Dyadic analysis of spatially homogeneous world models.
Spatial homogeneous world cosmological models analyzed with dyadic formalism, noting conservation of Bianch-Behr type
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Spatial homogeneous world cosmological models analyzed with dyadic formalism, noting conservation of Bianch-Behr type
Many cosmological models of gamma-ray bursts (GRBs) assume that a single relativistic shell carries kinetic energy away from the source and later converts it into gamma rays, perhaps by interactions with the interstellar medium or by internal shocks within the shell. Although such models are able to reproduce general trends in GRB time histories, it is difficult to reproduce the high degree of variability often seen in GRBs. The authors investigate methods of achieving this variability using a simplified external shock model. Since the model emphasizes geometric and statistical considerations, rather than the detailed physics of the shell, it is applicable to any theory that relies on relativistic shells. They find that the variability in GRBs gives strong clues to the efficiency with which the shell converts its kinetic energy into gamma rays.
Hierarchical neural posterior estimation has its place Hierarchical Bayesian Modeling (HBM) combined with MCMC algorithms has been shown to provide more robust and accurate inference for real-world phenomena in which nature takes a nested form. However, MCMC-based inference can be computationally expensive, and its performance often suffers for complex posterior geometries. These costs are especially pertinent for HBM. Studies have recently demonstrated the potential for a flexible, expressive, and amortized hierarchical neural posterior estimator (HNPE) built on Normalizing Flows. These studies have mostly been performed on simple datasets, or they focus on a single parameter from each level of the hierarchy. A systematic study analyzing how both hierarchical methods compare for more complex and realistic datasets is necessary before applying HNPE for scientific measurements. Here, we re-explore the theory behind HNPE and conduct comparative numerical experiments of HNPE and MCMC-based HBM methods on real and synthetic data, including strong gravitational lensing simulations. In particular, we use a suite of diagnostics to show trade-offs in terms of accuracy, precision, time to train or sample, reproducibility, and the need for expert domain knowledge. Especially for higher dimensional and complex posteriors, HNPE is expected to drastically improve on time for inference, accuracy, and precision with an upfront training time cost.
We study the topology of large-scale structure in the Center for Astrophysics Redshift Survey, which now includes approximately 12,000 galaxies with limiting magnitude m(sub B) is less than or equal to 15.5. The dense sampling and large volume of this survey allow us to compute the topology on smoothing scales from 6 to 20/h Mpc; we thus examine the topology of structure in both 'nonlinear' and 'linear' regimes. On smoothing scales less than or equal to 10/h Mpc this sample has 3 times the number of resolution elements of samples examined in previous studies. Isodensity surface of the smoothed galaxy density field demonstrate that coherent high-density structures and large voids dominate the galaxy distribution. We compute the genus-threshold density relation for isodensity surfaces of the CfA survey. To quantify phase correlation in these data, we compare the CfA genus with the genus of realizations of Gaussian random fields with the power spectrum measured for the CfA survey. On scales less than or equal to 10/h Mpc the observed genus amplitude is smaller than random phase (96% confidence level). This decrement reflects the degree of phase coherence in the observed galaxy distribution. In other words the genus amplitude on these scales is not good measure of the power spectrum slope. On scales greater than 10/h Mpc, where the galaxy distribution is rougly in the 'linear' regime, the genus ampitude is consistent with the random phase amplitude. The shape of the genus curve reflects the strong coherence in the observed structure; the observed genus curve appears broader than random phase (94% confidence level for smoothing scales less than or equal to 10/h Mpc) because the topolgoy is spongelike over a very large range of density threshold. This departre from random phase consistent with a distribution like a filamentary net of 'walls with holes.' On smoothing scales approaching approximately 20/h Mpc the shape of the CfA genus curve is consistent with random phase. There is very weak evidence for a shift of the genus toward a 'bubble-like' topology. To test cosmological models, we compute the genus for mock CfA surveys drawn from large (L greater than or approximately 400/h Mpc) N-body simulations of three variants of the cold dark matter (CDM) cosmogony. The genus amplitude of the 'standard' CDM model (omega h = 0.5, b = 1.5) differs from the observations (96% confidence level) on smoothing scales is less than or approximately 10/h Mpc. An open CDM model (omega h = 0.2) and a CDM model with nonzero cosmological constant (omega h = 0.24, lambda (sub 0) = 0.6) are consistent with the observed genus amplitude over the full range of smoothing scales. All of these models fail (97% confidence level) to match the broadness of the observed genus curve on smoothing scales is less than or equal to 10/h Mpc.
We determine the velocity correlation function, pairwise peculiar velocity difference, and rms pairwise peculiar velocity dispersion of rich clusters of galaxies, as a function of pair separation, for three cosmological models: Omega = 1 and Omega = 0.3 cold dark matter (CDM), and Omega = 0.3 primeval baryonic isocurvature (PBI) models (all flat and Cosmic Background Explorer (COBE)-normalized). We find that close cluster pairs, with separation r is less than or equal to 10/h Mpc, exhibit strong attractive peculiar velocities in all models; the cluster pairwise velocities depend sensitively on the model. The mean pairwise attractive velocity of clusters on 5/h Mpc scale ranges from approximately 1700 km/s for Omega = 1 CDM to approximately 1000 km/s for PBI to approximately 700 km/s for Omega = 0.3 CDM. The small-scale pairwise velocities depend also on cluster mass: richer, more massive clusters exhibit stronger attractive velocities than less massive clusters. On large scales, from approximately 20 to 200/h Mpc, the cluster peculiar velocities are increasingly dominated by bulk and random motions; they are independent of cluster mass. The cluster velocity correlation function is negative on small scales for Omega = 1 and Omega = 0.3 CDM, indicating strong pairwise motion relative to bulk motion on small scales; PBI exhibits relatively larger bulk motions. The cluster velocity correlation function is positive on very large scales, from r approximately 10/h Mpc to r approximately 200/h Mpc, for all models. These positive correlations, which decrease monotonically with scale, indicate significant bulk motions of clusters up to approximately 200/h Mpc. The strong dependence of the cluster velocity functions on models, especially at small separations, makes them useful tools in constraining cosmological models when compared with observations.
We present cosmological constraints from eight strongly lensed quasars (hereafter, the TDCOSMO-2025 sample). Building on previous work, our analysis incorporated new deflector stellar velocity dispersions measured from spectra obtained with the James Webb Space Telescope (JWST), the Keck Telescopes, and the Very Large Telescope (VLT), utilizing improved methods. We used integrated JWST stellar kinematics for five lenses, VLT-MUSE for 2, and resolved kinematics from Keck and JWST for RX J1131−1231. We also considered two samples of non-time-delay lenses: 11 from the Sloan Lens ACS (SLACS) sample with Keck-KCWI resolved kinematics; and four from the Strong Lenses in the Legacy Survey (SL2S) sample. We improved our analysis of line-of-sight effects, the surface brightness profile of the lens galaxies, and orbital anisotropy, and corrected for projection effects in the dynamics. Our uncertainties are maximally conservative by accounting for the mass-sheet degeneracy in the deflectors’ mass density profiles. The analysis was blinded to prevent experimenter bias. Our primary result is based on the TDCOSMO-2025 sample, in combination with Ωm constraints from the Pantheon+ Type Ia supernovae (SN) dataset. In the flat Λ cold dark matter (CDM), we find H0 = 71.6+3.9−3.3 km s−1 Mpc−1. The SLACS and SL2S samples are in excellent agreement with the TDCOSMO-2025 sample, improving the precision on H0 in flat ΛCDM to 4.6%. Using the Dark Energy Survey SN Year-5 dataset (DES-SN5YR) or DESI-DR2 baryonic acoustic oscillations (BAO) likelihoods instead of Pantheon+ yields very similar results. We also present constraints in the open ΛCDM, wCDM, w0waCDM, and wϕCDM cosmologies. The TDCOSMO H0 inference is robust and consistent across all presented cosmological models, and our cosmological constraints in them agree with those from the BAO and SN.Key words: cosmological parameters / cosmology: observations / dark energy / distance scale⋆⋆ Brinson Fellow.⋆⋆⋆ NHFP Einstein Fellow.
Void statistics of the galaxy distribution in the Center for Astrophysics Redshift Survey provide strong constraints on galaxy clustering in the nonlinear regime, i.e., on scales R equal to or less than 10/h Mpc. Computation of high-order moments of the galaxy distribution requires a sample that (1) densely traces the large-scale structure and (2) covers sufficient volume to obtain good statistics. The CfA redshift survey densely samples structure on scales equal to or less than 10/h Mpc and has sufficient depth and angular coverage to approach a fair sample on these scales. In the nonlinear regime, the void probability function (VPF) for CfA samples exhibits apparent agreement with hierarchical scaling (such scaling implies that the N-point correlation functions for N greater than 2 depend only on pairwise products of the two-point function xi(r)) However, simulations of cosmological models show that this scaling in redshift space does not necessarily imply such scaling in real space, even in the nonlinear regime; peculiar velocities cause distortions which can yield erroneous agreement with hierarchical scaling. The underdensity probability measures the frequency of 'voids' with density rho less than 0.2 -/rho. This statistic reveals a paucity of very bright galaxies (L greater than L asterisk) in the 'voids.' Underdensities are equal to or greater than 2 sigma more frequent in bright galaxy samples than in samples that include fainter galaxies. Comparison of void statistics of CfA samples with simulations of a range of cosmological models favors models with Gaussian primordial fluctuations and Cold Dark Matter (CDM)-like initial power spectra. Biased models tend to produce voids that are too empty. We also compare these data with three specific models of the Cold Dark Matter cosmogony: an unbiased, open universe CDM model (omega = 0.4, h = 0.5) provides a good match to the VPF of the CfA samples. Biasing of the galaxy distribution in the 'standard' CDM model (omega = 1, b = 1.5; see below for definitions) and nonzero cosmological constant CDM model (omega = 0.4, h = 0.6 lambda(sub 0) = 0.6, b = 1.3) produce voids that are too empty. All three simulations match the observed VPF and underdensity probability for samples of very bright (M less than M asterisk = -19.2) galaxies, but produce voids that are too empty when compared with samples that include fainter galaxies.
Measurements of galaxy distributions at large cosmic distances capture clustering from the past. In this study, we use a cosmological model to translate these observations into the present-day galaxy distribution. Specifically, we reconstruct the 3D linear matter power spectrum at redshift z = 0 using Dark Energy Spectroscopic Instrument (DESI) Year 1 (DR1) galaxy clustering data and Cosmic Microwave Background (CMB) observations, assuming the ΛCDM model, and compare it to the result assuming the w 0 w a CDM model. Building on previous state-of-the-art methods, we apply Effective Field Theory (EFT) modelling of the galaxy power spectrum to account for small-scale effects in the 2-point statistics of galaxy data. Implementation of the EFT approach improves the modelling of the galaxy power spectrum, providing a more robust consistency test of the assumed cosmological model. By casting both CMB and galaxy clustering observations, spanning distinct redshift regimes, into k-space, we can identify discrepancies between the datasets of different redshifts, which would indicate potential inaccuracies in the assumed expansion history. While previous studies have shown consistency with ΛCDM, this work extends the analysis with higher-quality data to further test the expansion histories of both ΛCDM and w 0 w a CDM. Our findings show that both ΛCDM and w 0 w a CDM provide consistent fits to the linear matter power spectrum recovered from DESI DR1 data.
We present a simplified treatment for calculating the cosmic microwave background anisotropy power spectrum in adiabatic models. It consists of solving for the evolution of a two-fluid model until the epoch of recombination and then integrating over the sources to obtain the cosmic microwave background (CMB) anisotropy power spectrum. The approximation is useful both for a physical understanding of CMB anisotropies as well as for a quantitative analysis of cosmological models. Comparison with exact calculations shows that the accuracy is typically 10%-20% over a large range of angles and cosmological models, including those with curvature and cosmological constant. Using this approximation we investigate the dependence of the CMB anisotropy on the cosmological parameters. We identify six dimensionless parameters that uniquely determine the anisotropy power spectrum within our approximation. CMB experiments on different angular scales could in principle provide information on all these parameters. In particular, mapping of the Doppler peaks would allow an independent determination of baryon mass density, matter mass density, and the Hubble constant.
In this paper, the properties of a special class of inhomogeneous cosmological models and the interaction of the inhomogeneities with the evolution of the background geometry and matter are studied. The cosmological model is chosen so that the initial inhomogeneities evolve into 'plane' gravitational waves propagating through a smooth Bianchi I dust background. It is shown how the inhomogeneities interact with matter, 3 K radiation, and the background geometry, causing the expansion to slow down in some regions and speed up in others. It is also shown how the gravitational waves can produce a 'dragging of the inertial frame' which will affect the observed distribution of matter and 3 K radiation. In particular, this frame-dragging effect can account for a major fraction of the obsserved dipole component between the 3 K background radiation and the rest frame of global matter, an effect usually assumed to have been produced by large-scale local motion.
Consideration of dissipative processes in anisotropic homogeneous world models, showing that dissipation reduces the anisotropy. The viscosity approximation and its range of applicability is discussed. Examples are presented which have been calculated by the use of a simple approximation to the collision-time method, using the cross section appropriate to weak interaction neutrino scattering. It is found that such dissipation is quite effective except for one particular cosmological model which is axisymmetric and in which the entire expansion of the model is taken up by expansion along the axis. A detailed multicomponent model is developed for dissipative processes in Euclidean homogeneous cosmological models. These processes involve neutrinos which might have long mean free times in interaction with other constituents which are thermalized by electromagnetic interactions, and whose weak interactions produce thermal neutrinos.
The relationship between the observed distribution of discrete sources of a flux limited sample, the luminosity function of these sources, and the cosmological model is discussed. It is stressed that some assumptions about the form and evolution of the luminosity function must be made in order to determine the cosmological parameters from the observed distribution of sources. Presented is a method to test the validity of these assumptions using the observations. It is shown how, using higher moments of the observed distribution, one can determine, independently of the cosmological model, all parameters of the luminosity function except those describing evolution of the density and the luminosity of the luminosity function. These methods are applied to the sample of approximately 1000 galaxies recently used by Loh and Spillar to determine a value of the cosmological density parameter Omega approx = 1. It is shown that the assumptions made by Loh and Spillar about the luminosity function are inconsistent with the data, and that a self-consistent treatment of the data indicates a lower value of Omega approx = 0.2 and a flatter luminosity function. It should be noted, however, that incompleteness in the sample could cause a flattening of the luminosity function and lower the calculated value of Omega and that uncertainty in the values of these parameters due to random fluctuations is large.
The relationship between the observed distribution of discrete sources of a flux limited sample, the luminosity function of these sources, and the cosmological model is discussed. It is stressed that some assumptions about the form and evolution of the luminosity function must be made in order to determine the cosmological parameters from the observed distribution of sources. Presented is a method to test the validity of these assumptions using the observations. It is shown how, using higher moments of the observed distribution, one can determine, independently of the cosmological model, all parameters of the luminosity function except those describing evolution of the density and the luminosity of the luminosity function. These methods are applied to the sample of approximately 1000 galaxies recently used by Loh and Spillar to determine a value of the cosmological density parameter Omega approx = 1. It is shown that the assumptions made by Loh and Spillar about the luminosity function are inconsistent with the data, and that a self-consistent treatment of the data indicates a lower value of Omega approx = 0.2 and a flatter luminosity function. It should be noted, however, that incompleteness in the sample could cause a flattening of the luminosity function and lower the calculated value of Omega and that uncertainty in the values of these parameters due to random fluctuations is large.
The cosmos withholds multiple mysteries such as dark forms of matter and energy that are yet beyond human comprehension. In the standard cosmological model, $\Lambda$CDM, the cosmological constant $\Lambda$ is thought to be responsible for the late accelerated expansion of the Universe. However, recent results from the Dark Energy Spectroscopic Instrument (DESI) suggest the possibility of evolving dark energy, which warrants further exploration. Future surveys such as the Rubin Observatory Legacy Survey of Space and Time (LSST) will map the large-scale structure (LSS) with unprecedented precision, giving us valuable statistical information about the cosmos. The goal of this research is to investigate the potential impact of an evolving dark energy scenario on cosmological parameters constrained by LSS probes, as will be mapped by the LSST. For this, we examine the power spectra of lens galaxies, source galaxies, and cross-power spectra between lens galaxies and source galaxies. The combination of these statistics is commonly referred to as '3 $\times$ 2 points'. For this investigation, we created a set of simulations resembling LSST data and used them to perform cosmological parameter inference in two scenarios: one in which the simulated data is based on the fiducial model and another on evolving dark energy. We then examined the degeneracy between the cosmological parameters and checked for potential shifts in the parametric space when the data contains dynamical dark energy but the modeling assumes $\Lambda$CDM. Our findings indicate that mismodeling the dark energy equation of state can significantly impact parameter inference, particularly affecting the total matter density, $\Omega_m$, and the growth of structures, as represented by the $S_8$ parameter. These results highlight the importance of further exploring extensions of the $\Lambda$CDM model in future LSS studies.
A cosmological gamma-ray burst model that reproduces the observed gamma-ray spectra was developed. This model, which is an outgrowth of work on synchrotron emission from cosmological sources, creates the observed spectra from a power law spectrum through Compton attenuation in dense molecular clouds. It restricts the burst source to the centers of galaxies, and it is easily tested through comparisons with time dependent burst spectra. Dr. Brainerd continued development of a Monte Carlo code that tracks the random walk of a gamma-ray through a plasma in a strong magnetic field and used this code to show that a two temperature plasma in a strong magnetic field can suppress soft x-ray emission.
The Dark Energy Survey (DES) recently released the final results of its two principal probes of the expansion history: Type Ia supernovae (SNe) and baryonic acoustic oscillations (BAO). In this paper, we explore the cosmological implications of these data in combination with external cosmic microwave background (CMB), big bang nucleosynthesis (BBN), and age-of-the-Universe information. The BAO measurement, which is ∼ 2 σ away from Planck ’s Λ CDM predictions, pushes for low values of Ω m compared to Planck, in contrast to SN which prefers a higher value than Planck. We identify several tensions among datasets in the Λ CDM model that cannot be resolved by including either curvature ( k Λ CDM ) or a constant dark energy equation of state ( w CDM ). By combining BAO + SN + CMB despite these mild tensions, we obtain Ω k = - 5.5 - 4.2 + 4.6 × 10 - 3 in k Λ CDM , and w = - 0.94 8 - 0.027 + 0.028 in w CDM . In w CDM , BAO and SN push again in different directions of parameter space, favoring, respectively, w < - 1 and w > - 1 . If we open the parameter space to w 0 w a CDM [where the equation of state of dark energy varies as w ( a ) = w 0 + ( 1 - a ) w a ], all the datasets are mutually more compatible, and we find concordance in the [ w 0 > - 1 , w a < 0 ] quadrant, with BAO pushing for w a < 0 and SN for [ w 0 > - 1 , w a < 0 ] . For DES BAO and SN in combination with Planck -CMB, we find a 3.2 σ deviation from Λ CDM , with w 0 = - 0.67 3 - 0.097 + 0.098 , w a = - 1.3 7 - 0.50 + 0.51 , a Hubble constant of H 0 = 67.8 1 - 0.86 + 0.96 km s - 1 Mpc - 1 , and an abundance of matter of Ω m = 0.310 9 - 0.0099 + 0.0086 . For the combination of all the background cosmological probes considered (including CMB’s angular acoustic scale θ ⋆ ), we still find a deviation of 2.8 σ from Λ CDM in the w 0 - w a plane. Assuming a minimal neutrino mass, this work provides tentative evidence for non- Λ CDM physics, which is consistent with recent claims in support of evolving dark energy, or a source of unknown systematics.
What is the role of clusters of galaxies in probing the large-scale velocity field of the universe? We investigate the distribution of peculiar velocities of clusters of galaxies in the popular low-density (omega = 0.3) flat cold dark matter (CDM) cosmological model, which best fits many large-scale structure observations. An omega = 1 CDM model is also studied for comparison. We find that clusters of galaxies are efficient tracers of the large-scale velocity field. The clusters exhibit a Maxwellian distribution of peculiar velocities, as expected from Gaussian initial density fluctuations. The cluster three-dimensional velocity distribution for the omega = 0.3 model peaks at nu approximately greater than 400 km/s and extends to high velocities of nu approximately 1200 km/s. The rms peculiar velocity of the clusters is 440 km/s. Approximately 10% of all model clusters move with high peculiar velocities nu greater or equal to 700 km/s. The observed velocity distribution of clusters of galaxies is compared with the predictions from cosmological models. The observed data exhibit a larger velocity tail than seen in the model simulations; however, due to the large observational uncertainties, the data are consistent at approximately equal to 3 sigma level with the odel predictions, and with a Gaussian initial density field. The large peculiar velocities reported for some clusters of galaxies (nu approximately greater than 3000 km/s) are likely to be overestimated, if the current model is viable.
Accurate modeling of the inflationary gravitational waves (GWs) requires time-consuming, iterative numerical integrations of differential equations to take into account their backreaction on the expansion history. To improve computational efficiency while preserving accuracy, we present the Stiff-amplified Gravitational-wave Emulator Network (SageNet), a deep learning framework designed to replace conventional numerical solvers (code available at https://github.com/YifangLuo/SageNet). SageNet employs a long short-term memory architecture to emulate the present-day energy density spectrum of the inflationary GWs with possible stiff amplification, Ω GW (f). Trained on a data set of 25,689 numerically generated solutions, SageNet allows accurate reconstructions of Ω GW (f) and generalizes well to a wide range of cosmological parameters; 90.9% of the test emulations with randomly distributed parameters exhibit errors of under 4%. In addition, SageNet demonstrates its ability to learn and reproduce the artificial, adaptive sampling patterns in numerical calculations, which implement denser sampling of frequencies around changes in spectral indices in Ω GW (f). The dual capability of learning both physical and artificial features of the numerical GW spectra establishes SageNet as a robust alternative to exact numerical methods. Finally, our benchmark tests show that SageNet reduces the computation time from tens of seconds to milliseconds, achieving a speedup of ∼10 4 times over standard CPU-based numerical solvers with the potential for further acceleration on GPU hardware. These capabilities make SageNet a powerful tool for accelerating Bayesian inference procedures for extended cosmological models. In a broad sense, the SageNet framework offers a fast, accurate, and generalizable solution to modeling cosmological observables whose theoretical predictions demand costly differential equation solvers.