Material-Driven Optimization of Transmon Qubits for Scalable and Efficient Quantum Architectures

Abstract

One of the most crucial steps in creating practical quantum computers is designing scalable and efficient superconducting qubits. Coherence times, connections between individual qubits, and reduction of environmental noise are critical factors in the success of these qubits. Because they can be lithographically fabricated and are less sensitive to charge noise, superconducting qubits, especially those based on the Transmon architecture, have emerged as top contenders for scalable platforms. In this work, we use a combination of design iteration, material analysis, and simulation to tackle the superconducting qubit optimization challenge. We created transmon-based layouts for 4 qubits and 8 qubits using Qiskit Metal and conducted an individual analysis for each qubit. We investigated anharmonicity and extracted eigenfrequencies, computing participation ratios across several design passes, and identifying the top five energy eigenstates using Ansys HFSS. We then created a 2D cross section of a single qubit design in COMSOL Multiphysics to evaluate how different materials affect performance. This enables us to assign various superconducting materials and substrates and investigate their effects on energy loss and electromagnetic properties. Qubit coherence and overall device quality are significantly influenced by the materials chosen. This integrated framework of material based simulation and circuit design offers a workable way to create reliable superconducting qubit systems and supports continued attempts to create scalable, fault-tolerant quantum computing.