LISA auto-correlation SNR equals the square root of T_obs times the integral of (signal/(noise+signal))^2 and is therefore bounded by sqrt(T_obs(f_max-f_min)).
Supernova Type Ia progenitors from merging double white dwarfs: Using a new population synthesis model
2 Pith papers cite this work. Polarity classification is still indexing.
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abstract
The study of Type Ia supernovae (SNIa) has lead to greatly improved insights into many fields in astrophysics, however a theoretical explanation of the origin of these events is still lacking. We investigate the potential contribution to the SNIa rate from the population of merging double carbon-oxygen white dwarfs. We aim to develope a model that fits the observed SNIa progenitors as well as the observed close double white dwarf population. We differentiate between two scenarios for the common envelope (CE) evolution; the alpha-formalism based on the energy equation and the gamma-formalism that is based on the angular momentum equation. In one model we apply the alpha-formalism always. In the second model the gamma-formalism is applied, unless the binary contains a compact object or the CE is triggered by a tidal instability for which the alpha-formalism is used. The binary population synthesis code SeBa was used to evolve binary systems from the zero-age main sequence to the formation of double white dwarfs and subsequent mergers. SeBa has been thoroughly updated since the last publication of the content of the code. The limited sample of observed double white dwarfs is better represented by the simulated population using the gamma-formalism than the alpha-formalism. For both CE formalisms, we find that although the morphology of the simulated delay time distribution matches that of the observations within the errors, the normalisation and time-integrated rate per stellar mass are a factor 7-12 lower than observed. Furthermore, the characteristics of the simulated populations of merging double carbon-oxygen white dwarfs are discussed and put in the context of alternative SNIa models for merging double white dwarfs.
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2026 2representative citing papers
Jet feedback in centrally concentrated clouds reduces star formation efficiency to 12-16% and yields cluster structures more consistent with observations than models without jets.
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Signal-to-Noise Ratio Contours for LISA
LISA auto-correlation SNR equals the square root of T_obs times the integral of (signal/(noise+signal))^2 and is therefore bounded by sqrt(T_obs(f_max-f_min)).
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Centrally concentrated star formation in young clusters II: Jet feedback
Jet feedback in centrally concentrated clouds reduces star formation efficiency to 12-16% and yields cluster structures more consistent with observations than models without jets.