Simulating reality: Less memory required on quantum computer than on classical computer, study shows
Researchers have discovered that complex systems can be less complex than originally thought if they allow quantum physics to help: quantum models of complex systems are simpler and predict their behaviour more efficiently than classical models.
A good measure of the complexity of a particular system or process is how predictable it is. For example, the outcome of a fair coin toss is inherently unpredictable and any resources (beyond a random guess) spent on predicting it would be wasted. Therefore, the complexity of such a process is zero.
Other systems are quite different, for example neural spike sequences (which indicate how sensory and other information is represented in the brain) or protein conformational dynamics (how proteins — the molecules that facilitate biological functions — undergo structural rearrangement). These systems have memory and are predictable to some extent; they are more complex than a coin toss.
The operation of such complex systems in many organisms is based on a simulation of reality. This simulation allows the organism to predict and thus react to the environment around it. However, if quantum dynamics can be exploited to make identical predictions with less memory, then such systems need not be as complex as originally thought.
Dr Wiesner added: “On a more fundamental level, we found that the efficiency of prediction still does not reach the lower bound given by the principles of thermodynamics — there is room for improvement. This might hint at a source of temporal asymmetry within the framework of quantum mechanics; that it is fundamentally impossible to simulate certain observable statistics reversibly and hence with perfect efficiency.”