Quantum Learning’s Noise Barrier

New research clarifies the limits of near-term quantum computers for machine learning tasks and highlights the crucial role of error correction.

New research clarifies the limits of near-term quantum computers for machine learning tasks and highlights the crucial role of error correction.

This review examines the potential of combining classical and quantum communication channels to build more efficient and secure Space-Air-Ground Integrated Networks.

A new analysis leverages the geometry of the torus to map out the performance limits of a leading quantum error correction code.

Researchers have identified a fundamental limit of 0.873 for approximating solutions to the Edge Partitioning Problem, suggesting that significant algorithmic advancements are required to achieve better results.

A new analysis exposes potential vulnerabilities in SecureDNA, a biosecurity platform used to vet DNA orders, and outlines improvements based on rigorous formal methods.

Researchers have successfully demonstrated a satellite-based quantum random number generator, paving the way for truly secure communication in orbit and beyond.

New research reveals significant vulnerabilities in paper-based Physically Unclonable Functions (PUFs) used for authentication, despite their promise as a cost-effective defense against counterfeiting.

New research rigorously tests the performance of quantum random number generators on the IQM Spark 5 quantum processing unit, offering insights into optimal circuit designs.
A new analysis reveals widespread flaws in how the security of large language models is tested, undermining confidence in current safety evaluations.

Researchers have developed a simplified device-independent quantum secret sharing protocol leveraging a multi-party pseudo-telepathy game to enhance secure communication.