The solution of MOCEX converges to that of a Monte Carlo code as the discretization of angle, space and energy is refined, unlike the 2D/1D method. This formulation overcomes the drawbacks of a full 3D MOC method requiring enormous memory and computational resources and resolves the more » instability issues of the 2D/1D method as well. Among them, the MOC solver based on the extruded geometry, thus named MOCEX, can produce the faithful 3-D transport solutions by employing the rigorous and robust 2D/3D MOC formulation. ![]() PROTEUS includes two distinct transport solvers: SN and MOC. Under the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the 3D whole core transport code PROTEUS has been developed at Argonne National Laboratory to perform the detailed 3D transport calculation for various reactor types including irregular or complex geometric reactors. 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. In addition, the coupling of QCAD with Dakota allows to rapidly identify which device layouts are more likely leading to few-electron quantum dots. 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. ![]() The QCAD simulator enables the calculation of dot-to-gate capacitances, and comparison with experiment and more » between solvers. 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 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 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 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. We present the Quantum Computer Aided Design (QCAD) simulator that targets modeling quantum devices, particularly silicon double quantum dots (DQDs) developed for quantum qubits.
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