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"Cosmology Computer simulation."
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The universe in a box : simulations and the quest to code the cosmos
\"How scientists are using simulations to recreate the universe, revealing the hidden nature of reality Cosmology is a tricky science--no one can make their own stars, planets, or galaxies to test its theories. But over the last few decades a new kind of physics has emerged to fill the gap between theory and experimentation. Harnessing the power of modern supercomputers, cosmologists have built simulations that offer profound insights into the deep history of our universe, allowing centuries-old ideas to be tested for the first time. Today, physicists are translating their ideas and equations into code, finding that there is just as much to be learned from computers as from laboratories. In The Universe in a Box, cosmologist Andrew Pontzen explains how physicists model the universe's most exotic phenomena, from black holes and colliding galaxies to dark matter and quantum entanglement, enabling them to study the evolution of virtual worlds and to shed new light on our reality. Simulations don't just allow experimentation with the cosmos; they are also essential to myriad disciplines like weather forecasting, epidemiology, neuroscience, financial planning, airplane design, and special effects for summer blockbusters. Crafting these simulations involves tough compromises and expert knowledge. Simulation is itself a whole new branch of science, one that we are only just beginning to appreciate and understand. The story of simulations is the thrilling history of how we arrived at our current knowledge of the world around us, and provides a sneak peek at what we may discover next\"-- Publisher's description.
Book
The CAMELS Project: Expanding the Galaxy Formation Model Space with New ASTRID and 28-parameter TNG and SIMBA Suites
We present CAMELS-ASTRID, the third suite of hydrodynamical simulations in the Cosmology and Astrophysics with MachinE Learning (CAMELS) project, along with new simulation sets that extend the model parameter space based on the previous frameworks of CAMELS-TNG and CAMELS-SIMBA, to provide broader training sets and testing grounds for machine-learning algorithms designed for cosmological studies. CAMELS-ASTRID employs the galaxy formation model following the ASTRID simulation and contains 2124 hydrodynamic simulation runs that vary three cosmological parameters (Ω m , σ 8, Ω b ) and four parameters controlling stellar and active galactic nucleus (AGN) feedback. Compared to the existing TNG and SIMBA simulation suites in CAMELS, the fiducial model of ASTRID features the mildest AGN feedback and predicts the least baryonic effect on the matter power spectrum. The training set of ASTRID covers a broader variation in the galaxy populations and the baryonic impact on the matter power spectrum compared to its TNG and SIMBA counterparts, which can make machine-learning models trained on the ASTRID suite exhibit better extrapolation performance when tested on other hydrodynamic simulation sets. We also introduce extension simulation sets in CAMELS that widely explore 28 parameters in the TNG and SIMBA models, demonstrating the enormity of the overall galaxy formation model parameter space and the complex nonlinear interplay between cosmology and astrophysical processes. With the new simulation suites, we show that building robust machine-learning models favors training and testing on the largest possible diversity of galaxy formation models. We also demonstrate that it is possible to train accurate neural networks to infer cosmological parameters using the high-dimensional TNG-SB28 simulation set.
Journal Article
The universe in a box : a new cosmic history
How was our universe built? What happened at its beginning? And where do humans fit in? We are a minuscule part of an incredible continuum: a chain of events spanning 13.8 billion years, with an infinite future. But what does that future hold? And will we ever truly understand our cosmic home? 'The Universe In a Box' is Andrew Pontzen's tribute to simulation - the remarkable fusion of technology and science that, over the last century, has allowed us to understand the distant past and far future of the universe. It challenges everything we think we know about galaxies, black holes and matter itself. And it reveals the pioneer scientists who unlocked mysteries of space, from redshift to improbable dark materials that pass, ghost-like, through solid rock.
BOOK
The Galaxy Cluster Mass Scale and Its Impact on Cosmological Constraints from the Cluster Population
The total mass of a galaxy cluster is one of its most fundamental properties. Together with the redshift, the mass links observation and theory, allowing us to use the cluster population to test models of structure formation and to constrain cosmological parameters. Building on the rich heritage from X-ray surveys, new results from Sunyaev-Zeldovich and optical surveys have stimulated a resurgence of interest in cluster cosmology. These studies have generally found fewer clusters than predicted by the baseline
Planck
Λ
CDM model, prompting a renewed effort on the part of the community to obtain a definitive measure of the true cluster mass scale. Here we review recent progress on this front. Our theoretical understanding continues to advance, with numerical simulations being the cornerstone of this effort. On the observational side, new, sophisticated techniques are being deployed in individual mass measurements and to account for selection biases in cluster surveys. We summarise the state of the art in cluster mass estimation methods and the systematic uncertainties and biases inherent in each approach, which are now well identified and understood, and explore how current uncertainties propagate into the cosmological parameter analysis. We discuss the prospects for improvements to the measurement of the mass scale using upcoming multi-wavelength data, and the future use of the cluster population as a cosmological probe.
Journal Article
Globular cluster formation and evolution in the context of cosmological galaxy assembly: open questions
We discuss some of the key open questions regarding the formation and evolution of globular clusters (GCs) during galaxy formation and assembly within a cosmological framework. The current state of the art for both observations and simulations is described, and we briefly mention directions for future research. The oldest GCs have ages greater than or equal to 12.5 Gyr and formed around the time of reionization. Resolved colour-magnitude diagrams of Milky Way GCs and direct imaging of lensed proto-GCs at z∼6 with the James Webb Space Telescope (JWST) promise further insight. GCs are known to host multiple populations of stars with variations in their chemical abundances. Recently, such multiple populations have been detected in ∼2 Gyr old compact, massive star clusters. This suggests a common, single pathway for the formation of GCs at high and low redshift. The shape of the initial mass function for GCs remains unknown; however, for massive galaxies a power-law mass function is favoured. Significant progress has been made recently modelling GC formation in the context of galaxy formation, with success in reproducing many of the observed GC-galaxy scaling relations.
Journal Article
Universal structure of dark matter haloes over a mass range of 20 orders of magnitude
Cosmological models in which dark matter consists of cold elementary particles predict that the dark halo population should extend to masses many orders of magnitude below those at which galaxies can form
1
–
3
. Here we report a cosmological simulation of the formation of present-day haloes over the full range of observed halo masses (20 orders of magnitude) when dark matter is assumed to be in the form of weakly interacting massive particles of mass approximately 100 gigaelectronvolts. The simulation has a full dynamic range of 30 orders of magnitude in mass and resolves the internal structure of hundreds of Earth-mass haloes in as much detail as it does for hundreds of rich galaxy clusters. We find that halo density profiles are universal over the entire mass range and are well described by simple two-parameter fitting formulae
4
,
5
. Halo mass and concentration are tightly related in a way that depends on cosmology and on the nature of the dark matter. For a fixed mass, the concentration is independent of the local environment for haloes less massive than those of typical galaxies. Haloes over the mass range of 10
−3
to 10
11
solar masses contribute about equally (per logarithmic interval) to the luminosity produced by dark matter annihilation, which we find to be smaller than all previous estimates by factors ranging up to one thousand
3
.
Simulations of formation of dark matter haloes ranging in size from Earth mass to clusters of galaxies find a universal halo density structure spanning 20 orders of magnitude in mass.
Journal Article
Learning to predict the cosmological structure formation
Matter evolved under the influence of gravity from minuscule density fluctuations. Nonperturbative structure formed hierarchically over all scales and developed non-Gaussian features in the Universe, known as the cosmic web. To fully understand the structure formation of the Universe is one of the holy grails of modern astrophysics. Astrophysicists survey large volumes of the Universe and use a large ensemble of computer simulations to compare with the observed data to extract the full information of our own Universe. However, to evolve billions of particles over billions of years, even with the simplest physics, is a daunting task. We build a deep neural network, the Deep Density Displacement Model (D³M), which learns from a set of prerun numerical simulations, to predict the nonlinear large-scale structure of the Universe with the Zel’dovich Approximation (ZA), an analytical approximation based on perturbation theory, as the input. Our extensive analysis demonstrates that D³M outperforms the second-order perturbation theory (2LPT), the commonly used fast-approximate simulation method, in predicting cosmic structure in the nonlinear regime. We also show that D³M is able to accurately extrapolate far beyond its training data and predict structure formation for significantly different cosmological parameters. Our study proves that deep learning is a practical and accurate alternative to approximate 3D simulations of the gravitational structure formation of the Universe.
Journal Article
The CAMELS Multifield Data Set: Learning the Universe’s Fundamental Parameters with Artificial Intelligence
We present the Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) Multifield Data set (CMD), a collection of hundreds of thousands of 2D maps and 3D grids containing many different properties of cosmic gas, dark matter, and stars from more than 2000 distinct simulated universes at several cosmic times. The 2D maps and 3D grids represent cosmic regions that span ∼100 million light-years and have been generated from thousands of state-of-the-art hydrodynamic and gravity-only N-body simulations from the CAMELS project. Designed to train machine-learning models, CMD is the largest data set of its kind containing more than 70 TB of data. In this paper we describe CMD in detail and outline a few of its applications. We focus our attention on one such task, parameter inference, formulating the problems we face as a challenge to the community. We release all data and provide further technical details at https://camels-multifield-dataset.readthedocs.io.
Journal Article
Overview of KAGRA: Detector design and construction history
Abstract
KAGRA is a newly built gravitational-wave telescope, a laser interferometer comprising arms with a length of 3 km, located in Kamioka, Gifu, Japan. KAGRA was constructed under the ground and it is operated using cryogenic mirrors that help in reducing the seismic and thermal noise. Both technologies are expected to provide directions for the future of gravitational-wave telescopes. In 2019, KAGRA finished all installations with the designed configuration, which we call the baseline KAGRA. For this occasion, we present an overview of the baseline KAGRA from various viewpoints in a series of articles. In this article, we introduce the design configurations of KAGRA with its historical background.
Journal Article
Observations of the missing baryons in the warm–hot intergalactic medium
It has been known for decades that the observed number of baryons in the local Universe falls about 30–40 per cent short
1
,
2
of the total number of baryons predicted
3
by Big Bang nucleosynthesis, as inferred
4
,
5
from density fluctuations of the cosmic microwave background and seen during the first 2–3 billion years of the Universe in the so-called ‘Lyman α forest’
6
,
7
(a dense series of intervening H
i
Lyman α absorption lines in the optical spectra of background quasars). A theoretical solution to this paradox locates the missing baryons in the hot and tenuous filamentary gas between galaxies, known as the warm–hot intergalactic medium. However, it is difficult to detect them there because the largest by far constituent of this gas—hydrogen—is mostly ionized and therefore almost invisible in far-ultraviolet spectra with typical signal-to-noise ratios
8
,
9
. Indeed, despite large observational efforts, only a few marginal claims of detection have been made so far
2
,
10
. Here we report observations of two absorbers of highly ionized oxygen (O
vii
) in the high-signal-to-noise-ratio X-ray spectrum of a quasar at a redshift higher than 0.4. These absorbers show no variability over a two-year timescale and have no associated cold absorption, making the assumption that they originate from the quasar’s intrinsic outflow or the host galaxy’s interstellar medium implausible. The O
vii
systems lie in regions characterized by large (four times larger than average
11
) galaxy overdensities and their number (down to the sensitivity threshold of our data) agrees well with numerical simulation predictions for the long-sought warm–hot intergalactic medium. We conclude that the missing baryons have been found.
Observations of two absorbers of highly ionized oxygen in the X-ray spectrum of a quasar account for the missing baryons in the Universe.
Journal Article