Science

Researchers have developed an agentic framework that significantly improves the accuracy and cost-effectiveness of identifying vulnerabilities in Ethereum smart contracts.

A novel security framework leverages the unique characteristics of physically unclonable functions to authenticate sensor data and protect critical infrastructure from faults and malicious intrusion.

A new approach to encoding quantum information using squeezed light and rotation diversity promises more robust and efficient wireless transmission.

Researchers are exploring how quantum graph neural networks can enhance message passing and scalability in next-generation wireless systems.

Researchers are developing methods to identify and prioritize smart contract audits by analyzing patterns of code obfuscation that drift across different blockchain ecosystems.

Researchers have refined the Gilbert-Varshamov bound, yielding tighter limits on the performance of both classical and quantum error-correcting codes.

Researchers are exploring the mathematical structure of braid groups to build a key exchange protocol that resists attacks from both classical and quantum computers.

New research demonstrates fundamental limitations in achieving simulation-based security for quantum functional encryption, extending known impossibilities to the quantum realm.

A novel two-component model, leveraging modified DGLAP evolution and unintegrated PDFs, provides a compelling description of particle production in high-energy proton-proton collisions.

A new framework translates questions about the maximum size of combinatorial structures into optimization problems, offering a powerful approach to extremal combinatorics.