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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Estimating Cosmological Parameters from the Dark Matter Distribution · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1711.02033/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1711.02033/feed.xml" rel="self" type="application/rss+xml" /><item><title>Estimating Cosmological Parameters from the Dark Matter Distribution — mentioned by mturmon</title><link>https://news.ycombinator.com/item?id=18117346</link><guid isPermaLink="false">urn:hackerpapers:mention:1711.02033:18117346</guid><pubDate>Mon, 01 Oct 2018 22:27:43 GMT</pubDate><description>&lt;p&gt;I took a quick look because I&amp;#x27;m aware of the work that has gone in to producing the best estimates of \Lambda CDM parameters from CMB data. This has been done by large-scale MCMC - not DL at all. But, the CMB signal really is Gaussian, so MCMC is well-suited. By going to the trouble of making a principled forward model including error statistics, you get error bars on all reported parameters, such as the age of the universe - these error bars are critical to later analysis. (&amp;quot;This model requires a Hubble constant in the range ... which is not supported by current observational evidence.&amp;quot;)…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1711.02033/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>astro-ph.CO</category></item></channel></rss>
