Hare and Hounds Exercises
Coordinators: Andrea Miglio, Luca Casagrande, Joris De Ridder
Coordinators: Andrea Miglio, Luca Casagrande, Joris De Ridder
- Generate various sets of artificial data representative of populations of giants in the fields of CoRoT and Kepler (including the fields of the 2-wheel mission).The 'raw' population synthesis data can be found on our Google Drive. Extinction is not yet taken into account, so we'll do this first before we apply any biases.
- Use parametrized models of the Milky Way (TRILEGAL, Besancon, Galaxia,...).
- The team's output will be artificial observational data such as:
- seismic data (such as large frequency separation, nu_max, and the period spacing),
- spectroscopic data (effective temperature, chemical abundances, radial velocity),
- photometric constraints (apparent magnitudes, colours),
- if possible: astrometric constraints (parallaxes and proper motions) as we will obtain them with Gaia.
- Add random (possibly non-gaussian) and systematic uncertainties to the "unbiased stellar population" generated by Team A.Reddened population synthesis data can also be found on our Google Drive ("extinctedmags" files). Progress on these is ongoing.
- Add reddening biases
- Add target selection biases
Gc, logAge, [M/H], m_ini, logL, logTe, logg, m-M0, Av, comp. mbol, Kepler g, r, i, z, DDO51_finf, J, H, Ks, Mact, ev_stage
R, B-V, V-R, V-I, mux, muy, Vr, UU, VV, WW, Mv, CL, Typ, Teff, logg, Age, Mass, Mbol, Radius, [Fe/H], l(deg), b(deg), RA2000.0, DEC2000.0, Dist, x(kpc), y(kpc), z(kpc), Av, [alpha/Fe]
popid, satid, partid, fieldid, smass, mact, mtip, age, lum, teff, grav, feh, alpha, px, py, pz, vx, vy, vz, rad, ra, dec, glon, glat, exbv_schlegel_inf, exbv_schlegel, exbv_solar, mag0, mag1, mag2, ubv_b, ubv_h, ubv_i, ubv_j, ubv_k, ubv_r, ubv_u, ubv_v
- Use stellar evolution and pulsation codes to model the "observed" stellar properties to estimate their age, distance, mass, etc.Mock catalogues generated by Teams A and B:
- Carefully keep record of the assumptions you use, such as which opacities you use, mixing length, overshoot parameter, etc.
- No information from team A will be available.
- dataset1.txt.gz
- dataset2.txt.gz
- dataset3.txt.gz
- dataset4.txt.gz
- Given the stellar properties derived by Team C, recover the global galactic population properties that constrain the chemical and dynamical evolution of the galactic disk.
- Estimate the age-metallicity and age-velocity dispersion relations as a function of the position in the disk. Retrieve possible gradients.
- Estimate the initial mass function.
- Estimate the star formation rate as a function of the position in the disk.
- Given the input and output population parameters, compare the results of the different groups using different methods/codes.
- Establish the reliability of the error bars returned by team D.
- Assess how robust the results are as a function of the noise levels.
- Make recommendations for an optimized observation strategy for the Kepler, CoRoT and APOGEE teams.