Squeezed Light: Key to Photonic Quantum Computing

NTT Research in Japan is at the forefront of developing a groundbreaking photonic quantum computer that promises to revolutionize the world of computing. The Coherent Ising Machine (CIM) being pioneered by NTT Research represents a fusion of classical and quantum computing principles, leveraging photonic circuits to achieve unprecedented speed and energy efficiency.

The CIM operates on a unique premise, utilizing a network of optical parametric oscillators (OPOs) that are meticulously programmed to tackle problems mapped to an Ising model. This model serves as a mathematical representation of magnetic systems, comprising spins or angular momentums of fundamental particles engaged in competitive interactions.

While traditional quantum computing approaches rely on gate-based systems, the CIM distinguishes itself by harnessing physics-based processing. By capitalizing on natural global coherence instead of entangled qubits, the CIM necessitates cutting-edge optical technologies such as Thin-Film Lithium Niobate (TFLN) devices manufactured at the nanometer scale.

An OPO, akin to a laser, serves as a coherent light source within the CIM, enabled by parametric amplification in an optical resonator. Through the Ising model, optimization challenges are mapped to OPOs, enabling the identification of the lowest-energy spin configuration that leads to a viable solution. This optimization process is steered by the nonlinearity of OPOs and the optical coupling between them.

The CIM's operational sequence commences with a mixed state encompassing all desired states. By initiating in a vacuum state with OPOs below threshold, the CIM gradually elevates the pump power until the OPOs surpass the threshold, culminating in the identification of a local minimum and the generation of a solution. Notably, the CIM's optical nature renders it impervious to thermal noise, ensuring robust performance.

Quantum gated computing, while effective, encounters scalability challenges when juxtaposed with the CIM. The necessity of maintaining superconducting hardware at extremely low temperatures for reliable qubit operation poses significant hurdles. In contrast, the CIM's utilization of optics and lasers endows it with a substantial bandwidth advantage over classical computing, facilitating expedited communications and computations while minimizing energy consumption.

Quantum gate computing, particularly with error correction, holds the promise of exponential acceleration in solving specific problems compared to classical computers. However, practical instances where quantum computers significantly outpace conventional systems remain limited. Quantum annealing and the CIM, both leveraging qubits in superpositions, adopt distinct methodologies to encode optimization functions.

Quantum annealing, while effective in theory, often necessitates impractically long anneal times for numerous problems. Digital annealers, a form of classical computing, excel in solving combinatorial optimization challenges swiftly but are constrained by digital hardware limitations. The CIM's potential extends to applications in artificial intelligence, with ongoing research exploring its integration into machine learning frameworks.

Despite the promising prospects of the CIM, several challenges persist, including the need to enhance squeezed light levels and adapt CIM hardware for diverse spin connectivities. Researchers are exploring solutions such as integrating field programmable gate arrays (FPGAs) to enhance parallelism and flexibility. Forecasts suggest a commercially available CIM could materialize by the early 2030s, resembling NTT's LASOLV computing machine, which currently operates under the auspices of NTT Computer and Data Science Laboratories.

For more information, visit www.ntt-research.com