Feedback optimization of shaped femtosecond laser pulses for controlling the wavepacket dynamics and reactivity of mixed alkaline clusters

Vajda, Štefan; Bartelt, Andreas; Kaposta, Eva-Cristina; Leisner, Thomas; Lupulescu, C.; Minemoto, Shinichirou; Rosendo-Francisco, P.; Wöste, L.

doi:10.1016/s0301-0104(01)00275-0

Cited by 119 publications

(77 citation statements)

References 13 publications

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“…OCEs have been successfully performed for a wide range of goals, including the control of molecular vibrational [13][14][15][16][17][18][19][20] and electronic states [21][22][23][24][25][26][27][28][29], the generation and coherent manipulation of X-rays [30][31][32][33][34], the control of decoherence processes [35,36], the selective cleavage and formation of chemical bonds [37][38][39][40][41][42][43], the manipulation of energy flow in macromolecular complexes [44][45][46][47], and the control of photoisomerization reactions [48][49][50][51][52]. Optimal control theory (OCT) [7,9,[53][54][55][56] has provided insights into the coherent control of a variety of quantum phenomena, such as electron transfer …”

Section: Introductionmentioning

confidence: 99%

Searching for an optimal control in the presence of saddles on the quantum-mechanical observable landscape

Riviello

Sun

et al. 2017

Phys. Rev. A

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The broad success of theoretical and experimental quantum optimal control is intimately connected to the topology of the underlying control landscape. For several common quantum control goals, including the maximization of an observable expectation value, the landscape has been shown to lack local optima if three assumptions are satisfied: (i) the quantum system is controllable, (ii) the Jacobian of the map from the control field to the evolution operator is full-rank, and (iii) the control field is not constrained. In the case of the observable objective, this favorable analysis shows that the associated landscape also contains saddles, i.e., critical points that are not local suboptimal extrema. In this paper, we investigate whether the presence of these saddles affects the trajectories of gradient-based searches for an optimal control. We show through simulations that both the detailed topology of the control landscape and the parameters of the system Hamiltonian influence whether the searches are attracted to a saddle. For some circumstances with a special initial state and target observable, optimizations may approach a saddle very closely, reducing the efficiency of the gradient algorithm. Encounters with such attractive saddles are found to be quite rare. Neither the presence of a large number of saddles on the control landscape nor a large number of system states increase the likelihood that a search will closely approach a saddle. Even for applications that encounter a saddle, well-designed gradient searches with carefully chosen algorithmic parameters will readily locate optimal controls.

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Section: Introductionmentioning

confidence: 99%

Searching for an optimal control in the presence of saddles on the quantum-mechanical observable landscape

Riviello

Sun

et al. 2017

Phys. Rev. A

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“…Successful optimal control experiments (OCEs) have included selective control of molecular vibrational [10][11][12][13][14][15][16][17] and electronic states [18][19][20][21][22][23][24][25][26][27], preservation of quantum coherence [28,29], control of photoisomerization reactions [30][31][32][33][34][35], selective manipulation of chemical bonds [36][37][38][39][40][41][42][43][44], high-harmonic generation and coherent manipulation of the resulting soft X-rays [45][46][47][48][49][50][51], and control of energy flow in biomolecular complexes [52][53][54][55]. Optimal control theory (OCT) [7,9,…”

Section: Introductionmentioning

confidence: 99%

Searching for quantum optimal controls under severe constraints

Riviello¹,

Tibbetts²,

Brif³

et al. 2015

Phys. Rev. A

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The success of quantum optimal control for both experimental and theoretical objectives is connected to the topology of the corresponding control landscapes, which are free from local traps if three conditions are met: (1) the quantum system is controllable, (2) the Jacobian of the map from the control field to the evolution operator is of full rank, and (3) there are no constraints on the control field. This paper investigates how the violation of assumption (3) affects gradient searches for globally optimal control fields. The satisfaction of assumptions (1) and (2) ensures that the control landscape lacks fundamental traps, but certain control constraints can still introduce artificial traps. Proper management of these constraints is an issue of great practical importance for numerical simulations as well as optimization in the laboratory. Using optimal control simulations, we show that constraints on quantities such as the number of control variables, the control duration, and the field strength are potentially severe enough to prevent successful optimization of the objective. For each such constraint, we show that exceeding quantifiable limits can prevent gradient searches from reaching a globally optimal solution. These results demonstrate that careful choice of relevant control parameters helps to eliminate artificial traps and facilitate successful optimization.

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“…29,30 The SLM provides a high-resolution spectral shaping of the pulse, but its intrinsic low damage threshold imposed to set it between the stretcher and the regenerative amplifier of the chirped pulse amplification ͑CPA͒ laser chain. In this configuration, the amplification distorts the pulse shape applied to the SLM.…”

Section: ͑1͒mentioning

confidence: 99%

Optimal control of filamentation in air

Ackermann

Salmon

Lascoux

et al. 2006

Applied Physics Letters

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The authors demonstrate optimal control of the propagation of ultrashort, ultraintense (multiterawatt) laser pulses in air over distances up to 36m in a closed-loop scheme. They optimized three spectral ranges within the white-light continuum as well as the ionization efficiency. Optimization results in signal enhancements by typical factors of 2 and 1.4 for the target parameters. The optimization results in shorter pulses by reducing their chirp in the case of white-light continuum generation, while they correct the pulse from its defects and set the filamentation onset near the detector as far as air ionization is concerned

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Feedback optimization of shaped femtosecond laser pulses for controlling the wavepacket dynamics and reactivity of mixed alkaline clusters

Cited by 119 publications

References 13 publications

Searching for an optimal control in the presence of saddles on the quantum-mechanical observable landscape

Searching for an optimal control in the presence of saddles on the quantum-mechanical observable landscape

Searching for quantum optimal controls under severe constraints

Optimal control of filamentation in air

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