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Innovative approach of adjusting quality parameters inspired by AAfit Lambda and Gaussian Distribution. Learn how the new function enhances solution quality and penalizes incorrect results. Dive into the current implementation and its impact on results, supported by insightful visuals
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Presentation Transcript
Quality Parameter Adjustment Inspired by AAfit Lambda Improved since start Inspired by Gaussian
Effect of the new function: Look at Alternative Fit solutions Improve/boost the Quality parameter of correct solutions Penalize the quality parameter of incorrect solutions
11 AAfit result 4001 JPP result with initial cuts : Beta < 0.012 rad Upgoing Chi^2 > 35 4002 JPP result with initial cuts and a cut on the quality parameter. 4011 AAfit exclusive results + Jpp fit results 1104 - AAfit exclusive results Angle between Primary solution and MC True Value
Adjusted Quality Parameter Angle between the primary solution and the MC_True values with respect to the adjusted quality parameter
Why not use Reduced Chi2? Reduced Chi2 Log_10 (theta) Angle between the primary solution and the MC_True values with respect to the Reduced Chi2
