Spectroscopic Sample Research Articles

J-PLUS: The fraction of calcium white dwarfs along the cooling sequence

Aims. We used the Javalambre Photometric Local Universe Survey (J-PLUS) second data release (DR2) photometry in 12 optical bands over 2176 deg2 to estimate the fraction of white dwarfs with the presence of Ca II H+K absorption along the cooling sequence. Methods. We compared the J-PLUS photometry against metal-free theoretical models to estimate the equivalent width in the J0395 passband of 10 nm centered at 395 nm (EWJ0395), a proxy to detect calcium absorption. A total of 4399 white dwarfs with effective temperatures within 30 000 > Teff > 5500 K and masses of M > 0.45 M⊙ were analyzed. Their EWJ0395 distribution was modeled using two populations, corresponding to polluted and non-polluted systems, to estimate the fraction of calcium white dwarfs (fCa) as a function of Teff. The probability of each individual white dwarf presenting calcium absorption, pCa, was also computed. Results. The comparison of EWJ0395 with both the measured Ca/He abundance and the identification of metal pollution from spectroscopy shows that EWJ0395 correlates with the presence of Ca II H+K absorption. The fraction of calcium white dwarfs changes along the cooling sequence, increasing from fCa ≈ 0 at Teff = 13 500 K to fCa ≈ 0.15 at Teff = 5500 K. This trend reflects the selection function of calcium white dwarfs in the optical. We compare our results with the fractions derived from the 40 pc spectroscopic sample and from Sloan Digital Sky Survey (SDSS) spectra. The trend found in J-PLUS observations is also present in the 40 pc sample; however, SDSS shows a deficit of metal-polluted objects at Teff < 12 000 K. Finally, we found 39 white dwarfs with pCa > 0.99. Twenty of them have spectra presented in previous studies, whereas we obtained follow-up spectroscopic observations for six additional targets. These 26 objects were all confirmed as metal-polluted systems. Conclusions. The J-PLUS optical data provide a robust statistical measurement for the presence of Ca II H+K absorption in white dwarfs. We find a 15 ± 3% increase in the fraction of calcium white dwarfs from Teff = 13 500 K to 5500 K, which reflects their selection function in the optical from the total population of metal-polluted systems.

The mass profiles of dwarf galaxies from Dark Energy Survey lensing

ABSTRACT We present a novel approach to extracting dwarf galaxies from photometric data to measure their average halo mass profile with weak lensing. We characterize their stellar mass and redshift distributions with a spectroscopic calibration sample. By combining the ${\sim} 5000\,\mathrm{deg}^2$ multiband photometry from the Dark Energy Survey and redshifts from the Satellites Around Galactic Analogs Survey with an unsupervised machine learning method, we select a low-mass galaxy sample spanning redshifts $z\lt 0.3$ and divide it into three mass bins. From low to high median mass, the bins contain [146 420, 330 146, 275 028] galaxies and have median stellar masses of $\log _{10}(M_*/\text{M}_\odot)=\left[8.52\substack{+0.57 -0.76},\, 9.02\substack{+0.50 -0.64},\, 9.49\substack{+0.50 -0.58}\right]$ . We measure the stacked excess surface mass density profiles, $\Delta \Sigma (R)$, of these galaxies using galaxy–galaxy lensing with a signal-to-noise ratio of [14, 23, 28]. Through a simulation-based forward-modelling approach, we fit the measurements to constrain the stellar-to-halo mass relation and find the median halo mass of these samples to be $\log _{10}(M_{\rm halo}/\text{M}_\odot)$ = [$10.67\substack{+0.2 -0.4}$, $11.01\substack{+0.14 -0.27}$, $11.40\substack{+0.08 -0.15}$]. The cold dark matter profiles are consistent with NFW (Navarro, Frenk, and White) profiles over scales ${\lesssim} 0.15 \, {h}^{-1}$ Mpc. We find that ${\sim} 20$ per cent of the dwarf galaxy sample are satellites. This is the first measurement of the halo profiles and masses of such a comprehensive, low-mass galaxy sample. The techniques presented here pave the way for extracting and analysing even lower mass dwarf galaxies and for more finely splitting galaxies by their properties with future photometric and spectroscopic survey data.

Reconstructing redshift distributions with photometric galaxy clustering

The accurate determination of the true redshift distributions in tomographic bins is critical for cosmological constraints from photometric surveys. The proposed redshift self-calibration method, which utilizes the photometric galaxy clustering alone, is highly convenient and avoids the challenges from incomplete or unrepresentative spectroscopic samples in external calibration. However, the imperfection of the theoretical approximation on broad bins as well as the flaw of the algorithm in previous work [1] risk the accuracy and application of the method. In this paper, we propose the improved self-calibration algorithm that incorporates novel update rules, which effectively accounts for heteroskedastic weights and noisy data with negative values. The improved algorithm greatly expands the application range of self-calibration method and accurately reconstructs the redshift distributions for various mock data. Using the luminous red galaxy (LRG) sample of the Dark Energy Spectroscopic Instrument (DESI) survey, we find that the reconstructed results are comparable to the state-of-the-art external calibration. This suggests the exciting prospect of using photometric galaxy clustering to reconstruct redshift distributions in the cosmological analysis of survey data.

Euclid preparation

Future data provided by the Euclid mission will allow us to better understand the cosmic history of the Universe. A metric of its performance is the figure-of-merit (FoM) of dark energy, usually estimated with Fisher forecasts. The expected FoM has previously been estimated taking into account the two main probes of Euclid, namely the three-dimensional clustering of the spectroscopic galaxy sample, and the so-called 3×2pt signal from the photometric sample (i.e., the weak lensing signal, the galaxy clustering, and their cross-correlation). So far, these two probes have been treated as independent. In this paper, we introduce a new observable given by the ratio of the (angular) two-point correlation function of galaxies from the two surveys. For identical (normalised) selection functions, this observable is unaffected by sampling noise, and its variance is solely controlled by Poisson noise. We present forecasts for Euclid where this multi-tracer method is applied and is particularly relevant because the two surveys will cover the same area of the sky. This method allows for the exploitation of the combination of the spectroscopic and photometric samples. When the correlation between this new observable and the other probes is not taken into account, a significant gain is obtained in the FoM, as well as in the constraints on other cosmological parameters. The benefit is more pronounced for a commonly investigated modified gravity model, namely the γ parametrisation of the growth factor. However, the correlation between the different probes is found to be significant and hence the actual gain is uncertain. We present various strategies for circumventing this issue and still extract useful information from the new observable.

The PAU survey: photometric redshift estimation in deep wide fields

ABSTRACT We present photometric redshifts (photo-z) for the deep wide fields of the Physics of the Accelerating Universe Survey (PAUS), covering an area of $\sim$50 deg$^{2}$, for $\sim$1.8 million objects up to $i_{\rm {AB}}\lt 23$. The PAUS deep wide fields overlap with the W1 and W3 fields from CFHTLenS and the G09 field from KiDS/GAMA. Photo-z are estimated using the 40 narrow bands (NB) of PAUS and the broad-bands (BB) of CFHTLenS and KiDS. We compute the redshifts with the SED template-fitting code bcnz, with a modification in the calibration technique of the zero-point between the observed and the modelled fluxes, that removes any dependence on spectroscopic redshift samples. We enhance the redshift accuracy by introducing an additional photo-z estimate ($z_{\textrm {b}}$), obtained through the combination of the bcnz and the BB-only photo-z. Comparing with spectroscopic redshift estimates ($z_{\textrm {s}}$), we obtain a $\sigma _{68} \simeq 0.020$ for all galaxies with $i_{\rm {AB}}\lt 23$ and a typical bias $|z_{\textrm {b}}\!-\!z_{\textrm {s}}|$ smaller than 0.01. For $z_{\textrm {b}} \sim (0.10\!-\!0.75)$, we find $\sigma _{68} \simeq (0.003\!-\!0.02)$, this is a factor of $10\!-\!2$ higher accuracy than the corresponding BB-only results. We obtain similar performance when we split the samples into red (passive) and blue (active) galaxies. We validate the redshift probability $p(z)$ obtained by bcnz and compare its performance with that of $z_{\textrm {b}}$. These photo-z catalogues will facilitate important science cases, such as the study of galaxy clustering and intrinsic alignment at high redshifts ($z \lesssim 1$) and faint magnitudes.

From gas to stars: MUSEings on the internal evolution of IC 1613

Context. The kinematics and chemical composition of stellar populations of different ages provide crucial information on the evolution of the various components of a galaxy. Aim. Our aim is to determine the kinematics of individual stars as a function of age in IC 1613, a star-forming, gas-rich, and isolated dwarf galaxy of the Local Group (LG). Methods. We present results of a new spectroscopic survey of IC 1613 conducted with MUSE, an integral field spectrograph mounted on the Very Large Telescope. We extracted ∼2000 sources, from which we separated stellar objects for their subsequent spectral analysis. The quality of the dataset allowed us to obtain accurate classifications (Teff to better than 500 K) and line-of-sight velocities (with average δv ∼ 7 km s−1) for about 800 stars. Our sample includes not only red giant branch (RGB) and main sequence (MS) stars, but also a number of probable Be and C stars. We also obtained reliable metallicities (δ[Fe/H] ∼ 0.25 dex) for about 300 RGB stars. Results. The kinematic analysis of IC 1613 revealed for the first time the presence of stellar rotation with high significance. We found general agreement with the rotation velocity of the neutral gas component. Examining the kinematics of stars as a function of broad age ranges, we find that the velocity dispersion increases as a function of age, with the behaviour being very clear in the outermost pointings, while the rotation-to-velocity dispersion support decreases. On timescales of < 1 Gyr, the stellar kinematics still follow very closely that of the neutral gas, while the two components decouple on longer timescales. The chemical analysis of the RGB stars revealed average properties comparable to other Local Group dwarf galaxies. We also provide a new estimation of the inclination angle using only independent stellar tracers. Conclusions. Our work provides the largest spectroscopic sample of an isolated LG dwarf galaxy. The results obtained seem to support the scenario in which the stars of a dwarf galaxy are born from a less turbulent gas over time.

A Spectral Atlas of Lyα Emitters at z = 5.7 and z = 6.6

We present two uniformly observed spectroscopic samples of Lyα emitters (LAEs; 127 at z = 5.7 and 82 at z = 6.6), which we use to investigate the evolution of the LAE population at these redshifts. The observations cover a large field (44 deg2) in the North Ecliptic Pole, as well as several smaller fields. We have a small number of exotic LAEs in the samples: double-peaked Lyα profiles; very extended red wings; and one impressive lensed LAE cross. We also find three broad-line active galactic nuclei. We compare the Lyα line width measurements at the two redshifts, finding that the lower-luminosity LAEs show a strong evolution of decreasing line width with increasing redshift, while the high-luminosity LAEs do not, with a transition luminosity of log L(Lyα) ≈ 43.25 erg s−1. Thus, at z = 6.6, the high-luminosity LAEs may be producing large ionized bubbles themselves, or they may be residing in overdense galaxy sites that are producing such bubbles. In order to avoid losses in the red wing, the radius of the ionized bubble must be larger than 1 pMpc. The double-peaked LAEs also require transmission on the blue side. For the four at z = 6.6, we use models to estimate the proximity radii, R a , where the ionizing flux of the galaxy is sufficient to make the surroundings have a low enough neutral fraction to pass the blue light. Since the required R a are large, multiple ionizing sources in the vicinity may be needed.

Geographical origin determination of the PDO hazelnut (cv. Giresun Tombul) by chemometric analysis of FT-NIR and Raman spectra acquired from shell and kernel.

Turkey is the leading producer of hazelnuts, contributing to 62% of the total global production. Among 18 distinct local hazelnut cultivars, Giresun Tombul is the only cultivar that has received Protected Designation of Origin denomination from the European Comission (EC). However, there is currently no practical objective method to ensure its geographic origin. Therefore, in this study NIR and Raman spectroscopy, along with chemometric methods, such as principal component analysis, PLS-DA (partial least squares-discriminant analysis), and SVM-C (support vector machine-classification), were used to determine the geographical origin of the Giresun Tombul hazelnut cultivar. For this purpose, samples from unique 118 orchards were collected from eight different regions in Turkey during the 2021 and 2022 growing seasons. NIR and Raman spectra were obtained from both the shell and kernel of each sample. The results indicated that hazelnut samples exhibited distinct grouping tendencies based on growing season regardless of the spectroscopic technique and sample type (shell or kernel). Spectral information obtained from hazelnut shells demonstrated higher discriminative power concerning geographical origin compared to that obtained from hazelnut kernels. The PLS-DA models utilizing FT-NIR (Fourier transform near-infrared) and Raman spectra for hazelnut shells achieved validation accuracies of 81.7% and 88.3%, respectively, while SVM-C models yielded accuracies of 90.9% and 86.3%. It was concluded that the lignocellulosic composition of hazelnut shells, indicative of their geographic origin, can be accurately assessed using FT-NIR and Raman spectroscopy, providing a nondestructive, rapid, and user-friendly method for identifying the geographical origin of Giresun Tombul hazelnuts. PRACTICAL APPLICATION: The proposed spectroscopic methods offer a rapid and nondestructive means for hazelnut value chain actors to verify the geographic origin of Giresun Tombul hazelnuts. This could definitely enhance consumer trust by ensuring product authenticity and potentially help in preventing fraud within the hazelnut market. In addition, these methods can also be used as a reference for future studies targeting the authentication of other shelled nuts.

Euclid preparation

We investigate the accuracy of the perturbative galaxy bias expansion in view of the forthcoming analysis of the Euclid spectroscopic galaxy samples. We compare the performance of a Eulerian galaxy bias expansion using state-of-the-art prescriptions from the effective field theory of large-scale structure (EFTofLSS) with a hybrid approach based on Lagrangian perturbation theory and high-resolution simulations. These models are benchmarked against comoving snapshots of the flagship I N-body simulation at z = (0.9, 1.2, 1.5, 1.8), which have been populated with Hα galaxies leading to catalogues of millions of objects within a volume of about 58 h−3 Gpc3. Our analysis suggests that both models can be used to provide a robust inference of the parameters (h, ωc) in the redshift range under consideration, with comparable constraining power. We additionally determine the range of validity of the EFTofLSS model in terms of scale cuts and model degrees of freedom. From these tests, it emerges that the standard third-order Eulerian bias expansion – which includes local and non-local bias parameters, a matter counter term, and a correction to the shot-noise contribution – can accurately describe the full shape of the real-space galaxy power spectrum up to the maximum wavenumber of kmax = 0.45 h Mpc−1, and with a measurement precision of well below the percentage level. Fixing either of the tidal bias parameters to physically motivated relations still leads to unbiased cosmological constraints, and helps in reducing the severity of projection effects due to the large dimensionality of the model. We finally show how we repeated our analysis assuming a volume that matches the expected footprint of Euclid, but without considering observational effects, such as purity and completeness, showing that we can get constraints on the combination (h, ωc) that are consistent with the fiducial values to better than the 68% confidence interval over this range of scales and redshifts.

The quiescent population at 0.5 ≤ z ≤ 0.9: Environmental impact on the mass–size relation

Context. How the quiescent galaxies evolve with redshift and the factors that impact their evolution are still debated. It is still unclear what the dominant mechanisms of passive galaxy growth are and what role is played by the environment in shaping their evolutionary paths over cosmic time. Aims. The population of quiescent galaxies is altered over time by several processes that can affect their mean properties. Our aim is to study the mass–size relation (MSR) of the quiescent population and to understand how the environment shapes the MSR at intermediate redshift. Methods. We used the VIMOS Public Extragalactic Redshift Survey (VIPERS), a large spectroscopic survey of ∼90 000 galaxies in the redshift range 0.5 ≤ z ≤ 1.2. We selected a mass-complete sample of 4786 passive galaxies based on the NUVrK diagram and refined it using the Dn4000 spectral index to study the MSR of the passive population over 0.5 ≤ z ≤ 0.9. The impact of the environment on the MSR and on the growth of the quiescent population is studied through the density contrast. Results. The slope and the intercept of the MSR, α = 0.62 ± 0.04 and log(A) = 0.52 ± 0.01, agree well with values from the literature at the same redshift. The intercept decreases with redshift, Re(z) = 8.20 × (1 + z)−1.70, while the slope remains roughly constant, and the same trend is observed in the low-density (LD) and high-density (HD) environments. Thanks to the largest spectroscopic sample at 0.5 ≤ z ≤ 0.9, these results are not prone to redshift uncertainties from photometric measurements. We find that the average size of the quiescent population in the LD and HD environments are identical within 3σ and this result is robust against a change in the definition of the LD and HD environments or a change in the selection of quiescent galaxies. In the LD and HD environments, ∼30 and ∼40% of the population have experienced a minor merger process between 0.5 ≤ z ≤ 0.9. However, minor mergers account only for 30–40% of the size evolution in this redshift range, the remaining evolution likely being due to the progenitor bias.

PAC. V. The Roles of Mass and Environment in the Quenching of Galaxies

The roles that mass and environment play in galaxy quenching are still under debate. Leveraging the Photometric objects Around Cosmic webs method, we analyze the excess surface distribution n¯2wp(rp) of photometric galaxies in different colors (rest-frame u − r) within the stellar mass range of 109.0 ∼ 1011.0 M ⊙ around spectroscopic massive central galaxies (1010.9 ∼ 1011.7 M ⊙) at the redshift interval of 0 < z s < 0.7, utilizing data from the Hyper Suprime-Cam Subaru Strategic Program and the spectroscopic samples of Slogan Digital Sky Survey (i.e., Main, LOWZ, and CMASS samples). We find that both mass and environmental quenching contribute to the evolution of companion galaxies. To isolate the environmental effect, we quantify the quenched fraction excess (QFE) of companion galaxies encircling massive central galaxies within 0.01h −1 Mpc < r p < 20h −1 Mpc, representing the surplus quenched fraction relative to the average. We find that the high-density halo environment affects star formation quenching up to about three times the virial radius, and this effect becomes stronger at lower redshift. We also find that even after being scaled by the virial radius, the environmental quenching efficiency is higher for more massive halos or for companion galaxies of higher stellar mass, though the trends are quite weak. We present a fitting formula that comprehensively captures the QFE across central and companion stellar mass bins, halo-centric distance bins, and redshift bins, offering a valuable tool for constraining galaxy formation models. Furthermore, we have made a quantitative comparison with IllustrisTNG that underscores some important differences, particularly in the excessive quenching of low-mass companion galaxies (<109.5 M ⊙) in the simulation.

The Lockman-SpReSO project

Aims. In this work, we carry out a comprehensive study using galaxy data from the Lockman Spectroscopic Redshift Survey using Osiris (Lockman-SpReSO) project, a far-infrared (FIR) selected sample of galaxies observed using optical spectroscopy. We analyse a sub-sample of star-forming galaxies (SFGs) with secure spectroscopic redshifts, mostly in the luminous infrared (IR) galaxy domain. From these galaxies, parameters such as the extinction, star formation rate (SFR), and metallicity have been derived. The present paper examines how these properties evolve in relation to each other and in comparison with low-redshift FIR and non-FIR-selected samples of galaxies. Methods. We applied distinct selection criteria to attain an SFG sample with minimal AGN contamination. Multiple approaches were used to estimate the intrinsic extinction, SFR, and gas-phase metallicity for the SFGs. In conjunction with findings in the literature, we examined the correlation between SFRs and stellar masses (M*), as well as the metallicity evolution depending on M*. Finally, we also studied the 3D relationship between M*, SFR, and metallicity. Results. From the initial spectroscopic sample of 409 FIR-selected objects from the Lockman-SpReSO catalogue, 69 active galactic nuclei (AGNs) were identified and excluded (17%), which is nearly double the percentage found in local studies, leaving us with a sample of 340 SFGs. The analysis of the M*–SFR relationship revealed that Lockman-SpReSO IR-selected SFGs show signs of evolution at redshifts z &gt; 0.4, shifting above the main sequence (MS), with a mean value of ∼0.4 dex. They are located within the starburst galaxy region since 78% of the galaxies fall into this category. In addition, no evident flattening was found in the relation to specific SFR with redshift for log M* (M⊙)≳10.5. In line with the M*–metallicity relation (MZR) outcomes published in previous studies for optically selected SFGs; however, during the analysis of the MZR, it was found that IR-selected SFGs exhibit lower metallicities than the values anticipated on the basis of their M* and redshift. During the investigation of the 3D M*–SFR–metallicity relation (FP), it was established that the research sample is consistent with relations published in the existing literature, with an average scatter of ∼0.2 dex. However, a re-calibration of the FP when using the SFR obtained from the IR luminosity is required and, in this case, no attenuation in the correlation for log M* (M⊙)≳10.5 was observed. This result points to a possible evolution of the more massive fraction of the sample in the sense that the present-day star formation rate is lower with respect to the average rate of star formation in the past.

Euclid: Testing photometric selection of emission-line galaxy targets

Multi-object spectroscopic galaxy surveys typically make use of photometric and colour criteria to select their targets. That is not the case of which will use the NISP slitless spectrograph to record spectra for every source over its field of view. Slitless spectroscopy has the advantage of avoiding defining a priori a specific galaxy sample, but at the price of making the selection function harder to quantify. In its Wide Survey was designed to build robust statistical samples of emission-line galaxies with fluxes brighter than $ 2e-16 erg s cm $, using the Halpha -$ N ii right $ complex to measure redshifts within the range $ $. Given the expected signal-to-noise ratio of NISP spectra, at such faint fluxes a significant contamination by incorrectly measured redshifts is expected, either due to misidentification of other emission lines, or to noise fluctuations mistaken as such, with the consequence of reducing the purity of the final samples. This can be significantly ameliorated by exploiting the extensive photometric information to identify emission-line galaxies over the redshift range of interest. Beyond classical multi-band selections in colour space, machine learning techniques provide novel tools to perform this task. Here, we compare and quantify the performance of six such classification algorithms in achieving this goal. We consider the case when only the photometric and morphological measurements are used, and when these are supplemented by the extensive set of ancillary ground-based photometric data, which are part of the overall scientific strategy to perform lensing tomography. The classifiers are trained and tested on two mock galaxy samples, the EL-COSMOS and Euclid Flagship2 catalogues. The best performance is obtained from either a dense neural network or a support vector classifier, with comparable results in terms of the adopted metrics. When training on on-board photometry alone, these are able to remove $87&lt;!PCT!&gt;$ of the sources that are fainter than the nominal flux limit or lie outside the $0.9&lt;z&lt;1.8$ redshift range, a figure that increases to $97&lt;!PCT!&gt;$ when ground-based photometry is included. These results show how by using the photometric information available to it will be possible to efficiently identify and discard spurious interlopers, allowing us to build robust spectroscopic samples for cosmological investigations.

Dark Energy Survey Deep Field photometric redshift performance and training incompleteness assessment

Context. The determination of accurate photometric redshifts (photo-zs) in large imaging galaxy surveys is key for cosmological studies. One of the most common approaches is machine learning techniques. These methods require a spectroscopic or reference sample to train the algorithms. Attention has to be paid to the quality and properties of these samples since they are key factors in the estimation of reliable photo-zs. Aims. The goal of this work is to calculate the photo-zs for the Year 3 (Y3) Dark Energy Survey (DES) Deep Fields catalogue using the Directional Neighborhood Fitting (DNF) machine learning algorithm. Moreover, we want to develop techniques to assess the incompleteness of the training sample and metrics to study how incompleteness affects the quality of photometric redshifts. Finally, we are interested in comparing the performance obtained by DNF on the Y3 DES Deep Fields catalogue with that of the EAzY template fitting approach. Methods. We emulated – at a brighter magnitude – the training incompleteness with a spectroscopic sample whose redshifts are known to have a measurable view of the problem. We used a principal component analysis to graphically assess the incompleteness and relate it with the performance parameters provided by DNF. Finally, we applied the results on the incompleteness to the photo-z computation on the Y3 DES Deep Fields with DNF and estimated its performance. Results. The photo-zs of the galaxies in the DES deep fields were computed with the DNF algorithm and added to the Y3 DES Deep Fields catalogue. We have developed some techniques to evaluate the performance in the absence of “true” redshift and to assess the completeness. We have studied the tradeoff in the training sample between the highest spectroscopic redshift quality versus completeness. We found some advantages in relaxing the highest-quality spectroscopic redshift requirements at fainter magnitudes in favour of completeness. The results achieved by DNF on the Y3 Deep Fields are competitive with the ones provided by EAzY, showing notable stability at high redshifts. It should be noted that the good results obtained by DNF in the estimation of photo-zs in deep field catalogues make DNF suitable for the future Legacy Survey of Space and Time (LSST) and Euclid data, which will have similar depths to the Y3 DES Deep Fields.

JWST’s First Glimpse of a z > 2 Forming Cluster Reveals a Top-heavy Stellar Mass Function

Clusters and their progenitors (protoclusters) at z ∼ 2 − 4, the peak epoch of star formation, are ideal laboratories to study the formation process of both the clusters themselves and their member galaxies. However, a complete census of their member galaxies has been challenging due to observational difficulties. Here we present new JWST/NIRCam observations targeting the distant cluster CLJ1001 at z = 2.51 from the COSMOS-Web program, which, in combination with previous narrowband imaging targeting Hα emitters and deep millimeter surveys of CO emitters, provide a complete view of massive galaxy assembly in CLJ1001. In particular, JWST reveals a population of massive, extremely red cluster members in the long-wavelength bands that were invisible in previous Hubble Space Telescope (HST)/F160W imaging (HST-dark members). Based on this highly complete spectroscopic sample of member galaxies, we show that the spatial distribution of galaxies in CLJ1001 exhibits a strong central concentration, with the central galaxy density already resembling that of low-z clusters. Moreover, we reveal a “top-heavy” stellar mass function for the star-forming galaxies (SFGs), with an overabundance of massive SFGs piled up in the cluster core. These features strongly suggest that CLJ1001 is caught in a rapid transition, with many of its massive SFGs likely soon becoming quiescent. In the context of cluster formation, these findings suggest that the earliest clusters form from the inside out and top to bottom, with the massive galaxies in the core assembling first, followed by the less massive ones in the outskirts.

Velocity reconstruction in the era of DESI and Rubin/LSST. I. Exploring spectroscopic, photometric, and hybrid samples

Velocity reconstruction in the era of DESI and Rubin/LSST. I. Exploring spectroscopic, photometric, and hybrid samples

Quantitative modelling of type Ia supernovae spectral time series: Constraining the explosion physics

Abstract Multiple explosion mechanisms have been proposed to explain type Ia supernovae (SNe Ia). Empirical modelling tools have also been developed that allow for fast, customised modelling of individual SNe and direct comparisons between observations and explosion model predictions. Such tools have provided useful insights, but the subjective nature with which empirical modelling is performed makes it difficult to obtain robust constraints on the explosion physics or expand studies to large populations of objects. Machine learning accelerated tools have therefore begun to gain traction. In this paper, we present riddler, a framework for automated fitting of SNe Ia spectral sequences up to shortly after maximum light. We train a series of neural networks on realistic ejecta profiles predicted by the W7 and N100 explosion models to emulate full radiative transfer simulations and apply nested sampling to determine the best-fitting model parameters for multiple spectra of a given SN simultaneously. We show that riddler is able to accurately recover the parameters of input spectra and use it to fit observations of two well-studied SNe Ia. We also investigate the impact of different weighting schemes when performing quantitative spectral fitting and show that best-fitting models and parameters are highly dependent on the assumed weighting schemes and priors. As spectroscopic samples of SNe Ia continue to grow, automated spectral fitting tools such as riddler will become increasingly important to maximise the physical constraints that can be gained in a quantitative and consistent manner.

Local primordial non-Gaussianity from the large-scale clustering of photometric DESI luminous red galaxies

ABSTRACT We use angular clustering of luminous red galaxies from the Dark Energy Spectroscopic Instrument (DESI) imaging surveys to constrain the local primordial non-Gaussianity parameter fNL. Our sample comprises over 12 million targets, covering 14 000 deg2 of the sky, with redshifts in the range 0.2 &amp;lt; z &amp;lt; 1.35. We identify Galactic extinction, survey depth, and astronomical seeing as the primary sources of systematic error, and employ linear regression and artificial neural networks to alleviate non-cosmological excess clustering on large scales. Our methods are tested against simulations with and without fNL and systematics, showing superior performance of the neural network treatment. The neural network with a set of nine imaging property maps passes our systematic null test criteria, and is chosen as the fiducial treatment. Assuming the universality relation, we find $f_{\rm NL} = 34^{+24(+50)}_{-44(-73)}$ at 68 per cent (95 per cent) confidence. We apply a series of robustness tests (e.g. cuts on imaging, declination, or scales used) that show consistency in the obtained constraints. We study how the regression method biases the measured angular power spectrum and degrades the fNL constraining power. The use of the nine maps more than doubles the uncertainty compared to using only the three primary maps in the regression. Our results thus motivate the development of more efficient methods that avoid overcorrection, protect large-scale clustering information, and preserve constraining power. Additionally, our results encourage further studies of fNL with DESI spectroscopic samples, where the inclusion of 3D clustering modes should help separate imaging systematics and lessen the degradation in the fNL uncertainty.

Improving Photometric Redshift Estimates with Training Sample Augmentation

Large imaging surveys will rely on photometric redshifts (photo-z's), which are typically estimated through machine-learning methods. Currently planned spectroscopic surveys will not be deep enough to produce a representative training sample for Legacy Survey of Space and Time (LSST), so we seek methods to improve the photo-z estimates that arise from nonrepresentative training samples. Spectroscopic training samples for photo-z's are biased toward redder, brighter galaxies, which also tend to be at lower redshift than the typical galaxy observed by LSST, leading to poor photo-z estimates with outlier fractions nearly 4 times larger than for a representative training sample. In this Letter, we apply the concept of training sample augmentation, where we augment simulated nonrepresentative training samples with simulated galaxies possessing otherwise unrepresented features. When we select simulated galaxies with (g-z) color, i-band magnitude, and redshift outside the range of the original training sample, we are able to reduce the outlier fraction of the photo-z estimates for simulated LSST data by nearly 50% and the normalized median absolute deviation (NMAD) by 56%. When compared to a fully representative training sample, augmentation can recover nearly 70% of the degradation in the outlier fraction and 80% of the degradation in NMAD. Training sample augmentation is a simple and effective way to improve training samples for photo-z's without requiring additional spectroscopic samples.

Increasing the power of weak lensing data with multipole-based intrinsic alignment estimators

Abstract It has long been known that galaxy shapes align coherently with the large-scale density field. Characterizing this effect is essential to interpreting measurements of weak gravitational lensing, the deflection of light from distant galaxies by matter overdensities along the line of sight, as it also produces coherent galaxy alignments that we wish to interpret in terms of a cosmological model. Existing direct measurements of intrinsic alignments using galaxy samples with high-quality shape and redshift measurements typically use well-understood but sub-optimal projected estimators, which do not make good use of the information in the data when comparing those estimators to theoretical models. We demonstrate a more optimal estimator, based on a multipole expansion of the correlation functions or power spectra, for direct measurements of galaxy intrinsic alignments. We show that even using the lowest order multipole alone increases the significance of inferred model parameters using simulated and real data, without any additional modeling complexity. We apply this estimator to measurements of parameters of the non-linear alignment model using data from the Sloan Digital Sky survey, demonstrating consistent results with a factor of ∼2 greater precision in parameter fits to intrinsic alignments models. This result is functionally equivalent to quadrupling the survey area, but without the attendant costs – thereby demonstrating the value in using this new estimator in current and future intrinsic alignments measurements using spectroscopic galaxy samples.