Predicting the behavior of many interacting quantum particles is a complicated process but is key to harness quantum computing for real-world applications. Researchers have developed a method for ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

Strongly interacting systems play an important role in quantum physics and quantum chemistry. Stochastic methods such as Monte Carlo simulations are a proven method for investigating such systems.

Right now, quantum computers are small and error-prone compared to where they’ll likely be in a few years. Even within those limitations, however, there have been regular claims that the hardware can ...

As quantum computing develops, scientists are working to identify tasks for which quantum computers have a clear advantage over classical computers. So far, researchers have only pinpointed a handful ...

Quantum computers promise to revolutionize our ability to solve problems thanks to their unique properties. However, a team of researchers has just discovered a computable task that appears impossible ...

The original version of this story appeared in Quanta Magazine. For computer scientists, solving problems is a bit like mountaineering. First they must choose a problem to solve—akin to identifying a ...

It remains an open question when a commercial quantum computer will emerge that can outperform classical (non-quantum) machines in speed and energy efficiency while solving real-world combinatorial ...

Magnetic materials are used to make MRI machines, hard drives, wireless chargers, and phone speakers. It takes a lot of expensive research and development to create new materials. “And there’s no ...

From subatomic particles to complex molecules, quantum systems hold the key to understanding how the universe works. But there's a catch: when you try to model these systems, that complexity quickly ...