Mapping Quantum States with Neural Geometries

A new machine learning approach leverages the inherent geometry of quantum states to improve the efficiency and interpretability of quantum state tomography.

A new machine learning approach leverages the inherent geometry of quantum states to improve the efficiency and interpretability of quantum state tomography.

A new distributed system, Lotus, tackles performance limitations in disaggregated memory architectures by radically rethinking how transactions and locking are handled.

Researchers have developed a robust algorithm for reliable data transmission in challenging underwater environments using light, even with faint signals and imprecise timing.

New research reveals that even minor data corruption can severely compromise the performance of promising state-space model architectures like Mamba.

Researchers have developed an automated method to create stronger safeguards against malicious prompts that can hijack large language models.

A new analysis shows that a surprisingly straightforward approach to identifying bug-inducing code changes can match-and even outperform-complex, spectrum-based techniques.
A new study determines the absolute minimum key size needed to guarantee secure aggregation of data across a network, even with malicious collaborators and varying privacy demands.

Researchers have achieved unprecedented control over the coherence of photons emitted from a quantum dot cascade, paving the way for advanced quantum light sources.
Researchers have developed a new quantum algorithm that efficiently constructs antisymmetric wavefunctions, paving the way for more realistic simulations of complex nuclear processes.
New research clarifies the conditions for creating effective locally testable codes with small alphabets, opening doors to more robust data transmission.