As the Internet of Things expands and relies increasingly on 5G, traditional security models are proving inadequate, necessitating a shift towards more intelligent, distributed approaches.
A new analysis reveals that applying the principles of quantum game theory can unlock cooperative solutions in the classic ‘centipede game,’ challenging traditional predictions of self-interest.
A new error mitigation technique boosts the performance of complex quantum algorithms on near-term hardware.
Researchers have developed a novel deep learning framework to dramatically compress holographic data without sacrificing reconstruction quality.
A new proof demonstrates the security of a practical quantum key distribution system using a simplified, passive measurement approach.
A new framework demonstrates how complex behavior in symmetric quantum circuits can emerge from the principles of holographic duality, shedding light on emergent phases and transitions.
![The system explores model architectures for quantum machine learning, contrasting a purely quantum approach with hybrid methods-one utilizing a classical multilayer perceptron on $Q(x)$ and another employing a residual hybrid that bypasses measurement bottlenecks with a $[x∥Q(x)]$ structure.](https://arxiv.org/html/2511.20922v1/x1.png)
Researchers are tackling limitations in quantum machine learning with a novel architecture that bypasses the traditional measurement stage, enhancing both accuracy and data privacy.
Researchers are leveraging the power of field-programmable gate arrays to achieve real-time decoding of quantum low-density parity-check codes, a critical step towards fault-tolerant quantum computing.
Researchers have developed a comprehensive system for translating quantum algorithms into physical circuits suitable for near-term, error-correcting quantum computers.
Researchers have demonstrated a practical, stable implementation of Twin-Field Quantum Key Distribution using a novel Sagnac interferometer design.