Graph Structures and Eigenvalue Extremes

New research explores the interplay between graph architecture and spectral properties, pinpointing graphs that maximize and minimize key connectivity measures.

New research explores the interplay between graph architecture and spectral properties, pinpointing graphs that maximize and minimize key connectivity measures.

Researchers have developed a method for monitoring neon film growth in real-time, paving the way for more reliable electron-on-neon qubits.

A new software package is poised to transform our understanding of active galactic nuclei by efficiently modeling their ever-changing brightness across multiple wavelengths.

New research introduces a comprehensive benchmark for evaluating how effectively AI agents can learn from ongoing experience and refine their own memories.

A new deterministic approach leverages the mathematical properties of prime numbers to create robust and efficient vector representations for complex datasets.

A new hybrid approach combines high-accuracy and reduced-order models to dramatically accelerate complex simulations without sacrificing precision.

Researchers have developed a novel method to encourage clearer, more independent factors in learned representations, improving performance under complex, nonlinear conditions.
New research demonstrates how the quantum link between emitted X-rays and photoelectrons varies depending on the atom’s inner-shell excitation, opening doors to more precise X-ray spectroscopy.
New observations with the upgraded HERA radio telescope are beginning to constrain the earliest moments of cosmic structure formation.

New research reveals how periodically driven spin systems transition from order to thermalization depending on the strength of interactions between particles.