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Travis L Scholten
Travis L Scholten
Technical Lead, Public Sector @IBM Quantum
Email verificata su ibm.com - Home page
Titolo
Citata da
Citata da
Anno
Gate set tomography
E Nielsen, JK Gamble, K Rudinger, T Scholten, K Young, R Blume-Kohout
Quantum 5, 557, 2021
2452021
Application-motivated, holistic benchmarking of a full quantum computing stack
D Mills, S Sivarajah, TL Scholten, R Duncan
Quantum 5, 415, 2021
562021
Analyzing the Performance of Variational Quantum Factoring on a Superconducting Quantum Processor
AH Karamlou, WA Simon, A Katabarwa, TL Scholten, B Peropadre, Y Cao
npj Quantum Information 7, 2021
502021
Behavior of the maximum likelihood in quantum state tomography
TL Scholten, R Blume-Kohout
New Journal of Physics 20 (2), 023050, 2018
332018
Assessing the benefits and risks of quantum computers
TL Scholten, CJ Williams, D Moody, M Mosca, W Hurley, WJ Zeng, ...
arXiv preprint arXiv:2401.16317, 2024
162024
Circuit knitting toolbox
L Bello, AM Branczyk, S Bravyi, AC Vazquez, A Eddins, DJ Egger, B Fuller, ...
112023
Classifying single-qubit noise using machine learning
TL Scholten, YK Liu, K Young, R Blume-Kohout
arXiv preprint arXiv:1908.11762, 2019
82019
Turbocharging quantum tomography
RJ Blume-Kohout, JK Gamble, E Nielsen, PLW Maunz, TL Scholten, ...
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2015
72015
Qiskit: An open-source framework for quantum computing
J Gambetta, DM Rodríguez, SP González, M Treinish, A Javadi-Abhari, ...
DOI, 2021
52021
A Model for Circuit Execution Runtime And Its Implications for Quantum Kernels At Practical Data Set Sizes
TL Scholten, D Perry II, J Washington, JR Glick, T Ward
arXiv preprint arXiv:2307.04980, 2023
12023
Kernel Matrix Completion for Offline Quantum-Enhanced Machine Learning
A Naveh, I Fitzgerald, A Phan, A Lockwood, TL Scholten
arXiv preprint arXiv:2112.08449, 2021
12021
Machine-learned QCVV for distinguishing single-qubit noise
T Scholten, YK Liu, K Young, R Blume-Kohout
APS March Meeting Abstracts 2019, E27. 011, 2019
2019
Towards Scalable Characterization of Noisy, Intermediate-Scale Quantum Information Processors
TL Scholten
University of New Mexico, 2018
2018
High-Accuracy Classification of Single-Qubit Noise via Machine Learning.
TL Scholten
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2018
2018
A Few Thoughts on Characterizing Quantum Hardware.
TL Scholten
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2018
2018
On the edge: Geometry model selection and quantum compressed sensing.
TL Scholten
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2018
2018
Machine Learning of Noise in Single-Qubit Hardware
T Scholten, R Blume-Kohout
APS March Meeting Abstracts 2018, C39. 007, 2018
2018
Learning Noise in Quantum Information Processors.
TL Scholten
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2017
2017
An Effective State Space Dimension For A Quantum System.
TL Scholten
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2016
2016
Tomographing Quantum State Tomography.
TL Scholten
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2016
2016
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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