Lecture 14 Flashcards
What is degeneracy
since only a few observables are “clean” and often depend on multiple parameters at once,
observations typically tell us values of some complicated combination of parameters
how do we decipher measurements and get around degeneracy
probability contour plots to visualise this, tells us how likely a combination for any pair of values is
what is good about the concordance model
it fits wide range of data with similar parameters. the contours for very different data sets all meet somewhere
what does it mean if contours for different observations don’t cross for a model
the observations disagree on what values the model parameters are so no parameter set is a good fit to both data sets.
theory is wrong or problem with data set
what can cause data sets to be wrong
they are contaminated, often due to:
cmb foregrounds, lensing redshift errors, star-galaxy separation
how is the CMB specifically contaminated and how is it fixed
contaminated by foreground material within our galaxy. modelling process removes this
how do you correctly interpret lensing and clustering without contamination
need to know galaxy redshifts,
need to use an approximate and fast method which is inaccurate as spectroscopy on individual galaxies is too slow
what else causes issue for measuring clustering?
distinguishing stars from galaxies which can be hard as the images are often poor quality/noisy
what are tensions
sets of measurements apparently disagreeing with each other or implying lambda CDM is wrong
what are issues with measuring Hubble parameter despite it not being entangled with cosmological parameters
need to ensure standard candles are actually standard and identify them clearly.
what is the S8 tension
quantity that measures amount of cosmic structure at a late time
cmb measurements projected predicted different things to this,
discrepancy could be caused by black hole jets pushing matter around the universe, decreasing clustering
