Quantum control provides a pathway to extract more - and more useful - information from quantum sensors. In this presentation we will highlight a series of experimental and numerical studies demonstrating how quantum control can augment the performance of atomic and solid-state devices for gravimetry, precision navigation, and magnetometry. We begin with demonstrations that a class of cloud-compute-enabled AI agents can be used to autonomously optimize cold-atom loading and BEC production without user intervention. Next, we focus on the application of robust control to mitigate platform noise in fielded atom interferometers. We show 10X improvements interferometer visibility under realistic noise conditions, and also demonstrate up to 1000X improvements in sensitivity under transverse acceleration. Finally, we present novel operating techniques for magnetometry in cluttered environments, in which Slepian window functions are employed to suppress out-of-band sensitivity.
Quantum control provides a pathway to extract more - and more useful - information from quantum sensors. In this presentation we will highlight a series of experimental and numerical studies demonstrating how quantum control can augment the performance of atomic and solid-state devices for gravimetry, precision navigation, and magnetometry. We begin with demonstrations that a class of cloud-compute-enabled AI agents can be used to autonomously optimize cold-atom loading and BEC production without user intervention. Next, we focus on the application of robust control to mitigate platform noise in fielded atom interferometers. We show 10X improvements interferometer visibility under realistic noise conditions, and also demonstrate up to 1000X improvements in sensitivity under transverse acceleration. Finally, we present novel operating techniques for magnetometry in cluttered environments, in which Slepian window functions are employed to suppress out-of-band sensitivity.
Quantum sensors based on cold atoms have enormous potential to unlock new capabilities in GPS-denied navigation, civil engineering, intelligence, and Earth observation. But operating these devices in realistic environments is currently extremely challenging, and for the most part the advantages of choosing a quantum sensor over a conventional alternative are lost in the transition from laboratory to noisy field-based environments. In this work, we demonstrate for the first time in hardware that tailored light pulses, designed and implemented in software using robust control techniques, can substantially mitigate some of the most nefarious effects in a Bragg atom interferometer. We show experimentally that embedding robust control into sensor operation can improve the signal-to-noise ratio of a state-of-the-art Bragg-pulse cold-atom interferometric sensor by a factor of 4× under ideal conditions. In the presence of laser-intensity noise that varies up to 20% from shot-to-shot, commensurate with common platform vibrations, we show experimentally that using the same robust control solutions preserves fringe visibility with minimal degradation while the utility of the primitive Gaussian pulses collapses, delivering an at least 8× improvement in phase-estimation uncertainty compared with primitive pulse schemes. Across all observations, robust control delivers better performance in a noisy environment than the native hardware performance with primitive pulses under approximately ideal conditions. Finally, building on this demonstration we present a validated theoretical concept to extend this performance improvement to compact devices using concatenated sequences of robust pulses designed to enhance the sensor’s scale factor. Time-domain simulations reveal up to 10× performance enhancement in the presence of realistic atomic-cloud effects at 102ℏk momentum separation. These results show for the first time that software-defined quantum sensor operation can deliver useful performance in environmental regimes where primitive operation is impossible, providing a pathway to augment the performance of current and next generation portable cold-atom inertial sensors in real fielded settings.
Abstract Effectively manipulating quantum computing (QC) hardware in the presence of imperfect devices and control systems is a central challenge in realizing useful quantum computers. Susceptibility to noise critically limits the performance and capabilities of today’s so-called noisy intermediate-scale quantum devices, as well as any future QC technologies. Fortunately, quantum control enables efficient execution of quantum logic operations and quantum algorithms with built-in robustness to errors, and without the need for complex logical encoding. In this manuscript we introduce software tools for the application and integration of quantum control in QC research, serving the needs of hardware R&D teams, algorithm developers, and end users. We provide an overview of a set of Python-based classical software tools for creating and deploying optimized quantum control solutions at various layers of the QC software stack. We describe a software architecture leveraging both high-performance distributed cloud computation and local custom integration into hardware systems, and explain how key functionality is integrable with other software packages and quantum programming languages. Our presentation includes a detailed mathematical overview of key features including a flexible optimization toolkit, engineering-inspired filter functions for analyzing noise susceptibility in high-dimensional Hilbert spaces, and new approaches to noise and hardware characterization. Pseudocode is presented in order to elucidate common programming workflows for these tasks, and performance benchmarking is reported for numerically intensive tasks, highlighting the benefits of the selected cloud-compute architecture. Finally, we present a series of case studies demonstrating the application of quantum control solutions derived from these tools in real experimental settings using both trapped-ion and superconducting quantum computer hardware.
Quantum sensors take advantage of the inherent sensitivity of quantum systems to external environment perturbations to precisely measure target signals. The same interaction with the environment, however, limits the device sensitivity by reducing the coherence of the quantum states. Quantum control can play a crucial role in improving the sensor performance. We explore quantum control tools to improve the performance of a NitrogenVacancy (NV) center as a single-qubit sensor of ultra-weak magnetic fields in noisy environments. We present a method to obtain a precise spectroscopic characterization of the NV environment, instrumental to design robust sensing strategies with improved noise protection. Then, we exploit optimal quantum control based on a set of numerical methods to optimize the temporal dependence of the sensor driving field adapted to quantum sensing purposes, and prove its advantage to achieve best compromises between signal acquisition and noise cancellation.
Over the past two decades there has been considerable and growing interest in the development of quantum sensors. These are devices whose function is based on quantum systems and offer the potential for unprecedented sensitivity in a range of measurements. This PhD has developed three different theoretical projects examining the sensitivity improvement of these devices with a focus on atom gravimeters, which are particularly useful for measuring inertial quantities such as rotations and accelerations. We have investigated the theoretical sensitivity limits of atom gravimeters and we examined different entanglement-enhanced schemes, in order to increase their performance. To start with, we used tools from estimation theory, in order to quantify the performance of current atom gravimeters. We showed that there is additional metrological potential in these devices, and that we can extract all this information by making innovative measurements, other than the conventional population difference measurement. Our analysis introduces a new way of evaluating the performance of atom gravimeters that could influence future sensor designs. In addition, we examined entanglement-enhanced schemes, in order to improve the performance of quantum sensors, which are limited by the atom shot-noise limit. We considered entanglement generation schemes based on atom-light interactions, in order for them to be compatible with atom interferometer based sensors. More particularly, we examined a quantum non-demolition measurement scheme and an one-axis-twisting scheme with cavity feedback. In both schemes we incorporated relevant decoherence mechanisms and we analysed how the optimum parameter regime can be found, by balancing between coherence loss and spin-squeezing strength. We also examined several modifications in both models that could offer additional improvements. The results presented here could have a big impact on the future design and understanding of atom-based quantum-enhanced sensors.
Inertial sensors based on cold atoms and light-pulse interferometry exhibit state-of-the-art sensitivity and ultra-low measurement bias that could revolutionize a variety of fields including geophysics and seismology, gravitational wave detection and fundamental tests of gravity, and inertial navigation. In the latter case, cold-atom interferometers are widely considered as breakthrough technology for future autonomous INSs. Nowadays, absolute quantum inertial sensors are available as commercial and field-deployable devices. Yet, their current size and complexity has not yet reached a technology readiness level compatible with mobile applications or plug-and-play operation by non-specialists. These systems are in desperate need of further development and miniaturization. We will present progress beyond these first experiments while exploring new methods relying on 3D matter-wave manipulation that can lead to interferometer geometries that are simultaneously sensitive to accelerations and rotations in 3D and can discern their vector components within a single measurement. These novel innovations produce additional sensitivity to rotations and gravity gradients which has not yet been exploited experimentally and could be a game changing innovation for future atomic sensors. The ability to measure the full acceleration and rotation vectors with a compact, high-precision, low-bias inertial sensor could strongly impact the fields of inertial navigation, gravity gradiometry, and gyroscopy.
Atom-interferometric quantum sensors could revolutionize navigation, civil engineering, and Earth observation. However, operation in real-world environments is challenging due to external interference, platform noise, and constraints on size, weight, and power. Here we experimentally demonstrate that tailored light pulses designed using robust control techniques mitigate significant error sources in an atom-interferometric accelerometer. To mimic the effect of unpredictable lateral platform motion, we apply laser-intensity noise that varies up to 20% from pulse-to-pulse. Our robust control solution maintains performant sensing, while the utility of conventional pulses collapses. By measuring local gravity, we show that our robust pulses preserve interferometer scale factor and improve measurement precision by 10× in the presence of this noise. We further validate these enhancements by measuring applied accelerations over a 200 μg range up to 21× more precisely at the highest applied noise level. Our demonstration provides a pathway to improved atom-interferometric inertial sensing in real-world settings.