Raphael C. Pooser

According to our database1, Raphael C. Pooser authored at least 19 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Characterizing and mitigating coherent errors in a trapped ion quantum processor using hidden inverses.
Quantum, May, 2023

Measuring qubit stability in a gate-based NISQ hardware processor.
Quantum Inf. Process., February, 2023

Evaluating Robust Entanglement on a Trapped Ion Platform.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

Molecular Symmetry in VQE: A Dual Approach for Trapped-Ion Simulations of Benzene.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

2022
Mode connectivity in the loss landscape of parameterized quantum circuits.
Quantum Mach. Intell., 2022

Collective neutrino oscillations on a quantum computer.
Quantum Inf. Process., 2022

Unsupervised Digit Recognition Using Cosine Similarity In A Neuromemristive Competitive Learning System.
ACM J. Emerg. Technol. Comput. Syst., 2022


2021
QuaSiMo: A composable library to program hybrid workflows for quantum simulation.
IET Quantum Commun., December, 2021

Quantum Circuit Transformations with a Multi-Level Intermediate Representation Compiler.
CoRR, 2021

Lessons Learned on the Interface Between Quantum and Conventional Networking.
Proceedings of the Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation, 2021

Discriminating Quantum States with Quantum Machine Learning.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2021

Composable Programming of Hybrid Workflows for Quantum Simulation.
Proceedings of the 18th IEEE International Conference on Software Architecture Companion, 2021

Mode connectivity in the QCBM loss landscape: ICCAD Special Session Paper.
Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2021

Building scalable variational circuit training for machine learning tasks.
Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

2020
Error-mitigated data-driven circuit learning on noisy quantum hardware.
Quantum Mach. Intell., 2020

Scalable quantum processor noise characterization.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2020

2019
Toward convergence of effective field theory simulations on digital quantum computers.
CoRR, 2019

2017
Evaluating online-learning in memristive neuromorphic circuits.
Proceedings of the Neuromorphic Computing Symposium, 2017


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