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Proceedings of NAS RA Physics

Автоматическая оптимизация лазерных полей для манипулирования квантовыми состояниями

Р. Саакян, Romik Sargsyan, Э. Погосян, Karen Arzumanyan, А. Амбарцумян, E. A. Gazazyan

Published Dec 9, 2025• 0 citations
Publisher

Abstract

This paper proposes a numerical approach to the problem of inverse quantum control with a focus on the automated formation of external laser control fields that ensure highprecision and controlled population transfer in multilevel quantum systems. The method is based on optimizing the parameters of control pulses using gradient algorithms in combination with automatic differentiation, which allows for effective control of the physical characteristics of laser fields and increases the stability of the transfer process. The obtained results provide a foundation for the development of more general quantum control methods focused on experimental implementation on real physical platforms.

DOI
10.54503/0002-3035-2025-60.4-477

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This paper proposes a numerical approach to the problem of inverse quantum control with a focus on the automated formation of external laser control fields that ensure highprecision and controlled population transfer in multilevel quantum systems. The method is based on optimizing the parameters of control pulses using gradient algorithms in combination with automatic differentiation, which allows for effective control of the physical characteristics of laser fields and increases the stability of the transfer process. The obtained results provide a foundation for the development of more general quantum control methods focused on experimental implementation on real physical platforms.
Abstract This paper proposes a numerical approach to the problem of inverse quantum control with a focus on the automated formation of external laser control fields that ensure high-precision and controlled population transfer in multilevel quantum systems. The method is based on optimizing the parameters of control pulses using gradient algorithms in combination with automatic differentiation, which allows for effective control of the physical characteristics of laser fields and increases the stability of the transfer process. The obtained results provide a foundation for the development of more general quantum control methods focused on experimental implementation on real physical platforms.
A gradient-based optimization approach combined with automatic differentiation is employed to ensure high accuracy and scalability when working with high-dimensional parameter spaces. Numerical simulations confirm the effectiveness of the proposed method: the population is reliably transferred to the target state with minimal occupation of intermediate levels, while the control pulses remain smooth and physically implementable. The developed framework serves as a universal and experimentally applicable tool for automated control pulse design in quantum systems. It is particularly useful in scenarios where analytical methods or manual parameter tuning--such as standard schemes like STIRAP--prove to be inefficient or inapplicable.
This work investigates laser control of the populations of magnetic sublevels of the ground hyperfine level of cesium atoms in the D₂ line D₂ (6S₁/₂ → 6P₃/₂). The theoretical model is formulated within the full density matrix formalism based on the Lindblad master equation, which accounts for coherent interaction with the laser field, spontaneous decay, and decoherence processes. The system dynamics is described by a set of coupled ordinary differential equations representing the complete Zeeman structure of the levels and the competing relaxation channels characteristic of a realistic multilevel atomic system. The main objective of this study is the controlled redistribution and transfer of population between selected magnetic sublevels while minimizing the population of excited states. To achieve this goal, an optimization problem for the laser field parameters is formulated, including amplitudes, frequency detunings, phases, and temporal pulse profiles. Numerical simulations are performed by integrating a high-dimensional system of evolution equations for the density matrix elements. The proposed approach provides a scalable computational framework for modeling and controlling Zeeman population dynamics in complex quantum systems and can be applied to problems of coherent control and quantum state preparation.
We investigate two classes of quantum control problems by using frequency-domain optimization algorithms in the context of ultrafast laser control of quantum systems. In the first class of problems, the system model is known and a frequency-domain gradient-based optimization algorithm is applied for searching an optimal control field to selectively and robustly manipulate the population transfer in atomic rubidium. The other class of quantum control problems involves an experimental system with an unknown model. In this case, we introduce a differential evolution algorithm with a mixed strategy to search for optimal control fields and demonstrate the capability in an ultrafast laser control experiment for the fragmentation of Pr(hfac)3molecules.
Abstract This work investigates laser control of populations of magnetic sublevels of the ground hyperfine level of the cesium atom on the D2 line (6S1/2 → 6P3/2). A theoretical model is developed within the full density-matrix formalism based on the Lindblad equation, which accounts for coherent interaction with the laser field, spontaneous decay, and decoherence processes. The dynamics of the system is described by a set of coupled ordinary differential equations that reflect the complete Zeeman level structure and the competing relaxation channels characteristic of a realistic multilevel atomic medium. The aim of this work is the controlled redistribution and transfer of population between selected magnetic sublevels while minimizing the population of excited states. To this end, an optimization problem for the laser field parameters is formulated, including pulse amplitudes, frequency detunings, phases, and temporal profiles. Numerical calculations are performed by integrating the high-dimensional system of density-matrix evolution equations. The proposed approach constitutes a scalable computation platform for modeling and controlling Zeeman population dynamics in complex quantum systems and can be applied to problems of quantum state control and preparation.
We develop a hybrid quantum-classical algorithm to solve an optimal population transfer problem for a molecule subject to a laser pulse. The evolution of the molecular wave function under the laser pulse is simulated on a quantum computer, while the optimal pulse is iteratively shaped via a machine learning (evolutionary) algorithm. A method to encode on the quantum computer the nnn-electrons wave function is discussed, the circuits accomplishing its quantum simulation are derived and the scalability in terms of number of operations is discussed. Performance on noisy intermediate-scale quantum devices (IBM Q X2) is provided to assess the current technological gap. Furthermore the hybrid algorithm is tested on a quantum emulator to compare performance of the evolutionary algorithm with standard ones. Our results show that such algorithms are able to outperform the optimization with a downhill simplex method and provide performance comparable to more advanced (but quantum-computer unfriendly) algorithms such as Rabitz's or gradient-based optimization.