David Rubin

David Rubin

orcid

Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 January 2012 in The Astrophysical Journal
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NSNao Suzuki
Nao Suzuki
DRDavid Rubin
David Rubin
CLC Lidman
C Lidman
GAGregory Scott Aldering
Gregory Scott Aldering
RAR Amanullah
R Amanullah
HYH K C Yee
H K C Yee

20 October 2008 in The Astrophysical Journal
Verified
Journal Article
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MKM. Kowalski
M. Kowalski
DRDavid Rubin
David Rubin
GAG. Aldering
G. Aldering
RARui Jorge Agostinho
Rui Jorge Agostinho
AAA. Amadon
A. Amadon
(P(The Supernova Cosmology Project)
(The Supernova Cosmology Project)
49 pages, 17 figures; accepted for publication in Astrophysical Journal. For data tables, code for cosmological analysis and full-resolution figures, see http://supernova.lbl.gov/UnionWe present a new compilation of Type Ia supernovae (SNe Ia), a new dataset of low-redshift nearby-Hubble-flow SNe and new analysis procedures to work with these heterogeneous compilations. This ''Union'' compilation of 414 SN Ia, which reduces to 307 SNe after selection cuts, includes the recent large samples of SNe Ia from the Supernova Legacy Survey and ESSENCE Survey, the older datasets, as well as the recently extended dataset of distant supernovae observed with HST. A single, consistent and blind analysis procedure is used for all the various SN Ia subsamples, and a new procedure is implemented that consistently weights the heterogeneous data sets and rejects outliers. We present the latest results from this Union compilation and discuss the cosmological constraints from this new compilation and its combination with other cosmological measurements (CMB and BAO). The constraint we obtain from supernovae on the dark energy density is $\Omega_\Lambda= 0.713^{+0.027}_{-0.029} (stat)}^{+0.036}_{-0.039} (sys)}$, for a flat, LCDM Universe. Assuming a constant equation of state parameter, $w$, the combined constraints from SNe, BAO and CMB give $w=-0.969^{+0.059}_{-0.063}(stat)^{+0.063}_{-0.066} (sys)$. While our results are consistent with a cosmological constant, we obtain only relatively weak constraints on a $w$ that varies with redshift. In particular, the current SN data do not yet significantly constrain $w$ at $z>1$. With the addition of our new nearby Hubble-flow SNe Ia, these resulting cosmological constraints are currently the tightest available

21 May 2010 in The Astrophysical Journal
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RAR Amanullah
R Amanullah
CLC Lidman
C Lidman
DRDavid Rubin
David Rubin
GAGregory Scott Aldering
Gregory Scott Aldering
PAP Astier
P Astier
NYNaoki Yasuda
Naoki Yasuda

20 June 2025 in The Astrophysical Journal
Verified
Journal Article
Open access
DRDavid Rubin
David Rubin
GAGreg Aldering
Greg Aldering
MBMarc Betoule
Marc Betoule
AFAndy Fruchter
Andy Fruchter
XHXiaosheng Huang
Xiaosheng Huang
NSNao Suzuki
Nao Suzuki
Type Ia supernovae (SNe Ia) were instrumental in establishing the acceleration of the Universe’s expansion. By virtue of their combination of distance reach, precision, and prevalence, they continue to provide key cosmological constraints, complementing other cosmological probes. Individual SN surveys cover only over about a factor of 2 in redshift, so compilations of multiple SN data sets are strongly beneficial. We assemble an up-to-date “Union” compilation of 2087 cosmologically useful SNe Ia from 24 data sets (“Union3”). We take care to put all SNe on the same distance scale and update the light-curve fitting with SALT3 to use the full rest-frame optical. Over the next few years, the number of cosmologically useful SNe Ia will increase by more than a factor of 10, and keeping systematic uncertainties subdominant will be more challenging than ever. We discuss the importance of treating outliers, selection effects, light-curve shape/color populations/standardization relations, unexplained dispersion, and heterogeneous observations simultaneously. We present an updated Bayesian framework, called UNITY1.5 (Unified Nonlinear Inference for Type-Ia cosmologY), that incorporates significant improvements in our ability to model selection effects, standardization, and systematic uncertainties compared to earlier analyses. As an analysis byproduct, we also recover the posterior of the SN-only peculiar-velocity field, although we do not interpret it in this work. We compute updated cosmological constraints with Union3 and UNITY1.5, finding weak 1.7σ–2.6σ tension with flat cold dark matter and possible evidence for thawing dark energy (w 0 > − 1, w a < 0). We release our SN distances, light-curve fits, and UNITY1.5 framework to the community.

17 March 2015 in The Astrophysical Journal
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Journal Article
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MRM. Rigault
M. Rigault
GAG. Aldering
G. Aldering
MKM. Kowalski
M. Kowalski
YCY. Copin
Y. Copin
PAP. Antilogus
P. Antilogus
BWB. A. Weaver
B. A. Weaver

1 February 2023 in The Astrophysical Journal
Verified
Journal Article
Open access
RTR. Brent Tully
R. Brent Tully
EKEhsan Kourkchi
Ehsan Kourkchi
HCHélène M. Courtois
Hélène M. Courtois
GAGagandeep S. Anand
Gagandeep S. Anand
JBJohn P. Blakeslee
John P. Blakeslee
BSBenjamin E. Stahl
Benjamin E. Stahl
With Cosmicflows-4, distances are compiled for 55,877 galaxies gathered into 38,065 groups. Eight methodologies are employed, with the largest numbers coming from the correlations between the photometric and kinematic properties of spiral galaxies (TF) and elliptical galaxies (FP). Supernovae that arise from degenerate progenitors (type Ia SNe) are an important overlapping component. Smaller contributions come from distance estimates from the surface brightness fluctuations of elliptical galaxies and the luminosities and expansion rates of core-collapse supernovae (SNe II). Cepheid period–luminosity relation and tip of the red giant branch observations founded on local stellar parallax measurements along with the geometric maser distance to NGC 4258 provide the absolute scaling of distances. The assembly of galaxies into groups is an important feature of the study in facilitating overlaps between methodologies. Merging between multiple contributions within a methodology and between methodologies is carried out with Bayesian Markov chain Monte Carlo procedures. The final assembly of distances is compatible with a value of the Hubble constant of H 0 = 74.6 km s−1 Mpc−1 with the small statistical error of ±0.8 km s−1 Mpc−1 but a large potential systematic error of ∼3 km s−1 Mpc−1. Peculiar velocities can be inferred from the measured distances. The interpretation of the field of peculiar velocities is complex because of large errors on individual components and invites analyses beyond the scope of this study.