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The rate of cosmic thermonuclear Explosions in the Local Universe

The rate of cosmic thermonuclear Explosions in the Local Universe
The rate of cosmic thermonuclear Explosions in the Local Universe
This thesis investigates the volumetric rates of thermonuclear supernovae (SNe) in the Palomar Transient Factory (PTF). SN rates are a measure of how frequently stellar explosions occur as a function of cosmological volumes, or host galaxy properties. SNe are powerful cosmological probes; understanding their rates offers insight into the progenitors to the explosion and the astrophysics of galactic chemical evolution.
The Palomar Transient Factory was an automated optical sky survey designed for transient discovery. It spectroscopically confirmed ~1900 SNe during the period of 2009-2012. PTF operated with a 3-5 day cadence, and scanned more than 8,000 square degrees of the sky. I quantified the performance of PTF through large scale simulations of transient events. Firstly, ~7 x 106 fake transient events were inserted into real observational images. These 'fakes' were designed to test the real-time transient discovery pipeline. The images were treated identically to a new PTF observation, where the fakes were either recovered or not.
Multidimensional grids were created to describe how a transient would be recovered as a function of the fake's brightness and observing conditions. I found that bright fakes (mR < 18.5) were recovered with ~97% efficiency. PTF was 50% complete at mR = 20.3. The recovery efficiency was also strongly dependent on: the limiting magnitude, the image quality, the sky background, and the immediate environment brightness.
The second stage of quantifying the performance of PTF was transient specific. Hundreds of millions of SNe Ia light curves were simulated on an artificial night sky. The simulations shared the statistical properties of the single epoch efficiencies. Through a Monte-Carlo simulation of the SNe Ia populations, I derived recovery efficiencies as a function of SNe Ia light curve parameters.
A sample of 90 SNe Ia (z ≤ 0.09), were compared to the simulation recovery efficiencies. This provided the probability of the SNe passing rigorous quality cuts, and was used as a weighting factor. The weighted objects were summed and the volumetric SNe Ia rate was found to be 2.43 (+0.29 0.29 stat) (+0.33 0.19 sys) ×10-5 SNe Ia yr-1 Mpc-3 h370.
I fit a simple delay-time model,  Ψ = Ψ1t, to the data and found β ~ 1.
I applied the same methodology to a newly discovered class of SN: Ca-rich SNe. Their volumetric rate was found to be 1.62(±1.07) × 10-5 SNe yr-1 Mpc-3 h370. Furthermore, I used model nucleosynthetic yields for Ca-Rich, SNe Ia and CCSNe models and found that a Ca-rich rate ~ 30 - 50% of the SNe Ia rate would explain the observed Ca/Fe intra-cluster medium abundances.
University of Southampton
Frohmaier, Christopher M.
9e031e04-b5ac-4949-80a5-92e5e13201c0
Frohmaier, Christopher M.
9e031e04-b5ac-4949-80a5-92e5e13201c0
Sullivan, Mark
2f31f9fa-8e79-4b35-98e2-0cb38f503850

Frohmaier, Christopher M. (2017) The rate of cosmic thermonuclear Explosions in the Local Universe. University of Southampton, Doctoral Thesis, 212pp.

Record type: Thesis (Doctoral)

Abstract

This thesis investigates the volumetric rates of thermonuclear supernovae (SNe) in the Palomar Transient Factory (PTF). SN rates are a measure of how frequently stellar explosions occur as a function of cosmological volumes, or host galaxy properties. SNe are powerful cosmological probes; understanding their rates offers insight into the progenitors to the explosion and the astrophysics of galactic chemical evolution.
The Palomar Transient Factory was an automated optical sky survey designed for transient discovery. It spectroscopically confirmed ~1900 SNe during the period of 2009-2012. PTF operated with a 3-5 day cadence, and scanned more than 8,000 square degrees of the sky. I quantified the performance of PTF through large scale simulations of transient events. Firstly, ~7 x 106 fake transient events were inserted into real observational images. These 'fakes' were designed to test the real-time transient discovery pipeline. The images were treated identically to a new PTF observation, where the fakes were either recovered or not.
Multidimensional grids were created to describe how a transient would be recovered as a function of the fake's brightness and observing conditions. I found that bright fakes (mR < 18.5) were recovered with ~97% efficiency. PTF was 50% complete at mR = 20.3. The recovery efficiency was also strongly dependent on: the limiting magnitude, the image quality, the sky background, and the immediate environment brightness.
The second stage of quantifying the performance of PTF was transient specific. Hundreds of millions of SNe Ia light curves were simulated on an artificial night sky. The simulations shared the statistical properties of the single epoch efficiencies. Through a Monte-Carlo simulation of the SNe Ia populations, I derived recovery efficiencies as a function of SNe Ia light curve parameters.
A sample of 90 SNe Ia (z ≤ 0.09), were compared to the simulation recovery efficiencies. This provided the probability of the SNe passing rigorous quality cuts, and was used as a weighting factor. The weighted objects were summed and the volumetric SNe Ia rate was found to be 2.43 (+0.29 0.29 stat) (+0.33 0.19 sys) ×10-5 SNe Ia yr-1 Mpc-3 h370.
I fit a simple delay-time model,  Ψ = Ψ1t, to the data and found β ~ 1.
I applied the same methodology to a newly discovered class of SN: Ca-rich SNe. Their volumetric rate was found to be 1.62(±1.07) × 10-5 SNe yr-1 Mpc-3 h370. Furthermore, I used model nucleosynthetic yields for Ca-Rich, SNe Ia and CCSNe models and found that a Ca-rich rate ~ 30 - 50% of the SNe Ia rate would explain the observed Ca/Fe intra-cluster medium abundances.

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Published date: November 2017

Identifiers

Local EPrints ID: 416901
URI: http://eprints.soton.ac.uk/id/eprint/416901
PURE UUID: f125c969-0c68-4fb3-bffd-080bd1827086
ORCID for Mark Sullivan: ORCID iD orcid.org/0000-0001-9053-4820

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Date deposited: 12 Jan 2018 17:30
Last modified: 14 Mar 2019 01:35

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