Jacob Lance Budd
Electrical engineering
Hometown: Mesa, Arizona, United States
Graduation date: Spring 2025
FURI | Spring 2025
Protecting Quantum States in Quantum Computing from Noise Through Optimized Dynamical Decoupling
Preserving the coherence of a quantum state is vital to the performance of quantum computing. Unwanted interactions with the environment cause the quantum state to decohere and render quantum computing challenging if not impossible. Several methods of quantum control have been developed to counteract the negative effects of noise, such as quantum error correcting codes and Dynamical Decoupling (DD). The objective of this research is to optimize dynamical decoupling sequences using classical optimization routines, referred to as learning dynamical decoupling (LDD), to address challenges associated with noise in quantum computing. By tuning the rotational gates of a DD sequence using a classical optimization routine, an optimized gate set can be found for eliminating any arbitrary noise. A DD sequence is chosen with consideration of the noise of the system, which is often non trivial, and the native gate set. LDD, by taking advantage of classical optimization, finds the ideal gate set to eliminate any arbitrary noise.
Mentor: Christian Arenz
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