Simulation and Optimization Studies of the LHCb Beetle Readout ASIC and Machine Learning Approach for Pulse Shape Reconstruction.

The optimization of the Beetle readout ASIC and the performance of the software for the signal processing based on machine learning methods are presented. The Beetle readout chip was developed for the LHCb (Large Hadron Collider beauty) tracking detectors and was used in the VELO (Vertex Locator) during Run 1 and 2 of LHC data taking. The VELO, surrounding the LHC beam crossing region, was a leading part of the LHCb tracking system. The Beetle chip was used to read out the signal from silicon microstrips, integrating and amplifying it. The studies presented in this paper cover the optimization of its electronic configuration to achieve the lower power consumption footprint and the lower operational temperature of the sensors, while maintaining a good condition of the analogue response of the whole chip. The studies have shown that optimizing the operational temperature is possible and can be beneficial when the detector is highly irradiated. Even a single degree drop in silicon temperature can result in a significant reduction in the leakage current. Similar studies are being performed for the future silicon tracker, the Upstream Tracker (UT), which will start operating at LHC in 2021. It is expected that the inner part of the UT detector will suffer radiation damage similar to the most irradiated VELO sensors in Run 2. In the course of analysis we also developed a general approach for the pulse shape reconstruction using an ANN approach. This technique can be reused in case of any type of front-end readout chip.

FunTuple: A New N-tuple Component for Offline Data Processing at the LHCb Experiment.

The offline software framework of the LHCb experiment has undergone a significant overhaul to tackle the data processing challenges that will arise in the upcoming Run 3 and Run 4 of the Large Hadron Collider. This paper introduces FunTuple, a novel component developed for offline data processing within the LHCb experiment. This component enables the computation and storage of a diverse range of observables for both reconstructed and simulated events by leveraging on the tools initially developed for the trigger system. This feature is crucial for ensuring consistency between trigger-computed and offline-analysed observables. The component and its tool suite offer users flexibility to customise stored observables, and its reliability is validated through a full-coverage set of rigorous unit tests. This paper comprehensively explores FunTuple's design, interface, interaction with other algorithms, and its role in facilitating offline data processing for the LHCb experiment for the next decade and beyond.

Probing new physics via the B(s)0→µ(+)µ- effective lifetime.

We have recently seen new upper bounds for B(s)(0)→µ(+)µ(-), a key decay to search for physics beyond the standard model. Furthermore a nonvanishing decay width difference ΔΓ(s) of the B(s) system has been measured. We show that ΔΓ(s) affects the extraction of the B(s)(0)→µ(+)µ(-) branching ratio and the resulting constraints on the new physics parameter space and give formulas for including this effect. Moreover, we point out that ΔΓ(s) provides a new observable, the effective B(s)(0)→µ(+)µ(-) lifetime τ(µ(+)µ(-)), which offers a theoretically clean probe for new physics searches that is complementary to the branching ratio. Should the B(s)(0)→µ(+)µ(-) branching ratio agree with the standard model, the measurement of τ(µ(+)µ(-)), which appears feasible at upgrades of the Large Hadron Collider experiments, may still reveal large new physics effects.