Opendata, web and dolomites


non-LinEar sigNal processing for solving data challenges in Astrophysics

Total Cost €


EC-Contrib. €






Project "LENA" data sheet

The following table provides information about the project.


Organization address
address: RUE LEBLANC 25
city: PARIS 15
postcode: 75015

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country France [FR]
 Project website
 Total cost 1˙497˙411 €
 EC max contribution 1˙497˙411 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2015-STG
 Funding Scheme ERC-STG
 Starting year 2016
 Duration (year-month-day) from 2016-09-01   to  2021-08-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

Astrophysics has arrived to a turning point where the scientific exploitation of data requires overcoming challenging analysis issues, which mandates the development of advanced signal processing methods. In this context, sparsity and sparse signal representations have played a prominent role in astrophysics. Indeed, thanks to sparsity, an extremely clean full-sky map of the Cosmic Microwave Background (CMB) has been derived from the Planck data [Bobin14], a European space mission that observes the sky in the microwave wavelengths. This led to a noticeable breakthrough: we showed that the large-scale statistical studies of the CMB can be performed without having to mask the galactic centre anymore thanks to the achieved high quality component separation [Rassat14]. Despite the undeniable success of sparsity, standard linear signal processing approaches are too simplistic to capture the intrinsically non-linear properties of physical data. For instance, the analysis of the Planck data in polarization requires new sparse representations to finely capture the properties of polarization vector fields (e.g. rotation invariance), which cannot be tackled by linear approaches. Shifting from the linear to the non-linear signal representation paradigm is an emerging area in signal processing, which builds upon new connections with fields such as deep learning [Mallat13]. Inspired by these active and fertile connections, the LENA project will: i) study a new non-linear signal representation framework to design non-linear models that can account for the underlying physics, and ii) develop new numerical methods that can exploit these models. We will further demonstrate the impact of the developed models and algorithms to tackle data analysis challenges in the scope of the Planck mission and the European radio-interferometer LOFAR. We expect the results of the LENA project to impact astrophysical data analysis as significantly as deploying sparsity to the field has achieved.


year authors and title journal last update
List of publications.
2019 A. Picquenot, F. Acero, J. Bobin, P. Maggi, J. Ballet, G. W. Pratt
Novel method for component separation of extended sources in X-ray astronomy
published pages: A139, ISSN: 0004-6361, DOI: 10.1051/0004-6361/201834933
Astronomy & Astrophysics 627 2019-10-29
2019 J. Frontera-Pons, F. Sureau, B. Moraes, J. Bobin, F. B. Abdalla
Representation learning for automated spectroscopic redshift estimation
published pages: A73, ISSN: 0004-6361, DOI: 10.1051/0004-6361/201834295
Astronomy & Astrophysics 625 2019-10-29
2019 Melis O. Irfan, Jérôme Bobin, Marc-Antoine Miville-Deschênes, Isabelle Grenier
Determining thermal dust emission from Planck HFI data using a sparse, parametric technique
published pages: A21, ISSN: 0004-6361, DOI: 10.1051/0004-6361/201834394
Astronomy & Astrophysics 623 2019-10-29
2018 Julien Fade, Estéban Perrotin, Jérôme Bobin
Polarizer-free two-pixel polarimetric camera by compressive sensing
published pages: B102, ISSN: 1559-128X, DOI: 10.1364/ao.57.00b102
Applied Optics 57/7 2019-07-08
2017 Melis O Irfan, Jérôme Bobin
Sparse estimation of model-based diffuse thermal dust emission
published pages: 5560-5574, ISSN: 0035-8711, DOI: 10.1093/mnras/stx3107
Monthly Notices of the Royal Astronomical Society 474/4 2019-07-08
2017 J. Frontera-Pons, F. Sureau, J. Bobin, E. Le Floc’h
Unsupervised feature-learning for galaxy SEDs with denoising autoencoders
published pages: A60, ISSN: 0004-6361, DOI: 10.1051/0004-6361/201630240
Astronomy & Astrophysics 603 2019-07-08
2017 Cécile Chenot, Jérôme Bobin
Blind separation of sparse sources in the presence of outliers
published pages: 233-243, ISSN: 0165-1684, DOI: 10.1016/j.sigpro.2017.03.024
Signal Processing 138 2019-07-08
2017 Ming Jiang, Jérôme Bobin, Jean-Luc Starck
Joint Multichannel Deconvolution and Blind Source Separation
published pages: 1997-2021, ISSN: 1936-4954, DOI: 10.1137/16M1103713
SIAM Journal on Imaging Sciences 10/4 2019-07-08
2017 Arnau Pujol, Ramin A. Skibba, Enrique Gaztañaga, Andrew Benson, Jeremy Blaizot, Richard Bower, Jorge Carretero, Francisco J. Castander, Andrea Cattaneo, Sofia A. Cora, Darren J. Croton, Weiguang Cui, Daniel Cunnama, Gabriella De Lucia, Julien E. Devriendt, Pascal J. Elahi, Andreea Font, Fabio Fontanot, Juan Garcia-Bellido, Ignacio D. Gargiulo, Violeta Gonzalez-Perez, John Helly, Bruno M. B. Henri
nIFTy Cosmology: the clustering consistency of galaxy formation models
published pages: , ISSN: 0035-8711, DOI: 10.1093/mnras/stx913
Monthly Notices of the Royal Astronomical Society 2019-07-08
2019 Arnau Pujol, Martin Kilbinger, Florent Sureau, Jerome Bobin
A highly precise shear bias estimator independent of the measured shape noise
published pages: A2, ISSN: 0004-6361, DOI: 10.1051/0004-6361/201833740
Astronomy & Astrophysics 621 2019-04-18
2018 C Chang, A Pujol, B Mawdsley, D Bacon, J Elvin-Poole, P Melchior, A Kovács, B Jain, B Leistedt, T Giannantonio, A Alarcon, E Baxter, K Bechtol, M R Becker, A Benoit-Lévy, G M Bernstein, C Bonnett, M T Busha, A Carnero Rosell, F J Castander, R Cawthon, L N da Costa, C Davis, J De Vicente, J DeRose, A Drlica-Wagner, P Fosalba, M Gatti, E Gaztanaga, D Gruen, J Gschwend, W G Hartley, B Hoyle, E M Huff, M Jarvis, N Jeffrey, T Kacprzak, H Lin, N MacCrann, M A G Maia, R L C Ogando, J Prat, M M Rau, R P Rollins, A Roodman, E Rozo, E S Rykoff, S Samuroff, C Sánchez, I Sevilla-Noarbe, E Sheldon, M A Troxel, T N Varga, P Vielzeuf, V Vikram, R H Wechsler, J Zuntz, T M C Abbott, F B Abdalla, S Allam, J Annis, E Bertin, D Brooks, E Buckley-Geer, D L Burke, M Carrasco Kind, J Carretero, M Crocce, C E Cunha, C B D\'Andrea, S Desai, H T Diehl, J P Dietrich, P Doel, J Estrada, A Fausti Neto, E Fernandez, B Flaugher, J Frieman, J García-Bellido, R A Gruendl, G Gutierrez, K Honscheid, D J James, T Jeltema, M W G Johnson, M D Johnson, S Kent, D Kirk, E Krause, K Kuehn, S Kuhlmann, O Lahav, T S Li, M Lima, M March, P Martini, F Menanteau, R Miquel, J J Mohr, E Neilsen, R C Nichol, D Petravick, A A Plazas, A K Romer, M Sako, E Sanchez, V Scarpine, M Schubnell, M Smith, R C Smith, M Soares-Santos, F Sobreira, E Suchyta, G Tarle, D Thomas, D L Tucker, A R Walker, W Wester, Y Zhang
Dark Energy Survey Year 1 results: curved-sky weak lensing mass map
published pages: 3165-3190, ISSN: 0035-8711, DOI: 10.1093/mnras/stx3363
Monthly Notices of the Royal Astronomical Society 475/3 2019-04-16
2017 Alexander Knebe, Frazer R Pearce, Violeta Gonzalez-Perez, Peter A Thomas, Andrew Benson, Rachel Asquith, Jeremy Blaizot, Richard Bower, Jorge Carretero, Francisco J Castander, Andrea Cattaneo, Sofía A Cora, Darren J Croton, Weiguang Cui, Daniel Cunnama, Julien E Devriendt, Pascal J Elahi, Andreea Font, Fabio Fontanot, Ignacio D Gargiulo, John Helly, Bruno Henriques, Jaehyun Lee, Gary A Mamon, Julian Onions, Nelson D Padilla, Chris Power, Arnau Pujol, Andrés N Ruiz, Chaichalit Srisawat, Adam R H Stevens, Edouard Tollet, Cristian A Vega-Martínez, Sukyoung K Yi
Cosmic CARNage I: on the calibration of galaxy formation models
published pages: 2936-2954, ISSN: 0035-8711, DOI: 10.1093/mnras/stx3274
Monthly Notices of the Royal Astronomical Society 475/3 2019-04-16
2018 C. Kervazo, J. Bobin, C. Chenot
Blind separation of a large number of sparse sources
published pages: 157-165, ISSN: 0165-1684, DOI: 10.1016/j.sigpro.2018.04.006
Signal Processing 150 2019-04-16
2018 Cécile Chenot, Jérôme Bobin
Blind Source Separation with Outliers in Transformed Domains
published pages: 1524-1559, ISSN: 1936-4954, DOI: 10.1137/17m1133919
SIAM Journal on Imaging Sciences 11/2 2019-04-16

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "LENA" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email ( and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "LENA" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.1.1.)


The Enemy of the Good: Towards a Theory of Moral Progress

Read More  


The Mass Politics of Disintegration

Read More  


3D printed micro- and nano-optics for future integrated vision and endoscopy systems

Read More