Keysight Introduces Quantum Circuit Simulation the First Circuit Environment with Frequency-Domain Flux Quantization

Keysight Technologies introduces Quantum Circuit Simulation (Quantum Ckt Sim), an innovative circuit design environment that speeds up the development of intricate quantum circuits. In addition, by joining forces with Google Quantum AI, the solution incorporates advanced flux quantization which marks an industry-first achievement. 

In the realm of superconducting quantum circuits, accurately modeling flux quantization is paramount. This fundamental property ensures that the magnetic flux through a superconducting loop is quantized in discrete units, a critical aspect for the operation of quantum circuits. Google Quantum AI and Keysight have collaborated to address this challenge and enhance quantum circuit simulations through the integration of frequency-domain flux quantization into circuit solvers. By precisely modeling flux quantization, the new solution enables researchers to design more reliable and efficient superconducting circuits. 

The collaboration’s success is detailed in a recently posted technical paper, titled “Modeling flux-quantizing Josephson junction circuits in Keysight ADS”. This paper demonstrates the innovative approach to flux-quantization and its significant impact on the field of quantum computing.  The success sets a new standard for accuracy and efficiency of modeling superconducting circuits.

The new solution streamlines quantum workflow with advanced flux quantization in the frequency domain, providing unparalleled accuracy and capability in analyzing large, highly nonlinear quantum circuits. This enables researchers to model complex quantum circuits with better accuracy, reducing computational errors and enhancing the overall reliability of simulations.

Key features of the Quantum Ckt Sim design and simulation solution include: 

• Quantum Devices Library – Incorporates a library of quantum devices in Keysight ADS encompassing those most frequently used such as RF/DC SQUIDs, SNAILs, FLUXONIUMs, and SNAKEs.
• Comprehensive Design Environment – Features a range of nonlinear circuit simulators such as harmonic balance, transient / convolution for time domain, circuit envelope for modulation domain, and x-parameters nonlinear model generator.
• Enhanced Quantum Control – Enables the driving of superconducting circuits with external flux, allowing for more precise control and manipulation of quantum circuits in advanced quantum computing applications.
• Streamlined design – Simplifies the design of parametric quantum circuits including quantum amplifiers, the critical blocks on the output chains of quantum systems that improve readout fidelity.

Google Quantum AI, has established itself as a key player in the quantum computing arena, driving significant advancements in the field. With its state-of-the-art quantum processors and pioneering research, Google has achieved notable milestones, including the demonstration of beyond-classical computation and has been actively involved in the development of advanced quantum amplifiers, which are essential for enhancing the performance of quantum systems. 

Ofer Naaman, Research Scientist, Google Quantum AI, said: “Using Quantum Ckt Sim, it is now possible to enforce flux quantization conditions in ADS frequency-domain simulations of superconducting devices. This is a critical capability whose absence thus far limited the usability of modern EDA tools in microwave superconducting circuit design.” 

Mohamed Hassan, Quantum Solutions Planning Lead, Keysight EDA, said, “It’s thrilling to witness the accurate modeling of frequency domain flux quantization of superconducting circuits using an EDA tool for the first time. This significant milestone leverages EDA capabilities to streamline the design of superconducting microwave circuits for quantum applications and beyond. We anticipate this advancement will empower quantum engineers to enhance the performance of parametric quantum circuits, particularly in terms of power handling and bandwidth, which are crucial for the readout of qubits in quantum computers.”