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.
Traditional quantum error correction methods typically require
additional qubits to store redundant information or use complex
quantum error-correcting codes to fix errors. However, these
methods not only consume significant quantum resources but also
impose higher demands on the physical implementation of current
NISQ devices. Against this backdrop, WiMi's MLQES
(Machine-Learning-Based Quantum Error Suppression) technology
offers a new direction—by relying solely on the combination of
classical computers and quantum devices, it can effectively reduce
quantum errors without the need for additional quantum
resources.
The core idea of WiMi's Machine Learning-Based Quantum Error
Suppression Technology (MLQES) is to predict potential errors in
quantum circuits using machine learning models and dynamically
adjust the circuit structure to minimize the impact of errors on
the final computational results.
In MLQES, the quantum circuit is first analyzed using a
supervised learning model. This supervised learning model is
trained on a large dataset of historical quantum circuits and error
distributions, enabling it to accurately predict common errors in
different quantum circuits. When a new quantum circuit is input,
MLQES can predict in real-time the potential error magnitude
associated with various operations in the circuit, such as quantum
gates, entanglement between qubits, and so on.
Once the machine learning model predicts that the error value in
a quantum circuit exceeds a predetermined threshold, WiMi's MLQES
system triggers a circuit segmentation mechanism. This is one of
the innovations of MLQES: to prevent the entire circuit from
running under high-error conditions, MLQES can use an
error-affected fragmentation strategy to split a large quantum
circuit into two or more smaller sub-circuits. This segmentation
strategy ensures that within each sub-circuit, errors are
controlled within an acceptable range. MLQES employs an iterative
segmentation process until the error prediction for each
sub-circuit is below the set threshold.
The segmented sub-circuits can operate independently on the
quantum device. Since the sub-circuits are smaller in scale, the
entanglement and interaction between qubits become easier to
control, thus reducing noise interference in quantum operations.
Once each sub-circuit completes its execution, its output is sent
to a classical computer for further processing.
On the classical computer, MLQES uses a classical reconstruction
algorithm to combine the results from multiple sub-circuits into
the output of the complete quantum circuit. This reconstruction
process does not rely on additional quantum operations but
leverages the powerful processing capabilities of classical
computing to compensate for the limitations of quantum
computation.
MLQES not only addresses the quantum error problem but also
provides a scalable computational framework for the future of
quantum computing. This technology combines the strengths of
quantum computers and classical computers, using the powerful
processing capabilities of classical computing to control the
execution of quantum circuits. This fusion of classical and quantum
computing opens up possibilities for further applications of future
NISQ devices, especially in scenarios where the number of qubits is
limited but high-precision computation is required. MLQES reduces
the reliance on quantum error-correcting codes and redundant qubits
in quantum computing while significantly enhancing the overall
efficiency of quantum computation.
The launch of WiMi's (NASDAQ: WIMI) MLQES technology marks an
important step forward in quantum computing. At a stage when NISQ
devices are still not fully matured, the ability to effectively
reduce quantum computation errors means that more practical
application scenarios can gradually be realized. Whether in quantum
chemistry, optimization problems, or cryptography, error reduction
will greatly enhance the feasibility and efficiency of quantum
computing.
Compared to existing quantum error correction methods, the
greatest advantage of MLQES is that it does not require additional
qubit resources. For current quantum devices, qubit resources are
highly limited, and maintaining these resources comes at a
significant cost. MLQES simplifies the complex quantum error
correction problem into a scalable classical-quantum hybrid
computation problem, relying solely on classical computing
control.
MLQES is designed for the current noisy intermediate-scale
quantum (NISQ) devices. On these devices, quantum error correction
becomes more challenging due to the operational noise of qubits and
their limitations. MLQES is capable of adapting to these
constraints, providing an easily implementable quantum error
suppression solution.
Quantum computing is expected to bring about significant
transformations in fields such as finance, materials science, and
artificial intelligence. Through the MLQES technology, WiMi offers
a more efficient and reliable quantum computing solution for these
industries, helping businesses and research institutions to apply
quantum computing to real-world production and research faster and
earlier.
As an important milestone in the development of quantum
computing technology, WiMi's Machine Learning-Based Quantum Error
Suppression Technology (MLQES) not only demonstrates the innovative
potential of combining quantum and classical computing but also
lays a solid foundation for more complex quantum computing
applications in the future. Amid the intensifying global
competition in quantum computing, the launch of MLQES will
undoubtedly accelerate the popularization and application of
quantum computing technology.
About WiMi Hologram Cloud
WiMi Hologram Cloud, Inc. (NASDAQ:WiMi) is a holographic cloud
comprehensive technical solution provider that focuses on
professional areas including holographic AR automotive HUD
software, 3D holographic pulse LiDAR, head-mounted light field
holographic equipment, holographic semiconductor, holographic cloud
software, holographic car navigation and others. Its services and
holographic AR technologies include holographic AR automotive
application, 3D holographic pulse LiDAR technology, holographic
vision semiconductor technology, holographic software development,
holographic AR advertising technology, holographic AR entertainment
technology, holographic ARSDK payment, interactive holographic
communication and other holographic AR technologies.
Safe Harbor Statements
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forward-looking statements can be identified by terminology such as
"will," "expects," "anticipates," "future," "intends," "plans,"
"believes," "estimates," and similar statements. Statements that
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other things, the business outlook and quotations from management
in this press release and the Company's strategic and operational
plans contain forward−looking statements. The Company may also make
written or oral forward−looking statements in its periodic reports
to the US Securities and Exchange Commission ("SEC") on Forms 20−F
and 6−K, in its annual report to shareholders, in press releases,
and other written materials, and in oral statements made by its
officers, directors or employees to third parties. Forward-looking
statements involve inherent risks and uncertainties. Several
factors could cause actual results to differ materially from those
contained in any forward−looking statement, including but not
limited to the following: the Company's goals and strategies; the
Company's future business development, financial condition, and
results of operations; the expected growth of the AR holographic
industry; and the Company's expectations regarding demand for and
market acceptance of its products and services.
Further information regarding these and other risks is included
in the Company's annual report on Form 20-F and the current report
on Form 6-K and other documents filed with the SEC. All information
provided in this press release is as of the date of this press
release. The Company does not undertake any obligation to update
any forward-looking statement except as required under applicable
laws.
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SOURCE WiMi Hologram Cloud Inc.
