1 / 20

A tool to simulate COROT light-curves

A tool to simulate COROT light-curves. R. Samadi 1 & F. Baudin 2 1 : LESIA, Observatory of Paris/Meudon 2 : IAS, Orsay. Purpose : to provide a tool to simulate CoRoT light-curves of the seismology channel. Interests : To help the preparation of the scientific analyses

cissy
Download Presentation

A tool to simulate COROT light-curves

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. A tool to simulate COROT light-curves R. Samadi1 & F. Baudin2 1: LESIA, Observatory of Paris/Meudon 2: IAS, Orsay

  2. Purpose : to provide a tool to simulate CoRoT light-curves of the seismology channel. Interests : • To help the preparation of the scientific analyses • To test some analysis techniques (e.g. Hare and Hound exercices) with a validated tool available for all the CoRoT SWG.  Public tool: the package can be downloaded at : http://www.lesia.obspm.fr/~corotswg/simulightcurve.html

  3. Main features: • Theoretical mode excitation rates are calculated according to Samadi et al (2003, A&A, 404, 1129) • Theoretical mode damping rates are obtained from the tables calculated by Houdek et al (1999, A&A 351, 582) • The mode light-curves are simulated according to Anderson et al (1990, Apj, 364, 699) • Stellar granulation simulation is based on : Harvey (1985, ESA-SP235, p.199). • Activity signal modelled from Aigrain et al (2004, A&A, 414, 1139) • Instrumental photon noise is computed in the case of COROT but can been changed.

  4. Simulated signal = modes + photon noise + granulation signal + activity signal Instrumental noise (orbital periodicities) not yet included (next version) Simulation inputs: • Duration of the time series and sampling • Characteristics (magnitude, age, etc…) of the star • Option : characteristics of the instrument performances (photon noise level for the given star magnitude) Simulation outputs: time series and spectra for : • mode signal (solar-like oscillations) • photon noise, granulation signal, activity signal

  5. Modeling the solar-like oscillations spectrum (1/4) Each solar-like oscillation is a superposition of a large number of excited and damped proper modes: Aj : amplitude at which the mode « j » is excited by turbulent convection tj : instant at which its is excited 0 : mode frequency  : mode (linear) damping rate H : Heaviside function

  6. Modeling the solar-like oscillations spectrum (2/4) Line-width : Fourier spectrum : Power spectrum : The stochastic fluctuations from the mean Lorentzian profil are simulated by generating the imaginary and real parts of U according to a normal distribution (Anderson et al , 1990).

  7. Modeling the solar-like oscillations spectrum (3/4) We have necesseraly: Line-width where <(L)²> is the rms value of the mode amplitude  constraints on: • and L/Lpredicted on the base of theoretical models • Excitations rates according to Samadi & Goupil(2001) model • Damping rates computed by G. Houdek on the base of Gough’s formulation of convection

  8. Modeling the solar-like oscillations spectrum (4/4) Simulated spectrum of solar-like oscillations for a stellar model with M=1.20 MO located at the end of MS.

  9. Photon noise Flat (white) noise COROT specification: For a star of magnitude m0=5.7, the photon noise in an amplitude spectrum of a time series of 5 days is B0 = 0.6 ppm For a given magnitude m, B = B010(m – m0)/5

  10. Granulation and activity signals Non white noise, characterised by its auto-correlation function: AC = A2 exp(-|t|/t) A: “amplitude” t: characteristic time scale Fourier transform of the auto-correlation function => Fourier spectrum of the initial signal: P(n) = 2A2t/(1 + (2ptn)2) s (or « rms variation ») from s2 =  P(n) dn => s = A/2and P(n) = 4s2t/(1 + (2ptn)2)

  11. Modelling the granulation characteristics (continue) Granulation spectrum = function of: • Eddies contrast (border/center of the granule) : (dL/L)granul • Eddie size at the surface : dgranul • Overturn time of the eddies at the surface : tgranul • Number of eddies at the surface : Ngranul Modelling the granulation characteristics • Eddie size : dgranul = dgranul,Sun (H*/HSun) • Number of eddies : Ngranul = 2p(R*/dgranul)² • Overturn time : tgranul= dgranul / V • Convective velocity : V, from Mixing-length Theory (MLT)

  12. Modelling the granulation characteristics (continue) • Eddies contrast : (dL/L)granul = function (T) • T : temperature difference between the granule and the medium ; function of the convective efficiency, . • and T from MLT • The relation is finally calibrated to match the Solar constraints.

  13. Granulation signal Inputs: • characteristic time scale (t) • dL/L for a granule | • size of a granule | (s) • radius of the star | Modelled on the base of the Mixing-length theory All calculations based on 1D stellar models computed with CESAM, assuming standard physics and solar metallicity Inputs from models

  14. Activity signal Inputs: • characteristic time scale of variability t [Aigrain et al 2004, A&A] t = intrinsic spot lifetime (solar case) or Prot How to do better? • standard deviation of variability s [Aigrain et al 2004, A&A, Noyes et al 1984, ApJ] s = f1 (CaII H & K flux) CaII H & K flux = f2 (Rossby number: Prot /tbcz) Prot = f3 (age, B-V) and B-V= f4 (Teff) tbcz , age,Teff from models fi are empirical (as t)

  15. The solar case Not too bad, but has to be improved

  16. Example: a Sun at m=8

  17. Example: a Sun at m=8

  18. Example: a young 1.2MO star (m=9)

  19. Example: a young 1.2MO star (m=9)

  20. Prospectives Next steps: - improvement of granulation and activity modelling - rotation (José Dias & José Renan) - orbital instrumental perturbations Simulation are not always close to reality, but they prepare you to face reality

More Related