Certifying Adversarial Robustness of Quantum Classifiers under Known-Readout Query Access
Framework certifies adversarial robustness of quantum classifiers using only measurement statistics and finite-shot outcomes, demonstrated on IBM Quantum hardware.
The paper introduces a measurement-only certification framework for adversarial robustness of quantum classifiers under known-readout query access, requiring no tomography, parameters, or gradients. It returns a lower bound ruling out untargeted errors within a radius and an attack-independent upper bound witnessing an adversarial state, both estimable with finite-sample guarantees. Evaluations show the lower bound tracks exact optima on tractable instances while the upper bound stays informative when standard attacks fail. The method was validated on IBM Quantum hardware using 40 executions of two 8-qubit quantum neural networks.
Cyber threats nudge Trump to sign executive order on foreign equipment in U.S. energy infrastructure
Trump signed an executive order declaring an emergency to bar foreign bulk-power equipment deemed a national security cyber risk.
The executive order, 'Declaring a National Energy Emergency to Secure the United States Bulk-Power System,' prohibits acquiring, importing, transferring, or installing foreign-produced bulk-power equipment and software deemed risky, citing fears of digital backdoors in Chinese-made grid gear. China supplies roughly 85% of solar supply chain capacity and is a major transformer manufacturer. The Energy Department has 120 days to develop implementing rules; the order revives a 2020 Trump-era measure the Biden administration had suspended after utilities found compliance difficult.