Search Results for author: Daniel Lidar

Found 3 papers, 1 papers with code

Charged particle tracking with quantum annealing-inspired optimization

no code implementations13 Aug 2019 Alexander Zlokapa, Abhishek Anand, Jean-Roch Vlimant, Javier M. Duarte, Joshua Job, Daniel Lidar, Maria Spiropulu

At the High Luminosity Large Hadron Collider (HL-LHC), traditional track reconstruction techniques that are critical for analysis are expected to face challenges due to scaling with track density.

Combinatorial Optimization

Quantum adiabatic machine learning with zooming

1 code implementation13 Aug 2019 Alexander Zlokapa, Alex Mott, Joshua Job, Jean-Roch Vlimant, Daniel Lidar, Maria Spiropulu

The significant improvement of quantum annealing algorithms for machine learning and the use of a discrete quantum algorithm on a continuous optimization problem both opens a new class of problems that can be solved by quantum annealers and suggests the approach in performance of near-term quantum machine learning towards classical benchmarks.

BIG-bench Machine Learning Quantum Machine Learning

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