Practical quantum computing is one step closer.
Researchers have introduced a new algorithm called Arbitrary Environment Automatic Compaction (ACE) designed to study the interaction of qubits with their surrounding environment and the accompanying quantum state changes. By simplifying quantum mechanics calculations, this algorithm, based on Feynman’s interpretation of quantum mechanics, offers a new avenue for understanding and exploiting quantum systems. Potential applications include advances in quantum telephony and computing, enabling more accurate predictions of quantum coherence and entanglement.
While traditional computers use bits represented by 0s and 1s to transmit information, quantum computers use quantum bits (qubits) instead. Like bits, qubits have two main states or values, 0 and 1. However, unlike bits, qubits can exist in both states simultaneously.
This may seem like a puzzling paradox, but it can be explained with a simple analogy to coins. A classical bit can be represented as a coin with the heads or tails (1 or 0) facing up. A qubit, on the other hand, can be thought of as a spinning coin that also has heads and tails, but the heads or tails are decided only when the rotation stops, i.e. when it loses its original state.
Acting as a quantum measurement analogy, when a spinning coin stops, one of the two states of a qubit is selected.in quantum computing, the different qubits must be linked together. For example, state 0 (1) of one qubit must be uniquely correlated with state 0 (1) of another qubit. When the quantum states of two or more bodies are correlated, it is called quantum entanglement.
Quantum Entanglement Challenge
A major difficulty in quantum computing is that qubits are surrounded by environments and interact with them. This interaction degrades the quantum entanglement of the qubits, which can lead to them becoming unentangled with each other.
A two-coin analogy helps to understand this concept. If two identical coins were spun at the same time, waited a short time, and then stopped, they could both have the same face, either heads or tails. This synchronicity between spinning coins can be compared to quantum entanglement. However, if the coin continues to spin for a longer period of time, it will eventually lose synchrony and the same side (heads or tails) will no longer be facing up.
Loss of synchrony occurs mainly because the spinning coin gradually loses energy due to friction with the table. Also, each coin loses energy in its own way. In the quantum world, friction, i.e. loss of energy due to interactions with the environment, ultimately leads to quantum decoherence, i.e. loss of synchrony between qubits. The result is qubit dephasing, in which the phase of the quantum state (represented by the angle of rotation of the coin) changes randomly over time, resulting in the loss of quantum information and making quantum computing impossible.
Quantum coherence and dynamics
A key challenge facing many researchers today is maintaining long-term quantum coherence. This can be achieved by accurately describing the evolution of quantum states over time, also known as quantum mechanics.
Scientists at the MIEM HSE Center for Quantum Metamaterials, in collaboration with colleagues in Germany and the UK, have developed an automatic compaction of arbitrary environments ( proposed an algorithm called ACE). Quantum state over time.
Insight into quantum mechanics
“The near-infinite number of vibrational modes or degrees of freedom in the environment makes the computation of quantum mechanics especially difficult. It involves calculating the dynamics, in which case it is impossible to calculate directly because computers cannot handle it.
But not all changes in the environment are of equal importance. Changes occurring at a sufficient distance from our quantum system cannot significantly affect its dynamics. A split into ‘relevant’ and ‘irrelevant’ environmental degrees of freedom underlies our method,” said Alexei, co-author of the paper and director of the MIEM HSE Center for Quantum Metamaterials. Vagoff said.
Feynman’s Interpretation and the ACE Algorithm
According to an interpretation of quantum mechanics proposed by the famous American physicist Richard Feynman, calculating the quantum state of a system involves calculating the sum of all possible ways that state can be achieved. . This interpretation assumes that quantum particles (systems) can move in all directions: forwards and backwards, to the right or left, and even back in time. To calculate the final state of a particle, we need to sum the quantum probabilities of all such orbitals.
“The problem is that there are too many possible trajectories for even a single particle, let alone the entire environment. In our method, the evolution of a qubit and its environment is captured by a tensor, a matrix or numerical table that describes the state of the entire system at various points in time. We select only the parts of the tensor that are relevant to the dynamics of ,” explains Alexei Vagov.
Conclusion: Implications of the ACE Algorithm
The researchers emphasize that any environment’s automatic compression algorithms are publicly available and implemented as computer code. According to the authors, this opens up entirely new possibilities for accurately computing the dynamics of multiple quantum systems. In particular, this method makes it possible to estimate the time until entanglement. photon Whether a pair of quantum phone lines can unwind, how far a quantum particle can “teleport”, and how long it takes a quantum computer’s qubits to lose coherence.
References: “Simulation of Open Quantum Systems with Automatic Compression of Arbitrary Environments” by Moritz Cygorek, Michael Cosacchi, Alexei Vagov, Vollrath Martin Axt, Brendon W. Lovett, Jonathan Keeling and Erik M. Gauger, 24 March 2022, Available here. natural physics.
DOI: 10.1038/s41567-022-01544-9