Quantum technology devices are approaching a level of maturity, which would allow for adoption by non-specialist users. The advancements made in microprocessor-based electronics and database software can be combined to create a flexible, efficient, and modular experimental monitoring system. We present an example of such a monitoring system where key experimental parameters such as vacuum pressure, laser beam powers and electrical currents across a network of cold atom laboratories are monitored. The ability to passively collect data and cross-diagnose issues reduces debugging time and allows for efficient control over several cold atom experiments. This level of control facilitates the progression of atomic physics experiments. In my talk, I will show how using such a monitoring system has led to the production of a Bose-Einstein condensate (BEC) from home in one of our laboratories that did not have a BEC before.
Quantum technology devices are approaching a level of maturity, which would allow for adoption by non-specialist users. The advancements made in microprocessor-based electronics and database software can be combined to create a flexible, efficient, and modular experimental monitoring system. We present an example of such a monitoring system where key experimental parameters such as vacuum pressure, laser beam powers and electrical currents across a network of cold atom laboratories are monitored. The ability to passively collect data and cross-diagnose issues reduces debugging time and allows for efficient control over several cold atom experiments. This level of control facilitates the progression of atomic physics experiments. In my talk, I will show how using such a monitoring system has led to the production of a Bose-Einstein condensate (BEC) from home in one of our laboratories that did not have a BEC before.
Quantum technology is approaching a level of maturity, recently demonstrated in space-borne experiments and in-field measurements, which would allow for adoption by non-specialist users. Parallel advancements made in microprocessor-based electronics and database software can be combined to create robust, versatile and modular experimental monitoring systems. Here, we describe a monitoring network used across a number of cold atom laboratories with a shared laser system. The ability to diagnose malfunction, unexpected or unintended behaviour and passively collect data for key experimental parameters, such as vacuum chamber pressure, laser beam power, or resistances of important conductors, significantly reduces debugging time. This allows for efficient control over a number of experiments and remote control when access is limited.
Quantum technology is approaching a level of maturity, recently demonstrated in space-borne experiments and in-field measurements, which would allow for adoption by non-specialist users. Parallel advancements made in microprocessor-based electronics and database software can be combined to create robust, versatile and modular experimental monitoring systems. Here, we describe a monitoring network used across a number of cold atom laboratories with a shared laser system. The ability to diagnose malfunction, unexpected or unintended behavior and passively collect data for key experimental parameters, such as vacuum chamber pressure, laser beam power, or resistances of important conductors, significantly reduces debugging time. This allows for efficient control over a number of experiments and remote control when access is limited.
Abstract Quantum technology is approaching a level of maturity, recently demonstrated in space-borne experiments and in-field measurements, which would allow for adoption by non-specialist users. Parallel advancements made in microprocessor-based electronics and database software can be combined to create robust, versatile and modular experimental monitoring systems. Here, we describe a monitoring network used across a number of cold atom laboratories with a shared laser system. The ability to diagnose malfunction, unexpected or unintended behavior and passively collect data for key experimental parameters, such as vacuum chamber pressure, laser beam power, or resistances of important conductors, significantly reduces debugging time. This allows for efficient control over a number of experiments and remote control when access is limited.
Ultra-cold atoms and Bose-Einstein condensates (BECs) provide a dramatic example of a quantum system on a macroscopic scale. Atoms can be cooled down to temperatures below 1μK and their de Broglie wavelengths become large enough to be readily observed in experiments. This has spawned a new research area known as atom optics which refers to the study and control of atoms based on their wave nature. In recent years, physicists have been performing experiments with coherent atoms from a Bose-Einstein condensate. The ability to produce and manipulate condensates above microfabricated surfaces may one day lead to new technologies such as atom interferometers on a chip.
The confinement and control of atomic clouds, at temperatures measured in nanokelvin, has become a valuable tool for physicists. As a source of new physics, development of cooling techniques has led to innovative new ways to probe the nature of reality. Of particular note are experiments carried out on new and exotic states of matter such as the Bose-Einstein condensate, unseen before the advent of these techniques. Likewise, the potential for applications outside of the lab is extensive and encompasses navigation, timekeeping, quantum communication and quantum computing. Manipulating cold atoms in the presence of a so-called ‘atom chip’ (a millimetre-scale electronic device) is currently considered the future of miniaturising these experiments and measurements, but since they still require precisely locked and stabilised lasers and predominantly must take place in the ultra-high vacuum regime, quantum control relies on an extensive and well-established infrastructure of optics, electronics, vacuum chambers and pumps. This encumbrance has slowed down the transition from chip-in-a-lab experiments to lab-on-a-chip technologies. This thesis is an account of work carried out in the development of enabling technologies which will accelerate this transition, including details of prototype devices made using established semiconductor and MEMS planar fabrication techniques. The construction and testing of an apparatus for anodically and eutectically bonding die-scale samples in ultra-high vacuum is described, along with an analysis and characterisation of some of its products.
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.