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Our recent work has shown that a novel much higher granularity forward calorimetry concept can enable much more detailed and precise reconstruction than the baseline designs based on LEP luminometers, along with the capability of electron/positron/photon separation. This new calorimeter concept is designed primarily to maximize the acceptance for e⁺e⁻→ γγ as an alternative luminosity process, where it serves to define the inner edge of the acceptance (there is no outer edge, as the complete detector is used in the measurement), while continuing to provide the standard luminosity measurement from small-angle Bhabha scattering (SABS). It will also serve as a general forward electromagnetic calorimeter helping ensure hermeticity and detecting individual electrons, positrons, and photons. In this contribution we highlight the Bhabha rejection capability in the context of the e⁺e⁻→ γγ luminosity measurement and motivate the utility of a Bhabha “mini-tracker” consisting of a few planes of upstream thin silicon detectors. This could further refine the e⁺/e⁻polar angle measurement, aid with charge measurement, improve Bhabha rejection (for γγ), and, last-but-not-least, help mitigate the beam-induced electromagnetic deflection that biases the Bhabha acceptance by providing high precision longitudinal vertex information in Bhabha events, which can be used to diagnose this effect of the beam on the final-state electron and positron. 

We present work on design and reconstruction methods for sampling electromagnetic calorimeters with emphasis on highly granular designs. We use the clustered logarithmically weighted center-of-gravity estimator (lwk-means) for initial benchmarking of position resolution. We find that the θ and φ resolution for high energy photons in Si-W designs improves when increasing both sampling frequency and sampling thickness. Augmenting only one is found to have mixed results. We find that lwk-means is unable to effectively use calorimeter transverse cell sizes smaller than 2 mm. New reconstruction methods for highly granular designs are developed. We find that methods that only measure the initial particle shower and disregard the remaining shower can take advantage of cell sizes down to at least 10 µm, significantly outperforming the benchmark method. Of these, the best method and design is the initial particle shower “single hit” method using the calorimeter design with the highest sampling frequency and sampling fraction. 

We discuss the improvements that the ILC can make in precision electroweak observables based on studies with the ILD detector concept. These include observables from WW production at a centre of mass energy of 250 GeV and above, and especially from a dedicated stage of running at the Z pole. These improvements take advantage of the ILC capabilities for polarized electron and positron beams, and an accelerator design that accommodates data-taking at a wide range of beam energies. The studies include experimental considerations evaluated in the context of the ILD detector concept and discussion of experimental strategies targeted at controlling especially systematic uncertainties associated with the center-of-mass energy. 

Abstract Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.