abstract The field of quantum computing has grown from concept to demonstration devices over the past 20 years. Universal quantum computing offers efficiency in approaching problems of scientific and commercial interest, such as factoring large numbers, searching databases, simulating intractable models from quantum physics, and optimizing complex cost functions. Here, we present an 11-qubit fully-connected, programmable quantum computer in a trapped ion system composed of 13 171 Yb + ions. We demonstrate average single-qubit gate fidelities of 99.5 $$\%$$ % , average two-qubit-gate fidelities of 97.5 $$\%$$ % , and SPAM errors of 0.7 $$\%$$ % . To illustrate the capabilities of this universal platform and provide a basis for comparison with similarly-sized devices, we compile the Bernstein-Vazirani and Hidden Shift algorithms into our native gates and execute them on the hardware with average success rates of 78 $$\%$$ % and 35 $$\%$$ % , respectively. These algorithms serve as excellent benchmarks for any type of quantum hardware, and show that our system outperforms all other currently available hardware.

arXiv:1903.08181•Nature Communications•Nov 29, 2019•517 citations

Characterizing and mitigating coherent errors in a trapped ion quantum processor using hidden inverses

Swarnadeep Majumder, Christopher G. Yale, Titus Morris +6 more

Quantum computing testbeds exhibit high-fidelity quantum control over small collections of qubits, enabling performance of precise, repeatable operations followed by measurements. Currently, these noisy intermediate-scale devices can support a sufficient number of sequential operations prior to decoherence such that near term algorithms can be performed with proximate accuracy (like chemical accuracy for quantum chemistry problems). While the results of these algorithms are imperfect, these imperfections can help bootstrap quantum computer testbed development. Demonstrations of these algorithms over the past few years, coupled with the idea that imperfect algorithm performance can be caused by several dominant noise sources in the quantum processor, which can be measured and calibrated during algorithm execution or in post-processing, has led to the use of noise mitigation to improve typical computational results. Conversely, benchmark algorithms coupled with noise mitigation can help diagnose the nature of the noise, whether systematic or purely random. Here, we outline the use of coherent noise mitigation techniques as a characterization tool in trapped-ion testbeds. We perform model-fitting of the noisy data to determine the noise source based on realistic physics focused noise models and demonstrate that systematic noise amplification coupled with error mitigation schemes provides useful data for noise model deduction. Further, in order to connect lower level noise model details with application specific performance of near term algorithms, we experimentally construct the loss landscape of a variational algorithm under various injected noise sources coupled with error mitigation techniques. This type of connection enables application-aware hardware codesign, in which the most important noise sources in specific applications, like quantum chemistry, become foci of improvement in subsequent hardware generations.

arXiv:2205.14225•Quantum•May 15, 2023•6 citations

Hardware requirements for trapped-ion-based verifiable blind quantum computing with a measurement-only client

Janice van Dam, Guus Avis, Tzula B. Propp +4 more

Abstract In blind quantum computing (BQC), a user with a simple client device can perform a quantum computation on a remote quantum server such that the server cannot gain knowledge about the computation. Here, we numerically investigate hardware requirements for verifiable BQC using an ion trap as server and a distant measurement-only client. While the client has no direct access to quantum-computing resources, it can remotely execute quantum programs on the server by measuring photons emitted by the trapped ion. We introduce a numerical model for trapped-ion quantum devices in NetSquid, a discrete-event simulator for quantum networks. Using this, we determine the minimal hardware requirements on a per-parameter basis to perform the verifiable BQC protocol. We benchmark these for a five-qubit linear graph state, with which any single-qubit rotation can be performed, where client and server are separated by 50 km. Current state-of-the-art ion traps satisfy the minimal requirements on a per-parameter basis, but all current imperfections combined make it impossible to perform the blind computation securely over 50 km using existing technology. Using a genetic algorithm, we determine the set of hardware parameters that minimises the total improvements required, finding directions along which to improve hardware to reach our threshold error probability that would enable experimental demonstration. In this way, we lay a path for the near-term experimental progress required to realise the implementation of verifiable BQC over a 50 km distance.

arXiv:2403.02656•Quantum Science and Technology•Aug 13, 2024•10 citations

Visible Photonic Component Development for Trapped-Ion Quantum Computing

Elliot M Lehman, Molly R. Krogstad, Molly P. Andersen +15 more

Trapped-ion quantum computers, leveraging a quantum charge-coupled device (QCCD) architecture, have world-class performance in the field of quantum computing, offering high fidelities and all-to-all connectivity [1]. While systems have advanced over the last decade, much work remains to scale quantum computers to fault-tolerance. Providing scalable light delivery is one key challenge. Current systems utilize engineered bulk- and fiber-optic-based light delivery systems, external to the vacuum chamber, to deliver arrays of beams to ions. However, fundamental optical limitations preclude the use of such systems when scaling beyond thousands of qubits. Integrated photonic-based beam delivery offers a potential solution, with encouraging proof-of-concept demonstrations from the photonics and quantum communities [2]–[5]. Quantinuum and Sandia National Labs have partnered to accelerate the development of integrated photonics for trapped-ion quantum computing applications, working towards photonic components supporting high-fidelity operations. Here, we present development of photonic integrated components designed to deliver laser light to$\text{Ba}^{+}$qubits, utilizing a low-loss, high-confinement, trap-integrable PECVD SiN platform. In order to demonstrate two-qubit gates at 532 nm, we developed low loss, tight bend waveguides, efficient edge couplers, and asymmetric multimode interference (MMI) splitters, along with beam-forming grating out-couplers delivering gaussian beams at the ion plane. For quantum state preparation and measurement (SPAM) applications at$\text{4 9 3 ~ n m}$, we demonstrate fabrication-tolerant splitters and low-crosstalk gratings. Measured component performance shows promise for future trap-integrated demonstrations.

IEEE International Conference on Quantum Computing and Engineering (QCE)•Aug 30, 2025•0 citations

Vacuum and Optical Designs for an Open-access Trapped Ion Quantum Processor

Noah Greenberg

This thesis focuses on the design of a vacuum system for a trapped ion quantum computer that will house an advanced ion chip trap from Sandia National Laboratories, capable of performing high fidelity operations on up to tens of qubits. The thesis will outline the different design considerations, criteria, and serve to document the final design choices, in addition to optical design work that will be used to drive resonant atomic transitions in the qubit of choice, 133Ba+, as well as the qudit, 137Ba+.

•Sep 21, 2020•1 citation
At the forefront of quantum technology, trapped ion quantum computing offers unparalleled prospects for computation and data processing. This paper proposes securing trapped ion computing hardware with physically unclonable characteristics (PUCs), leveraging fabrication-induced device variations. We review Sandia's High Optical Access trap and IonQ's Iris trap processors, suggesting potential PUC characteristics for evaluation. We also present our experimental methodology and preliminary results using calibration data (SPAM error, 1Q, and 2Q errors) and results from benchmarking algorithms (Single Qubit State Fidelity and Hadamard Quantum Walks) as characteristics. Our findings indicate that, except for 2Q errors, calibration data characteristics lack promise as PUCs due to low variation. In contrast, benchmarking algorithms, particularly the Single Qubit State Fidelity, the 2-, 3-, and 5-qubit, 1-step Hadamard Walk, and the 5-qubit, 10-step Hadamard Walk show potential as PUC characteristics due to their high variation.
Quantum computers are rapidly becoming more capable, with dramatic increases in both qubit count \cite{kim2023evidence} and quality \cite{moses2023race}. Among different hardware approaches, trapped-ion quantum processors are a leading technology for quantum computing, with established high-fidelity operations and architectures with promising scaling. Here, we demonstrate and thoroughly benchmark the IonQ Forte system: configured as a single-chain 30-qubit trapped-ion quantum computer with all-to-all operations. We assess the performance of our quantum computer operation at the component level via direct randomized benchmarking (DRB) across all 30 choose 2 = 435 gate pairs. We then show the results of application-oriented \cite{IonQ_AQ20_2022}\cite{qedcPeerReviewed} benchmarks and show that the system passes the suite of algorithmic qubit (AQ) benchmarks up to #AQ 29. Finally, we use our component-level benchmarking to build a system-level model to predict the application benchmarking data through direct simulation. While we find that the system-level model correlates with the experiment in predicting application circuit performance, we note quantitative discrepancies indicating significant out-of-model errors, leading to higher predicted performance than what is observed. This highlights that as quantum computers move toward larger and higher-quality devices, characterization becomes more challenging, suggesting future work required to push performance further.
Abstract The field of quantum computing has grown from concept to demonstration devices over the past 20 years. Universal quantum computing offers efficiency in approaching problems of scientific and commercial interest, such as factoring large numbers, searching databases, simulating intractable models from quantum physics, and optimizing complex cost functions. Here, we present an 11-qubit fully-connected, programmable quantum computer in a trapped ion system composed of 13 171 Yb + ions. We demonstrate average single-qubit gate fidelities of 99.5 %\%% % , average two-qubit-gate fidelities of 97.5 %\%% % , and SPAM errors of 0.7 %\%% % . To illustrate the capabilities of this universal platform and provide a basis for comparison with similarly-sized devices, we compile the Bernstein-Vazirani and Hidden Shift algorithms into our native gates and execute them on the hardware with average success rates of 78 %\%% % and 35 %\%% % , respectively. These algorithms serve as excellent benchmarks for any type of quantum hardware, and show that our system outperforms all other currently available hardware.
Quantum computing testbeds exhibit high-fidelity quantum control over small collections of qubits, enabling performance of precise, repeatable operations followed by measurements. Currently, these noisy intermediate-scale devices can support a sufficient number of sequential operations prior to decoherence such that near term algorithms can be performed with proximate accuracy (like chemical accuracy for quantum chemistry problems). While the results of these algorithms are imperfect, these imperfections can help bootstrap quantum computer testbed development. Demonstrations of these algorithms over the past few years, coupled with the idea that imperfect algorithm performance can be caused by several dominant noise sources in the quantum processor, which can be measured and calibrated during algorithm execution or in post-processing, has led to the use of noise mitigation to improve typical computational results. Conversely, benchmark algorithms coupled with noise mitigation can help diagnose the nature of the noise, whether systematic or purely random. Here, we outline the use of coherent noise mitigation techniques as a characterization tool in trapped-ion testbeds. We perform model-fitting of the noisy data to determine the noise source based on realistic physics focused noise models and demonstrate that systematic noise amplification coupled with error mitigation schemes provides useful data for noise model deduction. Further, in order to connect lower level noise model details with application specific performance of near term algorithms, we experimentally construct the loss landscape of a variational algorithm under various injected noise sources coupled with error mitigation techniques. This type of connection enables application-aware hardware codesign, in which the most important noise sources in specific applications, like quantum chemistry, become foci of improvement in subsequent hardware generations.
Abstract In blind quantum computing (BQC), a user with a simple client device can perform a quantum computation on a remote quantum server such that the server cannot gain knowledge about the computation. Here, we numerically investigate hardware requirements for verifiable BQC using an ion trap as server and a distant measurement-only client. While the client has no direct access to quantum-computing resources, it can remotely execute quantum programs on the server by measuring photons emitted by the trapped ion. We introduce a numerical model for trapped-ion quantum devices in NetSquid, a discrete-event simulator for quantum networks. Using this, we determine the minimal hardware requirements on a per-parameter basis to perform the verifiable BQC protocol. We benchmark these for a five-qubit linear graph state, with which any single-qubit rotation can be performed, where client and server are separated by 50 km. Current state-of-the-art ion traps satisfy the minimal requirements on a per-parameter basis, but all current imperfections combined make it impossible to perform the blind computation securely over 50 km using existing technology. Using a genetic algorithm, we determine the set of hardware parameters that minimises the total improvements required, finding directions along which to improve hardware to reach our threshold error probability that would enable experimental demonstration. In this way, we lay a path for the near-term experimental progress required to realise the implementation of verifiable BQC over a 50 km distance.
Trapped-ion quantum computers, leveraging a quantum charge-coupled device (QCCD) architecture, have world-class performance in the field of quantum computing, offering high fidelities and all-to-all connectivity [1]. While systems have advanced over the last decade, much work remains to scale quantum computers to fault-tolerance. Providing scalable light delivery is one key challenge. Current systems utilize engineered bulk- and fiber-optic-based light delivery systems, external to the vacuum chamber, to deliver arrays of beams to ions. However, fundamental optical limitations preclude the use of such systems when scaling beyond thousands of qubits. Integrated photonic-based beam delivery offers a potential solution, with encouraging proof-of-concept demonstrations from the photonics and quantum communities [2]–[5]. Quantinuum and Sandia National Labs have partnered to accelerate the development of integrated photonics for trapped-ion quantum computing applications, working towards photonic components supporting high-fidelity operations. Here, we present development of photonic integrated components designed to deliver laser light toBa+\text{Ba}^{+}Ba+qubits, utilizing a low-loss, high-confinement, trap-integrable PECVD SiN platform. In order to demonstrate two-qubit gates at 532 nm, we developed low loss, tight bend waveguides, efficient edge couplers, and asymmetric multimode interference (MMI) splitters, along with beam-forming grating out-couplers delivering gaussian beams at the ion plane. For quantum state preparation and measurement (SPAM) applications at4 9 3   n m\text{4 9 3 ~ n m}4 9 3   n m, we demonstrate fabrication-tolerant splitters and low-crosstalk gratings. Measured component performance shows promise for future trap-integrated demonstrations.
This thesis focuses on the design of a vacuum system for a trapped ion quantum computer that will house an advanced ion chip trap from Sandia National Laboratories, capable of performing high fidelity operations on up to tens of qubits. The thesis will outline the different design considerations, criteria, and serve to document the final design choices, in addition to optical design work that will be used to drive resonant atomic transitions in the qubit of choice, 133Ba+, as well as the qudit, 137Ba+.