Retrieving the solar EUV spectrum from a reduced set of spectral lines

Wit, T. Dudok de; Lilensten, Jean; Aboudarham, Jean; Amblard, Pierre‐Olivier; Kretzschmar, M.

doi:10.5194/angeo-23-3055-2005

Cited by 29 publications

(2 citation statements)

References 32 publications

(40 reference statements)

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“…Although this assumption is not mandatory, it enables us to project the observations on a lower-dimensional subspace which, as we shall see, eases their visualization. Many studies support the idea that the Sun-integrated spectral variability in the EUV can be described by a small number of elementary contributions (Lean et al, 1982;Woods et al, 2000;Dudok de Wit et al, 2005;Amblard et al, 2008). This number is most likely larger for solar images because of the spatial information.…”

Section: The Data and Physical Assumptionsmentioning

confidence: 86%

Coronal Temperature Maps from Solar EUV Images: A Blind Source Separation Approach

Wit

Moussaoui²,

Guennou

et al. 2012

Sol Phys

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Multi-wavelength solar images in the EUV are routinely used for analysing solar features such as coronal holes, filaments, and flares. However, images taken in different bands often look remarkably similar as each band receives contributions coming from regions with a range of different temperatures. This has motivated the search for empirical techniques that may unmix these contributions and concentrate salient morphological features of the corona in a smaller set of less redundant source images. Blind Source Separation (BSS) precisely does this. Here we show how this novel concept also provides new insight into the physics of the solar corona, using observations made by SDO/AIA. The source images are extracted using a Bayesian positive source separation technique. We show how observations made in six spectral bands, corresponding to optically thin emissions, can be reconstructed by linear combination of three sources. These sources have a narrower temperature response and allow for considerable data reduction since the pertinent information from all six bands can be condensed in only one single composite picture. In addition, they give access to empirical temperature maps of the corona. The limitations of the BSS technique and some applications are briefly discussed.

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Section: The Data and Physical Assumptionsmentioning

confidence: 86%

Coronal Temperature Maps from Solar EUV Images: A Blind Source Separation Approach

Wit

Moussaoui²,

Guennou

et al. 2012

Sol Phys

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“…For the Sun, de Wit et al (2005) did not find that Lyα is the best emission line to predict the extreme-UV spectrum. If using only one or two emission lines to predict the solar extreme-UV spectrum, they recommend using O I (λ1304 Å), C IV (λ1550 Å), or Si II (λ1817 Å), or Lyα in conjunction with Si II (λ1817 Å) or O I (λ1304 Å).…”

Section: Comparison With Other Chromospheric Andmentioning

confidence: 94%

The MUSCLES TREASURY SURVEY. II. INTRINSIC LYα AND EXTREME ULTRAVIOLET SPECTRA OF K AND M DWARFS WITH EXOPLANETS*

Youngblood

Loyd

Linsky

et al. 2016

ApJ

265

289

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The ultraviolet (UV) spectral energy distributions (SEDs) of low-mass (K-and M-type) stars play a critical role in the heating and chemistry of exoplanet atmospheres, but are not observationally well-constrained. Direct observations of the intrinsic flux of the Lyα line (the dominant source of UV photons from low-mass stars) are challenging, as interstellar H I absorbs the entire line core for even the closest stars. To address the existing gap in empirical constraints on the UV flux of K and M dwarfs, the MUSCLES Hubble Space Telescope Treasury Survey has obtained UV observations of 11 nearby M and K dwarfs hosting exoplanets. This paper presents the Lyα and extreme-UV spectral reconstructions for the MUSCLES targets. Most targets are optically inactive, but all exhibit significant UV activity. We use a Markov Chain Monte Carlo technique to correct the observed Lyα profiles for interstellar absorption, and we employ empirical relations to compute the extreme-UV SED from the intrinsic Lyα flux in ∼100 Å bins from 100-1170 Å. The reconstructed Lyα profiles have 300 km s −1 broad cores, while >1% of the total intrinsic Lyα flux is measured in extended wings between 300 and 1200 km s −1 . The Lyα surface flux positively correlates with the Mg II surface flux and negatively correlates with the stellar rotation period. Stars with larger Lyα surface flux also tend to have larger surface flux in ions formed at higher temperatures, but these correlations remain statistically insignificant in our sample of 11 stars. We also present H I column density measurements for 10 new sightlines through the local interstellar medium.

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Solar Parameters for Modeling the Interplanetary Background

Bzowski

Sokół

Tokumaru

et al. 2013

Cross-Calibration of Far UV Spectra of Solar System Objects and the Heliosphere

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The goal of the Fully Online Datacenter of Ultraviolet Emissions (FONDUE) Working Team of the International Space Science Institute (ISSI) in Bern, Switzerland, was to establish a common calibration of various UV and EUV heliospheric observations, both spectroscopic and photometric. Realization of this goal required a credible and up-to-date model of spatial distribution of neutral interstellar hydrogen in the heliosphere, and to that end, a credible model of the radiation pressure and ionization processes was needed. This chapter describes the latter part of the project: the solar factors responsible for shaping the distribution of neutral interstellar H in the heliosphere. Presented are the solar Lyman-alpha flux and the question of solar Lyman-alpha resonant radiation pressure force acting on neutral H atoms in the heliosphere, solar EUV radiation and the process of photoionization of heliospheric hydrogen, and their evolution in time and the still hypothetical variation with heliolatitude. Further, solar wind and its evolution with solar activity is 1

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Retrieving the solar EUV spectrum from a reduced set of spectral lines

Cited by 29 publications

References 32 publications

Coronal Temperature Maps from Solar EUV Images: A Blind Source Separation Approach

Coronal Temperature Maps from Solar EUV Images: A Blind Source Separation Approach

The MUSCLES TREASURY SURVEY. II. INTRINSIC LYα AND EXTREME ULTRAVIOLET SPECTRA OF K AND M DWARFS WITH EXOPLANETS*

Solar Parameters for Modeling the Interplanetary Background

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