Search for: All records

Poster presented at the American Association of Biological Anthropologists meeting on March 21, 2026 in Denver, CO. Session 37: Invited Symposium: Tooth wear: Emerging techniques, enduring questions, and future directions 

Post-processing of high contrast imaging data relies on an accurate model of the stellar point spread function (PSF). Current techniques build this model from the science images themselves, using observational diversity (e.g., angular, spectral or polarimetric diversity), which can cause self-subtraction of the companion signal and constrains the observing strategy. Telemetry-based forward modelling instead builds the stellar PSF model from wavefront sensor data that is already recorded during the observation. The wavefront sensor measures the coherent starlight and can therefore be used to create a PSF model that only models the stellar light and does not reproduce the incoherent light of a companion. We present a fully physical and differentiable digital twin of the focal plane low-order wavefront sensor (FLOWFS) and the coronagraphic science beam of the MagAO-X instrument, implemented in \texttt{dLux}, and calibrate it on laboratory data. When fitted directly to the science images, the model reproduces the coronagraphic PSF down to the photon and read noise floor of the data. When instead forward modelled from the FLOWFS telemetry alone, the residuals reach 6×10−5 of the stellar peak at 5 λ/D, a factor of 5 below the raw contrast, with the remaining residual set by how well the wavefront estimate transfers from the FLOWFS branch to the science branch of the model. An injected companion at 5 λ/D with a peak contrast of 10−3 is recovered without measurable self-subtraction. We discuss the model improvements currently under development and the path towards on-sky validation. 

Poster presented at the American Assocation of Biological Anthropologists meeting on March 20, 2026 in Denver, CO. Poster session 13: Dental Anthropology: Methods of Examining Human Variation. 

Poster presented at the American Association of Biological Anthropologists meeting on March 21, 2026 in Denver, CO. Session 37: Invited Symposium: Tooth wear: Emerging techniques, enduring questions, and future directions 

Mechanical vibrations are a significant source of residual wavefront error (WFE) in adaptive optics (AO) systems, limiting the performance of high-contrast imaging instruments. We present the design and on-sky deployment of a low-cost, modular accelerometer telemetry system for the MagAO-X extreme AO instrument on the 6.5 m Magellan Clay Telescope, consisting of piezoelectric accelerometers and a Raspberry Pi-based acquisition system that streams synchronized data to the real-time control computer with microsecond-level timing stability. The system is used to identify dominant telescope vibration sources and quantify their coupling to AO telemetry, revealing that several narrow-band modes originate from subsystems including the primary mirror glycol pump, secondary mirror actuation system, and telescope autofocus system. Coherence analysis between the synchronized accelerometer and wavefront sensor telemetry demonstrates that approximately one-third of the residual tip and tilt WFE is correlated with structural vibrations, indicating that accelerometer telemetry provides a promising foundation for future predictive control implementations. These results demonstrate that low-cost accelerometer telemetry provides a practical approach for vibration identification and a foundation for predictive control in current and future AO systems. 

We present the eXtreme Wavefront Control Toolkit (XWCTk) instrument control software system developed for the MagAO-X extreme adaptive optics (ExAO) instrument. The XWCTk is built on a foundation of the ImageStreamIO (ISIO) / MILK / CACAO low-latency image processing and high dimensional control tool chain. Instrument control is managed with the Instrument Neutral Distributed Interface (INDI). The application framework provides configuration, logging, and distributed IPC with INDI and low-latency IPC with ISIO. On MagAO-X, every detector is a potential wavefront sensor capable of sending commands to three separate DMs. MagAO-X utilizes a distributed control system, where multiple computers each manage low-latency wavefront control tasks but are capable of coordinated control. Implemented algorithms include neural networks for nonlinear reconstruction at over 3 kHz. We have incorporated distributed raspberry pis for accelerometer data acquisition with low-latency streaming to the real-time computers for sensor fusion control. A core design principle of the XWCTk is that all data can be saved all the time. This includes full-rate WFS images, DM commands, as well as science data. To facilitate this we have implemented a custom lossless compression system capable of sustaining high data rates to disk. A python interface for scripting and experimentation, as well as a python application framework is provided which can be used for non-real-time tasks. Remote operations (e.g. from Tucson Arizona when the instrument is at LCO in Chile) are routine. The XWCTk is under continuous development for the MagAO-X instrument, and will be adapted for GMagAO-X, the planned first-light ExAO coronagraph for the Giant Magellan Telescope. XWCTk is the baseline for a space high contrast imaging instrument, and as such ongoing development is focused on automation for robust operation in flight. 

The wind-driven halo (WDH) is a persistent, low spatial frequency noise artifact that arises due to the servo-lag error inherent to all adaptive optics (AO) instruments. Spatial filtering may be employed to overcome this artifact, however, filtering out the WDH while simultaneously preserving signal from an extended astrophysical object of interest is exceptionally challenging. Additionally, since the WDH changes in intensity and position angle through an observation, data-driven algorithms (e.g., KLIP) that are commonly used to subtract the starlight need to be overly-aggressive to remove both the static and dynamic noise components. Since wavefront sensors (WFSs) continuously track the closed-loop residual wavefront error, WFS telemetry presents the ideal resource for combating this type of noise artifact through postprocessing. Using archival WFS telemetry from MagAO-X, which is the ``extreme" AO instrument for the 6.5-meter Magellan-Clay telescope, we demonstrate a novel workflow for WDH reconstruction and removal in individual coronagraphic science images. MagAO-X is equipped with a pyramid WFS capable of recording wavefront telemetry at a high-cadence which is saved during data acquisition. Given this, we detail how our WFS data processing pipeline, windsoCC, cross-correlates the recorded closed-loop wavefront to measure the wind vectors of several turbulent layers of the atmosphere above Las Campanas Observatory. We then make use of the wind parameters learned through windsoCC to reconstruct the WDH footprint by leveraging a parametric model. Notably, we demonstrate a dramatic improvement in object recovery using on-sky MagAO-X images of the disk around HR~4796A at visible wavelengths.