Optimal robust stimulated Raman exact passage by inverse optimization

Laforgue, Xavier; Dridi, Ghassen; Guérin, S.

doi:10.1103/physreva.105.032807

Cited by 18 publications

(16 citation statements)

References 31 publications

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“…Recently, a new protocol combines inverse engineering and optimization methods [97]. Here, the control pulses are determined by trajectories φ and read,…”

Section: Stimulated Raman Exact Passage (Stirep)mentioning

confidence: 99%

“…with φ = φ[η(t)]. The trajectory φ is obtained by applying robust inverse optimization (RIO) [97], which optimizes a cost function represented by the total area of the two pulses and is given by A t = 2 η f ηi | η| φ2 + cos 2 φ dη. By using the Euler-Lagrange equations and the Lagrange Multipliers method we obtain the following differential equations for the trajectory,,…”

Section: Stimulated Raman Exact Passage (Stirep)mentioning

confidence: 99%

“…For a thorough benchmarking, we consider other methods used to find optimal control pulses besides STI-RAP [48,49], such as Stimulated Raman Exact Passage (STIREP) [97], Inverse Engineering [89,90] and Modified Superadiabatic Transitionless Driving (MOD-SATD) [20,91]. For detailed calculations of these pulses, see [81].…”

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confidence: 99%

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Physics-informed neural networks for quantum control

Norambuena¹,

Mattheakis²,

González³

et al. 2022

Preprint

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“…Recently, a new protocol combines inverse engineering and optimization methods [97]. Here, the control pulses are determined by trajectories φ and read,…”

Section: Stimulated Raman Exact Passage (Stirep)mentioning

confidence: 99%

Section: Stimulated Raman Exact Passage (Stirep)mentioning

confidence: 99%

See 1 more Smart Citation

Physics-informed neural networks for quantum control

Norambuena¹,

Mattheakis²,

González³

et al. 2022

Preprint

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“…It is known that adiabatic evolutions require long run time [19][20][21] and this makes STIRAP vulnerable to environmentinduced decoherence [8]. Recently, shortcuts to adiabaticity * xgf@sdu.edu.cn (STA) [22,23], which includes transitionless quantum driving, invariant-based inverse engineering and fast-forward approaches, has been used to speed up adiabatic population transfers [24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43] and design stimulated Raman exact passage [44][45][46][47][48][49]. However, when using such STA based schemes in spin systems, the existence of the frequency errors still influences the performance of these schemes.…”

Section: Introductionmentioning

confidence: 99%

Robust population transfer of spin states by geometric formalism

Li,

2022

Preprint

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Accurate population transfer of uncoupled or weakly coupled spin states is crucial for many quantum information processing tasks. In this paper, we propose a fast and robust scheme for population transfer which combines invariant-based inverse engineering and geometric formalism for robust quantum control. Our scheme is not constrained by the adiabatic condition and therefore can be implemented fast. It can also effectively suppress the dominant noise in spin systems, which together with the fast feature guarantees the accuracy of the population transfer. Moreover, the control parameters of the driving Hamiltonian in our scheme are easy to design because they correspond to the curvature and torsion of a three-dimensional visual space curve derived by using geometric formalism for robust quantum control. We test the efficiency of our scheme by numerically simulating the ground-state population transfer in 15 N nitrogen vacancy centers and comparing our scheme with stimulated Raman transition, stimulated Raman adiabatic passage and conventional shortcuts to adiabaticity based schemes, three types of popularly used schemes for population transfer. The numerical results clearly show that our scheme is advantageous over these previous ones.

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“…Numerical optimization, such as, e.g., gradientbased optimization algorithm (GRAPE algorithm [16]), * sguerin@u-bourgogne.fr provide only local optimal solutions. Only recently, techniques merging robustness and optimality have been proposed [17,18], including a method based on inverse optimization (RIO) [19,20]. In particular, time-optimal robust processes have been shown to feature driving pulses of constant amplitude, i.e.…”

Section: Introductionmentioning

confidence: 99%

Robust quantum control by smooth quasi-square pulses

Zhu¹,

Laforgue²,

Chen³

et al. 2022

J. Phys. B: At. Mol. Opt. Phys.

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Robust time-optimal control is known to feature constant (square) pulses. We analyze fast adiabatic dynamics that preserve robustness by using alternative smooth quasi-square pulses, typically represented by hyper-Gaussian pulses. We here consider the two protocols, robust inverse optimization and time-contracted adiabatic passage, allowing the design of the same pulse shape in both cases. The dynamics and their performance are compared. The superiority of the former protocol is shown.

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Optimal robust stimulated Raman exact passage by inverse optimization

Cited by 18 publications

References 31 publications

Physics-informed neural networks for quantum control

Physics-informed neural networks for quantum control

Robust population transfer of spin states by geometric formalism

Robust quantum control by smooth quasi-square pulses

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