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Adaptive Learning Algorithms for Coherent Control

J. L. White, Brett J. Pearson, T. C. Weinacht, P. H. Bucksbaum

Published Aug 4, 2000• 1 citation
OpenAlex

Abstract

We have constructed an automated learning apparatus to control quantum systems. By directing intense shaped ultrafast laser pulses into a variety of samples and using a measurement of the system as a feedback signal, we are able to reshape the laser pulses to direct the quantum system into a desired physical state. The feedback signal is the input to an adaptive learning algorithm. This algorithm programs a computer-controlled, acousto-optic modulator (AOM) pulse shaper. The learning algorithm generates new shaped laser pulses based on the success of previous pulses in achieving a predetermined goal.

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We have constructed an automated learning apparatus to control quantum systems. By directing intense shaped ultrafast laser pulses into a variety of samples and using a measurement of the system as a feedback signal, we are able to reshape the laser pulses to direct the quantum system into a desired physical state. The feedback signal is the input to an adaptive learning algorithm. This algorithm programs a computer-controlled, acousto-optic modulator (AOM) pulse shaper. The learning algorithm generates new shaped laser pulses based on the success of previous pulses in achieving a predetermined goal.
We have constructed an automated learning apparatus to control quantum systems. By directing intense shaped ultrafast laser pulses into a variety of samples and using a measurement of the system as a feedback signal, we are able to reshape the laser pulses to direct the system into a desired state. The feedback signal is the input to an adaptive learning algorithm. This algorithm programs a computer-controlled, acousto-optic modulator pulse shaper. The learning algorithm generates new shaped laser pulses based on the success of previous pulses in achieving a predetermined goal.
A longstanding goal in chemical physics has been the control of atoms and molecules using coherent light fields. This paper provides a brief overview of the field and discusses experiments that use a programmable pulse shaper to control the quantum state of electronic wavepackets in Rydberg atoms and electronic and nuclear dynamics in molecular liquids. The shape of Rydberg wavepackets was controlled by using tailored ultrafast pulses to excite a beam of caesium atoms. The quantum state of these atoms was measured using holographic techniques borrowed from optics. The experiments with molecular liquids involved the construction of an automated learning machine. A genetic algorithm directed the choice of shaped pulses which interacted with the molecular system inside a learning control loop. Analysis of successful pulse shapes that were found by using the genetic algorithm yield insight into the systems being controlled.
The control of atoms and molecules using coherent light fields has been a long-standing goal in chemical physics. This thesis discusses experiments which use a programmable pulse shaper to control the quantum state of electronic wavepackets in Rydberg atoms and electronic and nuclear dynamics in molecular liquids. The shape of Rydberg wavepackets was controlled by using tailored ultrafast pulses to excite a beam of cesium atoms. The quantum state of these atoms was measured using holographic techniques borrowed from optics. The experiments with molecular liquids involved the construction of an automated learning machine. A Genetic Algorithm directed the choice of shaped pulses which interacted with the molecular system inside a learning control loop. Analysis of successful pulse shapes that were found by using the GA yield insight into the systems being controlled.
Coherent control of light and matter is a major tool in current atomic physics and physical chemistry research. Technological advances in ultrafast laser pulse shaping allow control over the dynamics of molecular systems on sub-picosecond timescales. This thesis demonstrates feedback control over a variety of quantum systems and describes an adaptive genetic algorithm used in the experiments. In the gas phase, we examine control of multi-photon, dissociative ionization in diatomic sodium. The learning algorithm achieves control over the dissociative fraction primarily by adjusting the peak intensity of the laser field. We also investigate control of multi-mode stimulated Raman scattering in liquid phase methanol. Analysis of the results leads to identification of quasi-impulsive Raman coupling as a possible control mechanism. Further experiments, combined with numerical simulations of the interaction, demonstrate that an impulsive coupling of the two modes by the pump pulse can control the Raman gain. We extend the Raman control experiments to ethanol and isopropanol. Finally we apply feedback control techniques in an initial investigation of a liquid-phase chemical reaction. Specifically, we examine the ring-opening conversion of cyclohexadiene into hexatriene. The reaction dynamics occur on an excited state potential energy surface. Through control of the excitation pulse shape, we seek to guide the wavepacket evolution on the excited state to exert control over the reaction branching ratio.
Quantum computing exploits the quantum-mechanical nature of matter to exist in multiple possible states simultaneously. This new approach promises to revolutionize the present form of computing. As an approach to quantum computing, we discuss ultrafast laser pulse shaping, in particular, the acousto-optic modulator based Fourier-Transform pulse-shaper, which has the ability to modulate tunable high power ultrafast laser pulses. We show that optical pulse shaping is an attractive route to quantum computing since shaped pulses can be transmitted over optical hardware and the same infrastructure can be used for computation and optical information transfer. We also address the problem of extending coherence-times for optically induced processes.