Pith. sign in

REVIEW 3 major objections 4 minor 3 cited by

Optimal Control for Open Quantum System in Circuit Quantum Electrodynamics

T0 review · 3 major / 4 minor · reviewed 2026-08-10 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read A driven-dissipative LC resonator can be controlled by closed-form Pontryagin-optimal pulses whose energy cost saturates at a constant, and the same pulses give dispersive qubit readout with SNR comparable to longitudinal coupling at…

desk verdict The readout idea has some merit, but neither central analytical formula solves the stated problem, so the paper is not ready for referees. read the letter →

arxiv 2412.20149 v1 pith:LN3O63WX submitted 2024-12-28 quant-ph

Mo Zhou , F. A. Cárdenas-López , Sugny Dominique , Xi Chen This is my paper · ORCID
classification quant-ph
keywords quantumoptimalcontrolPontryaginmaximumprincipleopensystemsLangevinequationcircuitelectrodynamicsdispersivequbitreadoutsignal-to-noiseratioshortcutstoadiabaticity
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper tries to show that the driven-dissipative dynamics of an LC resonator coupled to a transmission line is not just numerically optimizable: its Langevin equation is a linear control system, and the Pontryagin Maximum Principle solves it in closed form. The energy-optimal pulses reach a target coherent state with an energy cost that saturates at $4\kappa|\alpha(t_f)|^2$ in the long-time limit, while standard Hahn and counter-diabatic pulses keep paying an energy cost that grows with time. The time-optimal pulses reach microsecond-scale transfer times under a maximum-amplitude constraint, which matters for practical drive-line limits. Reusing the same pulses in a dispersively coupled qubit-resonator system produces a readout signal-to-noise ratio that, for large critical photon numbers, is comparable to longitudinal-coupling readout within a time shorter than the cavity decay time. The paper itself flags that at $\bar n_{\rm crit}=1$ the coupling is so strong that Kerr nonlinearities dominate, so the linear model behind that case's IQ trajectory and SNR is not justified.

What carries the argument

The machinery is the linear-control interpretation of the quantum Langevin equation, $\dot x=\hat A x+\hat B u$, with state $x=(x_1,x_2)=(\mathrm{Re}\,\alpha,\mathrm{Im}\,\alpha)$, matrix $\hat A$ containing the damping $-\kappa/2$ and the rotation $\omega_r$, and control $u=(\varepsilon_1,\varepsilon_2)$. The Pontryagin Hamiltonian for energy, $H_c=u^Tu+p^T\dot x$, gives the stationarity condition $u=\hat B^T p$, and the adjoint equation $\dot p=-\hat A^T p$ turns the boundary-value problem into the explicit pulse $u_{\rm opt}(t)=\hat B^T e^{\hat A^T(t_f-t)}p(0)$, where $p(0)$ is fixed by the target state through a Gramian matrix that enforces the final boundary condition. For time minimization, the same Hamiltonian with cost $J_T=t_f$ and the amplitude constraint yields the phase $\phi_{\rm opt}(t)=\omega_r t+\theta$ and the closed trajectory for $\alpha_{\rm opt}(t)$. For readout, the substitution $\omega_r\to\chi_z$ with $\chi_z=\pm\chi$ carries the whole single-resonator solution over to the dispersive qubit-cavity system, so the pointer-state separation and the SNR are computed from the same analytic formulas.

What would settle it

A calibrated homodyne measurement of the output field from a driven damped cavity, with $\kappa$, $\omega_r$, and $\varepsilon(t)$ independently verified, should reproduce the analytic $\alpha_{\rm out}(t)$ from the input-output relation; a systematic discrepancy that grows with the qubit-resonator coupling $g$—already visible by $\bar n_{\rm crit}=1$—would falsify the linear-model readout claim.

Watch

Extended reading notes

Core claim

On the paper's own terms, the central discovery is that a dissipative cavity in circuit QED is not merely optimizable numerically: its Langevin equation is a linear control system, and the Pontryagin Maximum Principle solves that system in closed form for both cost functions. The energy-optimal drive $u_{\rm opt}(t)=\hat B^T e^{\hat A^T(t_f-t)}p(0)$ has cost $J_E^{\rm opt}(t_f)=4\kappa|\alpha(t_f)|^2/(1-e^{-\kappa t_f})$, which stays at the finite value $4\kappa|\alpha(t_f)|^2$ in the adiabatic limit, whereas the Hahn and counter-diabatic reference pulses keep paying a growing energy cost. The time-optimal drive uses a maximum-amplitude constraint $|\varepsilon(t)|\le\varepsilon_{\max}$ and reaches a target coherent state in about a microsecond at MHz amplitudes. Reusing the same analytic solution with $\omega_r$ replaced by the qubit-state-dependent shift $\chi_z=\pm\chi$ gives the pointer-state dynamics of dispersive readout, and for $\bar n_{\rm crit}=10$ and $100$ the resulting SNR exceeds one on timescales shorter than the cavity decay time, which the authors state is comparable to longitudinal-coupling readout. The paper explicitly registers that at $\bar n_{\rm crit}=1$ the coupling is strong enough for Kerr nonlinearities to dominate, which invalidates the linear model behind that case's IQ trajectory and SNR curve.

Load-bearing premise

The load-bearing premise is that the dispersive Hamiltonian and the linear Langevin equation with $\omega_r$ replaced by the Stark shift $\chi_z$ stay valid all the way up to the stated critical photon numbers, and the paper's own discussion of Fig. 4(a) says this fails at $\bar n_{\rm crit}=1$, where $g=2\pi\times 1$ GHz makes Kerr nonlinearities dominate.

Editorial extensions

If this is right

  • In the long-time limit the energy-optimal pulse costs a constant $4\kappa|\alpha(t_f)|^2$ to prepare a target coherent state, while the Hahn and counter-diabatic pulses keep adding energy linearly in $t_f$, so the optimal pulse becomes increasingly favourable the longer the operation.
  • Time-optimal pulses reach microsecond-scale transfer times at MHz drive amplitudes, making the scheme compatible with the amplitude ceilings of practical cQED drive lines.
  • For $\bar n_{\rm crit}=10$ and $100$, the analytic readout pulses give a signal-to-noise ratio that reaches order unity on timescales shorter than $\kappa^{-1}$, which the paper reports as comparable to longitudinal-coupling readout.
  • The maximal SNR grows monotonically with $\bar n_{\rm crit}$ because larger target photon numbers produce larger pointer-state displacements and better state discrimination.
  • At $\bar n_{\rm crit}=1$ the paper's own analysis shows Kerr nonlinearities dominate, so the linear-model IQ trajectory and SNR for that parameter set are not physically predictive.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Editorial inference: because the PMP solution only uses the linear form of the dynamics, any driven-dissipative system with the same structure—spin-qubit resonator readout, optomechanical cooling, or linearized flux qubits—can inherit the same closed-form pulses with an appropriate substitution for $\hat A$.
  • Editorial inference: the comparison suggests the practical advantage of the energy-optimal pulse is largest when operations run for many cavity lifetimes; at very short $t_f$ all compared schemes pay exponential energy costs, so the benefit there is only the exact constraint satisfaction, not the asymptotic scaling.
  • Editorial inference: the authors' own validity bound implies the readout advantage should be tested in the large-$\bar n_{\rm crit}$ regime; a direct experiment at $\bar n_{\rm crit}=1$ would likely see the claimed SNR degraded by the Kerr-induced trajectory distortion the paper describes.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 4 minor

Summary. The manuscript proposes a Pontryagin Maximum Principle (PMP) framework for driving a dissipative LC resonator modeled by a linear Langevin equation. It derives energy- and time-optimal pulses for coherent-state preparation and then applies these pulses to dispersive qubit readout in circuit QED, reporting SNR curves for three critical photon numbers. The central advertised results are analytical energy-optimal pulses with exponential energy scaling, microsecond-scale time-optimal pulses, and SNR comparable to longitudinal-coupling readout at large critical photon numbers.

Significance. If the derivations were correct, the paper would provide a useful analytically solvable example of PMP-based control for an open linear system, with a direct application to qubit readout. The comparison with counter-diabatic driving and the robustness analysis are valuable, and the energy-optimal construction appears to follow the standard Gramian/adjoint formalism. However, the time-optimal part contains a load-bearing integration error, and the low-critical-photon-number readout is modeled in a regime the paper itself says is dominated by nonlinearities; these issues materially affect the claims.

major comments (3)
  1. [Minimization of pulse energy and time, Eq. (7)] Equation (7) does not solve the stated time-optimal control problem. With ε₁(t)=ε_max cosφ(t), ε₂(t)=ε_max sinφ(t) and φ_opt(t)=ω_r t+θ, the drive is ε(t)=ε_max e^{i(ω_r t+θ)}. Direct integration of Eq. (1) from α(0)=0 gives α(t)= [2ε_max e^{iθ}/(κ+4iω_r)] [e^{-(κ/2+iω_r)t} − e^{iω_r t}], not the expression in Eq. (7), which contains [e^{-(κ/2+iω_r)t}−1] and corresponds to a different drive. The discrepancy is quantitative: for the Fig. 3 parameters (ω_r=2π×0.3 MHz, κ=2π×10 kHz, ε_max=10 MHz) the amplitude |α(t)| from the correct solution is bounded by approximately 2ε_max·2/|κ+4iω_r| ≈ 5.3, so the claimed target |α(t_f)|=10 is never reached. The quoted t_min^f=1.01 μs and the time-optimal curves in Figs. 3 and S1 therefore do not follow from the model in Eq. (1).
  2. [Minimization of pulse energy and time (adjoint equations); Supplementary Eqs. (32)–(33)] The adjoint equations used for the time-optimal derivation are internally inconsistent. The main text states ˙p_j = (−1)^{j+1}ω_r p_k − κ p_j/2, while the supplementary material gives ˙p_1 = κ/2 p_1 − ω_r p_2 and ˙p_2 = ω_r p_1 + κ/2 p_2. Neither matches the PMP canonical equation ˙p = −A^T p for the matrix A in Eq. (4), which would read ˙p_1 = κ/2 p_1 + ω_r p_2 and ˙p_2 = −ω_r p_1 + κ/2 p_2. Moreover, the stated solution p_j(t)=e^{-κt/2}[p_j(0)cos(ω_r t)+(−1)^{j+1}p_k(0)sin(ω_r t)] does not solve either form. These errors undermine the derivation of φ_opt(t)=ω_r t+θ and the associated minimal-time formula, and they also propagate to Eq. (12) and the time-optimal readout results.
  3. [Qubit-resonator interaction, Fig. 4 and Eqs. (11)–(13)] The readout results for n_crit=1 are computed with the linear Langevin equation in which ω_r is replaced by χ_z, but the paper itself states in the discussion of Fig. 4(a) that for g=2π×1 GHz 'nonlinearities, such as Kerr effect, dominate the dynamics'. Using a linear dispersive model to generate the IQ trajectory and SNR in that regime is therefore not justified. The n_crit=1 SNR curve and the 'exotic trajectory' in Fig. 4(a) are outputs of a model that the authors acknowledge is invalid there; either the calculation must be replaced by a nonlinear treatment (e.g., including the Kerr term), or the claims should be restricted to the regimes where the linear model applies.
minor comments (4)
  1. [Eq. (1) and surrounding text] The text calls Eq. (1) the Langevin equation 'in the rotating frame', but the equation contains the explicit term −iω_r α. Please clarify the frame convention, because the sign and meaning of the drive phase φ(t) depend on it.
  2. [Fig. 2(a) and Eq. (6)] The claim of 'exponential scaling' of the energy cost is imprecise: Eq. (6) grows as 1/(1−e^{−κt_f}) ≈ 1/(κt_f) for large t_f, which is algebraic, not exponential, in that limit. Please state the asymptotic behavior more carefully.
  3. [Eq. (13)] In Eq. (13) the noise operator M_N is already defined as the centered operator M−⟨M⟩, so writing ⟨M_N²|ℓ⟩ for the variance is acceptable, but the notation ⟨M²_N|ℓ⟩ in the denominator is confusing because it suggests a second centering. Please clarify.
  4. [Supplementary Eq. (49)] The expression for α_out(t) in the supplementary material appears to have a sign that is inconsistent with the input-output relation a_out(t)=a_in(t)+√κ a(t) used in the main text. Please check whether the sign in Eq. (49) should be positive or negative, since it feeds into the SNR calculation.

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity: the central PMP control derivation is self-contained, and the cited self-references are not load-bearing.

full rationale

The energy- and time-optimal pulses are derived from the stated Langevin equation and the Pontryagin Maximum Principle within the paper itself, with the detailed derivation reproduced in Supplementary Sec. II; no free parameter is fitted to the predicted photon number, energy cost, or SNR. The final coherent-state displacement is imposed as a boundary condition rather than extracted from the plotted results, and the SNR values are computed from the input-output relation and Eq. (13) rather than tuned. Self-citations such as Refs. [34], [37], and [40] either provide external comparison benchmarks or point to derivations reproduced in the supplementary material; none is used to import an unverified uniqueness theorem or to forbid alternative approaches. The readout extension uses the same linear LE with the substitution omega_r -> chi_z under the dispersive Hamiltonian (10); this is a stated modelling assumption with acknowledged validity limits, since the paper itself notes that Kerr nonlinearities dominate for n_crit = 1. That is a regime-of-validity or correctness concern, not a circular reduction. An adversarial check that Eq. (7) does not follow from phi_opt = omega_r t + theta for Eq. (1) indicates an internal-consistency issue in the derivation, not an equivalence between the claimed result and its inputs, so it does not raise the circularity score.

Assumptions & free parameters 0 free parameters · 5 assumptions · 0 invented entities

No data were fitted; the only tunable quantities are the illustrative physical parameters (omega_r, kappa, g, epsilon_max, n_crit). The central derivations rest on standard PMP, Markovian input-output theory, and the dispersive approximation, the last of which is strained at n_crit=1.

assumptions (5)
  • domain assumption The quantum Langevin equation for alpha(t)=<a>, with the input field identified with the coherent drive epsilon(t)=sqrt(kappa)*a_in, is equivalent to the Lindblad master equation for a damped driven harmonic oscillator.
    Used in the main text and Supplementary Sec. I to justify the linear control model; standard input-output theory but assumes a Markovian bath and a coherent-state ansatz.
  • standard math Pontryagin's maximum principle provides the unique minimizing control for the linear energy and time costs in Eqs. (2) and (4).
    The paper applies textbook PMP without proving controllability or uniqueness; this is acceptable background, though the time-optimal adjoint equations appear to contain sign inconsistencies.
  • domain assumption The dispersive Hamiltonian (10) with Stark shift chi=g^2/(omega_q-omega_r) and the substitution omega_r to chi_z in the Langevin equation remain valid at all three critical photon numbers.
    This is the load-bearing modeling assumption for the readout section; the paper itself states that at n_crit=1 Kerr nonlinearities dominate, which contradicts the linear model used for the IQ trajectory and SNR.
  • domain assumption The homodyne SNR definition (13) with a_out=a_in+sqrt(kappa)*a is the appropriate readout metric.
    Standard input-output theory, but the SNR includes only quantum noise and not added amplifier noise or other experimental imperfections.
  • standard math The coherent-state quantum speed limit bound (9) applies.
    Mandelstam-Tamm bound for coherent states cited from prior work; used to compare quantum efficiency of the pulses.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Optimal Control for Open Quantum System in Circuit Quantum Electrodynamics." pith.science (2026). https://pith.science/paper/LN3O63WX

@misc{pith2026241220149,
  author       = {Pith},
  title        = {Pith review of: Optimal Control for Open Quantum System in Circuit Quantum Electrodynamics},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/LN3O63WX}},
  note         = {Machine review of arXiv:2412.20149}
}
read the original abstract

We propose a quantum optimal control framework based on the Pontryagin Maximum Principle to design energy- and time-efficient pulses for open quantum systems. By formulating the Langevin equation of a dissipative LC circuit as a linear control problem, we derive optimized pulses with exponential scaling in energy cost, outperforming conventional shortcut-to-adiabaticity methods such as counter-diabatic driving. When applied to a resonator dispersively coupled to a qubit, these optimized pulses achieve an excellent signal-to-noise ratio comparable to longitudinal coupling schemes across varying critical photon numbers. Our results provide a significant step toward efficient control in dissipative open systems and improved qubit readout in circuit quantum electrodynamics.

Figures

Figures reproduced from arXiv: 2412.20149 by the authors.

Figure 1
Figure 1. (a) Schematic illustration of driven open quantum system, [PITH_FULL_IMAGE:figures/full_fig_p001_1.png] view at source ↗
Figure 2
Figure 2. (a) Energy cost versus time tf and (b) time evolution of total photon number for different drivings when tf = 10 µs. All schemes, including the energy-optimal (blue solid), the Hahn pulse (orange dotted), and its CD-assisted counterpart (green dashed), achieve the same target state α(tf) = 10e iϑ from the initial state α(0) = 0. Pa￾rameters: ωr = 2π × 0.3 MHz and κ = 2π × 10 kHz. The cavity frequency must be chosen … view at source ↗
Figure 4
Figure 4. (a) The evolution in the IQ plane (normalized by [PITH_FULL_IMAGE:figures/full_fig_p004_4.png] view at source ↗
Figures from the paper (1 more)
Figure 5
Figure 5. Figure 5: (a) Resonator frequency and (b) qubit frequency mismatch [PITH_FULL_IMAGE:figures/full_fig_p005_5.png]

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Quantum Transport Protected by Acceleration From Nonadiabaticity and Dissipation

    quant-ph 2025-06 conditional novelty 7.0 of 10

    Optimizing trap acceleration, rather than counterdiabatic fields, maximizes transport fidelity of a dissipating wavepacket even at supersonic speeds.

  2. Phase-Programmable Free Electron Quantum States in Synthetic Momentum Space

    quant-ph 2026-07 conditional novelty 6.0 of 10

    Phase-only Pontryagin optimization and deterministic Bragg-regime sequential coupling enable programmable free electron momentum-sideband populations and coherent superposition states with tunable relative phases.

  3. Arbitrary state preparation in quantum harmonic oscillators using neural networks

    quant-ph 2025-02 reject novelty 5.0 of 10

    A neural network predicts pulse sequences that prepare arbitrary qubit, qutrit, and qudit states in a harmonic oscillator, reaching 99.9% average fidelity for qubits and 97% for qutrits in simulation.

Reference graph

Works this paper leans on

66 extracted references · 56 canonical work pages · cited by 3 Pith papers

  1. [1]

    C. Brif, R. Chakrabarti, and H. Rabitz, Control of quantum phe- nomena: past, present and future, New Journal of Physics 12, 075008 (2010)

    work page 2010

  2. [2]

    ERDF A way of making Europe

    = p2 1(0) + p2 2(0) = C2 (C is a constant), which leads to the initial conditions p1(0) = C cosθ and p2(0) = C sinθ. According to PMP, optimiz- ing Hc requires ∂Hc/∂ϕ = 0, which yields the condition tanϕopt(t) = p2(t)/p1(t), or equivalently, ϕopt(t) = ωrt + θ. Solving the LE in Eq. (1) usingϕopt(t), we get αopt(t) =α(0) e−(κ 2 +iωr)t + 2εmax eiθ κ + 4iωr ...

  3. [3]

    C. P. Koch, U. Boscain, T. Calarco, G. Dirr, S. Filipp, S. J. Glaser, R. Koslo ff, S. Montangero, T. Schulte-Herbr ¨uggen, D. Sugny, and F. K. Wilhelm, Quantum optimal control in quan- tum technologies. strategic report on current status, visions and goals for research in europe, EPJ Quantum Technology 9, 19 (2022)

    work page 2022

  4. [4]

    S. J. Glaser, U. Boscain, T. Calarco, C. P. Koch, W. K ¨ock- enberger, R. Koslo ff, I. Kuprov, B. Luy, S. Schirmer, T. Schulte-Herbr ¨uggen, D. Sugny, and F. K. Wilhelm, Train- ing schr¨odinger’s cat: quantum optimal control, The European Physical Journal D 69, 279 (2015)

    work page 2015

  5. [5]

    I. P. D. Dong, Quantum control theory and applications: a sur- vey, IET Control Theory & Applications 4, 2651 (2010)

    work page 2010

  6. [6]

    Ac ´ın, I

    A. Ac ´ın, I. Bloch, H. Buhrman, T. Calarco, C. Eichler, J. Eis- ert, D. Esteve, N. Gisin, S. J. Glaser, F. Jelezko, S. Kuhr, M. Lewenstein, M. F. Riedel, P. O. Schmidt, R. Thew, A. Wall- raff, I. Walmsley, and F. K. Wilhelm, The quantum technologies roadmap: a european community view, New Journal of Physics 20, 080201 (2018)

    work page 2018

  7. [7]

    Gu ´ery-Odelin, A

    D. Gu ´ery-Odelin, A. Ruschhaupt, A. Kiely, E. Torrontegui, S. Mart ´ınez-Garaot, and J. G. Muga, Shortcuts to adiabatic- ity: Concepts, methods, and applications, Rev. Mod. Phys. 91, 045001 (2019)

    work page 2019

  8. [9]

    de Vega and D

    I. de Vega and D. Alonso, Dynamics of non-markovian open quantum systems, Rev. Mod. Phys. 89, 015001 (2017)

    2017

Show all 66 references
  1. [10]

    Vacanti, R

    G. Vacanti, R. Fazio, S. Montangero, G. M. Palma, M. Pater- nostro, and V . Vedral, Transitionless quantum driving in open quantum systems, New Journal of Physics 16, 053017 (2014)

    2014

  2. [11]

    R. Dann, A. Tobalina, and R. Koslo ff, Shortcut to equilibra- tion of an open quantum system, Phys. Rev. Lett. 122, 250402 (2019)

    2019

  3. [12]

    Alipour, A

    S. Alipour, A. Chenu, A. T. Rezakhani, and A. del Campo, 6 Shortcuts to Adiabaticity in Driven Open Quantum Systems: Balanced Gain and Loss and Non-Markovian Evolution, Quan- tum 4, 336 (2020)

    2020

  4. [13]

    Dupays, I

    L. Dupays, I. L. Egusquiza, A. del Campo, and A. Chenu, Su- peradiabatic thermalization of a quantum oscillator by engi- neered dephasing, Phys. Rev. Res. 2, 033178 (2020)

    2020

  5. [14]

    A. C. Santos and M. S. Sarandy, Generalized transitionless quantum driving for open quantum systems, Phys. Rev. A 104, 062421 (2021)

    2021

  6. [15]

    S. Wu, W. Ma, X. Huang, and X. Yi, Shortcuts to adiabaticity for open quantum systems and a mixed-state inverse engineer- ing scheme, Phys. Rev. Appl. 16, 044028 (2021)

    2021

  7. [16]

    Z. Yin, C. Li, J. Allcock, Y . Zheng, X. Gu, M. Dai, S. Zhang, and S. An, Shortcuts to adiabaticity for open systems in cir- cuit quantum electrodynamics, Nature Communications 13, 188 (2022)

    2022

  8. [17]

    Boubakour, S

    M. Boubakour, S. Endo, T. Fogarty, and T. Busch, Dynam- ical invariant based shortcut to equilibration, arXiv preprint arXiv:2401.11659 (2024)

    2024 arXiv

  9. [18]

    S. Bao, S. Kleer, R. Wang, and A. Rahmani, Optimal control of superconducting gmon qubits using pontryagin’s minimum principle: Preparing a maximally entangled state with singular bang-bang protocols, Phys. Rev. A 97, 062343 (2018)

    2018

  10. [19]

    Jirari and W

    H. Jirari and W. P ¨otz, Quantum optimal control theory and dynamic coupling in the spin-boson model, Phys. Rev. A 74, 022306 (2006)

    2006

  11. [20]

    Levin, W

    L. Levin, W. Skomorowski, L. Rybak, R. Koslo ff, C. P. Koch, and Z. Amitay, Coherent control of bond making, Phys. Rev. Lett. 114, 233003 (2015)

    2015

  12. [21]

    Sugny, A

    D. Sugny, A. Keller, O. Atabek, D. Daems, C. M. Dion, S. Gu´erin, and H. R. Jauslin, Laser control for the optimal evo- lution of pure quantum states, Phys. Rev. A 71, 063402 (2005)

    2005

  13. [22]

    T. E. Skinner, T. O. Reiss, B. Luy, N. Khaneja, and S. J. Glaser, Application of optimal control theory to the design of broad- band excitation pulses for high-resolution nmr, Journal of Mag- netic Resonance 163, 8 (2003)

    2003

  14. [23]

    Khaneja, T

    N. Khaneja, T. Reiss, C. Kehlet, T. Schulte-Herbr ¨uggen, and S. J. Glaser, Optimal control of coupled spin dynamics: design of nmr pulse sequences by gradient ascent algorithms, Journal of Magnetic Resonance 172, 296 (2005)

    2005

  15. [24]

    C. Lin, Y . Ma, and D. Sels, Application of pontryagin’s max- imum principle to quantum metrology in dissipative systems, Phys. Rev. A 105, 042621 (2022)

    2022

  16. [25]

    Alexeev, D

    Y . Alexeev, D. Bacon, K. R. Brown, R. Calderbank, L. D. Carr, F. T. Chong, B. DeMarco, D. Englund, E. Farhi, B. Fefferman, A. V . Gorshkov, A. Houck, J. Kim, S. Kimmel, M. Lange, S. Lloyd, M. D. Lukin, D. Maslov, P. Maunz, C. Monroe, J. Preskill, M. Roetteler, M. J. Savage, a...

    2021

  17. [26]

    Boscain, M

    U. Boscain, M. Sigalotti, and D. Sugny, Introduction to the pon- tryagin maximum principle for quantum optimal control, PRX Quantum 2, 030203 (2021)

    2021

  18. [27]

    C. Lin, D. Sels, Y . Ma, and Y . Wang, Stochastic optimal con- trol formalism for an open quantum system, Phys. Rev. A 102, 052605 (2020)

    2020

  19. [28]

    Li, J.-F

    G. Li, J.-F. Chen, C. P. Sun, and H. Dong, Geodesic path for the minimal energy cost in shortcuts to isothermality, Phys. Rev. Lett. 128, 230603 (2022)

    2022

  20. [29]

    Blais, A

    A. Blais, A. L. Grimsmo, S. M. Girvin, and A. Wallraff, Circuit quantum electrodynamics, Rev. Mod. Phys.93, 025005 (2021)

    2021

  21. [30]

    Krantz, M

    P. Krantz, M. Kjaergaard, F. Yan, T. P. Orlando, S. Gustavsson, and W. D. Oliver, A quantum engineer’s guide to superconduct- ing qubits, Applied Physics Reviews 6, 021318 (2019)

    2019

  22. [31]

    Kohler, Dispersive readout of adiabatic phases, Phys

    S. Kohler, Dispersive readout of adiabatic phases, Phys. Rev. Lett. 119, 196802 (2017)

    2017

  23. [32]

    Kohler, Dispersive readout: Universal theory beyond the rotating-wave approximation, Phys

    S. Kohler, Dispersive readout: Universal theory beyond the rotating-wave approximation, Phys. Rev. A 98, 023849 (2018)

    2018

  24. [33]

    Chessari, E

    A. Chessari, E. A. Rodr ´ıguez-Mena, J. C. Abadillo-Uriel, V . Champain, S. Zihlmann, R. Maurand, Y .-M. Niquet, and M. Filippone, Unifying floquet theory of longitudinal and dis- persive readout, arXiv preprint arXiv:2407.03417 (2024)

    2024 arXiv

  25. [34]

    M. F. Dumas, B. Groleau-Par ´e, A. McDonald, M. H. Mu ˜noz Arias, C. Lled ´o, B. D’Anjou, and A. Blais, Measurement- induced transmon ionization, Phys. Rev. X 14, 041023 (2024)

    2024

  26. [35]

    Zhang, X

    Q. Zhang, X. Chen, and D. Gu ´ery-Odelin, Robust control of linear systems and shortcut to adiabaticity based on superoscil- lations, Phys. Rev. Appl. 18, 054055 (2022)

    2022

  27. [36]

    Ansel, E

    Q. Ansel, E. Dionis, F. Arrouas, B. Peaudecerf, S. Gu ´erin, D. Gu´ery-Odelin, and D. Sugny, Introduction to theoretical and experimental aspects of quantum optimal control, Journal of Physics B: Atomic, Molecular and Optical Physics 57, 133001 (2024)

    2024

  28. [37]

    Didier, J

    N. Didier, J. Bourassa, and A. Blais, Fast quantum nondemo- lition readout by parametric modulation of longitudinal qubit- oscillator interaction, Phys. Rev. Lett. 115, 203601 (2015)

    2015

  29. [38]

    C ´ardenas-L´opez and X

    F. C ´ardenas-L´opez and X. Chen, Shortcuts to adiabaticity for fast qubit readout in circuit quantum electrodynamics, Phys. Rev. Appl. 18, 034010 (2022)

    2022

  30. [39]

    C. W. Gardiner and M. J. Collett, Input and output in damped quantum systems: Quantum stochastic di fferential equations and the master equation, Phys. Rev. A 31, 3761 (1985)

    1985

  31. [40]

    C. W. Gardiner, A. S. Parkins, and P. Zoller, Wave-function quantum stochastic di fferential equations and quantum-jump simulation methods, Phys. Rev. A 46, 4363 (1992)

    1992

  32. [41]

    Mo, C.-L

    Z. Mo, C.-L. F. A., D. Sugny, and C. Xi, Supplementary mate- rial: Optimal control for open quantum system in circuit quan- tum electrodynamics, (2024)

    2024

  33. [42]

    L. S. Pontryagin, Mathematical theory of optimal processes (Routledge, 2018)

    2018

  34. [44]

    De ffner and S

    S. De ffner and S. Campbell, Quantum speed limits: from heisenberg’s uncertainty principle to optimal quantum control, Journal of Physics A: Mathematical and Theoretical50, 453001 (2017)

    2017

  35. [45]

    Mandelstam and I

    L. Mandelstam and I. Tamm, The uncertainty relation between energy and time in non-relativistic quantum mechanics, in Se- lected papers (Springer, 1991) pp. 115–123

    1991

  36. [46]

    T. V . Stefanski and C. K. Andersen, Flux-pulse-assisted readout of a fluxonium qubit, Phys. Rev. Appl. 22, 014079 (2024)

    2024

  37. [47]

    Blais, R.-S

    A. Blais, R.-S. Huang, A. Wallra ff, S. M. Girvin, and R. J. Schoelkopf, Cavity quantum electrodynamics for supercon- ducting electrical circuits: An architecture for quantum com- putation, Phys. Rev. A 69, 062320 (2004)

    2004

  38. [48]

    J. Koch, T. M. Yu, J. Gambetta, A. A. Houck, D. I. Schus- ter, J. Majer, A. Blais, M. H. Devoret, S. M. Girvin, and R. J. Schoelkopf, Charge-insensitive qubit design derived from the cooper pair box, Phys. Rev. A 76, 042319 (2007)

    2007

  39. [49]

    Shillito, A

    R. Shillito, A. Petrescu, J. Cohen, J. Beall, M. Hauru, M. Ganahl, A. G. Lewis, G. Vidal, and A. Blais, Dynamics of transmon ionization, Phys. Rev. Appl. 18, 034031 (2022)

    2022

  40. [50]

    Siddiqi, R

    I. Siddiqi, R. Vijay, F. Pierre, C. M. Wilson, M. Metcalfe, C. Rigetti, L. Frunzio, and M. H. Devoret, Rf-driven joseph- son bifurcation amplifier for quantum measurement, Phys. Rev. Lett. 93, 207002 (2004)

    2004

  41. [51]

    M. D. Reed, L. DiCarlo, B. R. Johnson, L. Sun, D. I. Schuster, 7 L. Frunzio, and R. J. Schoelkopf, High-fidelity readout in cir- cuit quantum electrodynamics using the jaynes-cummings non- linearity, Phys. Rev. Lett.105, 173601 (2010)

    2010

  42. [52]

    D’Anjou and G

    B. D’Anjou and G. Burkard, Optimal dispersive readout of a spin qubit with a microwave resonator, Phys. Rev. B 100, 245427 (2019)

    2019

  43. [53]

    Bosco, P

    S. Bosco, P. Scarlino, J. Klinovaja, and D. Loss, Fully tunable longitudinal spin-photon interactions in si and ge quantum dots, Phys. Rev. Lett. 129, 066801 (2022)

    2022

  44. [54]

    Corrigan, B

    J. Corrigan, B. Harpt, N. Holman, R. Ruskov, P. Marciniec, D. Rosenberg, D. Yost, R. Das, W. D. Oliver, R. McDermott, C. Tahan, M. Friesen, and M. Eriksson, Longitudinal coupling between a si/si1−xgex double quantum dot and an o ff-chip TiN resonator, Phys. Rev. Appl. 20, 0640...

    2023

  45. [55]

    Gautier, ´E

    R. Gautier, ´E. Genois, and A. Blais, Optimal control in large open quantum systems: the case of transmon readout and reset, arXiv preprint arXiv:2403.14765 (2024)

    2024 arXiv

  46. [56]

    Rinaldi, R

    E. Rinaldi, R. Di Candia, S. Felicetti, and F. Minganti, Dis- persive qubit readout with machine learning, arXiv preprint arXiv:2112.05332 (2021)

    2021 arXiv

  47. [57]

    Koolstra, N

    G. Koolstra, N. Stevenson, S. Barzili, L. Burns, K. Siva, S. Greenfield, W. Livingston, A. Hashim, R. K. Naik, J. M. Kreikebaum, K. P. O’Brien, D. I. Santiago, J. Dressel, and I. Siddiqi, Monitoring fast superconducting qubit dynamics us- ing a neural network, Phys. Rev. X 12,...

    2022

  48. [58]

    Genois, J

    E. Genois, J. A. Gross, A. Di Paolo, N. J. Stevenson, G. Kool- stra, A. Hashim, I. Siddiqi, and A. Blais, Quantum-tailored machine-learning characterization of a superconducting qubit, PRX Quantum 2, 040355 (2021)

    2021

  49. [59]

    Y . Ding, X. Chen, R. Magdalena-Benedito, and J. D. Mart ´ın- Guerrero, Closed-loop control of a noisy qubit with reinforce- ment learning, Machine Learning: Science and Technology 4, 025020 (2023)

    2023

  50. [60]

    K. Funo, N. Shiraishi, and K. Saito, Speed limit for open quan- tum systems, New Journal of Physics 21, 013006 (2019)

    2019

  51. [61]

    del Campo, I

    A. del Campo, I. L. Egusquiza, M. B. Plenio, and S. F. Huelga, Quantum speed limits in open system dynamics, Phys. Rev. Lett. 110, 050403 (2013). 8 Supplementary Material: Optimal Control for Open Quantum System in Circuit Quantum Electrodynamics Mo Zhou, 1, 2 F. A. C ´ardenas...

    2013

  52. [62]

    This conservation law allows us to express the initial conditions as p1(0) = C cosθ, p2(0) = C sinθ

    = p2 1(0) + p2 2(0) = C2, which is constant. This conservation law allows us to express the initial conditions as p1(0) = C cosθ, p2(0) = C sinθ. According to PMP, to minimize the control time, we need to maximize the Pontryagin Hamiltonian. This leads to the condition ∂Hc/∂ϕ ...

  53. [63]

    Breuer and F

    H.-P. Breuer and F. Petruccione, The theory of open quantum systems (Oxford University Press, USA, 2002)

    2002

  54. [64]

    C. W. Gardiner and M. J. Collett, Input and output in damped quantum systems: Quantum stochastic di fferential equations and the master equation, Phys. Rev. A 31, 3761 (1985). 15 8 0.0 0.2 0.4 0.6 0.8 1.0 t/tf 10□7 10□5 10□3 10□1 101 103 105 SNR (a) 0.0 0.2 0.4 0.6 0.8 1.0 ϕ/π...

    1985

  55. [65]

    Zhang, X

    Q. Zhang, X. Chen, and D. Gu ´ery-Odelin, Robust control of linear systems and shortcut to adiabaticity based on superoscillations, Phys. Rev. Appl. 18, 054055 (2022)

    2022

  56. [66]

    Boscain, M

    U. Boscain, M. Sigalotti, and D. Sugny, Introduction to the pontryagin maximum principle for quantum optimal control, PRX Quantum 2, 030203 (2021)

    2021

  57. [67]

    Dionis and D

    E. Dionis and D. Sugny, Time-optimal control of two-level quantum systems by piecewise constant pulses, Phys. Rev. A 107, 032613 (2023)

    2023

  58. [68]

    Z. Yin, C. Li, J. Allcock, Y . Zheng, X. Gu, M. Dai, S. Zhang, and S. An, Shortcuts to adiabaticity for open systems in circuit quantum electrodynamics, Nature Communications 13, 188 (2022)

    2022

Pith tools

Reviewed August 10, 2026 · model on record in the stance chip above.