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NEWS
WiMi Develops Quantum Error Mitigation Technology Based on Machine Learning
Monday, 23rd December at 9:00 am
BEIJING, Dec. 23, 2024 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced the development of an innovative solution: Machine Learning-based Quantum Error Suppression Technology (MLQES). This technology not only breaks through the error bottleneck in quantum computing but also demonstrates the potential to enhance the accuracy of quantum circuits through classical control and hybrid computing methods, without requiring additional quantum resources.
The computational potential of quantum computers stems from the unique properties of their qubits: through superposition, a quantum computer with a system of n qubits can provide a computational space of 2^n. This gives it a significant advantage in solving large-scale problems, particularly in fields such as factorization, molecular simulation, and artificial intelligence.
However, current quantum devices are still at the noisy intermediate-scale quantum (NISQ) stage, and the noise, thermodynamic disturbances, and other external environmental interferences during quantum circuit operations often lead to errors in qubits. Compared to errors in classical computing, quantum computing errors are more complex and harder to correct, with the risk of errors propagating throughout the quantum circuit. Therefore, effectively reducing these quantum computing errors is crucial for advancing quantum computing technology.
Monday, 23rd December at 9:00 am
BEIJING, Dec. 23, 2024 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced the development of an innovative solution: Machine Learning-based Quantum Error Suppression Technology (MLQES). This technology not only breaks through the error bottleneck in quantum computing but also demonstrates the potential to enhance the accuracy of quantum circuits through classical control and hybrid computing methods, without requiring additional quantum resources.
The computational potential of quantum computers stems from the unique properties of their qubits: through superposition, a quantum computer with a system of n qubits can provide a computational space of 2^n. This gives it a significant advantage in solving large-scale problems, particularly in fields such as factorization, molecular simulation, and artificial intelligence.
However, current quantum devices are still at the noisy intermediate-scale quantum (NISQ) stage, and the noise, thermodynamic disturbances, and other external environmental interferences during quantum circuit operations often lead to errors in qubits. Compared to errors in classical computing, quantum computing errors are more complex and harder to correct, with the risk of errors propagating throughout the quantum circuit. Therefore, effectively reducing these quantum computing errors is crucial for advancing quantum computing technology.
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