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AMO Qubits: Scalable Decoding for Faster Quantum Computing

AMO Qubits Faster

Recent advances have made atomic, molecular, and optical (AMO) quantum computers possible. Despite its scalability and long coherence lengths (the time qubits can stay in their quantum state), syndrome extraction has always been slow, limiting AMO approaches. Syndrome extraction is a crucial measuring process in  quantum error correction that gives fault information without altering qubit quantum states. This slow technique hinders functional quantum computation with AMO qubits.

Riverlane experts and the University of Sheffield conducted the investigation to accelerate quantum error correction, particularly surface code decoding using AMO qubits. Surface codes are one of the best solutions to prevent quantum information mistakes. Decoding involves repairing errors without affecting quantum state.

Fast transversal logic, which speeds up quantum operations, disrupts structural properties that allow real-time decoding techniques like lattice surgery. Transversal logic may reduce syndrome extraction rounds, increasing the logical clock rate, or quantum computation speed. Its incompatibility with effective decoders was a problem.

The researchers created two novel windowed decoding methods to avoid this. These new protocols restore modularity and locality to overcome the decoding challenge. By restoring modularity and locality, decoding becomes easier.

In numerical simulations with the Stim quantum circuit simulator, performance improved significantly. Compared to lattice surgery, the revolutionary approaches accelerated transversal logic by an order of magnitude. This significant speedup increases computational cost slightly.

Additional simulations showed that “Ghost Decoding” worked. This approach suppressed errors exponentially as code distance, a measure of error correction code efficacy, increased. Importantly, the simulations showed that even at vast distances, “Ghost Decoding” did not require more decoding runs than the code distance, making it possible for general deployment.

The study also stressed the importance of properly adjusting parameters like decoding passes and “ghost singletons,” which are artificial mistake measures to improve accuracy. The quantum circuit structure determines the number of decoding passes, which increases as transversal CNOT gates approach closer. This flexibility is needed to support quantum algorithms and hardware limitations.

Our unique windowed decoding approaches overcome AMO qubits' slower syndrome extraction tempo, a major limitation. This work proves that large-scale algorithms can run on the promising AMO platform by increasing the logical clock rate by an order of magnitude with no overhead. Future research will analyse these protocols' shortcomings and develop better error correction methods to reach fault-tolerant quantum computation.

Publicly releasing simulated Stim circuits shows a commitment to reproducibility. The research “Scalable decoding protocols for fast transversal logic in the surface code,” by Mark L. Turner, Earl T. Campbell, Ophelia Crawford, Neil I. Gillespie, and Joan Camps, presents these methods and their results.

Understanding Transversal Logic Transversal logic is used in quantum computing, specifically for logical operations on encoded qubits. Quantum error correction codes like the surface code encode quantum information over numerous physical qubits to prevent errors. Quantum computation uses logical gates to process encoded data.

Transversal logic allows quantum operations on encoded qubits without physical modification. The alternative is “exploit higher connectivity.” Logical gates can be applied across encoded qubits in a simpler, often local fashion to transversal logic instead of lattice surgery's complex measurement sequences.

Sources say transversal logic's key benefit is increasing the logical clock rate. The logical clock rate is the speed at which error-corrected logical qubits can perform quantum calculations. Reducing syndrome extraction rounds speeds up calculations. As indicated, AMO syndrome extraction is slow. Transversal logic reduces these rounds, speeding computations.

Lattice surgery, an effective decoding method, struggles with rapid transversal logic. Transversal logic violates structural properties needed for real-time lattice surgery decoding, sources say. The localised nature of faults and error syndromes during typical operations may explain these structural traits, which help decoders analyse information. Transversal logic alters its structure, making real-time decoding harder.

Research in the news item addresses this conflict. Researchers have created new windowed decoding protocols that return modularity and locality to decoding to take advantage of transversal logic's performance advantages while preserving efficiency. This avoids the decoding bottleneck and enables transversal logic's order-of-magnitude speedup.

Transversal logic promises to speed up processing by reducing syndrome extraction overhead for quantum operations on encoded qubits. Due to improved protocols that eliminate this conflict, transversal logic, notably for AMO qubits, can now be decoded faster.