These simulations give the researchers the tools to build two types of code for interpreting the LHC data. Reconstruction code uses energy information from the detector and tripped sensors to track the behavior of specific particles. In effect, it plays a game of 3D connect-the-dots—with as many as 5,000 points to consider—and divines the LHC events and the particles they produced. Analysis code, meanwhile, sifts through these recreations, mining for particular events like the Higgs boson's photon decay.

"Reconstruction code gives us the properties of the event," says Bunn. "Analysis code lets us figure out the physics to determine the parameters of the events and see if those parameters match our hypotheses."

As researchers finetune these codes for the various events of interest, members of the NSF-funded GriPhyN collaboration—with an overarching goal of building petabyte-scale computing

environments for diverse data-intensive projects—are meeting other LHC data management and analysis challenges.The Globally Interconnected Object Database project, for example, is addressing data storage and access problems like authentification and job handling. And a common data analysis toolkit and a common reconstruction code are being encapsulated in Java for use through Web browsers.

Once the LHC is up and running, more than a thousand scientists are expected to take part in one way or another. It's a big, diverse team working on a big, diverse project—a team that may capture the fascinating magic that Einstein sparred with for years.