Multichannel Poisson denoising and deconvolution on the sphere: application to the<i>Fermi</i>Gamma-ray Space Telescope

Schmitt, Jérémy; Starck, Jean-Luc; Casandjian, J. M.; Fadili, Jalal M.; Grenier, I. A.

doi:10.1051/0004-6361/201118234

Cited by 17 publications

(12 citation statements)

References 14 publications

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“…This probabilistic model includes prior constraints to remedy the complexity of the inverse problem. Assuming a sparsity-based regularization, for example, Schmitt et al (2010Schmitt et al ( , 2012 proposed an analysis strategy using waveforms, which they applied to simulated Fermi data. A&A 581, A126 (2015) For the analysis of X-ray images, which pose the same challenges as γ-ray images, a Bayesian background-source separation technique was proposed by Guglielmetti et al (2009).…”

Section: Introductionmentioning

confidence: 99%

The denoised, deconvolved, and decomposedFermiγ-ray sky

Selig

Vacca

Oppermann

et al. 2015

A&A

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We analyze the 6.5 year all-sky data from the Fermi Large Area Telescope that are restricted to γ-ray photons with energies between 0.6-307.2 GeV. Raw count maps show a superposition of diffuse and point-like emission structures and are subject to shot noise and instrumental artifacts. Using the D 3 PO inference algorithm, we modeled the observed photon counts as the sum of a diffuse and a point-like photon flux, convolved with the instrumental beam and subject to Poissonian shot noise. The D 3 PO algorithm performs a Bayesian inference without the use of spatial or spectral templates; that is, it removes the shot noise, deconvolves the instrumental response, and yields separate estimates for the two flux components. The non-parametric reconstruction uncovers the morphology of the diffuse photon flux up to several hundred GeV. We present an all-sky spectral index map for the diffuse component. We show that the diffuse γ-ray flux can be described phenomenologically by only two distinct components: a soft component, presumably dominated by hadronic processes, tracing the dense, cold interstellar medium, and a hard component, presumably dominated by leptonic interactions, following the hot and dilute medium and outflows such as the Fermi bubbles. A comparison of the soft component with the Galactic dust emission indicates that the dust-to-soft-gamma ratio in the interstellar medium decreases with latitude. The spectrally hard component exists in a thick Galactic disk and tends to flow out of the Galaxy at some locations. Furthermore, we find the angular power spectrum of the diffuse flux to roughly follow a power law with an index of 2.47 on large scales, independent of energy. Our first catalog of source candidates includes 3106 candidates of which we associate 1381 (1897) with known sources from the second (third) Fermi source catalog. We observe γ-ray emission in the direction of a few galaxy clusters hosting known radio halos.

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Section: Introductionmentioning

confidence: 99%

The denoised, deconvolved, and decomposedFermiγ-ray sky

Selig

Vacca

Oppermann

et al. 2015

A&A

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“…This proba- bilistic model includes prior constraints to remedy the complexity of the inverse problem. Assuming a sparsity-based regularization, for example, Schmitt et al (2010Schmitt et al ( , 2012 proposed an analysis strategy using waveforms, which they applied to simulated Fermi data. For the analysis of X-ray images, which pose the same challenges as γ-ray images, a Bayesian background-source separation technique was proposed by Guglielmetti et al (2009).…”

Section: Introductionmentioning

confidence: 99%

The Denoised, Deconvolved, and Decomposed Fermi gamma-ray sky

Selig¹,

Vacca²,

Oppermann³

et al. 2016

Proceedings of the 34th International Cosmic Ray Conference — PoS(ICRC2015)

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We analyze the 6.5 year all-sky data from the Fermi Large Area Telescope in the energy range 0.6-307.2 GeV. Raw count maps show a superposition of diffuse and point-like emission structures and are subject to shot noise and instrumental artifacts. Using the Denoising, Deconvolving, and Decomposing Photon Observations D 3 PO algorithm, we modeled the observed photon counts as the sum of a diffuse and a point-like photon flux, convolved with the instrumental beam and subject to Poissonian shot noise, without the use of spatial or spectral templates. The D 3 PO algorithm performs a Bayesian inference and yields separate estimates for the two flux components. We show that the diffuse γ-ray flux can be described phenomenologically by only two distinct components: a soft component, presumably dominated by hadronic processes, tracing the dense, cold interstellar medium, and a hard component, presumably dominated by leptonic interactions, following the hot and dilute medium and outflows such as the Fermi bubbles.

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“…In fact, this sparsity property is extremely desirable as it can be used as a very powerful prior in the regularization of a wide range of inverse problems. Some applications to astronomy and astrophysics include denoising [12], deconvolution [13], blind source separation for CMB analysis [14], weak gravitational lensing [15].…”

Section: Morphological Component Analysismentioning

confidence: 99%

SNIa detection in the SNLS photometric analysis using Morphological Component Analysis

Möller

Ruhlmann-Kleider

Lanusse

et al. 2015

J. Cosmol. Astropart. Phys.

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Detection of supernovae (SNe) and, more generally, of transient events in large surveys can provide numerous false detections. In the case of a deferred processing of survey images, this implies reconstructing complete light curves for all detections, requiring sizable processing time and resources. Optimizing the detection of transient events is thus an important issue for both present and future surveys. We present here the optimization done in the SuperNova Legacy Survey (SNLS) for the 5-year data deferred photometric analysis. In this analysis, detections are derived from stacks of subtracted images with one stack per lunation. The 3-year analysis provided 300,000 detections dominated by signals of bright objects that were not perfectly subtracted. Allowing these artifacts to be detected leads not only to a waste of resources but also to possible signal coordinate contamination. We developed a subtracted image stack treatment to reduce the number of non SN-like events using morphological component analysis. This technique exploits the morphological diversity of objects to be detected to extract the signal of interest. At the level of our subtraction stacks, SN-like events are rather circular objects while most spurious detections exhibit different shapes. A two-step procedure was necessary to have a proper evaluation of the noise in the subtracted image stacks and thus a reliable signal extraction. We also set up a new detection strategy to obtain coordinates with good resolution for the extracted signal. SNIa Monte-Carlo (MC) generated images were used to study detection efficiency and coordinate resolution. When tested on SNLS 3-year data this procedure decreases the number of detections by a factor of two, while losing only 10% of SN-like events, almost all faint ones. MC results show that SNIa detection efficiency is equivalent to that of the original method for bright events, while the coordinate resolution is improved.

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Multichannel Poisson denoising and deconvolution on the sphere: application to theFermiGamma-ray Space Telescope

Cited by 17 publications

References 14 publications

The denoised, deconvolved, and decomposedFermiγ-ray sky

The denoised, deconvolved, and decomposedFermiγ-ray sky

The Denoised, Deconvolved, and Decomposed Fermi gamma-ray sky

SNIa detection in the SNLS photometric analysis using Morphological Component Analysis

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