A group of scientists has developed an algorithm and methodology to evaluate the performance of quantum computers and quantum systems based on the anti-butterfly effect. We know from science fiction that even small changes in the past can dramatically change the future (the infamous butterfly effect). Scientists have shown that a quantum system can be resistant to changes in the past.
“Time travel” in quantum systems may be purely conventional. We are talking about the work of systems with reversible time dynamics. In other words, the system can be rolled back to the “past” state by first bringing it to the “future” state, or vice versa. In classical mechanics, information (in all its diversity) is destroyed during these transitions. In quantum systems, it turns out, information can be stored with some minor changes. Simply put, by accidentally stomping on a butterfly in a clearing in the past, the main character will not return to a brand new, alien future. For quantum systems, almost nothing will change, no matter how many “butterflies” you’ve squashed in the past.
The new method was developed by Los Alamos National Laboratory scientists Bin Yang, Nikolai Sinitsyn and Joseph Harris. The method determines how much information is lost from the quantum system due to decoherence and how much is retained due to information mixing.
“Using a simple and robust protocol that we developed, we can determine how efficiently quantum computers can process information, and this also applies to information loss in other complex quantum systems,” said Bing Yang, a quantum theorist at Los Alamos. : National laboratory.
Reversible encoding or transformation of a digital stream to obtain the properties of a random sequence, which is needed, for example, in cryptography, is also used to model the quantum behavior of information. For example, entanglement is widely used to model the behavior of black holes, whose event horizon is assumed to return nothing but information, given their quantum basis.
Under normal conditions, degeneration occurs after some time. in fact, any noise in the environment destroys the quantum states of the qubits and information is lost. Scrambling allows you to stop these processes. Furthermore, the proposed algorithm provides a quantification of degeneracy and information relations, which allows for a very accurate assessment of the performance of a quantum system and, in fact, leads to a very, very accurate benchmark for evaluating quantum computers. and this is a tool to improve these platforms.
The Los Alamos team demonstrated the protocol using simulations on IBM’s cloud quantum computers. Before them, researchers could not definitively distinguish degeneration from confusion. Let’s just say that natural chaos and artificial chaos looked the same to scientists. The new algorithm fills this gap and paves the way for the future.
From a practical point of view, the system works as follows. A quantum system is created with some subsystem. The algorithm evolves the entire system over time, induces a “future” subsystem change, and then simultaneously evolves the system back. Future and present subsystem information can be accurately estimated, and data coverage shows how much information is preserved by entanglement and how much is lost due to divergence. The work was published in Physical Review Letters and is available by subscription only.