31 August 2026 to 4 September 2026
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Smartpixels at a 10 TeV Muon Collider: Machine Learning Algorithms for On-Pixel Rejection of Beam Induced Background

Not scheduled
12m
Presentation Contributed Talks

Speaker

Daniel Abadjiev (University of Chicago (US))

Description

At a 10TeV muon collider, a high level of beam induced background (BIB) will overlay signal produced from muon collisions, similar to how pile-up at the HL-LHC will overlay signal from proton-proton collisions. On-detector differentiation of BIB from signal would improve performance of the inner pixel tracker. Following the successful development of a prototype “smartpixel” application specific integrated circuit (ASIC) for hypothetical use in HL-LHC, we train analogous models to filter charge clusters of BIB from Signal based on cluster geometry in the first layer of the tracker at a muon collider. We explore the performance of 3 classes of smartpixel filter architectures and estimate their hardware usage using qkeras and hls4ml in order to develop a lightweight algorithm suitable for on-chip implementation.

Authors

Benjamin John Rosser (University of Chicago (US)) Dr Benjamin Roberts (University of Chicago) Daniel Abadjiev (University of Chicago (US)) Eliza Claire Howard (University of Chicago (US)) Karri Folan Di Petrillo (University of Chicago) Ryan Michaud Tsz Ngong You

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