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Binning is sinning! This is becoming a theme... @katestoreyfish @davidwhogg @david_kipping
Paper day with @samreayh and @DScol ! https://arxiv.org/abs/2012.05900
Headline: The systematic floor of constraints of dark energy with Type Ia Supernovae can be improved by 1.5x right now!
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Paper day with @samreayh and @DScol ! https://arxiv.org/abs/2012.05900
Headline: The systematic floor of constraints of dark energy with Type Ia Supernovae can be improved by 1.5x right now!
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The moral of the story is that we shouldn't be binning or smoothing over the valuable information in our data! Unlike what has been done in the most recent analyses. (I myself am partly to blame for this!)
Only then we can truly leverage the power of "self-calibration"!
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Only then we can truly leverage the power of "self-calibration"!
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This is really exciting because this implies that as the dataset size grows, so does the power of self calibration, and the systematic floor will drop! Which is really awesome news for upcoming supernova surveys like @VRubinObs @NASARoman @LSSTDESC
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But it presents a serious challenge for the scientific community as currently-used methodologies aren't yet equipped to handle the complexity of information that the future surveys will collect (i.e. non-Ia supernova contamination) without doing some kind of binning!
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So this is a call to action for my colleagues at @theDESurvey @LSSTDESC @CenterForAstro @pennphys to help solve this problem and facilitate what is looking like an amazing future of supernova cosmology!
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