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Optimal Control of Bose-Einstein Condensates

Ulrich Hohenester

Published Jan 1, 2012• 0 citations
OpenAlex

Abstract

In this thesis we use optimal control theory to control a BoseEinstein condensate. We focus on an experiment conducted at the Vienna University of Technology where a Bose-Einstein condensate is produced and trapped on an atom chip, and two entangled matter waves are produced. Such a twin atom beam has many technical applications and is necessary for matter wave interferometry, for example. One critical step in this experiment is the excitation of the condensate, which is achieved by displacing the minimum of the confinement potential (“shaking”). In order to find a time dependent potential that excites the condensate, optimal control theory is necessary and able to produce satisfying results. However, theoretical predictions and experimental data do not match perfectly. This is mainly due to the impulse response filter, causing a difference between the calculated and the experimentally accessible control field. To solve this problem in this thesis, we incorporate the effect of this impulse response filter in the optimal control algorithm. The new system is then not local in time anymore and there are new boundary conditions to meet. These problems are overcome and the obtained control fields are much closer to the experiment than without considering the effects of the impulse response filter. It is even possible to find working control fields with a transition time of only two milliseconds or to transfer the condensate in a higher excited state.

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This thesis develops a numerical optimal-control framework for investigating the manipulation of one-dimensional Bose–Einstein condensates governed by the Gross–Pitaevskii equation. The control problem is formulated as a constrained optimization problem in which time-dependent external potentials are optimized to steer condensate dynamics while minimizing unwanted excitations.The first part considers the compression of a condensate containing a darksoliton confined in a box potential. Optimal trajectories of the trap boundaries are obtained that preserve the solitonic structure while strongly reducing den-sity and phase excitations compared with conventional linear protocols. Thesecond part addresses the opposite problem of soliton absorption. By optimizing the motion of the trapping boundaries, moving gray solitons can be efficiently removed and the condensate driven toward its ground state. The third part investigates the merging of two condensates separated by a potential barrier. Optimal barrier-removal protocols are computed for different initialphase differences between the condensates. The dependence of the optimal control strategy on the phase mismatch is analyzed, including the formation of adark soliton in the case of a PI phase difference and the construction of robustprotocols applicable when the phase difference is unknown.Finally, the optimal-control framework is extended to tunnel-coupled con-densates. The coupled Gross–Pitaevskii equations are formulated as a con-strained optimization problem, and the corresponding adjoint equations arederived. This framework provides the foundation for future investigations of optimal control in coupled condensate systems.Together, these results demonstrate how optimal control can be used both to preserve and to manipulate nonlinear excitations and phase structures in Bose–Einstein condensates, providing tools for quantum-state engineering inultracold atomic systems.

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Bose-Einstein condensates (BECs), a quantum state of matter formed when bosonic atoms are cooled close to absolute zero, have become the premier platform for investigating fundamental physics with atomic vapours. Experiments on Bose-Einstein condensates now achieve exquisite control over many aspects of the system, including interactions, trapping potential, and dynamics. This has precipitated a new wave of research into many-body quantum phenomena and, in particular, solitons. These structures are fundamental excitations of an interacting non-linear medium, of interest to a multitude of scientific disciplines from non-linear optics to financial markets. The highly controllable environment of BECs form an attractive playground for the study of solitons allowing the non-linearity to be dynamically tuned, facilitating deeper investigations into these structures. Consistently generating and analysing solitons in BEC experiments continues to be problematic. 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SIAM Journal on Scientific Computing•Jan 1, 2008•24 citations
In this thesis we use optimal control theory to control a BoseEinstein condensate. We focus on an experiment conducted at the Vienna University of Technology where a Bose-Einstein condensate is produced and trapped on an atom chip, and two entangled matter waves are produced. Such a twin atom beam has many technical applications and is necessary for matter wave interferometry, for example. One critical step in this experiment is the excitation of the condensate, which is achieved by displacing the minimum of the confinement potential (“shaking”). In order to find a time dependent potential that excites the condensate, optimal control theory is necessary and able to produce satisfying results. However, theoretical predictions and experimental data do not match perfectly. This is mainly due to the impulse response filter, causing a difference between the calculated and the experimentally accessible control field. To solve this problem in this thesis, we incorporate the effect of this impulse response filter in the optimal control algorithm. The new system is then not local in time anymore and there are new boundary conditions to meet. These problems are overcome and the obtained control fields are much closer to the experiment than without considering the effects of the impulse response filter. It is even possible to find working control fields with a transition time of only two milliseconds or to transfer the condensate in a higher excited state.
This thesis develops a numerical optimal-control framework for investigating the manipulation of one-dimensional Bose–Einstein condensates governed by the Gross–Pitaevskii equation. The control problem is formulated as a constrained optimization problem in which time-dependent external potentials are optimized to steer condensate dynamics while minimizing unwanted excitations.The first part considers the compression of a condensate containing a darksoliton confined in a box potential. Optimal trajectories of the trap boundaries are obtained that preserve the solitonic structure while strongly reducing den-sity and phase excitations compared with conventional linear protocols. Thesecond part addresses the opposite problem of soliton absorption. By optimizing the motion of the trapping boundaries, moving gray solitons can be efficiently removed and the condensate driven toward its ground state. The third part investigates the merging of two condensates separated by a potential barrier. Optimal barrier-removal protocols are computed for different initialphase differences between the condensates. The dependence of the optimal control strategy on the phase mismatch is analyzed, including the formation of adark soliton in the case of a PI phase difference and the construction of robustprotocols applicable when the phase difference is unknown.Finally, the optimal-control framework is extended to tunnel-coupled con-densates. The coupled Gross–Pitaevskii equations are formulated as a con-strained optimization problem, and the corresponding adjoint equations arederived. This framework provides the foundation for future investigations of optimal control in coupled condensate systems.Together, these results demonstrate how optimal control can be used both to preserve and to manipulate nonlinear excitations and phase structures in Bose–Einstein condensates, providing tools for quantum-state engineering inultracold atomic systems.
In this paper we study the fast adiabatic-like expansion of a one-dimensional Bose-Einstein condensate (BEC) confined in a harmonic potential, using the theory of time-optimal control. We find that under reasonable assumptions suggested by the experimental setup, the minimum-time expansion occurs when the frequency of the potential changes in a bang-bang form between the permitted values. We calculate the necessary expansion time and show that it scales logarithmically with large values of the expansion factor. This work is expected to find applications in areas where the efficient manipulations of BEC is of utmost importance. As an example we present the field of atom interferometry with BEC, where the wavelike properties of atoms are used to perform interference experiments that measure with unprecedented precision small shifts induced by phenomena like rotation, acceleration, and gravity gradients.
This thesis presents the implementation of a control system for an ultra-cold atom experiment. This system allows for the acceleration of data acquisition and the use of machine learning algorithms to optimize the operation of the experiment. The characteristics of the new system are presented, as well as the software suite allowing the control and analysis of the data. The different algorithms used are described, as well as the first optimization results obtained.In the experiment, a Bose-Einstein condensate of rubidium atoms is confined to the surface of an ellipsoid of revolution. This original trapping geometry comes from the dressing of the atoms by a radiofrequency field in a magnetic quadrupole trap.In this geometry, it is possible to compensate for the effect of gravity, and I present the experimental results obtained. We observe the spontaneous formation of a condensed ring near the equator of the bubble, and we interpret this behavior as an effect of the zero point energy of the transverse confinement.A more elaborate model requiring the introduction of terms beyond the rotating wave approximation is compared to the experimental data.
Bose-Einstein condensates (BECs), a quantum state of matter formed when bosonic atoms are cooled close to absolute zero, have become the premier platform for investigating fundamental physics with atomic vapours. Experiments on Bose-Einstein condensates now achieve exquisite control over many aspects of the system, including interactions, trapping potential, and dynamics. This has precipitated a new wave of research into many-body quantum phenomena and, in particular, solitons. These structures are fundamental excitations of an interacting non-linear medium, of interest to a multitude of scientific disciplines from non-linear optics to financial markets. The highly controllable environment of BECs form an attractive playground for the study of solitons allowing the non-linearity to be dynamically tuned, facilitating deeper investigations into these structures. Consistently generating and analysing solitons in BEC experiments continues to be problematic. In particular, the non-linear dynamics of BECs, though required for the generation of solitons, produce particularly challenging control and optimization problems. These control problems must be solved before further investigations into the fundamental physics of soliton dynamics can be answered. This thesis makes three important advances in the control and measurement of BECs that will lead to better generation and observation of solitons. (1) a theoretical model for a control scheme capable of highly precise wavefunction engineering, (2) the experimental implementation of a machine learning algorithm for online optimisation, and (3) a continuous non-destructive imaging system capable of directly observing soliton dynamics in real-time. Together, these advances provide a suite of tools for manipulating and exploiting solitons in Bose-Einstein condensates. A novel technique was developed theoretically, offering control of the macroscopic wavefunction of a Bose-Einstein condensate with unprecedented spatial resolution and speed. The ability to control the atomic wavefunction at the fundamental length scale is key to the advancement of many quantum technologies such as quantum simulators. The magnetic resonance control scheme is demonstrated through simulation of a 87Rb condensate with the exemplar model generating a single dark soliton with corresponding π phase kink. The soliton represents a structure at the fundamental length scale of the system, and demonstrates the potential of the scheme for precision state engineering. The scheme is extended to generate higher-order soliton modes which are yet to be experimentally realised. A machine learning algorithm based on Gaussian processes was developed and implemented on the evaporative cooling stage of the production of a 87Rb Bose-Einstein condensate, successfully demonstrating fast optimisation to condensation. The Gaussian process develops a statistical model based on the data that enables the characterisation of the relationship between the experimental controls and resultant quality of the BEC. This relationship is often obfuscated through technical details of the apparatus, frustrating the use of theoretical models to design optimal evaporation ramps. These models often only consider ergodic dynamics with two-body s-wave interactions and no other loss rates with better ramps likely exploiting more complex interactions. The internal model generated from the Gaussian process utilised uncertainty in measured data, making the optimisation more robust to experimental noise than alternate methods. The algorithm is shown to produce high quality Bose-Einstein condensates in 10 times fewer experimental iterations than previously used online optimisation techniques. By exploiting information on the sensitivity of each control, the model can be used to aid experimental design. The convergence of the optimisation is further improved by eliminating a superfluous parameter identified by the model. The general usefulness of machine learning compared with bespoke optimisation algorithms has seen machine learning approach ubiquity. Finally, an experimentally straightforward technique for continuous non-destructive imaging of matter-wave solitons was developed and implemented, facilitating measurements of stochastic phenomena. The technique is readily practicable on any ultracold atom experiment with an existing absorption imaging system, simply requiring the probe laser be far-detuned from resonance. With a signal-to-noise of ∼ 33 at 1.25 GHz detuning, the technique is capable of producing 100 images with no observable heating or atom loss. Coupled with a fast optical phase locked loop, the technique can be used in conjunction with absorption imaging to generate a series of non-destructive images followed by a final high signal-to-noise absorption image solely through moving the laser on resonance for the final image. The high performance and utility of this imaging setup make it a powerful tool for ultra-cold atom experiments.
Abstract. We present theoretical and experimental results on high-fidelity transfer of a trapped Bose-Einstein condensate into its first vibrationally excited eigenstate. The excitation is driven by mechanical motion of the trap, along a trajectory obtained from optimal control theory. Excellent agreement between theory and experiment is found over a large range of parameters. We develop an approximate model to map the dynamics of the many-body condensate wave function to a driven two-level system.
The control of the transport of Bose–Einstein condensates in magnetic microtraps is formulated within the framework of optimal control theory and solved by multigrid optimization schemes. The time evolution of the wave function of Bose–Einstein condensates is governed by the Gross–Pitaevskii equation and can be manipulated through variation of a controllable magnetic confinement potential. In order to define an optimal control strategy, an appropriate cost functional is introduced that must be minimized under the constraint given by the dynamic equation. The resulting optimality system consists of two nonlinear Schrödinger-type equations with opposite time orientation coupled with an elliptic equation for the control function. These equations are approximated by using a time-splitting pseudospectral method and finite differences. To solve the resulting problem a cascadic nonlinear conjugate gradient scheme and a multigrid optimization scheme are considered. The convergence properties of these two schemes are investigated theoretically, and their computational performance is discussed based on results of numerical experiments. It appears that the multigrid optimization scheme provides a robust optimization strategy.