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friis |
1.1 |
Due to the low signal rates for many new physics scenarios and large QCD
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backgrounds, efficiently identifying tau leptons while maintaining an extremely
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low mis-tag rate will be an important part of the CMS physics program. The CMS
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particle flow algorithm combines all sub-detectors to provide a global
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reconstruction of a collision event and potentially improves spatial and energy
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resolution. Using the reconstructed objects from particle flow, an algorithm
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using an ensemble of neural nets corresponding to different tau decay
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resonances has been developed. This algorithm provides a large performance
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improvement with respect to previous CMS tau identification strategies and can
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potentially increase the reach of many CMS searches for physics beyond the
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Standard Model. Preliminary results are presented in this summary.
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