arXiv subjects

John R. Peterson

Publications and source records attributed to John R. Peterson.

10 recordsLinked to original sources

arXiv2025

Enabling Early Transient Discovery in LSST via Difference Imaging with DECam

We present SLIDE, a pipeline that enables transient discovery in data from the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), using archival images from the Dark Energy Camera (DECam) as templates for difference imaging. We apply this pipeline to the recently released Data Preview 1 (DP1; the first public release of Rubin commissioning data) and search for transients in the resulting difference images. The image subtraction, photometry extraction, and transient detection are all performed on the Rubin Science Platform. We demonstrate that SLIDE effectively extracts clean photometry by circumventing poor or missing LSST templates. We identified 29 previously unreported transients, 12 of which would not have been detected based on the DP1 DiaObject catalog. SLIDE will be especially useful for transient analysis in the early years of LSST, when template coverage will be largely incomplete or when templates may be contaminated by transients present at the time of acquisition. We present multiband light curves for a sample of known transients, along with new transient candidates identified through our search. Finally, we discuss the prospects of applying this pipeline during the main LSST survey. Our pipeline is broadly applicable and will support studies of all transients with slowly evolving phases.

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arXiv2025

Identification and photometric classification of extragalactic transients in the Vera C. Rubin Observatory's Data Preview 1

The Vera C. Rubin Observatory will soon survey the southern sky, delivering a depth and sky coverage that is unprecedented in time domain astronomy. As part of commissioning, Data Preview 1 (DP1) has been released. It comprises a LSSTComCam observing campaign between November and December 2024 with multi-band imaging of seven fields, covering roughly 0.4 square degrees each, providing a first glimpse into the data products that will become available once the Legacy Survey of Space and Time begins. In this work, we search three fields for extragalactic transients. We identify eight new likely supernovae, and three known ones from a sample of 369,644 difference image analysis objects. Photometric classification using Superphot+ assigns sub-classes with >95% confidence to only one SN Ia and one SN II in this sample. Our findings are in agreement with supernova detection rate predictions of $15\pm4$ supernovae from simulations using simsurvey. The supernova detection rate in the data is possibly affected by the lack of suitable templates. Nevertheless, this work demonstrates the quality of the data products delivered in DP1 and indicates that the Rubin Observatory's Legacy Survey of Space and Time (LSST) is well placed to fulfill its discovery potential in time domain astronomy.

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arXiv2025

Forced Measurement of Astronomical Sources at Low Signal to Noise

We propose a modified moment matching algorithm to avoid catastrophic failures for sources with a low signal to noise ratio (SNR). The proposed modifications include a method to eliminate non-physical negative pixel values and a forced single iteration with an initial guess derived from co-add measurements when iterative methods are unstable. We correct for all biases in measurements introduced by the method. We find that the proposed modifications allow the algorithm to avoid catastrophic failures in nearly 100\% of the cases, especially at low signal to noise ratio. Additionally, with a reasonable guess from co-add measurements, the algorithm measures the flux, centroid, size, shape and ellipticity with bias statistically consistent with zero. We show the proposed method allows us to measure sources seven times fainter than traditional methods when applied to images obtained from WIYN-ODI. We also present a scheme to find uncertainties in measurements when using the new method to measure astronomical sources.

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arXiv2020

The LSST DESC Data Challenge 1: Generation and Analysis of Synthetic Images for Next Generation Surveys

Data Challenge 1 (DC1) is the first synthetic dataset produced by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). DC1 is designed to develop and validate data reduction and analysis and to study the impact of systematic effects that will affect the LSST dataset. DC1 is comprised of $r$-band observations of 40 deg$^{2}$ to 10-year LSST depth. We present each stage of the simulation and analysis process: a) generation, by synthesizing sources from cosmological N-body simulations in individual sensor-visit images with different observing conditions; b) reduction using a development version of the LSST Science Pipelines; and c) matching to the input cosmological catalog for validation and testing. We verify that testable LSST requirements pass within the fidelity of DC1. We establish a selection procedure that produces a sufficiently clean extragalactic sample for clustering analyses and we discuss residual sample contamination, including contributions from inefficiency in star-galaxy separation and imperfect deblending. We compute the galaxy power spectrum on the simulated field and conclude that: i) survey properties have an impact of 50\% of the statistical uncertainty for the scales and models used in DC1 ii) a selection to eliminate artifacts in the catalogs is necessary to avoid biases in the measured clustering; iii) the presence of bright objects has a significant impact (2- to 6-$σ$) in the estimated power spectra at small scales ($\ell > 1200$), highlighting the impact of blending in studies at small angular scales in LSST;

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arXiv2019

Deblending and Classifying Astronomical Sources with Mask R-CNN Deep Learning

We apply a new deep learning technique to detect, classify, and deblend sources in multi-band astronomical images. We train and evaluate the performance of an artificial neural network built on the Mask R-CNN image processing framework, a general code for efficient object detection, classification, and instance segmentation. After evaluating the performance of our network against simulated ground truth images for star and galaxy classes, we find a precision of 92% at 80% recall for stars and a precision of 98% at 80% recall for galaxies in a typical field with $\sim30$ galaxies/arcmin$^2$. We investigate the deblending capability of our code, and find that clean deblends are handled robustly during object masking, even for significantly blended sources. This technique, or extensions using similar network architectures, may be applied to current and future deep imaging surveys such as LSST and WFIRST. Our code, Astro R-CNN, is publicly available at https://github.com/burke86/astro_rcnn.

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arXiv2019

PhoSim-NIRCam: Photon-by-photon image simulations of the James Webb Space Telescope's Near-Infrared Camera

Recent instrumentation projects have allocated resources to develop codes for simulating astronomical images. Novel physics-based models are essential for understanding telescope, instrument, and environmental systematics in observations. A deep understanding of these systematics is especially important in the context of weak gravitational lensing, galaxy morphology, and other sensitive measurements. In this work, we present an adaptation of a physics-based ab initio image simulator: The Photon Simulator (PhoSim). We modify PhoSim for use with the Near-Infrared Camera (NIRCam) -- the primary imaging instrument aboard the James Webb Space Telescope (JWST). This photon Monte Carlo code replicates the observational catalog, telescope and camera optics, detector physics, and readout modes/electronics. Importantly, PhoSim-NIRCam simulates both geometric aberration and diffraction across the field of view. Full field- and wavelength-dependent point spread functions are presented. Simulated images of an extragalactic field are presented. Extensive validation is planned during in-orbit commissioning.

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arXiv2018

Unveiling the Rich and Diverse Universe of Subsecond Astrophysics through LSST Star Trails

We present a unique method that allows the LSST to scan the sky for stellar variability on short timescales. The operational component of the strategy requires LSST to take star trail images. The image processing component uses deep learning to sift for transient events on timescales down to 10 ms. We advocate for enabling this observing mode with LSST, as coupling this capability with the LSST's tremendous 319.5 m$^2$deg$^2$ etendue will produce the first wide area optical survey of the universe on these timescales. We explain how these data will advance both planned lines of investigation and enable new research in the areas of stellar flares, cataclysmic variables, active galactic nuclei, Kuiper Belt objects, gamma-ray bursts, and fast radio bursts.

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arXiv2018

A Study of the Point Spread Function in SDSS Images

We use SDSS imaging data in $ugriz$ passbands to study the shape of the point spread function (PSF) profile and the variation of its width with wavelength and time. We find that the PSF profile is well described by theoretical predictions based on von Kármán's turbulence theory. The observed PSF radial profile can be parametrized by only two parameters, the profile's full width at half maximum (FWHM) and a normalization of the contribution of an empirically determined "instrumental" PSF. The profile shape is very similar to the "double gaussian plus power-law wing" decomposition used by SDSS image processing pipeline, but here it is successfully modeled with two free model parameters, rather than six as in SDSS pipeline. The FWHM variation with wavelength follows the $λ^α$ power law, where $α\approx-0.3$ and is correlated with the FWHM itself. The observed behavior is much better described by von Kármán's turbulence theory with the outer scale parameter in the range 5$-$100 m, than by the Kolmogorov's turbulence theory. We also measure the temporal and angular structure functions for FWHM and compare them to simulations and results from literature. The angular structure function saturates at scales beyond 0.5$-$1.0 degree. The power spectrum of the temporal behavior is found to be broadly consistent with a damped random walk model with characteristic timescale in the range $\sim5-30$ minutes, though data show a shallower high-frequency behavior. The latter is well fit by a single power law with index in the range $-1.5$ to $-1.0$. A hybrid model is likely needed to fully capture both the low-frequency and high-frequency behavior of the temporal variations of atmospheric seeing.

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arXiv2010

X-ray spectroscopy of the hot has in the M31 bulge

We present an X-ray spectroscopic study of the nuclear region of the M31 bulge, based on observations of the Xmm-Newton Reflection Grating Spectrometers. The obtained high-resolution grating spectra clearly show individual emission lines of highly-ionized iron and oxygen, which unambiguously confirm the presence of diffuse hot gas in the bulge, as indicated from previous X-ray CCD imaging studies. We model the spectra with detailed Monte-Carlo simulations, which provide a robust spectroscopic estimate of the hot gas temperature $\sim0.29$ keV and the O/Fe ratio $\sim0.3$ solar. The results indicate that iron ejecta of type Ia supernovae are partly-mixed with the hot gas. The observed spectra show an intensity excess at the OVII triplet, which most likely represents emission from charge exchanges at the interface between the hot gas and a known cool gas spiral in the same nuclear region.

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arXiv2003

High Resolution X-ray Spectroscopic Constraints on Cooling-Flow Models

We present XMM-Newton Reflection Grating Spectrometer observations of X-ray clusters and groups of galaxies. We demonstrate the failure of the standard cooling-flow model to describe the soft X-ray spectrum of clusters of galaxies. We also emphasize several new developments in the study of the soft X-ray spectrum of cooling flows. Although there is some uncertainty in the expected mass deposition rate for any individual cluster, we show that high resolution RGS spectra robustly demonstrate that the expected line emission from the isobaric cooling-flow model is absent below 1/3 of the background temperature rather than below a fixed temperature in all clusters. Furthermore, we demonstrate that the best-resolved cluster spectra are inconsistent with the predicted shape of the differential luminosity distribution and the measured distribution is tilted to higher temperatures. These observations create several fine-tuning challenges for current theoretical explanations for the soft X-ray cooling-flow problem. Comparisons between these observations and other X-ray measurements are discussed.

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