QuantumEon

Method Protects Quantum Data from Decoherence and Leak

A team of researchers from Aalto University in Finland and IAS Tsinghua University in China has developed a method to predict the behavior of quantum systems connected to external environments. This is essential for safeguarding quantum data in quantum devices and for paving the way for practical applications of quantum technology. Typically, connecting a system such as a quantum computer to its environment leads to decoherence and information leakage, compromising the data within the system. However, the researchers have devised a technique that transforms this issue into a beneficial solution by combining techniques from quantum many-body physics and non-Hermitian quantum physics.

 

The team showed that connecting a quantum device to an external system can be a strength in the right circumstances, leading to robustly protected quantum excitations whose resilience stems from the fact that they are open to the environment. This approach potentially leads to disruptive new strategies for quantum technologies that harness external coupling to protect information from decoherence and leaks. This study establishes a new theoretical method to calculate the correlations between quantum particles when they are coupled to their environment and helps move quantum research from idealized conditions to real-world applications.

 

The breakthrough in protecting quantum data from decoherence and leaks positively impacts the practical applications of quantum technology. It enables the safeguarding of quantum data in quantum devices, making them more reliable and secure for use in real-world applications. This breakthrough also potentially leads to disruptive new strategies for quantum technologies that harness external coupling to protect information from decoherence and leaks, which could result in new and innovative quantum devices and systems.

 

Reference:

Chen, G., Song, F., & Lado, J. L. (2023). Topological Spin Excitations in Non-Hermitian Spin Chains with a Generalized Kernel Polynomial Algorithm. Physical Review Letters, 130(10), 100401. https://doi.org/10.1103/PhysRevLett.130.100401

 

Hamed Nazari

Hamed Nazari

Hamed is an innovative and results-driven Chief Scientist with expertise in Quantum Science, Engineering, and AI. He has worked for leading tech companies in Silicon Valley and served as an Adjunct Professor at UC Berkeley and UCLA.

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