Speaker
Daniel Abadjiev
(The University of Chicago)
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. For the HL-LHC, we are developing a “smartpixel” application specific integrated circuit (ASIC) which implements a deep neural network on-chip for on-detector data compression and classification. We present testbench studies characterizing a prototype smartpixel ASIC and its potential application in the inner pixel tracker of a muon collider detector.
Primary authors
Daniel Abadjiev
(The University of Chicago)
Karri DiPetrillo
(University of Chicago)
Mira Littmann
(The University of Chicago)
Tsz Ngong You
(The University of Chicago)
