We present current developments in Keysight Pathwave Quantum Technology to analyze superconducting quantum circuits. Particularly, Pathwave ADS and its most recent Electromagnetic (EM) simulation package, QuantumPro, enable investigating nonlinear effects such as cavity quantum electrodynamics and automated computation of the quantum parameters including the qubit anharmonicities and cross-Kerr strengths. Under the low power assumption, superconducting qubits are treated as linear lumped circuit elements in the EM simulation environment. To study the nonlinear regime, Pathwave ADS provides a co-simulation approach that enables combining the linear frequency response from the full-wave EM simulation with the nonlinear circuit analysis in the ADS schematic. To assess the accuracy of Pathwave ADS, we compare the results to the two coupled transmons showcase example from the IBM Quantum Qiskit Metal framework. In addition, we also demonstrate power-dependent nonlinear bending of the frequency response by sweeping the input power into the superconducting circuits in Pathwave ADS.
We present current developments in Keysight Pathwave Quantum Technology to analyze superconducting quantum circuits. Particularly, Pathwave ADS and its most recent Electromagnetic (EM) simulation package, QuantumPro, enable investigating nonlinear effects such as cavity quantum electrodynamics and automated computation of the quantum parameters including the qubit anharmonicities and cross-Kerr strengths. Under the low power assumption, superconducting qubits are treated as linear lumped circuit elements in the EM simulation environment. To study the nonlinear regime, Pathwave ADS provides a co-simulation approach that enables combining the linear frequency response from the full-wave EM simulation with the nonlinear circuit analysis in the ADS schematic. To assess the accuracy of Pathwave ADS, we compare the results to the two coupled transmons showcase example from the IBM Quantum Qiskit Metal framework. In addition, we also demonstrate power-dependent nonlinear bending of the frequency response by sweeping the input power into the superconducting circuits in Pathwave ADS.
We present the analysis of 3D superconducting qubits using PathWave EMPro with its scripting feature that enables quantum parameter extraction and design automation of 3D qubits. In the electromagnetic study, the qubits are represented by their ‘linearized’ lumped inductances at very low signal excitation, and then for a full description of the quantum system, the nonlinear quantum parameters are extracted. We consider here the configuration in Ref. [1] as a showcase example of a 3D qubit with published measurements. Qubit anharmonicities and cross-Kerr strengths are calculated from both the frequency domain response using black-box quantization [2] and from the eigenmode solution using the energy participation method [3], [4]. For a rigorous nonlinear analysis, the frequency response of the 3D qubit using a nonlinear Josephson junction model is produced in PathWave ADS Co-simulation environment. Both the linear and nonlinear analyses in PathWave tools yield similar circuit responses, which validate the accuracy of EMPro to simulate 3D superconducting qubits.
Accurate prediction of qubit–qubit exchange coupling is essential for superconducting processor design. We present and benchmark an automated full-wave electromagnetic (EM) workflow in Keysight Advanced Design System (ADS) and QuantumPro that evaluates pairwise exchange couplings from layout-level multiport responses using the established transfer-impedance relation of Solgun et al. Because many scalable superconducting processors employ repeated or near-repeated coupling motifs, reduced EM models can lower computational cost if their error is quantified. We study nearest-neighbor couplings in a reconstructed geometry based on the IBM Q 16 Rueschlikon processor using a sixteen-qubit (16Q) coupling-network model, four-qubit (4Q) unit-cell models, and pair-specific two-qubit (2Q) sub-blocks. The 4Q models provide a like-for-like external benchmark because they match the model extent used by Solgun et al. for the published full-wave coupling calculations. The 4Q models reproduce the published simulated couplings with a 3.70% mean absolute percentage error and differ from 16Q by 3.62% on average. For the representative single solves reported here, the 16Q solve takes approximately 7.2 times as long as 4Q and requires 5.7 times the peak memory. This supports 4Q as a practical reduced model for quantitative local coupling prediction. Further reduction to 2Q changes the couplings by 6.17% on average but remains effective for inexpensive mesh-convergence screening. The resulting workflow provides automated exchange-coupling extraction together with model-extent and convergence assessment in a commercial microwave EDA environment.
We present an efficient, accurate, and comprehensive analysis framework for generic, multi-port nonlinear parametric circuits, in the presence of dissipation from lossy circuit components, based on "quantum-adapted" X-parameters. We apply this method to Josephson traveling-wave parametric amplifiers (JTWPAs) – a key component in superconducting and spin qubit quantum computing architectures – which are challenging to model accurately due to their thousands of linear and nonlinear circuit components. X-parameters are generated from a harmonic balance solution of the classical nonlinear circuit and then mapped to the field ladder operator basis, so that the energy associated with each of the multiple interacting modes corresponds to photon occupancy, rather than classical power waves. Explicit relations for the quantum efficiency of a generic, multi-port, multi-frequency parametric circuit are presented and evaluated for two distinct JTWPA designs. The gain and quantum efficiency are consistent with those obtained from Fourier analysis of time-domain solutions, but with enhanced accuracy, speed, and the ability to include real-world impairments, statistical variations, parasitic effects, and impedance mismatches (inand out-of-band) seamlessly. The unified flow is implemented in Keysight’s PathWave Advanced Design System (ADS) and independently in an open-source simulation code, JosephsonCircuits.jl, from the MIT authors.
The development of large-scale superconducting quantum computers critically depends on the accurate readout of qubit states. To enable this, cryogenic parametric amplifiers have been proposed and developed, and have since found widespread use in small-signal detection applications. Among various amplifier architectures, Josephson traveling-wave parametric amplifiers (JTWPAs) are widely adopted due to their broad bandwidth, high saturation power, and compatibility with superconducting qubits. In this work, we present a design workflow of JTWPAs based on a co-simulation approach combining electromagnetic (EM) and circuit-level simulation. We apply this method to a uniform JTWPA, comparing our simulation results with experimental data. To mitigate the challenge of constructing lumped element circuit models usually used in conventional simulation method, we directly perform full EM analysis of the device to accurately determine its linear response. The extracted S parameters are then fed into a nonlinear harmonic balance simulator with Josephson junctions modeled as circuit elements. By doing so, the linear and gain properties of the JTWPA are extracted. Different factors that impact device performance including gain compression, phase matching, and fabrication imperfections are further investigated and modeled. A good agreement between simulation and measurements is identified, establishing the effectiveness of our approach in designing quantum parametric amplifiers.
This paper examines the use of a quantum electronics Josephson Traveling-Wave Parametric Amplifier (JTWPA). The JTWPA presents distinctive features for amplifying quantum signals through the nonlinear Josephson junction, influenced by quantum effects at microwave energy scales. The study focuses on characterizing this quantum effects-based parametric amplification, offering perspectives in communication and information processing technologies. The results, obtained with the Advanced Design System (ADS) pathWave tool suggest promising applications of JTWPA, paving the way for significant advances in quantum electronics. Notably, the findings indicate that at a fixed frequency of 4 GHz and a constant pump current of 1.85 µA, the transmission efficiency of JTWPA decreases by 32% when exporting the design as layouts using the High-Frequency Structural Simulator (HFSS). Consequently, optimization with ADS emerges as a crucial step to assess transmission and information processing before the physical implementation of the JTWPA design.
Abstract Designing superconducting quantum circuits involves optimizing the layout to achieve certain target parameters. This optimization process usually depends on iterative electromagnetic simulations, which are computationally expensive and require manual intervention to adjust the layout parameters. Here, we present a method to efficiently automate the optimization of superconducting circuits, which significantly reduces the need for manual intervention. The method’s efficiency arises from approximate nonlinear model-driven (ANMod) parameter updates, which are constructed from the user’s physical knowledge. Additionally, we provide a full implementation using the ANMod-method as an open-source Python package, QDesignOptimizer. The package automates the design workflow by combining high-accuracy electromagnetic simulations in ansys HFSS and energy participation ratio (pyEPR) analysis integrated with the design tool quantum-metal (formerly known as Qiskit-Metal). Our implementation supports modular and flexible subsystem-level analysis and is easily extensible to optimize for additional parameters. The ANMod-method is not specific to superconducting circuits; as such, it can be applied to a range of nonlinear optimization problems across science and technology.