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Bulletin of the American Physical Society

Directed Field Ionization

Vincent C. Gregoric, Xinyue Kang, Zhimin Cheryl Liu, Zoe A. Rowley, Thomas J. Carroll, Michael W. Noel

Published Apr 5, 2017• 0 citations
OpenAlex

Abstract

Quantum control of the pathway along which a Rydberg electron field ionizes is demonstrated. Selective field ionization is typically done with a slowly rising electric field pulse. The $(1/n^*)^4$ scaling of the classical ionization threshold leads to a rough mapping between arrival time of the electron signal and principal quantum number of the Rydberg electron. This is complicated by the many avoided level crossings that the electron must traverse on the way to ionization, which in general leads to broadening of the time-resolved field ionization signal. In order to control the ionization pathway, thus directing the signal to the desired arrival time, a perturbing electric field produced by an arbitrary waveform generator is added to a slowly rising electric field. A genetic algorithm evolves the perturbing field in an effort to achieve the target time-resolved field ionization signal.

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Quantum control via a genetic algorithm of the field ionization pathway of a Rydberg electron

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Quantum control of the pathway along which a Rydberg electron field ionizes is experimentally and computationally demonstrated. Selective field ionization is typically done with a slowly rising electric field pulse. The ${(1/{n}^{*})}^{4}$ scaling of the classical ionization threshold leads to a rough mapping between arrival time of the electron signal and principal quantum number of the Rydberg electron. This is complicated by the many avoided level crossings that the electron must traverse on the way to ionization, which in general leads to broadening of the time-resolved field ionization signal. In order to control the ionization pathway, thus directing the signal to the desired arrival time, a perturbing electric field produced by an arbitrary wave-form generator is added to a slowly rising electric field. A genetic algorithm evolves the perturbing field in an effort to achieve the target time-resolved field ionization signal.

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The electron signals from the field ionization of two closely spaced Rydberg states of rubidium-85 are separated using quantum control. In selective field ionization, the state distribution of a collection of Rydberg atoms is measured by ionizing the atoms with a ramped electric field. Generally, atoms in higher energy states ionize at lower fields, so ionized electrons which are detected earlier in time can be correlated with higher energy Rydberg states. However, the resolution of this technique is limited by the Stark effect. As the electric field is increased, the electron encounters numerous avoided Stark level crossings which split the amplitude among many states, thus broadening the time-resolved ionization signal. Previously, a genetic algorithm has been used to control the signal shape of a single Rydberg state. The present work extends this technique to separate the signals from the $34s$ and $33p$ states of rubidium-85, which are overlapped when using a simple field ramp as in selective field ionization.

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A Rydberg atom has a highly excited valence electron which is weakly bound and far from the nucleus. These atoms have exaggerated properties that make them attractive candidates for quantum computation and studies of fundamental quantum mechanics. A widely used method for measuring the energy level of the outer electron is to ionize it with an electric field pulse and send it to a detector where the resulting spectrum is measured. However, this technique fails to resolve energy levels that are closely spaced. The electron’s path to ionization branches several hundreds of times, causing neighboring energy levels to overlap. By using an engineered electric field pulse, we can manipulate which branches the electron follows. To design our electric field pulse, we created a genetic algorithm. A genetic algorithm is an optimization process analogous to biological evolution. Our algorithm creates a random population of electric field pulses, evaluates the fitness of the field pulses, and allows the fittest members of the population to mate and create a new generation. We present results of our simulations.

•Jan 1, 2016•0 citations
Quantum control of the pathway along which a Rydberg electron field ionizes is demonstrated. Selective field ionization is typically done with a slowly rising electric field pulse. The (1/n∗)4(1/n^*)^4(1/n∗)4 scaling of the classical ionization threshold leads to a rough mapping between arrival time of the electron signal and principal quantum number of the Rydberg electron. This is complicated by the many avoided level crossings that the electron must traverse on the way to ionization, which in general leads to broadening of the time-resolved field ionization signal. In order to control the ionization pathway, thus directing the signal to the desired arrival time, a perturbing electric field produced by an arbitrary waveform generator is added to a slowly rising electric field. A genetic algorithm evolves the perturbing field in an effort to achieve the target time-resolved field ionization signal.
Quantum control of the pathway along which a Rydberg electron field ionizes is experimentally and computationally demonstrated. Selective field ionization is typically done with a slowly rising electric field pulse. The (1/n∗)4{(1/{n}^{*})}^{4}(1/n∗)4 scaling of the classical ionization threshold leads to a rough mapping between arrival time of the electron signal and principal quantum number of the Rydberg electron. This is complicated by the many avoided level crossings that the electron must traverse on the way to ionization, which in general leads to broadening of the time-resolved field ionization signal. In order to control the ionization pathway, thus directing the signal to the desired arrival time, a perturbing electric field produced by an arbitrary wave-form generator is added to a slowly rising electric field. A genetic algorithm evolves the perturbing field in an effort to achieve the target time-resolved field ionization signal.
The electron signals from the field ionization of two closely spaced Rydberg states of rubidium-85 are separated using quantum control. In selective field ionization, the state distribution of a collection of Rydberg atoms is measured by ionizing the atoms with a ramped electric field. Generally, atoms in higher energy states ionize at lower fields, so ionized electrons which are detected earlier in time can be correlated with higher energy Rydberg states. However, the resolution of this technique is limited by the Stark effect. As the electric field is increased, the electron encounters numerous avoided Stark level crossings which split the amplitude among many states, thus broadening the time-resolved ionization signal. Previously, a genetic algorithm has been used to control the signal shape of a single Rydberg state. The present work extends this technique to separate the signals from the 34s34s34s and 33p33p33p states of rubidium-85, which are overlapped when using a simple field ramp as in selective field ionization.
A Rydberg atom is an atom with a highly excited and weakly bound valence electron. A widespread method of studying quantum mechanics with Rydberg atoms is to ionize the electron and measure its arrival time. We use a Genetic Algorithm (GA) to control the electron's path to ionization. The Rydberg electron's energy levels are strongly shifted by the presence of an electric field. The energy levels shift and curve, but never cross. At an avoided crossing the electron can jump from one level to the next. By engineering the electric field's time dependence, we thereby control the path to ionization. A GA is an optimization method modeled on natural selection. We use a GA to evolve electric field pulses to achieve a target path to ionization. Our algorithm initially generates random members of a population and then assigns each member a fitness score based on how well they achieve our target solution. We use elitism to pass the best members of the population directly into the next generation. We use tournament style selection to choose fit members to mate and pass their genes to the next generation. We then mutate the offspring to provide genetic diversity to our population. We present our results on the effects of varying GA parameters and modifying the GA to better model the experiment.
Abstract Selective field ionization (SFI) is used to determine the state or distribution of states to which a Rydberg atom is excited. By evolving a small perturbation to the ramped electric field using a genetic algorithm, the shape of the time-resolved ionization signal can be controlled. This allows for the separation of signals from pairs of states that would be indistinguishable with unperturbed SFI. Measurements and calculations are presented that demonstrate this technique and shed light on how the perturbation directs the pathway of the electron to ionization. Pseudocode for the genetic algorithm is provided. Using the improved resolution afforded by this technique, quantitative measurements of the 36 p 3 / 2 + 36 p 3 / 2 → 36 s 1 / 2 + 37 s 1 / 2 dipole–dipole interaction are made.
Experimentally, we would like to demonstrate the process of selective field ionization of electrons as evidence of quantum control in a system of ultracold rubidium-85 Rydberg atoms. In order to accomplish this, an electric field pulse which is optimized to take an initial Rydberg electron state and produce the desired ionization spectra is necessary. We utilize techniques from artificial intelligence to develop a genetic algorithm for the optimization process. Our algorithm is computationally tested on an artificially constructed quantum system consisting of four energy states. In evaluating the viability of any given field pulse, we calculate the probability of an electron being found in a given state at a certain maximum field value by numerically evolving the electron’s wave function over time.
A Rydberg atom has a highly excited valence electron which is weakly bound and far from the nucleus. These atoms have exaggerated properties that make them attractive candidates for quantum computation and studies of fundamental quantum mechanics. A widely used method for measuring the energy level of the outer electron is to ionize it with an electric field pulse and send it to a detector where the resulting spectrum is measured. However, this technique fails to resolve energy levels that are closely spaced. The electron’s path to ionization branches several hundreds of times, causing neighboring energy levels to overlap. By using an engineered electric field pulse, we can manipulate which branches the electron follows. To design our electric field pulse, we created a genetic algorithm. A genetic algorithm is an optimization process analogous to biological evolution. Our algorithm creates a random population of electric field pulses, evaluates the fitness of the field pulses, and allows the fittest members of the population to mate and create a new generation. We present results of our simulations.