arXiv subjects

R. Dupke

Publications and source records attributed to R. Dupke.

At least 19 recordsLinked to original sources

arXiv2026

J-PAS & FLAMINGO: Cosmic voids and void galaxies in the gravitational landscape of photometric surveys

Photometric surveys offer a powerful way to map the large-scale structure of the Universe, but their redshift errors complicate the identification of cosmic voids, challenging studies of their environmental effect on galaxy properties. We present an approach to robustly identify dynamically relevant voids and void galaxies in galaxy mocks of the Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS), testing whether known trends in void galaxy properties survive photometric redshift errors. Using FLAMINGO mocks at z = 0.3 and mi < 20, we compare a FLAMINGO-based ideal (FBI) mock to a FLAMINGO-based JP mock with J-PAS-like redshift errors. We mitigate redshift errors using a quasi-gravitational potential field in the two galaxy mocks. We apply a watershed algorithm to the thresholded quasi-potential field to identify dynamically dominant voids, and define massive void galaxies alongside a comparison sample in high-density regions. Photometric errors lead to a slightly lower void abundance and a marginal shift toward larger, less spherical voids, but overall size and ellipticity distributions agree well between mocks. Their main impact is contamination of void interiors in the JP density profiles by galaxies scattered from high-density regions. We recover a reasonable number of FBI sample voids in the JP sample, with excellent size and shape agreement, occupying ~63% of the thresholded quasi-potential volume. In both mocks, void galaxies show lower stellar masses, bluer colours, and enhanced star formation relative to equal-mass galaxies in high-density regions. These results suggest a quasi-potential can mitigate redshift errors at the level expected for J-PAS, enabling identification of reliable, dynamically dominant voids that are less sensitive to small-scale noise. The massive void galaxy population shows the expected trends relative to high-density environments.

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arXiv2025

J-PAS: First Identification, Physical Properties and Ionization Efficiency of Extreme Emission Line Galaxies

Extreme emission line galaxies (EELGs) are key tracers of intense star formation and potential analogues of the sources that reionized the early Universe. Their low-redshift counterparts offer a unique opportunity to study the physical conditions that enable high ionizing-photon escape fractions. We present a robust method to photometrically identify EELGs in the J-PAS survey, which provides 56 optical bands over 8500 deg^2. Using data from a fully observed 30 deg^2 region, we combine narrow-band equivalent widths with machine-learning techniques to select galaxies with emission lines above 300 {\AA}. The method achieves 95% purity and 96% completeness for $i_\mathrm{SDSS}<22.5$ mag. We identify 917 EELGs up to $z=0.8$; spectroscopic cross-matching with DESI/DR1 confirms the reliability of our redshifts and emission-line measurements. The selected galaxies show strong correlations between $\xi_\mathrm{ion}$ and EW([OIII]), consistent with previous low- and high-z studies. Most sources exceed the ionizing efficiency threshold required for reionization, reinforcing their role as local analogues of early-Universe galaxies.

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arXiv2025

J-PAS: A value-added catalogue of optical line intensities for nebular emission galaxies (JOLINES)

We present the value-added catalogue JOLINES (J-PAS optical line intensities for nebular emission galaxies), which provides emission-line fluxes in galaxies at from the spectrophotometric catalogues of miniJPAS, J-NEP and the J-PAS early data release (EDR). This catalogue will be updated with future data releases, offering a growing resource for the study of emission-line galaxies. To obtain reliable emission-line fluxes from narrow-band photometry, we employed spectral energy distribution (SED) fitting using CIGALE, a robust tool that reconstructs the continuum emission and ensures accurate flux measurements. This method effectively mitigates uncertainties associated with direct continuum subtraction techniques, and systematics such as absorption components in the emission lines. We validate our approach using simulated observations of galaxy spectra with added noise, testing the method's performance across different equivalent width (EW) regimes and emission-line strengths. Additionally, we compare the recovered emission-line fluxes with spectroscopic measurements from the Sloan Digital Sky Survey (SDSS) and the Dark Energy Spectroscopic Instrument (DESI). Our results show a tight correlation between photometric and spectroscopic fluxes, particularly for bright emission lines, with a typical dispersion of $\sim$0.3 dex. Reliable fluxes are obtained for emission lines with EW $\gtrsim20\, \rm{\mathring{A}}$, in agreement with previous empirical studies. The current catalogue comprises approximately 13,900 sources with reliable flux measurements in the H$\alpha$+[NII] complex and 7,200 in [OIII]$\lambda 5007$, ensuring statistically robust samples for the brightest optical emission lines. This resource will be expanded in future J-PAS releases, facilitating large-scale studies of star formation, AGN activity, and galaxy evolution.

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arXiv2025

J-PAS: A Neural Network Approach to Single Stellar Population Characterization

J-PAS (Javalambre Physics of the Accelerating Universe Astrophysical Survey) will present a groundbreaking photometric survey covering 8500 deg$^2$ of the visible sky from Javalambre, capturing data in 56 narrow band filters. This survey promises to revolutionize galaxy evolution studies by observing $\sim$10$^8$ galaxies with low spectral resolution. A crucial aspect of this analysis involves predicting stellar population parameters from the observed galaxy photometry. In this study, we combine the exquisite J-PAS photometry with state-of-the-art single stellar population (SSP) libraries to accurately predict stellar age, metallicity, and dust attenuation with a neural network (NN) model. The NN is trained on synthetic J-PAS photometry from different SSP librares (E-MILES, Charlot & Bruzual, XSL), to enhance the robustness of our predictions against individual SSP model variations and limitations. To create mock samples with varying observed magnitudes we add artificial noise in the form of random Gaussian variations within typical observational uncertainties in each band. Our results indicate that the NN can accurately estimate stellar parameters for SSP models without evident degeneracies, surpassing a bayesian SED-fitting method on the same test set. We obtain median bias, scatter and percentage of outliers $\mu$ = (0.01 dex, 0.00 dex, 0.00 mag), $\sigma_{NMAD}$ = (0.23 dex, 0.29 dex, 0.04 mag), f$_{o}$ = (17 %, 24 %, 1 %) at $ i \sim$17 mag for age, metallicity and dust attenuation, respectively. The accuracy of the predictions is highly dependent on the signal-to-noise (S/N) ratio of the photometry, achieving robust predictions up to $i$ $\sim$ 20 mag.

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arXiv2025

J-PAS: Discovery of RaJav, a bright spatially extended Ly$\alpha$ Nebula at z=2.25

We report the discovery of a massive and potentially largest Ly$\alpha$ Nebula, RaJav, at z=2.25, associated with a quasar pair: the bright SDSS~J162029.07+433451.1 (hereafter J1620+4334) and the faint newly discovered quasar JPAS-9600-10844, at 2.265 $\pm$ 0.021 using the early data release (17 deg$^{2}$) of the J-PAS. The quasar JPAS-9600-10844 embedded in the nebula is located at ~ 60.2 kpc (7.3'') from J1620+4334, and shows a compact structure with broad emission lines (> 3000 km/s), typical of active galactic nuclei. At a 2$\sigma$ surface brightness (SB) contour of $\sim 1.86 \times 10^{-16}$ erg s$^{-1}$ cm$^{-2}$ arcsec$^{-2}$, the nebula extends > 100 kpcs and has a total Ly$\alpha$ luminosity of $\sim 5.8 \pm 0.7 \times 10^{44}$ erg s$^{-1}$ signify the presence of a giant Enormous Ly$\alpha$ Nebula (ELAN). The nebula traces an over density of quasars at redshift of 2.2-2.3 consistent with the progenitor of a massive galaxy cluster. The extended CIV emission indicates that the circum-galactic medium (CGM) is metal-enriched and not primordial. The current J-PAS observations suggest photoionization and shocks due to outflows as possible ionization mechanisms. The faint extended FUV and NUV continuum emission likely points to ongoing star formation around the two quasars, suggesting a complex interaction in their environments. These findings provide new insights into the environment of quasars and their role in shaping the dynamics and evolution of the CGM at cosmic noon. Further spectroscopic observations will be required to fully characterize the object's nature and its kinematic properties. This study demonstrates the unique capability of J-PAS to detect massive and rare Ly$\alpha$ nebulae, providing new insights into their properties, environments, and connections to large-scale structures in the cosmic web such as filaments and overdensities in a large cosmological volume.

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arXiv2025

The J-PAS survey: The effect of photometric redshift errors on cosmic voids

We investigated the impact of photometric redshift errors in the ongoing Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS) on void identification and properties using a watershed-based method, aiming to assess the recovery of individual voids and the overall void environment. We created galaxy mock catalogues for redshift z = 0.1 using the IllustrisTNG300-1 simulation, defining two datasets: an $ideal$ sample ($m_r < 21$ mag) and a $perturbed$ sample with the Z-coordinate errors mimicking J-PAS's line-of-sight errors, derived from the precursor miniJPAS survey data. We identified voids using ZOBOV, a watershed algorithm. We found 1065 voids in the $ideal$ sample and 2558 voids in the $perturbed$ sample. The $perturbed$ sample voids have, on average, smaller sizes and denser interiors. We filtered out voids based on density and radius in order to eliminate overdense and small spurious instances. The stacked density profile of filtered voids in the $perturbed$ sample remains close to the average density even at the boundary peak, indicating a strong blurring of structures by the redshift errors. The number of $ideal$ sample voids for which at least $50\%$ of the volume is recovered by a void in the $perturbed$ sample is 53 (29 for the filtered sample). The volume occupied by these voids is less than $10\%$ of the simulation volume. Merging voids in the $perturbed$ sample marginally improves the recovery. The overall volumes defined as voids in the two samples have an overlap of $80\%$, making up $61\%$ of the simulation box volume. While some statistical properties of voids might be recovered sufficiently well, the watershed algorithms may not be optimal for recovering the large-scale structure voids if applied straight to photometric redshift survey data.

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arXiv2024

The J-PLUS collaboration. Additive versus multiplicative systematics in surveys of the large scale structure of the Universe

Observational and/or astrophysical systematics modulating the observed number of luminous tracers can constitute a major limitation in the cosmological exploitation of surveys of the large scale structure of the universe. Part of this limitation arises on top of our ignorance on how such systematics actually impact the observed galaxy/quasar fields. In this work we develop a generic, hybrid model for an arbitrary number of systematics that may modulate observations in both an additive and a multiplicative way, after applying a nonlinear power law transformation. This model allows us devising a novel algorithm that addresses the identification and correction for either additive and/or multiplicative contaminants. We test this model on galaxy mocks and systematics templates inspired from data of the third data release of the {\it Javalambre Photometric Local Universe Survey} (J-PLUS). We find that our method clearly outperforms standard methods that assume either an additive or multiplicative character for all contaminants in scenarios where both characters are actually acting on the observed data. In simpler scenarios where only an additive or multiplicative imprint on observations is considered, our hybrid method does not lie far behind the corresponding simplified, additive/multiplicative methods. Nonetheless, in scenarios of mild/low impact of systematics, we find that our hybrid approach converges towards the standard method that assumes additive contamination, as predicted by our model describing systematics. Our methodology also allows for the estimation of biases induced by systematics residuals on different angular scales and under different observational configurations, although these predictions necessarily restrict to the subset of {\em known/identified} potential systematics, and say nothing about ``unknown unknowns" possibly impacting the data.

astro-ph.CO↗

arXiv2024

J-PLUS: Tomographic analysis of galaxy angular density and redshift fluctuations in Data Release 3. Constraints on photo-$z$ errors, linear bias, and peculiar velocities

The {\it Javalambre Photometric Local Universe Survey} (J-PLUS) is a {\it spectro-photometric} survey covering about 3,000~deg$^2$ in its third data release (DR3), and containing about 300,000 galaxies with high quality ({\it odds}$>0.8$) photometric redshifts (hereafter photo-$z$s). We use this galaxy sample to conduct a tomographic study of the counts and redshift angular fluctuations under Gaussian shells sampling the redshift range $z\in[0.05,0.25]$. We confront the angular power spectra of these observables measured under shells centered on 11 different redshifts with theoretical expectations derived from a linear Boltzmann code ({\tt ARFCAMB}). Overall we find that J-PLUS DR3 data are well reproduced by our linear, simplistic model. We obtain that counts (or density) angular fluctuations (hereafter ADF) are very sensitive to the linear galaxy bias $b_g(z)$, although weakly sensitive to radial peculiar velocities of the galaxy field, while suffering from systematics residuals for $z>0.15$. Angular redshift fluctuations (ARF), instead, show higher sensitivity to radial peculiar velocities and also higher sensitivity to the average uncertainty in photo-$z$s ($\sigma_{\rm Err}$), with no obvious impact from systematics. For $z<0.15$ both ADF and ARF agree on measuring a monotonically increasing linear bias varying from $b_g(z=0.05)\simeq 0.9\pm 0.06$ up to $b_g(z=0.15)\simeq 1.5\pm 0.05$, while, by first time, providing consistent measurements of $\sigma_{\rm Err}(z)\sim 0.014$ that are $\sim 40~\%$ higher than estimates from the photo-$z$ code {\tt LePhare}, ($\sigma_{\rm Err}^{\rm LePhare}=0.010$). As expected, this photo-$z$ uncertainty level prevents the detection of radial peculiar velocities in the modest volume sampled by J-PLUS DR3, although prospects for larger galaxy surveys of similar (and higher) photo-$z$ precision are promising.

astro-ph.CO↗

arXiv2024

TREASUREHUNT: Transients and Variability Discovered with HST in the JWST North Ecliptic Pole Time Domain Field

The JWST North Ecliptic Pole (NEP) Time Domain Field (TDF) is a $>$14 arcmin diameter field optimized for multi-wavelength time-domain science with JWST. It has been observed across the electromagnetic spectrum both from the ground and from space, including with the Hubble Space Telescope (HST). As part of HST observations over 3 cycles (the "TREASUREHUNT" program), deep images were obtained with ACS/WFC in F435W and F606W that cover almost the entire JWST NEP TDF. Many of the individual pointings of these programs partially overlap, allowing an initial assessment of the potential of this field for time-domain science with HST and JWST. The cumulative area of overlapping pointings is ~88 arcmin$^2$, with time intervals between individual epochs that range between 1 day and 4$+$ years. To a depth of $m_{AB}$ $\simeq$ 29.5 mag (F606W), we present the discovery of 12 transients and 190 variable candidates. For the variable candidates, we demonstrate that Gaussian statistics are applicable, and estimate that ~80 are false positives. The majority of the transients will be supernovae, although at least two are likely quasars. Most variable candidates are AGN, where we find 0.42% of the general $z$ $<$ 6 field galaxy population to vary at the $~3\sigma$ level. Based on a 5-year timeframe, this translates into a random supernova areal density of up to ~0.07 transients per arcmin$^2$ (~245 deg$^{-2}$) per epoch, and a variable AGN areal density of ~1.25 variables per arcmin$^2$ (~4500 deg$^{-2}$) to these depths.

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arXiv2023

The miniJPAS survey: Maximising the photo-z accuracy from multi-survey datasets with probability conflation

We present a new method for obtaining photometric redshifts (photo-z) for sources observed by multiple photometric surveys using a combination (conflation) of the redshift probability distributions (PDZs) obtained independently from each survey. The conflation of the PDZs has several advantages over the usual method of modelling all the photometry together, including modularity, speed, and accuracy of the results. Using a sample of galaxies with narrow-band photometry in 56 bands from J-PAS and deeper grizy photometry from the Hyper-SuprimeCam Subaru Strategic program (HSC-SSP), we show that PDZ conflation significantly improves photo-z accuracy compared to fitting all the photometry or using a weighted average of point estimates. The improvement over J-PAS alone is particularly strong for i>22 sources, which have low signal-to-noise ratio in the J-PAS bands. For the entire i<22.5 sample, we obtain a 64% (45%) increase in the number of sources with redshift errors |Dz|<0.003, a factor 3.3 (1.9) decrease in the normalised median absolute deviation of the errors (sigma_NMAD), and a factor 3.2 (1.3) decrease in the outlier rate compared to J-PAS (HSC-SSP) alone. The photo-z accuracy gains from combining the PDZs of J-PAS with a deeper broadband survey such as HSC-SSP are equivalent to increasing the depth of J-PAS observations by ~1.2--1.5 magnitudes. These results demonstrate the potential of PDZ conflation and highlight the importance of including the full PDZs in photo-z catalogues.

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arXiv2023

J-PLUS DR3: Galaxy-Star-Quasar classification

The Javalambre Photometric Local Universe Survey (J-PLUS) is a 12-band photometric survey using the 83-cm JAST telescope. Data Release 3 includes 47.4 million sources. J-PLUS DR3 only provides star-galaxy classification so that quasars are not identified from the other sources. Given the size of the dataset, machine learning methods could provide a valid alternative classification and a solution to the classification of quasars. Our objective is to classify J-PLUS DR3 sources into galaxies, stars and quasars, outperforming the available classifiers in each class. We use an automated machine learning tool called TPOT to find an optimized pipeline to perform the classification. The supervised machine learning algorithms are trained on the crossmatch with SDSS DR18, LAMOST DR8 and Gaia. We checked that the training set of about 660 thousand galaxies, 1.2 million stars and 270 thousand quasars is both representative and contain a minimal presence of contaminants (less than 1%). We considered 37 features: the twelve photometric bands with respective errors, six colors, four morphological parameters, galactic extinction with its error and the PSF relative to the corresponding pointing. With TPOT genetic algorithm, we found that XGBoost provides the best performance: the AUC for galaxies, stars and quasars is above 0.99 and the average precision is above 0.99 for galaxies and stars and 0.96 for quasars. XGBoost outperforms the classifiers already provided in J-PLUS DR3 and also classifies quasars.

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arXiv2023

The miniJPAS survey: AGN & host galaxy co-evolution of X-ray selected sources

Studies indicate strong evidence of a scaling relation in the local Universe between the supermassive black hole mass ($M_\rm{BH}$) and the stellar mass of their host galaxies ($M_\star$). They even show similar histories across cosmic times of their differential terms: star formation rate (SFR) and black hole accretion rate (BHAR). However, a clear picture of this coevolution is far from being understood. We select an X-ray sample of active galactic nuclei (AGN) up to $z=2.5$ in the miniJPAS footprint. Their X-ray to infrared spectral energy distributions (SEDs) have been modeled with CIGALE, constraining the emission to 68 bands. For a final sample of 308 galaxies, we derive their physical properties (e.g., $M_\star$, $\rm{SFR}$, $\rm{SFH}$, and $L_\rm{AGN}$). We also fit their optical spectra for a subsample of 113 sources to estimate the $M_\rm{BH}$. We calculate the BHAR depending on two radiative efficiency regimes. We find that the Eddington ratios ($λ$) and its popular proxy ($L_\rm{X}$/$M_\star$) have 0.6 dex of difference, and a KS-test indicates that they come from different distributions. Our sources exhibit a considerable scatter on the $M_\rm{BH}$-$M_\star$ relation, which can explain the difference between $λ$ and its proxy. We also model three evolution scenarios to recover the integral properties at $z=0$. Using the SFR and BHAR, we show a notable diminution in the scattering between $M_\rm{BH}$-$M_\star$. For the last scenario, we consider the SFH and a simple energy budget for the AGN accretion, obtaining a relation similar to the local Universe. Our study covers $\sim 1$ deg$^2$ in the sky and is sensitive to biases in luminosity. Nevertheless, we show that, for bright sources, the link between SFR and BHAR, and their decoupling based on an energy limit is the key that leads to the local $M_\rm{BH}$-$M_\star$ scaling relation.

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arXiv2023

J-NEP: 60-band photometry and photometric redshifts for the James Webb Space Telescope North Ecliptic Pole Time-Domain Field

The J-PAS survey will observe ~1/3 of the northern sky with a set of 56 narrow-band filters using the dedicated 2.55 m JST telescope at the Javalambre Astrophysical Observatory. Prior to the installation of the main camera, in order to demonstrate the scientific potential of J-PAS, two small surveys were performed with the single-CCD Pathfinder camera: miniJPAS (~1 deg2 along the Extended Groth Strip), and J-NEP (~0.3 deg2 around the JWST North Ecliptic Pole Time Domain Field), including all 56 J-PAS filters as well as u, g, r, and i. J-NEP is ~0.5-1.0 magnitudes deeper than miniJPAS, providing photometry for 24,618 r-band detected sources and photometric redshifts (photo-z) for the 6,662 sources with r<23. In this paper we describe the photometry and photo-z of J-NEP and demonstrate a new method for the removal of systematic offsets in the photometry based on the median colours of galaxies, dubbed "galaxy locus recalibration". This method does not require spectroscopic observations except in a few reference pointings and, unlike previous methods, is applicable to the whole J-PAS survey. We use a spectroscopic sample of 787 galaxies to test the photo-z performance for J-NEP and in comparison to miniJPAS. We find that the deeper J-NEP observations result in a factor ~1.5-2 decrease in sigma_NMAD (a robust estimate of the standard deviation of the photo-z error) and the outlier rate relative to miniJPAS for r>21.5 sources, but no improvement in brighter ones. We find the same relation between sigma_NMAD and odds in J-NEP and miniJPAS, suggesting sigma_NMAD can be predicted for any set of J-PAS sources from their odds distribution alone, with no need for additional spectroscopy to calibrate the relation. We explore the causes for photo-z outliers and find that colour-space degeneracy at low S/N, photometry artifacts, source blending, and exotic spectra are the most important factors.

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arXiv2022

TOPz: Photometric redshifts for J-PAS

The importance of photometric galaxy redshift estimation is rapidly increasing with the development of specialised powerful observational facilities. We develop a new photometric redshift estimation workflow TOPz to provide reliable and efficient redshift estimations for the upcoming large-scale survey J-PAS which will observe 8500 deg2 of the northern sky through 54 narrow-band filters. TOPz relies on template-based photo-z estimation with some added J-PAS specific features and possibilities. We present TOPz performance on data from the miniJPAS survey, a precursor to the J-PAS survey with an identical filter system. First, we generated spectral templates based on the miniJPAS sources using the synthetic galaxy spectrum generation software CIGALE. Then we applied corrections to the input photometry by minimising systematic offsets from the template flux in each filter. To assess the accuracy of the redshift estimation, we used spectroscopic redshifts from the DEEP2, DEEP3, and SDSS surveys, available for 1989 miniJPAS galaxies with r < 22 magAB. We also tested how the choice and number of input templates, photo-z priors, and photometric corrections affect the TOPz redshift accuracy. The general performance of the combination of miniJPAS data and the TOPz workflow fulfills the expectations for J-PAS redshift accuracy. Similarly to previous estimates, we find that 38.6% of galaxies with r < 22 mag reach the J-PAS redshift accuracy goal of dz/(1 + z) < 0.003. Limiting the number of spectra in the template set improves the redshift accuracy up to 5%, especially for fainter, noise-dominated sources. Further improvements will be possible once the actual J-PAS data become available.

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arXiv2021

The miniJPAS Survey: A Study on Wavelength Dependence of the Photon Response Non-uniformity of the JPAS-{\it Pathfinder} Camera

Understanding the origins of small-scale flats of CCDs and their wavelength-dependent variations plays an important role in high-precision photometric, astrometric, and shape measurements of astronomical objects. Based on the unique flat data of 47 narrow-band filters provided by JPAS-{\it Pathfinder}, we analyze the variations of small-scale flats as a function of wavelength. We find moderate variations (from about $1.0\%$ at 390 nm to $0.3\%$ at 890 nm) of small-scale flats among different filters, increasing towards shorter wavelengths. Small-scale flats of two filters close in central wavelengths are strongly correlated. We then use a simple physical model to reproduce the observed variations to a precision of about $\pm 0.14\%$, by considering the variations of charge collection efficiencies, effective areas and thicknesses between CCD pixels. We find that the wavelength-dependent variations of small-scale flats of the JPAS-{\it Pathfinder} camera originate from inhomogeneities of the quantum efficiency (particularly charge collection efficiency) as well as the effective area and thickness of CCD pixels. The former dominates the variations in short wavelengths while the latter two dominate at longer wavelengths. The effects on proper flat-fielding as well as on photometric/flux calibrations for photometric/slit-less spectroscopic surveys are discussed, particularly in blue filters/wavelengths. We also find that different model parameters are sensitive to flats of different wavelengths, depending on the relations between the electron absorption depth, the photon absorption length and the CCD thickness. In order to model the wavelength-dependent variations of small-scale flats, a small number (around ten) of small-scale flats with well-selected wavelengths are sufficient to reconstruct small-scale flats in other wavelengths.

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arXiv2021

The miniJPAS survey: the photometric redshift catalogue

MiniJPAS is a ~1 deg^2 imaging survey of the AEGIS field in 60 bands, performed to demonstrate the scientific potential of the upcoming JPAS survey. Full coverage of the 3800-9100 Årange with 54 narrow and 6 broad optical filters allow for extremely accurate photo-z, which applied over 1000s of deg^2 will enable new applications of the photo-z technique such as measurement of baryonic acoustic oscillations. In this paper we describe the method used to obtain the photo-z included in the publicly available miniJPAS catalogue, and characterise the photo-z performance. We build 100 Åresolution photo-spectra from the PSF-corrected forced-aperture photometry. Systematic offsets in the photometry are corrected by applying magnitude shifts obtained through iterative fitting with stellar population synthesis models. We compute photo-z with a customised version of LePhare, using a set of templates optimised for the J-PAS filter-set. We analyse the accuracy of miniJPAS photo-z and their dependence on multiple quantities using a subsample of 5,266 galaxies with spectroscopic redshifts from SDSS and DEEP, that we find to be representative of the whole r<23 miniJPAS sample. Formal uncertainties for the photo-z that are calculated with the δχ^2 method underestimate the actual redshift errors. The odds parameter has the stronger correlation with |Dz|, and accurately reproduces the probability of a redshift outlier (|Dz|>0.03) irrespective of the magnitude, redshift, or spectral type of the sources. We show that the two main summary statistics characterising the photo-z accuracy for a population of galaxies (snmad and η) can be predicted by the distribution of odds in such population, and use this to estimate them for the whole miniJPAS sample. At r<23 there are 17,500 galaxies/deg^2 with valid photo-z estimates, of which 4,200 are expected to have |Dz|<0.003 (abridged).

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arXiv2021

CODEX Weak Lensing Mass Catalogue and implications on the mass-richness relation

The COnstrain Dark Energy with X-ray clusters (CODEX) sample contains the largest flux limited sample of X-ray clusters at $0.35 < z < 0.65$. It was selected from ROSAT data in the 10,000 square degrees of overlap with BOSS, mapping a total number of 2770 high-z galaxy clusters. We present here the full results of the CFHT CODEX program on cluster mass measurement, including a reanalysis of CFHTLS Wide data, with 25 individual lensing-constrained cluster masses. We employ $lensfit$ shape measurement and perform a conservative colour-space selection and weighting of background galaxies. Using the combination of shape noise and an analytic covariance for intrinsic variations of cluster profiles at fixed mass due to large scale structure, miscentring, and variations in concentration and ellipticity, we determine the likelihood of the observed shear signal as a function of true mass for each cluster. We combine 25 individual cluster mass likelihoods in a Bayesian hierarchical scheme with the inclusion of optical and X-ray selection functions to derive constraints on the slope $α$, normalization $β$, and scatter $σ_{\ln λ| μ}$ of our richness-mass scaling relation model in log-space: $\left<\ln λ| μ\right> = αμ+ β$, with $μ= \ln (M_{200c}/M_{\mathrm{piv}})$, and $M_{\mathrm{piv}} = 10^{14.81} M_{\odot}$. We find a slope $α= 0.49^{+0.20}_{-0.15}$, normalization $ \exp(β) = 84.0^{+9.2}_{-14.8}$ and $σ_{\ln λ| μ} = 0.17^{+0.13}_{-0.09}$ using CFHT richness estimates. In comparison to other weak lensing richness-mass relations, we find the normalization of the richness statistically agreeing with the normalization of other scaling relations from a broad redshift range ($0.0<z<0.65$) and with different cluster selection (X-ray, Sunyaev-Zeldovich, and optical).

astro-ph.CO↗

arXiv2020

The miniJPAS survey: star-galaxy classification using machine learning

Future astrophysical surveys such as J-PAS will produce very large datasets, which will require the deployment of accurate and efficient Machine Learning (ML) methods. In this work, we analyze the miniJPAS survey, which observed about 1 deg2 of the AEGIS field with 56 narrow-band filters and 4 ugri broad-band filters. We discuss the classification of miniJPAS sources into extended (galaxies) and point-like (e.g. stars) objects, a necessary step for the subsequent scientific analyses. We aim at developing an ML classifier that is complementary to traditional tools based on explicit modeling. In order to train and test our classifiers, we crossmatched the miniJPAS dataset with SDSS and HSC-SSP data. We trained and tested 6 different ML algorithms on the two crossmatched catalogs. As input for the ML algorithms we use the magnitudes from the 60 filters together with their errors, with and without the morphological parameters. We also use the mean PSF in the r detection band for each pointing. We find that the RF and ERT algorithms perform best in all scenarios. When analyzing the full magnitude range of 15 21). We use our best classifiers, with and without morphology, in order to produce a value added catalog available at https://j-pas.org/datareleases .

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