A new artificial intelligence framework dramatically reduces the computational cost of modeling the epoch of reionization, opening the door to more efficient exploration of cosmological parameters.
New research reveals how graph theory can quantify the fundamental limitations of simultaneous quantum measurement.
New research reveals how quantum phase transitions can dramatically alter energy storage in quantum batteries, potentially unlocking faster charging and greater capacity.
Researchers have developed a novel architecture to bolster the safety of large AI models that process both text and images, protecting against harmful inputs and malicious manipulation.
New research reveals a wider applicability of existing quantum security theorems, streamlining the process of verifying cryptographic systems.
A new hybrid algorithm combines the power of quantum and classical computing to efficiently identify molecular resonances, a crucial step in understanding chemical behavior.
Researchers have unveiled ‘Cyclone,’ a novel hardware-software design for trapped-ion quantum computers that dramatically accelerates quantum error correction and improves memory fidelity.
Researchers are leveraging the power of graph neural networks to dramatically improve the performance and reliability of quantum key distribution systems.
Researchers propose a new e-voting system designed to withstand future quantum computing threats and enhance election integrity through biometric authentication and immutable blockchain records.
Researchers have developed a method to significantly reduce errors caused by ion loss in long-chain trapped ion quantum computers, paving the way for more scalable quantum systems.