arXiv subjects

Katarzyna Małek

Publications and source records attributed to Katarzyna Małek.

28 records · Page 2Linked to original sources

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.

astro-ph.GA↗

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

Limits on the flux of nuclearites and other heavy compact objects from the "Pi of the Sky" project

Many theories predict the existence of very heavy compact objects, that in terms of sizes would belong to the realms of nuclear or atomic physics, but in terms of masses could extend to the macroscopic world, reaching kilograms, tonnes or more. If they exist, it is likely that they reach our planet with high speeds and cross the atmosphere. Due to their high mass to size ratio and huge energy, in many cases, they would leave behind a trail in the form of sound and seismic waves, etches, or light in transparent media. Here we show results of a search for such objects in visual photographs of the sky taken by the "Pi of the Sky" experiment, illustrated with the most stringent limits on the isotropic flux of incoming so-called nuclearites, spanning between $5.4\cdot10^{-20}$ and $2.2\cdot10^{-21}\ \mathrm{cm}^{-2} \mathrm{s}^{-1} \mathrm{sr}^{-1}$ for masses between 100 g and 100 kg. In addition we establish a directional flux limit under an assumption of static "sea" of nuclearites in the Galaxy, which spans between $1.5\cdot10^{-18}$ and $2.1\cdot10^{-19}\ \mathrm{cm}^{-2} \mathrm{s}^{-1}$ in the same mass range. The general nature of the limits presented should allow one to constrain many specific models predicting the existence of heavy compact objects and both particle physics and astrophysical processes leading to their creation, and their sources.

astro-ph.HE↗

arXiv2019

HELP: A catalogue of 170 million objects, selected at 0.36-4.5 $μ$m, from 1270 deg.$^{2}$ of prime extragalactic fields

We present an optical to near-infrared selected astronomical catalogue covering 1270 deg.$^2$. This is the first attempt to systematically combine data from 23 of the premier extragalactic survey fields - the product of a vast investment of telescope time. The fields are those imaged by the Herschel Space Observatory which form the Herschel Extragalactic Legacy Project (HELP). Our catalogue of 170 million objects is constructed by a positional cross match of 51 public surveys. This high resolution optical, near-infrared, and mid-infrared catalogue is designed for photometric redshift estimation, extraction of fluxes in lower resolution far-infrared maps, and spectral energy distribution modelling. It collates, standardises, and provides value added derived quantities including corrected aperture magnitudes and astrometry correction over the Herschel extragalactic wide fields for the first time. $grizy$ fluxes are available on all fields with $g$ band data reaching $5σ$ point-source depths in a 2 arcsec aperture of 23.5, 24.4, and 24.6 (AB) mag at the 25th, 50th, and 75th percentiles, by area covered, across all HELP fields. It has $K$ or $K_s$ coverage over 1146 deg.$^2$ with depth percentiles of 20.2, 20.4, and 21.0 mag respectively. The IRAC Ch 1 band is available over 273 deg.$^2$ with depth percentiles of 17.7, 21.4, and 22.2 mag respectively. This paper defines the "masterlist" objects for the first data release (DR1) of HELP. This large sample of standardised total and corrected aperture fluxes, uniform quality flags, and completeness measures provides large well understood statistical samples over the full Herschel extragalactic sky.

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arXiv2018

Strong FeII emission in NLS1s: An unsolved mystery

The work initially started as a test to retrace the Shen & Ho (2014) Quasar Main Sequence diagram where they claimed that the parameter RFeII, which defines the Eigenvector 1 (EV1) is driven by the Eddington ratio alone. We subsequently construct a refined (error and redshift limited) sample from the original Shen et al. 2011 QSO catalogue. Based on our hypothesis - the main driver of the Quasar Main Sequence is the maximum of the accretion disk temperature defined by the Big Blue Bump on the Spectral Energy Distribution. We select the four extreme sources that have RFeII $\geq$ 4.0 and use the SED modelling code CIGALE to fit the multi-band photometric data for these sources. We also perform detailed spectral fitting including the FeII pseudo-continuum to estimate and compare the value of RFeII for them. We show the metallicity dependent FeII strength in the context of this study.

astro-ph.HE↗

arXiv2018

Using vo tools to iNvestIgate Quasar Spectra (UNIQS)

The work initially started as a test to retrace the Shen & Ho (2014) Quasar Main Sequence diagram where they (and references therein) claimed that the parameter RFeII, which defines the Eigenvector 1 (EV1) is driven by the Eddington ratio alone. We subsequently construct a refined (error and redshift limited) sample from the original Shen et. al (2011) QSO catalogue. Based on our hypothesis - the main driver of the Quasar Main Sequence is the maximum of the accretion disk temperature defined by the Big Blue Bump on the Spectral Energy Distribution. We select five extreme sources that have RFeII >= 4.0 and use the SED modelling code CIGALE to fit the multi-band photometric data for these sources. Incorporating the prescription for broad emission-line species dependent virial factors, we derive the black hole masses for the entire Shen+11 catalogue and compare their distribution with the black hole masses in the original catalogue. Here, we show the results of our analysis for one of the 5 extreme sources, SDSSJ082358.30+213545.2. We also show the detailed modelling, including the Fe II pseudo-continuum to estimate and compare the value of RFeII for this object.

astro-ph.HE↗

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]

astro-ph.GA↗

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.

astro-ph.GA↗

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.

astro-ph.GA↗

arXiv2015

Evolution of mid-infrared galaxy luminosity functions from the entire AKARI NEP-Deep field with new CFHT photometry

We present infrared galaxy luminosity functions (LFs) in the AKARI North Ecliptic Pole (NEP) deep field using recently-obtained, wider CFHT optical/near-IR images. AKARI has obtained deep images in the mid-infrared (IR), covering 0.6 deg$^2$ of the NEP deep field. However, our previous work was limited to the central area of 0.25 deg$^2$ due to the lack of optical coverage of the full AKARI NEP survey. To rectify the situation, we recently obtained CFHT optical and near-IR images over the entire AKARI NEP deep field. These new CFHT images are used to derive accurate photometric redshifts, allowing us to fully exploit the whole AKARI NEP deep field. AKARI's deep, continuous filter coverage in the mid-IR wavelengths (2.4, 3.2, 4.1, 7, 9, 11, 15, 18, and 24$μ$m) exists nowhere else, due to filter gaps of other space telescopes. It allows us to estimate restframe 8$μ$m and 12$μ$m luminosities without using a large extrapolation based on spectral energy distribution (SED) fitting, which was the largest uncertainty in previous studies. Total infrared luminosity (TIR) is also obtained more reliably due to the superior filter coverage. The resulting restframe 8$μ$m, 12$μ$m, and TIR LFs at $0.15<z<2.2$ are consistent with previous works, but with reduced uncertainties, especially at the high luminosity-end, thanks to the wide field coverage. In terms of cosmic infrared luminosity density ($Ω_{\mathrm{IR}}$), we found that the $Ω_{\mathrm{IR}}$ evolves as $\propto (1+z)^{4.2\pm 0.4}$.

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