In the Zuchongzhi 2.0 quantum processor, five random quantum circuits were generated, each with a different Schrödinger-Feynman algorithm complexity.

Quantum computers have the potential to speed up computation, help design new medicines, break codes, and discover exotic new materials—but that's only when they are truly functional.

As quantum computing technology continues to advance, MicroAlgo's multi-simulator collaborative subgraph isomorphism algorithm is expected to play a key role in more application areas.

Why repetition codes matter The focus on repetition codes isn't arbitrary. While other quantum error-correcting codes, like surface codes, have only achieved small distances and relatively high ...

Willow, Google's quantum chip, recently solved a benchmark task called random circuit sampling in five minutes; it would have taken up to 10 quadrillion years for a conventional supercomputer to ...

A “useless” algorithm that serves as a benchmark for demonstrating the power of quantum computers over ordinary devices could potentially be repurposed as a way to keep data secure from ...

MicroAlgo integrates LSQb algorithm with quantum encryption for enhanced secure data transmission and information hiding systems. Quiver AI Summary MicroAlgo Inc. announced the integration of its ...