The OTELO survey. A case study of [O III]4959,5007 emitters at <z> = 0.83

The OTELO survey is a very deep, blind exploration of a selected region of the Extended Groth Strip and is designed for finding emission-line sources (ELSs). The survey design, observations, data reduction, astrometry, and photometry, as well as the correlation with ancillary data used to obtain a final catalogue, including photo-z estimates and a preliminary selection of ELS, were described in a previous contribution. Here, we aim to determine the main properties and luminosity function (LF) of the [O III] ELS sample of OTELO as a scientific demonstration of its capabilities, advantages, and complementarity with respect to other surveys. The selection and analysis procedures of ELS candidates obtained using tunable filter (TF) pseudo-spectra are described. We performed simulations in the parameter space of the survey to obtain emission-line detection probabilities. Relevant characteristics of [O III] emitters and the LF([O III]), including the main selection biases and uncertainties, are presented. A total of 184 sources were confirmed as [O III] emitters at a mean redshift z=0.83. The minimum detectable line flux and equivalent width (EW) in this ELS sample are $\sim$5 $\times$ 10$^{-19}$ erg s$^{-1}$ cm$^{2}$ and $\sim$6 \AA, respectively. We are able to constrain the faint-end slope ($\alpha = -1.03\pm0.08$) of the observed LF([O III]) at z=0.83. This LF reaches values that are approximately ten times lower than those from other surveys. The vast majority (84\%) of the morphologically classified [O III] ELSs are disc-like sources, and 87\% of this sample is comprised of galaxies with stellar masses of M$_\star$ $<$ 10$^{10}$ M$_{\odot}$.Comment: v1: 16 pages, 6 figures. Accepted in Astronomy \& Astrophysics. v2: Author added in metadat

Galaxy classification: deep learning on the OTELO and COSMOS databases

Context. The accurate classification of hundreds of thousands of galaxies observed in modern deep surveys is imperative if we want to understand the universe and its evolution. Aims. Here, we report the use of machine learning techniques to classify early- and late-type galaxies in the OTELO and COSMOS databases using optical and infrared photometry and available shape parameters: either the Sersic index or the concentration index. Methods. We used three classification methods for the OTELO database: 1) u-r color separation , 2) linear discriminant analysis using u-r and a shape parameter classification, and 3) a deep neural network using the r magnitude, several colors, and a shape parameter. We analyzed the performance of each method by sample bootstrapping and tested the performance of our neural network architecture using COSMOS data. Results. The accuracy achieved by the deep neural network is greater than that of the other classification methods, and it can also operate with missing data. Our neural network architecture is able to classify both OTELO and COSMOS datasets regardless of small differences in the photometric bands used in each catalog. Conclusions. In this study we show that the use of deep neural networks is a robust method to mine the cataloged dataComment: 20 pages, 10 tables, 14 figures, Astronomy and Astrophysics (in press

The OTELO survey I. Description, data reduction, and multi-wavelength catalogue

ABSTRACT: Context. The evolution of galaxies through cosmic time is studied observationally by means of extragalactic surveys. The usefulness of these surveys is greatly improved by increasing the cosmological volume, in either depth or area, and by observing the same targets in different wavelength ranges. A multi-wavelength approach using different observational techniques can compensate for observational biases. Aims. The OTELO survey aims to provide the deepest narrow-band survey to date in terms of minimum detectable flux and emission line equivalent width in order to detect the faintest extragalactic emission line systems. In this way, OTELO data will c omplements other broad-band, narrow-band, and spectroscopic surveys. Methods. The red tunable filter of the OSIRIS instrument on the 10.4 m Gran Telescopio Canarias (GTC) is used to scan a spectral window centred at 9175 Å, which is free from strong sky emission lines, with a sampling interval of 6 Å and a bandwidth of 12 Å in the most deeply explored EGS region. Careful data reduction using improved techniques for sky ring subtraction, accurate astrometry, photometric calibration, and source extraction enables us to compile the OTELO catalogue. This catalogue is complemented with ancillary data ranging from deep X-ray to far-infrared, including high resolution HST images, which allow us to segregate the different types of targets, derive precise photometric redshifts, and obtain the morphological classification of the extragalactic objects detected. Results. The OTELO multi-wavelength catalogue contains 11 237 entries and is 50% complete at AB magnitude 26.38. Of these sources, 6600 have photometric redshifts with an uncertainty δ z phot better than 0.2 (1+z phot). A total of 4336 of these sources correspond to preliminary emission line candidates, which are complemented by 81 candidate stars and 483 sources that qualify as absorption line systems. The OTELO survey results will be released to the public on the second half of 2019.This work was supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under the grants AYA2013-46724-P, AYA2014-58861-C3-1-P, AYA2014-58861-C3-2-P, AYA2014-58861-C3-3-P, AYA2016-75808-R, AYA2016-75931-C2-2-P, AYA2017-88007-C3-1-P and AYA2017-88007-C3-2-P

The OTELO survey: A case study of [O III] lambda 4959,5007 emitters at z=0.83

Context. The OSIRIS Tunable Filter Emission Line Object (OTELO) survey is a very deep, blind exploration of a selected region of the Extended Groth Strip and is designed for finding emission-line sources (ELSs). The survey design, observations, data reduction, astrometry, and photometry, as well as the correlation with ancillary data used to obtain a final catalogue, including photo-z estimates and a preliminary selection of ELS, were described in a previous contribution. Aims. Here, we aim to determine the main properties and luminosity function (LF) of the [O III] ELS sample of OTELO as a scientific demonstration of its capabilities, advantages, and complementarity with respect to other surveys. Methods. The selection and analysis procedures of ELS candidates obtained using tunable filter pseudo-spectra are described. We performed simulations in the parameter space of the survey to obtain emission-line detection probabilities. Relevant characteristics of [O III] emitters and the LF ([O III]), including the main selection biases and uncertainties, are presented. Results. From 541 preliminary emission-line source candidates selected around z = 0.8, a total of 184 sources were confirmed as [O III] emitters. Consistent with simulations, the minimum detectable line flux and equivalent width in this ELS sample are ∼5 × 10−19 erg s−1 cm2 and ∼6 Å, respectively. We are able to constrain the faint-end slope (α = −1.03 ± 0.08) of the observed LF ([O III]) at a mean redshift of z = 0.83. This LF reaches values that are approximately ten times lower than those from other surveys. The vast majority (84%) of the morphologically classified [O III] ELSs are disc-like sources, and 87% of this sample is comprised of galaxies with stellar masses of M⋆ <  1010 M⊙

Detailed Analysis of ITPR1 Missense Variants Guides Diagnostics and Therapeutic Design

BACKGROUND: The ITPR1 gene encodes the inositol 1,4,5-trisphosphate (IP3 ) receptor type 1 (IP3 R1), a critical player in cerebellar intracellular calcium signaling. Pathogenic missense variants in ITPR1 cause congenital spinocerebellar ataxia type 29 (SCA29), Gillespie syndrome (GLSP), and severe pontine/cerebellar hypoplasia. The pathophysiological basis of the different phenotypes is poorly understood. OBJECTIVES: We aimed to identify novel SCA29 and GLSP cases to define core phenotypes, describe the spectrum of missense variation across ITPR1, standardize the ITPR1 variant nomenclature, and investigate disease progression in relation to cerebellar atrophy. METHODS: Cases were identified using next-generation sequencing through the Deciphering Developmental Disorders study, the 100,000 Genomes project, and clinical collaborations. ITPR1 alternative splicing in the human cerebellum was investigated by quantitative polymerase chain reaction. RESULTS: We report the largest, multinational case series of 46 patients with 28 unique ITPR1 missense variants. Variants clustered in functional domains of the protein, especially in the N-terminal IP3 -binding domain, the carbonic anhydrase 8 (CA8)-binding region, and the C-terminal transmembrane channel domain. Variants outside these domains were of questionable clinical significance. Standardized transcript annotation, based on our ITPR1 transcript expression data, greatly facilitated analysis. Genotype-phenotype associations were highly variable. Importantly, while cerebellar atrophy was common, cerebellar volume loss did not correlate with symptom progression. CONCLUSIONS: This dataset represents the largest cohort of patients with ITPR1 missense variants, expanding the clinical spectrum of SCA29 and GLSP. Standardized transcript annotation is essential for future reporting. Our findings will aid in diagnostic interpretation in the clinic and guide selection of variants for preclinical studies. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Testing Momentum Effect for the US Market: From Equity to Option Strategies

Conventional financial theory considers ex-ante that risk, generally measured by the volatility, has to be appropriately rewarded by expected returns. In modern financial markets, there are countless quantitative and systematic strategies which may test and eventually lead to excess returns when quantified by these conventional stochastic measures. One of them is the momentum effect which denotes an ongoing movement of the prices of financial assets in a certain direction, for a determined time horizon. Colloquially, assets that have performed better in the past tend to do so in the future. The objective of this paper is to test the existence of excess returns from momentum strategies. To do the aforementioned, we test different selection criteria with diverse weighting schemes. Finally, we analyze how is the behavior of equity options on those underlying assets in order to establish a two-way strategy; first performing pure equity option strategies and then blending equity options with index options