Classiq Technologies has announced a major milestone in financial quantum computing, achieving up to 95% quantum circuit compression in Monte Carlo simulation algorithms for credit portfolio risk management. The project was conducted in partnership with Sumitomo Corporation and Mizuho–DL Financial Technology, aiming to assess the feasibility of quantum algorithms in real-world financial applications, particularly in simulating large-scale probabilistic models used for Value at Risk (VaR) calculations.
Monte Carlo methods are widely used in finance for tasks such as derivative pricing and asset risk assessment but are computationally intensive due to the large number of random scenarios required. Mizuho–DL FT introduced a new approach using pseudo-random number generation to reduce the number of required qubits. However, this introduces deeper circuits that may impact fault tolerance. Classiq’s quantum circuit design platform, using its Qmod high-level quantum language, was employed to generate and compress circuits for both traditional and pseudo-random quantum Monte Carlo simulations.
The study demonstrated that both circuit types could be compressed by up to 95% in depth while maintaining computational accuracy and without significantly increasing qubit count. This reduction in depth has a direct impact on lowering noise susceptibility and hardware resource consumption—two of the key bottlenecks in near-term quantum computing. The results support the potential for quantum-accelerated risk analytics in finance, particularly for large-scale simulations where classical methods struggle.
This achievement highlights the value of automated quantum circuit optimization for enabling early practical use cases of quantum algorithms. Classiq’s technology, which abstracts quantum circuit design into high-level, hardware-agnostic code, continues to push the boundaries of algorithm implementation in real-world domains such as finance, while supporting integration with cloud and HPC backends.
For more information, refer to the announcement here.
March 25, 2025
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