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Learning the EFT likelihood with tree boosting
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abstract
We develop a tree boosting algorithm for collider measurements of multiple Wilson coefficients in effective field theories describing phenomena beyond the standard model of particle physics. The design of the discriminant exploits per-event information of the simulated data sets that encodes the predictions for different values of the Wilson coefficients. This ``Boosted Information Tree'' algorithm provides nearly optimal discrimination power order-by-order in the expansion in the Wilson coefficients and approaches the optimal likelihood ratio test statistic. As a proof-of-principle, we apply the algorithm to the $\textrm{pp}\rightarrow\textrm{Zh}$ process for different types of modeling.
Forward citations
Cited by 3 Pith papers
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Constraints on standard model effective field theory for a Higgs boson produced in association with W or Z bosons in the H $\to\mathrm{b\bar{b}}$ decay channel in proton-proton collisions at $\sqrt{s}$ = 13 TeV
CMS reports simultaneous constraints on six dimension-six SMEFT Wilson coefficients from VH, H to bb production at sqrt(s) = 13 TeV; all results agree with the standard model.
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Unbinning global LHC analyses
Simulation-based inference produces stronger combined LHC constraints on SMEFT Wilson coefficients than histogram-based inference for four di-boson processes.
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Fingerprinting New Physics with Effective Field Theories
A thesis compiling published SMEFT global fits, automated UV-model constraints, and ML-based unbinned observables, with projections for HL-LHC, FCC-ee, and CEPC.
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