Riverlane’s updated decoder enables unlimited quantum memory experiments

Riverlane, a leading quantum computing company, has made a significant breakthrough in unlocking unlimited quantum memory experiments with its updated decoder technology. The team, led by Kenton Barnes, has integrated a ‘sliding window’ decoding technique into its proprietary Collision Clustering decoder, allowing for arbitrarily long memory experiments to run in real-time.

This innovation enables the processing of continuous streams of measurement results as they arrive, eliminating the need to collect all data before starting an experiment. The updated decoder also improves speed and resource scaling, bringing Riverlane closer to its goal of achieving one-million error-free quantum operations by 2026. The Collision Clustering decoder is a key component of Riverlane’s Quantum Error Correction Stack, Deltaflow, which provides fast, resource-efficient, and scalable quantum decoding solutions for quantum hardware companies.

Unlocking Unlimited Quantum Memory Experiments with Riverlane’s Updated Decoder

Riverlane has made a significant breakthrough in quantum error correction (QEC) by integrating a ‘sliding window’ decoding technique into its proprietary Collision Clustering decoder. This innovation enables arbitrarily long memory experiments to run in real-time, paving the way for unlimited quantum memory experiments.

The updated decoder is a crucial component of Riverlane’s Quantum Error Correction Stack, Deltaflow, which provides a full-stack QEC solution for quantum hardware companies. The decoder can be implemented in software or hardware, with the latter being used by companies requiring mature QEC solutions to correct errors in their qubits in real-time.

Real-Time Decoding and Unlimited Memory Experiments

The ‘sliding window’ technique allows the decoder to process continuous streams of measurement results as they arrive, eliminating the need to collect all measurement data and wait until after an experiment has finished. This approach enables arbitrarily long memory experiments to run without any limitations on the number of rounds of data that can be streamed into the decoder.

The updated decoder also improves the speed of Riverlane’s Collision Clustering decoder, providing better resource scaling. The per-round decoding time is approximately half that of the previous version, making it possible to achieve a crucial 1µs per round decoding time up to and including distance 27.

Resource Scaling and Optimizations

The optimisations made to the decoder have improved its resource scaling, resulting in better utilisation of the Field-Programmable Gate Array (FPGA). The FPGA corresponds to the cost and power requirements of the decoder, making it smaller than the previous decoder at modest-sized codes. For example, for a distance 23 rotated planar surface code, the Look-Up Table (LUT) count has reduced from 21,693 to 4,794, and the flip-flop count has reduced from 15,126 to 3,310.

Long-Lived Memory and Sliding Window Technique

The ‘sliding window’ technique enables the decoder to deal with arbitrarily long memory experiments. Before this innovation, the decoder was fixed to a certain number of rounds in the memory experiment, limiting its ability to maintain the state of a logical qubit for an extended period.

Now, the decoder can maintain the state of a logical qubit for as long as the underlying physical error-rates allow. The technique involves dealing with a “window” of the data at once and then sliding the window of data being processed through the entire experiment, constantly updating the error state of the logical qubit being decoded.

Riverlane’s updated decoder is a significant step forward in achieving real-time decoding, which is vital to unlock useful quantum computing. The company is continuing to tackle this challenge, with its sights set on achieving one-million error-free quantum operations by 2026, with intermediate releases every year.