George Li

College of Engineering

Works (2)

Updated: April 5th, 2024 12:29

2020 article

Application of Quantum Machine Learning to VLSI Placement

PROCEEDINGS OF THE 2020 ACM/IEEE 2ND WORKSHOP ON MACHINE LEARNING FOR CAD (MLCAD '20), pp. 61–66.

By: I. Turtletaub n, G. Li n, M. Ibrahim n & P. Franzon n

author keywords: Quantum Machine Learning; Balanced Min-Cut; Variational Quantum Eigensolver; Recursive Partitioning Placement
TL;DR: The Variational Quantum Eigensolver (VQE) is used to formulate a recursive Balanced Min-Cut (BMC) algorithm, and it is suggested that quantum machine learning techniques can lower error rates and allow for faster convergence to an optimal solution. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: August 16, 2021

2019 article

Implementing NChooseK on IBM Q Quantum Computer Systems

REVERSIBLE COMPUTATION (RC 2019), Vol. 11497, pp. 209–223.

By: H. Khetawat n, A. Atrey n, G. Li n, F. Mueller n & S. Pakin*

author keywords: IBM Q; Quantum computing; NChooseK
TL;DR: This work implements a code generator that, given arbitrary parameters for N and K, generates code suitable for execution on IBM Q quantum hardware and assess the performance of the code generator, limitations in the size of circuit depth and number of gates, and proposed optimizations. (via Semantic Scholar)
Source: Web Of Science
Added: November 25, 2019

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