<!--HTML-->Trapped ions are one of the leading and furthest developed technologies in quantum computing. However, despite higher quality operations than on any other platform and the absence of variations in qubit quality, the road to fault-tolerant quantum computing remains long and steep. In this talk, I will briefly review the state of the art of the trapped-ion platform, illustrate the current attempts to scaling up to larger numbers of qubits and highlight the challenges faced in control electronics and reliable manufacturing.
<!--HTML-->Trapped ions are one of the leading and furthest developed technologies in quantum computing. However, despite higher quality operations than on any other platform and the absence of variations in qubit quality, the road to fault-tolerant quantum computing remains long and steep. In this talk, I will briefly review the state of the art of the trapped-ion platform, illustrate the current attempts to scaling up to larger numbers of qubits and highlight the challenges faced in control electronics and reliable manufacturing.
Abstract The trapped-ion architecture was the first platform to demonstrate quantum gate operations in 1995 and continues to be a leading candidate for building a fault-tolerant quantum computer. This chapter provides a brief background on common performance metrics and nomenclature, summarizes the state of the art, and places them in context within the larger pursuit of error-corrected quantum computers. Current research thrusts in academia and industry are referenced, and an example roadmap is examined to show where the platform is right now and where it might be headed on the road to realizing a scaled-up device.
This is the second paper in a series of papers providing an overview of different quantum computing hardware platforms from an industrial end-user perspective. It follows our first paper on neutral-atom quantum computing. In the present paper, we provide a survey on the current state-of-the-art in trapped-ion quantum computing, taking up again the perspective of an industrial end-user. To this end, our paper covers, on the one hand, a comprehensive introduction to the physical foundations and mechanisms that play an important role in operating a trapped-ion quantum computer. On the other hand, we provide an overview of the key performance metrics that best describe and characterise such a device's current computing capability. These metrics encompass performance indicators such as qubit numbers, gate times and errors, native gate sets, qubit stability and scalability as well as considerations regarding the general qubit types and trap architectures. In order to ensure that these metrics reflect the current state of trapped-ion quantum computing as accurate as possible, they have been obtained by both an extensive review of recent literature and, more importantly, from discussions with various quantum hardware vendors in the field. We combine these factors and provide - again from an industrial end-user perspective - an overview of what is currently possible with trapped-ion quantum computers, which algorithms and problems are especially suitable for this platform, what are the relevant end-to-end wall clock times for calculations, and what might be possible with future fault-tolerant trapped-ion quantum computers.
Ion trap is one of the leading physical platforms to implement quantum computation. Currently, high-fidelity elementary quantum operations above the fault-tolerant threshold, including state preparation, measurement and universal gates, have been demonstrated for tens of ionic qubits. One important future research direction is to further enlarge the qubit number to the scale required for solving practical problems while maintaining the high performance of individual qubits. This paper introduces the current mainstream schemes for scalable ion trap quantum computation like quantum charge-coupled device (QCCD) and ion-photon quantum network, and describes the main limiting factors in current research. Then we further explore new schemes to scale up the qubit number like two-dimensional ion crystals and dual-type qubit, and discuss the future research directions.
Quantum computation has emerged as a prominent research field with the potential to revolutionize information processing. Recent advancements have focused on extending qubit coherence times and enhancing error correction and fault-tolerant protocols, achieving coherence time to gate time ratios as high as 10⁸ and reducing error rates to as low as 0.143% ± 0.003% per cycle for 101 qubit system. The next critical challenge lies in scaling up qubit systems to support large-scale quantum computation that exceeds the performance of classical supercomputer. In this study, we summarize the working mechanisms, physical properties, gate operations, and limitations of three leading qubit platforms—superconducting qubits, trapped-ion qubits, and neutral atom qubits. Through a systematic comparison, we identify the key challenges that hinder qubit system scalability. Finally, we outline future research directions to address these challenges, including exploring the fundamental physics underpinning long coherence times, improving control tools such as laser systems, enhancing material quality and fabrication precision, and investigating hybrid quantum architectures. We hope this study offers a valuable perspective for researchers working toward the development of scalable and reliable quantum computing systems.
Abstract The future of quantum information processing requires a stable hardware platform to execute quantum circuits reliably and with low error rates, such that solutions for industrial applications can be built on top of it. Trapped-ion quantum computing, among other platforms, currently proves to be very suitable for the transition from tabletop, lab-based experiments to rack-mounted, on-premise systems which allow operation in data center environments. Several technical challenges need to be solved and controlling many degrees of freedom needs to be optimized and automated, before industrial applications can be successfully implemented on quantum computers situated within data centers. These necessary developments range from the architecture of an ion trap that fundamentally defines the supported instruction sets, over the control electronics and laser systems, which limit the quality of qubit operations, to the optimized compilation of quantum circuits based on qubit properties and gate fidelities. In this chapter, we give an introduction to the ion-trap quantum computing platform, present the current technical state of the art of Alpine Quantum Technologies’ ion-trapping hardware and rack-based quantum computing systems, and highlight parts of the execution stack.
<!--HTML--> In this talk, I will review the fundamental principles of quantum information processing and provide an update on the Innsbruck trapped-ion quantum computer [1]. Using strings of trapped ions, we realize a programmable quantum processor capable of performing universal operations. I will give an overview of the experimental quantum toolbox and discuss current strategies for scaling the system to larger sizes. The versatility of this platform is illustrated through both analog and digital quantum simulations. By exploiting the trapped-ion toolbox for entanglement-enhanced Ramsey interferometry, we identify optimal parameters for quantum metrology [2]. Employing universal quantum computation, we explore the dynamics of the Lattice Schwinger model [3] - a one-dimensional gauge theory of quantum electrodynamics - and, using a hybrid quantum-classical variational approach, we determine steady-state properties of the corresponding Hamiltonian [4]. Finally, with a trapped-ion qudit quantum processor, in which quantum information is encoded in multiple internal states, we simulate a two-dimensional lattice gauge theory [5}. [1] I. Pogorelov et al., PRX Quantum 2, 020343 (2021) [2] C. D. Marciniak et al., Nature 603, 604 (2022) [3] E. A. Martinez et al., Nature 534, 516 (2016) [4] C. Kokail et al., Nature 569, 355–360 (2019) [5] M. Meth et al., Nature Physics 21, 570 (2025)