To appreciate what B mesons are, and what is the magic of their behaviour, which is the topic of this article, I need to give you a three-paragraph introduction below.

At the smallest distance scales, matter is made of quarks and leptons, which we consider as point-like objects endowed with different properties and interactions. Most of the matter around us is in fact made up of three-quark systems: protons and neutrons, organized in tightly packed nuclei kept together by the strong force; with electrons (which are the lightest charged leptons) orbiting around them thanks to the electromagnetic force attracting them to the protons. 

Physicists from the CMS experiment at CERN's Large Hadron Collider have used the total data sample of 13 TeV proton-proton collisions collected in the past few years to search for resonant decays of heavy hadrons into pairs of J/Psi mesons, and they found three of them. 
One of the three new resonances is likely to be the same as a particle already identified for the first time by the competitor LHCb experiment, while the other two are new finds. LHCb is also a LHC detector, but it is one optimized for heavy hadron spectroscopy; while CMS is a "general purpose" detector built with the primary goal of finding the Higgs boson (a 2012 success) and searching for new phenomena at the highest-energy frontier. 

Yes, I know - I have touched on this topic already a couple of times in this blog, so you have the right to be bored and surf away. I am bound to talk about this now and then anyway, though, because this is the focus of my research these days. 
Recently I was in the Elba island (a wonderful place) for a conference on advanced detectors for fundamental physics, and I presented a poster there on the topic of artificial-intelligence-assistend design of instruments for fundamental physics. Below is the poster (I hope it's readable in this compressed version - if you really want a better pic just ask).

Neural networks are everywhere today. They are used to drive vehicles, classify images, translate texts, determine your shopping preferences, or finding your quickest route to the supermarket. Their power at making sense of small or large datasets alike is enabling great progress in a number of areas of human knowledge, too. Yet there is nothing magical about them, and in fact what makes them powerful is something that has been around for century: differential calculus.

When I explain to the public (in this blog, or at public conferences or schools) how the Large Hadron Collider operates, I have to gloss over a lot of detail that is unnecessary to grasp the important concepts, which enable other discussions on interesting subnuclear physics. This is good practice, and it also saves me from having to study details I have forgotten along the way - they say that what you are left with when you forget everything is culture, and I tend to agree. I have a good culture in particle physics and that's all I need to do some science popularization ;-)