REVIEW 2 major objections 103 references
Closed-loop control for two-qubit gates with trapped ions
T0 review · 2 major / 0 minor · reviewed 2026-07-02 · grok-4.3
Pith's one-line read A spectator ion monitored by fluorescence enables closed-loop reinforcement learning to correct two-qubit gate disturbances in real time.
desk verdict Spectator-ion monitoring plus RL on geometric phase is a fresh control idea for ion gates, but the order-of-magnitude fidelity claim sits on an untested negligibility assumption with no numbers or simulations shown. read the letter →
The pith
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
The reading
What carries the argument
The stochastic quantum master equation for driven ion-trap dynamics with the spectator ion, together with reinforcement learning whose reward is the actual geometric phase accumulated by that ion.
What would settle it
A direct comparison of Bell-state preparation infidelity measured with and without the spectator ion plus reinforcement-learning correction, confirming whether the reduction reaches an order of magnitude and whether added monitoring noise stays below thermal levels.
Extended reading notes
Core claim
Incorporating a spectator ion into the ion chain allows continuous position monitoring through dipole fluorescence; the resulting data feeds a reinforcement-learning controller that corrects gate errors as they occur, described by a stochastic quantum master equation that includes motional coupling, thermal effects, recoil, spontaneous decay, and light shifts. This closed-loop method is feasible for linear Paul traps and is expected to reduce two-qubit gate Bell-state preparation infidelity by an order of magnitude, with monitoring errors remaining smaller than the thermal motional heating already present in the system.
Load-bearing premise
Continuous position monitoring via dipole fluorescence introduces recoil and spontaneous-decay errors that remain negligible compared with existing thermal motional heating.
Editorial extensions
If this is right
- Two-qubit gates achieve higher fidelity with lower calibration overhead due to on-the-fly correction of small parameter drifts.
- Disturbances occurring during gate operation are learned and compensated in real time rather than relying solely on precomputed open-loop sequences.
- The approach remains practical for existing linear Paul trap hardware without major redesign.
- Reduced sensitivity to motional heating and other trap imperfections follows from the closed-loop feedback.
Reading between the lines
- The method could be tested by adding one extra ion to current multi-ion chains and measuring fidelity improvement under realistic heating rates.
- Similar spectator-ion monitoring might apply to gates in other platforms that support collective modes, such as neutral-atom arrays.
- Extending the reward function to include additional observables could handle error sources beyond those modeled in the master equation.
Signed reviews
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The manuscript proposes a closed-loop control method for two-qubit gates in linear Paul traps that incorporates a spectator ion whose position is continuously monitored via dipole fluorescence. The ion-chain dynamics, including the amplitude-modulation multimode-motional coupling gate, are modeled by a stochastic quantum master equation that incorporates motional drift, thermal heating, photon recoil, spontaneous decay, and light shifts. On-the-fly correction is performed via reinforcement learning whose reward is based on the geometric phase accumulated by the spectator ion. The central claims are that the spectator-ion approach is feasible for existing trap hardware and yields an order-of-magnitude reduction in Bell-state preparation infidelity while the additional decoherence channels introduced by fluorescence monitoring remain negligible compared with existing thermal rates.
Significance. If the quantitative claims are substantiated, the work would constitute a meaningful step toward adaptive, disturbance-correcting two-qubit gates in trapped-ion processors, potentially lowering calibration overhead and improving fidelity in the presence of slow parameter drift. The combination of a spectator-ion sensor with reinforcement-learning control is a distinctive architectural choice that could be extended to other platforms.
major comments (2)
- [Abstract] Abstract: the claim that position monitoring introduces recoil and spontaneous-decay errors that are negligible relative to thermal motional heating is asserted without any numerical comparison (e.g., scattering rate Γ_sc versus heating rate Ṅ_thermal, or integrated phase noise over the gate duration). The stochastic master equation is stated to include these Lindblad terms, yet no solution, error budget, or sensitivity scan is supplied to demonstrate the negligibility assumption that underpins the order-of-magnitude infidelity reduction.
- [Abstract] Abstract (paragraph describing the stochastic master equation): the central quantitative assertion—an order-of-magnitude reduction in Bell-state infidelity—is presented as a demonstrated result, but the manuscript supplies neither explicit numerical integration of the master equation nor RL training curves or final infidelity values. Without these data the feasibility and performance claims rest on an unshown derivation.
Simulated Author's Rebuttal
We thank the referee for their thorough review and constructive suggestions. We address the two major comments point-by-point below and will revise the manuscript to incorporate additional numerical comparisons and explicit data references as requested.
read point-by-point responses
-
Referee: [Abstract] Abstract: the claim that position monitoring introduces recoil and spontaneous-decay errors that are negligible relative to thermal motional heating is asserted without any numerical comparison (e.g., scattering rate Γ_sc versus heating rate Ṅ_thermal, or integrated phase noise over the gate duration). The stochastic master equation is stated to include these Lindblad terms, yet no solution, error budget, or sensitivity scan is supplied to demonstrate the negligibility assumption that underpins the order-of-magnitude infidelity reduction.
Authors: We agree that the abstract would benefit from a concise numerical comparison to support the negligibility statement. In the revised manuscript we will add explicit values (e.g., Γ_sc / Ṅ_thermal ratio and an estimate of integrated phase noise over the gate duration) drawn from the existing stochastic-master-equation solutions already presented in Sections 3–4. A short error-budget paragraph will be inserted so that the assumption is quantitatively justified rather than asserted. revision: yes
-
Referee: [Abstract] Abstract (paragraph describing the stochastic master equation): the central quantitative assertion—an order-of-magnitude reduction in Bell-state infidelity—is presented as a demonstrated result, but the manuscript supplies neither explicit numerical integration of the master equation nor RL training curves or final infidelity values. Without these data the feasibility and performance claims rest on an unshown derivation.
Authors: The full manuscript contains the stochastic-master-equation integrations and RL training results that yield the reported infidelity reduction; however, these are not summarized numerically in the abstract. We will revise the abstract to include a brief statement of the key quantitative outcomes (final Bell-state infidelity before/after control and the reduction factor) together with explicit references to the relevant figures and sections that display the training curves and master-equation solutions. This will make the demonstrated result transparent without changing the underlying analysis. revision: yes
Circularity Check
No circularity: proposal relies on independent modeling assumptions and RL optimization, not self-referential derivations.
full rationale
The paper presents a forward-looking proposal for closed-loop control of two-qubit gates via a spectator ion, stochastic master equation dynamics (including recoil, decay, and thermal terms), and reinforcement learning based on geometric phase. No equations reduce a claimed prediction to a fitted input by construction, no self-citations are invoked as load-bearing uniqueness theorems, and no ansatz or result is smuggled via prior author work. The negligibility of monitoring errors relative to thermal heating is an explicit modeling assumption rather than a derived output, and the infidelity reduction is stated as an expectation from simulation, not a tautological renaming or self-definition. The derivation chain is self-contained against external benchmarks.
Assumptions & free parameters
Cite this review
Pith. "Pith review of Closed-loop control for two-qubit gates with trapped ions." pith.science (2026). https://pith.science/paper/3X6HJMSL
@misc{pith2026260700462,
author = {Pith},
title = {Pith review of: Closed-loop control for two-qubit gates with trapped ions},
year = {2026},
howpublished = {\url{https://pith.science/paper/3X6HJMSL}},
note = {Machine review of arXiv:2607.00462}
}
read the original abstract
State-of-the-art two-qubit gates with trapped ions employ open-loop control that rely on simplified models to precompute control sequences. Our aim is to introduce closed-loop control for two-qubit gates to correct disturbances as they occur during the gate implementation. We introduce a spectator ion into the ion chain used for quantum logic processing, where it couples with the other ions through collective motional modes. The spectator ion's position is continuously monitored by driving dipole transitions and detecting the resultant fluorescence. We show that incorporating a spectator ion is feasible for linear Paul trap implementations and is expected to reduce the two-qubit gate Bell-state preparation infidelity by an order of magnitude with the deleterious effects of position monitoring being negligible compared to the thermal effects that exist in the system, even in the absence of the spectator ions. Mathematically, we describe driven ion-trap dynamics, including the spectator ion, by a stochastic quantum master equation involving the amplitude-modulation multimode-motional coupling gate, motional drift, thermal effects, recoil from photon scattering, spontaneous decay, and light shift. Our on-the-fly control method employs reinforcement learning with the reward function based on the actual geometric phase of the spectator ion. A key advantage of our approach is that we introduce a control method that involves `learning' and correcting disturbances happening in the trap on-the-fly, thus achieving high-fidelity gates. Our approach will lead to a significantly higher two-qubit gate fidelity at a reduced calibration overhead owing to the small parameter drift in the control system.
Figures
Figures from the paper (6 more)
Reference graph
Works this paper leans on
-
[1]
Control elements We employ the definitions of the plant, controller, and policy as given in [21]. The plant comprises (i) all the elements necessary to load, stabilise, and cool the ion- crystal; (ii) all devices necessary to generate, stabilise, reference, and redirect laser light towards the ion crystal; (iii) all devices and parts necessary to generate...
-
[2]
, N+ 1},(6) where the last ion is the spectator
Model description A linear Paul trap confinesN+ 1 alkali-like ions, with labels ȷ∈[N+ 1] :={1, . . . , N+ 1},(6) where the last ion is the spectator. The ions are pre- pared in an electronic (meta)stable stationary state|0⟩. The spectator ion is treated as described in§II B. The remaining ions are used for information processing. Any pair of ions are used...
-
[3]
Simulated ion-trap environment We employ quantum trajectory theory (QTT) to un- ravel the QME for the 2QG gate design. This method allows us to reduce the complexity fromN 2 to 2Nimply- ing a significant reduction in time and memory to solve the QME. Another crucial reason is that we can ascribe a subjective degree of reality to each quantum trajectory so...
-
[4]
Hamiltonian The HamiltonianH s must be expressed in the interac- tion picture, similar to the AM-MMC HamiltonianH SM in Eq. (3). The transformation of the motional part into the interaction picture is standard and it is equivalent to a transformation from the Schr¨ odinger to Heisenberg pic- ture. The transformation is complete by simply changing notation...
-
[5]
Noise and decoherence Sources such as the AT and motional Bloch–Siegert shifts depend on the intensity of the bichromatic fields. The former is modelled by adding an offset to the ef- fective frequency of the bichromatic field, whose value isα(ω 0,1)Ω2, whereα(ω 0,1) is the effective scalar con- tribution between the hyperfine levels|m F = 0, F= 0⟩ and|m ...
-
[6]
Impact of position-monitoring of spectator ion We use the truncated Dyson series, givenTas the time ordering operator U=1−i Z t 0 dt1H(t1) − 1 2 T Z t 0 Z t 0 dt1dt2H(t1)H(t2) +O(t 3),(11) whereOis the round-off error due to higher-order terms in the series, which determines the evolution of Eq. (9). The resulting terms of the series allow us to quantify ...
-
[7]
Casting 2QG design as learning We introduce continuous monitoring of the spectator ion in a chain ofN+ 1 ions to reconstructα ȷk(t) in real- time. This information is used to devise robust control policies for implementing 2QG against motional heating, drift in motional frequencies, and scattering processes. We also discretise time by introducing a time m...
-
[8]
Choice of reinforcement learning heuristic The motivation is to have an algorithm with data effi- ciency and reliable performance of a trusted region policy optimisation algorithm (TRPO) [17], while using only a first-order expansion. We pass (x, p) to a RL algorithm called Proximal Policy Optimisation (PPO) [64] to con- fection policies. The search for a...
Show all 103 references
-
[9]
Cost function We approach the training from a different angle based on the actual observation of thephase-spacetrajectories and the hypothetically actual geometric phase. The gist of this approach lies in providing to the learning agent a sense of the intensity of the laser be...
-
[10]
Signal rate The maximal slope of the standing wave between the back mirror and the spectator ion plays a crucial role in position-monitoring schemes. The Rabi strength in- creases linearly with the electric field in a standing wave configuration; hence, a displacement of 1 nm ...
-
[11]
Signal latency and processing time The total path travelled by fluorescence photons until they reach the photodetector, as illustrated in Fig. (2). The photon travel time until it reaches the spectator ion is 1.6 ns and 2.4 ns more to the photodetector. From the information ab...
-
[12]
The compu- tation is performed continuously, mimicking continuous monitoring, although the actions are taken at intervals ∆ti
Reconstruction of phase-space trajectories In our control scheme, the position and momentum of the motional modes are extracted from the wave-vector state resolved using quantum trajectories. The compu- tation is performed continuously, mimicking continuous monitoring, althoug...
-
[13]
Impact of spin coupling In this work, we demonstrate the validity of our control scheme in a three-ion chain confined in a linear Paul trap, whose transverse motional frequencies along the x–axis are νx ∈ {4.3807,4.3414,4.2857}MHz.(18) 11 The gate is mediated via transverse mo...
-
[14]
The type of ex- citation that takes place here involves a different tran- sition from the Raman lasers on the gate ions, namely, the 2S1/2–2P1/2 dipole transition
Motion-mediated entanglement The motional modes are also excited via dipole- transition driving of the spectator ion. The type of ex- citation that takes place here involves a different tran- sition from the Raman lasers on the gate ions, namely, the 2S1/2–2P1/2 dipole transit...
-
[15]
Impact of mirror-mode coupling The motion of the spectator ion gets coupled to the mirror mode via its dipole momentd eg and the quantum noise operatorb m. In the regime where the photon flight- time is much smaller than the natural decay rate of the dipole transition 1S1/2–2P...
-
[16]
Additionally, we in- corporate the carrier term, AT and BS energy shifts, and motional heating at rates Γ H = 100 s −1 for all motional modes
Reinforcement-learning agent training We train the RL agent by running quantum trajecto- ries with the corresponding jump operator for position monitoring at ΓCLPM = 2×10 5 s−1. Additionally, we in- corporate the carrier term, AT and BS energy shifts, and motional heating at r...
-
[17]
In our case, we let the algorithm to only observe thephase-spacetra- jectories and execute actions but with no reward until the end of the gate durationτ g
2QG employing episodic rewards An episodic approach is always interesting to observe in any reinforcement learning application. In our case, we let the algorithm to only observe thephase-spacetra- jectories and execute actions but with no reward until the end of the gate durat...
-
[18]
2QG employing geometric phase In Fig. 9 we can observe the average nin-segment pulse delivering minI= 14×10 −4 and ¯I= 85×10 −4.The benefits of employing less power are even more present in this scenario, additionally, we observe the trend of a Bell-like shape to some extent, ...
-
[19]
[16, 40, 56, 57]
Test 1: thermal effects As the fundamental position measurement block has been experimentally realised, we refer the reader to Refs. [16, 40, 56, 57]. The central idea of this stage is to gather information about the fluorescence signal strength and cooling effects in a three-...
-
[20]
4, 5, and 6
Test 2: induced perturbative errors The core idea here is to perturb the gate implementa- tion and reproduce the errors in the 2QG infidelity, as shown in Figs. 4, 5, and 6. As these three effects are always present, they cannot be completely isolated from one another. This re...
-
[21]
Here, the task at hand involves an experimen- tal validation [15] of the 2QG implementation
Validation: error mitigation In this last stage, the experimenter effectively closes the control loop by implementing a 2QG, whose learning agent has been previously trained in our simulated envi- ronment. Here, the task at hand involves an experimen- tal validation [15] of th...
-
[22]
L. Egan, D. M. Debroy, C. Noel, A. Risinger, D. Zhu, D. Biswas, M. Newman, M. Li, K. R. Brown, M. Cetina, and C. Monroe, Fault-tolerant control of an error- corrected qubit, Nature598, 281 (2021)
2021
-
[23]
Srinivas, S
R. Srinivas, S. C. Burd, H. M. Knaack, R. T. Sutherland, A. Kwiatkowski, S. Glancy, E. Knill, D. J. Wineland, D. Leibfried, A. C. Wilson, D. T. C. Allcock, and D. H. Slichter, High-fidelity laser-free universal control of trapped ion qubits, Nature597, 209 (2021)
2021
-
[24]
D. T. C. Allcock, W. C. Campbell, J. Chiaverini, I. L. Chuang, E. R. Hudson, I. D. Moore, A. Ransford, C. Ro- man, J. M. Sage, and D. J. Wineland,omgblueprint for trapped ion quantum computing with metastable states, Appl. Phys. Lett.119, 214002 (2021)
2021
-
[25]
J.-S. Chen, E. Nielsen, M. Ebert, V. Inlek, K. Wright, V. Chaplin, A. Maksymov, E. P´ aez, A. Poudel, P. Maunz, and J. Gamble, Benchmarking a trapped-ion quantum computer with 30 qubits, Quantum8, 1516 (2024)
2024
-
[26]
Bl¨ umel, A
R. Bl¨ umel, A. Maksymov, and M. Li, Toward a Mølmer Sørensen gate with .9999 fidelity, J. Phys. B57, 205501 (2024)
2024
-
[27]
Ransford, M
A. Ransford, M. S. Allman, J. Arkinstall, and et al., A 98-qubit trapped-ion quantum computer with all-to-all connectivity, Nature , 1 (2026)
2026
-
[28]
T. Choi, S. Debnath, T. A. Manning, C. Figgatt, Z.- X. Gong, L.-M. Duan, and C. Monroe, Optimal quan- tum control of multimode couplings between trapped ion qubits for scalable entanglement, Phys. Rev. Lett.112, 190502 (2014)
2014
-
[29]
Wright, K
K. Wright, K. M. Beck, S. Debnath, J. M. Amini, Y. Nam, N. Grzesiak, J.-S. Chen, N. C. Pisenti, M. Chmielewski, C. Collins, K. M. Hudek, J. Mizrahi, J. D. Wong-Campos, S. Allen, J. Apisdorf, P. Solomon, M. Williams, A. M. Ducore, A. Blinov, S. M. Kreike- meier, V. Chaplin, M. ...
2019
-
[30]
J. P. Gaebler, T. R. Tan, Y. Lin, Y. Wan, R. Bowler, A. C. Keith, S. Glancy, K. Coakley, E. Knill, D. Leibfried, and D. J. Wineland, High-fidelity universal gate set for 9Be+ ion qubits, Phys. Rev. Lett.117, 060505 (2016)
2016
-
[31]
M. Kang, Y. Wang, C. Fang, B. Zhang, O. Khosravani, J. Kim, and K. R. Brown, Designing Filter Functions of Frequency-Modulated Pulses for High-Fidelity Two- Qubit Gates in Ion Chains, Phys. Rev. Appl.19, 014014 (2023)
2023
-
[32]
C. R. Clark, H. N. Tinkey, B. C. Sawyer, A. M. Meier, K. A. Burkhardt, C. M. Seck, C. M. Shappert, N. D. Guise, C. E. Volin, S. D. Fallek, H. T. Hayden, W. G. Rel- lergert, and K. R. Brown, High-fidelity Bell-state prepa- ration with 40Ca+ optical qubits, Phys. Rev. Lett.127, ...
2021
-
[33]
C. J. Ballance, T. P. Harty, N. M. Linke, M. A. Sepiol, and D. M. Lucas, High-fidelity quantum logic gates us- ing trapped-ion hyperfine qubits, Phys. Rev. Lett.117, 060504 (2016)
2016
-
[34]
Kumar, N
S. Kumar, N. N. Hegade, M. Henrique de Oliveira, E. Solano, A. Gomez Cadavid, and F. Albarr´ an- Arriagada, Digital-analog counterdiabatic quantum op- timization with trapped ions, Quantum Sci. Technol.10, 015023 (2024)
2024
-
[35]
Ellert-Beck and W
L. Ellert-Beck and W. Ge, Power-optimized amplitude modulation for robust trapped-ion entangling gates: A study of gate-timing errors, Phys. Rev. A111, 062422 (2025)
2025
-
[36]
S. S. Vedaie, E. J. P´ aez, N. H. Nguyen, N. M. Linke, and B. C. Sanders, Bespoke pulse design for robust rapid two- qubit gates with trapped ions, Phys. Rev. Res.5, 023098 (2023)
2023
-
[37]
Cerchiari, G
G. Cerchiari, G. Araneda, L. Podhora, L. Slodiˇ cka, Y. Colombe, and R. Blatt, Measuring ion oscillations at the quantum level with fluorescence light, Phys. Rev. Lett.127, 063603 (2021)
2021
-
[38]
Li and H
H. Li and H. He, Multiagent trust region policy opti- mization, IEEE Transactions on Neural Networks and Learning Systems35, 12873
-
[39]
Y. Wang, H. He, and X. Tan, Truly proximal policy opti- mization, inProceedings of The 35th Uncertainty in Ar- tificial Intelligence Conference, Proceedings of Machine Learning Research, Vol. 115, edited by R. P. Adams and V. Gogate (PMLR, 2020) pp. 113–122
2020
-
[40]
C. D. Bruzewicz, J. Chiaverini, R. McConnell, and J. M. Sage, Trapped-ion quantum computing: Progress and challenges, Appl. Phys. Rev.6, 021314 (2019)
2019
-
[41]
A. R. Milne, C. L. Edmunds, C. Hempel, F. Roy, S. Mavadia, and M. J. Biercuk, Phase-modulated entan- gling gates robust to static and time-varying errors, Phys. Rev. Appl.13, 024022 (2020)
2020
-
[42]
S. S. Vedaie, A. Dalal, E. J. P´ aez, and B. C. Sanders, Framework for learning and control in the classical and 18 quantum domains, Ann. Phys. (N. Y.)458, 169471 (2023)
2023
-
[43]
Jacobs and D
K. Jacobs and D. A. Steck, A straightforward intro- duction to continuous quantum measurement, Contemp. Phys.47, 279 (2006)
2006
-
[44]
C. W. Gardiner and M. J. Collett, Input and output in damped quantum systems: Quantum stochastic differen- tial equations and the master equation, Phys. Rev. A31, 3761 (1985)
1985
-
[45]
Bouten, R
L. Bouten, R. Van Handel, and M. R. James, An intro- duction to quantum filtering, SIAM J. Control Optim. 46, 2199 (2007)
2007
-
[46]
Eschner, C
J. Eschner, C. Raab, F. Schmidt-Kaler, and R. Blatt, Light interference from single atoms and their mirror im- ages, Nature413, 495 (2001)
2001
-
[47]
Bushev, D
P. Bushev, D. Rotter, A. Wilson, F. m. c. Dubin, C. Becher, J. Eschner, R. Blatt, V. Steixner, P. Rabl, and P. Zoller, Feedback cooling of a single trapped ion, Phys. Rev. Lett.96, 043003 (2006)
2006
-
[48]
Z. K. Minev, S. O. Mundhada, S. Shankar, P. Rein- hold, R. Guti´ errez-J´ auregui, R. J. Schoelkopf, M. Mir- rahimi, H. J. Carmichael, and M. H. Devoret, To catch and reverse a quantum jump mid-flight, Nature570, 200 (2019)
2019
-
[49]
Defenu, T
N. Defenu, T. Donner, T. Macr` ı, G. Pagano, S. Ruffo, and A. Trombettoni, Long-range interacting quantum systems, Rev. Mod. Phys.95, 035002 (2023)
2023
-
[50]
Morigi, J
G. Morigi, J. Eschner, and C. H. Keitel, Ground state laser cooling using electromagnetically induced trans- parency, Phys. Rev. Lett.85, 4458 (2000), arXiv:quant- ph/0005009
2000
-
[51]
Evers and C
J. Evers and C. H. Keitel, Double-EIT ground-state laser cooling withoutblue-sideband heating, Europhys. Lett. 68, 370 (2004)
2004
-
[52]
Debnath, N
S. Debnath, N. M. Linke, C. Figgatt, K. A. Landsman, K. Wright, and C. Monroe, Demonstration of a small programmable quantum computer with atomic qubits, Nature536, 63 (2016)
2016
-
[53]
P. H. Leung, K. A. Landsman, C. Figgatt, N. M. Linke, C. Monroe, and K. R. Brown, Robust 2-qubit gates in a linear ion crystal using a frequency-modulated driving force, Phys. Rev. Lett.120, 020501 (2018)
2018
-
[54]
Monroe, W
C. Monroe, W. C. Campbell, L.-M. Duan, Z.-X. Gong, A. V. Gorshkov, P. W. Hess, R. Islam, K. Kim, N. M. Linke, G. Pagano, P. Richerme, C. Senko, and N. Y. Yao, Programmable quantum simulations of spin systems with trapped ions, Rev. Mod. Phys.93, 025001 (2021)
2021
-
[55]
K. R. Islam,Quantum Simulation of Interacting Spin Models with Trapped Ions, Ph.D. thesis, University of Maryland (2012)
2012
-
[56]
Motlakunta, N
S. Motlakunta, N. Kotibhaskar, C.-Y. Shih, A. Vogliano, D. McLaren, L. Hahn, J. Zhu, R. Habl¨ utzel, and R. Islam, Preserving a qubit during state-destroying operations on an adjacent qubit at a few micrometers distance, Nat. Commun.15, 6575 (2024)
2024
-
[57]
R. S. Gupta, L. C. G. Govia, and M. J. Biercuk, Integra- tion of spectator qubits into quantum computer architec- tures for hardware tune-up and calibration, Phy. Rev. A 102, 042611 (2020)
2020
-
[58]
R. S. Gupta, C. L. Edmunds, A. R. Milne, C. Hempel, and M. J. Biercuk, Adaptive characterization of spatially inhomogeneous fields and errors in qubit registers, npj Quantum. Inf.6, 53 (2020)
2020
-
[59]
S. N. Miao, H. R. Qin, N. C. Xin, J. Z. Han, Y. T. Chen, J. W. Zhang, and L. J. Wang, Sympathetic cooling of a large 113Cd+ ion crystal with 40ca+ in a linear Paul trap, Chinese Journal of Physics83, 242 (2023)
2023
-
[60]
J. J. Wu, P.-Y. Hou, S. D. Erickson, A. D. Brandt, Y. Wan, G. Zarantonello, D. C. Cole, A. C. Wilson, D. H. Slichter, and D. Leibfried, Electromagnetically-induced- transparency cooling with a tripod structure in a hyper- fine trapped ion with mixed-species crystals, Phys. Rev...
2025
-
[61]
Steixner, P
V. Steixner, P. Rabl, and P. Zoller, Quantum feedback cooling of a single trapped ion in front of a mirror, Phys. Rev. A72, 043826 (2005)
2005
-
[62]
Slodiˇ cka, G
L. Slodiˇ cka, G. H´ etet, N. R¨ ock, S. Gerber, P. Schindler, M. Kumph, M. Hennrich, and R. Blatt, Interferometric thermometry of a single sub-Doppler-cooled atom, Phys. Rev. A85, 043401 (2012)
2012
-
[63]
Zhang, W
S. Zhang, W. Wu, C.-W. Wu, F.-G. Li, T. Li, X. Wang, and W.-S. Bao, Quantum feedback cooling of two trapped ions, Chin. Phys. B26, 074205
-
[64]
N. M. Linke, D. Maslov, M. Roetteler, S. Debnath, C. Figgatt, K. A. Landsman, K. Wright, and C. Monroe, Experimental comparison of two quantum computing ar- chitectures, Proc. Natl. Acad. Sci. U. S. A.114, 3305 (2017)
2017
-
[65]
Leibfried, B
D. Leibfried, B. DeMarco, V. Meyer, D. Lucas, M. Bar- rett, J. Britton, W. M. Itano, B. Jelenkovi´ c, C. Langer, T. Rosenband, and D. J. Wineland, Experimental demonstration of a robust, high-fidelity geometric two ion-qubit phase gate, Nature422, 412 (2003)
2003
-
[66]
Q. A. Turchette, C. J. Myatt, B. E. King, C. A. Sack- ett, D. Kielpinski, W. M. Itano, C. Monroe, and D. J. Wineland, Decoherence and decay of motional quantum states of a trapped atom coupled to engineered reservoirs, Phys. Rev. A62, 053807 (2000)
2000
-
[67]
Ozeri, W
R. Ozeri, W. M. Itano, R. B. Blakestad, J. Britton, J. Chiaverini, J. D. Jost, C. Langer, D. Leibfried, R. Re- ichle, S. Seidelin, J. H. Wesenberg, and D. J. Wineland, Errors in trapped-ion quantum gates due to spontaneous photon scattering, Phys. Rev. A75, 042329 (2007)
2007
-
[68]
Gardiner and P
C. Gardiner and P. Zoller,Quantum noise: A handbook of Markovian and non-Markovian quantum stochastic meth- ods with applications to quantum optics, 3rd ed., Springer Series in Synergetics (Springer Science & Business Media, Berlin, 2004)
2004
-
[69]
Tanimura, Stochastic Liouville, Langevin, Fokker–Planck, and master equation approaches to quantum dissipative systems, J
Y. Tanimura, Stochastic Liouville, Langevin, Fokker–Planck, and master equation approaches to quantum dissipative systems, J. Phys. Soc. Japan75, 082001 (2006)
2006
-
[70]
D. J. Wineland, C. Monroe, W. M. Itano, D. Leibfried, B. E. King, and D. M. Meekhof, Experimental issues in coherent quantum-state manipulation of trapped atomic ions, J. Res. Natl. Inst. Stand. Technol.103, 259 (1998)
1998
-
[71]
H¨ affner, C
H. H¨ affner, C. Roos, and R. Blatt, Quantum computing with trapped ions, Phys. Rep.469, 155 (2008)
2008
-
[72]
Carmichael,An open systems approach to quantum optics: lectures presented at the Universit´ e Libre de Brux- elles, October 28 to November 4, 1991, Vol
H. Carmichael,An open systems approach to quantum optics: lectures presented at the Universit´ e Libre de Brux- elles, October 28 to November 4, 1991, Vol. 18 (Springer Science and Business Media, 2009)
1991
-
[73]
T. A. Brun, Continuous measurements, quantum trajec- tories, and decoherent histories, Phys. Rev. A61, 042107 (2000)
2000
-
[74]
Gisin and I
N. Gisin and I. C. Percival, The quantum-state diffusion model applied to open systems, J. Phys. A Math. Gen. 19 25, 5677 (1992)
1992
-
[75]
Weiser, T
Y. Weiser, T. Faorlin, L. Panzl, T. Lafenthaler, L. Dania, D. S. Bykov, T. Monz, R. Blatt, and G. Cerchiari, Back- action suppression for levitated dipolar scatterers, Phys. Rev. A111, 013503 (2025)
2025
-
[76]
Cerchiari, L
G. Cerchiari, L. Dania, D. S. Bykov, R. Blatt, and T. E. Northup, Position measurement of a dipolar scatterer via self-homodyne detection, Phys. Rev. A104, 053523 (2021)
2021
-
[77]
Cerchiari, G
G. Cerchiari, G. Araneda, L. Podhora, L. Slodiˇ cka, Y. Colombe, and R. Blatt, Motion analysis of a trapped ion chain by single photon self-interference, Appl. Phys. Lett.119, 024003 (2021)
2021
-
[78]
Dania, K
L. Dania, K. Heidegger, D. S. Bykov, G. Cerchiari, G. Araneda, and T. E. Northup, Position measurement of a levitated nanoparticle via interference with its mirror image, Phys. Rev. Lett.129, 013601 (2022)
2022
-
[79]
Bushev, G
P. Bushev, G. H´ etet, L. Slodiˇ cka, D. Rotter, M. A. Wil- son, F. Schmidt-Kaler, J. Eschner, and R. Blatt, Shot- noise-limited monitoring and phase locking of the motion of a single trapped ion, Phys. Rev. Lett.110, 133602 (2013)
2013
-
[80]
Tebbenjohanns, M
F. Tebbenjohanns, M. Frimmer, and L. Novotny, Optimal position detection of a dipolar scatterer in a focused field, Phys. Rev. A100, 043821 (2019)
2019
-
[81]
Z.-q. Yin, A. A. Geraci, and T. Li, Optomechanics of levitated dielectric particles, Int. J. Mod. Phys. B27, 1330018 (2013)
2013
-
[82]
A. D. Ludlow, M. M. Boyd, J. Ye, E. Peik, and P. Schmidt, Optical atomic clocks, Reviews of Modern Physics87, 637 (2015)
2015
-
[83]
Schack and T
R. Schack and T. A. Brun, A C++ library using quantum trajectories to solve quantum master equations, Comput. Phys. Commun.102, 210 (1997)
1997
-
[84]
S.-L. Zhu, C. Monroe, and L.-M. Duan, Arbitrary-speed quantum gates within large ion crystals through mini- mum control of laser beams, EPL73, 485 (2006)
2006
-
[85]
Schulman, F
J. Schulman, F. Wolski, P. Dhariwal, A. Radford, and O. Klimov, Proximal policy optimization algorithms (2017), arXiv:1707.06347 [cs.LG]
2017 arXiv
-
[86]
Dorner and P
U. Dorner and P. Zoller, Laser-driven atoms in half- cavities, Phys. Rev. A66, 023816 (2002)
2002
-
[87]
H. M. Wiseman, Quantum theory of continuous feedback, Phys. Rev. A49, 2133 (1994)
1994
-
[88]
Sørensen and K
A. Sørensen and K. Mølmer, Quantum computation with ions in thermal motion, Phys. Rev. Lett.82, 1971 (1999)
1971
-
[89]
Sørensen and K
A. Sørensen and K. Mølmer, Entanglement and quantum computation with ions in thermal motion, Phys. Rev. A 62, 022311 (2000)
2000
-
[90]
McCloskey and N
M. McCloskey and N. J. Cohen, Catastrophic interfer- ence in connectionist networks: The sequential learn- ing problem, inPsychology of Learning and Motivation, Vol. 24, edited by G. H. Bower (Academic Press, 1989) pp. 109–165
1989
-
[91]
R. M. French, Catastrophic forgetting in connectionist networks, Trends in Cognitive Sciences3, 128 (1999)
1999
-
[92]
Robins, Catastrophic forgetting, rehearsal and pseu- dorehearsal, Connection Science7, 123 (1995)
A. Robins, Catastrophic forgetting, rehearsal and pseu- dorehearsal, Connection Science7, 123 (1995)
1995
-
[93]
Atkinson, B
C. Atkinson, B. McCane, L. Szymanski, and A. Robins, Pseudo-rehearsal: Achieving deep reinforcement learning without catastrophic forgetting, Neurocomputing428, 291 (2021)
2021
-
[94]
Kirkpatrick, R
J. Kirkpatrick, R. Pascanu, N. Rabinowitz, J. Veness, G. Desjardins, A. A. Rusu, K. Milan, J. Quan, T. Ra- malho, A. Grabska-Barwinska, D. Hassabis, C. Clopath, D. Kumaran, and R. Hadsell, Overcoming catastrophic forgetting in neural networks, Proceedings of the Na- tional Aca...
2017
-
[95]
G. I. Parisi, R. Kemker, J. L. Part, C. Kanan, and S. Wermter, Continual lifelong learning with neural net- works: A review, Neural Networks113, 54 (2019)
2019
-
[96]
Nottbeck, Noel, Schmitt, Christian, and B¨ uscher, Volker, Highly performant, deep neural networks with sub- microsecond latency on FPGAs for trigger applications, EPJ Web Conf.245, 01023 (2020)
2020
-
[97]
Zhang, J
X. Zhang, J. Wang, C. Zhu, Y. Lin, J. Xiong, W.-m. Hwu, and D. Chen, DNNBuilder: an automated tool for building high-performance dnn hardware accelerators for FPGAs, in2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)(2018) pp. 1–8
2018
-
[98]
N. M. Linke, private communication (2022)
2022
-
[99]
L. P. Hughston and L. A. Meng¨ ut¨ urk, Martingale pro- jections and quantum decoherence, J. Phys. A: Math. Theor.59, 105304 (2026)
2026
-
[100]
D. C. Brody and L. P. Hughston, Decoherence implies information gain, Phys. Rev. Res.7(2025). 20 Appendix A: Errors onIdue to position-monitoring of a spectator ion We use the truncated Dyson series, ifTis the time ordering operator U=1−i Z t 0 dt1H(t1)− 1 2 T Z t 0 dt1 Z t 0 ...
2025
-
[101]
Let us takeAfromH(t 1) andBfromH(t 2) according to Eq
Gate ions and spectator spin interaction Because the terms A and C involved in this interaction commute, the time-ordering operator can be dropped to simplify notation. Let us takeAfromH(t 1) andBfromH(t 2) according to Eq. A1 and usingβ s =k sˆxs, then we obtain IAC =− Ωs 2 X...
-
[102]
Motion-mediated entanglement Because the motion of the spectator is excited by an external laser (terms B and C), this disrupts the collective mode of motion during an ideal 2QG gate implementation, and the extent of the disruption depends on the strength and duration of the i...
-
[103]
Mirror-modes entanglement A careful inspection (terms B and D) reveals that the motion of the ion is coupled to the mirror mode via the quantum noise operatorb m as a consequence of the light reflected from the back mirror. In the regime where the light travel is much smaller ...
Reviewed July 2, 2026 · model on record in the stance chip above.
Discussion (0). Continue with ORCID to comment.