These maps will also enhance our understanding of the connection between dark matter and galaxies.” It also shows the power of artificial intelligence methods to analyse one of the largest data sets in astronomy.”Ĭo-author Dr Chihway Chang (University of Chicago) said: “ Our map projects 3D space, extending out over seven billion light years, into a 2D representation. In our next phase of work, we will analyse tomographic maps at varying distances to build a 3D view of the Universe. This brings us closer to understanding what the Universe is made of and how it has evolved. “By calculating how gravity distorts light, a technique known as gravitational lensing, we get the whole picture – both visible and invisible matter. When we look at the night sky, we see the galaxy’s light but not the surrounding dark matter - like looking at the lights of a city at night. Dark matter, like dark energy, remains mysterious, but its existence is inferred from galaxies behaving in ways not predicted – for instance, the fact that galaxies stay clustered together, and that galaxies within clusters move faster than expected.Ĭo-author Professor Ofer Lahav (UCL Physics & Astronomy), chair of the DES UK consortium and co-Director of UCL’s Centre for Doctoral Training Centre in Data Intensive Science, said: “Visible galaxies form in the densest regions of dark matter. Since the 1930s, astronomers have suspected there is more material in the Universe than we can see. “Observing these cosmic-scale structures can help us to answer fundamental questions about the Universe.” “In our map, which mainly shows dark matter, we see a similar pattern as we do with visible matter only– a web-like structure with dense clumps of matter separated by large empty voids. These structures are revealed using the distorted shapes of hundreds of millions of distant galaxies with photographs from the Dark Energy Camera in Chile. It is a real wonder to get a glimpse of these vast, hidden structures across a large portion of the night sky. It is described in a new paper posted on the DES website and to be published in the Monthly Notices of the Royal Astronomical Society.Ĭo-lead author Dr Niall Jeffrey (both at École Normale Supérieure, Paris, and UCL Physics & Astronomy) said: “Most of the matter in the Universe is dark matter. The new map, a representation of all matter detected in the foreground of the observed galaxies, covers a quarter of the sky of the Southern Hemisphere. The team used artificial intelligence methods to analyse images of 100 million galaxies, looking at their shape – spots of light made up of 10 or so pixels – to see if they have been stretched. Wich gives: indx gene_id length Total A1 A2 A3 A4 Summarise_each(funs(func(.,Total,length))) with lapply(.SD, function(x) (x * 1e6) / (Total * length)) you apply the required calculation to each column which is not specified in the by statementĪ similar solution with dplyr: library(dplyr).with by=.(indx,gene_id,length,Total) you determine the columns by which you want to group the data (these columns will not be transformed), by including the indx you make sure that each row is an unique group.with you create a unique identifier for each row.

with setDT(df1) you convert the dataframe to a datatable.SetDT(df1)[, lapply(.SD, function(x) (x * 1e6) / (Total * length)), Using the data.table package: library(data.table) You can achieve this also without reshaping.

Millions mapped