Photo credit: phys.org
Innovative Technique Reveals Insights into Quantum Systems
Understanding the intricacies of quantum systems can resemble deciphering a complex machine without access to its components. This is a significant challenge for scientists, primarily because traditional investigative methods demand substantial resources, limiting their feasibility for extensive applications.
A team from UC San Diego, in partnership with IBM Quantum, Harvard, and UC Berkeley, has introduced a groundbreaking technique known as “robust shallow shadows.” This method enables researchers to efficiently and accurately derive critical information from quantum systems, even amidst real-world noise and imperfections. The findings of this study are detailed in the journal Nature Communications.
Visualize capturing shadows of an object from different viewpoints; these shadows can then be utilized to reconstruct the original object. Utilizing advanced algorithms, the researchers enhance sample efficiency while employing noise-reduction techniques to create clearer, more intricate “shadows” that are instrumental in characterizing quantum states.
“Our methodology improves measurement techniques, significantly enhancing the reliability and accessibility of quantum computing,” stated Associate Professor of Physics Yi-Zhuang You, the paper’s corresponding author.
The technique’s effectiveness has been experimentally validated on a superconducting quantum processor, demonstrating that it surpasses conventional single-qubit measurement methods in accurately predicting various quantum state properties, including fidelity and entanglement entropy, even in the presence of noise.
More information: Hong-Ye Hu et al, Demonstration of robust and efficient quantum property learning with shallow shadows, Nature Communications (2025). DOI: 10.1038/s41467-025-57349-w
Citation: Utilizing ‘shallow shadows’ to unveil quantum properties (2025, April 28) retrieved 28 April 2025 from https://phys.org/news/2025-04-shallow-shadows-uncover-quantum-properties.html
This content is for informational purposes only and should not be reproduced without permission.
Source
phys.org