Large scale quantum computers will generate terabytes of syndrome data every second that must be decoded as fast as it’s acquired to stop errors propagating and rendering calculations useless.
To tackle this challenge, we’ve created Deltaflow.Decode, the world's most powerful scalable quantum error decoder. Customisable to each quantum computer maker's requirements, Deltaflow.Decode can be tightly integrated with any qubit control system to implement a complete high-speed quantum error correction cycle.
Deltaflow.Decode is the product of ground-breaking research into quantum error correction (QEC) by the world’s top experts in decoding, noise modelling and chip design.
Deltaflow.Decode can spot qubit errors quickly and accurately, and is designed to support the next generation of bigger and more powerful quantum computers.
Our approach
We use a robust process and a powerful set of tools to create decoders tailored to each quantum computer maker’s hardware.
Using prototyping and simulation to validate the design at every step, we start by modelling the decoder in pure software, then move to software modelling of a decoder chip, before creating a physical chip and integrating it inside the quantum computer.
The result is a high-performance decoder that delivers significant improvements over existing state-of-the-art Union Find decoders that can process more syndrome data more accurately and more quickly using smaller and more power efficient devices.
Resources
Deltaflow.Decode
with lower power consumption
Deltaflow.Decode IP
Deltaflow.Decode is a powerful quantum decoder technology, balancing speed and accuracy with resource requirements to provide a practical route to error-corrected quantum computing.
Riverlane’s quantum decoder granted US patent
Riverlane granted a US Patent for its "quantum computing decoder and associated methods" to address the 'backlog problem' – a fundamental barrier to scaling quantum computers.
Riverlane Launches World’s Most Powerful Quantum Decoder
The paper “A real-time, scalable, fast and highly resource efficient decoder for a quantum computer” explains how Riverlane’s latest quantum decoder balances the speed, accuracy, cost, hardware and power requirements to provide a practical route to error-corrected quantum computing.
Introducing the Riverlane Roadmap: Three basic steps to decoder success
Riverlane has announced a significant milestone in our development of the error correction stack for quantum computers. We have posted our first arXiv pre-print that dives deep into our current generation decoder (DD1) for quantum error correction.
What is a TeraQuop decoder?
A TeraQuop decoder would enable a quantum computer to perform a trillion reliable operations – this is important because this represents the scale at which quantum computers start to solve problems that are intractable for any supercomputer.
Featured experts
Our world-leading team of researchers and engineers have decades of combined experience in the design and implementation of high speed, high performance error correction solutions.
Our dedicated noise team, led by Hari Krovi, builds circuit level noise models for our partners' quantum computing hardware, enabling us to create powerful and efficient decoders tailored to their qubits.
Dr Earl Campbell
VP Quantum Science
Earl is a world expert in quantum error correction with nearly two decades of experience fresh design concepts for fault-tolerant quantum computing architectures. He's made significant contributions to quantum error correction, fault-tolerant quantum logic and compilation and quantum algorithms. Before joining Riverlane Earl worked as a senior research scientist at Amazon Web Services and a senior lecturer at the University of Sheffield.
Dr Neil Gillespie
Head of Decoding
Neil is a mathematician with a passion for applying ideas and techniques from pure maths to real world scenarios. Neil completed his PhD in Mathematics from the University of Western Australia in 2011. After a post-doctoral position in Australia, he returned to the UK to join the Heilbronn Institute for Mathematical Research as a research fellow, based at the University of Bristol.
Dr Hari Krovi
Tech Lead
Hari is a quantum information theorist with over 10 years' experience in quantum computing and communication. He holds a PhD in Electrical Engineering from the University of Southern California where he worked on quantum algorithms, complexity theory and quantum communications. More recently Hari has worked on quantum algorithms for differential equations, analysis of noise on quantum circuits and quantum tomography.
Dr Ophelia Crawford
Senior Quantum Scientist
Ophelia holds a PhD in computational and theoretical geophysics from the University of Cambridge. Her work on applying PDE-constrained optimisation to post-glacial sea level change earnt her awards for the best paper from Geophysical Journal International and the best thesis from the Royal Astronomical Society. Since joining Riverlane in 2018 Ophelia has worked on understanding and developing algorithms for quantum computers.
Kauser Johar
Head of Silicon
Kauser is an engineer with over 12 years' experience in computer architecture, hardware design and development of high performance microprocessors. He holds a Masters in Microelectronics from the University of Liverpool, and pursued a career at ARM where he recently led the development of automotive CPUs. Notably, Kauser was instrumental in the development of a CPU for the Mars Exploration Rovers.
