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相关论文: A More General Model for the Intrinsic Scatter in …

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For spectroscopically confirmed Type Ia supernovae we evaluate models of intrinsic brightness variations with detailed data/Monte Carlo comparisons of the dispersion in the following quantities: Hubble-diagram scatter, color difference…

The use of Type Ia Supernovae (SNe Ia) as cosmological tools has motivated significant effort to: understand what drives the intrinsic scatter of SN Ia distance modulus residuals after standardization, characterize the distribution of SN Ia…

宇宙学与河外天体物理 · 物理学 2021-03-10 Dillon Brout , Daniel Scolnic

Past analyses of Type Ia Supernovae (SNe Ia) have identified an irreducible scatter of 5-10% in distance widely attributed to an intrinsic dispersion in luminosity. Another, equally valid, source of this scatter is intrinsic dispersion in…

宇宙学与河外天体物理 · 物理学 2015-06-16 Daniel M. Scolnic , Adam G. Riess , Ryan J. Foley , Armin Rest , Steven A. Rodney , Dillon J. Brout , David O. Jones

Conventional Type Ia supernova (SN Ia) cosmology analyses currently use a simplistic linear regression of magnitude versus color and light curve shape, which does not model intrinsic SN Ia variations and host galaxy dust as physically…

宇宙学与河外天体物理 · 物理学 2017-06-28 Kaisey S. Mandel , Daniel Scolnic , Hikmatali Shariff , Ryan J. Foley , Robert P. Kirshner

Measurement of the growth rate of structures ($\fsig$) with Type Ia supernovae (\sns) will improve our understanding of the nature of dark energy and enable tests of general relativity. In this paper, we generate simulations of the 10 year…

The ZTF DR2 includes light curves of 3628 Type Ia supernovae (SNe Ia), making it the largest low-redshift SNe Ia sample available. One central question for analyses of SNe Ia is whether the remaining diversity of standardized luminosities…

宇宙学与河外天体物理 · 物理学 2025-05-09 Yukei S. Murakami , Daniel Scolnic

Type Ia supernovae (SNe Ia) are a key probe in modern cosmology, as they can be used to measure luminosity distances at gigaparsec scales. Models of their light-curves are used to project heterogeneous observed data onto a common basis for…

We present an empirical model of Type Ia supernovae spectro-photometric evolution with time. The model is built using a large data set including light-curves and spectra of both nearby and distant supernovae, the latter being observed by…

As type Ia supernova (SN Ia) cosmology transitions from a statistics-dominated to a systematics-dominated era, it is crucial to understand the remaining unexplained uncertainties that affect their luminosity, such as those stemming from…

By using the Sloan Digital Sky Survey (SDSS) first year type Ia supernova (SN Ia) compilation, we compare two different approaches (traditional \chi^2 and complete likelihood) to determine parameter constraints when the magnitude dispersion…

宇宙学与河外天体物理 · 物理学 2015-05-27 B. L. Lago , M. O. Calvão , S. E. Jorás , R. R. R. Reis , I. Waga , R. Giostri

Recent studies have shown that the observed colour distributions of Type Ia SNe (SNIa) are well-described by a combination of distributions from dust and intrinsic colour. Here we present a new forward-modeling fitting method (Dust2Dust) to…

宇宙学与河外天体物理 · 物理学 2022-12-06 Brodie Popovic , Dillon Brout , Richard Kessler , Daniel Scolnic

Type Ia Supernovae are standard candles so their mean apparent magnitude has been exploited to learn about the redshift-distance relationship. Besides intrinsic scatter in this standard candle, additional source of scatter is caused by…

天体物理学 · 物理学 2008-11-26 Scott Dodelson , Alberto Vallinotto

I present an analysis for fitting cosmological parameters from a Hubble Diagram of a standard candle with unknown intrinsic magnitude dispersion. The dispersion is determined from the data themselves, simultaneously with the cosmological…

宇宙学与河外天体物理 · 物理学 2015-05-27 Alex Kim

Type Ia Supernovae (SNe Ia) spectra are compared regarding the coefficient of the largest wavelet scale in their decomposition. Two distinct subgroups were identified and their occurrence is discussed in light of use of SNe Ia as…

宇宙学与河外天体物理 · 物理学 2015-05-27 Vladan Arsenijevic

Type Ia supernovae (SNe Ia) provide us with a unique tool for measuring extragalactic distances and determining cosmological parameters. As a result, the precise and effective calibration for peak luminosities of SNe Ia becomes extremely…

天体物理学 · 物理学 2016-08-30 Xiaofeng Wang , Lifan Wang , Xu Zhou , Yuqing Lou , Zongwei Li

The success of Type Ia supernova (SN Ia) distance standardisation for cosmology relies on a single global linear relationship between their peak luminosity and colour, the $\beta$ parameter. However, there are several pieces of evidence and…

宇宙学与河外天体物理 · 物理学 2021-10-13 S. Gonzalez-Gaitan , T. de Jaeger , L. Galbany , A. Mourao , A. Paulina-Afonso , A. V. Filippenko

[Abridged] We investigate the use of a wide variety of spectroscopic measurements to determine distances to low-redshift Type Ia supernovae (SN Ia). We consider linear models for predicting distances to SN Ia using light-curve width and…

宇宙学与河外天体物理 · 物理学 2011-01-04 Stéphane Blondin , Kaisey S. Mandel , Robert P. Kirshner

We investigate the statistical dependence of the peak intrinsic colors of Type Ia supernovae (SN Ia) on their expansion velocities at maximum light, measured from the Si II 6355 spectral feature. We construct a new hierarchical Bayesian…

宇宙学与河外天体物理 · 物理学 2014-12-01 Kaisey S. Mandel , Ryan J. Foley , Robert P. Kirshner

Type Ia Supernovae (SNe Ia) are widely used to measure distances in the Universe. Despite the recent progress achieved in SN Ia standardisation, the Hubble diagram still shows some remaining intrinsic dispersion. The remaining scatter in…

宇宙学与河外天体物理 · 物理学 2020-11-18 Maria Pruzhinskaya , Aleksandra Novinskaya , Nicoleta Pauna , Philippe Rosnet

Type Ia Supernovae (SNeIa) provided the first evidence of an accelerated expansion of the universe and remain a valuable probe to cosmology. They are deemed standardizable candles due to the observed correlations between its luminosity and…

宇宙学与河外天体物理 · 物理学 2024-09-04 Cássia S. Nascimento , João Paulo C. França , Ribamar R. R. Reis
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