Detecting the Global Memory Effect of Multiqubit Systems Under Repeated Use of a Noisy Channel.

What is it about?

The unavoidable interaction between quantum systems and their environment creates a noisy channel that induces decoherence, leading to the loss of the system’s quantum properties. These interactions can be either memoryless, known as the Markovian regime, or associated with inherent memory, known as the non-Markovian regime. When there is a connection between repeated uses of a noisy channel, it is called a correlated noisy channel, and it exhibits memory. Therefore, in a correlated noisy channel, the global memory effect refers to both the intrinsic memory of the noise and the memory arising from correlations between channel uses. In this work, we use the Hilbert–Schmidt speed (HSS) as a reliable figure of merit to detect global memory effects in multiqubit correlated noisy channels for both dissipative and non-dissipative cases. We also investigate how the correlations between repeated uses of a noisy channel influence the non-Markovian memory effects in multiqubit systems within noisy environments, using the Hilbert–Schmidt speed.

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Photo by aj_aaaab on Unsplash

Photo by aj_aaaab on Unsplash

Why is it important?

Understanding and managing noisy channels with memory is essential for developing scalable and stable quantum technologies. We show that the Hilbert–Schmidt speed (HSS) is a robust and effective method for distinguishing between different types of dissipative and non-dissipative correlated noisy channels. Additionally, HSS not only effectively detects and quantifies global memory effects but also reveals that these effects become weaker as the number of qubits—each independently interacting with a correlated noisy channel—increases. Larger systems experience stronger decoherence, which hides signs of non-Markovian behavior, such as the flow of information back from the environment to the system. Our study helps researchers better understand how to make quantum systems more stable and resilient in noisy environments; using HSS serves as a proven approach to support the development of more robust quantum computers and networks.

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