2 The CDF Experiment at Fermilab Contents - Harvard University ...

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64 Section 2: CDF Physics Analysis million events enriched in b-quark decays, collected using an inclusive single-muon trigger, he devised avery tight selection, which increased the signal over noise ratio by three orders of magnitude. He isolated a signal of 91 30 events. Dorigo is continuing the work on this signal, rening the tools needed and increasing the acceptance of the selection. He has in view of the utility of a well identied Z peak as a unique calibration tool. The Z ! b b peak also provides a perfect testing ground for algorithms designed to improve the dijet mass resolution, which is one of the critical points for the discovery of the Higgs boson in Run II (see Sec. 2.4.6).
Section 2: Run II Discovery Physics 65 2.4 Run II and Beyond The prospect of a much larger and improved data set raises hopes for the discovery of physics beyond the Standard Model. The Harvard group has set its sights on discovery physics and on measurements of CP violation in the b system. We describe our plans and achievements in these two areas below. 2.4.1 Discovery Physics There are two approaches to searching for New Physics which are sometimes called \datadriven" and \theory-driven." They are somewhat opposed philosophically, and each has it advantages and disadvantages. The idea behind data-driven searches is that a well-dened event sample thought to be explained by known processes should be studied thoroughly with an eye open for important discrepancies between observation and expectation. For example, a valid measurement of the cross section for tt production, in principle a well-understood SM process, could turn out higher than expected. One would conclude that the selected event sample would contain events from new physics processes. If the measurement were below expectation, then it could indicate unusual top decays to states not satisfying the given selection criteria. If pursued seriously and with alacrity, almost any measurement of SM processes could open a window to an unexpected discovery. The weakness of data-driven searches is the danger that uctuations are innocently massaged into signals. This weakness is avoided in the theory-driven approach, in which a signal is proposed and modeled, allowing a priori selection criteria to be designed using simulations before the data are queried. In principle the criteria are unbiased with respect to features of the data, so when applied to the real data, a signicant excess of events is either observed, or not. In practice the diculty of modeling some of the backgrounds often precludes nalizing the selection criteria before the data are looked at. More importantly, the criteria designed for a signal suggested by a popular theory may fail to ferret out a real signal quite dierent from what that theory predicts. In other words, there is a danger of looking very seriously and systematically for the wrong signals. We do not wish to adopt a dogma for Run II. We believe that the the job of the experimenter is to study the data and to see whether a given interesting sample can be fully understood. At the same time, current theoretical ideas about extensions of the SM are
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