Reverse the cause and the effect is not a problem for quantum computers [Report] – Brinkwire



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Look at a movie in reverse and you may be confused, but not a quantum computer. This is the conclusion of researcher Mile Gu at the Center for Quantum Technologies (CQT) at the National University of Singapore and at the Nanyang Technological University and its collaborators.

In a research published July 18 in Physical Review X the international team shows that a quantum computer is less slavery of the time arrow than a conventional computer . In some cases, it's as if the quantum computer did not need to distinguish between cause and effect

The new work is inspired by an influential discovery made almost 10 years ago by complexity scientists James Crutchfield and John Mahoney at the University of California, Davis. They showed that many statistical data sequences have an integrated time arrow. An observer who sees the data played from start to finish, like the images of a movie, can model the sequel using only a small amount of memory about what happened before. An observer who tries to model the system in reverse has a much more difficult task, potentially requiring to follow orders of magnitude more information.

This discovery is known as causal asymmetry. This sounds intuitive – after all, modeling a system when time is running backwards is like trying to infer a cause of an effect. We are used to finding this more difficult than predicting an effect of a cause. In everyday life, it is easier to understand what will happen next if you know what just happened and what happened before.

However, researchers are still intrigued by time-related asymmetries. This is because the basic laws of physics are ambivalent as to whether time is moving forward or backward. "When does physics impose no direction in time, where does the causal asymmetry – the memory overhead necessary to reverse the cause and effect?" Request Gu.

Early studies of causal asymmetry used classical physics models to generate predictions. Crutchfield and Mahoney teamed up with Gu and collaborators Jayne Thompson, Andrew Garner and Vlatko Vedral at CQT to see if quantum mechanics is changing the situation.

They found that this was the case. Models that use quantum physics, prove the team, can fully mitigate memory overhead. A quantum model forced to emulate the process in inverse time will always surpass a classical model that emulates the process in real time.

The work has profound implications. "The most exciting thing for us is the possible connection with the arrow of time," says Thompson, the first author on the job. "If causal asymmetry is only found in classical models, it suggests that our perception of the cause and effect, and therefore of time, may emerge from a classical explanation of events in a fundamentally quantum world. "

wants to understand how this relates to other ideas of time. "Every community has its own arrow and everyone wants to explain where it comes from," says Vedral. Crutchfield and Mahoney have called causal asymmetry an example of a "barbed arrow" of time.

The most iconic is the thermodynamic arrow. This comes from the idea that disorder, or entropy, will always increase – a little here and there, in whatever happens, until the universe ends up as a big mess hot. Although the causal asymmetry is not the same as the thermodynamic deflection, they could be interrelated. Classic models that follow more information also generate more mess. "This suggests that causal asymmetry may have an entropic consequence," says Thompson.

The results may also be of practical value. Eliminate conventional overhead to reverse the cause and the effect could help quantum simulation. "Like a film that plays backwards, sometimes we may need to make sense of things that are presented in an inherently difficult order to model in. In such cases, quantum methods might prove to be wrong. much more efficient than their conventional counterparts, "explains Gu.

More information:
Jayne Thompson et al, Causal Asymmetry in a Quantum World, Physical Review X (2018). DOI: 10.1103 / PhysRevX.8.031013

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