A5046803617- Gamma-ray bursts and supernovae
- Astronomy and Astrophysical Research
- Stellar, planetary, and galactic studies
- Astrophysics and Cosmic Phenomena
- Astrophysical Phenomena and Observations
- Astronomical Observations and Instrumentation
- CCD and CMOS Imaging Sensors
- Neutrino Physics Research
- GNSS positioning and interference
- Infrared Target Detection Methodologies
- Human Pose and Action Recognition
- Inertial Sensor and Navigation
- Context-Aware Activity Recognition Systems
- Video Surveillance and Tracking Methods
- Adaptive optics and wavefront sensing
- Radio Astronomy Observations and Technology
- Geophysics and Gravity Measurements
- Marine and environmental studies
- Ocular and Laser Science Research
- Advanced Optical Network Technologies
- History and Developments in Astronomy
- Advanced Optical Sensing Technologies
- Multimodal Machine Learning Applications
- Advanced Chemical Sensor Technologies
- Ecology and biodiversity studies
Lawrence Berkeley National Laboratory
2017-2023
University of California, Berkeley
2018-2023
Western Washington University
2018-2019
As part of an on-going effort to identify, understand and correct for astrophysics biases in the standardization Type Ia supernovae (SNIa) cosmology, we have statistically classified a large sample nearby SNeIa into those located predominantly younger or older environments. This classification is based on specific star formation rate measured within projected distance 1kpc from each SN location (LsSFR). important refinement compared using local directly as it provides normalization relative...
Type Ia supernova cosmology depends on the ability to fit and standardize observations of magnitudes with an empirical model. We present here a series new models Supernova spectral time that capture greater amount diversity than possible are currently customary. These entitled SuperNova Empirical MOdels (\textsc{SNEMO}\footnote{https://snfactory.lbl.gov/snemo}). The constructed using spectrophotometric from $172$ individual supernovae Nearby Factory, comprising more $2000$ spectra. Using...
Abstract We present a new empirical Type Ia supernova (SN Ia) model with three chromatic flux variation templates: one phase dependent and two independent. No underlying dust extinction or patterns of intrinsic variability are assumed. Implemented S tan trained using spectrally binned Nearby Supernova Factory spectrophotometry, we examine this model's 2D, phase-independent space motivated basis representations. In both, the first template captures that appears dust-like, while second...
As a candidate 'super-Chandrasekhar' or 09dc-like Type Ia supernova (SN Ia), SN 2012dn shares many characteristics with other members of this remarkable class objects but lacks their extraordinary luminosity. Here, we present and discuss the most comprehensive optical data set to date, comprised densely sampled series early-time spectra obtained within Nearby Supernova Factory project, plus photometry spectroscopy at VLT about 1 yr after explosion. The light curves, colour spectral time...
Abstract We calibrate spectrophotometric optical spectra of 32 stars commonly used as standard stars, referenced to 14 already on the Hubble Space Telescope–based CALSPEC flux system. Observations and non-CALSPEC were obtained with SuperNova Integral Field Spectrograph over wavelength range 3300–9400 Å calibration for Nearby Supernova Factory cosmology experiment. In total, this analysis 4289 standard-star taken photometric nights. As a modern analysis, all presubmission methodological...
Abstract We present the discovery and measurements of a gravitationally lensed supernova (SN) behind galaxy cluster MOO J1014+0038. Based on multi-band Hubble Space Telescope Very Large (VLT) photometry supernova, VLT spectroscopy host galaxy, we find 97.5% probability that this SN is Ia, 2.5% chance CC SN. Our typing algorithm combines shape color light curve with expected rates each type in galaxy. With redshift 2.2216, highest Ia discovered spectroscopic host-galaxy redshift. A further...
Type Ia Supernovae (SNe Ia) are powerful standardizable candles for constraining cosmological models and provided the first evidence of accelerated expansion universe. Their precision derives from empirical correlations, now measured $>1000$ SNe Ia, between their luminosities, light-curve shapes, colors most recently with stellar mass host galaxy. As correlates other galaxy properties, alternative parameters have been investigated to improve SN standardization though none shown significantly...
We study the spectral diversity of Type Ia supernovae (SNe Ia) at maximum light using high signal-to-noise spectrophotometry 173 SNe from Nearby Supernova Factory. decompose these spectra into different extrinsic and intrinsic components, we construct a nonlinear parameterization that preserves pairings "twin" Ia. call this "Twins Embedding". Our methodology naturally handles highly variability in spectra, such as changes photosphere expansion velocity, uses full spectrum rather than being...
Type Ia Supernovae (SNe Ia) are widely used to measure the expansion of Universe. Improving distance measurements SNe is one technique better constrain acceleration and determine its physical nature. This document develops a new spectral energy distribution (SED) model, called SUpernova Generator And Reconstructor (SUGAR), which improves description Ia, consequently could improve measurements. model constructed from properties spectrophotometric data The Nearby Supernova Factory...
The See Change survey was designed to make $z>1$ cosmological measurements by efficiently discovering high-redshift Type Ia supernovae (SNe Ia) and improving cluster mass through weak lensing. This observed twelve galaxy clusters with the Hubble Space Telescope spanning redshift range $z=1.13$ $1.75$, 57 likely transients 27 SNe at $z\sim 0.8-2.3$. As in similar previous surveys (Dawson et al. 2009), this proved be a highly efficient use of HST for SN observations; additionally tested...
We apply the color-magnitude intercept calibration method (CMAGIC) to Nearby Supernova Factory SNe Ia spectrophotometric dataset. The currently existing CMAGIC parameters are slope and of a straight line fit first linear region in diagram, which occurs over span approximately 30 days after maximum brightness. define new parameter, $\omega_{XY}$, size ``bump'' feature near brightness for arbitrary filters $X$ $Y$. find significant correlation between region, $\beta_{XY, 1}$, diagram...
Context. Observations of type Ia supernovae (SNe Ia) can be used to derive accurate cosmological distances through empirical standardization techniques. Despite this success neither the progenitors SNe nor explosion process are fully understood. The U -band region has been less well observed for nearby SNe, due technical challenges, but is most readily accessible band high-redshift SNe. Aims. Using spectrophotometry from Nearby Supernova Factory, we study origin and extent spectroscopic...
To determine if the SuperNova Empirical Model (SNEMO) can improve Type Ia supernova (SN Ia) standardization of several currently available photometric data sets, we perform an initial test, comparing results with much-used SALT2 approach. We fit SNEMO light-curve parameters and pass them to Bayesian hierarchical model UNITY1.2 estimate Tripp-like coefficients, including a host mass term as proxy for redshift dependent astrophysical systematics. find that, among existing large only Carnegie...
Abstract The Nearby Supernova Factory presents an interim data release of spectrophotometric timeseries 210 SNe Ia. Two slightly different versions the are included, corresponding to training sets used for SNEMO and SUGAR Type Ia models. has been shifted restframe is blinded with respect cosmology.
Type Ia Supernovae (SNe Ia) are widely used to measure the expansion of Universe. To perform such measurements luminosity and cosmological redshift ($z$) SNe have be determined. The uncertainty on $z$ includes an unknown peculiar velocity, which can very large for in virialized cores massive clusters. We determine exploded galaxy then study how correction velocities host galaxies inside clusters improves Hubble residuals. Using 145 from Nearby Supernova Factory we found 11 candidates...
Abstract We construct a physically parameterized probabilistic autoencoder (PAE) to learn the intrinsic diversity of Type Ia supernovae (SNe Ia) from sparse set spectral time series. The PAE is two-stage generative model, composed an that interpreted probabilistically after training using normalizing flow. demonstrate learns low-dimensional latent space captures nonlinear range features exists within population and can accurately model evolution SNe across full wavelength observation times...
We have discovered an anomalous behavior of CCD readout electronics that affects their use in many astronomical applications. An offset the digitization output voltage depends on binary encoding one pixel is added to pixels are read out one, two, and/or three later. One result this effect introduction a differential background when comparing regions with and without flux from science targets. Conventional data reduction methods do not correct for offset. find 16 22 instruments investigated,...
The field of human activity recognition from video data has recently made great strides. However, the large amount labelled needed to train models remains a common bottleneck. This paper introduces simulation platform procedurally generate synthetic videos household activities, which randomizes portions virtual scene like camera position, model, and interaction motion introduce variation. We describe our system design, methodology, planned next steps for evaluation.
Abstract Several Type Ia supernova analyses make use of non-simultaneous regressions between observed and host galaxy properties luminosity: first the magnitudes are corrected for their light curve shape color, then they separately masses. This two-step regression methodology does not introduce any biases when there no correlations variables regressed in each correction step. However, these covariates will bias estimates size corrections, as well variance final residuals. In this work, we...
Abstract We show how spectra of Type Ia supernovae (SNe Ia) at maximum light can be used to improve cosmological distance estimates. In a companion article, we manifold learning build three-dimensional parameterization the intrinsic diversity SNe that call “Twins Embedding.” this discuss Twins Embedding standardization Ia. With single spectrophotometrically calibrated spectrum near light, standardize our sample with an rms 0.101 ± 0.007 mag, which corresponds 0.084 0.009 mag if peculiar...
Aims. The scientific yield of current and future optical surveys is increasingly limited by systematic uncertainties in the flux calibration. This case for type Ia supernova (SN Ia) cosmology programs, where an improved calibration directly translates into cosmological constraints. Current methodology rests on models stars. Here we aim to obtain that traceable state-of-the-art detector-based Methods. We present SNIFS Calibration Apparatus (SCALA), a color (relative) system developed...
The field of human activity recognition from video data has recently made great strides. However, the large amount labelled needed to train models remains a common bottleneck. This paper describes design novel simulation platform procedurally generate synthetic videos household activities, which randomizes portions virtual scene like camera position, model, and interaction motion introduce variation. We describe our system design, evaluation methodology, discuss experimental results.