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Efficient Quantum Process Tomography for Enabling Scalable Optical Quantum Computing <(From Left) Ph.D candidate Geunhee Gwak, Professor Young-Sik Ra, Dr. Chan Roh, Ph.D candidate Young-Do Yoon from KAIST, (Top Left) Professor M.S Kim from Imperial College London> Optical quantum computers are gaining attention as a next-generation computing technology with high speed and scalability. However, accurately characterizing complex optical processes, where multiple optical modes interact to generate quantum entanglement, has been considered an extremely challenging task. KAIST research team has overcome this limitation, developing a highly efficient technique that enables complete characterization of complex multimode quantum operations in experiment. This technology, which can analyze large-scale operations with less data, represents an important step toward scalable quantum computing and quantum communication technologies. KAIST announced on November 17th that a research team led by Professor Young-Sik Ra from the Department of Physics has developed a Multimode Quantum Process Tomography technique capable of efficiently identifying the characteristics of second-order nonlinear optical quantum processes that are essential for optical quantum computing. Efficient 'CT Scan' Technology for Quantum Computers 'Tomography' is a technique, similar to a medical CT scan, that reconstructs an invisible internal structure from diverse measurements. Similarly, quantum computing requires a method that reconstructs the internal workings of quantum operations using various measurement data. To outperform conventional computers, a quantum computer must be capable of manipulating a large number of quantum units (qubits or qumodes) at the same time. However, as the number of qubits or quantum optical modes (qumodes) increases, the resources required for tomography grows exponentially, making existing technologies unable to analyze systems with even five or more optical modes. With the newly developed technique, the research team is now able to clearly determine what actually happens inside an optical quantum computer, as if taking a CT scan. Introducing a New Mathematical Framework Based on Amplification and Noise Matrices Inside a quantum computer, multiple optical modes interact in a highly complex and entangled way. The research team has introduced a new mathematical framework that precisely describes multimode second-order nonlinear optical quantum processes. This method analyzes how input states change under a given operation using two key components: the 'Amplification matrix,' which describes how the mean fields of light are transformed, and the 'Noise matrix,' which captures the noise or loss introduced through environmental interactions. Together, these components create a 'quantum state map' that enables accurate and simultaneous observation of both the ideal quantum evolution of light (unitary changes) and the unavoidable noise (non-unitary changes) present in real devices. This leads to a much more realistic characterization of how an optical quantum computer actually operates. Reducing the Required Measurement Data and Expanding Analysis to 16 Modes To determine how a quantum operation works, the research team input several types of quantum states and observed how the outputs changed. They then applied a statistical method known as Maximum Likelihood Estimation to reconstruct the internal operation that most accurately explains the collected data while satisfying the necessary physical conditions. Using this approach, the research team dramatically reduced the amount of measurement data required. Whereas existing methods quickly become impractical—requiring enormous datasets even for systems with slightly more than a few modes and typically limiting analysis to about five modes—the new technique overcomes this bottleneck. The team successfully performed the world’s first experimental characterization of a large-scale optical quantum operation involving 16 modes, an unprecedented milestone in the field. <Figure1.Experimental scheme. (Left) Various coherent states are used as input probes to determine the amplification matrix. (Right) A vacuum input state is used to additionally determine the noise matrix.> <Figure2.Characterization results. (a) 16-mode second-order nonlinear optical quantum process. (b) Cluster state generation. (c) Mode-dependent loss with nonlinear interaction. (d) Quantum noise channel. Left and right columns show the amplification and noise matrices, respectively> Professor Young-Sik Ra stated, "This research significantly increases the efficiency of Quantum Process Tomography, a foundational technology essential for quantum computing. The acquired technology will greatly contribute to enhancing the scalability and reliability of various quantum technologies, including quantum computing, quantum communication, and quantum sensing." The study, in which Geunhee Gwak (Integrated M.S, Ph.D. Candidate, Department of Physics) participated as the first author, and Dr. Chan Roh (Postdoctoral Researcher), Young-Do Yoon (Integrated M.S./Ph.D. Candidate), and Professor Myungshik Kim (Imperial College London) participated as co-authors, was formally published online in the prominent international academic journal 'Nature Photonics' on November 11, 2025. ※ Article Title: Completely characterizing multimode second-order nonlinear optical quantum processes, DOI:10.1038/s41566-025-01787-x This research was supported by the National Research Foundation of Korea (Quantum Computing Technology Development Project, Mid-career Researcher Support Project, Quantum Simulator Development for Material Innovation Project, Quantum Technology R&D Flagship Project, Basic Research Lab Support Project), the Institute of Information & Communications Technology Planning & Evaluation (Core Source Technology for Quantum Internet Project, University ICT Research Center Support Project), and the US Air Force Research Laboratory.
2025.11.18 View 4206