Robots could one day crawl across the moon. These undergrads are laying the groundwork
Peer-Reviewed Publication
Updates every hour. Last Updated: 8-Jul-2025 03:10 ET (8-Jul-2025 07:10 GMT/UTC)
Hadrons are bound by quarks and gluons through the strong interaction. Their properties at low energies are non-perturbative, especially because of the phenomenon of quark confinement. According to quark model, hadrons consist of two or three quarks, called mesons and baryons, respectively. Exotic hadrons, like those formed by four, five or more quarks are allowed by Quantum Chromodynamics, QCD. Since 2003, many exotic mesons have been observed, as the X(3872), Tcc(3875) and so on. Regarding exotic baryons, the \Lambda(1405), discovered in the late 1950s in bubble chamber experiments, has been one of the most controversial states. This is because this resonance has unusual properties as its two-pole structure, which makes it an ideal exotic baryon candidate. To gain insights on the properties of the Lambda(1405), researchers extracted the quark mass dependence of this state from a recent LatticeQCD simulation, or QCD in the discretized space-time, and confirm its two-pole structure.
An unexpectedly strong solar storm rocked our planet on April 23, 2023, sparking auroras as far south as southern Texas in the U.S. and taking the world by surprise.
Two days earlier, the Sun blasted a coronal mass ejection (CME) — a cloud of energetic particles, magnetic fields, and solar material — toward Earth. But the CME wasn’t especially fast or massive, suggesting the storm would be minor. But it became severe.
Using NASA heliophysics missions, new studies of this storm and others are helping scientists learn why some CMEs have more intense effects — and better predict the impacts of future solar eruptions on our lives.
Moving mesh adaptation provides optimal resource allocation to computational fluid dynamics for the capture of different key physical features, i.e., high-resolution flow field solutions on low-resolution meshes. Although many moving mesh methods are available, they require artificial experience as well as computation of a posteriori information about the flow field, which poses a significant challenge for practical applications. Para2Mesh uses a double-diffusion framework to accomplish accurate flow field reconstruction through iterative denoising to provide flow field features as supervised information for fast and reliable mesh movement, thus enabling adaptive mesh prediction from design parameters.