Researchers have presented an automated protocol-design method in a study published in the Intelligent Computing journal.
(A–C) Classical simulation costs, with the corresponding Schrödinger-Feynman algorithm costs shown in the legend. (D) The optimal random quantum circuit is designed by the proposed method for Google’s latest quantum computational advantage experiment. Image Credit: He-Liang Huang et al.
This method may enable the computational capacity of quantum devices to be accessed sooner than previously thought.
Quantum computational advantage is a crucial milestone in the development of quantum technologies. It shows that quantum computers can execute some jobs better than traditional supercomputers. Specifically crafted protocols are necessary to attain the benefits of quantum computing.
For instance, recent experiments have shown encouraging results with random circuit sampling. When attempting to use random circuit sampling, it is essential to remember that proper design of a random quantum circuit's structure is necessary to widen the gap between quantum computing and classical simulation.
Researchers He-Liang Huang, Youwei Zhao, and Chu Guo created an automated protocol-design method to solve the problem of identifying the best random quantum circuit in quantum computing advantage studies.
Two-qubit gate designs are employed in the quantum processor architecture used in random circuit sampling research. By modifying the states of the two qubits, the 2-qubit gate creates an interaction between them that enables the creation of a quantum circuit and the realization of quantum computing.
To effectively utilize the enhanced computational efficiency of quantum computing, optimizing the cost of classical simulation is imperative. However, finding the best random quantum circuit architecture to optimize the classical simulation cost is not simple.
It is necessary to exhaust all potential patterns to find the best random quantum circuit. Then, each pattern's classical simulation cost must be estimated and the highest-cost pattern must be chosen. Although the choice of algorithm significantly impacts the cost of classical simulation, the existing traditional algorithm is limited by its excessively long estimating time.
The authors' innovative approach makes use of the Schrödinger-Feynman algorithm. This approach splits the system into two subsystems, and state vectors represent each subsystem's quantum state.
The amount of entanglement created between the two subsystems determines the algorithm's cost. This approach makes complexity evaluation significantly faster, and its benefits become more noticeable as the size of the random quantum circuit rises.
Compared to alternative algorithms, the authors' experimental work demonstrated the efficacy of the random quantum circuit produced by the suggested technique. Five randomly generated quantum circuits with varying Schrödinger-Feynman algorithm complexity were produced in the Zuchongzhi 2.0 quantum processor. According to experimental findings, circuits with greater complexity also cost more.
The competition between classical and quantum computing is anticipated to end within ten years. With this innovative method, the computational capability of quantum computing is maximized without adding new demands to the quantum hardware.
Furthermore, the quicker rise of quantum entanglement might be the primary explanation for this novel method's ability to produce random quantum circuits with greater conventional simulation costs. In the future, knowing the physics behind this occurrence could aid researchers in looking into practical applications using quantum advantage experiments.
Journal Reference:
Huang, H, L., et al. (2024) How to Design a Classically Difficult Random Quantum Circuit for Quantum Computational Advantage Experiments. Intelligent Computing. doi.org/10.34133/icomputing.0079
Source: https://spj.science.org/journal/icomputing