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14 results on '"Kainulainen, Jouni"'

1. Deep learning denoising by dimension reduction: Application to the ORION-B line cubes

Author

Einig, Lucas, primary, Pety, Jérôme, additional, Roueff, Antoine, additional, Vandame, Paul, additional, Chanussot, Jocelyn, additional, Gerin, Maryvonne, additional, Orkisz, Jan H., additional, Palud, Pierre, additional, Santa-Maria, Miriam G., additional, de Souza Magalhaes, Victor, additional, Bešlić, Ivana, additional, Bardeau, Sébastien, additional, Bron, Emeric, additional, Chainais, Pierre, additional, Goicoechea, Javier R., additional, Gratier, Pierre, additional, Guzmán, Viviana V., additional, Hughes, Annie, additional, Kainulainen, Jouni, additional, Languignon, David, additional, Lallement, Rosine, additional, Levrier, François, additional, Lis, Dariusz C., additional, Liszt, Harvey S., additional, Le Bourlot, Jacques, additional, Le Petit, Franck, additional, Öberg, Karin, additional, Peretto, Nicolas, additional, Roueff, Evelyne, additional, Sievers, Albrecht, additional, Thouvenin, Pierre-Antoine, additional, and Tremblin, Pascal, additional

Published
2023
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2. Revealing which Combinations of Molecular Lines are Sensitive to the Gas Physical Parameters of Molecular Clouds

Author

Pety Jérôme, Gerin Maryvonne, Bron Emeric, Gratier Pierre, Orkisz Jan H., Palud Pierre, Roueff Antoine, Einig Lucas, Santa-Maria Miriam G., de Souza Magalhaes Victor, Bardeau Sébastien, Chanussot Jocelyn, Chainais Pierre, Goicoechea Javier R., Guzman Viviana V., Hughes Annie, Kainulainen Jouni, Languignon David, Levrier François, Lis Darek, Liszt Harvey S., Le Bourlot Jacques, Le Petit Franck, Oberg Karin, Peretto Nicolas, Roueff Evelyne, Sievers Albrecht, Thouvenin Pierre-Antoine, and Tremblin Pascal

Subjects
Physics, QC1-999
Abstract

Atoms and molecules have long been thought to be versatile tracers of the cold neutral gas in the universe, from high-redshift galaxies to star forming regions and proto-planetary disks, because their internal degrees of freedom bear the signature of the physical conditions where these species reside. However, the promise that molecular emission has a strong diagnostic power of the underlying physical and chemical state is still hampered by the difficulty to combine sophisticated chemical codes with gas dynamics. It is therefore important 1) to acquire self-consistent data sets that can be used as templates for this theoretical work, and 2) to reveal the diagnostic capabilities of molecular lines accurately. The advent of sensitive wideband spectrometers in the (sub)- millimeter domain (e.g., IRAM-30m/EMIR, NOEMA, …) during the 2010s has allowed us to image a significant fraction of a Giant Molecular Cloud with enough sensitivity to detect tens of molecular lines in the 70 – 116 GHz frequency range. Machine learning techniques applied to these data start to deliver the next generation of molecular line diagnostics of mass, density, temperature, and radiation field.

Published
2022
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3. Learning from model grids: Tracers of the ionization fraction in the ISM

Author

Bron Emeric, Roueff Evelyne, Gerin Maryvonne, Pety Jérôme, Gratier Pierre, Le Petit Franck, Guzman Viviana, Orkisz Jan, de Souza Magalhaes Victor, Gaudel Mathilde, Palud Pierre, Einig Lucas, Bardeau Sébastien, Chainais Pierre, Chanussot Jocelyn, Goicoechea Javier, Hughes Annie, Kainulainen Jouni, Languignon David, Le Bourlot Jacques, Levrier François, Lis Darek, Liszt Harvey, Öberg Karin, Peretto Nicolas, Roueff Antoine, Sievers Albrecht, Thouvenin Pierre-Antoine, and Tremblin Pascal

Subjects
Physics, QC1-999
Abstract

The ionization fraction in neutral interstellar clouds is a key physical parameter controlling multiple physical and chemical processes, and varying by orders of magnitude from the UV irradiated surface of the cloud to its cosmic-ray dominated central regions. Traditional observational tracers of the ionization fraction, which mostly rely on deuteration ratios of molecules like HCO+, suffer from the fact that the deuterated molecules are only detected in a tiny fraction of a given Giant Molecular Cloud (GMC). In [1], we propose a machine learning-based, semi-automatic method to search in a large dataset of astrochemical model results for new tracers of the ionization fraction, and propose several new tracers relevant in different ranges of physical conditions.

Published
2022
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4. Deep learning denoising by dimension reduction: Application to the ORION-B line cubes

Author

Centre National de la Recherche Scientifique (France), Agence Nationale de la Recherche (France), Centre National D'Etudes Spatiales (France), Ministerio de Ciencia e Innovación (España), National Aeronautics and Space Administration (US), Universities Space Research Association (US), Einig, Lucas [0000-0003-4250-7638], Pety, Jérôme [0000-0003-3061-6546], #NODATA#, Chanussot, Jocelyn [0000-0003-4817-2875], Gerin, Maryvonne [0000-0002-2418-7952], Orkisz, Jan H. [0000-0002-3382-9208], Palud, Pierre [0000-0002-5850-6325], Santa-María, Miriam G. [0000-0002-3941-0360], Bešlić, Ivana [0000-0003-0583-7363], Bron, Emeric E. [0000-0003-1532-7818], Chainais,Pierre [0000-0003-4377-7584], Goicoechea, Javier R. [0000-0001-7046-4319], Gratier, Pierre [0000-0002-6636-4304], Lis, Dariuscz C. [0000-0002-0500-4700], Le Bourlot,Jacques [0000-0003-3920-8063], Le Petit, Franck [0000-0001-8738-6724], Roueff, Evelyne [0000-0002-4949-8562], Sievers, Albrecht [0000-0003-0151-2924], Thouvenin, Pierre-Antoine [0000-0003-1246-9458], Einig, Lucas, Pety, Jérôme, Roueff, Antoine, Vandame, Paul, Chanussot, Jocelyn, Gerin, Maryvonne, Orkisz, Jan H., Palud, Pierre, Santa-María, Miriam G., Souza Magalhaes, Victor de, Bešlić, Ivana, Bardeau, Sébastien, Bron, Emeric E., Chainais,Pierre, Goicoechea, Javier R., Gratier, Pierre, Guzman Veloso, Viviana, Hughes, Annie, Kainulainen, Jouni, Languignon, David, Lallement, Rosine, Levrier, François, Lis, Dariuscz C., Liszt, Harvey, Le Bourlot,Jacques, Le Petit, Franck, Öberg,Karin Danielsson, Peretto, Nicolas, Roueff, Evelyne, Sievers, Albrecht, Thouvenin, Pierre-Antoine, Tremblin, Pascal, Centre National de la Recherche Scientifique (France), Agence Nationale de la Recherche (France), Centre National D'Etudes Spatiales (France), Ministerio de Ciencia e Innovación (España), National Aeronautics and Space Administration (US), Universities Space Research Association (US), Einig, Lucas [0000-0003-4250-7638], Pety, Jérôme [0000-0003-3061-6546], #NODATA#, Chanussot, Jocelyn [0000-0003-4817-2875], Gerin, Maryvonne [0000-0002-2418-7952], Orkisz, Jan H. [0000-0002-3382-9208], Palud, Pierre [0000-0002-5850-6325], Santa-María, Miriam G. [0000-0002-3941-0360], Bešlić, Ivana [0000-0003-0583-7363], Bron, Emeric E. [0000-0003-1532-7818], Chainais,Pierre [0000-0003-4377-7584], Goicoechea, Javier R. [0000-0001-7046-4319], Gratier, Pierre [0000-0002-6636-4304], Lis, Dariuscz C. [0000-0002-0500-4700], Le Bourlot,Jacques [0000-0003-3920-8063], Le Petit, Franck [0000-0001-8738-6724], Roueff, Evelyne [0000-0002-4949-8562], Sievers, Albrecht [0000-0003-0151-2924], Thouvenin, Pierre-Antoine [0000-0003-1246-9458], Einig, Lucas, Pety, Jérôme, Roueff, Antoine, Vandame, Paul, Chanussot, Jocelyn, Gerin, Maryvonne, Orkisz, Jan H., Palud, Pierre, Santa-María, Miriam G., Souza Magalhaes, Victor de, Bešlić, Ivana, Bardeau, Sébastien, Bron, Emeric E., Chainais,Pierre, Goicoechea, Javier R., Gratier, Pierre, Guzman Veloso, Viviana, Hughes, Annie, Kainulainen, Jouni, Languignon, David, Lallement, Rosine, Levrier, François, Lis, Dariuscz C., Liszt, Harvey, Le Bourlot,Jacques, Le Petit, Franck, Öberg,Karin Danielsson, Peretto, Nicolas, Roueff, Evelyne, Sievers, Albrecht, Thouvenin, Pierre-Antoine, and Tremblin, Pascal

Abstract

Context. The availability of large bandwidth receivers for millimeter radio telescopes allows the acquisition of position-position-frequency data cubes over a wide field of view and a broad frequency coverage. These cubes contain much information on the physical, chemical, and kinematical properties of the emitting gas. However, their large size coupled with inhomogenous signal-to-noise ratio (SNR) are major challenges for consistent analysis and interpretation.Aims. We search for a denoising method of the low SNR regions of the studied data cubes that would allow to recover the low SNR emission without distorting the signals with high SNR.Methods. We perform an in-depth data analysis of the 13 CO and C 17 O (1 -- 0) data cubes obtained as part of the ORION-B large program performed at the IRAM 30m telescope. We analyse the statistical properties of the noise and the evolution of the correlation of the signal in a given frequency channel with that of the adjacent channels. This allows us to propose significant improvements of typical autoassociative neural networks, often used to denoise hyperspectral Earth remote sensing data. Applying this method to the 13 CO (1 -- 0) cube, we compare the denoised data with those derived with the multiple Gaussian fitting algorithm ROHSA, considered as the state of the art procedure for data line cubes.Results. The nature of astronomical spectral data cubes is distinct from that of the hyperspectral data usually studied in the Earth remote sensing literature because the observed intensities become statistically independent beyond a short channel separation. This lack of redundancy in data has led us to adapt the method, notably by taking into account the sparsity of the signal along the spectral axis. The application of the proposed algorithm leads to an increase of the SNR in voxels with weak signal, while preserving the spectral shape of the data in high SNR voxels.Conclusions. The proposed algorithm that combines a detailed ana

Published
2023

5. Gas kinematics around filamentary structures in the Orion B cloud

Author

Gaudel, Mathilde, primary, Orkisz, Jan H., additional, Gerin, Maryvonne, additional, Pety, Jérôme, additional, Roueff, Antoine, additional, Marchal, Antoine, additional, Levrier, François, additional, Miville-Deschênes, Marc-Antoine, additional, Goicoechea, Javier R., additional, Roueff, Evelyne, additional, Le Petit, Franck, additional, de Souza Magalhaes, Victor, additional, Palud, Pierre, additional, Santa-Maria, Miriam G., additional, Vono, Maxime, additional, Bardeau, Sébastien, additional, Bron, Emeric, additional, Chainais, Pierre, additional, Chanussot, Jocelyn, additional, Gratier, Pierre, additional, Guzman, Viviana, additional, Hughes, Annie, additional, Kainulainen, Jouni, additional, Languignon, David, additional, Le Bourlot, Jacques, additional, Liszt, Harvey, additional, Öberg, Karin, additional, Peretto, Nicolas, additional, Sievers, Albrecht, additional, and Tremblin, Pascal, additional

Published
2023
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7. Gas kinematics around filamentary structures in the Orion B cloud

Author

Agence Nationale de la Recherche (France), Centre National de la Recherche Scientifique (France), Centre National D'Etudes Spatiales (France), l'Observatoire de Paris, Ministerio de Ciencia, Innovación y Universidades (España), Swedish Research Council, Orkisz, Jan H. [0000-0002-3382-9208], Pety, Jérôme [0000-0003-3061-6546], Roueff, Antoine [0000-0002-7498-4407], Marchal, Antoine [0000-0002-5501-232X], Levrier, François [0000-0002-3065-9944], Miville-Deschênes, Marc-Antoine [0000-0002-7351-6062], Goicoechea, Javier R. [0000-0001-7046-4319], Roueff, Evelyne [0000-0002-4949-8562], Santa-Maria, Miriam G. [0000-0002-3941-0360], Bron, Emeric [0000-0003-1532-7818], Chainais, Pierre [0000-0003-4377-7584], Chanussot, Jocelyn [0000-0003-4817-2875], Gratier, Pierre [0000-0002-6636-4304], Guzman, Viviana [0000-0003-4784-3040], Le Bourlot,Jacques [0000-0003-3920-8063], Liszt, Harvey [0000-0002-6116-1911], Gaudel, Mathilde, Orkisz, Jan H., Gerin, Maryvonne, Pety, Jérôme, Roueff, Antoine, Marchal, Antoine, Levrier, François, Miville-Deschênes, Marc-Antoine, Goicoechea, Javier R., Roueff, Evelyne, Le Petit, Franck, Souza Magalhaes, Victor de, Palud, Pierre, Santa-Maria, Miriam G., Vono, Maxime, Bardeau, Sébastien, Bron, Emeric, Chainais, Pierre, Chanussot, Jocelyn, Gratier, Pierre, Guzman, Viviana, Hughes, Annie, Kainulainen, Jouni, Languignon, David, Le Bourlot,Jacques, Liszt, Harvey, Öberg, Karin, Peretto, Nicolas, Sievers, Albrecht, Tremblin, Pascal, Agence Nationale de la Recherche (France), Centre National de la Recherche Scientifique (France), Centre National D'Etudes Spatiales (France), l'Observatoire de Paris, Ministerio de Ciencia, Innovación y Universidades (España), Swedish Research Council, Orkisz, Jan H. [0000-0002-3382-9208], Pety, Jérôme [0000-0003-3061-6546], Roueff, Antoine [0000-0002-7498-4407], Marchal, Antoine [0000-0002-5501-232X], Levrier, François [0000-0002-3065-9944], Miville-Deschênes, Marc-Antoine [0000-0002-7351-6062], Goicoechea, Javier R. [0000-0001-7046-4319], Roueff, Evelyne [0000-0002-4949-8562], Santa-Maria, Miriam G. [0000-0002-3941-0360], Bron, Emeric [0000-0003-1532-7818], Chainais, Pierre [0000-0003-4377-7584], Chanussot, Jocelyn [0000-0003-4817-2875], Gratier, Pierre [0000-0002-6636-4304], Guzman, Viviana [0000-0003-4784-3040], Le Bourlot,Jacques [0000-0003-3920-8063], Liszt, Harvey [0000-0002-6116-1911], Gaudel, Mathilde, Orkisz, Jan H., Gerin, Maryvonne, Pety, Jérôme, Roueff, Antoine, Marchal, Antoine, Levrier, François, Miville-Deschênes, Marc-Antoine, Goicoechea, Javier R., Roueff, Evelyne, Le Petit, Franck, Souza Magalhaes, Victor de, Palud, Pierre, Santa-Maria, Miriam G., Vono, Maxime, Bardeau, Sébastien, Bron, Emeric, Chainais, Pierre, Chanussot, Jocelyn, Gratier, Pierre, Guzman, Viviana, Hughes, Annie, Kainulainen, Jouni, Languignon, David, Le Bourlot,Jacques, Liszt, Harvey, Öberg, Karin, Peretto, Nicolas, Sievers, Albrecht, and Tremblin, Pascal

Abstract

Understanding the initial properties of star-forming material and how they affect the star formation process is key. From an observational point of view, the feedback from young high-mass stars on future star formation properties is still poorly constrained. In the framework of the IRAM 30m ORION-B large program, we obtained observations of the translucent and moderately dense gas, which we used to analyze the kinematics over a field of 5 deg^2 around the filamentary structures. We used the ROHSA algorithm to decompose and de-noise the C18O(1-0) and 13CO(1-0) signals by taking the spatial coherence of the emission into account. We produced gas column density and mean velocity maps to estimate the relative orientation of their spatial gradients. We identified three cloud velocity layers at different systemic velocities and extracted the filaments in each velocity layer. The filaments are preferentially located in regions of low centroid velocity gradients. By comparing the relative orientation between the column density and velocity gradients of each layer from the ORION-B observations and synthetic observations from 3D kinematic toy models, we distinguish two types of behavior in the dynamics around filaments: (i) radial flows perpendicular to the filament axis that can be either inflows (increasing the filament mass) or outflows and (ii) longitudinal flows along the filament axis. The former case is seen in the Orion B data, while the latter is not identified. We have also identified asymmetrical flow patterns, usually associated with filaments located at the edge of an HII region. This is the first observational study to highlight feedback from HII regions on filament formation and, thus, on star formation in the Orion B cloud. This simple statistical method can be used for any molecular cloud to obtain coherent information on the kinematics.

Published
2022

9. Tracers of the ionization fraction in dense and translucent gas

Author

Bron, Emeric, primary, Roueff, Evelyne, additional, Gerin, Maryvonne, additional, Pety, Jérôme, additional, Gratier, Pierre, additional, Le Petit, Franck, additional, Guzman, Viviana, additional, Orkisz, Jan H., additional, de Souza Magalhaes, Victor, additional, Gaudel, Mathilde, additional, Vono, Maxime, additional, Bardeau, Sébastien, additional, Chainais, Pierre, additional, Goicoechea, Javier R., additional, Hughes, Annie, additional, Kainulainen, Jouni, additional, Languignon, David, additional, Le Bourlot, Jacques, additional, Levrier, François, additional, Liszt, Harvey, additional, Öberg, Karin, additional, Peretto, Nicolas, additional, Roueff, Antoine, additional, and Sievers, Albrecht, additional

Published
2020
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10. Quantitative inference of the H2 column densities from 3 mm molecular emission: case study towards Orion B

Author

Gratier, Pierre, primary, Pety, Jérôme, additional, Bron, Emeric, additional, Roueff, Antoine, additional, Orkisz, Jan H., additional, Gerin, Maryvonne, additional, de Souza Magalhaes, Victor, additional, Gaudel, Mathilde, additional, Vono, Maxime, additional, Bardeau, Sébastien, additional, Chanussot, Jocelyn, additional, Chainais, Pierre, additional, Goicoechea, Javier R., additional, Guzmán, Viviana V., additional, Hughes, Annie, additional, Kainulainen, Jouni, additional, Languignon, David, additional, Le Bourlot, Jacques, additional, Le Petit, Franck, additional, Levrier, François, additional, Liszt, Harvey, additional, Peretto, Nicolas, additional, Roueff, Evelyne, additional, and Sievers, Albrecht, additional

Published
2020
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11. C18O,13CO, and12CO abundances and excitation temperatures in the Orion B molecular cloud

Author

Roueff, Antoine, primary, Gerin, Maryvonne, additional, Gratier, Pierre, additional, Levrier, François, additional, Pety, Jérôme, additional, Gaudel, Mathilde, additional, Goicoechea, Javier R., additional, Orkisz, Jan H., additional, de Souza Magalhaes, Victor, additional, Vono, Maxime, additional, Bardeau, Sébastien, additional, Bron, Emeric, additional, Chanussot, Jocelyn, additional, Chainais, Pierre, additional, Guzman, Viviana V., additional, Hughes, Annie, additional, Kainulainen, Jouni, additional, Languignon, David, additional, Le Bourlot, Jacques, additional, Le Petit, Franck, additional, Liszt, Harvey S., additional, Marchal, Antoine, additional, Miville-Deschênes, Marc-Antoine, additional, Peretto, Nicolas, additional, Roueff, Evelyne, additional, and Sievers, Albrecht, additional

Published
2020
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12. Quantitative inference of the H2 column densities from 3 mm molecular emission: case study towards Orion B

Author

Centre National de la Recherche Scientifique (France), Max Planck Society, Instituto Geográfico Nacional (España), Université Paris-Saclay, Istituto Nazionale di Astrofisica, Ministerio de Ciencia, Innovación y Universidades (España), Gratier, Pierre, Pety, Jérôme, Bron, Emeric, Roueff, Antoine, Orkisz, Jan H., Gerin, Maryvonne, Souza Magalhaes, Victor de, Gaudel, Mathilde, Vono, Maxime, Bardeau, Sébastien, Chanussot, Jocelyn, Chainais, Pierre, Goicoechea, Javier R., Guzmán, Viviana V., Hughes, Annie, Kainulainen, Jouni, Languignon, David, Le Bourlot, Jacques, Le Petit, Franck, Levrier, François, Liszt, Harvey, Peretto, Nicolas, Roueff, Evelyne, Sievers, Albrecht, Centre National de la Recherche Scientifique (France), Max Planck Society, Instituto Geográfico Nacional (España), Université Paris-Saclay, Istituto Nazionale di Astrofisica, Ministerio de Ciencia, Innovación y Universidades (España), Gratier, Pierre, Pety, Jérôme, Bron, Emeric, Roueff, Antoine, Orkisz, Jan H., Gerin, Maryvonne, Souza Magalhaes, Victor de, Gaudel, Mathilde, Vono, Maxime, Bardeau, Sébastien, Chanussot, Jocelyn, Chainais, Pierre, Goicoechea, Javier R., Guzmán, Viviana V., Hughes, Annie, Kainulainen, Jouni, Languignon, David, Le Bourlot, Jacques, Le Petit, Franck, Levrier, François, Liszt, Harvey, Peretto, Nicolas, Roueff, Evelyne, and Sievers, Albrecht

Abstract

Molecular hydrogen being unobservable in cold molecular clouds, the column density measurements of molecular gas currently rely either on dust emission observation in the far-IR or on star counting. (Sub-)millimeter observations of numerous trace molecules are effective from ground based telescopes, but the relationships between the emission of one molecular line and the H2 column density (NH2) is non-linear and sensitive to excitation conditions, optical depths, abundance variations due to the underlying physico-chemistry. We aim to use multi-molecule line emission to infer NH2 from radio observations. We propose a data-driven approach to determine NH2 from radio molecular line observations. We use supervised machine learning methods (Random Forests) on wide-field hyperspectral IRAM-30m observations of the Orion B molecular cloud to train a predictor of NH2, using a limited set of molecular lines as input, and the Herschel-based dust-derived NH2 as ground truth output. For conditions similar to the Orion B molecular cloud, we obtain predictions of NH2 within a typical factor of 1.2 from the Herschel-based estimates. An analysis of the contributions of the different lines to the predictions show that the most important lines are $^{13}$CO(1-0), $^{12}$CO(1-0), C$^{18}$O(1-0), and HCO$^+$(1-0). A detailed analysis distinguishing between diffuse, translucent, filamentary, and dense core conditions show that the importance of these four lines depends on the regime, and that it is recommended to add the N$_2$H$^+$(1-0) and CH$_3$OH(20-10) lines for the prediction of NH2 in dense core conditions. This article opens a promising avenue to directly infer important physical parameters from the molecular line emission in the millimeter domain. The next step will be to try to infer several parameters simultaneously (e.g., NH2 and far-UV illumination field) to further test the method. [Abridged]

Published
2020

13. VISION − Vienna survey in Orion

Author

Meingast, Stefan, primary, Alves, João, additional, Mardones, Diego, additional, Teixeira, Paula Stella, additional, Lombardi, Marco, additional, Großschedl, Josefa, additional, Ascenso, Joana, additional, Bouy, Herve, additional, Forbrich, Jan, additional, Goodman, Alyssa, additional, Hacar, Alvaro, additional, Hasenberger, Birgit, additional, Kainulainen, Jouni, additional, Kubiak, Karolina, additional, Lada, Charles, additional, Lada, Elizabeth, additional, Moitinho, André, additional, Petr-Gotzens, Monika, additional, Rodrigues, Lara, additional, and Román-Zúñiga, Carlos G., additional

Published
2016
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14. VISION - Vienna survey in Orion I. VISTA Orion A Survey

Author

Meingast, Stefan, Alves, João, Mardones, Diego, Teixeira, Paula Stella, Lombardi, Marco, Großschedl, Josefa, Ascenso, Joana, Bouy, Herve, Forbrich, Jan, Goodman, Alyssa A., Hacar, Alvaro, Hasenberger, Birgit, Kainulainen, Jouni, Kubiak, Karolina, Lada, Charles J., Lada, Elizabeth, Moitinho, André, Petr-Gotzens, Monika, Rodrigues, Lara, and Román-Zúñiga, Carlos G.

Subjects
techniques: image processing, methods: data analysis, stars: formation, stars: pre-main sequence
Abstract

Context. Orion A hosts the nearest massive star factory, thus offering a unique opportunity to resolve the processes connected with the formation of both low- and high-mass stars. Here we present the most detailed and sensitive near-infrared (NIR) observations of the entire molecular cloud to date. Aims. With the unique combination of high image quality, survey coverage, and sensitivity, our NIR survey of Orion A aims at establishing a solid empirical foundation for further studies of this important cloud. In this first paper we present the observations, data reduction, and source catalog generation. To demonstrate the data quality, we present a first application of our catalog to estimate the number of stars currently forming inside Orion A and to verify the existence of a more evolved young foreground population. Methods. We used the European Southern Observatory’s (ESO) Visible and Infrared Survey Telescope for Astronomy (VISTA) to survey the entire Orion A molecular cloud in the NIR J,H, and KS bands, covering a total of ~18.3 deg2. We implemented all data reduction recipes independently of the ESO pipeline. Estimates of the young populations toward Orion A are derived via the KS-band luminosity function. Results. Our catalog (799 995 sources) increases the source counts compared to the Two Micron All Sky Survey by about an order of magnitude. The 90% completeness limits are 20.4, 19.9, and 19.0 mag in J,H, and KS, respectively. The reduced images have 20% better resolution on average compared to pipeline products. We find between 2300 and 3000 embedded objects in Orion A and confirm that there is an extended foreground population above the Galactic field, in agreement with previous work. Conclusions. The Orion A VISTA catalog represents the most detailed NIR view of the nearest massive star-forming region and provides a fundamental basis for future studies of star formation processes toward Orion., Astronomy

Published
2016
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