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Trapped-ion quantum computer

A trapped-ion quantum computer is a quantum computing platform that employs individual atomic ions, confined in electromagnetic traps such as radiofrequency Paul traps or Penning traps, to serve as qubits for processing quantum information. The qubits are encoded in the ions' internal electronic states—such as hyperfine, Zeeman, optical, or fine-structure levels—while laser pulses, Raman beams, or microwave fields manipulate these states and couple them via the ions' shared collective motional modes to implement quantum logic gates. This architecture, first proposed by Ignacio Cirac and Peter Zoller in 1995, enables universal quantum computation by satisfying all DiVincenzo criteria, including scalable qubit initialization, long coherence times exceeding 600 seconds in some cases (with records over one hour for single ions), high-fidelity single-qubit gates exceeding 99.99999%, two-qubit gates up to 99.99%, and state readout fidelities up to 99.9993% as of 2025. Trapped-ion systems leverage the identical properties of ions, such as ytterbium-171 (^171Yb^+), beryllium-9 (^9Be^+), calcium-43 (^43Ca^+), or barium-137 (^137Ba^+), to achieve precise control and minimal variability in behavior. Ion loading typically occurs via photoionization of neutral atoms followed by to near the motional , ensuring low for reliable operations. Common gate implementations include the Mølmer-Sørensen scheme for entangling two- operations, which uses bichromatic fields to induce state-dependent forces without populating lossy excited states, and direct microwave-driven gates for single- rotations. These methods support all-to-all connectivity in linear ion chains, facilitating complex algorithms without the need for extensive shuttling in early designs. One of the primary advantages of trapped-ion quantum computers is their exceptional and gate fidelities, which surpass many other modalities like superconducting circuits, enabling demonstrations of quantum algorithms such as Shor's factoring on small scales with over 99% success rates. Systems have scaled to controlled operations on up to 98 qubits in quantum (QCCD) architectures and over 200 ions in linear traps as of 2025, with benchmarks on 98-qubit devices achieving two-qubit gate fidelities of 99.92%. However, challenges persist in scaling to thousands of qubits due to heating from noise, slow gate speeds (typically 1.6–100 µs), ion loss requiring reloading, and the complexity of delivering multiple wavelengths to microfabricated surface- traps. Ongoing advancements address these limitations through modular architectures, such as ion shuttling in segmented traps, dual-species operations for error correction, integrated photonics for light delivery, and cryogenic trap operation to reduce noise. Materials science plays a crucial role, with research focusing on low-noise trap electrodes and dielectric coatings to mitigate electric-field fluctuations that limit coherence. Commercial efforts, including those by IonQ (following its 2025 acquisition of Oxford Ionics) and Quantinuum, have produced accessible systems like the 98-qubit Helios, highlighting trapped ions' potential for near-term quantum advantage in simulation and optimization tasks. Despite these strides, full fault-tolerant quantum computing remains a future goal, contingent on integrating quantum error correction and achieving rapid, high-fidelity scaling.

Basic Principles

Electromagnetic Trapping of Ions

Electromagnetic trapping of ions relies on the interaction of charged particles with precisely engineered electric and magnetic fields to confine them in vacuum, creating stable environments for quantum operations. The two primary trap types used are and , each offering distinct advantages in achieving long confinement times and low motional temperatures essential for quantum coherence. The Paul trap, invented by in the 1950s, employs oscillating radiofrequency (RF) electric fields to generate a time-varying potential that provides radial confinement. In a linear Paul trap, four rod electrodes apply an RF voltage, typically in the range of 100–500 V at frequencies of 10–50 MHz, creating a that confines ions radially while electrodes provide axial electrostatic confinement. The stability of ion motion in this dynamic field is governed by the Mathieu equations, which describe the parametric resonance conditions for bounded trajectories: \frac{d^2 u}{d \tau^2} + (a_u - 2 q_u \cos 2\tau) u = 0 where u represents the radial coordinates, \tau = \Omega t / 2 with \Omega the RF angular frequency, and the stability parameters a_u and q_u depend on the RF voltage, ion mass, and charge. Typical ion heights above the trap electrodes range from 50–1000 μm to minimize electric field noise, ensuring confinement depths of 0.1–1 eV. In contrast, the uses a uniform static , often 1–6 T, for radial cyclotron motion confinement and a static for axial trapping, avoiding RF-induced micromotion but requiring cryogenic operation to suppress anomalous heating. This configuration cyclically orbits at the cyclotron frequency \omega_c = qB/m, where q is the ion charge, B the strength, and m the , providing exceptional stability for precision measurements. Common ion species for trapping include singly charged ytterbium (Yb⁺), calcium (Ca⁺), and (Ba⁺), selected for their suitable electronic transitions, long-lived internal states, and masses that enable low motional frequencies (typically 1–10 MHz) compatible with laser manipulation. The first demonstration of single-ion trapping occurred in 1980 by Neuhauser et al., who confined a Ba⁺ ion in a Paul trap at room temperature using laser fluorescence detection. To prepare ions for quantum applications, laser cooling reduces motional temperatures from initial eV-scale energies to near the quantum ground state. Doppler cooling, achieved by red-detuning a laser from an atomic resonance by an amount comparable to the natural linewidth (e.g., ~20 MHz for Ca⁺), imparts momentum kicks that damp velocity, reaching millikelvin temperatures in seconds. Subsequent resolved-sideband cooling addresses the Doppler limit by sequentially exciting and de-exciting red-sideband transitions, coupling internal electronic states to motional modes until the ion's center-of-mass motion occupies less than one quantum of harmonic oscillator energy, with final temperatures below 0.1 mK.

Qubit Encoding in Ion States

In trapped-ion quantum computers, s are encoded using the internal electronic and motional states of individually confined s, which provide stable platforms for storing and manipulating due to their atomic-scale precision and isolation from the environment. The predominant encoding scheme employs hyperfine s, utilizing Zeeman sublevels within the electronic manifold, such as the ²S_{1/2} state. These levels are split by the hyperfine interaction between the and nuclear spins, offering magnetic-field-insensitive transitions ideal for robust qubit operations. For instance, in ^{171}Yb^{+} s, the is typically encoded in the clock states |0\rangle = |F=0, m_F=0\rangle and |1\rangle = |F=1, m_F=0\rangle of the ²S_{1/2} manifold, where F denotes the ; these states are separated by a hyperfine splitting frequency of approximately 12.6 GHz. The general superposition state of such a hyperfine is expressed as \begin{equation} |\psi\rangle = \alpha |0\rangle + \beta |1\rangle, \end{equation} where \alpha and \beta are complex coefficients satisfying |\alpha|^2 + |\beta|^2 = 1, representing arbitrary states on the . Optical qubits represent an alternative encoding, pairing the ground ²S_{1/2} state with a long-lived metastable , such as the ²D_{3/2} level in ^{171}Yb^{+} ions, which enables faster laser-driven transitions at shorter wavelengths (around 435 nm) compared to hyperfine schemes. However, their coherence is inherently limited by the metastable state's lifetime, typically on the order of milliseconds. Vibrational qubits, or qumodes, encode in the collective motional of the chain, arising from the shared harmonic vibrational modes coupled via repulsion; these bosonic modes operate at MHz frequencies and support continuous-variable protocols. Hyperfine qubits exhibit exceptional properties, with dephasing times T_2 typically spanning 1-10 seconds under standard conditions and energy relaxation times T_1 often exceeding minutes, particularly when using dynamical to suppress magnetic noise. For instance, early demonstrations with ^{171}Yb^{+} achieved T_2 values of about 2.5 seconds for these clock states. In contrast, optical qubits have shorter T_1 limited by spontaneous decay from the metastable state, approximately 1.2 s for systems like ^{40}Ca^{+}. To maintain these long times, quantum operations are confined to the Lamb-Dicke regime, where the parameter \eta = k z_0 \ll 1 (with k the wavevector and z_0 the ground-state motion extent) ensures minimal heating from or . A significant advantage of ion-based encoding is the intrinsic identicality of qubits derived from the same isotope, which guarantees uniform atomic properties across the ensemble and simplifies error characterization and calibration. Furthermore, the Coulomb interactions among ions enable all-to-all qubit connectivity through the shared vibrational modes, facilitating native entangling operations between arbitrary ion pairs in linear chains without requiring ion shuttling in some architectures.

Quantum Operations

State Initialization and Measurement

State initialization in trapped-ion quantum computers typically involves to prepare ions in a well-defined state, such as the computational |0⟩. This process uses resonant , often circularly polarized, to drive electronic that preferentially populate the desired state through repeated absorption and cycles. For common like ^{40}Ca^+, pumping on the S_{1/2} to P_{1/2} at 397 nm achieves this, with repumping lasers (e.g., at nm or 854 nm) addressing metastable states like D_{3/2} or D_{5/2} to prevent population trapping and ensure high efficiency. The procedure is probabilistic but highly reliable, yielding initialization exceeding 99% in times under 1 ms as of early experiments, with optimized protocols reaching >99.9% in ~10 μs for hyperfine or Zeeman qubits. Recent advancements as of 2024 have demonstrated state preparation and measurement (SPAM) up to 99.9993% using improved cooling and detection techniques. Measurement of the qubit state relies on state-dependent fluorescence detection, where a resonant illuminates the , causing it to scatter only if in the bright state (typically |1⟩ coupled to a cycling transition like S_{1/2} to P_{1/2}). The orthogonal |0⟩ state remains dark, producing minimal scattering, and the photon count is thresholded (e.g., >7 indicates |1⟩) using tubes or electron-multiplying CCDs. For optical qubits encoded in long-lived states like S_{1/2} to D_{5/2}, electron shelving techniques transfer one state to a metastable level (e.g., D_{5/2}) to avoid off-resonant excitation and enable unambiguous discrimination without destroying the in the measured basis. Detection cycles typically last ~100–200 μs, achieving fidelities >99.9% in early systems and >99.99% in recent implementations as of 2024, with scattering rates of 10^7–10^8 /s. Overall detection efficiencies are ~1–10% due to collection and detector losses, though integrated have improved single-photon detection probabilities to ~9% as of 2025. Quantum non-demolition (QND) measurements, which preserve the measured state, can be implemented via motional s by resolving and sideband transitions to probe the without full projection, or through sympathetic readout using auxiliary ions. The detection is given by F = 1 - \epsilon, where \epsilon is the error rate, often dominated by off-resonant with probabilities ~10^{-4} to 10^{-3} per cycle, leading to overall readout errors below 0.1% in optimized systems.

Single-Qubit Gates

Single-qubit gates in trapped-ion quantum computers enable precise manipulation of individual states through coherent control using pulses. These operations are essential for implementing arbitrary unitary transformations on a single ion's internal states, typically encoded in hyperfine or optical transitions. The most common approach employs Raman transitions, which are two-photon processes driven by a pair of counter-propagating beams detuned from the resonance to avoid carrier excitation and minimize . This method facilitates spin flips between states, such as the ground and metastable hyperfine levels in ions like ^{171}Yb^+ or ^{43}Ca^+, while coupling to the ion's motional state is suppressed in the Lamb-Dicke regime. The effective for these transitions is given by \Omega = \frac{\Omega_1 \Omega_2}{2\Delta}, where \Omega_1 and \Omega_2 are the single-photon Rabi frequencies of the two lasers, and \Delta is the detuning from the intermediate . Common single-qubit gates include \pi/2 and \pi pulses that induce rotations about the , or axes on the , achieved by varying the phase and duration of the Raman pulses to control the axis and angle. For instance, a \pi pulse performs a full flip (), while phase shifts for or arbitrary SU(2) operations are realized via AC Stark shifts induced by off-resonant pulses, which impart a light shift between qubit states without changing the population. These gates typically operate on timescales of 10-100 \mu s, balancing speed with to mitigate decoherence from fluctuations or instability. Fidelities exceeding 99.9% (error rates <10^{-4}) were routinely achieved in early 2010s experiments, with recent demonstrations as of 2024 reaching errors below 10^{-7} using optimized pulse shaping, dynamical decoupling, and microwave control in ^{43}Ca^+ hyperfine s. Recent advances include laser-free universal control via radiofrequency fields, enabling high-fidelity operations without optical addressing complexities. For optical qubits, such as the long-lived D_{3/2} state in ^{40}Ca^+, single-qubit gates can be implemented via direct resonant driving with a single laser beam, bypassing the need for two-photon Raman processes and enabling faster operations with Rabi frequencies up to MHz. Implementation requires precise spatial addressing to target individual ions in a linear chain, accomplished by focusing laser beams to a waist of approximately 2 \mu m, comparable to the 3-5 \mu m inter-ion spacing, often using acousto-optic deflectors for beam steering. This selective illumination ensures minimal crosstalk, maintaining high gate fidelity even in multi-ion strings. All-electronic approaches using integrated microwave lines have emerged as of 2025 for scalable, low-noise control.

Two-Qubit Entangling Gates

Two-qubit entangling gates in trapped-ion quantum computers rely on the coupling between the ions' internal qubit states and their shared collective motional modes, mediated by laser-induced spin-dependent forces. These gates generate entanglement without leaving residual excitation in the motional degrees of freedom, enabling high-fidelity operations even with ions in thermal motion. The primary approach, the , uses bichromatic laser fields tuned near the blue and red sidebands of the motional frequencies to drive a spin-dependent force that entangles multiple ions via phonon modes. In the MS gate, two laser beams with frequencies detuned symmetrically around the qubit transition carrier frequency illuminate the ions simultaneously, creating an effective interaction Hamiltonian of the form H = \frac{\hbar \Omega^2}{2 \mu} (S_x^\phi)^2, where \Omega is the Rabi frequency, \mu is the effective motional frequency, and S_x^\phi = \sum_j \sigma_x^j e^{i \phi_j} is the collective spin operator along a phase-adjusted direction. This Hamiltonian induces an XX-type interaction, producing a maximally entangling \pi/2 phase shift for the state |11\rangle relative to |00\rangle. The gate duration \tau is chosen such that \int_0^\tau \Omega(t) \, dt = \pi / \sqrt{2} to achieve the desired entangling angle for the XX interaction. The MS gate supports all-to-all entanglement in linear ion chains by leveraging the collective normal modes of motion, allowing simultaneous pairwise interactions without requiring individual ion addressing for connectivity. In small systems of up to a few ions, MS gates achieved fidelities exceeding 99.9% in pre-2020 experiments, with recent implementations as of 2025 reaching >99.99% without ground-state cooling and 99.99% in commercial systems using electronic qubit control. Advances include fast mixed-species gates via ultrafast state-dependent kicks with laser pulses, reducing gate times and enabling error-corrected operations. Alternative entangling methods include light-shift gates, where a single off-resonant beam induces an AC Stark shift that couples the qubits through their shared motion, generating a state-dependent phase accumulation. gates, based on cycling the ions through closed trajectories in via spin-dependent kicks, accumulate a conditional proportional to the enclosed area, enabling entanglement with reduced sensitivity to certain noise sources. To implement a controlled-NOT (CNOT) gate, a partial MS gate with a \pi/4 entangling angle is combined with single-qubit rotations to correct the target qubit's phase and basis. Phonon recycling in these protocols is achieved through fast gate implementations that resolve motional sidebands, ensuring the collective modes return to their initial state with minimal heating and enabling gate times on the order of microseconds.

Scalable System Designs

Trap Architectures

Trapped-ion quantum computers rely on ion trap architectures that confine multiple ions in stable configurations to enable scalable qubit arrays. Linear traps, consisting of segmented electrodes, form the foundational design for holding linear chains of ions, with demonstrations up to over 200 ions as of 2025, by applying radio-frequency (RF) potentials to create a ponderomotive force that confines ions radially while static potentials control axial positioning. These traps often feature endcap electrodes and RF ring configurations, with electrode spacings on the order of 100 μm to maintain ion separations of several micrometers, allowing precise laser addressing of individual ions. Segmented linear traps for quantum computing applications were developed by the Wineland group at NIST in the early 2000s, enabling the manipulation of small ion strings and laying the groundwork for multi-qubit operations. Surface traps, also known as chip traps, represent a microfabricated of Paul traps, using lithographically patterned gold electrodes on insulating substrates such as alumina or silicon to generate the necessary electric fields. This design facilitates the creation of two-dimensional ion crystals or three-dimensional arrays, with ions positioned tens to hundreds of micrometers above the chip surface, offering advantages in through integration with on-chip , , and control systems. Prototypes emerged in the late with laser-machined electrodes, advancing to monolithic lithographic fabrication by the mid-2000s for reproducible, compact structures suitable for large-scale quantum processors. To mitigate electric-field noise and enhance ion lifetime, these traps are frequently operated at cryogenic temperatures around 4 K. Advanced trap designs incorporate time-varying potentials for ion shuttling, enabling modular architectures where ions can be transported between zones to perform operations and overcome limitations of static linear chains. structures, such as X-junctions and T-junctions, allow ions to be routed in two dimensions: T-junctions facilitate linear shuttling and swapping in multi-zone arrays, demonstrated as early as with 11-zone traps holding individual laser-cooled ions, while X-junctions support grid-like connectivity for more complex routing in scalable systems. These features, combined with segmented electrodes, enable the reconfiguration of ion chains for fault-tolerant without requiring all-to-all connectivity in a single trap. Recent advancements as of 2025 include multi-layer stacked traps and integrated for efficient light delivery, supporting systems with over 50 qubits and shuttling.

Decoherence and Noise Sources

In trapped-ion quantum computers, decoherence arises primarily from interactions between the ions' internal qubit states and their motional degrees of freedom, as well as environmental fluctuations. Motional heating, a key noise source, excites the ions' vibrational modes, leading to loss of during gate operations. This heating is predominantly caused by anomalous electric-field originating from surface electrodes in the ion trap, with observed heating rates typically ranging from 1 to 10 per on timescales in room-temperature surface traps. The heating rate \dot{\bar{n}} due to this electric-field noise is given by \dot{\bar{n}} = \frac{q^2}{4 m \hbar \omega} S_E(\omega), where q is the ion charge, m is the ion mass, \omega is the trap frequency, \hbar is the reduced Planck's constant, and S_E(\omega) is the spectral density of the electric-field noise at the trap frequency. An empirical form approximates this as \dot{N} \approx \left( \frac{e V_{\mathrm{rms}}}{\hbar d^2} \right)^2, where e is the elementary charge, V_{\mathrm{rms}} is the root-mean-square voltage fluctuation, and d is the ion-electrode distance; the noise scales inversely with d^4, making proximity to trap surfaces a critical factor. To mitigate heating, heavier ions like ^{138}\mathrm{Ba}^+ are employed in dual-species chains, as the heating rate decreases with increasing ion mass m, and cryogenic cooling of the trap to 4 K reduces rates by up to 100 times by suppressing surface noise mechanisms. Dephasing, another major decoherence channel, randomizes the phase of qubit superpositions without energy exchange. It stems from fluctuations, which limit the inhomogeneous dephasing time T_2^* to around 1 second for Zeeman qubits, and laser , which constrains coherence times of optical qubits to approximately 0.2 seconds. Spin-echo techniques, such as dynamical pulses, extend these times by refocusing phase errors, achieving up to several seconds for protected states. During two-qubit entangling gates like the Mølmer-Sørensen () gate, decoherence is exacerbated by spin-motion entanglement errors, where imperfect recoupling of the ions' internal and motional states leads to residual excitations. These errors scale with the motional heating rate and increase gate infidelity, though they can be reduced to below 0.1% with optimized and higher trap frequencies.

Historical Development

Early Experiments

The development of trapped-ion quantum computing emerged from foundational work in precision and atomic clocks, where techniques for trapping, cooling, and coherently manipulating individual ions were refined in the and . David J. Wineland's group at the National Institute of Standards and Technology (NIST) played a pivotal role, demonstrating of trapped ions in 1978 and quantum jumps—coherent transitions between electronic states—in 1986 using single ions (Ba⁺), which enabled high-fidelity state initialization and readout essential for processing. This heritage in , focused on extending coherence times for frequency standards, naturally transitioned to quantum computing by leveraging the same tools for controllable operations. A seminal theoretical proposal came in 1995 from Ignacio Cirac and , who outlined a scalable quantum computer using cold trapped ions confined in a linear Paul trap, with qubits encoded in internal electronic states and entangling operations mediated by shared vibrational modes (phonons) to implement a controlled-NOT (CNOT) gate. This scheme highlighted the potential of ion traps for universal quantum computation, as the collective motion could couple multiple ions without direct qubit-qubit interactions. Shortly thereafter, Wineland's NIST group experimentally realized a key element of this proposal: the first demonstration of quantum logic spectroscopy using a two-ion crystal of beryllium-9 ions (⁹Be⁺), where the motional state served as a control qubit to conditionally flip the internal state of the target ion, achieving a CNOT operation with fidelity limited primarily by off-resonant excitations. Early experiments also showcased advanced coherent manipulations of ion states, building toward nonclassical motional superpositions. In the mid-1990s, the NIST team generated Schrödinger cat-like states of motion for a single ⁹Be⁺ , creating even and odd superpositions of coherent states in the harmonic trap via laser-induced displacements, which demonstrated control over macroscopic quantum coherence with displacements up to α ≈ 1.4. Complementary work explored coherent population trapping (CPT) techniques for state preparation and cooling, initially adapted from free-atom methods and applied to trapped ions in the early 1990s to create dark states immune to spontaneous decay, enhancing coherence for subsequent quantum operations; calcium-40 ions (⁴⁰Ca⁺) were among the early species tested alongside ⁹Be⁺ due to their suitable optical transitions. Progress accelerated with the first high-fidelity two-qubit entangling gate in 2003, again by the NIST group led by Wineland. Using two ⁹Be⁺ ions, David Leibfried et al. implemented a gate via spin-dependent optical dipole forces that displaced the ions' shared motional state along a closed loop in , yielding a π-phase shift conditional on both qubits' states with 97% and enabling the creation of a . This marked a crucial step beyond single-ion logic, validating trapped ions as a viable platform for multi-qubit quantum processing while highlighting the role of motional modes in achieving robust entanglement.

Key Milestones and Demonstrations

In 2005, researchers demonstrated the first implementation of Grover's search algorithm on a trapped-ion quantum computer using two ions, marking an early algorithmic milestone that showcased the platform's ability to perform quantum search tasks with a success probability exceeding 80%. This experiment highlighted the feasibility of universal quantum computation primitives on trapped ions. A pivotal advance came in 2016 when a team at the executed to factor the 15 using five trapped calcium ions, achieving a success probability over 90% and demonstrating the platform's potential for cryptographic applications on small scales. The same year, the Innsbruck group also advanced scalability by realizing high-fidelity entangling operations across chains of up to 14 ions, paving the way for larger register control. Scalability demonstrations accelerated in 2018 with the generation of complex entangled states involving 20 individually addressable trapped-ion qubits, where full confirmed genuine multipartite entanglement, a key step toward handling system sizes relevant for near-term algorithms. In 2021, (now ) reported a of 1024 on a 10-qubit trapped-ion system, the highest at the time for commercial hardware, underscoring improved circuit depth and width capabilities. Error correction progress was evident in 2021 with the first real-time fault-tolerant on a trapped-ion device, using seven ions to encode a single logical via the distance-3 surface and suppressing errors below the physical rate, extending by over a factor of 2.5. Trapped-ion systems have since achieved two-qubit gate fidelities above 99.9% (error rates ~10^{-3}), meeting thresholds for fault-tolerant in surface architectures. Recent developments from 2023 to 2025 include IonQ's Forte system, which supports algorithmic qubit counts exceeding 35 with high-fidelity operations, enabling simulations of complex molecules and optimization problems beyond classical limits. In 2024, 's H2 system demonstrated 56- operations with quantum volume surpassing 2^{20}, while IonQ's Forte achieved benchmarks on 30 physical qubits with all-to-all connectivity, approaching 100-qubit effective simulations for tasks. By September 2025, the H2 system achieved a of 2^{25}, demonstrating enhanced circuit depth and width capabilities. These advances build on the foundational universal gate sets proposed in early architectures, such as Kielpinski et al.'s 2002 blueprint, adapted for modular scaling.

Current Implementations and Challenges

Leading Systems and Research Efforts

Several leading research institutions have pioneered and continue to advance trapped-ion quantum computing. The National Institute of Standards and Technology (NIST) and the University of Maryland (UMD) maintain a longstanding collaboration focused on improving fidelity and scalability in trapped-ion systems, building on the foundational work of David Wineland. At the , the group led by Rainer Blatt has developed scalable ion-trap architectures and contributed to commercial spinouts, emphasizing high-fidelity quantum operations with chains of trapped ions. IonQ stands as a prominent commercial leader in trapped-ion quantum computing, deploying systems like the Forte platform, which features 32 qubits and achieves two-qubit gate fidelities exceeding 99.9%. In 2023, IonQ introduced rack-mountable quantum computers designed for data center integration, enhancing modularity through photonic interconnects that enable remote ion-ion entanglement across trap modules. By 2024, IonQ made its quantum systems accessible via cloud platforms, including AWS Braket, allowing global users to run algorithms on hardware with up to 36 algorithmic qubits. In October 2025, IonQ achieved a world-record 99.99% two-qubit gate fidelity using its electronic qubit control technology. IonQ employs ¹⁷¹Yb⁺ ions in its traps, supporting research into scalable multi-qubit operations and error-corrected computing. Quantinuum, a Honeywell spinout, operates the H-Series trapped-ion processors, with the H2 model demonstrating 56 all-to-all connected physical qubits as of 2024. In 2025, Quantinuum achieved a milestone with the demonstration of 12 logical qubits using error correction on its H2 system, including high-fidelity logical magic state preparation for fault-tolerant algorithms. Like IonQ, Quantinuum utilizes ¹⁷¹Yb⁺ ions to enable scalable qubit transport and entanglement in its quantum charge-coupled device (QCCD) architecture. Other notable efforts include Oxford Ionics, which developed electronic qubit control for trapped ions and delivered a full-stack system to the UK's National Quantum Computing Centre in 2025 before its acquisition by IonQ. Alpine Quantum Technologies (AQT), a spinout from the University of Innsbruck, has deployed 20-qubit trapped-ion computers integrated with high-performance computing infrastructure in Europe, such as at the Leibniz Supercomputing Centre and the inauguration of the 20-qubit PIAST-Q system in Poland in June 2025 via the EuroHPC initiative. These advancements are supported by significant funding from programs like DARPA's Quantum Benchmarking Initiative, which includes in its efforts to evaluate scalable quantum hardware, and the EU Quantum Flagship, which backs projects involving AQT and researchers for trapped-ion development.

Fidelity, Scalability, and Error Correction

Fidelity in trapped-ion quantum computers remains a critical performance metric, particularly for two-qubit entangling gates, where error rates as low as 0.01% or better have been achieved as of 2025 due to factors such as coherent from imperfect laser addressing and phase instabilities in the control lasers. arises when laser beams intended for specific ion pairs inadvertently affect neighboring ions, introducing residual interactions that degrade gate performance, while laser limits the precision of qubit manipulations by introducing errors. Mitigation strategies, such as dynamical decoupling pulses, have been employed to suppress these errors by refocusing the qubit states against noise, achieving improvements in gate up to 99.99% in recent demonstrations without ground-state cooling. Scalability challenges in trapped-ion systems center on maintaining high-fidelity all-to-all for over 1000 qubits, addressed through modular architectures like ion zones or photonic interconnects. In zone-based designs, ions are shuttled between segmented regions to enable interactions across the , providing effective all-to-all while limiting local within each zone to reduce control complexity. Photonic links between remote traps facilitate entanglement distribution for larger-scale systems, allowing modular expansion beyond single-trap limits. However, shuttling introduces speed constraints, with typical transport velocities around 10 m/s, which can limit overall gate rates and increase exposure to decoherence during movement. Error correction in trapped-ion quantum computers adapts surface codes to the linear or modular trap geometry, encoding logical qubits across multiple physical ions to suppress errors below the fault-tolerance threshold. Demonstrations as of 2025, including on Quantinuum's H2, have achieved up to 12 logical qubits with high-fidelity operations using single-shot correction protocols and real-time error correction, enabling repeated error detection and correction cycles. The quantum threshold theorem applies when the physical error rate η falls below approximately 1%, allowing arbitrary computation with polynomial overhead in resources. Projections for scalable systems aim to support around 100 logical qubits through enhanced modular interconnects, while hybrid interfaces with superconducting circuits offer pathways for integrating trapped ions with cryogenic electronics to improve control scalability. For specific codes like the , adapted to ion chains, the logical error rate scales favorably as \varepsilon_L \approx 100 \, \varepsilon_\text{physical}^3 for small physical error rates ε_physical, providing cubic suppression that supports fault-tolerant operations with modest qubit overhead.

References

  1. [1]
    Trapped-Ion Quantum Computing: Progress and Challenges - arXiv
    Apr 8, 2019 · 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.
  2. [2]
  3. [3]
  4. [4]
    Benchmarking a trapped-ion quantum computer with 30 qubits
    Nov 7, 2024 · 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 ...
  5. [5]
    Materials challenges for trapped-ion quantum computers - Nature
    Mar 25, 2021 · In this Review, we consider the materials requirements for such integrated systems, with a focus on problems that hinder current progress towards practical ...Missing: paper | Show results with:paper
  6. [6]
    Wolfgang Paul – Facts - NobelPrize.org
    In the 1950s Wolfgang Paul developed a method for using electrical currents and electromagnetic fields to capture charged atoms—ions—in a trap.Missing: invention | Show results with:invention
  7. [7]
    Trapping Electrons in a Room-Temperature Microwave Paul Trap
    Jan 29, 2021 · While the Mathieu equation provides useful intuition for quadrupole traps, it should be noted that the pseudopotential picture and the treatment ...
  8. [8]
    [PDF] A surface electrode point Paul trap - Stanford University
    Sep 16, 2010 · We demonstrate trapping of single 88Sr+ ions over an ion height range of 200–1000µm for several hours under Doppler laser cooling, and use these ...
  9. [9]
    Penning Trap | ALPHA Experiment - CERN
    A Penning trap uses magnetic and electric fields to confine charged plasmas. It uses electric potentials for axial confinement and a magnetic field for radial ...
  10. [10]
    Localized visible mono-ion oscillator | Phys. Rev. A
    Sep 1, 1980 · An individual barium ion, continuously observed by laser fluorescence, has been isolated in a Paul rf quadrupole trap at room temperature.Missing: first | Show results with:first
  11. [11]
    [PDF] Laser Cooling of Trapped Ions. - Time and Frequency Division
    typical cases, T = 1 mK. Optical sideband cooling in a Paul trap was first demonstrated experhen- tally by NEUHAUSER et al.[21]. They cooled Ba+ ions, using the ...
  12. [12]
    None
    Below is a merged summary of the provided segments on trapped-ion quantum computing, combining all information into a comprehensive response. To retain maximum detail, I’ve organized key sections into a dense, tabular format where appropriate (e.g., for qubit encoding, gate operations, and current status), while maintaining a narrative structure for introductory and overarching content. All unique details from the summaries are included, with redundancies minimized.
  13. [13]
    Determination of the ground-state hyperfine splitting of trapped 171 ...
    Aug 20, 2024 · The 171Yb+ ion, characterized by its simple structure (⁠ I = 1 / 2 ⁠) and relatively large ν HFS (12.6 GHz), is an ideal candidate for the ...
  14. [14]
    Manipulation and Detection of a Trapped Yb+ Ion Hyperfine Qubit
    Aug 5, 2007 · We implement fast, efficient state preparation and state detection of the first-order magnetic field-insensitive hyperfine levels of 171Yb+, with a measured ...
  15. [15]
    [2410.07346] Toward hybrid quantum simulations with qubits and ...
    Oct 9, 2024 · We explore the feasibility of gate-based hybrid quantum computing using both discrete (qubit) and continuous (qumode) variables on trapped-ion platforms.
  16. [16]
  17. [17]
    Entanglement and quantum computation with ions in thermal motion
    Feb 9, 2000 · In this paper we present a unified analysis of this process for both weak and strong fields, for slow and fast gates.
  18. [18]
    Efficient arbitrary simultaneously entangling gates on a trapped-ion ...
    Jun 11, 2020 · In addition, a TIQIP may leverage the all-to-all connectivity between ion qubits. The ability to directly apply a two-qubit gate to any pair of ...
  19. [19]
    Light-shift-induced quantum gates for ions in thermal motion - arXiv
    Mar 26, 2001 · An effective interaction between trapped ions in thermal motion can be generated by illuminating them simultaneously with a single laser ...
  20. [20]
    [quant-ph/9710025] Experimental issues in coherent quantum-state ...
    Oct 7, 1997 · Experimental issues in coherent quantum-state manipulation of trapped atomic ions. Authors:D.J. Wineland, C. Monroe, W.M. Itano, D. Leibfried, ...
  21. [21]
  22. [22]
    Trapped-ion quantum computing: Progress and challenges
    May 29, 2019 · 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.Trapped ions for quantum... · Considerations for scaling a... · Quantum control...
  23. [23]
  24. [24]
  25. [25]
  26. [26]
    [1507.08852] Realization of a scalable Shor algorithm - arXiv
    Jul 31, 2015 · The scalable algorithm has been realized with an ion-trap quantum computer exhibiting success probabilities in excess of 90%. Comments: 5 pages, ...
  27. [27]
    Quantinuum Launches Industry-First, Trapped-Ion 56-Qubit ...
    With the additional physical qubits available on Quantinuum's new machine, we anticipate creating more logical qubits with even lower error rates. As we ...
  28. [28]
    Quantum Computing with Trapped Ions | NIST
    Apr 7, 2023 · We develop new methods and technologies to improve the fidelity and scalability of quantum control and readout for quantum computing based on trapped ions in ...
  29. [29]
    Quantum Computing - UMD CMNS - University of Maryland
    Formed as a research partnership between UMD and NIST and ... trapped-ion quantum computer hardware and collaborate with IonQ scientists and engineers.
  30. [30]
    Quantum Optics and Spectroscopy: Home
    Nicolas has now joined the CryoTrap team where he will work on integrated photonics for surface ion traps. ... Ion Trapping in Innsbruck. Alpine Quantum ...
  31. [31]
    About - AQT - Alpine Quantum Technologies
    Oct 22, 2024 · ... trapped ion quantum technologies, we have teamed up to realise the world's first general-purpose ion-trap quantum computer. AQT already ...
  32. [32]
    IonQ Forte: The First Software-Configurable Quantum Computer
    Mar 3, 2023 · IonQ Forte is initially equipped with 32 detection channels, which makes simultaneous readout of 32 qubits straightforward. We started operating ...Missing: Rackham | Show results with:Rackham
  33. [33]
    IonQ plans to launch a rack-mounted quantum computer for data ...
    Dec 9, 2020 · IonQ now says that it will be able to sell modular, rack-mounted quantum computers for the data center in 2023 and that by 2025, its systems will be powerful ...
  34. [34]
    IonQ Demonstrates Remote Ion-Ion Entanglement, a Significant ...
    Oct 3, 2024 · The IonQ team achieved remote entanglement by developing a system to collect photons from two trap wells and routing them to a single detection hub.
  35. [35]
    IonQ Announces Continued Collaboration with Amazon Web ...
    Our extended collaboration aims to provide users with access to IonQ's newest systems, features, and on-demand support through Amazon Braket.
  36. [36]
    IonQ | Trapped Ion Quantum Computing
    Meet our newest and most powerful quantum computers ; IonQ Aria. Our universally accessible, high-performing flagship quantum system ; IonQ Forte. Our highest ...
  37. [37]
    Towards multiqudit quantum processor based on a 171 Yb + ion string
    Oct 31, 2024 · An inherent path to scale trapped-ion-based quantum processors is to use multilevel encoding. Indeed, each of the ions admits encoding not ...
  38. [38]
    Our Trapped Ion Quantum Computers | System Model H2
    Our second-generation trapped-ion system is the highest-performing commercially available quantum computer that leads in quantum volume and has unique ...<|control11|><|separator|>
  39. [39]
    Quantinuum's H-Series hits 56 physical qubits that are all-to-all ...
    Jun 5, 2024 · Quantinuum's H-Series combines full scalability with market-leading fidelity, performance, and error correction capabilities.
  40. [40]
    Experimental Demonstration of High-Fidelity Logical Magic States ...
    Oct 14, 2025 · We experimentally demonstrate this protocol on an ion-trap quantum processor, yielding a logical magic state encoded in an error-correcting code ...
  41. [41]
    Quantinuum's H1 quantum computer successfully executes a fully ...
    The ion trap architecture of our H-Series offers the lowest physical error rates and the flexibility derived from qubit transport, which allows users of our ...<|separator|>
  42. [42]
    Our Trapped Ion Quantum Computers - Quantinuum
    Experience the accuracy, reliability, and performance of the world's most powerful quantum computer | Trapped-ion QCCD processors are proven to scale.Quantinuum System Model H1 · Contact Quantinuum Systems · Helios
  43. [43]
    Oxford Ionics Delivers Quantum Computer to the UK's National ...
    Aug 13, 2025 · QUARTET is a full-stack, trapped-ion quantum computer that leverages Oxford Ionics' proprietary Electronic Qubit Control technology, which ...
  44. [44]
    IonQ Completes Acquisition of Oxford Ionics, Rapidly Accelerating ...
    Sep 17, 2025 · IonQ plans to integrate Oxford Ionics' record-breaking ion trap technology, which is manufactured using standard semiconductor chips, with ...
  45. [45]
    Ion-trap quantum computer ready for novel research and ...
    Sep 16, 2024 · The ion-trap quantum computer from Alpine Quantum Technologies ... The system is based on trapped-ion technology and computes with 20 qubits.
  46. [46]
    EuroHPC JU Inaugurates PIAST-Q: AQT's Trapped-Ion Quantum ...
    Jun 26, 2025 · The EuroHPC Joint Undertaking (EuroHPC JU) has inaugurated PIAST-Q in Poznań, Poland, marking the first operational deployment of a EuroHPC quantum computer.<|separator|>
  47. [47]
    IonQ: The Leader in Trapped-Ion Quantum Computing
    Nov 2, 2025 · ... 2025, IonQ now guides to $82–$100M revenue. If achieved, this would be roughly 80%–150% growth over 2024 (implying a rapid ramp in H2 2025).
  48. [48]
    Quantum Technologies Flagship | Shaping Europe's digital future
    It is funding projects in four core application areas: quantum computing; quantum simulation; quantum communication; quantum sensing and metrology. It also ...Missing: DARPA | Show results with:DARPA
  49. [49]
    EU-Funded QCDC Project Concludes, Launches Cloud-Based ...
    Aug 29, 2025 · The service grants European researchers access to devices from Alpine Quantum Technologies (AQT) to perform advanced quantum computing tasks, ...Missing: DARPA Flagship<|separator|>
  50. [50]
    Crosstalk Suppression in Individually Addressed Two-Qubit Gates in ...
    Dec 7, 2022 · We show that in our laser-driven trapped-ion system coherent crosstalk error can be modeled as residual 𝑋 ⁢ ^ 𝜎 𝜙 interaction and can be ...Missing: instability | Show results with:instability
  51. [51]
    Limits on atomic qubit control from laser noise - Nature
    Jun 27, 2022 · Technical noise present in laser systems can limit their ability to perform high fidelity quantum control of atomic qubits.
  52. [52]
    [2510.17286] Trapped-ion two-qubit gates with >99.99% fidelity ...
    These results indicate that trapped-ion quantum computation can achieve high fidelity at temperatures above the Doppler limit, which enables ...Missing: 2024 | Show results with:2024
  53. [53]
    Architecting Scalable Trapped Ion Quantum Computers using ... - arXiv
    Oct 27, 2025 · We use this compiler to examine how hardware trap capacity, connectivity and electrode wiring choices can be optimised for surface code ...
  54. [54]
    Distributed quantum computing across an optical network link - Nature
    Feb 5, 2025 · Here we experimentally demonstrate the distribution of quantum computations between two photonically interconnected trapped-ion modules.
  55. [55]
    [PDF] Transport of Trapped-Ion Qubits within a Scalable Quantum Processor
    May 9, 2017 · Trapped ions are transported physically between zones in an array to share information, enabling multi-qubit gates. Excitation during transport ...
  56. [56]
    Quantinuum-led Scientists Explore Single-Shot Error Correction to ...
    Aug 20, 2024 · Researchers have successfully demonstrated single-shot quantum error correction on Quantinuum's H2 trapped-ion quantum computer.
  57. [57]
    IonQ's Accelerated Roadmap: Turning Quantum Ambition into Reality
    Jun 13, 2025 · Our modular architecture, linking high-quality qubit traps via photonic interconnects, enables high connectivity and allows for multiple error ...Missing: modularity | Show results with:modularity
  58. [58]
    Hybrid Quantum Systems with Artificial Atoms in Solid State
    Apr 19, 2024 · Current mature quantum computing platforms include trapped ions and superconducting circuits. Trapped ion quantum computing involves the use ...<|separator|>