9 research outputs found

    Non-parametric Spherical Jeans Mass Estimation with B-splines

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    HonorsAstronomy and AstrophysicsUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/167889/1/nabeelr.pd

    The Zwicky Transient Facility Bright Transient Survey. III. BTSbot\texttt{BTSbot}: Automated Identification and Follow-up of Bright Transients with Deep Learning

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    The Bright Transient Survey (BTS) aims to obtain a classification spectrum for all bright (mpeak ≤ 18.5 m_\mathrm{peak}\,\leq\,18.5\,mag) extragalactic transients found in the Zwicky Transient Facility (ZTF) public survey. BTS critically relies on visual inspection ("scanning") to select targets for spectroscopic follow-up, which, while effective, has required a significant time investment over the past ∼5\sim5 yr of ZTF operations. We present BTSbot\texttt{BTSbot}, a multi-modal convolutional neural network, which provides a bright transient score to individual ZTF detections using their image data and 25 extracted features. BTSbot\texttt{BTSbot} is able to eliminate the need for daily human scanning by automatically identifying and requesting spectroscopic follow-up observations of new bright transient candidates. BTSbot\texttt{BTSbot} recovers all bright transients in our test split and performs on par with scanners in terms of identification speed (on average, ∼\sim1 hour quicker than scanners). We also find that BTSbot\texttt{BTSbot} is not significantly impacted by any data shift by comparing performance across a concealed test split and a sample of very recent BTS candidates. BTSbot\texttt{BTSbot} has been integrated into Fritz and Kowalski\texttt{Kowalski}, ZTF's first-party marshal and alert broker, and now sends automatic spectroscopic follow-up requests for the new transients it identifies. During the month of October 2023, BTSbot\texttt{BTSbot} selected 296 sources in real-time, 93% of which were real extragalactic transients. With BTSbot\texttt{BTSbot} and other automation tools, the BTS workflow has produced the first fully automatic end-to-end discovery and classification of a transient, representing a significant reduction in the human-time needed to scan. Future development has tremendous potential for creating similar models to identify and request follow-up observations for specific types of transients.Comment: 26 pages, 12 figures; to be submitted to ApJ; comments welcom

    Dramatic rebrightening of the type-changing stripped-envelope supernova SN 2023aew

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    Multi-peaked supernovae with precursors, dramatic light-curve rebrightenings, and spectral transformation are rare, but are being discovered in increasing numbers by modern night-sky transient surveys like the Zwicky Transient Facility (ZTF). Here, we present the observations and analysis of SN 2023aew, which showed a dramatic increase in brightness following an initial luminous (-17.4 mag) and long (~100 days) unusual first peak (possibly precursor). SN 2023aew was classified as a Type IIb supernova during the first peak but changed its type to resemble a stripped-envelope supernova (SESN) after the marked rebrightening. We present comparisons of SN 2023aew's spectral evolution with SESN subtypes and argue that it is similar to SNe Ibc during its main peak. P-Cygni Balmer lines are present during the first peak, but vanish during the second peak's photospheric phase, before Hα\alpha resurfaces again during the nebular phase. The nebular lines ([O I], [Ca II], Mg I], Hα\alpha) exhibit a double-peaked structure which hints towards a clumpy or non-spherical ejecta. We analyze the second peak in the light curve of SN 2023aew and find it to be broader than normal SESNe as well as requiring a very high 56^{56}Ni mass to power the peak luminosity. We discuss the possible origins of SN 2023aew including an eruption scenario where a part of the envelope is ejected during the first peak which also powers the second peak of the light curve through SN-CSM interaction.Comment: 22 pages, 11 figures, 5 table

    BTSbot training set

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    Direct detection of supernova progenitor stars with ZTF and LSST

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    International audienceThe direct detection of core-collapse supernova (SN) progenitor stars is a powerful way of probing the last stages of stellar evolution. However, detections in archival Hubble Space Telescope images are limited to about one per year. Here, we explore whether we can increase the detection rate by using data from ground-based wide-field surveys. Due to crowding and atmospheric blurring, progenitor stars can typically not be identified in pre-explosion images alone. Instead, we combine many pre-SN and late-time images to search for the disappearance of the progenitor star. As a proof of concept, we implement our search for ZTF data. For a few hundred images, we achieve limiting magnitudes of about 23 mag in the g and r band. However, no progenitor stars or long-lived outbursts are detected for 29 SNe within z<0.01, and the ZTF limits are typically several magnitudes less constraining than detected progenitors in the literature. Next, we estimate progenitor detection rates for the Legacy Survey of Space and Time (LSST) with the Vera C. Rubin telescope by simulating a population of nearby SNe. The background from bright host galaxies reduces the nominal LSST sensitivity by, on average, 0.4 mag. Over the ten-year survey, we expect the detection of about 50 red supergiant progenitors and several yellow and blue supergiants. The progenitors of SNe Ib and Ic are detectable if they are brighter than -4.7 mag or -4.0 mag in the LSST i band, respectively. In addition, we expect the detection of hundreds of pre-SN outbursts depending on their brightness and duration

    Direct detection of supernova progenitor stars with ZTF and LSST

    No full text
    International audienceThe direct detection of core-collapse supernova (SN) progenitor stars is a powerful way of probing the last stages of stellar evolution. However, detections in archival Hubble Space Telescope images are limited to about one per year. Here, we explore whether we can increase the detection rate by using data from ground-based wide-field surveys. Due to crowding and atmospheric blurring, progenitor stars can typically not be identified in pre-explosion images alone. Instead, we combine many pre-SN and late-time images to search for the disappearance of the progenitor star. As a proof of concept, we implement our search for ZTF data. For a few hundred images, we achieve limiting magnitudes of about 23 mag in the g and r band. However, no progenitor stars or long-lived outbursts are detected for 29 SNe within z<0.01, and the ZTF limits are typically several magnitudes less constraining than detected progenitors in the literature. Next, we estimate progenitor detection rates for the Legacy Survey of Space and Time (LSST) with the Vera C. Rubin telescope by simulating a population of nearby SNe. The background from bright host galaxies reduces the nominal LSST sensitivity by, on average, 0.4 mag. Over the ten-year survey, we expect the detection of about 50 red supergiant progenitors and several yellow and blue supergiants. The progenitors of SNe Ib and Ic are detectable if they are brighter than -4.7 mag or -4.0 mag in the LSST i band, respectively. In addition, we expect the detection of hundreds of pre-SN outbursts depending on their brightness and duration

    Dramatic Rebrightening of the Type-changing Stripped-envelope Supernova SN 2023aew

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    © 2024. The Author(s). Published by the American Astronomical Society. cc-byMultipeaked supernovae with precursors, dramatic light-curve rebrightenings, and spectral transformation are rare, but are being discovered in increasing numbers by modern night-sky transient surveys like the Zwicky Transient Facility. Here, we present the observations and analysis of SN 2023aew, which showed a dramatic increase in brightness following an initial luminous (−17.4 mag) and long (∼100 days) unusual first peak (possibly precursor). SN 2023aew was classified as a Type IIb supernova during the first peak but changed its type to resemble a stripped-envelope supernova (SESN) after the marked rebrightening. We present comparisons of SN 2023aew’s spectral evolution with SESN subtypes and argue that it is similar to SNe Ibc during its main peak. P-Cygni Balmer lines are present during the first peak, but vanish during the second peak’s photospheric phase, before Hα resurfaces again during the nebular phase. The nebular lines ([O i], [Ca ii], Mg i], Hα) exhibit a double-peaked structure that hints toward a clumpy or nonspherical ejecta. We analyze the second peak in the light curve of SN 2023aew and find it to be broader than that of normal SESNe as well as requiring a very high 56Ni mass to power the peak luminosity. We discuss the possible origins of SN 2023aew including an eruption scenario where a part of the envelope is ejected during the first peak and also powers the second peak of the light curve through interaction of the SN with the circumstellar medium

    Overview of the DESI Milky Way Survey

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    We describe the Milky Way Survey (MWS) that will be undertaken with the Dark Energy Spectroscopic Instrument (DESI) on the Mayall 4m Telescope at the Kitt Peak National Observatory. Over the next 5 years DESI MWS will observe approximately 7 million stars at Galactic latitudes |b|>20 deg, with an inclusive target selection scheme focused on the thick disk and stellar halo. MWS will also include several high-completeness samples of rare stellar types, including white dwarfs, low-mass stars within 100pc of the Sun, and horizontal branch stars. We summarize the potential of DESI to advance understanding of Galactic structure and stellar evolution. We introduce the final definitions of the main MWS target classes and estimate the number of stars in each class that will be observed. We describe our pipelines to derive radial velocities, atmospheric parameters and chemical abundances. We use ~500,000 spectra of unique stellar targets from the DESI Survey Validation program (SV) to demonstrate that our pipelines can measure radial velocities to approximately 1 km/s and [Fe/H] accurate to approximately 0.2 dex for typical stars in our main sample. We find stellar parameter distributions from 100 sq. deg. of SV observations with >90% completeness on our main sample are in good agreement with expectations from mock catalogues and previous surveys

    Overview of the DESI Milky Way Survey

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    We describe the Milky Way Survey (MWS) that will be undertaken with the Dark Energy Spectroscopic Instrument (DESI) on the Mayall 4 m telescope at the Kitt Peak National Observatory. Over the next 5 yr DESI MWS will observe approximately seven million stars at Galactic latitudes ∣b∣ > 20°, with an inclusive target selection scheme focused on the thick disk and stellar halo. MWS will also include several high-completeness samples of rare stellar types, including white dwarfs, low-mass stars within 100 pc of the Sun, and horizontal branch stars. We summarize the potential of DESI to advance understanding of the Galactic structure and stellar evolution. We introduce the final definitions of the main MWS target classes and estimate the number of stars in each class that will be observed. We describe our pipelines for deriving radial velocities, atmospheric parameters, and chemical abundances. We use ≃500,000 spectra of unique stellar targets from the DESI Survey Validation program (SV) to demonstrate that our pipelines can measure radial velocities to ≃1 km s−1 and [Fe/H] accurate to ≃0.2 dex for typical stars in our main sample. We find the stellar parameter distributions from ≈100 deg2 of SV observations with ≳90% completeness on our main sample are in good agreement with expectations from mock catalogs and previous surveys. Issue date: 10.4.2
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