Synthesis of Long Scale Coherence Time Vacancy Defects in Silicon Carbide via Pulsed UV Laser and Photonic Curing for Industrial Scale Qubit Manufacturing

Qubits have unique capability to exhibit superposition and entanglement which makes them stand out to exist in multiples states simultaneously with ability to perform parallel computations. Serving as a fundamental building block of Quantum computers (QC) which leverages the superposition and entanglement of Qubits to perform quantum parallel operations at exponential speed. The applications of QC include cryptography, solving optimization problems, materials science, drug discovery and materials science. IBM Quantum System One is the first QC powered by 127-Qubits reported by RPI of Troy, NY. The unmatching wonders of Qubits comes with certain challenges to make and build QC such as their susceptibility to environmental noise and decohering, and difficulty in their fabrication and scalability. In this work we utilized pulsed UV laser and a broad spectrum (220-1500 nm) intense and short (0.03–100 ms) pulsed light (called photonic curing) to create and anneal the vacancy defects in silicon carbide (SiC) respectively. The study of vacancy formation will help to explore the mechanism of defect formation after laser irradiation as well as the mechanism of the subsequent photonic annealing of residual damage. The combination of these processes will give us an extensive combinatorial library of data to be used to train a deep learning neural network algorithm to predict the best possible Qubit defect architectures, processing conditions, and their expected performance. Excimer lasers like ArF (10 nsec, 193 nm) are efficient in creating color centers with 6.42 eV photons and can even etch SiC at a high enough laser fluence, < 2 J/cm². We propose to use an ArF excimer laser or a quintupled YAG (266 nm) and to optimize the conditions for different defect constructs and test their efficacy as defect-based Qubits.The as created defects will then be selectively annealed using photonic curing, which initiates rapid transformations, and reactions due to non-equilibrium processes. The acquired dataset will serve as the foundation for crafting a machine learning algorithm. This algorithm will be trained using innovative open-ended material selections to ensure statistically reliable predictions for future Qubit outcomes, with accuracy that can be empirically verified. Combination of Pulsed UV laser and photonic curing offers an instantaneous and roll-to-roll compatible approach for large-scale synthesis of Qubits.