MicroCloud Hologram Develops Approximate Quantum Multiplier for NISQ Devices
MicroCloud Hologram Inc. has developed a new approximate quantum multiplier technology designed for NISQ environments. The technology reduces circuit depth and T-gate count, enhancing performance on current quantum computers.
SHENZHEN, China, July 9, 2026 – MicroCloud Hologram Inc. (NASDAQ: HOLO) announced on Tuesday the development of a practical approximate quantum multiplier technology specifically engineered for NISQ (Noisy Intermediate-Scale Quantum) environments.
The company states that this new technology significantly improves quantum circuit depth and reduces the need for costly T-gates, offering a more balanced approach to the efficiency and precision of current noisy quantum devices.
Quantum addition and multiplication have presented key bottlenecks in quantum computation. Traditional quantum multipliers typically require deep and complex circuits that are susceptible to noise. MicroCloud Hologram's solution utilizes approximate computing, intentionally controlling error margins. This allows for a constant-depth (O(1)) circuit structure where the impact of errors remains within acceptable levels, verified through probabilistic analysis.
The new technology features four distinct approximate adder circuits, providing users with flexibility to choose between precision and resource utilization based on specific application needs. Building upon this modular unit, an approximate quantum multiplier has also been constructed, substantially reducing both circuit depth and the T-gate count compared to existing schemes.
The company conducted tests using simulation environments and actual quantum hardware. Results indicated that while the approximate multiplier exhibits minor deviations in precision, the overall error distribution is controllable. The reduced circuit depth and T-gate count also improved the fidelity of the final results in noisy NISQ environments, suggesting that approximation may enhance computational quality under certain conditions.
This technology holds potential for applications in machine learning and optimization problems, and it is compatible with existing quantum platforms. MicroCloud Hologram views this as a significant development trend in the design of quantum algorithms.