The Scale Of The Universe Download [UPD]
Selene Bulger
The Scale of the Universe 2 is an educational game in which you are shown the sizes of different things in our universe in relation to other different things. Slide your way into the largest objects that our universe has to offer, or into the smallest things that exist in our known universe. There are a lot of things to discover in this game, and you can click each one of them to find out more info about that specific object.DeveloperThe Scale of the Universe 2 was made by Cary and Michael Huang.
Tapping into the power of machine learning and artificial intelligence, a team led by Lawrence Berkeley National Laboratory (Berkeley Lab) scientists will host a series of competitions to spur future breakthroughs in high energy physics (HEP) and will work to build a supercomputer-scale platform where researchers can train and fine-tune their AI models.
A computer model of the large-scale structure of the universe using the Illustris simulator. This image depicts the dark matter and gas involved in forming galaxies and galaxy clusters, as well as the filaments connecting them.
Proteins are the major actors in all cellular processes, from the generation of energy to the division of the cell. Knowing their structure is relevant for studying their function, their evolution and potentially for the design of drugs. Although our knowledge of protein sequences has grown considerably over the past years, reaching over hundreds of millions of sequences, the knowledge of their 3D structures has lagged behind owing to the lack of highly scalable experimental methods. Improvements in methods for predicting structure from sequences1,3,4 now enable the scalable prediction of protein structures for the known protein universe. The AlphaFold Protein Structure Database (AFDB) is a publicly available data repository of protein structures and their confidence metrics, predicted using the AlphaFold2 AI system1,2. The AlphaFold-predicted structures have been generally assessed to be of high quality when the predicted local distance difference test (pLDDT) confidence metrics are accounted for, despite remaining inferior to experimentally determined structures5. AlphaFold2 and its predicted structures have now been used for diverse applications, including studies of protein pockets6, prediction of structures of complexes7,8, studies of structural similarity9, novel fold predictions10 and even improvement of genomic annotation11.
The distribution of the known and unknown clusters as a function of their size is shown in Fig. 1d. The sizes of clusters that lack annotations are smaller compared with the annotated clusters. For this reason, the dark clusters map to a proportionally smaller fraction of the protein universe. Although these clusters comprise approximately 30.9% of the AFDB clusters, they represent only 4.06% of the AFDB. This is consistent with the expectation that structures with many representatives in the protein universe are better studied and that the vast majority of protein structures can be annotated with at least partial similarity to a known structure of domain family annotation.
Large Scale Structure also tells us about dark energy. Most theoretical models of dark energy act to slow down this process of gravity creating large structures. Essentially, as the universe accelerates in its expansion, it takes more time for matter to come together because it must travel more distance. Studying the growth of large scale structure across time gives us information about gravity, dark energy, and how each may be changing as the Universe evolves with time.
Quasar light reveals clues about the large-scale structure of the universe, on the scale of 20 million light years across or more, as it shines through enormous clouds of neutral hydrogen gas formed shortly after the Big Bang.
The PRIYA simulation suite is connected to a large-scale cosmological simulation co-developed by Bird, called ASTRID, which helps study galaxy formation, the coalescence of supermassive black holes, and the re-ionization period early in the history of the universe. PRIYA goes a step further by taking the galaxy information and the black hole formation rules found in ASTRID and changing the initial conditions.
I spent a little time fiddling with a small Javscript program to organize all of my images into a logarithmic scale by their distance in our observable universe. It still baffles me all the time of what I am able to see from my backyard! I think this gives a nice sense of just how far away some of these things are that we image.
Comparison of the void and particle nearest-neighbor probability density functions for the cosmological and Poissonian dataset, as defined in Eqs. (14) and (15). Panel (a) shows the probability distribution of finding a void of radius r in the cosmological (blue) and Poisson (red) datasets, averaged over 100 realizations, while panel (b) gives the distribution function of the distance of a given particle from its nearest neighbor. For the Poisson case, the dashed lines show theory curves (defined in Sec. 2c), which are in excellent agreement with the simulations. The void distribution in the quijote simulations follows the (mean-density-matched) Poisson distribution at small r, but has an excess of large voids (shown by much broader tails), due to the quasi-long-range correlations. In contrast, the particle distribution HP(r) differs between the cosmological and Poissonian simulations on all scales, notably with an absence of small separations (due to halo exclusion effects) and an enhancement on large scales.
Direct-connectedness function C2(r,η) for the Poisson (left) and cosmological (right) simulations. This follows Fig. 6, but focuses on smaller scales, and additionally includes analytic predictions from the Percus-Yevick model. We additionally normalize all quantities by g2(r), and exclude values of η for which C2(r,η) is not well-behaved (beyond the percolation threshold).
The distribution of galaxies on large scales encodes valuable information about the origin and fate of the universe. To study this, BOSS, a branch of the Sloan Digital Sky Survey (SDSS-III), has measured the redshift distribution of galaxies with unprecedented accuracy. One important question arises in the analysis of the data provided by such surveys: If the universe is comparable to a huge unique experiment, how can we determine the uncertainties in the measurement of quantities derived from observing it?
While common experiments can be repeated an arbitrary number of times in the laboratory, the cosmic universe is only reproducible in super-computing facilities. One needs to consider the statistical fluctuations caused by the so-called cosmic variance, having its origin in the primordial seed fluctuations. However, reconstructing the large-scale structure covering the volumes of a survey like BOSS from the fluctuations generated after the Big Bang until the formation of the observed galaxies after about 14 billion years of cosmic evolution is an extremely expensive task, requiring millions of super-computing hours.
Proteins are key to all cellular processes and their structure is important in understanding their function and evolution. Sequence-based predictions of protein structures have increased in accuracy1, and over 214 million predicted structures are available in the AlphaFold database2. However, studying protein structures at this scale requires highly efficient methods. Here, we developed a structural-alignment-based clustering algorithm-Foldseek cluster-that can cluster hundreds of millions of structures. Using this method, we have clustered all of the structures in the AlphaFold database, identifying 2.30 million non-singleton structural clusters, of which 31% lack annotations representing probable previously undescribed structures. Clusters without annotation tend to have few representatives covering only 4% of all proteins in the AlphaFold database. Evolutionary analysis suggests that most clusters are ancient in origin but 4% seem to be species specific, representing lower-quality predictions or examples of de novo gene birth. We also show how structural comparisons can be used to predict domain families and their relationships, identifying examples of remote structural similarity. On the basis of these analyses, we identify several examples of human immune-related proteins with putative remote homology in prokaryotic species, illustrating the value of this resource for studying protein function and evolution across the tree of life.
Diagrams like the one above of the distribution of galaxies in the Universe seem to imply that the Universe isn't homogeneous and isotropic. In other words, the galaxies in one direction are not distributed in exactly the same way as the galaxies in another direction. However, if you look at the scale on the plot, the galaxies it contains only extend to a redshift of z < 0.2, which is equivalent to a distance of about 750 Mpc. When we study the most distant objects we can find at much larger distances from Earth, the structure appears to smooth out and become more homogeneous on the largest scales. For example, the all-sky map of the locations of objects detected by radio telescopes shown below reveals a much more uniform appearance. These objects are mostly expected to lie at higher redshifts than the ones in the pie slice diagram above, suggesting that when we consider the largest distance scales, the Universe appears to be homogeneous and isotropic. Thus, we currently find support for the Cosmological Principle in the distribution of galaxies in the Universe.
The new NASA animation shows 10 supersized black holes that occupy center stage in their host galaxies, including the Milky Way and M87, scaled by the sizes of their shadows. Starting near the Sun, the camera steadily pulls back to compare ever-larger black holes to different structures in our solar system.
The term Large Scale structure of the Universe refers to the patterns of galaxies and matter on scales much larger than individual galaxies and groupings of galaxies. These correlated structures can be seen up to billion of light years in length and are created and shaped by gravity.[1] On large scales, the Universe displays coherent structure with galaxies residing in groups and clusters on scale(s)of 1-3 megaparsecs(Mpc) which lie at the intersections of long filament of galaxies that are usually >10 Mpc in length. Vast regions of relatively empty space, known as voids, contain very few galaxies and span in the volume in between these structures.[2]
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