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Admittance extraction of quantum dot arrays for charge sensing
Abstract
This work demonstrates admittance extraction of quantum dot arrays using a rate equation frame- work matching experimental reflectometry measurements. Using a semiclassical rate equation, we consider a perturbation of the source/drain chemical potential to model reflectometry readout in a quantum dot array. This is a time-dependent extension of the rate equation which has been employed in literature for pumped arrays of quantum dots and capacitance extractions. Here we extend this to a double quantum dot for admittance extraction. The simulations are calibrated us- ing Fermi-Hubbard parameters extracted from experimental data, which it is then shown to closely approximate to.
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BibTeX
@misc{power2026admittance,
title = {{Admittance extraction of quantum dot arrays for charge sensing}},
author = {Conor Power and Mathieu Moras and Andrii Sokolov and Robert Bogdan Staszewski and Elena Blokhina},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.16590},
eprint = {2610.16590},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.16590},
}
RIS
TY - UNPB
TI - Admittance extraction of quantum dot arrays for charge sensing
AU - Conor Power
AU - Mathieu Moras
AU - Andrii Sokolov
AU - Robert Bogdan Staszewski
AU - Elena Blokhina
PY - 2026
DA - 2026/10/12
PB - arXiv
DO - 10.48550/arxiv.2610.16590
UR - https://arxiv.org/abs/2610.16590
AB - This work demonstrates admittance extraction of quantum dot arrays using a rate equation frame- work matching experimental reflectometry measurements. Using a semiclassical rate equation, we consider a perturbation of the source/drain chemical potential to model reflectometry readout in a quantum dot array. This is a time-dependent extension of the rate equation which has been employed in literature for pumped arrays of quantum dots and capacitance extractions. Here we extend this to a double quantum dot for admittance extraction. The simulations are calibrated us- ing Fermi-Hubbard parameters extracted from experimental data, which it is then shown to closely approximate to.
ER -