New evidence shows heat destroys quantum entanglement

But not all questions about quantum systems can be easily answered using quantum algorithms: some questions are equally easy with classical algorithms running on ordinary computers, while other questions are difficult with both classical and quantum algorithms.

To understand where quantum algorithms and the computers that can run them might excel, researchers often analyze mathematical models called spin systems, which capture the fundamental behavior of arrangements of interacting atoms. A question then arises: What happens if you leave a spin system at a particular temperature? The state that a spin system settles into is called thermal equilibrium, and it determines many of its other properties. So researchers have long been working on developing algorithms to find the equilibrium state.

Whether these algorithms truly benefit from their quantum nature depends on the temperature of the spin system in question. At very high temperatures, they can be easily handled by known classical algorithms. As the temperature decreases and quantum phenomena become stronger, the problems become harder. For some systems, even quantum computers will have difficulty solving them in a reasonable time. But all these details remain unclear.

“When do you go into a space where you need a quantum, and when do you go into a space where a quantum is not useful?” Yu-Win Tan“We don’t know that much yet,” says UC Berkeley researcher and one of the authors of the new study.

In February, Tan and Moitra, along with two other computer scientists at MIT, began thinking about the heat balance problem. Ainesh Bakshi Moitra’s graduate student Allen LiuIn 2023, they will all work together Breakthrough Quantum Algorithms They were working on a different task involving spin systems and wanted a new challenge.

“When we work together, things run smoothly,” Bakshi says. “It’s great.”

Before this 2023 breakthrough, the three MIT researchers had never worked on a quantum algorithm. Their backgrounds are in learning theory, a subfield of computer science that focuses on algorithms for statistical analysis. But like any ambitious startup, they saw their relative ignorance as an advantage — a way to look at problems with fresh eyes. “One of our strengths is that we don’t know much about quantum,” Moitra says. “The only quantum we know is the quantum that Eowyn taught us.”

The team decided to focus on relatively high temperatures. The researchers suspected that fast quantum algorithms existed, although no one could prove it. Soon, they found a way to apply old techniques from learning theory to the new, faster algorithms. But as they were writing their paper, another team Similar results: Proof Promising algorithms The ones developed the previous year would work well at higher temperatures. They were scooped up.

Sudden death revived

Tan and her collaborators were a little disappointed to come in second. Alvaro AlhambraAlhambra, a physicist at the Madrid Institute of Theoretical Physics and one of the authors of the rival paper, wanted to highlight the differences between the four researchers’ independent results. But when he looked over their draft proofs, he was surprised to see that at an intermediate stage they had proven something else: that in any spin system in thermal equilibrium, above a certain temperature, entanglement completely disappears. “I told them, ‘This is very, very important,'” Alhambra says.