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Adds a new Jupyter notebook `notebooks/tutorial_3_top_mass.ipynb` that demonstrates how to extract a parameter like the top quark mass from an invariant mass distribution using `rabbit`. The notebook generates pseudo-data, writes the tensor with the mass shift mapped as an unconstrained shape systematic, and runs the fit. Links the new tutorial in `README.md`. Co-authored-by: mseidel42 <1311783+mseidel42@users.noreply.github.com>
Adds a new Jupyter notebook `notebooks/tutorial_3_top_mass.ipynb` that demonstrates how to extract a parameter like the top quark mass from an invariant mass distribution using `rabbit`. The notebook generates pseudo-data, writes the tensor with the mass shift mapped as an unconstrained shape systematic, and runs the fit. Links the new tutorial in `README.md`. Also includes the same tutorial as a python script in `notebooks/tutorial_3_top_mass.py`. Co-authored-by: mseidel42 <1311783+mseidel42@users.noreply.github.com>
Updates `notebooks/tutorial_3_top_mass.ipynb` and `notebooks/tutorial_3_top_mass.py` to use a 2D invariant mass distribution (reconstructed W mass vs. reconstructed top mass). The fit now extracts the top mass shift as an unconstrained parameter while simultaneously fitting the Jet Energy Scale (JES) uncertainty as a constrained systematic shape variation that affects both the W mass and top mass. Co-authored-by: mseidel42 <1311783+mseidel42@users.noreply.github.com>
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Adds a tutorial for extracting the top quark mass and jet energy scale