A quantum computer has been used to simulate a holographic wormhole for the first time. In this case, the word "holographic" indicates a way to simplify physics problems involving both quantum mechanics and gravity, not a literal hologram, so simulations like this could help us understand how to combine those two concepts into a theory of quantum gravity – perhaps the toughest and most important problem in physics right now. Both quantum mechanics, which governs the very small, and general relativity, which describes gravity and the very large, are extraordinarily successful in their respective realms, but these two fundamental theories do not fit together. This incompatibility is particularly apparent in areas where both theories should apply, such as in and around black holes. These areas are extraordinarily complicated, and that is where holography comes in.

By employing quantum-compatible machine learning techniques, they developed a method of extracting a rare Higgs boson signal from copious noise data. Higgs is the particle that was predicted to imbue elementary particles with mass and was discovered at the Large Hadron Collider in 2012. The new quantum machine learning method is found to perform well even with small datasets, unlike the standard counterparts. Despite the central role of physics in quantum computing, until now, no problem of interest for physics researchers has been resolved by quantum computing techniques. In this new work, the researchers successfully extracted meaningful information about Higgs particles by programming a quantum annealer--a type of quantum computer capable of only running optimization tasks--to sort through particle-measurement data littered with errors.

Workers insert a new CMS Beam Pipe during maintenance on the Large Hadron Collider. Everything about the Large Hadron Collider (LHC), the particle accelerator most famous for the Nobel Prize-winning discovery of the elusive Higgs boson, is massive--from its sheer size to the grandeur of its ambition to unlock some of the most fundamental secrets of the universe. At 27 kilometers (17 miles) in circumference, the accelerator is easily the largest machine in the world. This size enables the LHC, housed deep beneath the ground at CERN (the European Organization for Nuclear Research) near Geneva, to accelerate protons to speeds infinitesimally close to the speed of light, thus creating proton-on-proton collisions powerful enough to recreate miniature Big Bangs. The data about the output of these collisions, which is processed and analyzed by a worldwide network of computing centers and thousands of scientists, is measured in petabytes: for example, one of the LHC's main pixel detectors, the ultra-durable high-precision cameras that capture information about these collisions, records an astounding 40 million pictures per second--far too much to store in its entirety.