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Supanut Thanasilp
Supanut Thanasilp
PhD student, Centre for Quantum Technologies
Verified email at u.nus.edu
Title
Cited by
Cited by
Year
Exponential concentration and untrainability in quantum kernel methods
S Thanasilp, S Wang, M Cerezo, Z Holmes
arXiv preprint arXiv:2208.11060, 2022
472022
Subtleties in the trainability of quantum machine learning models
S Thanasilp, S Wang, NA Nghiem, P Coles, M Cerezo
Quantum Machine Intelligence 5 (1), 21, 2023
352023
Expressibility and trainability of parametrized analog quantum systems for machine learning applications
J Tangpanitanon, S Thanasilp, N Dangniam, MA Lemonde, DG Angelakis
Physical Review Research 2 (4), 043364, 2020
282020
Qubit-efficient encoding schemes for binary optimisation problems
B Tan, MA Lemonde, S Thanasilp, J Tangpanitanon, DG Angelakis
Quantum 5, 454, 2021
232021
Does provable absence of barren plateaus imply classical simulability? Or, why we need to rethink variational quantum computing
M Cerezo, M Larocca, D García-Martín, NL Diaz, P Braccia, E Fontana, ...
arXiv preprint arXiv:2312.09121, 2023
112023
Trainability barriers and opportunities in quantum generative modeling
MS Rudolph, S Lerch, S Thanasilp, O Kiss, S Vallecorsa, M Grossi, ...
arXiv preprint arXiv:2305.02881, 2023
102023
Exponential concentration and untrainability in quantum kernel methods,(2022)
S Thanasilp, S Wang, M Cerezo, Z Holmes
arXiv preprint arXiv:2208.11060, 0
8
Quantum supremacy and quantum phase transitions
S Thanasilp, J Tangpanitanon, MA Lemonde, N Dangniam, DG Angelakis
Physical Review B 103 (16), 165132, 2021
72021
Signatures of a sampling quantum advantage in driven quantum many-body systems
J Tangpanitanon, S Thanasilp, MA Lemonde, N Dangniam, DG Angelakis
Quantum Science and Technology 8 (2), 025019, 2023
42023
Quantum supremacy with analog quantum processors for material science and machine learning
J Tangpanitanon, S Thanasilp, MA Lemonde, DG Angelakis
arXiv preprint arXiv:1906.03860, 2019
32019
On fundamental aspects of quantum extreme learning machines
W Xiong, G Facelli, M Sahebi, O Agnel, T Chotibut, S Thanasilp, Z Holmes
arXiv preprint arXiv:2312.15124, 2023
22023
Efficiently extracting multi-point correlations of a floquet thermalized system
YG Zheng, WY Zhang, YC Shen, A Luo, Y Liu, MG He, HR Zhang, W Lin, ...
arXiv preprint arXiv:2210.08556, 2022
22022
A unified framework for trace-induced quantum kernels
BY Gan, D Leykam, S Thanasilp
arXiv preprint arXiv:2311.13552, 2023
12023
Quantum supremacy in driven quantum many-body systems
J Tangpanitanon, S Thanasilp, MA Lemonde, N Dangiam, DG Angelakis
arXiv preprint arXiv:2002.11946, 2020
12020
Potentials and Limitations of Analog Quantum Simulators in Variational Quantum Algorithms
K Srimahajariyapong, S Thanasilp, T Chotibut
Bulletin of the American Physical Society, 2024
2024
arXiv: Trainability barriers and opportunities in quantum generative modeling
MS Rudolph, S Lerch, Z Holmes, S Vallecorsa, S Thanasilp, M Grossi, ...
2023
Expressivity and generalization error of projected fidelity quantum kernels
BY Gan, S Thanasilp, D Leykam, D Angelakis
Bulletin of the American Physical Society, 2023
2023
Qubit-efficient encoding schemes for binary optimisation problems
B Tan, MA Lemonde, S Thanasilp, J Tangpanitanon, D Angelakis
Bulletin of the American Physical Society, 2021
2021
Quantum supremacy in driven quantum many-body systems
J Tangpanitanon, S Thanasilp, MA Lemonde, N Dangniam, D Angelakis
Bulletin of the American Physical Society, 2021
2021
Quantum supremacy and quantum phase transitions
S Thanasilp, J Tangpanitanon, MA Lemonde, N Dangniam, D Angelakis
Bulletin of the American Physical Society, 2021
2021
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Articles 1–20