wiki:observational_astronomy:thermal_signal

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wiki:observational_astronomy:thermal_signal [2023/11/07 12:55] – created Roy Proutywiki:observational_astronomy:thermal_signal [2023/11/09 12:54] (current) – removed Roy Prouty
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-====== Measuring Thermal Signal ====== 
-The THERMAL calibration frame is trickier than collecting a BIAS frame. Due to the thermal signal being a time-integrated term, we cannot simply take a $0s$ exposure as we did with the BIAS--there would be no thermal signal in such a frame! 
  
-Consider removing all possible source signal: 
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-$$L_{ij}(\lambda) = \Bigl[\epsilon_{ij}(\lambda)I_{ij}(\lambda) + T_{ij}(\lambda)\Bigr]t + B_{ij}(\lambda) ~~|~~ I_{ij}(\lambda)=0 ~ \forall ~ i,j$$ 
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-$$L_{ij}(\lambda) =  T_{ij}(\lambda)t + B_{ij}(\lambda)$$ 
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-We are now left with the Dark Signal as defined on our [[wiki:observational_astronomy:data_reduction|Data Reduction]] page. 
-$$L_{ij}(\lambda) =  T_{ij}(\lambda)t + B_{ij}(\lambda) = D_{ij}(\lambda)$$ 
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-This brings up an important point in reduction pipelines. A point that is often lost on those new to the idea of data reduction. YOU.MUST.ALWAYS.ACCOUNT.FOR.BIAS. Some forums and guides suggest otherwise, saying that you don't need to take bias frames for calibration. 
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-What the authors of those posts neglect to say is that if you take a THERMAL frame, it'll have the bias built-in. This is evident in the quick maths above. What is also evident is that the THERMAL frame must be of the same integration time as the LIGHT frame. 
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-Such frames that account for both are called DARKS. They have both thermal and bias signals in them and are of the same integration time as the light frames. 
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-In the sad case where your thermal frame was taken with a different integration time, you will need to cheat by scaling the thermal signal by the ratio of the integration times so as to appropriately scale the thermal signal. In this (again SAD) case, you will need to subtract the BIAS frames from the thermal frames **before** scaling and subtract it out again at reduction time. Neglecting to do so would scale the BIAS signal unnecessarily--introducing unwanted signal into your attempt at a science frame.