arXiv Machine Learning

Lie Group Diffusion Models for Hardware-Aware Quantum Circuit Synthesis

arXiv:2606. 29636v1 Announce Type: cross Abstract: An important task in quantum computing is unitary circuit synthesis compatible with physical hardware constraints.

arXiv Machine Learning
Jun 11

Family-Aware Residual Architecture for Predicting Quantum Circuit Simulation Performance

arXiv:2606. 11620v1 Announce Type: cross Abstract: Approximate tensor-network simulators enable classical simulation of quantum circuits beyond the reach of exact methods, but selecting optimal approximation parameters -- such as bond dimension thresholds -- remains a costly trial-and-error process.

By Honjar Xing, Yehong Jiang, Xianbang Wang, Zehua Wang, Zhicheng Jiang
arXiv Machine Learning
Jul 24

Neural Guided Sampling for Quantum Circuit Optimization

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.

By Bodo Rosenhahn, Tobias J. Osborne, Christoph Hirche
arXiv Machine Learning
6d ago

Generative Learning for Quantum Measurement Design

arXiv:2608. 11396v1 Announce Type: cross Abstract: Extracting quantum information from a quantum state is a fundamental task of quantum computation, often requiring the estimation of many non-commuting observables under a finite measurement budget.

By Jun Dai, Olivier Nahman-L\'{e}vesque, Guillaume Rabusseau, Hong-Ye Hu, Cunlu Zhou