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Tau-Squared Description Software » Manual Example 1 Example 2 Hints and Tips
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| Home > Group > Tim Naylor > tau-squared > Manual # CMDfit Manual The basic use of the code involves running the following programs in this order. ## 1) monte This creates the 2D isochrone models required by grid using a Monte-Carlo. You will be asked for a model number and the colour combination you want. The output files consist of the 2D isochrones (e.g. geneva_V_B-V_07.000.00.fit, where the number is the base ten logarithm of the age in years) and a list of the first 10,000 simulated stars. The latter is useful if the isochrone does not stretch as far in the 2D CMD as you think it should. If you sort the file on the third column (mass), and then examine the last column (flag) you can get an idea of if it is (say) the model isochrone which does not stretch to the mass you want, or the conversions from luminosity and temperature to magnitude and colour. ## 2) grid This takes a catalogue of observations in cluster format and fits them to a model. It does this by a grid search in the parameter space. It assumes that the uncertainties you give for say V and B-V are correlated, unless the uncertainties in colour are smaller than those in magnitude. It then creates uncertainties in each magnitude, e.g. V and B. The final tau-squared it gives you is after removing data points whose tau-squared lies above the clipping threshold. The output files are as follows. unclipped.cat - All the data points that were actually used, with the systematic uncertainty added. grid.fit - The grid of tau-squared as a function of the parameters searched (in FITS format). The values of tau-squared in this file include the contributions from all data points, though those with high tau-squared will have had their values set to the maximum allowed. Where the probability of any single datapoint becomes so small that it would cause a numerical underflow (and hence taking the log of it would be problematical) the tau-squared for the entire fit is set to a high number. Hence the grid will have a sudden jump in tau-squared where the underflow happens. unclipped_abs.cat - As above but in absolute magnitude. best_model.fit - The best fitting model corrected to the appropriate reddening and distance modulus. distrib.tau - The histogram of the tau-squared from each data point. grid_npts.fit - An image representing the number of data points within the magnitude range of the model images as a function of the parameters searched. ## 3) tau2 Calculates the expected value of tau^2 for you. For tau2 to give statistically meaningful answers you must have run grid to obtain a fit which has no datapoints soft clipped. You can achieve this by running grid once with a soft clipping of 20, and then renaming unclipped.cat to something like fitme.cat, and then re-running grid with this as the datafile and with a negative value for the soft clipping parameter (this switches it off). ### Inputs The best fitting model (e.g. best_model.fit) unclipped.cat from grid. (In principle you can use the original catalogue if you have not added an extra uncertainty when running grid, but in practice its best to always use unclipped.cat.) Subtley, it takes the best fitting tau2 from grid.fit, which of course does not include the effect of soft clipping. ### Outputs integ.tau - The cumulative distribution of tau-squared. Search through this file to find the nearest value of tau-squared to the one you have, and the number next to it is the corresponding value of Pr(tau-squared). This is also given in the output from the program. one.tau - The expected distrubution of tau2 amoungst the datapoints. If you have removed datapoints compare this with distrib.tau from grid to see if the remaining ones have a reasonable distrubution of tau2. tau.diff ## 4) Uncer Derives uncertainty contours in tau-squared space. The 68 percent confidence limit is printed to the screen, as are some one-dimensional parameter limits. Use the latter with the same caution you would in the chi-squared case, i.e. if you have one free parameter they are right, more than that and they do not allow for any correlation in the parameters. Furthermore, as they are derived by summing the tau^2 space in the direction of the other parameter, they will sometimes give rather different answers for the best value to grid. This is the right thing to do, but as it depends on the prior for the other parameter, can be confusing. There is a brief description of the underlying idea behind uncer. ### Inputs grid.fit - From grid. The tau-squared grid from the fitting process. You are not prompted for this, it is read automatically. ### Outputs uncer.out - The values of tau^2 appropriate for each confidence limit. Read down the confidence limits to find the appropriate value for a tau-squared contour. ## Sim Creates a simulated catalogue of observations from an isochrone. One possible input is a linear isochrone, such as Sim/linear.iso ## The isochrones The isochrones consist of two distinct parts, the model interiors which give effective temperature and luminosity, and the model atmospheres which convert these into colour and magnitude. We provide three sets of conversions. Jeffries/Naylor: The bolometric corrections are derived from fitting observations for cool low-mass stars, and from Bessell, Castelli & Plez (1998) for the the hooter stars. The technique is outlined in Naylor et al (2002). In one case the bolometric correction is from Flower (1996). You can see the polynomials for the bolometric corrections in the code. The conversions from effective temperature are derived from fitting the Pleiades ("Pleiades tuning") and is described in Jeffries et al (2001). The problem this produces is that we have not determined the effective temperature to colour conversion for all models. Making them is not hard, checking that dozens of them are right is. So, if the conversion is not present for the particular isochrone you want (the error message will be from monte, and something like "Error opening file /h/timn/CMDfit/Data/dam97_K_J-K.dat"), let me know, and I can generate it for you; provided you undertake to check its reasonable). Bessell: These are solar metallicity bolometric corrections, effective temperature to colour conversions and colour dependent reddening vectors from Bessell, Castelli & Plez (1998). The model atmospheres folded through the filter responses do not always give the colours of Vega to be zero (the V magnitude is zero). We choose to tweak the colour scale so all the colours are zero (though there is a compilation option to change this). These can give problems when dealing with post-main-sequence isochrones as the higher temperatures do not have the lower gravities required for the giants. Bessell Tycho: Bolometric corrections and effective temperature to colour conversions into the Hipparcos Tycho system from Bessell (2000). Note that we then use the extinctions from Bessell, Castelli & Plez (1998), but in the cases we've done the extinction is so small the error is not important. These can then be applied to the following models. Note, however, that you may want to be careful about combining one metallicity of interior with a different metallicity atmosphere. dam97: from D'Antona & Mazzitelli (1997) newbaraffe :the mixing length 1.0 models from Baraffe et at (2002) newbaraffe_19: the mixing length 1.9 models from Baraffe et at (2002) siessz02: the Z=0.02 models from Siess et al (2000) siessz01: the Z=0.01 models from Siess et al (2000) The following models come ready converted into colour and absolute magnitude, but you can also apply any of the above atmospheres. padova: z=0.019 (i.e. solar metallicity) from Girardi et al (2002) geneva: from Lejeune & Schaerer (2001) (Also see their web pages.) Finally, you can supply your own isochrones at fixed ages. The files should be call something like user_V_B-V_06.800.dat. The format us as follows. The code uses the last header line to pick out the columns it wants, and is quite intelligent at doing so. so not all the columns are needed. The mass used is M_ini. # # # # log(age/yr) M_ini M_act logTe logG logL/Lo V B U 6.8 0.8 0.8 3.687 4.6518 -0.612 6.6713 7.5805 8.0755 6.8 0.81 0.81 3.6909 4.6498 -0.589 6.6005 7.4943 7.9698 Home > Group > Tim Naylor > tau-squared > Manual

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