WiMi Develops Binary String Polynomial Encoding for Quantum Random Access Memory (QRAM)

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BEIJING, Jan. 16, 2025 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced the development of a binary string polynomial encoding for Quantum Random Access Memory (QRAM). Random Access Memory (RAM) is a crucial component in classical computing, enabling computers to quickly and randomly access stored data. In the context of quantum computing, QRAM is a type of memory that allows quantum computers to efficiently and parallelly access stored data without disrupting quantum states. QRAM is not only a core architecture for quantum data storage, but also a fundamental component for many quantum algorithms, such as the Grover search algorithm and Shor's algorithm.

However, the process of quantum data access is far more complex than in classical computing. The nature of quantum states requires that data access preserves the superposition of the states while avoiding the introduction of measurement interference. As a result, designing an efficient QRAM architecture is highly challenging. Most existing QRAM designs are very costly in terms of computational resources (such as qubits, T gates, depth, etc.), making it difficult to implement large-scale applications on practical quantum computers.

WiMi has designed an entirely new QRAM architecture by introducing binary string polynomial encoding. In this design, Clifford+T circuits are utilized, and by optimizing the use of T gates, the efficiency of quantum circuits is significantly improved. Compared to the state-of-the-art QRAM bucket brigade architecture, this design has made significant breakthroughs in multiple key metrics.

T-depth is one of the key metrics of quantum computing performance. The smaller the depth, the shorter the time required for the computational process, which in turn helps improve the overall efficiency of quantum algorithms. In this new QRAM design, we have achieved an exponential improvement in T-depth through polynomial encoding of binary strings. Specifically, in previous state-of-the-art bucket brigade QRAM architectures, the T-depth typically grows linearly with the number of memory locations, whereas WiMi has reduced the T-depth exponentially through polynomial encoding.

T-count is also a crucial optimization goal. T gates are expensive operations in quantum computing; their implementation not only consumes time but also depletes significant resources, especially in fault-tolerant quantum computing. To keep the T-count low, WiMi has adopted an innovative gate circuit optimization strategy in its design, ensuring that the T-count does not significantly increase while reducing the T-depth. Compared to previous state-of-the-art designs, this architecture maintains an asymptotically similar T-count. This means that, while the computational depth has been significantly reduced, the number of T gates required by the circuit has not increased drastically, ensuring efficient resource utilization.