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Evaluating L0 and L1 Trigger Efficiencies Using Data in Hadronic and Muon Channels

This study investigates the efficiencies of L0 and L1 triggers in particle physics using real data. We analyze hadronic channels through muon-triggered events, assessing trigger frequency and comparing L0 efficiencies for hadrons and muons, revealing non-independence. We examine the efficiency of L1 global variables from B-tracks, focusing on events involving non-B tracks. Detailed tuning of L0 and L1 efficiencies is performed, highlighting the complexities in extracting accurate values. Insights are derived from extensive Monte Carlo simulations, demonstrating that L0 efficiency extraction is more challenging than anticipated.

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Evaluating L0 and L1 Trigger Efficiencies Using Data in Hadronic and Muon Channels

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  1. Measuring L0 and L1 trigger efficiencies with “DATA” • L0: • Hadronic channels: • Take -triggered events • How often did hadron trigger trigger? • Muon channels: • Vice versa • L1: • Consider L1 global variable from B-tracks • Look at events that passed due to non-B tracks N.Tuning

  2. L0 hadron • 200k Bh+h- events • Use MC: • 47.0 +/- 0.1% pass L0 h • Use “DATA” • 54.1 +/- 0.5% pass L0 h, if events passed L0 . •  L0 hadron and L0  NOT independent! • L0  selects hard events N.Tuning

  3. L0 muon • Similar story for the L0  efficiency • Hadron selected events have higher L0  efficiency. N.Tuning

  4. L1 tracks • ‘Updated’ plot • Bug: did not take into account the oscillations B0d-K+ intoB0dK-+ • L1: • 60.2% =2 tracks from signal B • 22.9%1 track from other B • 16.9% =1 signal B-track, 1 non-B track • 0.6% =2 non-B tracks N.Tuning

  5. Tagging efficiency • “Triggered on other B” means now: • >1 track from other B, and NOT from signal B. N.Tuning

  6. L1 efficiency • Consider sample where the (signal) B-tracks could have triggered • Measure L1 trigger efficiency: • Take sample that could have triggered on non-B tracks (5.4%) • Measure how often (signal) B-tracks passed L1. • Assumptions: • Offline analysis uses only events where B-tracks could have triggered • 2 B-tracks and 2 non-B tracks are independent • Almost true… : Out of all L1 rejected events, 0.4% would have passed with B-tracks N.Tuning

  7. B++K0Sand B0d-K+ • . N.Tuning

  8. Conclusions • Extracting L0 efficiency is not as easy as I thought… • Maybe need random events? • First try to extract L1 efficiency • 2% (abs) statistical uncertainty on data of ~0.1 year N.Tuning

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