The GRIDCafe team at CERN. To handle the mountains of data at the Large Hadron Collider, CERN built the world's largest grid computing resource. However, it needs further help in simulating potential random events and is relying on virtualized machines running on private computers to get it done.

The computing needs of the LHC, especially when it comes to comparing various theories with experimental results, are enormous. Basically, the physicists' appetite for computing power expands to fill all available resources, because there are always more theories to test than there are computers to test them with.

Access to volunteer resources is seen by CERN as an opportunity to expand computing capacity. Anyone with Internet connectivity and a computer can participate by helping run more simulation of particle physics. These simulations, which are submitted to a central database from the user’s home computers, will provide scientists with theoretical references for measurements obtained at accelerators like the Large Hadron Collider (LHC).

Prior to the completion of the LHC, a massive grid project was completed that would give more scientists the opportunity to participate in computer-aided research and would give CERN the ability to handle the mountains of data that the world’s biggest accelerator is capable of generating.

However, this grid’s core function of managing mountains of data doesn’t leave enough room left over for extensive testing and simulation work.

LHC@home, known to CERN as Test4Theory@Home, is a project designed to help CERN with these simulation needs, and is organized by the Citizen Cyberscience Centre, which is a partnership between CERN, UNITAR, and the University of Geneva. Its goal is to promote volunteer-based science.

Those who want to volunteer will download an x86 Sun Microsystems virtualization software package called VirtualBox, which runs the Monte Carlo simulations on home computers. An open-source distributed computing platform called Boinc to manages the Test4Theory tasks. Boinc is also used in distributed computing projects like searches for extraterrestrial intelligence or protein folding.

According to project organizers, this is the first distributed computing project to make use of virtualized computers on volunteers’ machines.

How Test4Theory@Home works

Solving multi-particle dynamics in relativistic quantum field theory is (almost) as hard as constructing the accelerators and experiments that perform the collisions in the real world. Doing a small part of such a calculation can be the topic of an entire PhD thesis for a gifted student, and doing a full calculation usually entails a multi-year effort by a collaboration of many theoretical high energy physicists working together.

Sophisticated calculations typically also require enormous computing resources. For instance, to probe anywhere near a reasonable number of the infinitely many quantum histories that can contribute to every single "event".

Most often, therefore, observed discrepancies point us—not to a breakdown of the theory itself—but to a problem with our ability to model all aspects of it with the extremely high accuracy achievable by the intense beams and sensitive detectors that are used to do the real-world measurements to which the calculations are compared.

It is therefore crucial to be able to distinguish between the breakdown of a model of a physical theory, and the breakdown of the theory behind it. We are looking for three possible sources of discrepancy:

  1. Tuning: A discrepancy is found, but the same model can still be made to describe all the available data by a readjustment of its parameters. Thus, while no new phenomenon has been uncovered, the model has been better constrained, and the improved constraints will factor into future tests of the same model.
  2. Modeling: A discrepancy is found that no parameter set of the model is able to describe. A phenomenon not included in the model has been (re)discovered. A careful analysis of the approximations used in the model must then be brought to bear to determine whether the model could be improved by including previously ignored parts of the same underlying theory, or ...
  3. Eureka!: A discrepancy is found which fundamentally contradicts the underlying theory. In this case, a truly new phenomenon of nature has been discovered, whose origin must then be puzzled out by further tests and theorizing.