Researchers use symmetry to decode quantum noise behavior in next-gen processors

Researchers at Johns Hopkins Applied Physics Laboratory (APL) and Johns Hopkins University have made a significant advance in characterizing quantum noise, a major obstacle to reliable quantum computing. Quantum processors are highly sensitive to disturbances such as temperature shifts, vibrations, electrical fluctuations, and atomic-scale effects, which disrupt fragile quantum states and complicate computations. Existing noise models are often too simplistic, failing to capture noise that spreads across both time and space within processors, thereby hindering the development of fault-tolerant quantum error-correcting codes. To address this, the researchers employed symmetry—a mathematical property that simplifies complex structures—to better understand noise behavior. Using a technique called root space decomposition, they structured the quantum system into discrete states arranged like rungs on a ladder. By observing how noise causes transitions between these states, they can classify disturbances and apply targeted mitigation strategies. This novel framework offers a more precise characterization of noise, which is expected to enhance both hardware design and algorithm development for quantum computing. The study, published in