TOPz: Photometric redshifts for J-PAS

Laur, J.; Tempel, Elmo; Tamm, A.; Kipper, Rain; Liivamägi, L. J.; Hernán-Caballero, A.; Muru, M. M.; Chaves-Montero, Jonás; Díaz-García, L. A.; Turner, Sebastian; Tuvikene, T.; Queiroz, Carolina; Fernández-Ontiveros, J. A.; Delgado, R. M. González; Civera, T.; Abramo, R.; Alcaniz, J. S.; Benı́tez, N.; Bonoli, Silvia; Carneiro, S.; Cenarro, J.; Cristóbal-Hornillos, D.; Dupke, Renato A.; Ederoclite, A.; López-Sanjuán, C.; Marín-Franch, A.; Oliveira, C. Mendes de; Moles, M.; Sodré, L.; Taylor, Keith; Varela, J.; Ramió, H. Vázquez

doi:10.1051/0004-6361/202243881

Cited by 9 publications

(4 citation statements)

References 53 publications

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“…Unfortunately, all current photometric surveys have unusably large uncertainties for the redshifts, but there will be some new surveys with suitable accuracy in the near future. One prominent candidate for photometric redshift data is the upcoming Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS, Benitez et al 2014;Bonoli et al 2021;Laur et al 2022). J-PAS is designed to measure the positions and redshifts of 14 million galaxies.…”

Section: Samplesmentioning

confidence: 99%

Using photometric redshift data to improve the detection of galactic filaments with the Bisous model

Muru

Tempel

2023

A&A

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Context. Filament finders are limited, among other things, by the abundance of spectroscopic redshift data. This limits the sky areas and depth where we can detect the filamentary network. Aims. As there are proportionally more photometric redshift data than spectroscopic, we aim to use data with photometric redshifts to improve and expand the areas where we can detect the large-scale structure of the Universe. The Bisous model is a filament finder that uses only the galaxy positions. We present a proof of concept, showing that the Bisous filament finder can improve the detected filamentary network with photometric redshift data. Methods. We created mock data from the MULTIDARK-GALAXIES catalogue. Galaxies with spectroscopic redshifts were given exact positions from the simulation. Galaxies with photometric redshifts were given uncertainties along one coordinate. The errors were generated with different Gaussian distributions for different samples. We sample the photometric galaxy positions for each Bisous run based on the uncertainty distribution. In some runs, the sampled positions are closer to the true positions and produce persistent filaments; other runs produce noise, which is suppressed in the post-processing. Results. There are three different types of samples: spectroscopic only, photometric only, and mixed samples of galaxies with photometric and spectroscopic redshifts. In photometric-only samples, the larger the uncertainty for photometric redshifts, the fewer filaments are detected, and the filaments strongly align along the line of sight. Using mixed samples improves the number of filaments detected and decreases the alignment bias of those filaments. The results are compared against the full spectroscopic sample. The recall for photometric-only samples depends heavily on the size of uncertainty and dropped close to 20%; for mixed samples, the recall stayed between 40% and 80%. The false discovery rate stayed below 5% in every sample tested in this work. Mixed samples showed better results than corresponding photometric-only or spectroscopic-only samples for every uncertainty size and number of spectroscopic galaxies in mixed samples. Conclusions. Mixed samples of galaxies with photometric and spectroscopic redshifts help us to improve and extend the large-scale structure further than possible with only spectroscopic samples. Although the uncertainty sizes tested in this work are smaller than those for the available photometric data, upcoming surveys, such as J-PAS, will achieve sufficiently small uncertainties to be useful for large-scale structure detection.

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Section: Samplesmentioning

confidence: 99%

Using photometric redshift data to improve the detection of galactic filaments with the Bisous model

Muru

Tempel

2023

A&A

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“…An important step in determining accurate photo-z over a large area will be taken by the Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS; Benítez et al 2009Benítez et al , 2014, which will cover one third of the northern hemisphere with a unique set of 56 optical filters (plus i band for detection) and provides, for each 0.48 ′′ × 0.48 ′′ pixel in the sky, an R ∼ 60 photo-spectrum (J-spectrum) covering the 3800-9100 Å range. Two small surveys were carried out to demonstrate the scientific potential of J-PAS: miniJPAS (Bonoli et al 2021) and J-NEP (Hernán-Caballero et al 2023), showing that σ(∆z)=0.3% is attainable with the 56 bands of J-PAS plus u, g, r, and i (Hernán- Caballero et al 2021Caballero et al , 2023Laur et al 2022).…”

Section: Introductionmentioning

confidence: 99%

“…As a consequence, photo-z measurements from multi-narrow-band photometry rely almost exclusively on SED-fitting with spectral templates (e.g. Wolf et al 2003;Moles et al 2008;Pérez-González et al 2013;Barro et al 2019;Eriksen et al 2019;Alarcon et al 2021;Laur et al 2022). Doing an SED fit to the combined deep and shallow photometry is tricky because of the cross-calibration issue mentioned above, but also because the optimal number of templates depends on the number of bands with detections (Hernán-Caballero et al, in prep.).…”

Section: Introductionmentioning

confidence: 99%

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

Hernán-Caballero,

Akhlaghi,

López-Sanjuan

et al. 2024

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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 the 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 $i$gtrsim 22 sources, which have low signal-to-noise ratios in the J-PAS bands. For the entire $i$$<$22.5 sample, we obtain a 64<!PCT!> (45<!PCT!>) increase in the number of sources with redshift errors $ z a factor of 3.3 (1.9) decrease in the normalised median absolute deviation of the errors ($ NMAD $), and a factor of 3.2 (1.3) decrease in the outlier rate (eta ) compared to J-PAS (HSC-SSP) alone. The photo-$z$ accuracy gains from combining the PDZs of J-PAS with a deeper broad-band survey such as HSC-SSP are equivalent to increasing the depth of J-PAS observations by sim 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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“…Most of the observing time with Pathfinder was devoted to performing a ∼1 deg 2 survey of the Extended Groth Strip with the 56 filters of J-PAS along with u, g, r, and i, reaching depths comparable to those expected for J-PAS (Bonoli et al 2021). This survey, dubbed miniJPAS, has been used to test the performance of the telescope and the Pathfinder camera (Bonoli et al 2021;Xiao et al 2021), the algorithms for detection of emission lines (Martínez-Solaeche et al 2021;Iglesias-Páramo et al 2022), star, galaxy, and quasar classification (Baqui et al 2021;Queiroz et al 2022), and photo-z calculation (Hernán-Caballero et al 2021;Laur et al 2022), as well as to obtain the first scientific results on the properties of J-PAS galaxies (González Martínez-Solaeche et al 2022;Rodríguez-Martín et al 2022) and quasars (Chaves-Montero et al 2022).…”

Section: Introductionmentioning

confidence: 99%

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

Hernán-Caballero

Willmer

Varela

et al. 2023

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The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) will observe approximately one-third of the northern sky with a set of 56 narrow-band filters using the dedicated 2.55 m Javalambre Survey Telescope (JST) 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 mag deeper than miniJPAS, providing photometry for 24,618 r-band-detected sources and photometric redshifts (photo-z) for the 6662 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, which we call ‘galaxy locus recalibration’. This method does not require spectroscopic observations except in a few reference pointings and, unlike previous methods, is directly 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 σNMAD (a robust estimate of the standard deviation of the photo-z error) and η (the outlier rate) relative to miniJPAS for r > 21.5 sources, but no improvement in brighter ones, which is probably because of systematic uncertainties. We find the same relation between σNMAD and odds in J-NEP and miniJPAS, which suggests that we will be able to predict the σNMAD of 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 of photo-z outliers and find that colour-space degeneracy at low S/N, photometry artefacts, source blending, and exotic spectra are the most important factors.

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TOPz: Photometric redshifts for J-PAS

Cited by 9 publications

References 53 publications

Using photometric redshift data to improve the detection of galactic filaments with the Bisous model

Using photometric redshift data to improve the detection of galactic filaments with the Bisous model

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

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

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