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The Microchannel X-ray Telescope (MXT) will be the first focusing X-ray telescope based on a narrow field "Lobster-Eye" optical design to be flown on a satellite, namely the Sino-French mission SVOM. SVOM will be dedicated to the study of Gamma-Ray Bursts and more generally time-domain astrophysics. The MXT telescope is a compact (focal length ∼ 1.15 m) and light (< 42 kg) instrument, sensitive in the 0.2–10 keV energy range. It is composed of an optical system, based on micro-pore optics (MPOs) of 40 μ m pore size, coupled to a low-noise pnCDD X-ray detector. In this paper we describe the expected scientific performance of the MXT telescope, based on the End-to-End calibration campaign performed in fall 2021, before the integration of the SVOM payload on the satellite. [ABSTRACT FROM AUTHOR]

In time-domain astronomy, a substantial number of transients will be discovered by multi-wavelength and multi-messenger observatories, posing a great challenge for follow-up capabilities. We have thus proposed an intelligent X-ray constellation, the Chasing All Transients Constellation Hunters (CATCH) space mission. Consisting of 126 micro-satellites in three types, CATCH will have the capability to perform follow-up observations for a large number of different types of transients simultaneously. Each satellite in the constellation will carry lightweight X-ray optics and use a deployable mast to increase the focal length. The combination of different optics and detector systems enables different types of satellites to have multiform observation capabilities, including timing, spectroscopy, imaging, and polarization. Controlled by the intelligent system, different satellites can cooperate to perform uninterrupted monitoring, all-sky follow-up observations, and scanning observations with a flexible field of view (FOV) and multi-dimensional observations. Therefore, CATCH will be a powerful mission to study the dynamic universe. Here, we present the current design of the spacecraft, optics, detector system, constellation configuration and observing modes, as well as the development plan. [ABSTRACT FROM AUTHOR]

In this research, we are interested in constraining the nonlinear interacting and noninteracting Tsallis holographic dark energy (THDE) with Ricci horizon cutoff by employing three observational datasets. To this aim, the THDE with Ricci horizon considering the noninteraction and nonlinear interaction terms will be fitted by the SNe Ia, SNe Ia+H(z), and SNe Ia+H(z)+GRB samples to investigate the Hubble (H (z) ), dark-energy equation of state ( ω D E ), effective equation of state ( ω e f f ), and deceleration (q ) parameters. Investigating the H (z) parameter illustrates that our models are in good consistency with respect to observations. Also, it can reveal the turning point for both noninteracting and nonlinear interacting THDE with Ricci cutoff in the late-time era. Next, the analysis of the ω D E for our models displays that the dark energy can experience the phantom state at the current time. However, this lies in the quintessence regime in the early era and approaches the cosmological constant in the late-time epoch. Similar results will be given for the ω e f f parameter with the difference that the ω e f f will experience the quintessence region at the current redshift. In addition to the mentioned parameters, the study of the q parameter indicates that the models satisfy an acceptable transition phase from the matter- to the dark energy-dominated era. After that, the classical stability ( v s 2 ) will be analyzed for our models. The v s 2 shows that the noninteracting and nonlinear interacting THDE with Ricci cutoff will be stable in the past era but unstable in the present and progressive epochs. Then, we will employ the J e r k (J ) and O M parameters to distinguish between our models and the Λ C D M model. Finally, we will calculate the age of the Universe for the THDE and nonlinear interacting THDE with Ricci as the IR cutoff. [ABSTRACT FROM AUTHOR]

The Diffraction-Limited Near-Infrared Spectropolarimeter (DL-NIRSP) is one of the first-light instruments for the National Science Foundation's Daniel K. Inouye Solar Telescope (DKIST). DL-NIRSP is an integral-field, dual-beam spectropolarimeter intended for studying magnetically sensitive spectral lines in the Sun's photosphere, chromosphere, and corona with high spectral resolution and polarimetric accuracy. Two novel fiber-optic integral-field units (IFUs), paired with selectable feed optics and a field-scanning mirror provide great flexibility in spatial sampling ( 0.03 ″ , 0.08 ″ , and 0.5 ″ ) and field coverage ( 2 ′ × 2 ′ ). The IFUs allow DL-NIRSP to record all the spectra from a 2D field of view simultaneously, enabling the instrument to study the evolution of highly dynamic events. The spectrograph is an all-reflecting, near-Littrow design, which achieves a resolving power of approximately 125,000. Multiple wavelengths can be observed simultaneously using three spectral arms: one for visible wavelengths (500 – 900 nm) and two for infrared wavelengths (900 – 1350 nm and 1350 – 1800 nm). Each supporting camera sub-system is capable of a 30-Hz frame rate, making it possible to track dynamic phenomena on the Sun. [ABSTRACT FROM AUTHOR]

Astronomy, being one of the oldest observational sciences, has collected a lot of data over the ages. In recent times, it is experiencing a huge data surge due to advancements in telescopic technologies with automated digital outputs. The main driver behind this article is to present various relevant Machine Learning (ML) algorithms and big data frameworks or tools being applied and can be employed in large astronomical data-set analysis to assist astronomers in solving multiple vital intriguing problems. Throughout this survey, we attempt to review, evaluate and summarize diverse astronomical data sources, gain knowledge of structure, the complexity of the data, and challenges in the data processing. Additionally, we discuss ample technologies being developed to handle and process this voluminous data. We also look at numerous activities being carried out all over the world enriching this domain. While going through existing literature, we perceived a limited number of comprehensive studies reported so far analyzing astronomy data-sets from the viewpoint of parallel processing and machine learning collectively. This motivated us to pursue this extensive literature review task by outlining up-to-date contributions and opportunities available in this area. Besides, this article also discusses briefly a cloud-based machine learning approach to estimate the extra-galactic object redshifts considering photometric data as input features. As the intersection of big data, machine learning and astronomy is a quite new paradigm, this article will create a strong awareness among interested young scientists for future research and provide an appropriate insight on how these algorithms and tools are becoming inevitable to the astronomy community day by day. [ABSTRACT FROM AUTHOR]

The probabilistic nature of the IMF in stellar systems implies that clusters of the same mass and age do not present the same unique values of their observed parameters. Instead they follow a distribution. We address the study of such distributions in terms of their confidence limits that can be obtained by evolutionary synthesis models. These confidence limits can be understood as the inherent uncertainties of synthesis models. We will compare such confidence limits arising from the discreteness of the number of stars obtained with Monte Carlo simulations with the dispersion resulting from an analytical formalism. We give some examples of the effects on the kinetic energy, V–K, EW(Hβ) and multiwavelength continuum. [ABSTRACT FROM AUTHOR]

Today, thanks in particular to the results of the ESA Planck mission, the concordance cosmological model appears to be the most robust to describe the evolution and content of the Universe from its early to late times. It summarizes the evolution of matter, made mainly of dark matter, from the primordial fluctuations generated by inflation around 10− 30 second after the Big Bang to galaxies and clusters of galaxies, 13.8 billion years later, and the evolution of the expansion of space, with a relative slowdown in the matter-dominated era and, since a few billion years, an acceleration powered by dark energy. But we are far from knowing the pillars of this model which are inflation, dark matter and dark energy. Comprehending these fundamental questions requires a detailed mapping of our observable Universe over the whole of cosmic time. The relic radiation provides the starting point and galaxies draw the cosmic web. JAXA's LiteBIRD mission will map the beginning of our Universe with a crucial test for inflation (its primordial gravity waves), and the ESA Euclid mission will map the most recent half part, crucial for dark energy. The mission concept GAUSS, described in this White Paper, aims at being a mission to fully map the cosmic web up to the reionization era, linking early and late evolution, to tackle and disentangle the crucial degeneracies persisting after the Euclid era between dark matter and inflation properties, dark energy, structure growth and gravitation at large scale. [ABSTRACT FROM AUTHOR]

The existence of optical-ultraviolet Tidal Disruption Events (TDEs) could be considered surprising because their electromagnetic output was originally predicted to be dominated by X-ray emission from an accretion disk. Yet over the last decade, the growth of optical transient surveys has led to the identification of a new class of optical transients occurring exclusively in galaxy centers, many of which are considered to be TDEs. Here we review the observed properties of these events, identified based on a shared set of both photometric and spectroscopic properties. We present a homogeneous analysis of 33 sources that we classify as robust TDEs, and which we divide into classes. The criteria used here to classify TDEs will possibly get updated as new samples are collected and potential additional diversity of TDEs is revealed. We also summarize current measurements of the optical-ultraviolet TDE rate, as well as the mass function and luminosity function. Many open questions exist regarding the current sample of events. We anticipate that the search for answers will unlock new insights in a variety of fields, from accretion physics to galaxy evolution. [ABSTRACT FROM AUTHOR]

The coincidental detection of the gravitational wave event GW 170817 and the gamma-ray burst GRB 170817A marked the advent of multi-messenger astronomy and represented a milestone in the study of GRBs. Significant progress in this field is expected in the coming years with the increased sensitivity of gravitational waves detectors and the launch of new facilities for the high-energy survey of the sky. In this context, the launch of SVOM in mid-2022, with its two wide-field high-energy instruments ECLAIRs and GRM, will foster the possibilities of coincidental transient detection with gravitational waves and gamma-rays events. The purpose of this paper is to assess the ability of SVOM/ECLAIRs to detect and quickly characterize high-energy transients in the local Universe (z ≤ 0.3), and to discuss the contribution of this instrument to multi-messenger astronomy and to gamma-ray burst (GRB) astrophysics in the 2020’s. A list of local HE transients, along with their main characteristics, is constructed through an extensive literature survey. This list includes 41 transients: 24 long GRBs, 10 short GRBs and 7 SGR Giant Flares. The detectability of these transients with ECLAIRs is assessed with detailed simulations using tools developed for the SVOM mission, including a GEANT4 simulation of the energy response and a simulated trigger algorithm representative of the onboard trigger algorithm. SVOM/ECLAIRs would have been able to detect 88% of the short high-energy transients in our list: 22 out of 24 long GRBs, 8 out of 10 short GRBs and 6 out of 7 SGR Giant Flares. The SNR for almost all detections will be sufficiently high to allow the on-board ECLAIRs trigger algorithm to derive the localisation of the transient, transmitting it to the SVOM satellite and ground-based instruments. Coupled with the anti-solar pointing strategy of SVOM, this will enable an optimal follow-up of the events, allowing the observation of their afterglows, supernovae/kilonovae counterparts, and host galaxies. We conclude the paper with a discussion of the unique contribution expected from SVOM and of the possibility of simultaneous GW detection for each type of transient in our sample. [ABSTRACT FROM AUTHOR]

The ESA-Gaia satellite is regularly producing Alerts on objects where photometric variability has been detected after several passages over the same region of the sky. The physical nature of these objects has often to be determined with the help of complementary observations from ground-based facilities. We have compared the list of Gaia Alerts (from the beginning in 2014 to Nov. 1st, 2018) with archival LAMOST and SDSS spectroscopic data. A search radius of 3″ has been adopted. In using survey data, the date of the ground-based observation rarely corresponds to the date of the Alert, but this allows at least the identification of the source if it is persistent, or the host galaxy if the object was only transient like a supernova (SN). Some of the objects have several LAMOST observations, and we complemented this search by adding also SDSS DR15 data in order to look for long-term variability. A list of Gaia Nuclear Transients (GNT) from Kostrzewa-Rutkowska et al. (Mon. Not. R. Astron. Soc. 481(1):307, 2018) has been included in this search also. We found 26 Gaia Alerts with spectra in LAMOST+SDSS labelled as stars, among which 12 have multi-epoch spectra. A majority of them are Cataclysmic Variables (CVs). Similarly, 206 Gaia Alerts have associated spectra labelled as galaxies, among which 49 have multi-epoch spectra. Those spectra were generally obtained on a date widely different from the Alert date, and are mostly emission-line galaxies with no particularity (except a few Seyferts), leading to the suspicion that most of the Alerts were due to a SN. As for the GNT list, we found 55 associated spectra labelled as galaxies, among them 13 with multi-epoch spectra. In these two galaxy samples, in only two cases, Gaia17aal and GNTJ170213+2543, was the date of the spectroscopic observation close enough to the Alert date: we find a trace of the SN itself in their LAMOST spectrum, both being now classified here as a type Ia SN. Compared to the galaxy sample from the Gaia alerts, the GNT sample has a higher proportion of AGNs, suggesting that some of the detected variations are also due to the AGN itself. Similarly for Quasars, we found only 30 Gaia Alerts but 68 GNT cases associated with single epoch quasar spectra in the databases. In addition to those, 12 plus 23 are quasars where multi-epoch spectra are available. For ten out of these 35, their multi-epoch spectra show appearance or disappearance of the broad Balmer lines and also variations in the continuum, qualifying them as "Changing Look Quasars" and therefore significantly increasing the available sample of such objects. [ABSTRACT FROM AUTHOR]

Recent studies of Tidal Disruption Events (TDEs) have revealed unexpected correlations between the TDE rate and the large-scale properties of the host galaxies. In this review, we present the host galaxy properties of all TDE candidates known to date and quantify their distributions. We consider throughout the differences between observationally-identified types of TDEs and differences from spectroscopic control samples of galaxies. We focus here on the black hole and stellar masses of TDE host galaxies, their star formation histories and stellar populations, the concentration and morphology of the optical light, the presence of AGN activity, and the extra-galactic environment of the TDE hosts. We summarize the state of several possible explanations for the links between the TDE rate and host galaxy type. We present estimates of the TDE rate for different host galaxy types and quantify the degree to which rate enhancement in some types results in rate suppression in others. We discuss the possibilities for using TDE host galaxies to assist in identifying TDEs in upcoming large transient surveys and possibilities for TDE observations to be used to study their host galaxies. [ABSTRACT FROM AUTHOR]

Deep generative models, such as Generative Adversarial Networks (GANs) or Variational Autoencoders (VAs) have been demonstrated to produce images of high visual quality. However, the existing hardware on which these models are trained severely limits the size of the images that can be generated. The rapid growth of high dimensional data in many fields of science therefore poses a significant challenge for generative models. In cosmology, the large-scale, three-dimensional matter distribution, modeled with N-body simulations, plays a crucial role in understanding the evolution of structures in the universe. As these simulations are computationally very expensive, GANs have recently generated interest as a possible method to emulate these datasets, but they have been, so far, mostly limited to two dimensional data. In this work, we introduce a new benchmark for the generation of three dimensional N-body simulations, in order to stimulate new ideas in the machine learning community and move closer to the practical use of generative models in cosmology. As a first benchmark result, we propose a scalable GAN approach for training a generator of N-body three-dimensional cubes. Our technique relies on two key building blocks, (i) splitting the generation of the high-dimensional data into smaller parts, and (ii) using a multi-scale approach that efficiently captures global image features that might otherwise be lost in the splitting process. We evaluate the performance of our model for the generation of N-body samples using various statistical measures commonly used in cosmology. Our results show that the proposed model produces samples of high visual quality, although the statistical analysis reveals that capturing rare features in the data poses significant problems for the generative models. We make the data, quality evaluation routines, and the proposed GAN architecture publicly available at https://github.com/nperraud/3DcosmoGAN. [ABSTRACT FROM AUTHOR]

Deep generative models, such as Generative Adversarial Networks (GANs) or Variational Autoencoders (VAs) have been demonstrated to produce images of high visual quality. However, the existing hardware on which these models are trained severely limits the size of the images that can be generated. The rapid growth of high dimensional data in many fields of science therefore poses a significant challenge for generative models. In cosmology, the large-scale, three-dimensional matter distribution, modeled with N-body simulations, plays a crucial role in understanding the evolution of structures in the universe. As these simulations are computationally very expensive, GANs have recently generated interest as a possible method to emulate these datasets, but they have been, so far, mostly limited to two dimensional data. In this work, we introduce a new benchmark for the generation of three dimensional N-body simulations, in order to stimulate new ideas in the machine learning community and move closer to the practical use of generative models in cosmology. As a first benchmark result, we propose a scalable GAN approach for training a generator of N-body three-dimensional cubes. Our technique relies on two key building blocks, (i) splitting the generation of the high-dimensional data into smaller parts, and (ii) using a multi-scale approach that efficiently captures global image features that might otherwise be lost in the splitting process. We evaluate the performance of our model for the generation of N-body samples using various statistical measures commonly used in cosmology. Our results show that the proposed model produces samples of high visual quality, although the statistical analysis reveals that capturing rare features in the data poses significant problems for the generative models. We make the data, quality evaluation routines, and the proposed GAN architecture publicly available at https://github.com/nperraud/3DcosmoGAN. [ABSTRACT FROM AUTHOR]

Superluminous supernovae are a new class of supernovae that were recognized about a decade ago. Both observational and theoretical progress has been significant in the last decade. In this review, we first briefly summarize the observational properties of superluminous supernovae. We then introduce the three major suggested luminosity sources to explain the huge luminosities of superluminous supernovae, i.e., the nuclear decay of 56Ni, the interaction between supernova ejecta and dense circumstellar media, and the spin down of magnetars. We compare these models and discuss their strengths and weaknesses. [ABSTRACT FROM AUTHOR]

The formal division of the distance indicators into primary and secondary leads to difficulties in description of methods which can actually be used in two ways: with, and without the support of the other methods for scaling. Thus instead of concentrating on the scaling requirement we concentrate on all methods of distance determination to extragalactic sources which are designated, at least formally, to use for individual sources. Among those, the Supernovae Ia is clearly the leader due to its enormous success in determination of the expansion rate of the Universe. However, new methods are rapidly developing, and there is also a progress in more traditional methods. We give a general overview of the methods but we mostly concentrate on the most recent developments in each field, and future expectations. [ABSTRACT FROM AUTHOR]

We reconsider the issue of cosmological dynamics in a DGP setup with a bulk scalar field. The ghost-free, normal branch of this DGP-inspired braneworld scenario has the potential to realize a self-consistent phantom-like behavior. The roles played by the bulk canonical scalar field on this phantom-like dynamics are explored. Within a dynamical system approach, the effective phantom nature of the scenario is investigated with details. This analysis shows that there is a stable, late-time de Sitter phase. [ABSTRACT FROM AUTHOR]

In this contribution we examine the problem of inferring ages and initial cluster masses from synthesis models at the limit of low-mass clusters ( M≤ a few ×104 M⊙). We show that it is not possible to apply directly synthesis models using standard methods to such clusters, since the basic hypothesis implicit in the models (a fixed proportionality between the number of stars in different evolutionary phases) is not fulfilled due to an insufficient number of stars for a reliable sampling of the stellar initial mass function. The consequence of this incomplete sampling is a non-Gaussian distribution of the mass–luminosity relation for clusters that share the same evolutionary conditions (age, metallicity and stellar initial mass distribution function). We review some tests, that can be performed before the start of the analysis, to estimate if the observed cluster can be analyzed with synthesis models following traditional procedures (like χ2 minimization) or if it is necessary make use of synthesis models in a probabilistic framework. Finally, we show the implications of these results for estimating the low-mass tail in the initial cluster mass distribution function. [ABSTRACT FROM AUTHOR]

We review here the interplay of cluster and galaxy evolution. As a case study, we consider the Butcher-Oemler effect and propose that it is the result of the changing rate of cluster merger events in a hierarchical universe. This case study highlights the need for new catalogs of clusters and groups that possess quantified morphologies. We present such a sample here, namely the Sloan Digital Sky Survey (SDSS) C4 Catalog, which has been objectively-selected from the SDSS spectroscopic galaxy sample. We outline here the C4 algorithm and present first results based on the SDSS Early Data Release, including an X-ray luminosity-velocity dispersion (Lx-σv) scaling relationship (as a function of cluster morphology) and the density-SFR relation of galaxies within C4 clusters (Gomez et al., 2003). We also discuss the merger of Coma and the NGC4839 group and its effect on the galaxy populations in these systems. We finish with a brief discussion of a new sample of HΔ-selected galaxies (i.e., k+a, post-starburst galaxies) obtained from the SDSS spectroscopic survey. [ABSTRACT FROM AUTHOR]

We present the full public release of all data from the TNG100 and TNG300 simulations of the IllustrisTNG project. IllustrisTNG is a suite of large volume, cosmological, gravo-magnetohydrodynamical simulations run with the moving-mesh code Arepo. TNG includes a comprehensive model for galaxy formation physics, and each TNG simulation self-consistently solves for the coupled evolution of dark matter, cosmic gas, luminous stars, and supermassive black holes from early time to the present day, z = 0 . Each of the flagship runs—TNG50, TNG100, and TNG300—are accompanied by halo/subhalo catalogs, merger trees, lower-resolution and dark-matter only counterparts, all available with 100 snapshots. We discuss scientific and numerical cautions and caveats relevant when using TNG. The data volume now directly accessible online is ∼750 TB, including 1200 full volume snapshots and ∼80,000 high time-resolution subbox snapshots. This will increase to ∼1.1 PB with the future release of TNG50. Data access and analysis examples are available in IDL, Python, and Matlab. We describe improvements and new functionality in the web-based API, including on-demand visualization and analysis of galaxies and halos, exploratory plotting of scaling relations and other relationships between galactic and halo properties, and a new JupyterLab interface. This provides an online, browser-based, near-native data analysis platform enabling user computation with local access to TNG data, alleviating the need to download large datasets. [ABSTRACT FROM AUTHOR]

Inferring model parameters from experimental data is a grand challenge in many sciences, including cosmology. This often relies critically on high fidelity numerical simulations, which are prohibitively computationally expensive. The application of deep learning techniques to generative modeling is renewing interest in using high dimensional density estimators as computationally inexpensive emulators of fully-fledged simulations. These generative models have the potential to make a dramatic shift in the field of scientific simulations, but for that shift to happen we need to study the performance of such generators in the precision regime needed for science applications. To this end, in this work we apply Generative Adversarial Networks to the problem of generating weak lensing convergence maps. We show that our generator network produces maps that are described by, with high statistical confidence, the same summary statistics as the fully simulated maps. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

As the largest virialized structures in the universe, galaxy clusters continue to grow and accrete matter from the cosmic web. Due to the low gas density in the outskirts of clusters, measurements are very challenging, requiring extremely sensitive telescopes across the entire electromagnetic spectrum. Observations using X-rays, the Sunyaev-Zeldovich effect, and weak lensing and galaxy distributions from the optical band, have over the last decade helped to unravel this exciting new frontier of cluster astrophysics, where the infall and virialization of matter takes place. Here, we review the current state of the art in our observational and theoretical understanding of cluster outskirts, and discuss future prospects for exploration using newly planned and proposed observatories. [ABSTRACT FROM AUTHOR]

Most galaxies comparable to or larger than the mass of the Milky Way host hot, X-ray emitting atmospheres, and many such galaxies are radio sources. Hot atmospheres and radio jets and lobes are the ingredients of radio-mechanical active galactic nucleus (AGN) feedback. While a consensus has emerged that such feedback suppresses cooling of hot cluster atmospheres, less attention has been paid to massive galaxies where similar mechanisms are at play. Observation indicates that the atmospheres of elliptical and S0 galaxies were accreted externally during the process of galaxy assembly and augmented significantly by stellar mass loss. Their atmospheres have entropy and cooling time profiles that are remarkably similar to those of central cluster galaxies. About half display filamentary or disky nebulae of cool and cold gas, much of which has likely cooled from the hot atmospheres. We review the observational and theoretical perspectives on thermal instabilities in galactic atmospheres and the evidence that AGN heating is able to roughly balance the atmospheric cooling. Such heating and cooling may be regulating star formation in all massive spheroids at late times. [ABSTRACT FROM AUTHOR]

Dark matter in the universe evolves through gravity to form a complex network of halos, filaments, sheets and voids, that is known as the cosmic web. Computational models of the underlying physical processes, such as classical N-body simulations, are extremely resource intensive, as they track the action of gravity in an expanding universe using billions of particles as tracers of the cosmic matter distribution. Therefore, upcoming cosmology experiments will face a computational bottleneck that may limit the exploitation of their full scientific potential. To address this challenge, we demonstrate the application of a machine learning technique called Generative Adversarial Networks (GAN) to learn models that can efficiently generate new, physically realistic realizations of the cosmic web. Our training set is a small, representative sample of 2D image snapshots from N-body simulations of size 500 and 100 Mpc. We show that the GAN-generated samples are qualitatively and quantitatively very similar to the originals. For the larger boxes of size 500 Mpc, it is very difficult to distinguish them visually. The agreement of the power spectrum Pk is 1-2% for most of the range, between k=0.06 and k=0.4. For the remaining values of k, the agreement is within 15%, with the error rate increasing for k>0.8. For smaller boxes of size 100 Mpc, we find that the visual agreement to be good, but some differences are noticable. The error on the power spectrum is of the order of 20%. We attribute this loss of performance to the fact that the matter distribution in 100 Mpc cutouts was very inhomogeneous between images, a situation in which the performance of GANs is known to deteriorate. We find a good match for the correlation matrix of full Pk range for 100 Mpc data and of small scales for 500 Mpc, with ∼20% disagreement for large scales. An important advantage of generating cosmic web realizations with a GAN is the considerable gains in terms of computation time. Each new sample generated by a GAN takes a fraction of a second, compared to the many hours needed by traditional N-body techniques. We anticipate that the use of generative models such as GANs will therefore play an important role in providing extremely fast and precise simulations of cosmic web in the era of large cosmological surveys, such as Euclid and Large Synoptic Survey Telescope (LSST). [ABSTRACT FROM AUTHOR]

We review three distance measurement techniques beyond the local universe: (1) gravitational lens time delays, (2) baryon acoustic oscillation (BAO), and (3) HI intensity mapping. We describe the principles and theory behind each method, the ingredients needed for measuring such distances, the current observational results, and future prospects. Time-delays from strongly lensed quasars currently provide constraints on H0 with <4% uncertainty, and with 1% within reach from ongoing surveys and efforts. Recent exciting discoveries of strongly lensed supernovae hold great promise for time-delay cosmography. BAO features have been detected in redshift surveys up to z≲0.8 with galaxies and z∼2 with Ly-α forest, providing precise distance measurements and H0 with <2% uncertainty in flat ΛCDM. Future BAO surveys will probe the distance scale with percent-level precision. HI intensity mapping has great potential to map BAO distances at z∼0.8 and beyond with precisions of a few percent. The next years ahead will be exciting as various cosmological probes reach 1% uncertainty in determining H0, to assess the current tension in H0 measurements that could indicate new physics. [ABSTRACT FROM AUTHOR]