arXiv Machine Learning By Bodo Rosenhahn, Tobias J. Osborne, Christoph Hirche

Neural Guided Sampling for Quantum Circuit Optimization

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arXiv:2510. 12430v2 Announce Type: replace-cross Abstract: Translating a general quantum circuit on a specific hardware topology with a reduced set of available gates, also known as transpilation, comes with a substantial increase in the length of the equivalent circuit.

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arXiv Machine Learning
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Zero-shot Quantum Neural Architecture Search

arXiv:2605. 27410v2 Announce Type: replace-cross Abstract: Variational Quantum Algorithms (VQAs) are a leading approach to exploiting near-term quantum hardware, leveraging parameterized quantum circuits and classical optimization to achieve advantage.

By Tung Dao, Son N. Tran, Huynh Thi Thanh Binh
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Adaptive directional gradients for parameterised quantum circuits

arXiv:2606. 09734v1 Announce Type: cross Abstract: Training parameterised quantum circuits (PQCs) on quantum hardware is bottlenecked by the measurement cost of gradient estimation, which under the parameter-shift rule scales linearly in the number of trainable parameters and dominates the total shot budget of training at scale.

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