News at work

In particle accelerators, the greater a beam’s intensity, the more opportunities there are to study particle interactions. One way to increase the intensity is to merge two beams with a technique called slip-stacking. However, when combining them, the beams’ interaction may cause instability. A Fermilab scientist has created a successful model of the fraught dynamics of two particle beams in close contact, leading to smoother sailing in this area of particle acceleration.

The MINOS+ collaboration at Fermilab collected data with a medium-energy neutrino beam from September 2013 to June 2016. The collaboration has exploited the data to set more stringent boundaries on the possibility of sterile neutrinos mixing with muon neutrinos.

The MINERvA neutrino experiment has a new crime scene investigation technique, one that takes a hard look at the traces that particles leave before fleeing the scene. Researchers used a new technique in a recent MINERvA neutrino investigation. And the new insights they gained on the workings of nuclear effects can help other neutrino experiments.

Scientists on the ArgoNeuT experiment have developed a method that enables them to better distinguish the tracks that particles leave behind in liquid argon, as well as a way to better differentiate between signals and background. And thanks to the software’s great performance, ArgoNeuT will aid larger neutrino experiments in their quest to understand the nature of the subtle neutrino.

For the first time, scientists have demonstrated that low-energy neutrinos can be thoroughly identified with a liquid-argon particle detector. The results, obtained with the ArgoNeuT experiment, are promising for experiments that use liquid argon to catch neutrinos, including the upcoming Deep Underground Neutrino Experiment.

Researchers demonstrate the cryogen-free operation of a superconducting radio-frequency cavity that might ease barriers to its use in societal applications.

One of the most interesting scientific topics at IOTA will be studies of beams made of a single electron.

An SRF team at Fermilab has demonstrated record performance from an accelerating cavity using a technique that could lead to significant cost savings for future accelerators.

Recently, the MicroBooNE experiment published a paper describing how they used convolutional neural networks — a particular type of deep neural network — to sort individual pixels coming from images made by a particular type of detector.

CMS observes Higgs boson decays into bottom quarks, furthering our knowledge of how the particles that make up matter behave.