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Quantum Computing Error Mitigation

250715 Department of Computer Science & Engineering Quantum Error Detection and Mitigation Quantum computing has the potential to significantly improve computational tasks. Unfortunately, errors due to outside interactions cause the data to be noisy. Our group is focusing on finding a way to decrease these errors by reverting the data back to what it was before the noise. To simulate realistic errors, we used a bosonic bath model on the surface code. We use both Convolutional Neural Networks (CNNs) for preprocessing and feature extraction, and Graph Neural Networks (GNNs) for predicting and correcting errors in the surface codes. By training and evaluating the CNNs and the GNNs, we can increase performance in quantum computing. These changes will allow for major developments in the field and will be a significant contribution to making an accurate quantum structure. RESEARCHERS: Arhaan Reddy, The Quarry Lane School '28; Satvik Dronavalli, Independence High School '26; Vihaan Krishnakumar, Archbishop Mitty High School '26 ADVISOR: McMahan Lab, Quantum Computing & Computer Science KEYWORDS: Quantum Computing