arXiv:2608. 05686v1 Announce Type: cross Abstract: Quantum error correction protects logical information only when every physical operation remains below the fault-tolerance threshold, a condition that must be maintained continuously rather than only at the initial calibration.
By Weiyuan Gong, Hong-Ye Hu
The paper introduces QEMScore, a metric that compares learned quantum error mitigators to capacity‑matched controls that do not use measurement data. Using simulated circuits with exact ideal answers, the study finds that many mitigators gain little from measurement inputs, with a plain polynomial model often outperforming them. On real hardware data, however, measurement inputs can provide predictive benefits, highlighting that performance depends on representation and protocol specifics.
By Yue Zhao, Huayue Gu, Yushun Dong, Xiyang Hu
arXiv:2607. 03193v1 Announce Type: cross Abstract: Calibrating a superconducting transmon chip is a sequential decision problem under noise, drift, and a finite budget: an expert must choose experiments, read ambiguous plots, judge fit quality, and revise stale beliefs as the chip drifts.
By Animesh Tripathy, Aswanth Krishnan
The paper investigates how approximate numerical solvers used in recursive state estimation can be repaired using bounded corrections, characterizing when such corrections meet local admissibility tolerances and how they influence finite‑horizon covariance. It derives error identities that separate solve error from gain drift, revealing quartic and sixth‑order contributions to the covariance response. The framework is applied to a power‑grid tolerance study, showing that learned corrections reduce the required conjugate‑gradient iterations, and it demonstrates a unified interface for classical, quantum, and hybrid solvers.
By Yanjun Ji, Dennis Willsch, Orkun \c{S}ensebat, Priyanka Arkalgud Ganeshamurthy, Zhi Pei, M. Sahnawaz Alam, Ivelina Stoyanova, Frank K. Wilhelm, Bo Zhao, Chao Wang, Kristel Michielsen
arXiv:2606. 19356v1 Announce Type: cross Abstract: When multi-agent LLM systems produce bad answers, not all failures are equal: some answers are grounded in the right material but incomplete, while others are simply ungrounded and should be stopped.
By Anantha Sharma
arXiv:2607. 28422v1 Announce Type: new Abstract: Fault-tolerant quantum computing (FTQC) relies on quantum error correction to suppress physical errors and preserve logical information at scale.
By Ran Miao, Rui Luo, Xiaohan Shan, Xiaoming Sun