Undergrad Curve fitting the luminosity distance and redshift data

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SUMMARY

This discussion focuses on the challenge of curve fitting redshift as a function of luminosity distance for type Ia supernovae and gamma-ray bursts without assuming a specific physical model, such as the Friedmann–Lemaître–Robertson–Walker (FLRW) metric. Participants seek papers that present a "best fit" function for redshift (z) in relation to luminosity distance (d_l) without predefined assumptions about the relationship between these variables. The Supernova Cosmology Project provides a valuable resource, offering downloadable data and a summary table of the distance/redshift relation, which extends to a redshift of approximately 1.4.

PREREQUISITES
  • Understanding of redshift and luminosity distance concepts
  • Familiarity with curve fitting techniques
  • Knowledge of type Ia supernovae and gamma-ray bursts
  • Basic proficiency in data analysis and interpretation
NEXT STEPS
  • Research the Supernova Cosmology Project's data repository for high-redshift data
  • Examine papers on curve fitting without physical model assumptions
  • Explore various mathematical functions for curve fitting (linear, exponential, trigonometric)
  • Investigate statistical methods for assessing fit quality in astronomical data
USEFUL FOR

Astronomers, astrophysicists, data analysts, and researchers interested in luminosity distance and redshift relationships, particularly those focusing on type Ia supernovae and gamma-ray bursts.

redtree
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Can anyone recommend papers that directly curve-fit redshift as a function of luminosity distance for type Ia supernova and gamma ray bursts? I am looking for papers that do not curve-fit the data via an assumed model, even one as simple as Friedmann–Lemaître–Robertson–Walker (FLRW) metric. I am really just curious to see what the following function ##f## might look like, where ##z## denotes redshift and ##d_l## denotes luminosity distance:

##z = f(d_l) ##
 
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You need some assumptions for f to do curve fitting. The "best fit" is a function that attains the best estimate for z at the best estimate for dl for every single measurement exactly, but that won't give a realistic function.
 
Sure, but the assumptions for ##f## can be about the relationship between the variables (linear? exponential? trigonometric? etc.) without assuming a particular physical model.

Has anyone published the "best fit" function for ##z## as a function of ##d_l## WITHOUT first assuming a particular physical model?
 
Linear, exponential, trigonometric etc. all don't fit. Mathematically you can do it but the fit quality is just too bad to publish it.
 
Is there an online repository of the data out to high ##z## that is downloadable for analysis?
 
redtree said:
Is there an online repository of the data out to high ##z## that is downloadable for analysis?
Depends upon what you mean by high-z. Easiest to work with is probably supernova data. One relatively recent compilation is here, at the Supernova Cosmology Project:
http://supernova.lbl.gov/union/

They have published a summary table of the per-supernova distance/redshift relation:
http://supernova.lbl.gov/union/figures/SCPUnion2.1_mu_vs_z.txt

You'd have to read their papers to understand what the various columns of that table are, to apply them to your own fit. Looks like they go out to a redshift of about 1.4 or so.
 

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