arXiv subjects

Rachel Cooper

Publications and source records attributed to Rachel Cooper.

7 recordsLinked to original sources

arXiv2025

AMIGO: a Data-Driven Calibration of the JWST Interferometer

The James Webb Space Telescope (JWST) hosts a non-redundant Aperture Masking Interferometer (AMI) in its Near Infrared Imager and Slitless Spectrograph (NIRISS) instrument, providing the only dedicated interferometric facility aboard - magnitudes more precise than any interferometric experiment previously flown. However, the performance of AMI (and other high resolution approaches such as kernel phase) in recovery of structure at high contrasts has not met design expectations. A major contributing factor has been the presence of uncorrected detector systematics, notably charge migration effects in the H2RG sensor, and insufficiently accurate mask metrology. Here we present Amigo, a data-driven calibration framework and analysis pipeline that forward-models the full JWST AMI system - including its optics, detector physics, and readout electronics - using an end-to-end differentiable architecture implemented in the Jax framework and in particular exploiting the dLux optical modelling package. Amigo directly models the generation of up-the-ramp detector reads, using an embedded neural sub-module to capture non-linear charge redistribution effects, enabling the optimal extraction of robust observables, for example kernel amplitudes and phases, while mitigating systematics such as the brighter-fatter effect. We demonstrate Amigo's capabilities by recovering the ABDor AC binary from commissioning data with high-precision astrometry, and detecting both HD206893B and the inner substellar companion HD206893c: a benchmark requiring contrasts approaching 10 magnitudes at separations of only 100 mas. These results exceed outcomes from all published pipelines, and re-establish AMI as a viable competitor for imaging at high contrast at the diffraction limit. Amigo is publicly available as open-source software community resource.

astro-ph.IM↗

arXiv2023

The JWST Early Release Science Program for Direct Observations of Exoplanetary Systems IV: NIRISS Aperture Masking Interferometry Performance and Lessons Learned

We present a performance analysis for the aperture masking interferometry (AMI) mode on board the James Webb Space Telescope Near Infrared Imager and Slitless Spectrograph (JWST/NIRISS). Thanks to self-calibrating observables, AMI accesses inner working angles down to and even within the classical diffraction limit. The scientific potential of this mode has recently been demonstrated by the Early Release Science (ERS) 1386 program with a deep search for close-in companions in the HIP 65426 exoplanetary system. As part of ERS 1386, we use the same data set to explore the random, static, and calibration errors of NIRISS AMI observables. We compare the observed noise properties and achievable contrast to theoretical predictions. We explore possible sources of calibration errors and show that differences in charge migration between the observations of HIP 65426 and point-spread function calibration stars can account for the achieved contrast curves. Lastly, we use self-calibration tests to demonstrate that with adequate calibration NIRISS F380M AMI can reach contrast levels of $\sim9-10$ mag at $\gtrsim \lambda/D$. These tests lead us to observation planning recommendations and strongly motivate future studies aimed at producing sophisticated calibration strategies taking these systematic effects into account. This will unlock the unprecedented capabilities of JWST/NIRISS AMI, with sensitivity to significantly colder, lower-mass exoplanets than lower-contrast ground-based AMI setups, at orbital separations inaccessible to JWST coronagraphy.

astro-ph.EP↗

arXiv2023

The JWST Early Release Science Program for Direct Observations of Exoplanetary Systems III: Aperture Masking Interferometric Observations of the star HIP 65426 at 3.8 um

We present aperture masking interferometry (AMI) observations of the star HIP 65426 at $3.8\,\rm{\mu m}$ as a part of the JWST Direct Imaging Early Release Science (ERS) program obtained using the Near Infrared Imager and Slitless Spectrograph (NIRISS) instrument. This mode provides access to very small inner working angles (even separations slightly below the Michelson limit of $0.5\lambda/D$ for an interferometer), which are inaccessible with the classical inner working angles of the JWST coronagraphs. When combined with JWST's unprecedented infrared sensitivity, this mode has the potential to probe a new portion of parameter space across a wide array of astronomical observations. Using this mode, we are able to achieve a $5\sigma$ contrast of $\Delta m{\sim}7.62{\pm}0.13$ mag relative to the host star at separations ${\gtrsim}0.07{"}$, and the contrast deteriorates steeply at separations ${\lesssim}0.07{"}$. However, we detect no additional companions interior to the known companion HIP 65426 b (at separation ${\sim}0.82{"}$ or, $87^{+108}_{-31}\,\rm{au}$). Our observations thus rule out companions more massive than $10{-}12\,\rm{M_{Jup}}$ at separations ${\sim}10{-}20\,\rm{au}$ from HIP 65426, a region out of reach of ground or space-based coronagraphic imaging. These observations confirm that the AMI mode on JWST is sensitive to planetary mass companions at close-in separations (${\gtrsim}0.07{"}$), even for thousands of more distant stars at $\sim$100 pc, in addition to the stars in the nearby young moving groups as stated in previous works. This result will allow the planning and successful execution of future observations to probe the inner regions of nearby stellar systems, opening an essentially unexplored parameter space.

astro-ph.EP↗

arXiv2022

Performance of near-infrared high-contrast imaging methods with JWST from commissioning

The James Webb Space Telescope (JWST) will revolutionize the field of high-contrast imaging and enable both the direct detection of Saturn-mass planets and the characterization of substellar companions in the mid-infrared. While JWST will feature unprecedented sensitivity, angular resolution will be the key factor when competing with ground-based telescopes. Here, we aim to characterize the performance of several extreme angular resolution imaging techniques available with JWST in the 3-5 micron regime based on data taken during commissioning. Firstly, we introduce custom tools to simulate, reduce, and analyze NIRCam and MIRI coronagraphy data and use these tools to extract companion detection limits from on-sky NIRCam round and bar mask coronagraphy observations. Secondly, we present on-sky NIRISS aperture masking interferometry (AMI) and kernel phase imaging (KPI) observations from which we extract companion detection limits using the publicly available fouriever tool. Scaled to a total integration time of one hour and a target of the brightness of AB Dor, we find that NIRISS AMI and KPI reach contrasts of $\sim$7-8 mag at $\sim$70 mas and $\sim$9 mag at $\sim$200 mas. Beyond $\sim$250 mas, NIRCam coronagraphy reaches deeper contrasts of $\sim$13 mag at $\sim$500 mas and $\sim$15 mag at $\sim$2 arcsec. While the bar mask performs $\sim$1 mag better than the round mask at small angular separations $\lesssim$0.75 arcsec, it is the other way around at large angular separations $\gtrsim$1.5 arcsec. Moreover, the round mask gives access to the full 360 deg field-of-view which is beneficial for the search of new companions. We conclude that already during the instrument commissioning, JWST high-contrast imaging in the L- and M-bands performs close to its predicted limits.

astro-ph.EP↗

arXiv2022

Two Rings and a Marginally Resolved, 5 AU, Disk Around LkCa 15 Identified Via Near Infrared Sparse Aperture Masking Interferometry

Sparse aperture masking interferometry (SAM) is a high resolution observing technique that allows for imaging at and beyond a telescope's diffraction limit. The technique is ideal for searching for stellar companions at small separations from their host star; however, previous analysis of SAM observations of young stars surrounded by dusty disks have had difficulties disentangling planet and extended disk emission. We analyse VLT/SPHERE-IRDIS SAM observations of the transition disk LkCa\,15, model the extended disk emission, probe for planets at small separations, and improve contrast limits for planets. We fit geometrical models directly to the interferometric observables and recover previously observed extended disk emission. We use dynamic nested sampling to estimate uncertainties on our model parameters and to calculate evidences to perform model comparison. We compare our extended disk emission models against point source models to robustly conclude that the system is dominated by extended emission within 50 au. We report detections of two previously observed asymmetric rings at $\sim$17 au and $\sim$45 au. The peak brightness location of each model ring is consistent with the previous observations. We also, for the first time with imaging, robustly recover an elliptical Gaussian inner disk, previously inferred via SED fitting. This inner disk has a FWHM of ~5 au and a similar inclination and orientation as the outer rings. Finally, we recover no clear evidence for candidate planets. By modelling the extended disk emission, we are able to place a lower limit on the near infrared companion contrast of at least 1000.

astro-ph.EP↗

arXiv2021

Adjoint-Matching Neural Network Surrogates for Fast 4D-Var Data Assimilation

Data assimilation is the process of fusing information from imperfect computer simulations with noisy, sparse measurements of reality to obtain improved estimates of the state or parameters of a dynamical system of interest. The data assimilation procedures used in many geoscience applications, such as numerical weather forecasting, are variants of the our-dimensional variational (4D-Var) algorithm. The cost of solving the underlying 4D-Var optimization problem is dominated by the cost of repeated forward and adjoint model runs. This motivates substituting the evaluations of the physical model and its adjoint by fast, approximate surrogate models. Neural networks offer a promising approach for the data-driven creation of surrogate models. The accuracy of the surrogate 4D-Var solution depends on the accuracy with each the surrogate captures both the forward and the adjoint model dynamics. We formulate and analyze several approaches to incorporate adjoint information into the construction of neural network surrogates. The resulting networks are tested on unseen data and in a sequential data assimilation problem using the Lorenz-63 system. Surrogates constructed using adjoint information demonstrate superior performance on the 4D-Var data assimilation problem compared to a standard neural network surrogate that uses only forward dynamics information.

cs.LG↗

arXiv2021

Investigation of Nonlinear Model Order Reduction of the Quasigeostrophic Equations through a Physics-Informed Convolutional Autoencoder

Reduced order modeling (ROM) is a field of techniques that approximates complex physics-based models of real-world processes by inexpensive surrogates that capture important dynamical characteristics with a smaller number of degrees of freedom. Traditional ROM techniques such as proper orthogonal decomposition (POD) focus on linear projections of the dynamics onto a set of spectral features. In this paper we explore the construction of ROM using autoencoders (AE) that perform nonlinear projections of the system dynamics onto a low dimensional manifold learned from data. The approach uses convolutional neural networks (CNN) to learn spatial features as opposed to spectral, and utilize a physics informed (PI) cost function in order to capture temporal features as well. Our investigation using the quasi-geostrophic equations reveals that while the PI cost function helps with spatial reconstruction, spatial features are less powerful than spectral features, and that construction of ROMs through machine learning-based methods requires significant investigation into novel non-standard methodologies.

cs.LG↗