arXiv subjects

William Thompson

Publications and source records attributed to William Thompson.

45 records · Page 3Linked to original sources

arXiv2023

Detecting Exoplanets Closer to Stars with Moderate Spectral Resolution Integral-Field Spectroscopy

While radial velocity surveys have demonstrated that the population of gas giants peaks around $3~\text{au}$, the most recent high-contrast imaging surveys have only been sensitive to planets beyond $\sim~10~\text{au}$. Sensitivity at small angular separations from stars is currently limited by the variability of the point spread function. We demonstrate how moderate-resolution integral field spectrographs can detect planets at smaller separations ($\lesssim~0.3$ arcseconds) by detecting the distinct spectral signature of planets compared to the host star. Using OSIRIS ($R$ $\approx$ 4000) at the W. M. Keck Observatory, we present the results of a planet search via this methodology around 20 young targets in the Ophiuchus and Taurus star-forming regions. We show that OSIRIS can outperform high-contrast coronagraphic instruments equipped with extreme adaptive optics and non-redundant masking in the $0.05-0.3$ arcsecond regime. As a proof of concept, we present the $34σ$ detection of a high-contrast M dwarf companion at $\approx0.1$" with a flux ratio of $\approx0.92\%$ around the field F2 star HD 148352. We developed an open-source Python package, breads, for the analysis of moderate-resolution integral field spectroscopy data in which the planet and the host star signal are jointly modeled. The diffracted starlight continuum is forward-modeled using a spline model, which removes the need for prior high-pass filtering or continuum normalization. The code allows for analytic marginalization of linear hyperparameters, simplifying posterior sampling of other parameters (e.g., radial velocity, effective temperature). This technique could prove very powerful when applied to integral field spectrographs like NIRSpec on the JWST and other upcoming first-light instruments on the future Extremely Large Telescopes.

astro-ph.EP↗

arXiv2023

Satellite-based high-resolution maps of cocoa planted area for Côte d'Ivoire and Ghana

Côte d'Ivoire and Ghana, the world's largest producers of cocoa, account for two thirds of the global cocoa production. In both countries, cocoa is the primary perennial crop, providing income to almost two million farmers. Yet precise maps of cocoa planted area are missing, hindering accurate quantification of expansion in protected areas, production and yields, and limiting information available for improved sustainability governance. Here, we combine cocoa plantation data with publicly available satellite imagery in a deep learning framework and create high-resolution maps of cocoa plantations for both countries, validated in situ. Our results suggest that cocoa cultivation is an underlying driver of over 37% and 13% of forest loss in protected areas in Côte d'Ivoire and Ghana, respectively, and that official reports substantially underestimate the planted area, up to 40% in Ghana. These maps serve as a crucial building block to advance understanding of conservation and economic development in cocoa producing regions.

cs.CV↗

arXiv2023

Direct Imaging and Astrometric Detection of a Gas Giant Planet Orbiting an Accelerating Star

Direct imaging of gas giant exoplanets provides key information on planetary atmospheres and the architectures of planetary systems. However, few planets have been detected in blind surveys used to achieve imaging detections. Using Gaia and Hipparcos astrometry we identified dynamical evidence for a gas giant planet around the nearby star HIP 99770 and then confirmed this planet by direct imaging with the Subaru Coronagraphic Extreme Adaptive Optics Project. HIP 99770 b orbits 17 astronomical units from its host star, with an insolation comparable to Jupiter's and a dynamical mass of 13.9--16.1 Jupiter masses. Its planet-to-star mass ratio (7--8$\times$10$^{-3}$) is comparable to that other directly-imaged planets. The planet's atmosphere resembles an older, less-cloudy analogue of the atmospheres of previously-imaged exoplanets around HR 8799.

astro-ph.EP↗

arXiv2022

Causal Vector Autoregression Enhanced with Covariance and Order Selection

A causal vector autoregressive (CVAR) model is introduced for weakly stationary multivariate processes, combining a recursive directed graphical model for the contemporaneous components and a vector autoregressive model longitudinally. Block Cholesky decomposition with varying block sizes is used to solve the model equations and estimate the path coefficients along a directed acyclic graph (DAG). If the DAG is decomposable, i.e. the zeros form a reducible zero pattern (RZP) in its adjacency matrix, then covariance selection is applied that assigns zeros to the corresponding path coefficients. Real life applications are also considered, where for the optimal order $p\ge 1$ of the fitted CVAR$(p)$ model, order selection is performed with various information criteria.

stat.ME↗

arXiv2022

Deep orbital search for additional planets in the HR 8799 system

The HR 8799 system hosts four massive planets orbiting 15 and 80 AU. Studies of the system's orbital stability and its outer debris disk open the possibility of additional planets, both interior to and exterior to the known system. Reaching a sufficient sensitivity to search for interior planets is very challenging due to the combination of bright quasi static speckle noise close to the stellar diffraction core and relatively fast orbital motion. In this work, we present a deep L-band imaging campaign using NIRC2 at Keck comprising 14 observing sequences. We further re-reduce archival data for a total of 16.75 hours, one of the largest uniform datasets of a single direct imaging target. Using a Bayesian modeling technique for detecting planets in images while compensating for plausible orbital motion, we then present deep limits on the existence of additional planets in the HR 8799 system. The final combination shows a tentative candidate, consistent with 4-7 $M_{jup}$ at 4-5 AU, detected with an equivalent false alarm probability better than $3σ$. This analysis technique is widely applicable to archival data and to new observations from upcoming missions that revisit targets at multiple epochs.

astro-ph.EP↗

arXiv2021

Improved Contrast in Images of Exoplanets using Direct SNR Optimization

Direct imaging of exoplanets is usually limited by quasi-static speckles. These uncorrected aberrations in a star's point spread function (PSF) obscure faint companions and limit the sensitivity of high-contrast imaging instruments. Most current approaches to processing differential imaging sequences like angular differential imaging (ADI) and spectral differential imaging (SDI) produce a self-calibrating dataset that are combined in a linear least squares solution to minimize the noise. Due to temporal and chromatic evolution of a telescope's PSF, the best correlated reference images are usually the most contaminated by the planet, leading to self-subtraction and reducing the planet throughput. In this paper, we present an algorithm that directly optimizes the non-linear equation for planet signal to noise ratio (SNR). This new algorithm does not require us to reject adjacent reference images and optimally balances noise reduction with self-subtraction. We then show how this algorithm can be applied to multiple images simultaneously for a further reduction in correlated noise, directly maximizing the SNR of the final combined image. Finally, we demonstrate the technique on an illustrative sequence of HR8799 using the new Julia-based Signal to Noise Analysis Pipeline (SNAP). We show that SNR optimization can provide up to a $5\times$ improvement in contrast close to the star. Applicable to both new and archival data, this technique will allow for the detection of lower mass, and closer in companions, or achieve the same sensitivity with less telescope time.

astro-ph.IM↗

arXiv2020

Workshop on Quantification, Communication, and Interpretation of Uncertainty in Simulation and Data Science

Modern science, technology, and politics are all permeated by data that comes from people, measurements, or computational processes. While this data is often incomplete, corrupt, or lacking in sufficient accuracy and precision, explicit consideration of uncertainty is rarely part of the computational and decision making pipeline. The CCC Workshop on Quantification, Communication, and Interpretation of Uncertainty in Simulation and Data Science explored this problem, identifying significant shortcomings in the ways we currently process, present, and interpret uncertain data. Specific recommendations on a research agenda for the future were made in four areas: uncertainty quantification in large-scale computational simulations, uncertainty quantification in data science, software support for uncertainty computation, and better integration of uncertainty quantification and communication to stakeholders.

cs.CY↗

arXiv2019

Standing on the Shoulders of Giants: AI-driven Calibration of Localisation Technologies

High accuracy localisation technologies exist but are prohibitively expensive to deploy for large indoor spaces such as warehouses, factories, and supermarkets to track assets and people. However, these technologies can be used to lend their highly accurate localisation capabilities to low-cost, commodity, and less-accurate technologies. In this paper, we bridge this link by proposing a technology-agnostic calibration framework based on artificial intelligence to assist such low-cost technologies through highly accurate localisation systems. A single-layer neural network is used to calibrate less accurate technology using more accurate one such as BLE using UWB and UWB using a professional motion tracking system. On a real indoor testbed, we demonstrate an increase in accuracy of approximately 70% for BLE and 50% for UWB. Not only the proposed approach requires a very short measurement campaign, the low complexity of the single-layer neural network also makes it ideal for deployment on constrained devices typically for localisation purposes.

cs.NI↗

arXiv2013

Performance of Spatial Modulation using Measured Real-World Channels

In this paper, for the first time real-world channel measurements are used to analyse the performance of spatial modulation (SM), where a full analysis of the average bit error rate performance (ABER) of SM using measured urban correlated and uncorrelated Rayleigh fading channels is provided. The channel measurements are taken from an outdoor urban multiple input multiple output (MIMO) measurement campaign. Moreover, ABER performance results using simulated Rayleigh fading channels are provided and compared with a derived analytical bound for the ABER of SM, and the ABER results for SM using the measured urban channels. The ABER results using the measured urban channels validate the derived analytical bound and the ABER results using the simulated channels. Finally, the ABER of SM is compared with the performance of spatial multiplexing (SMX) using the measured urban channels for small and large scale MIMO. It is shown that SM offers nearly the same or a slightly better performance than SMX for small scale MIMO. However, SM offers large reduction in ABER for large scale MIMO.

cs.IT↗