Efficient quantum process tomography for enabling scalable optical quantum computing

by Riko Seibo
Tokyo, Japan (SPX) Nov 24, 2025

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.

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."

Research Report:Completely characterizing multimode second-order nonlinear optical quantum processes