arXiv:2607. 05814v1 Announce Type: cross Abstract: Real-time decoding is a major bottleneck in scaling quantum error correction (QEC) from noisy intermediate-scale quantum (NISQ) devices to fault-tolerant quantum computing.
By Sumit Chongder
arXiv:2607. 01329v1 Announce Type: cross Abstract: The geometric and topological structure of quantum cost landscapes (QCLs) governs the optimization and thus the predictive power of variational quantum algorithms (VQAs).
By Felix J. Beckmann, Jo\~ao F. Bravo
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: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.
By Brian Coyle, Snehal Raj, Virag Umathe, El Amine Cherrat, Elham Kashefi
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
arXiv:2510. 03389v2 Announce Type: replace-cross Abstract: Current quantum computers require algorithms that use limited resources economically.
By Jonas J\"ager, Philipp Els\"asser, Elham Torabian