arXiv subjects

Agnieszka Pollo

Publications and source records attributed to Agnieszka Pollo.

At least 55 records · Page 3Linked to original sources

arXiv2021

Synergies between low- and intermediate-redshift galaxy populations revealed with unsupervised machine learning

The colour bimodality of galaxies provides an empirical basis for theories of galaxy evolution. However, the balance of processes that begets this bimodality has not yet been constrained. A more detailed view of the galaxy population is needed, which we achieve in this paper by using unsupervised machine learning to combine multi-dimensional data at two different epochs. We aim to understand the cosmic evolution of galaxy subpopulations by uncovering substructures within the colour bimodality. We choose a clustering algorithm that models clusters using only the most discriminative data available, and apply it to two galaxy samples: one from the second edition of the GALEX-SDSS-WISE Legacy Catalogue (GSWLC-2; $z \sim 0.06$), and the other from the VIMOS Public Extragalactic Redshift Survey (VIPERS; $z \sim 0.65$). We cluster within a nine-dimensional feature space defined purely by rest-frame ultraviolet-through-near-infrared colours. Both samples are similarly partitioned into seven clusters, breaking down into four of mostly star-forming galaxies (including the vast majority of green valley galaxies) and three of mostly passive galaxies. The separation between these two families of clusters suggests differences in the evolution of their galaxies, and that these differences are strongly expressed in their colours alone. The samples are closely related, with star-forming/green-valley clusters at both epochs forming morphological sequences, capturing the gradual internally-driven growth of galaxy bulges. At high stellar masses, this growth is linked with quenching. However, it is only in our low-redshift sample that additional, environmental processes appear to be involved in the evolution of low-mass passive galaxies.

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arXiv2021

Active galactic nuclei catalog from the AKARI NEP Wide field

Context. The North Ecliptic Pole (NEP) field provides a unique set of panchromatic data, well suited for active galactic nuclei (AGN) studies. Selection of AGN candidates is often based on mid-infrared (MIR) measurements. Such method, despite its effectiveness, strongly reduces a catalog volume due to the MIR detection condition. Modern machine learning techniques can solve this problem by finding similar selection criteria using only optical and near-infrared (NIR) data. Aims. Aims of this work were to create a reliable AGN candidates catalog from the NEP field using a combination of optical SUBARU/HSC and NIR AKARI/IRC data and, consequently, to develop an efficient alternative for the MIR-based AKARI/IRC selection technique. Methods. A set of supervised machine learning algorithms was tested in order to perform an efficient AGN selection. Best of the models were formed into a majority voting scheme, which used the most popular classification result to produce the final AGN catalog. Additional analysis of catalog properties was performed in form of the spectral energy distribution (SED) fitting via the CIGALE software. Results. The obtained catalog of 465 AGN candidates (out of 33 119 objects) is characterized by 73% purity and 64% completeness. This new classification shows consistency with the MIR-based selection. Moreover, 76% of the obtained catalog can be found only with the new method due to the lack of MIR detection for most of the new AGN candidates. Training data, codes and final catalog are available via the github repository. Final AGN candidates catalog will be also available via the CDS service after publication.

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arXiv2021

An Active Galactic Nucleus Recognition Model based on Deep Neural Network

To understand the cosmic accretion history of supermassive black holes, separating the radiation from active galactic nuclei (AGNs) and star-forming galaxies (SFGs) is critical. However, a reliable solution on photometrically recognising AGNs still remains unsolved. In this work, we present a novel AGN recognition method based on Deep Neural Network (Neural Net; NN). The main goals of this work are (i) to test if the AGN recognition problem in the North Ecliptic Pole Wide (NEPW) field could be solved by NN; (ii) to shows that NN exhibits an improvement in the performance compared with the traditional, standard spectral energy distribution (SED) fitting method in our testing samples; and (iii) to publicly release a reliable AGN/SFG catalogue to the astronomical community using the best available NEPW data, and propose a better method that helps future researchers plan an advanced NEPW database. Finally, according to our experimental result, the NN recognition accuracy is around 80.29% - 85.15%, with AGN completeness around 85.42% - 88.53% and SFG completeness around 81.17% - 85.09%.

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arXiv2021

Viewing angle effects in quasar application to cosmology

The symmetry axes of active galactic nuclei (AGN) are randomly distributed in space but highly inclined sources are heavily obscured and are not seen as quasars with broad emission lines. The obscuring torus geometry determines the average viewing angle, and if the torus geometry changes with the redshift, this average viewing angle will also change. Thus the ratio between the isotropic luminosity and observed luminosity may change systematically with redshift. Therefore, if we use quasars to measure the luminosity distance by evaluating the isotropic absolute luminosity and measuring the observed flux, we can have a redshift-dependent bias which can propagate to cosmological parameters. We propose a toy model for testing the effect of viewing angle uncertainty on measurement of the luminosity distance. The model is based on analytical description of the obscuring torus applied to one-parameter observational data. It illustrates the possible change of the torus covering factor between the two chosen redshift ranges. We have estimated the possible error on specific cosmological parameters (H0,Omega_m) for the flat Lambda-CDM cosmology if a method is calibrated at low redshift and applied to the higher redshift. The errors on cosmological parameters due to potential dependence of viewing angle on redshift are found to be potentially significant, and the effect will have to be accommodated in the future in all quasar-based cosmological methods. A careful systematic study of AGN mean viewing angle across redshift is necessary, with the use of appropriate samples and models which uniquely determine the inclination of each source.

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arXiv2020

Photometric Redshifts in the North Ecliptic Pole Wide Field based on a Deep Optical Survey with Hyper Suprime-Cam

The $AKARI$ space infrared telescope has performed near- to mid-infrared (MIR) observations on the North Ecliptic Pole Wide (NEPW) field (5.4 deg$^2$) for about one year. $AKARI$ took advantage of its continuous nine photometric bands, compared with NASA's $Spitzer$ and WISE space telescopes, which had only four filters with a wide gap in the MIR. The $AKARI$ NEPW field lacked deep and homogeneous optical data, limiting the use of nearly half of the IR sources for extra-galactic studies owing to the absence of photometric redshifts (photo-zs). To remedy this, we have recently obtained deep optical imaging over the NEPW field with 5 bands ($g$, $r$, $i$, $z$, and $Y$) of the Hyper Suprime-Camera (HSC) on the Subaru 8m telescope. We optically identify AKARI-IR sources along with supplementary $Spitzer$ and WISE data as well as pre-existing optical data. In this work, we derive new photo-zs using a $χ^2$ template-fitting method code ($Le$ $Phare$) and reliable photometry from 26 selected filters including HSC, $AKARI$, CFHT, Maidanak, KPNO, $Spitzer$ and WISE data. We take 2026 spectroscopic redshifts (spec-z) from all available spectroscopic surveys over the NEPW to calibrate and assess the accuracy of the photo-zs. At z < 1.5, we achieve a weighted photo-z dispersion of $σ_{Δ{z/(1+z)}}$ = 0.053 with $η$ = 11.3% catastrophic errors.

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arXiv2020

Identification of AKARI infrared sources by Deep HSC Optical Survey: Construction of New Band-Merged Catalogue in the NEP-Wide field

The north ecliptic pole (NEP) field is a natural deep field location for many satellite observations. It has been targeted manytimes since it was surveyed by the AKARI space telescope with its unique wavelength coverage from the near- to mid-infrared(mid-IR). Many follow-up observations have been carried out and made this field one of the most frequently observed areas witha variety of facilities, accumulating abundant panchromatic data from X-ray to radio wavelength range. Recently, a deep opticalsurvey with the Hyper Suprime-Cam (HSC) at the Subaru telescope covered the NEP-Wide (NEPW) field, which enabled us toidentify faint sources in the near- and mid-IR bands, and to improve the photometric redshift (photo-z) estimation. In this work,we present newly identified AKARI sources by the HSC survey, along with multi-band photometry for 91,861 AKARI sourcesobserved over the NEPW field. We release a new band-merged catalogue combining various photometric data from GALEXUV to the submillimetre (sub-mm) bands (e.g., Herschel/SPIRE, JCMT/SCUBA-2). About 20,000 AKARI sources are newlymatched to the HSC data, most of which seem to be faint galaxies in the near- to mid-infrared AKARI bands. This cataloguemotivates a variety of current research, and will be increasingly useful as recently launched (eROSITA/ART-XC) and futurespace missions (such as JWST, Euclid, and SPHEREx) plan to take deep observations in the NEP field.

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arXiv2020

Extinction-free Census of AGNs in the $AKARI$/IRC North Ecliptic Pole Field from 23-band Infrared Photometry from Space Telescopes

In order to understand the interaction between the central black hole and the whole galaxy or their co-evolution history along with cosmic time, a complete census of active galactic nuclei (AGN) is crucial. However, AGNs are often missed in optical, UV and soft X-ray observations since they could be obscured by gas and dust. A mid-infrared (mid-IR) survey supported by multiwavelength data is one of the best ways to find obscured AGN activities because it suffers less from extinction. Previous large IR photometric surveys, e.g., $WISE$ and $Spitzer$, have gaps between the mid-IR filters. Therefore, star forming galaxy (SFG)-AGN diagnostics in the mid-IR were limited. The $AKARI$ satellite has a unique continuous 9-band filter coverage in the near to mid-IR wavelengths. In this work, we take advantage of the state-of-the-art spectral energy distribution (SED) modelling software, CIGALE, to find AGNs in mid-IR. We found 126 AGNs in the NEP-Wide field with this method. We also investigate the energy released from the AGN as a fraction of the total IR luminosity of a galaxy. We found that the AGN contribution is larger at higher redshifts for a given IR luminosity. With the upcoming deep IR surveys, e.g., $JWST$, we expect to find more AGNs with our method.

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arXiv2020

Space Project for Astrophysical and Cosmological Exploration (SPACE), an ESA stand-alone mission and a possible contribution to the Origins Space Telescope

We propose a new mission called Space Project for Astrophysical and Cosmological Exploration (SPACE) as part on the ESA long term planning Voyage 2050 programme. SPACE will study galaxy evolution at the earliest times, with the key goals of charting the formation of the heavy elements, measuring the evolution of the galaxy luminosity function, tracing the build-up of stellar mass in galaxies over cosmic time, and finding the first super-massive black holes (SMBHs) to form. The mission will exploit a unique region of the parameter space, between the narrow ultra-deep surveys with HST and JWST, and shallow wide-field surveys such as Roman Space Telescope and EUCLID, and should yield by far the largest sample of any current or planned mission of very high redshift galaxies at z > 10 which are sufficiently bright for detailed follow-up spectroscopy. Crucially, we propose a wide-field spectroscopic near-IR + mid-IR capability which will greatly enhance our understanding of the first galaxies by detecting and identifying a statistical sample of the first galaxies and the first SMBH, and to chart the metal enrichment history of galaxies in the early Universe - potentially finding signatures of the very first stars to form from metal-free primordial gas. The wide-field and wavelength range of SPACE will also provide us a unique opportunity to study star formation by performing a wide survey of the Milky Way in the near-IR + mid-IR. This science project can be enabled either by a stand-alone ESA-led M mission or by an instrument for an L mission (with ESA and/or NASA, JAXA and other international space agencies) with a wide-field (sub-)millimetre capability at wavelength > 500 microns.

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arXiv2019

AGN selection in the AKARI NEP deep field with the fuzzy SVM algorithm

The aim of this work is to create a new catalog of reliable AGN candidates selected from the AKARI NEP-Deep field. Selection of the AGN candidates was done by applying a fuzzy SVM algorithm, which allows to incorporate measurement uncertainties into the classification process. The training dataset was based on the spectroscopic data available for selected objects in the NEP-Deep and NEP-Wide fields. The generalization sample was based on the AKARI NEP-Deep field data including objects without optical counterparts and making use of the infrared information only. A high quality catalog of previously unclassified 275 AGN candidates was prepared.

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arXiv2017

Searching for previously unknown classes of objects in the AKARI-NEP Deep data with fuzzy logic SVM algorithm

In this proceedings application of a fuzzy Support Vector Machine (FSVM) learning algorithm, to classify mid-infrared (MIR) sources from the AKARI NEP Deep field into three classes: stars, galaxies and AGNs, is presented. FSVM is an improved version of the classical SVM algorithm, incorporating measurement errors into the classification process; this is the first successful application of this algorithm in the astronomy. We created reliable catalogues of galaxies, stars and AGNs consisting of objects with MIR measurements, some of them with no optical counterparts. Some examples of identified objects are shown, among them O-rich and C-rich AGB stars.

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arXiv2017

Exploring cosmic origins with CORE: gravitational lensing of the CMB

Lensing of the CMB is now a well-developed probe of large-scale clustering over a broad range of redshifts. By exploiting the non-Gaussian imprints of lensing in the polarization of the CMB, the CORE mission can produce a clean map of the lensing deflections over nearly the full-sky. The number of high-S/N modes in this map will exceed current CMB lensing maps by a factor of 40, and the measurement will be sample-variance limited on all scales where linear theory is valid. Here, we summarise this mission product and discuss the science that it will enable. For example, the summed mass of neutrinos will be determined to an accuracy of 17 meV combining CORE lensing and CMB two-point information with contemporaneous BAO measurements, three times smaller than the minimum total mass allowed by neutrino oscillations. In the search for B-mode polarization from primordial gravitational waves with CORE, lens-induced B-modes will dominate over instrument noise, limiting constraints on the gravitational wave power spectrum amplitude. With lensing reconstructed by CORE, one can "delens" the observed polarization internally, reducing the lensing B-mode power by 60%. This improves to 70% by combining lensing and CIB measurements from CORE, reducing the error on the gravitational wave amplitude by 2.5 compared to no delensing (in the null hypothesis). Lensing measurements from CORE will allow calibration of the halo masses of the 40000 galaxy clusters that it will find, with constraints dominated by the clean polarization-based estimators. CORE can accurately remove Galactic emission from CMB maps with its 19 frequency channels. We present initial findings that show that residual Galactic foreground contamination will not be a significant source of bias for lensing power spectrum measurements with CORE. [abridged]

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arXiv2016

Towards automatic classification of all WISE sources

The WISE satellite has detected hundreds of millions sources over the entire sky. Classifying them reliably is however a challenging task due to degeneracies in WISE multicolour space and low levels of detection in its two longest-wavelength bandpasses. Here we aim at obtaining comprehensive and reliable star, galaxy and quasar catalogues based on automatic source classification in full-sky WISE data. This means that the final classification will employ only parameters available from WISE itself, in particular those reliably measured for a majority of sources. For the automatic classification we applied the support vector machines (SVM) algorithm, which requires a training sample with relevant classes already identified, and we chose to use the SDSS spectroscopic dataset for that purpose. By calibrating the classifier on the test data drawn from SDSS, we first established that a polynomial kernel is preferred over a radial one for this particular dataset. Next, using three classification parameters (W1 magnitude, W1-W2 colour, and a differential aperture magnitude) we obtained very good classification efficiency in all the tests. At the bright end, the completeness for stars and galaxies reaches ~95%, deteriorating to ~80% at W1=16 mag, while for quasars it stays at a level of ~95% independently of magnitude. Similar numbers are obtained for purity. Application of the classifier to full-sky WISE data, flux-limited to 16 mag (Vega) in the 3.4 μm channel, and appropriate a posteriori cleaning allowed us to obtain reliably-looking catalogues of star and galaxy candidates. However, the sources flagged by the classifier as `quasars' are in fact dominated by dusty galaxies but also exhibit contamination from sources located mainly at low ecliptic latitudes, consistent with Solar System objects. [abridged]

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arXiv2015

Learning algorithms at the service of WISE survey

We have undertaken a dedicated program of automatic source classification in the WISE database merged with SuperCOSMOS scans, comprehensively identifying galaxies, quasars and stars on most of the unconfused sky. We use the Support Vector Machines classifier for that purpose, trained on SDSS spectroscopic data. The classification has been applied to a photometric dataset based on all-sky WISE 3.4 and 4.6 $μ$m information cross-matched with SuperCOSMOS B and R bands, which provides a reliable sample of $\sim170$ million sources, including galaxies at $z_{\rm med}\sim0.2$, as well as quasars and stars. The results of our classification method show very high purity and completeness (more than 96\%) of the separated sources, and the resultant catalogs can be used for sophisticated analyses, such as generating all-sky photometric redshifts.

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arXiv2015

Automatised classification of WISE sources: first results, future prospects

We present the first results of our dedicated programme of automatised classification of galaxies, stars and quasars in the mid-infrared all-sky data from the WISE survey. We employ the Support Vector Machines (SVM) algorithm, which defines a hyperplane separating different classes of sources in a multidimensional space of arbitrarily chosen parameters. This approach consists of four general steps: 1) selection of the training sample, 2) selection of the optimal parameter space, 3) training of the classifier, 4) application to target data. Here, as the training set, we use sources from a cross-correlation of the WISE catalogue with the SDSS spectroscopic sample. The performance of the SVM classifier was tested as a function of size of the training set, dimension of the parameter space, WISE apparent magnitude and Galactic extinction. We find that our classifier provides promising results already for three classification parameters: magnitude, colour and differential aperture magnitude. Completeness and purity levels as high as 95% are obtained for quasars, while for galaxies and stars they vary between 80-95% depending on the magnitude, deteriorating for fainter sources.

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arXiv2012

Problems of Clustering of Radiogalaxies

We present the preliminary analysis of clustering of a sample of 1157 radio-identified galaxies from Machalski & Condon (1999). We found that for separations $2-15 h^{-1}$Mpc their redshift space autocorrelation function $ξ(s)$ can be approximated by the power law with the correlation length $\sim 3.75h^{-1}$Mpc and slope $γ\sim 1.8$. The correlation length for radiogalaxies is found to be lower and the slope steeper than the corresponding parameters of the control sample of optically observed galaxies. Analysis the projected correlation function $Ξ(r)$ displays possible differences in the clustering properties between active galactic nuclei (AGN) and starburst (SB) galaxies.

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arXiv2012

The North Ecliptic Pole Wide survey of AKARI: a near- and mid-infrared source catalog

We present a photometric catalog of infrared (IR) sources based on the North Ecliptic PoleWide field (NEP-Wide) survey of AKARI, which is an infrared space telescope launched by Japan. The NEP-Wide survey covered 5.4 deg2 area, a nearly circular shape centered on the North Ecliptic Pole, using nine photometric filter-bands from 2 - 25 μm of the Infrared Camera (IRC). Extensive efforts were made to reduce possible false objects due to cosmic ray hits, multiplexer bleeding phenomena around bright sources, and other artifacts. The number of detected sources varied depending on the filter band: with about 109,000 sources being cataloged in the near-IR bands at 2 - 5 μm, about 20,000 sources in the shorter parts of the mid-IR bands between 7 - 11 μm, and about 16,000 sources in the longer parts of the mid-IR bands, with \sim 4,000 sources at 24 μm. The estimated 5? detection limits are approximately 21 magnitude (mag) in the 2 - 5 μm bands, 19.5 - 19 mag in the 7 - 11 μm, and 18.8 - 18.5 mag in the 15 - 24 μm bands in the AB magnitude scale. The completenesses for those bands were evaluated as a function of magnitude: the 50% completeness limits are about 19.8 mag at 3 μm, 18.6 mag at 9 μm, and 18 mag at 18 μm band, respectively. To construct a reliable source catalog, all of the detected sources were examined by matching them with those in other wavelength data, including optical and ground-based near-IR bands. The final band-merged catalog contains about 114,800 sources detected in the IRC filter bands. The properties of the sources are presented in terms of the distributions in various color-color diagrams.

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arXiv2010

Star-galaxy separation by far-infrared color-color diagrams for the AKARI FIS All-Sky Survey (Bright Source Catalogue Version beta-1)

To separate stars and galaxies in the far infrared AKARI All-Sky Survey data, we have selected a sample with the complete color information available in the low extinction regions of the sky and constructed color-color plots for these data. We looked for the method to separate stars and galaxies using the color information. We performed an extensive search for the counterparts of these selected All-Sky Survey sources in the NED and SIMBAD databases. Among 5176 objects, we found 4272 galaxies, 382 other extragalactic objects, 349 Milky Way stars, 50 other Galactic objects, and 101 sources detected before in various wavelengths but of an unknown origin. 22 sources were left unidentified. Then, we checked colors of stars and galaxies in the far-infrared flux-color and color-color plots. In the resulting diagrams, stars form two clearly separated clouds. One of them is easy to be distinguished from galaxies and allows for a simple method of excluding a large part of stars using the far-infrared data. The other smaller branch, overplotting galaxies, consists of stars known to have an infrared excess, like Vega and some fainter stars discovered by IRAS or 2MASS. The color properties of these objects in any case make them very difficult to distinguish from galaxies. We conclude that the FIR color-color diagrams allow for a high-quality star-galaxy separation. With the proposed simple method we can select more that 95 % of galaxies rejecting at least 80 % of stars.

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arXiv2009

Post-starburst galaxies: more than just an interesting curiosity

From the VIMOS VLT DEEP Survey (VVDS) we select a sample of 16 galaxies with spectra which identify them as having recently undergone a strong starburst and subsequent fast quenching of star formation. These post-starburst galaxies lie in the redshift range 0.5 10^9.75Msun. They have a number density of 1x10^-4 per Mpc^3, almost two orders of magnitude sparser than the full galaxy population with the same mass limit. We compare with simulations to show that the galaxies are consistent with being the descendants of gas rich major mergers. Starburst mass fractions must be larger than ~5-10% and decay times shorter than ~10^8 years for post-starburst spectral signatures to be observed in the simulations. We find that the presence of black hole feedback does not greatly affect the evolution of the simulated merger remnants through the post-starburst phase. The multiwavelength spectral energy distributions of the post-starburst galaxies show that 5/16 have completely ceased the formation of new stars. These 5 galaxies correspond to a mass flux entering the red-sequence of rhodot(A->Q, PSB) = 0.0038Msun/Mpc^3/yr, assuming the defining spectroscopic features are detectable for 0.35Gyr. If the galaxies subsequently remain on the red sequence, this accounts for 38(+4/-11)% of the growth rate of the red sequence. Finally, we compare our high redshift results with a sample of galaxies with 0.05<z<0.1 observed in the SDSS and UKIDSS surveys. We find a very strong redshift evolution: the mass density of strong post-starburst galaxies is 230 times lower at z~0.07 than at z~0.7.

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