HQNET: Harnessing Quantum Noise for Effective Training of Quantum Neural Networks in NISQ Era ...
arXiv, 2024
report
Zugriff:
This paper delves into the intricate dynamics of quantum noise and its influence on the onset and mitigation of barren plateaus (BPs) - a phenomenon that critically impedes the scalability of QNNs. We find that BPs appear earlier in noisy quantum environments compared to ideal, noise-free conditions.However, strategic selection of qubit measurement observables can effectively tackle this issue. To this end, we examine a variety of observables, such as PauliZ,PauliX, PauliY, and a specially designed arbitrary Hermitian observable, tailored to the requirements of the cost function and the desired outputs of quantum circuits. Our analysis encompasses both global and local cost function definitions, with the former involving measurements across all qubits and the latter focusing on single-qubit measurements within the QNN framework. Our findings indicate that in a global cost function scenario, PauliX and PauliY observables lead to flatter optimization landscapes, signaling BPs with increasing qubits, especially ...
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HQNET: Harnessing Quantum Noise for Effective Training of Quantum Neural Networks in NISQ Era ...
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Autor/in / Beteiligte Person: | Kashif, Muhammad ; Shafique, Muhammad |
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Veröffentlichung: | arXiv, 2024 |
Medientyp: | report |
DOI: | 10.48550/arxiv.2402.08475 |
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