Experience with Artificial Neural Networks Applied in Multi-object Adaptive Optics

The use of artificial Intelligence techniques has become widespread in many fields of science, due to their ability to learn from real data and adjust to complex models with ease. These techniques have landed in the field of adaptive optics, and are being used to correct distortions caused by atmospheric turbulence in astronomical images obtained by ground-based telescopes. Advances for multi-object adaptive optics are considered here, focusing particularly on artificial neural networks, which have shown great performance and robustness when compared with other artificial intelligence techniques. The use of artificial neural networks has evolved to the extent of the creation of a reconstruction technique that is capable of estimating the wavefront of light after being deformed by the atmosphere. Based on this idea, different solutions have been proposed in recent years, including the use of new types of artificial neural networks. The results of techniques based on artificial neural networks have led to further applications in the field of adaptive optics, which are included in here, such as the development of new techniques for solar observation or their application in novel types of sensors

Multi-frequency point source detection with fully convolutional networks: Performance in realistic microwave sky simulations

Context. Point source (PS) detection is an important issue for future cosmic microwave background (CMB) experiments since they are one of the main contaminants to the recovery of CMB signal on small scales. Improving its multi-frequency detection would allow us to take into account valuable information otherwise neglected when extracting PS using a channel-by-channel approach. Aims. We aim to develop an artificial intelligence method based on fully convolutional neural networks to detect PS in multi-frequency realistic simulations and compare its performance against one of the most popular multi-frequency PS detection methods, the matrix filters. The frequencies used in our analysis are 143, 217, and 353 GHz, and we imposed a Galactic cut of 30°. Methods. We produced multi-frequency realistic simulations of the sky by adding contaminating signals to the PS maps as the CMB, the cosmic infrared background, the Galactic thermal emission, the thermal Sunyaev-Zel’dovich effect, and the instrumental and PS shot noises. These simulations were used to train two neural networks called flat and spectral MultiPoSeIDoNs. The first one considers PS with a flat spectrum, and the second one is more realistic and general because it takes into account the spectral behaviour of the PS. Then, we compared the performance on reliability, completeness, and flux density estimation accuracy for both MultiPoSeIDoNs and the matrix filters. Results. Using a flux detection limit of 60 mJy, MultiPoSeIDoN successfully recovered PS reaching the 90% completeness level at 58 mJy for the flat case, and at 79, 71, and 60 mJy for the spectral case at 143, 217, and 353 GHz, respectively. The matrix filters reach the 90% completeness level at 84, 79, and 123 mJy. To reduce the number of spurious sources, we used a safer 4σ flux density detection limit for the matrix filters, the same as was used in the Planck catalogues, obtaining the 90% of completeness level at 113, 92, and 398 mJy. In all cases, MultiPoSeIDoN obtains a much lower number of spurious sources with respect to the filtering method. The recovering of the flux density of the detections, attending to the results on photometry, is better for the neural networks, which have a relative error of 10% above 100 mJy for the three frequencies, while the filter obtains a 10% relative error above 150 mJy for 143 and 217 GHz, and above 200 mJy for 353 GHz. Conclusions. Based on the results, neural networks are the perfect candidates to substitute filtering methods to detect multi-frequency PS in future CMB experiments. Moreover, we show that a multi-frequency approach can detect sources with higher accuracy than single-frequency approaches also based on neural networks.We warmly thank the anonymous referee for the very useful comments on the original manuscript. J.M.C., J.G.N., L.B., M.M.C. and D.C. acknowledge financial support from the PGC 2018 project PGC2018-101948-B-I00 (MICINN, FEDER). DH acknowledges the Spanish MINECO and the Spanish Ministerio de Ciencia, Innovación y Universidades for partial financial support under project PGC2018-101814-B-I00. M.M.C. acknowledges PAPI-20-PF-23 (Universidad de Oviedo). J.D.C.J., M.L.S., S.L.S.G., J.D.S. and F.S.L. acknowledge financial support from the I+D 2017 project AYA2017-89121-P and support from the European Union’s Horizon 2020 research and innovation programme under the H2020-INFRAIA-2018-2020 grant agreement No 210489629. This research has made use of the python packages ipython (Pérez & Granger 2007), matplotlib (Hunter 2007), TensorFlow (Abadi et al. 2015), Numpy (Oliphant 2006) and Scipy (Jones et al. 2001), also the HEALPix (Górski et al. 2005) and healpy (Zonca et al. 2019) packages

Herschel-ATLAS: Evolution of the 250 μm luminosity function out to z = 0.5

We have determined the luminosity function of 250 μm-selected galaxies detected in the ~14 deg2 science demonstration region of the Herschel-ATLAS project out to a redshift of z = 0.5. Our findings very clearly show that the luminosity function evolves steadily out to this redshift. By selecting a sub-group of sources within a fixed luminosity interval where incompleteness effects are minimal, we have measured a smooth increase in the comoving 250 μm luminosity density out to z = 0.2 where it is 3.6-0.9+1.4 times higher than the local value.S.D. Acknowledges the UK STFC for support

Herschel -ATLAS: The dust energy balance in the edge-on spiral galaxy UGC 4754

We use Herschel PACS and SPIRE observations of the edge-on spiral galaxy UGC 4754, taken as part of the H-ATLAS SDP observations, to investigate the dust energy balance in this galaxy. We build detailed SKIRT radiative models based on SDSS and UKIDSS maps and use these models to predict the far-infrared emission. We find that our radiative transfer model underestimates the observed FIR emission by a factor of two to three. Similar discrepancies have been found for other edge-on spiral galaxies based on IRAS, ISO, and SCUBA data. Thanks to the good sampling of the SED at FIR wavelengths, we can rule out an underestimation of the FIR emissivity as the cause for this discrepancy. Instead we support highly obscured star formation that contributes little to the optical extinction as a more probable explanation.This work used data from the UKIDSS DR5 and SDSS DR7. The UKIDSS project is defined in Lawrence et al. (2007) and uses the UKIRT Wide Field Camera (WFCAM; Casali et al. 2007). Funding for the SDSS and SDSS-II has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, the US Department of Energy, the National Aeronautics and Space Administration, the Japanese Monbukagakusho, the Max Planck Society, and the Higher Education Funding Council for England

The Cantabrian capercaillie: A population on the edge

The capercaillie Tetrao urogallus - the world's largest grouse- is a circumboreal forest species, which only two remaining populations in Spain: one in the Cantabrian mountains in the west and the other in the Pyrenees further east. Both have shown severe declines, especially in the Cantabrian population, which has recently been classified as “Critically Endangered”. To develop management plans, information on demographic parameters is necessary to understand and forecast population dynamics. We used spatial capture-recapture (SCR) modeling and non-invasive DNA samples to estimate the current population size in the whole Cantabrian mountain range. In addition, for the assessment of population status, we analyzed the population trajectory over the last 42 years (1978–2019) at 196 leks on the Southern slope of the range, using an integrated population model with a Dail-Madsen model at its core, combined with a multistate capture-recapture model for survival and a Poisson regression for productivity. For 2019, we estimate the size of the entire population at 191 individuals (95% BCI 165–222) for an estimated 60 (48–78) females and 131 (109–157) males. Since the 1970s, our study estimates a shrinkage of the population range by 83%. The population at the studied leks in 2019 was at about 10% of the size estimated for 1978. Apparent annual survival was estimated at 0.707 (0.677–0.735), and per-capita recruitment at 0.233 (0.207–0.262), and insufficient to maintain a stable population. We suggest work to improve the recruitment (and survival) and manage these mountain forests for capercaillie conservation. Also, in the future, management should assess the genetic viability of this population.Ministerio para la Transición Ecológica y el Reto Demográfico (18MNES002 and 19MNES001); Junta de Castilla y León (EN-16/19); Gobierno del Principado de Asturias (SCP025/2019)].Peer reviewe

High triglyceride to HDL-cholesterol ratio as a biochemical marker of severe outcomes in COVID-19 patients

Background & aims Coronavirus disease 2019 (COVID-19) patients with severe complications have shown comorbidities with cardiovascular-disease, hypertension and type 2 diabetes mellitus; clinical disorders that share the common metabolic alterations of insulin resistance and dyslipidaemia. A high triglyceride to high density lipoprotein cholesterol (Tg/HDL c) ratio has been associated with reduced insulin sensitivity, metabolic syndrome and adverse cardiovascular events. Our aim in this study was to determine the association between different components of the lipid profile and particularly the Tg/HDL c ratio with severe complications like the requirement of invasive mechanical ventilation in COVID-19 patients. Methods We collected demographic, clinical and biochemical data to conduct a cohort study in 43 adult patients with confirmed COVID-19 diagnosis by quantitative polymerase chain reaction (qPCR) at baseline and in the subsequent 15 days. Patients were subjected to a very similar treatment scheme with the JAK1/2 inhibitor ruxolitinib. Descriptive statistics, variable association and logistic regression were applied to identify predictors of disease severity among elements and calculations from the lipid profile. Results Patients were aged 57 ± 14 years; 55.8% were male from which 75% required hospitalization and 44.2% were female who 58% were hospitalized. The most common comorbidities were type 2 diabetes mellitus (58%) and hypertension (40%). Hospitalized and critical care patients showed lower HDL c blood levels and increased Tg/HDL c ratio than those with outpatient management and mild/asymptomatic COVID-19. Tg/HDL c ratio correlated with variables of disease severity such as lactate dehydrogenase (LDH) levels (r = 0.356; p < 0.05); National Early Warning Score 2 (NEWS 2) (r = 0.495; p < 0.01); quick sequential organ failure assessment (qSOFA) (r = 0.538; p < 0.001); increased need of oxygen support (r = 0.447; p < 0.01) and requirement of mechanical ventilation (r = 0.378; p < 0.05). Tg/HDL c ratio had a negative correlation with partial oxygen saturation/fraction of inspired oxygen (SaO 2/FiO2) ratio (r = −0.332;p < 0.05). Linear regression analysis showed that Tg/HDL c ratio can predict increases in inflammatory factors like LDH (p < 0.01); ferritin (p < 0.01) and D-dimer (p < 0.001). Logistic regression model indicated that ≥7.45 Tg/HDL c ratio predicts requirement of invasive mechanical ventilation (OR 11.815, CI 1.832–76.186, p < 0.01). Conclusions The Tg/HDLc ratio can be used as an early biochemical marker of COVID-19 severe prognosis with requirement of invasive mechanical ventilation

The Herschel–ATLAS data release 2, Paper I. Submillimeter and far-infrared images of the South and North Galactic Poles: the largest Herschel survey of the extragalactic sky

We present the largest submillimeter images that have been made of the extragalactic sky. The Herschel Astrophysical Terahertz Large Area Survey (H-ATLAS) is a survey of 660 deg2 with the PACS and SPIRE cameras in five photometric bands: 100, 160, 250, 350, and 500 μm. In this paper we present the images from our two largest fields, which account for ~75% of the survey. The first field is 180.1 deg2 in size, centered on the north Galactic pole (NGP), and the second is 317.6 deg2 in size, centered on the south Galactic pole. The NGP field serendipitously contains the Coma cluster. Over most (~80%) of the images, the pixel noise, including both instrumental noise and confusion noise, is approximately 3.6, and 3.5 mJy pix−1 at 100 and 160 μm, and 11.0, 11.1 and 12.3 mJy beam−1 at 250, 350 and 500 μm, respectively, but reaches lower values in some parts of the images. If a matched filter is applied to optimize point-source detection, our total 1σ map sensitivity is 5.7, 6.0, and 7.3 mJy at 250, 350, and 500 μm, respectively. We describe the results of an investigation of the noise properties of the images. We make the most precise estimate of confusion in SPIRE maps to date, finding values of 3.12 ± 0.07, 4.13 ± 0.02, and 4.45 ± 0.04 mJy beam−1 at 250, 350, and 500 μm in our un-convolved maps. For PACS we find an estimate of the confusion noise in our fast-parallel observations of 4.23 and 4.62 mJy beam−1 at 100 and 160 μm. Finally, we give recipes for using these images to carry out photometry, both for unresolved and extended sources

Exploring Cosmic Origins with CORE: Cosmological Parameters

We forecast the main cosmological parameter constraints achievable with theCORE space mission which is dedicated to mapping the polarisation of the CosmicMicrowave Background (CMB). CORE was recently submitted in response to ESA'sfifth call for medium-sized mission proposals (M5). Here we report the resultsfrom our pre-submission study of the impact of various instrumental options, inparticular the telescope size and sensitivity level, and review the great,transformative potential of the mission as proposed. Specifically, we assessthe impact on a broad range of fundamental parameters of our Universe as afunction of the expected CMB characteristics, with other papers in the seriesfocusing on controlling astrophysical and instrumental residual systematics. Inthis paper, we assume that only a few central CORE frequency channels areusable for our purpose, all others being devoted to the cleaning ofastrophysical contaminants. On the theoretical side, we assume LCDM as ourgeneral framework and quantify the improvement provided by CORE over thecurrent constraints from the Planck 2015 release. We also study the jointsensitivity of CORE and of future Baryon Acoustic Oscillation and Large ScaleStructure experiments like DESI and Euclid. Specific constraints on the physicsof inflation are presented in another paper of the series. In addition to thesix parameters of the base LCDM, which describe the matter content of aspatially flat universe with adiabatic and scalar primordial fluctuations frominflation, we derive the precision achievable on parameters like thosedescribing curvature, neutrino physics, extra light relics, primordial heliumabundance, dark matter annihilation, recombination physics, variation offundamental constants, dark energy, modified gravity, reionization and cosmicbirefringence. (ABRIDGED

Planck 2015 results. XIV. Dark energy and modified gravity

We study the implications of Planck data for models of dark energy (DE) and modified gravity (MG), beyond the cosmological constant scenario. We start with cases where the DE only directly affects the background evolution, considering Taylor expansions of the equation of state, principal component analysis and parameterizations related to the potential of a minimally coupled DE scalar field. When estimating the density of DE at early times, we significantly improve present constraints. We then move to general parameterizations of the DE or MG perturbations that encompass both effective field theories and the phenomenology of gravitational potentials in MG models. Lastly, we test a range of specific models, such as k-essence, f(R) theories and coupled DE. In addition to the latest Planck data, for our main analyses we use baryonic acoustic oscillations, type-Ia supernovae and local measurements of the Hubble constant. We further show the impact of measurements of the cosmological perturbations, such as redshift-space distortions and weak gravitational lensing. These additional probes are important tools for testing MG models and for breaking degeneracies that are still present in the combination of Planck and background data sets. All results that include only background parameterizations are in agreement with LCDM. When testing models that also change perturbations (even when the background is fixed to LCDM), some tensions appear in a few scenarios: the maximum one found is \sim 2 sigma for Planck TT+lowP when parameterizing observables related to the gravitational potentials with a chosen time dependence; the tension increases to at most 3 sigma when external data sets are included. It however disappears when including CMB lensing