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# lect14 - UCF Physics AST 5765/4762(Advanced Astronomical...

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UCF Physics: AST 5765/4762: (Advanced) Astronomical Data Analysis Fall 2009 Lecture Notes: 14. General Fitting, CCD Systematics 1 Check In: 10:30 — 10:35, 5 min Questions before we start? Gone rest of today, tomorrow Return quiz. Grads: 66. Undergrads: 75 average. 2 General Linear Fitting: 10:35 — 10:45, 5+5 min Summarize general linear fitting with sketch If model has just multiply parameter, intercept is used as a final background fit Can still do if data are in more than 2 axes E.g., model depends on x and y in an image fitting demo 3 Function Minimization Fitting: 10:45 — 11:00, 10+5 min Linear fitting doesn’t work if there is more than a multiply and an add parameter E.g., multiply, add, and shift Could derive a new expression like linear least squares formulae Or, do it numerically: Define an Python function that has parameters of model as inputs Usually the parameters are in a vector Run scipy.optimize.leastsq on the data with the function It finds the optimal values, and errors! Can be slow, depending on model and data space Can be fooled if data space is strange: local minima in χ 2 space What scipy.optimize.leastsq does is: Evaluate the function Compute χ 2 vs. data 1

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Vary the parameters and repeat
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lect14 - UCF Physics AST 5765/4762(Advanced Astronomical...

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