arXiv Open Access 2023

Smartpixels: Towards on-sensor inference of charged particle track parameters and uncertainties

Jennet Dickinson Rachel Kovach-Fuentes Lindsey Gray Morris Swartz Giuseppe Di Guglielmo +18 lainnya
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Abstrak

The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to determine angular information of the charged particle passing through from pixel-cluster properties. This detector technology immediately improves the situation for offline tracking, but any major improvements in physics reach are unrealized since they are dominated by lowest-level hardware trigger acceptance. We will demonstrate track angle and hit position prediction, including errors, using a mixture density network within a single layer of silicon as well as the progress towards and status of implementing the neural network in hardware on both FPGAs and ASICs.

Topik & Kata Kunci

Penulis (23)

J

Jennet Dickinson

R

Rachel Kovach-Fuentes

L

Lindsey Gray

M

Morris Swartz

G

Giuseppe Di Guglielmo

A

Alice Bean

D

Doug Berry

M

Manuel Blanco Valentin

K

Karri DiPetrillo

F

Farah Fahim

J

James Hirschauer

S

Shruti R. Kulkarni

R

Ron Lipton

P

Petar Maksimovic

C

Corrinne Mills

M

Mark S. Neubauer

B

Benjamin Parpillon

G

Gauri Pradhan

C

Chinar Syal

N

Nhan Tran

D

Dahai Wen

J

Jieun Yoo

A

Aaron Young

Format Sitasi

Dickinson, J., Kovach-Fuentes, R., Gray, L., Swartz, M., Guglielmo, G.D., Bean, A. et al. (2023). Smartpixels: Towards on-sensor inference of charged particle track parameters and uncertainties. https://arxiv.org/abs/2312.11676

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2023
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en
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arXiv
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