ABSTRACT
In this series of papers, we employ several machine learning (ML) methods to classify the point-like sources from the miniJPAS catalogue, and identify quasar candidates. Since no ...representative sample of spectroscopically confirmed sources exists at present to train these ML algorithms, we rely on mock catalogues. In this first paper, we develop a pipeline to compute synthetic photometry of quasars, galaxies, and stars using spectra of objects targeted as quasars in the Sloan Digital Sky Survey. To match the same depths and signal-to-noise ratio distributions in all bands expected for miniJPAS point sources in the range 17.5 ≤ r < 24, we augment our sample of available spectra by shifting the original r-band magnitude distributions towards the faint end, ensure that the relative incidence rates of the different objects are distributed according to their respective luminosity functions, and perform a thorough modelling of the noise distribution in each filter, by sampling the flux variance either from Gaussian realizations with given widths, or from combinations of Gaussian functions. Finally, we also add in the mocks the patterns of non-detections which are present in all real observations. Although the mock catalogues presented in this work are a first step towards simulated data sets that match the properties of the miniJPAS observations, these mocks can be adapted to serve the purposes of other photometric surveys.
ABSTRACT
Astrophysical surveys rely heavily on the classification of sources as stars, galaxies, or quasars from multiband photometry. Surveys in narrow-band filters allow for greater discriminatory ...power, but the variety of different types and redshifts of the objects present a challenge to standard template-based methods. In this work, which is part of a larger effort that aims at building a catalogue of quasars from the miniJPAS survey, we present a machine learning-based method that employs convolutional neural networks (CNNs) to classify point-like sources including the information in the measurement errors. We validate our methods using data from the miniJPAS survey, a proof-of-concept project of the Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS) collaboration covering ∼1 deg2 of the northern sky using the 56 narrow-band filters of the J-PAS survey. Due to the scarcity of real data, we trained our algorithms using mocks that were purpose-built to reproduce the distributions of different types of objects that we expect to find in the miniJPAS survey, as well as the properties of the real observations in terms of signal and noise. We compare the performance of the CNNs with other well-established machine learning classification methods based on decision trees, finding that the CNNs improve the classification when the measurement errors are provided as inputs. The predicted distribution of objects in miniJPAS is consistent with the putative luminosity functions of stars, quasars, and unresolved galaxies. Our results are a proof of concept for the idea that the J-PAS survey will be able to detect unprecedented numbers of quasars with high confidence.
A 3D model of polarized dust emission in the Milky Way Martínez-Solaeche, Ginés; Karakci, Ata; Delabrouille, Jacques
Monthly notices of the Royal Astronomical Society,
05/2018, Letnik:
476, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Abstract
We present a three-dimensional model of polarized galactic dust emission that takes into account the variation of the dust density, spectral index and temperature along the line of sight, ...and contains randomly generated small-scale polarization fluctuations. The model is constrained to match observed dust emission on large scales, and match on smaller scales extrapolations of observed intensity and polarization power spectra. This model can be used to investigate the impact of plausible complexity of the polarized dust foreground emission on the analysis and interpretation of future cosmic microwave background polarization observations.
The miniJPAS survey quasar selection Pérez-Ràfols, Ignasi; Abramo, Luis Raul; Martínez-Solaeche, Ginés ...
Astronomy and astrophysics (Berlin),
10/2023, Letnik:
678
Journal Article
Recenzirano
Odprti dostop
Aims
. Quasar catalogues from photometric data are used in a variety of applications including those targeting spectroscopic follow-up, measurements of supermassive black hole masses, Baryon Acoustic ...Oscillations, or non-Gaussianities. Here, we present a list of quasar candidates including photometric redshift estimates from the miniJPAS Data Release constructed using SQUEzE. miniJPAS is a small proof-of-concept survey covering 1 deg
2
with the full J-PAS filter system, consisting of 54 narrow filters and 2 broader filters covering the entire optical wavelength range.
Methods
. This work is based on the machine-learning classification of photometric data of quasar candidates using SQUEzE. It has the advantage that its classification procedure can be explained to some extent, making it less of a ‘black box’ when compared with other classifiers. Another key advantage is that the use of user-defined metrics means the user has more control over the classification. While SQUEzE was designed for spectroscopic data, we have adapted it for multi-band photometric data; that is we treat multiple narrow-band filters as very low-resolution spectra. We trained our models using specialised mocks. We estimated our redshift precision using the normalised median absolute deviation,
σ
NMAD
, applied to our test sample.
Results
. Our test sample returns an
f
1
score (effectively the purity and completeness) of 0.49 for high-
z
quasars (with
z
≥ 2.1) down a to magnitude of
r
= 24.3 and 0.24 for low-
z
quasars (with
z
< 2.1), also down to a magnitude of
r
= 24.3. For high-
z
quasars, this goes up to 0.9 for magnitudes of
r
< 21.0. We present two catalogues of quasar candidates including redshift estimates: 301 from point-like sources and 1049 when also including extended sources. We discuss the impact of including extended sources in our predictions (they are not included in the mocks), as well as the impact of changing the noise model of the mocks. We also give an explanation of SQUEzE reasoning. Our estimates for the redshift precision using the test sample indicate a
σ
NMAD
= 0.92% for the entire sample, reduced to 0.81% for
r
< 22.5 and 0.74% for
r
< 21.3. Spectroscopic follow-up of the candidates is required in order to confirm the validity of our findings.
B-mode forecast of CMB-Bhārat Adak, Debabrata; Sen, Aparajita; Basak, Soumen ...
Monthly notices of the Royal Astronomical Society,
06/2022, Letnik:
514, Številka:
2
Journal Article
Recenzirano
Odprti dostop
ABSTRACT
Exploring Cosmic History and Origin (ECHO), popularly known as ‘CMB-Bh$\overline{a}$rat’, is a space mission that has been proposed to the Indian Space Research Organisation for the ...scientific exploitation of the cosmic microwave background (CMB) at the next level of precision and accuracy. The quest for the CMB polarization B-mode signals, generated by inflationary gravitational waves in the very early universe, is one of the key scientific goals of its experimental design. This work studies the potential of the proposed ECHO instrumental configuration to detect the target tensor-to-scalar ratio r ∼ 10−3 at 3σ significance level, which covers the predictions of a large class of inflationary models. We investigate the performance of two different component separation pipelines, ${\mathtt {NILC}}$ and ${\mathtt {Commander}}$, for the measurement of r in the presence of different physically motivated models of astrophysical foregrounds. For a simplistic foreground model (only polarized dust and synchrotron), both component separation pipelines can achieve the desired sensitivity of ECHO, i.e. σ(r = 0) ∼ (0.4–0.7) × 10−3. ${\mathtt {NILC}}$ performs better than ${\mathtt {Commander}}$ in terms of bias on recovered r for complex spectral models (power law and curved power law) of the synchrotron emission and complex dust models (dust decorrelation). Assuming 84 per cent delensing, we can achieve an improvement of σ(r = 0) by approximately 50 per cent as compared to the results obtained for the same configuration without any lensing correction.
We study the impact of black hole nuclear activity on both the global and radial star formation rate (SFR) profiles in X-ray-selected active galactic nuclei (AGN) in the field of miniJPAS, the ...precursor of the much wider J-PAS project. Our sample includes 32 AGN with $z<0.3$ detected via the XMM-Newton and Chandra surveys. For comparison, we assembled a control sample of 71 star-forming (SF) galaxies with similar magnitudes, sizes, and redshifts. To derive the global properties of both the AGN and the control SF sample, we used CIGALE to fit the spectral energy distributions derived from the 56 narrowband and 4 broadband filters from miniJPAS. We find that AGN tend to reside in more massive galaxies than their SF counterparts. After matching samples based on stellar mass and comparing their SFRs and specific SFRs (sSFRs), no significant differences appear. This suggests that the presence of AGN does not strongly influence overall star formation. However, when we used miniJPAS as an integral field unit (IFU) to dissect galaxies along their position angle, a different picture emerges. We find that AGN tend to be more centrally concentrated in mass with respect to SF galaxies. Moreover, we find a suppression of the sSFR up to 1R$ _e $ and then an enhancement beyond 1R$ _e $, strongly contrasting with the decreasing radial profile of sSFRs in SF galaxies. This could point to an inside-out quenching of AGN host galaxies. Additionally, we examined how the radial profiles of the sSFRs in AGN and SF galaxies depend on galaxy morphology, by dividing our sample into disk-dominated (DD), pseudo-bulge (PB), and bulge-dominated (BD) systems. In DD systems, AGN exhibit a flat sSFR profile in the central regions and enhanced star formation beyond 1R$ _e $, contrasting with SF galaxies. In PB systems, SF galaxies show a decreasing sSFR profile, while AGN hosts exhibit an inside-out quenching scenario. In BD systems, both populations demonstrate consistent flat sSFR profiles. These findings suggest that the reason we do not see differences on a global scale is because star formation is suppressed in the central regions and enhanced in the outer regions of AGN host galaxies. While limited in terms of sample size, this work highlights the potential of the upcoming J-PAS as a wide-field low-resolution IFU for thousands of nearby galaxies and AGN.
We present a three-dimensional model of polarised galactic dust emission that takes into account the variation of the dust density, spectral index and temperature along the line of sight, and ...contains randomly generated small scale polarisation fluctuations. The model is constrained to match observed dust emission on large scales, and match on smaller scales extrapolations of observed intensity and polarisation power spectra. This model can be used to investigate the impact of plausible complexity of the polarised dust foreground emission on the analysis and interpretation of future CMB polarisation observations.
Exploring Cosmic History and Origins (ECHO), popularly known as
`CMB-Bh$\overline{a}$rat', is a space mission that has been proposed to the
Indian Space Research Organisation (ISRO) for the ...scientific exploitation of
the Cosmic Microwave Background (CMB) at the next level of precision and
accuracy. The quest for the CMB polarization $B$-mode signals, generated by
inflationary gravitational waves in the very early universe, is one of the key
scientific goals of its experimental design. This work studies the potential of
the proposed ECHO instrumental configuration to detect the target
tensor-to-scalar ratio $r \sim 10^{-3}$ at $3\sigma$ significance level, which
covers the predictions of a large class of inflationary models. We investigate
the performance of two different component separation pipelines, NILC and
Commander, for the measurement of $r$ in presence of different physically
motivated models of astrophysical foregrounds. For a simplistic foreground
model (only polarized dust and synchrotron), both component separation
pipelines can achieve the desired sensitivity of ECHO, i.e. $\sigma (r =0) \sim
(0.4 - 0.7)\times 10^{-3}$. NILC performs better than Commander in terms of
bias on recovered $r$ for complex spectral models (power-law and curved
power-law) of the synchrotron emission and complex dust models (dust
decorrelation). Assuming 84 % delensing, we can achieve an improvement of
$\sigma (r = 0)$ by approximately 50 % as compared to the results obtained for
the same configuration without any lensing correction.
We study the impact of black hole nuclear activity on both the global and radial star formation rate (SFR) profiles in X-ray-selected active galactic nuclei (AGN) in the field of miniJPAS, the ...precursor of the much wider J-PAS project. Our sample includes 32 AGN with z < 0.3 detected via the XMM-Newton and Chandra surveys. For comparison, we assembled a control sample of 71 star-forming (SF) galaxies with similar magnitudes, sizes, and redshifts. To derive the global properties of both the AGN and the control SF sample, we used CIGALE to fit the spectral energy distributions derived from the 56 narrowband and 4 broadband filters from miniJPAS. We find that AGN tend to reside in more massive galaxies than their SF counterparts. After matching samples based on stellar mass and comparing their SFRs and specific SFRs (sSFRs), no significant differences appear. This suggests that the presence of AGN does not strongly influence overall star formation. However, when we used miniJPAS as an integral field unit (IFU) to dissect galaxies along their position angle, a different picture emerges. We find that AGN tend to be more centrally concentrated in mass with respect to SF galaxies. Moreover, we find a suppression of the sSFR up to 1Re and then an enhancement beyond 1Re , strongly contrasting with the decreasing radial profile of sSFRs in SF galaxies. This could point to an inside-out quenching of AGN host galaxies. These findings suggest that the reason we do not see differences on a global scale is because star formation is suppressed in the central regions and enhanced in the outer regions of AGN host galaxies. While limited in terms of sample size, this work highlights the potential of the upcoming J-PAS as a wide-field low-resolution IFU for thousands of nearby galaxies and AGN.
We present a list of quasar candidates including photometric redshift estimates from the miniJPAS Data Release constructed using SQUEzE. This work is based on machine-learning classification of ...photometric data of quasar candidates using SQUEzE. It has the advantage that its classification procedure can be explained to some extent, making it less of a `black box' when compared with other classifiers. Another key advantage is that using user-defined metrics means the user has more control over the classification. While SQUEzE was designed for spectroscopic data, here we adapt it for multi-band photometric data, i.e. we treat multiple narrow-band filters as very low-resolution spectra. We train our models using specialized mocks from Queiroz et al. (2022). We estimate our redshift precision using the normalized median absolute deviation, \(\sigma_{\rm NMAD}\) applied to our test sample. Our test sample returns an \(f_1\) score (effectively the purity and completeness) of 0.49 for quasars down to magnitude \(r=24.3\) with \(z\geq2.1\) and 0.24 for quasars with \(z<2.1\). For high-z quasars, this goes up to 0.9 for \(r<21.0\). We present two catalogues of quasar candidates including redshift estimates: 301 from point-like sources and 1049 when also including extended sources. We discuss the impact of including extended sources in our predictions (they are not included in the mocks), as well as the impact of changing the noise model of the mocks. We also give an explanation of SQUEzE reasoning. Our estimates for the redshift precision using the test sample indicate a \(\sigma_{NMAD}=0.92\%\) for the entire sample, reduced to 0.81\% for \(r<22.5\) and 0.74\% for \(r<21.3\). Spectroscopic follow-up of the candidates is required in order to confirm the validity of our findings.
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