arXiv subjects

David Barker

Publications and source records attributed to David Barker.

16 recordsLinked to original sources

arXiv2025

Information Thermodynamics in a Quantum Dot Szilard Engine - Experimentally Investigating Fluctuation Theorems and Thermodynamic Uncertainty Relations

In Szilard's engine, measurement and feedback allows to extract work from an equilibrium environment, a process otherwise forbidden by the laws of thermodynamics. Recent theoretical developments have established fluctuation theorems and thermodynamic uncertainty relations that constrain the fluctuations in Szilard's engine. These relations rely on auxiliary experimental protocols known as backward experiments. Here, we experimentally investigate the thermodynamics of Szilard's engine by implementing two distinct types of backward experiments. We verify and compare the corresponding fluctuation theorems and thermodynamic uncertainty relations associated with each protocol. Our results reveal that the entropy production inferable from measurement may serve as a more relevant quantifier of information than the widely used mutual information.

cond-mat.mes-hall↗

arXiv2024

Imagen 3

We introduce Imagen 3, a latent diffusion model that generates high quality images from text prompts. We describe our quality and responsibility evaluations. Imagen 3 is preferred over other state-of-the-art (SOTA) models at the time of evaluation. In addition, we discuss issues around safety and representation, as well as methods we used to minimize the potential harm of our models.

cs.CV↗

arXiv2024

Squeezing the quantum noise of a gravitational-wave detector below the standard quantum limit

Precision measurements of space and time, like those made by the detectors of the Laser Interferometer Gravitational-wave Observatory (LIGO), are often confronted with fundamental limitations imposed by quantum mechanics. The Heisenberg uncertainty principle dictates that the position and momentum of an object cannot both be precisely measured, giving rise to an apparent limitation called the Standard Quantum Limit (SQL). Reducing quantum noise below the SQL in gravitational-wave detectors, where photons are used to continuously measure the positions of freely falling mirrors, has been an active area of research for decades. Here we show how the LIGO A+ upgrade reduced the detectors' quantum noise below the SQL by up to 3 dB while achieving a broadband sensitivity improvement, more than two decades after this possibility was first presented.

gr-qc↗

arXiv2024

Continuous microwave photon counting by semiconductor-superconductor hybrids

The growing interest in quantum information has enabled the manipulation and readout of microwave photon states with high fidelities. The presently available microwave photon counters, based on superconducting circuits, are limited to non-continuous pulsed mode operation, requiring additional steps for qubit state preparation before an actual measurement. Here, we present a continuous microwave photon counter based on superconducting cavity-coupled semiconductor quantum dots. The device utilizes photon-assisted tunneling in a double quantum dot with tunneling events being probed by a third dot. Our device detects both single and multiple-photon absorption events independently, thanks to the energy tunability of a two-level double-dot absorber. We show that the photon-assisted tunnel rates serve as the measure of the cavity photon state in line with the P(E) theory - a theoretical framework delineating the mediation of the cavity photon field via a two-level environment. We further describe the single photon detection using the Jaynes-Cummings input-output theory and show that it agrees with the P(E) theory predictions.

cond-mat.mes-hall↗

arXiv2022

Minimally dissipative information erasure in a quantum dot via thermodynamic length

In this work we explore the use of thermodynamic length to improve the performance of experimental protocols. In particular, we implement Landauer erasure on a driven electron level in a semiconductor quantum dot, and compare the standard protocol in which the energy is increased linearly in time with the one coming from geometric optimisation. The latter is obtained by choosing a suitable metric structure, whose geodesics correspond to optimal finite-time thermodynamic protocols in the slow driving regime. We show experimentally that geodesic drivings minimise dissipation for slow protocols, with a bigger improvement as one approaches perfect erasure. Moreover, the geometric approach also leads to smaller dissipation even when the time of the protocol becomes comparable with the equilibration timescale of the system, i.e., away from the slow driving regime. Our results also illustrate, in a single-electron device, a fundamental principle of thermodynamic geometry: optimal finite-time thermodynamic protocols are those with constant dissipation rate along the process.

cond-mat.mes-hall↗

arXiv2021

Experimental verification of the work fluctuation-dissipation relation for information-to-work conversion

We study experimentally work fluctuations in a Szilard engine that extracts work from information encoded as the occupancy of an electron level in a semiconductor quantum dot. We show that as the average work extracted per bit of information increases towards the Landauer limit $k_BT \ln 2$, the work fluctuations decrease in accordance with the work fluctuation-dissipation relation. We compare the results to a protocol without measurement and feedback and show that when no information is used, the work output and fluctuations vanish simultaneously contrasting the information-to-energy conversion case where increasing amount of work is produced with decreasing fluctuations. Our work highlights the importance of fluctuations in the design of information-to-work conversion processes.

cond-mat.mes-hall↗

arXiv2021

Initial Results from the LIGO Newtonian Calibrator

The precise calibration of the strain readout of the LIGO gravitational wave observatories is paramount to the accurate interpretation of gravitational wave events. This calibration is traditionally done by imparting a known force on the test masses of the observatory via radiation pressure. Here we describe the implementation of an alternative calibration scheme: the Newtonian Calibrator. This system uses a rotor consisting of both quadrupole and hexapole mass distributions to apply a time-varying gravitational force on one of the observatory's test masses. The force produced by this rotor can be predicted to $<1\%$ relative uncertainty and is well-resolved in the readout of the observatory. This system currently acts as a cross-check of the existing absolute calibration system.

gr-qc↗

arXiv2021

Point absorbers in Advanced LIGO

Small, highly absorbing points are randomly present on the surfaces of the main interferometer optics in Advanced LIGO. The resulting nano-meter scale thermo-elastic deformations and substrate lenses from these micron-scale absorbers significantly reduces the sensitivity of the interferometer directly though a reduction in the power-recycling gain and indirect interactions with the feedback control system. We review the expected surface deformation from point absorbers and provide a pedagogical description of the impact on power build-up in second generation gravitational wave detectors (dual-recycled Fabry-Perot Michelson interferometers). This analysis predicts that the power-dependent reduction in interferometer performance will significantly degrade maximum stored power by up to 50% and hence, limit GW sensitivity, but suggests system wide corrections that can be implemented in current and future GW detectors. This is particularly pressing given that future GW detectors call for an order of magnitude more stored power than currently used in Advanced LIGO in Observing Run 3. We briefly review strategies to mitigate the effects of point absorbers in current and future GW wave detectors to maximize the success of these enterprises.

physics.ins-det↗

arXiv2020

S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency

A robot's ability to act is fundamentally constrained by what it can perceive. Many existing approaches to visual representation learning utilize general-purpose training criteria, e.g. image reconstruction, smoothness in latent space, or usefulness for control, or else make use of large datasets annotated with specific features (bounding boxes, segmentations, etc.). However, both approaches often struggle to capture the fine-detail required for precision tasks on specific objects, e.g. grasping and mating a plug and socket. We argue that these difficulties arise from a lack of geometric structure in these models. In this work we advocate semantic 3D keypoints as a visual representation, and present a semi-supervised training objective that can allow instance or category-level keypoints to be trained to 1-5 millimeter-accuracy with minimal supervision. Furthermore, unlike local texture-based approaches, our model integrates contextual information from a large area and is therefore robust to occlusion, noise, and lack of discernible texture. We demonstrate that this ability to locate semantic keypoints enables high level scripting of human understandable behaviours. Finally we show that these keypoints provide a good way to define reward functions for reinforcement learning and are a good representation for training agents.

cs.RO↗

arXiv2020

Scaling data-driven robotics with reward sketching and batch reinforcement learning

We present a framework for data-driven robotics that makes use of a large dataset of recorded robot experience and scales to several tasks using learned reward functions. We show how to apply this framework to accomplish three different object manipulation tasks on a real robot platform. Given demonstrations of a task together with task-agnostic recorded experience, we use a special form of human annotation as supervision to learn a reward function, which enables us to deal with real-world tasks where the reward signal cannot be acquired directly. Learned rewards are used in combination with a large dataset of experience from different tasks to learn a robot policy offline using batch RL. We show that using our approach it is possible to train agents to perform a variety of challenging manipulation tasks including stacking rigid objects and handling cloth.

cs.RO↗

arXiv2020

advligorts: The Advanced LIGO Real-Time Digital Control and Data Acquisition System

The Advanced LIGO detectors are sophisticated opto-mechanical devices. At the core of their operation is feedback control. The Advanced LIGO project developed a custom digital control and data acquisition system to handle the unique needs of this new breed of astronomical detector. The advligorts is the software component of this system. This highly modular and extensible system has enabled the unprecedented performance of the LIGO instruments, and has been a vital component in the direct detection of gravitational waves.

physics.ins-det↗

arXiv2019

Ground motion prediction at gravitational wave observatories using archival seismic data

Gravitational wave observatories have always been affected by tele-seismic earthquakes leading to a decrease in duty cycle and coincident observation time. In this analysis, we leverage the power of machine learning algorithms and archival seismic data to predict the ground motion and the state of the gravitational wave interferometer during the event of an earthquake. We demonstrate improvement from a factor of 5 to a factor of 2.5 in scatter of the error in the predicted ground velocity over a previous model fitting based approach. The level of accuracy achieved with this scheme makes it possible to switch control configuration during periods of excessive ground motion thus preventing the interferometer from losing lock. To further assess the accuracy and utility of our approach, we use IRIS seismic network data and obtain similar levels of agreement between the estimates and the measured amplitudes. The performance indicates that such an archival or prediction scheme can be extended beyond the realm of gravitational wave detector sites for hazard-based early warning alerts.

astro-ph.IM↗

arXiv2019

The US Program in Ground-Based Gravitational Wave Science: Contribution from the LIGO Laboratory

Recent gravitational-wave observations from the LIGO and Virgo observatories have brought a sense of great excitement to scientists and citizens the world over. Since September 2015,10 binary black hole coalescences and one binary neutron star coalescence have been observed. They have provided remarkable, revolutionary insight into the "gravitational Universe" and have greatly extended the field of multi-messenger astronomy. At present, Advanced LIGO can see binary black hole coalescences out to redshift 0.6 and binary neutron star coalescences to redshift 0.05. This probes only a very small fraction of the volume of the observable Universe. However, current technologies can be extended to construct "$3^\mathrm{rd}$ Generation" (3G) gravitational-wave observatories that would extend our reach to the very edge of the observable Universe. The event rates over such a large volume would be in the hundreds of thousands per year (i.e.tens per hour). Such 3G detectors would have a 10-fold improvement in strain sensitivity over the current generation of instruments, yielding signal-to-noise ratios of 1000 for events like those already seen. Several concepts are being studied for which engineering studies and reliable cost estimates will be developed in the next 5 years.

astro-ph.IM↗

arXiv2019

Individually addressable double quantum dots formed with nanowire polytypes and identified by epitaxial markers

Double quantum dots (DQDs) hold great promise as building blocks for quantum technology as they allow for two electronic states to coherently couple. Defining QDs with materials rather than using electrostatic gating allows for QDs with a hard-wall confinement potential and more robust charge and spin states. An unresolved problem is how to individually address these quantum dots, which is necessary for controlling quantum states. We here report the fabrication of double quantum dot devices defined by the conduction band edge offset at the interface of the wurtzite and zinc blende crystal phases of InAs in nanowires. By using sacrifical epitaxial GaSb markers selectively forming on one crystal phase, we are able to precisely align gate electrodes allowing us to probe and control each QD independently. We hence observe textbook-like charge stability diagrams, a discrete energy spectrum and electron numbers consistent with theoretical estimates and investigate the tunability of the devices, finding that changing the electron number can be used to tune the tunnel barrier as expected by simple band diagram arguments.

cond-mat.mes-hall↗

arXiv2019

Blip glitches in Advanced LIGO data

Blip glitches are short noise transients present in data from ground-based gravitational-wave observatories. These glitches resemble the gravitational-wave signature of massive binary black hole mergers. Hence, the sensitivity of transient gravitational-wave searches to such high-mass systems and other potential short duration sources is degraded by the presence of blip glitches. The origin and rate of occurrence of this type of glitch have been largely unknown. In this paper we explore the population of blip glitches in Advanced LIGO during its first and second observing runs. On average, we find that Advanced LIGO data contains approximately two blip glitches per hour of data. We identify four subsets of blip glitches correlated with detector auxiliary or environmental sensor channels, however the physical causes of the majority of blips remain unclear.

physics.ins-det↗

arXiv2018

A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning

Insertion is a challenging haptic and visual control problem with significant practical value for manufacturing. Existing approaches in the model-based robotics community can be highly effective when task geometry is known, but are complex and cumbersome to implement, and must be tailored to each individual problem by a qualified engineer. Within the learning community there is a long history of insertion research, but existing approaches are typically either too sample-inefficient to run on real robots, or assume access to high-level object features, e.g. socket pose. In this paper we show that relatively minor modifications to an off-the-shelf Deep-RL algorithm (DDPG), combined with a small number of human demonstrations, allows the robot to quickly learn to solve these tasks efficiently and robustly. Our approach requires no modeling or simulation, no parameterized search or alignment behaviors, no vision system aside from raw images, and no reward shaping. We evaluate our approach on a narrow-clearance peg-insertion task and a deformable clip-insertion task, both of which include variability in the socket position. Our results show that these tasks can be solved reliably on the real robot in less than 10 minutes of interaction time, and that the resulting policies are robust to variance in the socket position and orientation.

cs.RO↗