Distribution Of Galaxies Research Articles

Action-based dynamical models of M31-like galaxies

ABSTRACT In this work, we present an action-based dynamical equilibrium model to constrain the phase-space distribution of stars in the stellar halo, present-day dark matter distribution, and the total mass distribution in M31-like galaxies. The model comprises a three-component gravitational potential (stellar bulge, stellar disc, and a dark matter halo), and a double power-law distribution function (DF), $f(\mathbf {J})$, which is a function of actions. A Bayesian model-fitting algorithm was implemented that enabled both parameters of the potential and DF to be explored. After testing the model-fitting algorithm on mock data drawn from the model itself, it was applied to a set of three M31-like haloes from the Auriga simulations (Auriga 21, Auriga 23, and Auriga 24). Furthermore, we tested the equilibrium assumption and the ability of a double power-law DF to represent the stellar halo stars. The model incurs an error in the total enclosed mass of around 10 per cent out to 100 kpc, thus justifying the equilibrium assumption. Furthermore, the double power-law DF used proves to be an appropriate description of the investigated M31-like haloes. The anisotropy profiles of the haloes were also investigated and discussed from a merger history point of view, however, our approach underscores to capture the non-equilibrium anisotropy information of stellar haloes in Auriga models, which is expected.

The conditional colour–magnitude distribution – II. A comparison of galaxy colour and luminosity distribution in galaxy groups

ABSTRACT The Conditional Colour-Magnitude Distribution (CCMD) is a comprehensive formalism of the colour–magnitude–halo mass relation of galaxies. With joint modelling of a large sample of SDSS galaxies in fine bins of galaxy colour and luminosity, Xu et al. inferred parameters of a CCMD model that well reproduces colour- and luminosity-dependent abundance and clustering of present-day galaxies. In this work, we provide a test and investigation of the CCMD model by studying the colour and luminosity distribution of galaxies in galaxy groups. An apples-to-apples comparison of group galaxies is achieved by applying the same galaxy group finder to identify groups from the CCMD galaxy mocks and from the SDSS data, avoiding any systematic effect of group finding and mass assignment on the comparison. We find an overall nice agreement in the conditional luminosity function (CLF), the conditional colour function (CCF), and the CCMD of galaxies in galaxy groups inferred from CCMD mock and SDSS data. We also discuss the subtle differences revealed by the comparison. In addition, using two external catalogues constructed to only include central galaxies with halo mass measured through weak lensing, we find that their colour-magnitude distribution shows two distinct and orthogonal components, in line with the prediction of the CCMD model. Our results suggest that the CCMD model provides a good description of halo mass-dependent galaxy colour and luminosity distribution. The halo and CCMD mock catalogues are made publicly available to facilitate other investigations.

Galaxies, gas flows and metallicities

Abstract In his 2024 Presidential Address, Mike Edmunds reviews attempts to uncover how element distributions in galaxies evolve

Dark Matter Distribution in Milky Way analog Galaxies

Our current understanding of how dark matter (DM) is distributed within the Milky Way (MW) halo, particularly in the solar neighborhood, is based on either careful studies of the local stellar orbits, model assumptions on the global shape of the MW halo, or from direct acceleration measurements. In this work, we undertake a study of external galaxies, with the intent of providing insight into the DM distribution in MW-analog galaxies. For this, we carefully select a sample of galaxies similar to the MW, based on maximum atomic hydrogen (H i) rotational velocity ( vmax,HI=200–280 km s−1) and morphological type (Sab–Sbc) criteria. With a need for deep, highly resolved H i, our resulting sample is composed of five galaxies from the VLA Imaging of Virgo in Atomic Gas (VIVA) survey and The H i Nearby Galaxy Survey (THINGS). To perform our baryonic analysis, we use deep mid-IR images at 3.6 and 4.5 μm from the Spitzer Survey of Stellar Structures in Galaxies (S4G). Based on the dynamical three-dimensional modeling software 3D-Based Analysis of Rotating Objects via Line Observations (3D-BAROLO), we construct rotation curves (RCs) and derive the gas and stellar contributions from the galaxy's gaseous and stellar disks' mass surface density profiles. Through a careful decomposition of their RCs into their baryonic (stars, gas) and DM components, we isolate the DM contribution by using a Markov Chain Monte Carlo-based approach. Based on the Sun's location and the MW’s R 25, we define the corresponding location of the solar neighborhood in these systems. We put forward a window for the DM density (ρ dm = 0.21–0.55 GeV cm−3) at these galactocentric distances in our MW analog sample, consistent with the values found for the MW’s local DM density, based on more traditional approaches found in the literature.

Peering into cosmic reionization: Lyα visibility evolution from galaxies at z = 4.5–8.5 with JWST

The resonant scattering interaction between Lyα photons and neutral hydrogen implies that a partially neutral intergalactic medium has the ability to significantly impact the detectability of Lyα emission in galaxies. Thus, the redshift evolution of the Lyα equivalent width distribution of galaxies offers a key observational probe of the degree of ionization during the Epoch of Reionization (EoR). Previous in-depth investigations at z ≥ 7 were limited by ground-based instrument capabilities. We present an extensive study of the evolution of Lyα emission from galaxies at 4.5 < z < 8.5, observed as part of the CEERS and JADES surveys in the JWST NIRSpec/PRISM configuration. The sample consists of 235 galaxies in the redshift range of 4.1 < z < 9.9. We identified 65 of them as Lyα emitters. We first measured the Lyα escape fractions from Lyα to Balmer line flux ratios and explored the correlations with the inferred galaxies’ physical properties, which are similar to those found at lower redshift. We also investigated the possible connection between the escape of Lyα photons and the inferred escape fractions of LyC photons obtained from indirect indicators, finding no secure correlation. We then analyzed the redshift evolution of the Lyα emitter fraction, finding lower average values at z = 5 and 6 compared to previous ground-based observations. At z = 7, the GOODS-S results are aligned with previous findings, whereas the visibility in the EGS field appears to be enhanced. This discrepancy in Lyα visibility between the two fields could potentially be attributed to the presence of early reionized regions in the EGS. Such a broad variance is also expected in the Cosmic Dawn II radiation-hydrodynamical simulation. The average Lyα emitter fraction obtained from the CEERS+JADES data continues to increase from z = 5 to 7, ultimately declining at z = 8. This suggests a scenario in which the ending phase of the EoR is characterized by ∼1 pMpc ionized bubbles around a high fraction of moderately bright galaxies. Finally, we characterize such two ionized regions found in the EGS at z = 7.18 and z = 7.49 by estimating the radius of the ionized bubble that each of the spectroscopically-confirmed members could have created.

Debiasing with Diffusion: Probabilistic Reconstruction of Dark Matter Fields from Galaxies with CAMELS

Galaxies are biased tracers of the underlying cosmic web, which is dominated by dark matter (DM) components that cannot be directly observed. Galaxy formation simulations can be used to study the relationship between DM density fields and galaxy distributions. However, this relationship can be sensitive to assumptions in cosmology and astrophysical processes embedded in galaxy formation models, which remain uncertain in many aspects. In this work, we develop a diffusion generative model to reconstruct DM fields from galaxies. The diffusion model is trained on the CAMELS simulation suite that contains thousands of state-of-the-art galaxy formation simulations with varying cosmological parameters and subgrid astrophysics. We demonstrate that the diffusion model can predict the unbiased posterior distribution of the underlying DM fields from the given stellar density fields while being able to marginalize over uncertainties in cosmological and astrophysical models. Interestingly, the model generalizes to simulation volumes ≈500 times larger than those it was trained on and across different galaxy formation models. The code for reproducing these results can be found at https://github.com/victoriaono/variational-diffusion-cdm ✎.

No Catch-22 for fuzzy dark matter: testing substructure counts and core sizes via high-resolution cosmological simulations

ABSTRACT Fuzzy dark matter (FDM) has recently emerged as an interesting alternative model to the standard cold dark matter (CDM). In this model, dark matter consists of very light bosonic particles with wave-like behaviour on galactic scales. Using the N-body code ax-gadget, we perform cosmological simulations of FDM that fully model the dynamical effects of the quantum potential throughout cosmic evolution. Through the combined analysis of FDM volume and high-resolution zoom-in simulations of different FDM particle masses ($m_{\chi }$$\sim$$10^{-23}\!-\!10^{-21}$ eV c−2), we study how FDM impacts the abundance of substructure and the inner density profiles of dark matter haloes. For the first time, using our FDM volume simulations, we provide a fitting formula for the FDM-to-CDM subhalo abundance ratio as a function of the FDM mass. More importantly, our simulations clearly demonstrate that there exists an extended FDM particle mass interval able to reproduce the observed substructure counts and, at the same time, create substantial cores ($r_{c} \sim 1$ kpc) in the density profile of dwarf galaxies ($\approx 10^{9}\!-\!10^{10}$ M$_{\odot }$), which stands in stark contrast with CDM predictions even with baryonic effects taken into account. The dark matter distribution in the faintest galaxies offers then a clear way to discriminate between FDM and CDM.

Spin parity of spiral galaxies. IV. Differential reddening of globular cluster systems of nearby spiral galaxies

Abstract The north-west side of the disk of M 31 is known as the near side because of the differential reddening of globular clusters found from their photographic photometry. This paper reports a simple geometric model to evaluate the visibility of the effect and its application to published CCD photometry on globular cluster systems of three spiral galaxies, M 31, M 33, and NGC 253. The color difference of globular cluster systems due to differential reddening was confirmed for M 31 and NGC 253; however, the data for M 33 were insufficient. The analysis reaffirms the currently adopted interpretation that the side on the minor axis of the galactic disk, where more conspicuous dust features and interstellar reddening are visible, is the nearer side to us and provides an additional basis for using spiral galaxies with identified spiral windings, S-wise or Z-wise, to study the large-scale spin distribution of galaxies in the universe.

Estimation of line-of-sight velocities of individual galaxies using neural networks – I. Modelling redshift–space distortions at large scales

ABSTRACT We present a scheme based on artificial neural networks (ANNs) to estimate the line-of-sight velocities of individual galaxies from an observed redshift–space galaxy distribution. We find an estimate of the peculiar velocity at a galaxy based on galaxy counts and barycentres in shells around it. By training the network with environmental characteristics, such as the total mass and mass centre within each shell surrounding every galaxy in redshift space, our ANN model can accurately predict the line-of-sight velocity of each individual galaxy. When this velocity is used to eliminate the RSD effect, the two-point correlation function (TPCF) in real space can be recovered with an accuracy better than 1 per cent at s > 8 $\, h^{-1}\, \mathrm{Mpc}$, and 4 per cent on all scales compared to ground truth. The real-space power spectrum can be recovered within 3 per cent on k< 0.5 $\, \mathrm{Mpc}^{-1}\, h$, and less than 5 per cent for all k modes. The quadrupole moment of the TPCF or power spectrum is almost zero down to s = 10 $\, h^{-1}\, \mathrm{Mpc}$ or all k modes, indicating an effective correction of the spatial anisotropy caused by the RSD effect. We demonstrate that on large scales, without additional training with new data, our network is adaptable to different galaxy formation models, different cosmological models, and mock galaxy samples at high-redshifts and high biases, achieving less than 10 per cent error for scales greater than 15 $\, h^{-1}\, \mathrm{Mpc}$. As it is sensitive to large-scale densities, it does not manage to remove Fingers of God in large clusters, but works remarkably well at recovering real-space galaxy positions elsewhere. Our scheme provides a novel way to predict the peculiar velocity of individual galaxies, to eliminate the RSD effect directly in future large galaxy surveys, and to reconstruct the three-dimensional cosmic velocity field accurately.

A catalogue of merging clusters of galaxies: cluster partners, merging subclusters, and post-collision clusters

ABSTRACT Clusters of galaxies are merging during the formation of large-scale structures in the Universe. Based on optical survey data, we identify a large sample of pre-mergers of galaxy clusters and merging subclusters in rich clusters. We find 39 382 partners within a velocity difference of 1500 km s$^{-1}$ and a projected separation of 5 $r_{500}$ around 33 126 main clusters, where $r_{500}$ is the radius of the main cluster. Based on the galaxy distribution inside rich clusters with more than 30 member galaxy candidates, we identify subclusters by modelling the smoothed optical distribution with a two-component profile, and a coupling factor is obtained for merging subclusters in 7845 clusters. In addition, we find 3446 post-collision mergers according to the deviations of brightest cluster galaxies from other member galaxies, most of which have been partially validated by using the Chandra and XMM–Newton X-ray images. Two new bullet-like clusters have been identified by using the optical and X-ray images. The large samples of merging clusters of galaxies presented here are important databases for studying the hierarchical structure formation, cluster evolution, and the physics of intergalactic medium.

Detecting relativistic Doppler in galaxy clustering with tailored galaxy samples

We present a method to obtain a high-significance detection of relativistic effects on cosmological scales. Measurements of such effects would be instrumental for our understanding of the Universe, as they would provide a further confirmation of the validity of general relativity as the correct description of the gravitational interaction, in a regime very far from that of strong gravity, where it has been tested to exquisite accuracy. Despite its relevance, the detection of relativistic effects has hitherto eluded us, mainly because they are stronger on the largest cosmic scales, plagued by cosmic variance. Our work focuses on the cosmological probe of galaxy clustering, describing the excess probability of finding pairs of galaxies at a given separation due to them being part of the same underlying cosmic large-scale structure. We focus on the two-point correlation function of the distribution of galaxies in Fourier space — the power spectrum — where relativistic effects appear as an imaginary contribution to the real power spectrum. By carefully tailoring cuts in magnitude/luminosity, we are able to obtain two samples (bright and faint) of the same galaxy population, whose cross-correlation power spectrum allows for a detection of the relativistic contribution. In particular, we optimise the definition of the samples to maximise the detection significance of the relativistic Doppler term for both a low-z Bright Galaxy Sample and a high-z Hα emission line galaxy population.

Anisotropies in the spatial distribution and kinematics of dwarf galaxies in the Local Group and beyond

ABSTRACT The mass distribution in the Local Group (LG), dominated by the Andromeda (M31) and Milky Way (MW) pair, is highly anisotropic. We use the APOSTLE simulations to examine how this anisotropy manifests on the spatial distribution and kinematics of dwarf galaxies out to a distance of $d_{\rm MW}\sim 3$ Mpc from the MW. The simulations indicate a preference for dwarfs to be located near the axis defined by the MW-M31 direction, even for dwarfs in the LG periphery (LGP; i.e. at distances $1.25\ \lt\ d_{\rm MW}/$Mpc $\lt\ 3$). The ‘Hubble flow’ in the periphery is also affected; at fixed $d_{\rm MW}$ the mean recession speed, $\langle V_{\rm rad} \rangle$, varies with angular distance to M31, peaking in the anti-M31 direction and reaching a minimum behind M31. The M31-MW mass decelerates the local expansion; the LG ‘turnaround radius’ (i.e. where $\langle V_{\rm rad} \rangle =0$) in APOSTLE is at $r \sim 1.25$ Mpc from the LG barycentre and the pure Hubble flow (where $\langle V_{\rm rad} \rangle \sim H_0*d$) is reached beyond $r\sim 3$ Mpc. The predicted flow is very cold, with a barycentric dispersion of $\lt 40$ km s−1. Comparing these predictions with observations yields mixed results. There is little evidence for a preferred alignment of dwarfs along the MW-M31 direction, but some evidence for an angular anisotropy in $\langle V_{\rm rad} \rangle$. Although the ‘coldness’ of the Hubble flow is consistent with the simulations, it is less decelerated: relative to the MW all galaxies beyond $d_{\rm MW} \sim 1.25$ Mpc seem to be already on a pure Hubble flow. We argue that these oddities may result at least partly from incompleteness and inhomogeneous sky coverage in our current inventory of nearby dwarfs.

Galaxies’ properties in the Fundamental Plane across time

Context. Using the Illustris-1 and IllustrisTNG-100 simulations, we investigate the properties of the Fundamental Plane (FP), which is the correlation between the effective radius Re, the effective surface intensity Ie, and the central stellar velocity dispersion σ of galaxies, at different cosmic epochs. Aims. Our aim is to study the properties of galaxies in the FP and its projections across time, adopting samples covering different intervals of mass. We would like to demonstrate that the position of a galaxy in the FP space strongly depends on its degree of evolution, which might be represented by the β and $ L^\prime_0 $ parameters entering the L = $ L^\prime_0 $ (t)σβ(t) law. Methods. Starting from the comparison of the basic relations among the structural parameters of artificial and real galaxies at low redshift, we obtain the fit of the FP and its coefficients at different cosmic epochs for samples of different mass limits. Then, we analyze the dependence of the galaxy position in the FP space as a function of the β parameter and the star formation rate (SFR). Results. We find that: (1) the coefficients of the FP change with the mass range of the galaxy sample; (2) the low luminous and less massive galaxies do not share the same FP of the bright massive galaxies; (3) the scatter around the fitted FP is quite small at any epoch and increases when the mass interval increases; (4) the distribution of galaxies in the FP space strongly depends on the β values (i.e., on the degree of virialization and the star formation rate). Conclusions. The FP is a complex surface that is well approximated by a plane only when galaxies share similar masses and condition of virialization.

CLASS-OneLoop: accurate and unbiased inference from spectroscopic galaxy surveys

The power spectrum is the most commonly applied summary statistics to extract cosmological information from the observed three-dimensional distribution of galaxies in spectroscopic surveys. We present CLASS-OneLoop, a new numerical tool, fully integrated into the Boltzmann code CLASS, enabling the calculation of the one-loop power spectrum of biased tracers in spectroscopic surveys. Built upon the Eulerian moment expansion framework for redshift-space distortions, the implemented model incorporates a complete set of nonlinear biases, counterterms, and stochastic contributions, and includes the infrared resummation and the Alcock-Paczynski effect. The code features an evaluation of the loops by either direct numerical integration or Fast Fourier Transform, and employs a fast-slow parameter decomposition, which is essential for accelerating MCMC runs. After presenting performance and validation tests, as an illustration of the capabilities of the code, we apply it to fit the measured redshift-space halo power spectrum wedges on a ΛCDM subset of the AbacusSummit simulation suite and considering scales up to kmax = 0.3 h/Mpc. We find that the one-loop model adeptly recovers the fiducial cosmology of the simulation, while a simplified model commonly used in the literature for sensitivity forecasts yields significantly biased results. Furthermore, we conduct Monte Carlo Markov Chain (MCMC) forecasts for a DESI-like survey, considering a model with a dynamical dark energy component. Our results demonstrate the ability to independently constrain cosmological and nuisance parameters, even in the presence of a large parameter space with twenty-nine variables.

Neutrino Mass Constraint from an Implicit Likelihood Analysis of BOSS Voids

Cosmic voids identified in the spatial distribution of galaxies provide complementary information to two-point statistics. In particular, constraints on the neutrino mass sum, ∑m ν , promise to benefit from the inclusion of void statistics. We perform inference on the CMASS Northern Galactic Cap sample of the third-generation Sloan Digital Sky Survey/Baryon Oscillation Spectroscopic Survey (BOSS) with the aim of constraining ∑m ν . We utilize the void size function, the void–galaxy cross power spectrum, and the galaxy auto power spectrum. To extract constraints from these summary statistics we use a simulation-based approach, specifically implicit likelihood inference. We populate approximate gravity-only, particle-neutrino cosmological simulations with an expressive halo occupation distribution model. With a conservative scale cut of kmax=0.15hMpc−1 and a Planck-inspired Lambda cold dark matter prior, we find upper bounds on ∑m ν of 0.43 and 0.35 eV from the galaxy auto power spectrum and the full data vector, respectively (95% credible interval). Relaxing the scale cut to kmax=0.2hMpc−1 , we find 0.28 and 0.32 eV. Generally, void statistics appear to add modest but nonzero information beyond the auto power spectrum. We also substantiate the usual assumption that the void size function is Poisson distributed.

The hierarchical cosmic web and assembly bias

Accurate modeling of galaxy distributions is paramount for cosmological analysis using galaxy redshift surveys. However, this endeavor is often hindered by the computational complexity of resolving the dark matter halos that host these galaxies. To address this challenge, we propose the development of effective assembly bias models down to small scales, i.e., going beyond the local density dependence capturing non-local cosmic evolution. We introduce a hierarchical cosmic web classification that indirectly captures up to third-order long- and short-range non-local bias terms. This classification system also enables us to maintain positive definite parametric bias expansions. Specifically, we subdivide the traditional cosmic web classification, which is based on the eigenvalues of the tidal field tensor, with an additional classification based on the Hessian matrix of the negative density contrast. We obtain the large-scale dark matter field on a mesh with ~3.9 h -1 Mpc cell side resolution through Augmented Lagrangian Perturbation Theory. To assess the effectiveness of our model, we conduct tests using a reference halo catalogue extracted from the UNIT project simulation, which was run within a cubical volume of 1 h -1 Gpc side. The resulting mock halo catalogs, generated through our approach, exhibit a high level of accuracy in terms of the one-, two- and three-point statistics. They reproduce the reference power-spectrum within better than 2 percent accuracy up to wavenumbers k ~ 0.8 h Mpc-1 and provide accurate bispectra within the scales that are crucial for cosmological analysis. This effective bias approach provides a forward model appropriate for field-level cosmological inference and holds significant potential for facilitating cosmological analysis of galaxy redshift surveys, particularly in the context of projects such as DESI, EUCLID, and LSST.

Galaxy Group Ellipticity Confirms a Younger Cosmos

We present an analysis of the ellipticities of galaxy groups, derived from the spatial distribution of member galaxies, revealing a notable incongruity between the observed local galaxy groups and their counterparts in the Lambda cold dark matter cosmology. Specifically, our investigation reveals a substantial disparity in the ellipticities of observed groups with masses 1013.0<Mh<1014.5M⊙h−1 exhibiting significantly higher ellipticities (at a confidence level of approximately 4σ) compared to their simulated counterparts. Notably, the consistent use of the same group finder for identifying galaxy groups in both observational and simulated datasets underscores the robustness of this result. This observation may imply a potential incongruence between the inferred age of the Universe from observations and the predictions of the model, which aligns with the younger Universe hypothesis suggested by the elevated fraction of observed satellite pairs with correlated line-of-sight relative velocities compared to simulations. Our findings significantly strengthen the plausibility of a younger age for our Universe.

Measuring the substructure mass power spectrum of 23 SLACS strong galaxy–galaxy lenses with convolutional neural networks

ABSTRACT Strong gravitational lensing can be used as a tool for constraining the substructure in the mass distribution of galaxies. In this study we investigate the power spectrum of dark matter perturbations in a population of 23 Hubble Space Telescope images of strong galaxy–galaxy lenses selected from The Sloan Lens ACS (SLACS) survey. We model the dark matter substructure as a Gaussian random field perturbation on a smooth lens mass potential, characterized by power-law statistics. We expand upon the previously developed machine learning framework to predict the power-law statistics by using a convolutional neural network (CNN) that accounts for both epistemic and aleatoric uncertainties. For the training sets, we use the smooth lens mass potentials and reconstructed source galaxies that have been previously modelled through traditional fits of analytical and shapelet profiles as a starting point. We train three CNNs with different training set: the first using standard data augmentation on the best-fitting reconstructed sources, the second using different reconstructed sources spaced throughout the posterior distribution, and the third using a combination of the two data sets. We apply the trained CNNs to the SLACS data and find agreement in their predictions. Our results suggest a significant substructure perturbation favouring a high frequency power spectrum across our lens population.

Strong lensing of tidal disruption events: Detection rates in imaging surveys

Tidal disruption events (TDEs) are multi-messenger transients in which a star is tidally destroyed by a supermassive black hole at the center of galaxies. The Rubin Observatory Legacy Survey of Space and Time (LSST) is anticipated to detect hundreds to thousands of TDEs annually, such that the first gravitationally lensed TDE may be observed in the coming years. Using Monte-Carlo simulations, we quantify the rate of both unlensed and lensed TDEs as a function of limiting magnitudes in four different optical bands ($u$, $g$, $r$, and $i$) for a range of TDE temperatures that match observations. Dependent on the temperature and luminosity model, we find that $g$ and $r$ bands are the most promising bands with unlensed TDE detections that can be as high as $ sim $ annually. By populating a cosmic volume with realistic distributions of TDEs and galaxies that can act as gravitational lenses, we estimate that a few lensed TDEs (depending on the TDE luminosity model) can be detected annually in $g$ or $r$ bands in the LSST survey, with TDE redshifts in the range of $ sim 0.5$ to $ sim 2$. The ratio of lensed to unlensed detections indicates that we may detect $ sim 1$ lensed event for every $10^ $ unlensed events, which is independent of the luminosity model. The number of lensed TDEs decreases as a function of the image separations and time delays, and most of the lensed TDE systems are expected to have image separations below $ sim and time delays within sim 30$ days. At fainter limiting magnitudes, the $i$ band becomes notably more successful. These results suggest that strongly lensed TDEs are likely to be observed within the coming years and such detections will enable us to study the demographics of black holes at higher redshifts through the lensing magnifications. Our simulated catalogs of lensed TDEs are publicly available.

On Dark Matter and Dark Energy in CCC+TL Cosmology

Relaxing the temporal constancy constraint on coupling constants in an expanding universe results in Friedmann equations containing terms that may be interpreted as dark energy and dark matter. When tired light (TL) was considered to complement the redshift due to the expanding universe, the resulting covarying coupling constants (CCC+TL) model not only fit the Type Ia supernovae data as precisely as the ΛCDM model, but also resolved concerns about the angular size of cosmic dawn galaxies observed by the James Webb Space Telescope. The model was recently shown to be compliant with the baryon acoustic oscillation features in the galaxy distribution and the cosmic microwave background (CMB). This paper demonstrates that dark energy and dark matter of the standard ΛCDM model are not arbitrary but can be derived from the CCC approach based on Dirac’s 1937 hypothesis. The energy densities associated with dark matter and dark energy turn out to be about the same in the ΛCDM and the CCC+TL models. However, the critical density in the new model can only account for the baryonic matter in the universe, raising concerns about how to account for observations requiring dark matter. We therefore analyze some key parameters of structure formation and show how they are affected in the absence of dark matter in the CCC+TL scenario. It requires reconsidering alternatives to dark matter to explain observations on gravitationally bound structures. The model’s consistency with the CMB power spectrum, BBN element abundances, and other critical observations is yet to be established.