Mila Bileska

most citedSpectroscopy and modeling of

^{171}

Yb Rydberg states for high-fidelity two-qubit gates

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

physics.ins-det2025

Design and FPGA Implementation of WOMBAT: A Deep Neural Network Level-1 Trigger System for Jet Substructure Identification and Boosted $H \to b b ˉ$ Tagging at the CMS Experiment

Mila Bileska

This thesis investigates the physics performance, trigger efficiency, and Field Programmable Gate Array (FPGA) implementation of machine learning (ML)-based algorithms for Lorentz-…

physics.atom-ph2024★ 1 cited

Spectroscopy and modeling of $^{171}$ Yb Rydberg states for high-fidelity two-qubit gates

Michael Peper, Yiyi Li, Daniel Y. Knapp +8

Highly excited Rydberg states and their interactions play an important role in quantum computing and simulation. These properties can be predicted accurately for alkali atoms with…

Design and FPGA Implementation of WOMBAT: A Deep Neural Network Level-1 Trigger System for Jet Substructure Identification and Boosted H→bbˉ Tagging at the CMS Experiment

Spectroscopy and modeling of 171Yb Rydberg states for high-fidelity two-qubit gates

Design and FPGA Implementation of WOMBAT: A Deep Neural Network Level-1 Trigger System for Jet Substructure Identification and Boosted $H \to b b ˉ$ Tagging at the CMS Experiment

Spectroscopy and modeling of $^{171}$ Yb Rydberg states for high-fidelity two-qubit gates