☆ 4.7 Article

Astronomical Data Analysis and Sparsity: From Wavelets to Compressed Sensing

PROCEEDINGS OF THE IEEE (2010)

Journal

PROCEEDINGS OF THE IEEE

Volume 98, Issue 6, Pages 1021-1030

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

DOI: 10.1109/JPROC.2009.2025663

Keywords

Astronomical data analysis; compressed sensing; curvelet; restoration; wavelet

Categories

Engineering, Electrical & Electronic

Funding

French National Agency for Research [ANR-08-EMER-009-01]

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Abstract

Wavelets have been used extensively for several years now in astronomy for many purposes, ranging from data filtering and deconvolution to star and galaxy detection or cosmic-ray removal. More recent sparse representations such as ridgelets or curvelets have also been proposed for the detection of anisotropic features such as cosmic strings in the cosmic microwave background. We review in this paper a range of methods based on sparsity that have been proposed for astronomical data analysis. We also discuss the impact of compressed sensing, the new sampling theory, in astronomy for collecting the data, transferring them to earth or reconstructing an image from incomplete measurements.

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Article Astronomy & Astrophysics

Euclid: Forecasts from the void-lensing cross-correlation

M. Bonici, C. Carbone, S. Davini, P. Vielzeuf, L. Paganin, V. Cardone, N. Hamaus, A. Pisani, A. J. Hawken, A. Kovacs, S. Nadathur, S. Contarini, G. Verza, I. Tutusaus, F. Marulli, L. Moscardini, M. Aubert, C. Giocoli, A. Pourtsidou, S. Camera, S. Escoffier, A. Caminata, S. Di Domizio, M. Martinelli, M. Pallavicini, V. Pettorino, Z. Sakr, D. Sapone, G. Testera, S. Tosi, V. Yankelevich, A. Amara, N. Auricchio, M. Baldi, D. Bonino, E. Branchini, M. Brescia, J. Brinchmann, V. Capobianco, J. Carretero, M. Castellano, S. Cavuoti, R. Cledassou, G. Congedo, L. Conversi, Y. Copin, L. Corcione, F. Courbin, M. Cropper, A. Da Silva, H. Degaudenzi, M. Douspis, F. Dubath, C. A. J. Duncan, X. Dupac, S. Dusini, A. Ealet, S. Farrens, S. Ferriol, P. Fosalba, M. Frailis, E. Franceschi, M. Fumana, P. Gomez-Alvarez, B. Garilli, B. Gillis, A. Grazian, F. Grupp, L. Guzzo, S. V. H. Haugan, W. Holmes, F. Hormuth, A. Hornstrup, K. Jahnke, M. Kuemmel, S. Kermiche, A. Kiessling, M. Kilbinger, M. Kunz, H. Kurki-Suonio, R. Laureijs, S. Ligori, P. B. Lilje, I. Lloro, E. Maiorano, O. Mansutti, O. Marggraf, K. Markovic, R. Massey, E. Medinaceli, M. Melchior, M. Meneghetti, G. Meylan, M. Moresco, E. Munari, S. M. Niemi, C. Padilla, S. Paltani, F. Pasian, K. Pedersen, W. J. Percival, S. Pires, G. Polenta, M. Poncet, L. Popa, F. Raison, R. Rebolo, A. Renzi, J. Rhodes, E. Rossetti, R. Saglia, B. Sartoris, M. Scodeggio, A. Secroun, G. Seidel, C. Sirignano, G. Sirri, L. Stanco, J. -L. Starck, C. Surace, P. Tallada-Crespi, D. Tavagnacco, A. N. Taylor, I. Tereno, R. Toledo-Moreo, F. Torradeflot, E. A. Valentijn, L. Valenziano, Y. Wang, J. Weller, G. Zamorani, J. Zoubian, S. Andreon

Summary: The Euclid space telescope will survey cosmic voids using galaxy samples and estimate its performance in utilizing photometric void clustering, galaxy weak lensing, and their cross-correlation. The study finds that the inclusion of the void-lensing cross-correlation signal enhances parameter constraints and improves the joint void clustering and galaxy lensing figure of merit. When combined with spectroscopic galaxy clustering, the study shows that the FoM increases significantly. The conclusion suggests that photometric void clustering and its cross-correlation with galaxy lensing should be utilized in the data analysis of the Euclid galaxy survey to improve its constraining power.

ASTRONOMY & ASTROPHYSICS (2023)

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Article Astronomy & Astrophysics

Euclid: Calibrating photometric redshifts with spectroscopic cross-correlations

K. Naidoo, H. Johnston, B. Joachimi, J. L. van den Busch, H. Hildebrandt, O. Ilbert, O. Lahav, N. Aghanim, B. Altieri, A. Amara, M. Baldi, R. Bender, C. Bodendorf, E. Branchini, M. Brescia, J. Brinchmann, S. Camera, V. Capobianco, C. Carbone, J. Carretero, F. J. Castander, M. Castellano, S. Cavuoti, A. Cimatti, R. Cledassou, G. Congedo, C. J. Conselice, L. Conversi, Y. Copin, L. Corcione, F. Courbin, M. Cropper, A. Da Silva, H. Degaudenzi, J. Dinis, F. Dubath, X. Dupac, S. Dusini, S. Farrens, S. Ferriol, P. Fosalba, M. Frailis, E. Franceschi, P. Franzetti, M. Fumana, S. Galeotta, B. Garilli, W. Gillard, B. Gillis, C. Giocoli, A. Grazian, F. Grupp, S. V. H. Haugan, W. Holmes, F. Hormuth, A. Hornstrup, K. Jahnke, M. Kuemmel, A. Kiessling, M. Kilbinger, T. Kitching, R. Kohley, H. Kurki-Suonio, S. Ligori, P. B. Lilje, I. Lloro, E. Maiorano, O. Mansutti, O. Marggraf, K. Markovic, F. Marulli, R. Massey, S. Maurogordato, M. Meneghetti, E. Merlin, G. Meylan, M. Moresco, L. Moscardini, E. Munari, R. Nakajima, S. M. Niemi, C. Padilla, S. Paltani, F. Pasian, K. Pedersen, W. J. Percival, V. Pettorino, S. Pires, G. Polenta, M. Poncet, L. Popa, L. Pozzetti, F. Raison, R. Rebolo, A. Renzi, J. Rhodes, G. Riccio, E. Romelli, C. Rosset, E. Rossetti, R. Saglia, D. Sapone, B. Sartoris, P. Schneider, A. Secroun, G. Seidel, C. Sirignano, G. Sirri, J. -l. Starck, C. Surace, P. Tallada-Crespi, A. N. Taylor, I. Tereno, R. Toledo-Moreo, F. Torradeflot, I. Tutusaus, E. A. Valentijn, L. Valenziano, T. Vassallo, Y. Wang, J. Weller, M. Wetzstein, A. Zacchei, G. Zamorani, J. Zoubian, S. Andreon, D. Maino, V. Scottez, A. H. Wright

Summary: Cosmological constraints from the Euclid imaging survey rely on accurate determination of tomographic redshift bins' true redshift distributions, n(z). We investigate the calibration of mean redshift, < z >, of ten Euclid tomographic redshift bins using cross-correlation with spectroscopic samples. Our results show that clustering redshifts can attain uncertainties exceeding the Euclid requirement by at least a factor of three, but systematic biases limit the accuracy. Future work includes extending the method to higher redshifts with quasar reference samples.

ASTRONOMY & ASTROPHYSICS (2023)

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Article Astronomy & Astrophysics

Probabilistic mass-mapping with neural score estimation

B. Remy, F. Lanusse, N. Jeffrey, J. Liu, J. -l. Starck, K. Osato, T. Schrabback

Summary: This study introduces a novel methodology that efficiently samples the high-dimensional Bayesian posterior of weak lensing mass-mapping problem, using a non-Gaussian prior based on simulations. The results demonstrate that the proposed method outperforms previous algorithms in terms of root-mean-square error and Pearson correlation, and successfully reconstructs the highest-quality convergence map of the HST/ACS COSMOS field.

ASTRONOMY & ASTROPHYSICS (2023)

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Article Mathematics, Applied

Rethinking data-driven point spread function modeling with a differentiable optical model

Tobias Liaudat, Jean-Luc Starck, Martin Kilbinger, Pierre-Antoine Frugier

Summary: Upcoming space telescopes with wide-field optical instruments have a spatially varying point spread function (PSF). This paper presents a new data-driven model called WaveDiff, which shifts the modeling space from pixels to the wavefront, allowing for the capture of chromatic variations in the PSF. The proposed model achieves significant performance improvements in pixel reconstruction errors and ellipticity errors compared to existing approaches.

INVERSE PROBLEMS (2023)

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Article Astronomy & Astrophysics

Starlet higher order statistics for galaxy clustering and weak lensing

Virginia Ajani, Joachim Harnois-Deraps, Valeria Pettorino, Jean-Luc Starck

Summary: We introduce a wavelet-based multi-scale summary statistics for photometric galaxy clustering and weak lensing, including local maxima count and integral(1)-norm. We use cosmo-SLICS simulations to compute wavelet-based non-Gaussian statistics for weak-lensing convergence maps and galaxy maps. Forecasts on important cosmological parameters are obtained, and the starlet peaks and integral-norm are found to be useful summary statistics that improve constraints compared to the power spectrum, even when combining the two probes.

ASTRONOMY & ASTROPHYSICS (2023)

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