This document explains how I try to get temperatures from XRT filter ratios. The filters for the HOP 177 run are Be_thin/Open and Open/Ti_poly. wave_resp=make_xrt_wave_resp(contam_time='9-feb-2011 09:00') temp_resp=make_xrt_temp_resp(wave_resp,/apec_default) Now temp_resp is a structure array giving responses for each filter combination. The indices for my filters are: Be_thin: 3 Ti_poly: 4 Thus I can plot the temperature response ratio for these channels with: k=where(temp_resp[3].temp ne 0) temp=temp_resp[3].temp[k] resp_be=temp_resp[3].temp_resp[k] resp_ti=temp_resp[4].temp_resp[k] plot,temp,resp_ti/resp_be,/xlog,xra=[1e5,1e8] This gives a curve that is zero up to 10^6 and rises up to 0.76 at 2x10^7. The rise to 0.5 occurs between 1 and 3x10^6. --- To measure the ratio it's necessary to run xrt_prep with the /norm and /float keywords. This gives the intensities in DN/s, suitable for comparing with the temperature curve. There are two problems: - the jet kernels are very dynamic and so intensity changes between the Ti and Be exposures - the brightest kernels are saturated in the 16s Ti exposures (there are shorter exposures available, though) --- I've saved calibrated maps for the period 08:30 to 09:05 at: /Users/young/data/hinode/hop177/fe12_vel_features/raster23/xrt/xrt_calib_maps.save 09:02 - Ti exp 24, Be exp 13 Averaged 4x3 block of pixels in each image I(Ti)=2939.7 I(Be)=149.7 Ratio=0.051 09:00 - Ti exp 22, Be exp 12 Averaged 4x3 block of pixels in each image Choose weaker of brightenings in Ti image. I(Ti)=929.9 I(Be)=383.6 Ratio=0.413 08:57 - Ti exp 20, Be exp 11 Averaged 4x3 block of pixels in each image I(Ti)=1137.9 I(Be)=158.3 Ratio=0.139 Conclusion: the temperature is always below 3x10^6, but higher than 1x10^6.