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Microelectronics and Quantum Chip Modeling


CCSE Microelectronics Modeling Team

Jackie Yao

Ann Almgren

Revathi Jambunathan

Prabhat Kumar

Andy Nonaka

Artemis

What is ARTEMIS?


ARTEMIS (Adaptive mesh Refinement Time-domain ElectrodynaMics Solver) is a time-domain electrodynamics solver developed in CCSE that is fully open-source and portable from laptops to many-core/GPU exascale systems. The core solver is a finite-difference time-domain (FDTD) implementation for Maxwell's equations that has been adapted to conditions found in microelectronic circuitry. This includes spatially-varying material properties, boundary conditions, and external sources to model our target problems. In order to achieve portability and performance on a range of platforms, ARTEMIS leverages the developments of two DOE Exascale Computing Project (ECP) code frameworks. First, the AMReX software library is the product of the ECP co-design center for adaptive, structured grid calculations. AMReX provides complete data structure and parallel communication support for massively parallel many-core/GPU implementations of structuredgrid simulations such as FDTD. Second, the WarpX accelerator code is an ECP application code for modeling plasma wakefield accelerators and contains many features that have been leveraged by ARTEMIS. These features include core computational kernels for FDTD, an overall time stepping framework, and I/O. Using the ARTEMIS python-style function interpreter, we can define more advanced structures containing many different material types using different geometrical configurations. Additionally, the GPU capability of the code provides extreme speed, as a GPU build offers a 59x speedup over the host on a node-by-node basis. Thus, using HPC resources will allow for high-resolution and rapid prototyping of various configurations with different geometries and material properties. We also note algorithmic flexibility for additional physics such as magnetic and superconducting materials.

For more information about ARTEMIS or any of the applications below, contact the ARTEMIS Team or visit the ARTEMIS github page.


Spin Dynamics


The trend of technology in recent years has been towards miniaturization and interconnection. Continuous scaling down of circuitry is pushing Moore's law in the semiconductor industry nearly to an end and has entailed novel materials and new techniques to generate nanoscale devices with desired performance. Such new materials and techniques usually involve multiple physical mechanisms. For instance, one of the thriving techniques is to use magnetic spins to control and manipulate electromagnetic (EM) signals in radio-frequency (RF) circuitry, with exceptional scalability and low power dissipation. The corporation of new mechanism also enables things like quantum computing. However, the state-of-the-art design of RF magnetic devices has been hindered mainly by the lack of effective modeling tool to tackle the interaction between oscillating magnetization and EM waves. This problem is primarily due to the inherent disparity in time and length scale between magnetic spin oscillations and EM waves. Hence, in order to fully understand the underlying physics and design the next-generation devices, a new multiphysics modeling approach is needed.

We are using new physical coupling in potential electronic devices. This includes modeling and characterization of miniaturized magnetic components in radio-frequency (RF) systems, specifically nonlinear dynamic magnetic spin oscillations interacting with EM waves. We are developing a unique numerical algorithm to predict the influence of magnetic spins on the performance of compact RF devices. The Development of this multi-physics software is under the framework of AMReX, with features of massively parallel computing and block-structured adaptive mesh refinement (AMR). Such modeling tools enable a unique ability to accurately model and design next-generation RF systems and components.

Classical Modeling of Quantum Chips


In an effort to aid in the design of better quantum chip prototypes, we are developing a new numerical modeling capability to predict both the interaction between qubits and photons (known as circuit quantum electrodynamics, or QED) and the cross-talk between qubits and in-air electromagnetic (EM) waves.

This requires implementation of new physical models to resolve the non-linear interactions between the EM field and the quantum response from the Josephson junction modeled using a hybrid classical-quantum approach. Additionally, to model the photon-qubit interaction, the Maxwell's equations will be implicitly coupled to the Schrodinger equation that quantifies the qubit response to the applied and self-consistent EM field.

With the use of adaptive mesh and adaptive algorithm approach for this complex electrodynamic material model with a complex embedded geomtry, we will be able to conduct a detailed numerical study on the loss mechanisms for a given quantum chip prototype.


Nano-Sensors on CMOS


As traditional CMOS scaling offers diminishing gains in performance, alternative approaches, such as codesign and heterogeneous integration of low-dimensional (0D, 1D and 2D) materials, present new opportunities. We are developing scalable integration of photon nano-sensors on a CMOS platform. CMOS circuit simulation is an indispensable part of any modern design. Manufacturers provide extremely detailed simulation models for the devices in their process, to be used with specific circuit simulators. These are generally based on SPICE for the lowest level simulations that are carried out. Incorporating new active devices that will be part of the same circuit along with CMOS transistors requires the same level of detail and full compatibility with the commercial simulator codes used. While transistor models have typically been extracted from parameter analyzer measurements on a large variety of device geometries and test conditions, this approach would be prohibitive for initial modeling of new nano-devices, where generating a large variety of test devices and making hundreds of measurements on each would represent a large effort and take a long time. We will instead rely on physical modeling starting from the device structure using ARTEMIS.


Publications


Z. Yao, R. Jambunathan, Y. Zeng, and A. Nonaka, A Massively Parallel Time-Domain Coupled Electrodynamics-Micromagnetics Solver, submitted for publication, 2021. [arxiv]