| Title: | Stellar CharactEristics Pisa Estimation gRid for Binary Systems |
|---|---|
| Description: | SCEPtER pipeline for estimating the stellar age for double-lined detached binary systems. The observational constraints adopted in the recovery are the effective temperature, the metallicity [Fe/H], the mass, and the radius of the two stars. The results are obtained adopting a maximum likelihood technique over a grid of pre-computed stellar models. |
| Authors: | Matteo Dell'Omodarme [aut, cre], Giada Valle [aut] |
| Maintainer: | Matteo Dell'Omodarme <[email protected]> |
| License: | GPL (>= 2) |
| Version: | 0.1-1 |
| Built: | 2025-01-25 03:33:11 UTC |
| Source: | https://github.com/cran/SCEPtERbinary |
The package estimates the age of stars in double-lined detached binary systems, given observational effective temperature, metallicity [Fe/H], mass, and radius of both stars. The results are obtained adopting a maximum likelihood technique on a grid of computed stellar models.
G. Valle, M. Dell'Omodarme, P.G. Prada Moroni, and S. Degl'Innocenti (2014). Uncertainties in grid-based estimates of stellar mass and radius. SCEPtER: Stellar CharactEristics Pisa Estimation gRid. A&A, 561, A125.
G. Valle, M. Dell'Omodarme, P.G. Prada Moroni, and S. Degl'Innocenti (2014). Uncertainties in asteroseismic grid-based estimates of stellar ages. SCEPtER: Stellar CharactEristics Pisa Estimation gRid. A&A, accepted.
G. Valle, M. Dell'Omodarme, P.G. Prada Moroni, and S. Degl'Innocenti (2014). Grid-based estimates of stellar ages in binary systems. SCEPtER: Stellar CharactEristics Pisa Estimation gRid. A&A, submitted.
The function computes the group identifier for grid rows, according to their initial metallicities.
block(grid)block(grid)
grid |
the grid of stellar models. |
block returns a vector with the group identifier for
each row of the supplied grid.
The function returns a perturbed object, starting from observational data and a vector of uncertainties.
errorObsBin(sigma, STAR, parallel=FALSE, corr=c(0,0,0,0,0,0,0))errorObsBin(sigma, STAR, parallel=FALSE, corr=c(0,0,0,0,0,0,0))
sigma |
a vector of 14 elements containing the uncertainties on observational data. The error on mass and radius must be expressed as relative error. If the errors on the observations of the two stars are identical, it is possible to provide a vector of length 7. |
STAR |
a vector of 18 elements containing the observational data. |
parallel |
logical flag specifying if the computation should be performed in parallel on a multi-core architecture. |
corr |
a vector with the assumed the correlation between corresponding observables of the two stars. Default to zero (no correlations). |
The vector of observations STAR must contain, in the order:
The effective temperature (in K) of the star.
The logarithm of the surface gravity of the star (in cm s^-2).
The metallicity [Fe/H] of the star.
The value of large frequency separation of the star, divided by the solar value of this quantity.
The value of the frequency of maximum oscillation power of the star, divided by the solar value of this quantity.
The mass (in solar units) of the star.
The radius (in solar unit) of the star.
The vector of the uncertainties on the observation sigma must
contain the uncertainty on the above quantity. The
uncertainty on the asteroseismic parameters, mass, and radius
must be expressed as relative error.
errorObsBin returns an object obtained sampling from a
multivariate normal distribution with vector of mean STAR and
covariance matrix computed
according to the value of corr.
The function computes the grid-based estimates of the age for the supplied binary systems.
estimateBin(data, STAR, sigma, thr, sel, parallel=FALSE)estimateBin(data, STAR, sigma, thr, sel, parallel=FALSE)
data |
the matrix estimation grid. The matrix should be sorted according to the values in the first column (the stellar effective temperature). |
STAR |
a matrix of 18 columns, containing in each row the observational data of the stellar objects. |
sigma |
a vector of 14 elements, containing the error on observational data. The error on mass and radius are expressed as relative error. If the errors on the observables of the two stars are identical, it is possible to provide a vector of length 7. |
thr |
the threshold for the selection of cases over which the computation of likelihood is performed. |
sel |
a vector of 7 elements, containing 1 or 0 for inclusion or exclusion of a observational data from the likelihood computation. |
parallel |
logical flag indicating if the estimations should be performed in parallel on a multi-core architecture. |
STAR should contains the observables for primary and
secondary stars. In order, it should contains the stellar effective
temperature,
the logarithm of the surface gravity, the metallicity [Fe/H], the
average large frequency separation (in micro Hz), the maximum
oscillation power (in micro Hz), the mass (in solar units), the radius
(in solar units), the age (if known), and the relative age (if known).
Identical quantities for the secondary stars should follows.
sigma should contain, in the same order, the
uncertainties on the observational quantities.
estimateBin returns a data frame obtained with the
estimates
of stellar parameters for each row of the input matrix STAR.
In the columns of the data frame there are:
the identifier id
of the row of the object matrix adopted for the estimate; the
independent star estimate of the primary mass
M1 (in solar units), radius R1 (in
solar units), age age1 (in Gyr); the corresponding independent
estimates for the secondary (M2, R2, age2); the
joint-likelihood estimates of these quantities obtained explicitly assuming
coevality (M1b, R1b, age1b, M2b,
R2b, age2b); the relative age r of the primary
star (0 = ZAMS; 1 = TAMS); the best estimate of the age of the system
ageBin under coevality assumption; the mean of the age of the two
independent estimates of the stellar ages.
Age estimates are obtained by a maximum likelihood technique. Details on the technique can be found in the references reported below.
G. Valle, M. Dell'Omodarme, P.G. Prada Moroni, and S. Degl'Innocenti (2014). Uncertainties in grid-based estimates of stellar mass and radius. SCEPtER: Stellar CharactEristics Pisa Estimation gRid. A&A, 561, A125.
G. Valle, M. Dell'Omodarme, P.G. Prada Moroni, and S. Degl'Innocenti (2014). Uncertainties in asteroseismic grid-based estimates of stellar ages. SCEPtER: Stellar CharactEristics Pisa Estimation gRid. A&A, accepted.
G. Valle, M. Dell'Omodarme, P.G. Prada Moroni, and S. Degl'Innocenti (2014). Grid-based estimates of stellar ages in binary systems. SCEPtER: Stellar CharactEristics Pisa Estimation gRid. A&A, submitted.
require(SCEPtER) data(stdGrid) ogrid <- stdGrid[ do.call(order, as.data.frame(stdGrid[,1])), ] ## observational constraint: Teff, [Fe/H], M, R vsel <- c(1,0,1,0,0,1,1) sigma <- c(100, 0.25, 0.1, 0.025, 0.05, 0.01, 0.005) ## syntetic sample of 10 bynary systems bl <- block(stdGrid) sam <- sampleBinStar(10, stdGrid, bl, restrict=TRUE) ## add Gaussian noise to the observations starbp <- errorObsBin(sigma, sam) resB <- estimateBin(ogrid, starbp, sigma, 3, vsel, parallel=FALSE) ## An observed system: PK Peg ## observation from Clausen et al. (2010). A&A, 516, A42. obs <- c(6265,NA,-0.12,NA,NA,1.414,1.988,NA,NA, 6320,NA,-0.12,NA,NA,1.257,1.474,NA,NA) sigma <- c(85,0,0.07,0,0,0.007/1.414,0.008/1.988, 90,0,0.07,0,0,0.005/1.257,0.017/1.474) ## for sensible estimate adopt at least nrow=10000 star <- matrix(obs, nrow=100, ncol=18, byrow=TRUE) ## add Gaussian noise starp <- errorObsBin(sigma, star) resB <- estimateBin(ogrid, starp, sigma, 3, vsel, parallel=FALSE) quantile(resB$ageBin, c(0.16, 0.5, 0.84))require(SCEPtER) data(stdGrid) ogrid <- stdGrid[ do.call(order, as.data.frame(stdGrid[,1])), ] ## observational constraint: Teff, [Fe/H], M, R vsel <- c(1,0,1,0,0,1,1) sigma <- c(100, 0.25, 0.1, 0.025, 0.05, 0.01, 0.005) ## syntetic sample of 10 bynary systems bl <- block(stdGrid) sam <- sampleBinStar(10, stdGrid, bl, restrict=TRUE) ## add Gaussian noise to the observations starbp <- errorObsBin(sigma, sam) resB <- estimateBin(ogrid, starbp, sigma, 3, vsel, parallel=FALSE) ## An observed system: PK Peg ## observation from Clausen et al. (2010). A&A, 516, A42. obs <- c(6265,NA,-0.12,NA,NA,1.414,1.988,NA,NA, 6320,NA,-0.12,NA,NA,1.257,1.474,NA,NA) sigma <- c(85,0,0.07,0,0,0.007/1.414,0.008/1.988, 90,0,0.07,0,0,0.005/1.257,0.017/1.474) ## for sensible estimate adopt at least nrow=10000 star <- matrix(obs, nrow=100, ncol=18, byrow=TRUE) ## add Gaussian noise starp <- errorObsBin(sigma, star) resB <- estimateBin(ogrid, starp, sigma, 3, vsel, parallel=FALSE) quantile(resB$ageBin, c(0.16, 0.5, 0.84))
The function extracts, without replacement, a sample of binary systems out of a grid.
sampleBinStar(n, grid, block, restrict=TRUE, parallel=FALSE)sampleBinStar(n, grid, block, restrict=TRUE, parallel=FALSE)
n |
the number of objects to be sampled. |
grid |
the grid from which the objects are sampled. |
block |
the length of blocks of the same initial metallicity [Fe/H] |
restrict |
logical flag indicating if only models younger than 14 Gyr should be considered. |
parallel |
logical flag indicating if the estimations should be performed in parallel on a multi-core architecture. |
sampleBinStar returns a matrix of n rows, sampled without
replacement from grid.
A maximum age difference of 10 Myr is allowed in the binary system
selection.
require(SCEPtER) data(stdGrid) bl <- block(stdGrid) sam <- sampleBinStar(10, stdGrid, bl, restrict=TRUE)require(SCEPtER) data(stdGrid) bl <- block(stdGrid) sam <- sampleBinStar(10, stdGrid, bl, restrict=TRUE)