Redshift Range Research Articles

Early Results from GLASS-JWST. XXV. Electron Density in the Interstellar Medium at 0.7 ≲ z ≲ 9.3 with NIRSpec High-resolution Spectroscopy**Based on observations acquired by the JWST under the ERS program ID 1324 (PI: T. Treu).

Abstract The electron density (n e) of the interstellar medium (ISM) in star-forming galaxies is intimately linked to star formation and ionization condition. Using the high-resolution spectra obtained from the JWST Near-Infrared Spectrograph (NIRSpec) microshutter assembly (MSA) as part of the GLASS-JWST program, we have assembled the largest sample to date (34 galaxies) with individual n e measurements derived from the [O ii] λλ3726, 29 and/or [S ii] λλ6718, 32 doublets at 0.7 ≲ z ≲ 9.3. The gravitational lensing magnification by the foreground A2744 cluster allows us to probe n e in galaxies with stellar masses (M *) down to ≃107.5 M ⊙ across the entire redshift range. Our analysis reveals that the [O ii] flux ratios are marginally anticorrelated with a specific star formation rate (sSFR) within a 1σ confidence interval, whereas the [S ii] flux ratios show no significant correlation with sSFR. Despite a clear correlation between sSFR and redshift within our sample, we find no apparent redshift evolution of n e at z ≃ 1–9. Our data set also includes 13 galaxies where n e can be measured from both [O ii] and [S ii]. Contrary to findings at lower redshifts, we observe considerable scatter in n e measurements from [O ii] and [S ii], indicating a complex gaseous environment with significant variations in n e in high-redshift galaxies. This work highlights the unique capability of JWST NIRSpec/MSA high-resolution spectroscopy to characterize the detailed physical properties of the ISM in individual high-redshift galaxies.

The spectrometer development of CosmoCube, lunar orbiting satellite to detect 21-cm hydrogen signal from cosmic dark ages

Abstract The cosmic Dark Ages represent a pivotal epoch in the evolution of the Universe, marked by the emergence of the first cosmic structures under the influence of dark matter. The 21-cm hydrogen line, emanating from the hyperfine transition of neutral hydrogen, serves as a critical probe into this era. We describe the development and implementation of the spectrometer for CosmoCube, a novel lunar orbiting CubeSat designed to detect the redshifted 21-cm signal within the redshift range of 13 to 150. Our instrumentation utilizes a Xilinx Radio Frequency System-on-Chip (RFSoC), which integrates both Analog-to-Digital Converters (ADCs) and Digital-to-Analog Converters (DACs), tailored for the spectrometer component of the radiometer. This system is characterized by a 4096 FFT length at 62.5 kHz steps using a Polyphase Filter Bank (PFB), achieving an average Effective Number of Bits (ENOB) of 11.5 bits throughout the frequency of interest, from 10 MHz to 100 MHz. The spectrometer design is further refined through loopback tests involving both DAC and ADC of the RFSoC, with DAC outputs varying between high (+1 dBm) and low (-3 dBm) power modes to characterize system performance. The power consumption was optimized to 5.45 W using three ADCs and one DAC for the radiometer. Additionally, the stability of the ADC noise floor was investigated in a thermal chamber with environmental temperatures ranging from 5○C to 40○C. A consistent noise floor of approximately -152.5 dBFS/Hz was measured, with a variation of ±0.2 dB, ensuring robust performance under varying thermal conditions.

Psi-GAN: a power-spectrum-informed generative adversarial network for the emulation of large-scale structure maps across cosmologies and redshifts

ABSTRACT Simulations of the dark matter distribution throughout the Universe are essential in order to analyse data from cosmological surveys. N-body simulations are computationally expensive, and many cheaper alternatives (such as lognormal random fields) fail to reproduce accurate statistics of the smaller, non-linear scales. In this work, we present Psi-GAN (power-spectrum-informed generative adversarial network), a machine learning model that takes a two-dimensional lognormal dark matter density field and transforms it into a more realistic field. We construct Psi-GAN so that it is continuously conditional, and can therefore generate realistic realizations of the dark matter density field across a range of cosmologies and redshifts in $z \in [0, 3]$. We train Psi-GAN as a generative adversarial network on $2\, 000$ simulation boxes from the Quijote simulation suite. We use a novel critic architecture that utilizes the power spectrum as the basis for discrimination between real and generated samples. Psi-GAN shows agreement with N-body simulations over a range of redshifts and cosmologies, consistently outperforming the lognormal approximation on all tests of non-linear structure, such as being able to reproduce both the power spectrum up to wavenumbers of $1~h~\mathrm{Mpc}^{-1}$, and the bispectra of target N-body simulations to within ${\sim }5$ per cent. Our improved ability to model non-linear structure should allow more robust constraints on cosmological parameters when used in techniques such as simulation-based inference.

Large-scale dual AGN in large-scale cosmological hydrodynamical simulations

Abstract Detecting dual active galactic nuclei (DAGN) in observations and understanding theoretically which massive black holes (MBHs) compose them and in which galactic and large-scale environment they reside are becoming increasingly important questions as we enter the multi-messenger era of MBH astronomy. This paper presents the abundance and properties of DAGN produced in nine large-scale cosmological hydrodynamical simulations. We focus on DAGN powered by AGN with $L_{\rm bol}\geqslant 10^{43}\, \rm erg\, s^{-1}$ and belonging to distinct galaxies, i.e. pairs that can be characterised with current and near-future electromagnetic observations. We find that the number density of DAGN separated by a few to 30 proper kpc varies from 10−8 (or none) to $10^{-3} \, \rm comoving\, Mpc^{3}$ in the redshift range z = 0–7. At a given redshift, the densities of the DAGN numbers vary by up to two orders of magnitude from one simulation to another. However, for all simulations, the DAGN peak is in the range z = 1–3, right before the peak of cosmic star formation or cosmic AGN activity. The corresponding fractions of DAGN (with respect to the total number of AGN) range from 0 to 6 %. We find that simulations could produce too few DAGN at z = 0 (or merge pairs too quickly) compared to current observational constraints while being consistent with preliminary constraints at high redshift (z ∼ 3). Next-generation observatories (e.g., AXIS) will be of paramount importance to detect DAGN across cosmic times. We predict the detectability of DAGN with future X-ray telescopes and discuss DAGN as progenitors for future LISA gravitational wave detections.

The kinematics of massive high-redshift dusty star-forming galaxies

Abstract We present a new method for modelling the kinematics of galaxies from interferometric observations by performing the optimization of the kinematic model parameters directly in visibility-space instead of the conventional approach of fitting velocity fields produced with the clean algorithm in real-space. We demonstrate our method on ALMA observations of 12CO (2−1), (3−2) or (4−3) emission lines from an initial sample of 30 massive 850 $\mu$m-selected dusty star-forming galaxies with far-infrared luminosities ≳ 1012 L⊙ in the redshift range z ∼ 1.2–4.7. Using the results from our modelling analysis for the 12 of the 20 sources with the highest signal-to-noise emission lines that show disk-like kinematics, we conclude the following: (i) Our sample prefers a CO-to-H2 conversion factor, of αCO = 0.74 ± 0.37; (ii) These far-infrared luminous galaxies follow a similar Tully–Fisher relation between the circular velocity, Vcirc, and baryonic mass, Mb, as less strongly star-forming samples at high redshift, but extend this relation to much higher masses – showing that these are some of the most massive disk-like galaxies in the Universe; (iii) Finally, we demonstrate support for an evolutionary link between massive high-redshift dusty star-forming galaxies and the formation of local early-type galaxies using the both the distributions of the baryonic and kinematic masses of these two populations on the Mb – σ plane and their relative space densities.

The redshift dependence of the inferred H0 in a local void solution to the Hubble tension

Abstract Galaxy number counts suggest that we are located within the Gpc-scale KBC void. The Hubble tension might arise due to gravitationally driven outflow from this void, as explored in detail by Haslbauer et al. We explore how the impact of the void on redshift decays at large distances. We define H0(z) as the present expansion rate H0 that would be inferred from observations in a narrow redshift range centred on z. We find H0(z) in three different ways, all of which give similar results. We then compare these results with the observations of Jia et al., who were careful to minimise the impact of correlations between H0 measurements from data in different redshift bins. We find reasonable agreement with their results for the Gaussian and Exponential void underdensity profiles, although the agreement is less good in the Maxwell-Boltzmann case. The latter profile causes severe disagreement with the observed bulk flow curve at z < 0.1 (Mazurenko et al.), so the tension with higher redshift data further highlights that the deepest part of the KBC void is probably near its centre. The observations show a decline of H0(z) towards the background Planck value in qualitative agreement with the considered models, even if we use a larger void. The good overall agreement with the recent results of Jia et al. suggests that the local supervoid evident from the galaxy luminosity density out to a Gpc might also solve the Hubble tension while retaining a low background H0 consistent with Planck data, assuming enhanced structure formation on >100 Mpc scales.

Neural network emulator to constrain the high-z IGM thermal state from Lyman-α forest flux autocorrelation function

ABSTRACT We present a neural network emulator to constrain the thermal parameters of the intergalactic medium (IGM) at $5.4 \le z \le 6.0$ using the Lyman-$\alpha$ (Ly $\alpha$) forest flux autocorrelation function. Our autodifferentiable JAX-based framework accelerates the surrogate model generation process using approximately 100 sparsely sampled Nyx hydrodynamical simulations with varying combinations of thermal parameters, i.e. the temperature at mean density $T_0$, the slope of the temperature–density relation $\gamma$, and the mean transmission flux $\langle F \rangle$. We show that this emulator has a typical accuracy of 1.0 per cent across the specified redshift range. Bayesian inference of the IGM thermal parameters, incorporating emulator uncertainty propagation, is further expedited using NumPyro Hamiltonian Monte Carlo. We compare both the inference results and computational cost of our framework with the traditional nearest-neighbour interpolation approach applied to the same set of mock Ly $\alpha$ flux. By examining the credibility contours of the marginalized posteriors for $T_0, \gamma , \text{and}~\langle F \rangle$ obtained using the emulator, the statistical reliability of measurements is established through inference on 100 realistic mock data sets of the autocorrelation function.

Testing consistency of cosmological parameters in spatially flat ΛCDM model from observational data in different redshift regions

The Hubble tension has become the most significant crisis in modern cosmology, suggesting that the [Formula: see text]CDM model may not accurately describe cosmic evolution. In this paper, we test the spatially flat [Formula: see text]CDM model by comparing constraints on cosmological parameters from observational data across different redshift regions. Utilizing Pantheon[Formula: see text] SN Ia sample, cosmic chronometer data, and baryon acoustic oscillation data, we derive six distinct sets of constraints within the redshift range [Formula: see text]. At the first three and the last redshift points, the observed values of the present matter density parameter, [Formula: see text], are consistent with those from the full dataset within [Formula: see text] confidence level (CL), whereas values at [Formula: see text] and [Formula: see text] are not, and the maximum deviation occurring at [Formula: see text] reaches [Formula: see text]. The data indicate a decreasing trend in the Hubble constant, [Formula: see text], and the SN Ia absolute magnitude, M, with increasing redshift. Despite the variation of both [Formula: see text] and [Formula: see text] across different redshifts, the values of [Formula: see text] remain consistent within [Formula: see text] CL across all regions.

Predicting HCN, HCO^+, multitransition CO, and dust emission of star-forming galaxies. Extension to luminous infrared galaxies and the role of cosmic-ray ionization

The specific star formation rate of star-forming main sequence galaxies significantly decreased since $z 1.5$ because the molecular gas fraction and star formation efficiency decreased. The gas velocity dispersion decreased within the same redshift range and is apparently correlated with the star formation efficiency (inverse of the molecular gas depletion time). However, the radio--infrared (IR) correlation has not changed significantly since $z 1.5$. The theory of turbulent clumpy star-forming gas disks together with the scaling relations of the interstellar medium describes the large- and small-scale properties of galactic gas disks. We extend our previous work on the IR multitransition molecular line, and radio continuum emission of local and high-z star-forming and starburst galaxies to local and $z 0.5$ luminous IR galaxies. The model reproduces the IR luminosities, CO, HCN, and HCO$^+$ line luminosities, and the CO spectral line energy distributions of these galaxies. We derived CO(1-0) and HCN(1-0) conversion factors for all galaxy samples. The relation between the star formation rate per unit area and the H$_2$ surface density cannot be fit simply for all redshifts. The star formation efficiency, the product of the gas turbulent velocity dispersion, and the angular velocity of the galaxies are tightly correlated. Galaxies with lower stellar masses can in principle compensate their gas consumption via star formation by radial viscous gas accretion. The limiting stellar mass increases with redshift. The radio continuum emission is directly proportional to the density of cosmic-ray (CR) electrons, but the molecular line emission depends on the CR ionization rate via the gas chemistry. The normalization of the CR ionization rate we found for the different galaxy samples is higher by about a factor of three to five than the normalization for the solar neighborhood. This means that the mean yield of low-energy CR particles for a given star formation rate per unit area is higher by about three to ten times in external galaxies than was observed by Voyager I.

Reionization relics in the cross-correlation between the Lyα forest and 21 cm intensity mapping in the post-reionization era

Abstract The tumultuous effects of ultraviolet photons that source cosmic reionization, the subsequent compression and shock-heating of low-density regions, and the modulation of baryons in shallow potential wells induced by the passage of ionization fronts, collectively introduce perturbations to the evolution of the intergalactic medium in the post-reionization era. These enduring fluctuations persist deep into the post-reionization era, casting a challenge upon precision cosmology endeavors targeting tracers in this cosmic era. Simultaneously, these relics from reionization also present a unique opportunity to glean insights into the astrophysics that govern the epoch of reionization. In this work, we propose a first study of the cross-correlation of Lyα forest and 21 cm intensity mapping, accounting for the repercussions of inhomogeneous reionization in the post-reionization era. We investigate the ability of SKA × DESI-like, SKA × MUST-like, and PUMA × MUST-like instrumental setups to achieve a high signal-to-noise ratio (SNR) in the redshift range 3.5 ≤ z ≤ 4. Moreover, we assess how alterations in integration time, survey area, and reionization scenarios impact the SNR. Furthermore, we forecast the cross-correlation’s potential to constrain cosmological parameters under varying assumptions: considering or disregarding reionization relics, marginalizing over reionization astrophysics, and assuming perfect knowledge of reionization. Notably, our findings underscore the remarkable capability of a futuristic PUMA × MUST-like setup, with a modest 100-hour integration time over a 100 sq. deg. survey, to constrain the ionization efficiency error to σζ = 3.42.

Galaxy morphologies revealed with Subaru HSC and super-resolution techniques. II. Environmental dependence of galaxy mergers at z ∼ 2–5

Abstract We super-resolve the seeing-limited Subaru Hyper Suprime-Cam (HSC) images for 32187 galaxies at $z\sim 2$–5 using three techniques, namely, the classical Richardson–Lucy (RL) point spread function (PSF) deconvolution, sparse modeling, and generative adversarial networks, to investigate the environmental dependence of galaxy mergers. These three techniques generate overall similar high spatial resolution images but with some slight differences in galaxy structures; for example, more residual noises are seen in the classical RL PSF deconvolution. To alleviate the disadvantages of each technique, we create combined images by averaging over the three types of super-resolution images, resulting in galaxy substructures resembling those seen in the Hubble Space Telescope images. Using the combined super-resolution images, we measure the relative galaxy major merger fraction corrected for the chance projection effect, $f_{\rm merger}^{\rm rel,col}$, for galaxies in the $\sim$300 deg$^2$ area data of the HSC Strategic Survey Program and the CFHT Large Area U-band Survey. Our $f_{\rm merger}^{\rm rel,col}$ measurements at $z\sim 3$ validate previous findings showing that $f_{\rm merger}^{\rm rel,col}$ is higher in regions with a higher galaxy overdensity $\delta$ at $z\sim 2$–3. Thanks to the large galaxy sample, we identify a nearly linear increase in $f_{\rm merger}^{\rm rel,col}$ with increasing $\delta$ at $z\sim 4$–5, providing the highest-z observational evidence that galaxy mergers are related to $\delta$. In addition to our $f_{\rm merger}^{\rm rel,col}$ measurements, we find that the galaxy merger fractions in the literature also broadly align with the linear $f_{\rm merger}^{\rm rel,col}$–$\delta$ relation across a wide redshift range of $z\sim 2$–5. This alignment suggests that the linear $f_{\rm merger}^{\rm rel,col}$–$\delta$ relation can serve as a valuable tool for quantitatively estimating the contributions of galaxy mergers to various environmental dependences. This super-resolution analysis can be readily applied to datasets from wide field-of-view space telescopes such as Euclid and Roman.

Morphologies of galaxies within voids

Among the largest structures in which matter is distributed in the Universe, we find cosmic voids, which are large, under-dense regions almost devoid of galaxies. The study of these structures and the galaxies that inhabit them, the void galaxies, provides key information for understanding galaxy evolution. In this work we investigate the effects of the environment on the evolution of void galaxies. In particular, we study their morphology and explore its dependence on the location within the void where the galaxies reside, as well as on the properties of the void, such as its size and the galaxy number density. The sample of void galaxies that we use in this study is based on the catalogue of cosmic voids and void galaxies in the Sloan Digital Sky Survey Data Release 7 (SDSS-DR7). As we are interested in studying the morphology of void galaxies, we select galaxies in the redshift range of 0.005\,leq \,z\,leq \,0.080, and use the public galaxy morphologies of the SDSS sample together with deep learning algorithms to divide the sample into early- and late-type void galaxies. We analyse the fractions of galaxies of each morphological type as a function of the void-centric distance, the size of the voids, and the density of galaxies in each void. There is a higher abundance of late-type galaxies with respect to early-type galaxies within voids, which remains nearly constant from the inner to the outer part of the voids. We do not find any dependence of the fraction of early- and late-type galaxies on void size or on the number-density of galaxies in the voids. Galaxies in voids follow the morphology--density relation, in the sense that the majority of the galaxies in voids (the most under-dense large-scale environments) are late-type galaxies. However, we find no difference between voids with lower or higher volume number-density of galaxies: the fractions of early- and late-type galaxies do not depend on the density of the voids. The physical processes responsible for the evolution from late towards earlier types (such as external environmental quenching) are not sufficiently effective in voids or are so slow (internal secular quenching) that their contributions do not appear in the morphology--density relation.

Euclid and KiDS-1000: Quantifying the impact of source-lens clustering on cosmic shear analyses

Cosmic shear is a powerful probe of cosmological models and the transition from current Stage-III surveys such as the Kilo-Degree Survey (KiDS) to the increased area and redshift range of Stage IV surveys such as will significantly increase the precision of weak lensing analyses. However, with increasing precision, the accuracy of model assumptions needs to be evaluated. In this study, we quantify the impact of the correlated clustering of weak lensing source galaxies with the surrounding large-scale structure, known as source-lens clustering (SLC), which is commonly neglected. We include the impact of realistic scatter in photometric redshift estimates, which impacts the assignment of galaxies to tomographic bins and increases the SLC . For this, we use simulated cosmological datasets with realistically distributed galaxies and measure shear correlation functions for both clustered and uniformly distributed source galaxies. Cosmological analyses are performed for both scenarios to quantify the impact of SLC on parameter inference for a KiDS-like and a setting. We find for Stage III surveys such as KiDS, SLC has a minor impact when accounting for nuisance parameters for intrinsic alignments and shifts of tomographic bins, as these nuisance parameters absorb the effect of SLC, thus changing their original meaning. For KiDS ( the inferred intrinsic alignment amplitude $A_ IA $ changes from $0.11_ $) for data without SLC to $0.28_ $) with SLC. However, fixed nuisance parameters lead to shifts in $S_8$ and $ m $, emphasizing the need for including SLC in the modelling. For we find that $ m $, and $w_0$ are shifted by 0.19, 0.12, and 0.12 sigma , respectively when including free nuisance parameters and by 0.20, 0.16, and 0.32 sigma when fixing the nuisance parameters. Consequently, SLC on its own has only a small impact on the inferred parameter inference when using uninformative priors for nuisance parameters. However, SLC might conspire with the breakdown of other modelling assumptions, such as magnification bias or source obscuration, which could collectively exert a more pronounced effect on inferred parameters.

The Star-forming Main Sequence in JADES and CEERS at z > 1.4: Investigating the Burstiness of Star Formation

We have used public JWST/NIRSpec and JWST/NIRCam observations from the CEERS and JADES surveys in order to analyze the star-forming main sequence (SFMS) over the redshift range 1.4 ≤ z < 7. We calculate the star formation rates (SFRs) of the galaxy sample using three approaches: Balmer line luminosity, spectral energy distribution (SED) fitting, and UV luminosity. We find a larger degree of scatter about the SFMS using the Balmer-based SFRs compared to the UV-based SFRs. Because these SFR indicators are sensitive to star formation on different timescales, the difference in scatter may be evidence of bursty star formation histories in the early Universe. We additionally compare the Hα-to-UV luminosity ratio (L(Hα)/ν L ν,1600) for individual galaxies in the sample and find that 29%–52% of the ratios across the sample are poorly described by predictions from a smooth star formation history. Measuring the burstiness of star formation in the early Universe has multiple significant implications, such as deriving accurate physical parameters from SED fitting, explaining the evolution of the UV luminosity function, and providing constraints for subgrid models of feedback in simulations of galaxy formation and evolution.

Dark Matter Halos of Luminous Active Galactic Nuclei from Galaxy–Galaxy Lensing with the HSC Subaru Strategic Program

We assess the dark matter halo masses of luminous active galactic nuclei (AGNs) over the redshift range 0.2–1.2 using galaxy–galaxy lensing based on imaging data from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). We measure the weak lensing signal of a sample of 48,907 AGNs constructed using HSC and Wide-field Infrared Survey Explorer photometry. As expected, we find that the lensing mass profile of total AGN sample is consistent with that of massive galaxies ( log(M*/h−2M⊙)∼ 10.61). Surprisingly, the lensing signal remains unchanged when the AGN sample is split into four host galaxy stellar mass bins. Specifically, we find that the excess surface density of AGNs residing in galaxies with high stellar masses significantly differs from that of the control sample. We further fit a halo occupation distribution model to the data to infer the posterior distribution of parameters including the average halo mass. We find that the characteristic halo mass of the full AGN population lies near the knee ( log(Mh/h−1M⊙)=12.0 ) of the stellar-to-halo mass relation (SHMR). Illustrative of the results given above, the halo masses of AGNs residing in host galaxies with high stellar masses (i.e., above the knee of the SHMR) fall below the calibrated SHMR while the halo masses of the low stellar mass sample are more consistent with the established SHMR. These results indicate that massive halos with a higher clustering bias tend to suppress AGN activity, probably due to the lack of available gas.

Distinguishing coupled dark energy models with neural networks

Aims. We investigate whether neural networks (NNs) can accurately differentiate between growth-rate data of the large-scale structure (LSS) of the Universe simulated via two models: a cosmological constant and Λ cold dark matter (CDM) model and a tomographic coupled dark energy (CDE) model. Methods. We built an NN classifier and tested its accuracy in distinguishing between cosmological models. For our dataset, we generated fσ8(z) growth-rate observables that simulate a realistic Stage IV galaxy survey-like setup for both ΛCDM and a tomographic CDE model for various values of the model parameters. We then optimised and trained our NN with Optuna, aiming to avoid overfitting and to maximise the accuracy of the trained model. We conducted our analysis for both a binary classification, comparing between ΛCDM and a CDE model where only one tomographic coupling bin is activated, and a multi-class classification scenario where all the models are combined. Results. For the case of binary classification, we find that our NN can confidently (with &gt; 86% accuracy) detect non-zero values of the tomographic coupling regardless of the redshift range at which coupling is activated and, at a 100% confidence level, detect the ΛCDM model. For the multi-class classification task, we find that the NN performs adequately well at distinguishing ΛCDM, a CDE model with low-redshift coupling, and a model with high-redshift coupling, with 99%, 79%, and 84% accuracy, respectively. Conclusions. By leveraging the power of machine learning, our pipeline can be a useful tool for analysing growth-rate data and maximising the potential of current surveys to probe for deviations from general relativity.

Optimizing redshift distribution inference through joint self-calibration and clustering-redshift synergy

Context. Accurately characterizing the true redshift (true-z) distribution of a photometric redshift (photo-z) sample is critical for cosmological analyses in imaging surveys. Clustering-based techniques, which include clustering-redshift (CZ) and self-calibration (SC) methods–depending on whether external spectroscopic data are used–offer powerful tools for this purpose. Aims. In this study, we explore the joint inference of the true-z distribution by combining SC and CZ (denoted as SC+CZ). Methods. We derived simple multiplicative update rules to perform the joint inference. By incorporating appropriate error weighting and an additional weighting function, our method shows significant improvement over previous algorithms. We validated our approach using a DES Y3 mock catalog. Results. The true-z distribution estimated through the combined SC+CZ method is generally more accurate than using SC or CZ alone. To account for the different constraining powers of these methods, we assigned distinct weights to the SC and CZ contributions. The optimal weights, which minimize the distribution error, depend on the relative constraining strength of the SC and CZ data. Specifically, for a spectroscopic redshift sample that amounts to 1% of the photo-z sample, the optimal combination reduces the total error by 20% (40%) compared to using CZ (SC) alone, and it keeps the bias in mean redshift [Δ͞z/(1+z)] at the level of 0.003. Furthermore, when CZ data are only available in the low-z range and the high-z range relies solely on SC data, SC+CZ enables consistent estimation of the true-z distribution across the entire redshift range. Conclusions. Our findings demonstrate that SC+CZ is an effective tool for constraining the true-z distribution, paving the way for clustering-based methods to be applied at z ≳ 1.

A Systematic Search for Rapid Transients in the Subaru HSC-SSP Transient Survey

Recent high-cadence transient surveys have discovered rapid transients whose light-curve timescales are shorter than those of typical supernovae (SNe). In this paper, we present a systematic search for rapid transients at medium-high redshifts among 3381 SNe candidates obtained from the Hyper Suprime-Cam Subaru Strategic Program transient survey. We developed a machine learning classifier to classify the SN candidates into four types (Type Ia, Ibc, II SNe and rapid transients) based on the features derived from the light curves. By applying this classifier to the 3381 SN candidates and by further applying the quality cut, we selected 14 rapid transient samples. They are located at a wide range of redshifts (0.34 ≤ z ≤ 1.85) and show a wide range of the peak absolute magnitude (−17 ≥ M ≥ −22). The event rate of the rapid transients is estimated to be ∼6 × 103 events yr−1 Gpc−3 at z ∼ 0.74, which corresponds to about 2% of the event rate of normal core-collapse SNe at a similar redshift. Based on the luminosity and color evolution, we selected two candidates of Type Ibn SNe at z ∼ 0.75. The event rate of Type Ibn SN candidates is more than 1% of Type Ib SN rate at the same redshift, suggesting that this fraction of massive stars at this redshift range eruptively ejects their He-rich envelope just before the explosions. Also, two objects at z = 1.37 and 1.85 show high luminosities comparable to superluminous SNe. Their event rate is about 10%–25% of superluminous SNe at z ∼ 2.

The Excess of JWST Bright Galaxies: A Possible Origin in the Ground State of Dynamical Dark Energy in the Light of DESI 2024 Data

Recent observations by JWST yield a large abundance of luminous galaxies at z ≳ 10 compared to that expected in the ΛCDM scenario based on extrapolations of the star formation efficiency measured at lower redshifts. While several astrophysical processes can be responsible for such observations, here we explore to what extent such an effect can be rooted in the assumed dark energy (DE) sector of the current cosmological model. This is motivated by recent results from different cosmological probes combined with the last data release of the Dark Energy Spectroscopic Instrument, which indicate a tension in the DE sector of the concordance ΛCDM model. We have considered the effect of assuming a DE characterized by a negative Λ as the ground state of a quintessence field on the galaxy luminosity function at high redshifts. We find that such models naturally affect the galaxy UV luminosities in the redshift range 10 ≲ z ≲ 15 needed to match the JWST observations, and with the value of ΩΛ = [−0.6, −0.3] remarkably consistent with that required by independent cosmological probes. A sharp prediction of such models is the steep decline of the abundance of bright galaxies in the redshift range 15 ≲ z ≲ 16.

The impact of baryons on the internal structure of dark matter haloes from dwarf galaxies to superclusters in the redshift range 0 &amp;lt; z &amp;lt; 7

ABSTRACT We investigate the redshift evolution of the concentration–mass relationship of dark matter haloes in state-of-the-art cosmological hydrodynamic simulations and their dark-matter-only (DMO) counterparts. By combining the IllustrisTNG suite and the novel MillenniumTNG simulation, our analysis encompasses a wide range of box size ($50{-}740 \: \rm cMpc$) and mass resolution ($8.5 \times 10^4 {-} 3.1 \times 10^7 \: \rm {\rm M}_{\odot }$ per baryonic mass element). This enables us to study the impact of baryons on the concentration–mass relationship in the redshift interval $0\lt z\lt 7$ over an unprecedented halo mass range, extending from dwarf galaxies to superclusters ($\sim 10^{9.5}{-}10^{15.5} \, \rm {\rm M}_{\odot }$). We find that the presence of baryons increases the steepness of the concentration–mass relationship at higher redshift, and demonstrate that this is driven by adiabatic contraction of the profile, due to gas accretion at early times, which promotes star formation in the inner regions of haloes. At lower redshift, when the effects of feedback start to become important, baryons decrease the concentration of haloes below the mass scale $\sim 10^{11.5} \, \rm {\rm M}_{\odot }$. Through a rigorous information criterion test, we show that broken power-law models accurately represent the redshift evolution of the concentration–mass relationship, and of the relative difference in the total mass of haloes induced by the presence of baryons. We provide the best-fitting parameters of our empirical formulae, enabling their application to models that mimic baryonic effects in DMO simulations over six decades in halo mass in the redshift range $0\lt z\lt 7$.