702 citations · 847 across the 8 of their papers we have counts for
9 papers
A scalable and real-time neural decoder for topological quantum codes
Andrew W. Senior, Thomas Edlich, Francisco J. H. Heras +21
Fault-tolerant quantum computing will require error rates far below those achievable with physical qubits. Quantum error correction (QEC) bridges this gap, but depends on decoders…
Discovery of Unstable Singularities
Yongji Wang, Mehdi Bennani, James Martens +19
Whether singularities can form in fluids remains a foundational unanswered question in mathematics. This phenomenon occurs when solutions to governing equations, such as the 3D Eul…
AlphaEvolve: A coding agent for scientific and algorithmic discovery
Alexander Novikov, Ngân Vũ, Marvin Eisenberger +15
In this white paper, we present AlphaEvolve, an evolutionary coding agent that substantially enhances capabilities of state-of-the-art LLMs on highly challenging tasks such as tack…
Drums of high width
Alex Davies, Prateek Gupta, Sebastien Racaniere +4
We provide a family of -dimensional prismatoids whose width grows linearly in the number of vertices. This provides a new infinite family of counter-examples to the Hirsch conje…
Advancing Geometry with AI: Multi-agent Generation of Polytopes
Grzegorz Swirszcz, Adam Zsolt Wagner, Geordie Williamson +7
Polytopes are one of the most primitive concepts underlying geometry. Discovery and study of polytopes with complex structures provides a means of advancing scientific knowledge. C…
Scaling and logic in the color code on a superconducting quantum processor
Nathan Lacroix, Alexandre Bourassa, Francisco J. H. Heras +212
Quantum error correction is essential for bridging the gap between the error rates of physical devices and the extremely low logical error rates required for quantum algorithms. Re…
The unknotting number, hard unknot diagrams, and reinforcement learning
Taylor Applebaum, Sam Blackwell, Alex Davies +5
We have developed a reinforcement learning agent that often finds a minimal sequence of unknotting crossing changes for a knot diagram with up to 200 crossings, hence giving an upp…
Quantum error correction below the surface code threshold
Rajeev Acharya, Laleh Aghababaie-Beni, Igor Aleiner +246
Quantum error correction provides a path to reach practical quantum computing by combining multiple physical qubits into a logical qubit, where the logical error rate is suppressed…
Learning to Decode the Surface Code with a Recurrent, Transformer-Based Neural Network
Johannes Bausch, Andrew W Senior, Francisco J H Heras +15
Quantum error-correction is a prerequisite for reliable quantum computation. Towards this goal, we present a recurrent, transformer-based neural network which learns to decode the…