- #MACHINE LEARNING QUANTUM ERROR CORRECTION SOFTWARE#
- #MACHINE LEARNING QUANTUM ERROR CORRECTION CODE#
Quantum error correction will stand at the core of future fault-tolerant quantum computers on the course to quantum advantage. Topic: Scaling up real-time decoding in the near and long term
#MACHINE LEARNING QUANTUM ERROR CORRECTION CODE#
of Tokyo & TU Munich Title: Online decoding of surface code with a superconducting circuitġ5:15-15:40 Speaker: Poulami Das, Georgia Tech (virtual) Title: An architect’s role in error decoding for fault-tolerant quantum computers.Ĭhristopher Chamberland, (Amazon, virtual) of Wisconsin-Madison Title: Understanding System-level Complexity of Running Quantum Error Correction Codesġ3:45-14:08 Speaker: Ramon Overwater, TU Delft (virtual) Title: Hardware Considerations of Neural Network Decoders.ġ4:08-14:30 Speaker: Yosuke Ueno, Univ. of Melbourne and Data61/CSIRO (virtual) Title: Machine-learning-based fast and autonomous decoder for scalable surface codesġ3:00-13:23 Speaker: Luka Skoric, Riverlane Title: No maximum latency requirement for decoding quantum error correction syndromes.ġ3:23-13:45 Speaker: Swamit Tannu, Univ. Target audience: Researchers and experts from the quantum error correction, quantum computation, computer science, classical architectures and digital design communities, both from academia and industry.ġ0:00-10:15 Speaker: Francesco Battistel, Qblox Title: Introduction to the workshop and overview of real-time decoding.ġ0:15-10:40 Speaker: Christopher Chamberland, Amazon (virtual) Title: Techniques for combining fast local decoders with global decoders under circuit-level noise.ġ0:40-11:05 Speaker: Natalie Brown, Quantinuum Title: Wasm + QASM: Assembling real-time decoding.ġ1:05-11:30 Speaker: Muhammad Usman, Univ. Keywords: Real-Time Decoding, Decoding, Quantum Error Correction, Computing Architectures, Computer Science, Fault-Tolerant Quantum Computing
The market-readiness of real-time decoding will also be discussed to shed light on a possible future roadmap for the broader quantum-technology industry.
#MACHINE LEARNING QUANTUM ERROR CORRECTION SOFTWARE#
The topics of the workshop cover a variety of decoding algorithms, decoding architectures and hardware, as well as co-design strategies for software and hardware. Challenges and advantages of different approaches will be discussed within both a quantum track and a classical-architecture track. This workshop aims to create a comprehensive discussion on the subject of real-time decoding and pool ideas for directions in the near and long term. It is of great importance to find the right combination of these key elements to build a practically-useful decoding architecture. Since the speed and scalability of the decoder are as critical as its accuracy, real-time decoding manifests itself as a multi-layer challenge: an efficient decoding algorithm must be implemented with the appropriate software layer, which must be executed on fast classical hardware. While previous research has primarily focused on the accuracy and threshold of a decoder, its real-time implementation is still understudied.
However, the efficacy of a code, such as the surface code, is underpinned by the decoder, which can detect errors and suggest appropriate corrections.
The quantum error correcting code forms the core to realize fault tolerance. Fault-tolerant quantum computation stands as a turning point for reaching quantum advantage.
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