Sandesh Kalantre
Sandesh Kalantre
JQI-QuICS Lanczos Graduate Fellow, University of Maryland
Bestätigte E-Mail-Adresse bei umd.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Machine learning techniques for state recognition and auto-tuning in quantum dots
SS Kalantre, JP Zwolak, S Ragole, X Wu, NM Zimmerman, MD Stewart, ...
npj Quantum Information 5 (1), 1-10, 2019
412019
Autotuning of Double-Dot Devices In Situ with Machine Learning
JP Zwolak, T McJunkin, SS Kalantre, JP Dodson, ER MacQuarrie, ...
Physical review applied 13 (3), 034075, 2020
292020
QFlow lite dataset: A machine-learning approach to the charge states in quantum dot experiments
JP Zwolak, SS Kalantre, X Wu, S Ragole, JM Taylor
PloS one 13 (10), e0205844, 2018
162018
Supercurrent interference in semiconductor nanowire Josephson junctions
P Sriram, SS Kalantre, K Gharavi, J Baugh, B Muralidharan
Physical Review B 100 (15), 155431, 2019
132019
Josephson detection of time-reversal symmetry broken superconductivity in SnTe nanowires
CJ Trimble, MT Wei, NFQ Yuan, SS Kalantre, P Liu, HJ Han, MG Han, ...
npj Quantum Materials 6 (1), 1-6, 2021
82021
Machine learning techniques for state recognition and auto-tuning in quantum dots. npj Quantum Inf. 5
SS Kalantre
52019
Ray-based framework for state identification in quantum dot devices
JP Zwolak, T McJunkin, SS Kalantre, SF Neyens, ER MacQuarrie, ...
PRX Quantum 2 (2), 020335, 2021
42021
Ray-based classification framework for high-dimensional data
JP Zwolak, SS Kalantre, T McJunkin, BJ Weber, JM Taylor
arXiv preprint arXiv:2010.00500, 2020
42020
Anomalous phase dynamics of driven graphene Josephson junctions
SS Kalantre, F Yu, MT Wei, K Watanabe, T Taniguchi, ...
Physical Review Research 2 (2), 023093, 2020
32020
Theoretical bounds on data requirements for the ray-based classification
BJ Weber, SS Kalantre, T McJunkin, JM Taylor, JP Zwolak
SN Computer Science 3 (1), 1-10, 2022
12022
Toward Robust Autotuning of Noisy Quantum Dot Devices
J Ziegler, T McJunkin, ES Joseph, SS Kalantre, B Harpt, DE Savage, ...
arXiv preprint arXiv:2108.00043, 2021
12021
Learning the states of double quantum dot systems: A ray-based approach
J Zwolak, T McJunkin, S Kalantre, S Neyens, E MacQuarrie, L Edge, ...
Bulletin of the American Physical Society 65, 2020
12020
Towards autonomous tuning of noisy quantum dots
J Ziegler, S Kalantre, T McJunkin, M Eriksson, J Taylor, J Zwolak
Bulletin of the American Physical Society, 2021
2021
Learning the states of quantum dot systems: The ray-based approach
J Zwolak, T McJunkin, S Kalantre, S Neyens, E MacQuarrie, L Edge, ...
Bulletin of the American Physical Society, 2021
2021
Machine Learning-Based control of 2D Arrays of Quantum Dots
A Izadi Rad, S Kalantre, J Taylor, J Zwolak
Bulletin of the American Physical Society 65, 2020
2020
True machine learning for quantum dot tune-up
J Zwolak, J Taylor, S Kalantre, X Wu
APS March Meeting Abstracts 2019, X34. 001, 2019
2019
Quantum-Transport in Semiconductor Nanowire Josephson Junctions
P Sriram, S Kalantre, K Gharavi, J Baugh, B Muralidharan
APS March Meeting Abstracts 2019, S05. 009, 2019
2019
AC Josephson effect in a capacitively shunted graphene Josephson junction
F Yu, S Kalantre, G Finkelstein, F Amet, J Williams
APS March Meeting Abstracts 2019, L54. 007, 2019
2019
Non-linear dynamical effects and crisis in an RF-driven graphene Josephson junction
S Kalantre, F Yu, J Williams
Bulletin of the American Physical Society 63, 2018
2018
Applying Machine Learning to Quantum-Dot Experiments: Generation of Training Datasets and Auto-tuning
S Kalantre, J Zwolak, X Wu, S Ragole, J Taylor
APS March Meeting Abstracts 2018, K28. 002, 2018
2018
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