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Title: QCAD simulation and optimization of semiconductor double quantum dots

Abstract

We present the Quantum Computer Aided Design (QCAD) simulator that targets modeling quantum devices, particularly silicon double quantum dots (DQDs) developed for quantum qubits. The simulator has three di erentiating features: (i) its core contains nonlinear Poisson, e ective mass Schrodinger, and Con guration Interaction solvers that have massively parallel capability for high simulation throughput, and can be run individually or combined self-consistently for 1D/2D/3D quantum devices; (ii) the core solvers show superior convergence even at near-zero-Kelvin temperatures, which is critical for modeling quantum computing devices; (iii) it couples with an optimization engine Dakota that enables optimization of gate voltages in DQDs for multiple desired targets. The Poisson solver includes Maxwell- Boltzmann and Fermi-Dirac statistics, supports Dirichlet, Neumann, interface charge, and Robin boundary conditions, and includes the e ect of dopant incomplete ionization. The solver has shown robust nonlinear convergence even in the milli-Kelvin temperature range, and has been extensively used to quickly obtain the semiclassical electrostatic potential in DQD devices. The self-consistent Schrodinger-Poisson solver has achieved robust and monotonic convergence behavior for 1D/2D/3D quantum devices at very low temperatures by using a predictor-correct iteration scheme. The QCAD simulator enables the calculation of dot-to-gate capacitances, and comparison with experiment andmore » between solvers. It is observed that computed capacitances are in the right ballpark when compared to experiment, and quantum con nement increases capacitance when the number of electrons is xed in a quantum dot. In addition, the coupling of QCAD with Dakota allows to rapidly identify which device layouts are more likely leading to few-electron quantum dots. Very efficient QCAD simulations on a large number of fabricated and proposed Si DQDs have made it possible to provide fast feedback for design comparison and optimization.« less

Authors:
 [1];  [1];  [1];  [1];  [1];  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1204068
Report Number(s):
SAND2013-10575
498148
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English

Citation Formats

Nielsen, Erik, Gao, Xujiao, Kalashnikova, Irina, Muller, Richard Partain, Salinger, Andrew Gerhard, and Young, Ralph Watson. QCAD simulation and optimization of semiconductor double quantum dots. United States: N. p., 2013. Web. doi:10.2172/1204068.
Nielsen, Erik, Gao, Xujiao, Kalashnikova, Irina, Muller, Richard Partain, Salinger, Andrew Gerhard, & Young, Ralph Watson. QCAD simulation and optimization of semiconductor double quantum dots. United States. https://doi.org/10.2172/1204068
Nielsen, Erik, Gao, Xujiao, Kalashnikova, Irina, Muller, Richard Partain, Salinger, Andrew Gerhard, and Young, Ralph Watson. 2013. "QCAD simulation and optimization of semiconductor double quantum dots". United States. https://doi.org/10.2172/1204068. https://www.osti.gov/servlets/purl/1204068.
@article{osti_1204068,
title = {QCAD simulation and optimization of semiconductor double quantum dots},
author = {Nielsen, Erik and Gao, Xujiao and Kalashnikova, Irina and Muller, Richard Partain and Salinger, Andrew Gerhard and Young, Ralph Watson},
abstractNote = {We present the Quantum Computer Aided Design (QCAD) simulator that targets modeling quantum devices, particularly silicon double quantum dots (DQDs) developed for quantum qubits. The simulator has three di erentiating features: (i) its core contains nonlinear Poisson, e ective mass Schrodinger, and Con guration Interaction solvers that have massively parallel capability for high simulation throughput, and can be run individually or combined self-consistently for 1D/2D/3D quantum devices; (ii) the core solvers show superior convergence even at near-zero-Kelvin temperatures, which is critical for modeling quantum computing devices; (iii) it couples with an optimization engine Dakota that enables optimization of gate voltages in DQDs for multiple desired targets. The Poisson solver includes Maxwell- Boltzmann and Fermi-Dirac statistics, supports Dirichlet, Neumann, interface charge, and Robin boundary conditions, and includes the e ect of dopant incomplete ionization. The solver has shown robust nonlinear convergence even in the milli-Kelvin temperature range, and has been extensively used to quickly obtain the semiclassical electrostatic potential in DQD devices. The self-consistent Schrodinger-Poisson solver has achieved robust and monotonic convergence behavior for 1D/2D/3D quantum devices at very low temperatures by using a predictor-correct iteration scheme. The QCAD simulator enables the calculation of dot-to-gate capacitances, and comparison with experiment and between solvers. It is observed that computed capacitances are in the right ballpark when compared to experiment, and quantum con nement increases capacitance when the number of electrons is xed in a quantum dot. In addition, the coupling of QCAD with Dakota allows to rapidly identify which device layouts are more likely leading to few-electron quantum dots. Very efficient QCAD simulations on a large number of fabricated and proposed Si DQDs have made it possible to provide fast feedback for design comparison and optimization.},
doi = {10.2172/1204068},
url = {https://www.osti.gov/biblio/1204068}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Dec 01 00:00:00 EST 2013},
month = {Sun Dec 01 00:00:00 EST 2013}
}