Quantum Error Correction
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Discovering autonomous quantum error correction via deep reinforcement learning
Announce Type: replace-cross Abstract: Quantum error correction is essential for fault-tolerant quantum computing. However, standard methods relying on active measurements may introduce additional errors. Autonomous quantum error correction (AQEC) circumvents this by utilizing engineered dissipation and drives in bosonic systems, but identifying practical encoding remains challenging due to stringent Knill-Laflamme conditions.
Quantum Global Variational Learning for Quantum Error Correction
arXiv:2606.08592v1 Announce Type: new Abstract: Efficient quantum error correction is essential for the advancement of quantum computing. We propose a quantum neural network with a global structure that reduces the number of unitary matrices required in quantum circuits. This approach resulted in a 97\% reduction in training time and up to a 25\% improvement in the training completion rate, ultimately achieving a 100\% success rate in training while surpassing the error correction...
Improved quantum processor logical error rates via correction and detection
Abstract Performing quantum algorithms for critical problems in physics and chemistry requires substantially lower error rates than the physical error rates of present quantum computers. Achieving such low logical error rates requires quantum error correction1,2 and physical error rates below a critical threshold value3,4,5,6,7,8. We experimentally demonstrate on a trapped-ion quantum charge-coupled device (QCCD)9,10 improvements in logical error rates ranging from 11× to 800× compared with...
Learning Logical Operations for Arbitrary Quantum Error Correction Codes
Announce Type: replace-cross Abstract: Logical operations are essential for quantum computation within quantum error-correcting codes. However, discovering their physical realizations is challenging, especially for non-additive codes that lack a stabilizer description. We present a general learning-based framework that, given only an encoding circuit, constructs physical implementations of logical operations while enforcing structural properties such as transversality or shallow depth.
Quantum error correction with the toric code
arXiv:2606.04079v1 Announce Type: cross Abstract: Quantum computing platforms based on arrays of tweezer-confined neutral atoms have recently emerged as a competitive modality thanks to a direct path toward high qubit count, rapidly advancing operation fidelities, and their ability to execute circuits with arbitrary qubit connectivity. These features will enable the use of efficient error correction schemes with high encoding-rates, time-efficient decoding, and resource-efficient...
An Explicit Scott-Type Bound for Absolutely Maximally Entangled States with Arbitrary Defect
arXiv:2606.01943v1 Announce Type: cross Abstract: Absolutely maximally entangled (AME) states and, more generally, $k$-uniform states in $(\C^q)^{\otimes n}$ are central objects in multipartite entanglement theory, with applications to quantum secret sharing, quantum masking, and quantum error correction. In the extremal case $k=\lfloor n/2\rfloor$, Scott (2004) proved a sharp nonexistence bound showing that AME states cannot exist once the number of parties $n$ exceeds a threshold of order...
Hardware-aware Low-latency Quantum Compilation with Data-driven Lightweight Error Detection for Early Fault-Tolerant Systems
arXiv:2606.07666v1 Announce Type: cross Abstract: Noisy intermediate-scale quantum (NISQ) processors are entering an early fault-tolerance regime where full quantum error correction carries prohibitive resource costs, yet lightweight error detection can meaningfully improve algorithmic success rates. Existing compilation and error-detection toolchains treat these concerns in isolation, with no principled way to balance detection overhead against success probability under latency constraints....
Cloud-tested quantum noise model predicts superconducting qubit errors with sevenfold better accuracy
Cloud-tested quantum noise model predicts superconducting qubit errors with sevenfold better accuracy Gaby Clark Scientific Editor Robert Egan Associate Editor Researchers from the Johns Hopkins Applied Physics Laboratory (APL) in Laurel, Maryland, and Johns Hopkins University in Baltimore have developed a practical, comprehensive noise-modeling framework for a popular class of superconducting quantum processors. Their work, published in the journal PRX Quantum, offers a sevenfold...
'Don't scare the cat!' Engineers find smarter way to measure quantum systems
'Don't scare the cat!' Engineers find smarter way to measure quantum systems Gaby Clark Scientific Editor Robert Egan Associate Editor UNSW Sydney engineers have riffed on the famous Schrödinger's cat analogy to demonstrate a more efficient way to eliminate errors in quantum computing. "Imagine you're trying to find your cat hiding in one of eight identical cardboard boxes, in a dark and noisy room," says UNSW Scientia Professor Andrea Morello.
Parallelizing Large-Scale Tensor Network Contraction on Multiple GPUs
arXiv:2606.01852v1 Announce Type: new Abstract: Exact tensor network contraction underpins quantum circuit simulation, quantum error correction, combinatorial optimization, and many-body dynamics. The dominant parallelization strategy, slicing, scales exponentially and incurs redundant computation. We present a multi-GPU framework that instead distributes intermediate tensors across devices with explicit communication, converting a fixed contraction path into a communication-efficient...