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Jiale Lu

Publications and source records attributed to Jiale Lu.

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The Omitted Noise Contribution of Surface Normal Variation: Farassat's Formulation 1A revisited

Farassat's Formulations 1 and 1A have been extensively employed for propeller noise prediction. However, in the derivation of Formulation 1A from Formulation 1, the contribution associated with the temporal variation of the direction of the unsteady force is omitted, appearing mathematically as the temporal derivative of the local surface normal vector. Through rigorous mathematical derivation, this study demonstrates that the omitted term constitutes an indispensable component of the acoustic source representation. Accordingly, a Modified Formulation 1A is proposed by explicitly retaining the normal vector temporal derivative term in the time-domain formulation. Far-field acoustic predictions for propellers are performed to evaluate the proposed formulation, and the results confirm both its theoretical consistency and predictive capability.

physics.flu-dyn

MindSpore Quantum: A User-Friendly, High-Performance, and AI-Compatible Quantum Computing Framework

We introduce MindSpore Quantum, a pioneering hybrid quantum-classical framework with a primary focus on the design and implementation of noisy intermediate-scale quantum (NISQ) algorithms. Leveraging the robust support of MindSpore, an advanced open-source deep learning training/inference framework, MindSpore Quantum exhibits exceptional efficiency in the design and training of variational quantum algorithms on both CPU and GPU platforms, delivering remarkable performance. Furthermore, this framework places a strong emphasis on enhancing the operational efficiency of quantum algorithms when executed on real quantum hardware. This encompasses the development of algorithms for quantum circuit compilation and qubit mapping, crucial components for achieving optimal performance on quantum processors. In addition to the core framework, we introduce QuPack, a meticulously crafted quantum computing acceleration engine. QuPack significantly accelerates the simulation speed of MindSpore Quantum, particularly in variational quantum eigensolver (VQE), quantum approximate optimization algorithm (QAOA), and tensor network simulations, providing astonishing speed. This combination of cutting-edge technologies empowers researchers and practitioners to explore the frontiers of quantum computing with unprecedented efficiency and performance.

quant-ph