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Related papers: Universal graph representation of stabilizer codes

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Typical stabilizer codes aim to solve the general problem of fault-tolerance without regard for the structure of a specific system. By incorporating a broader representation-theoretic perspective, we provide a generalized framework that…

Quantum Physics · Physics 2026-03-30 Zachary P. Bradshaw , Margarite L. LaBorde , Dillon Montero

The discovery of holographic codes established a surprising connection between quantum error correction and the anti-de Sitter-conformal field theory correspondence. Recent technological progress in artificial quantum systems renders the…

Quantum Physics · Physics 2025-01-29 Gerard Anglès Munné , Valentin Kasper , Felix Huber

To leverage the full potential of quantum error-correcting stabilizer codes it is crucial to have an efficient and accurate decoder. Accurate, maximum likelihood, decoders are computationally very expensive whereas decoders based on more…

In this thesis, we study concepts in quantum computing using graphical languages, specifically using the ZX-calculus. The core of the research revolves around (graphical) stabilizer decompositions. The first major focus is on the…

Quantum Physics · Physics 2025-03-07 Yves Vollmeier

Quantum stabilizer states over GF(m) can be represented as self-dual additive codes over GF(m^2). These codes can be represented as weighted graphs, and orbits of graphs under the generalized local complementation operation correspond to…

Information Theory · Computer Science 2009-11-11 Lars Eirik Danielsen

Recent advances in classical simulation of Clifford+T circuits make use of the ZX calculus to iteratively decompose and simplify magic states into stabiliser terms. We improve on this method by studying stabiliser decompositions of ZX…

Quantum Physics · Physics 2025-09-23 Mark Koch , Richie Yeung , Quanlong Wang

We consider design of the quantum stabilizer codes via a two-step, low-complexity approach based on the framework of codeword-stabilized (CWS) codes. In this framework, each quantum CWS code can be specified by a graph and a binary code.…

Quantum Physics · Physics 2012-02-23 Alexey A. Kovalev , Ilya Dumer , Leonid P. Pryadko

Graph representations are the generalization of geometric graph drawings from the plane to higher dimensions. A method introduced by Tutte to optimize properties of graph drawings is to minimize their energy. We explore this minimization…

Computational Geometry · Computer Science 2023-09-07 Matt DeVos , Danielle Rogers , Alexandra Wesolek

Stabilizer codes are a powerful method for implementing fault-tolerant quantum memory and in the case of topological codes, they form useful models for topological phases of matter. In this paper, we discuss the theory of stabilizer codes…

Quantum Physics · Physics 2019-10-02 Albert T. Schmitz

Topological quantum error correcting codes have emerged as leading candidates towards the goal of achieving large-scale fault-tolerant quantum computers. However, quantifying entanglement in these systems of large size in the presence of…

Quantum Physics · Physics 2020-08-18 David Amaro , Markus Müller , Amit Kumar Pal

Efficient simulation of quantum computers relies on understanding and exploiting the properties of quantum states. This is the case for methods such as tensor networks, based on entanglement, and the tableau formalism, which represents…

Quantum Physics · Physics 2024-12-25 Sergi Masot-Llima , Artur Garcia-Saez

Deciding if a given family of quantum states is topologically ordered is an important but nontrivial problem in condensed matter physics and quantum information theory. We derive necessary and sufficient conditions for a family of graph…

Quantum Physics · Physics 2022-09-09 Pengcheng Liao , Barry C. Sanders , David L. Feder

Graph states are widely used in quantum information theory, including entanglement theory, quantum error correction, and one-way quantum computing. Graph states have a nice structure related to a certain graph, which is given by either a…

Quantum Physics · Physics 2015-11-20 Shawn X Cui , Nengkun Yu , Bei Zeng

Learning from source code usually requires a large amount of labeled data. Despite the possible scarcity of labeled data, the trained model is highly task-specific and lacks transferability to different tasks. In this work, we present…

Machine Learning · Computer Science 2021-03-05 Linfeng Liu , Hoan Nguyen , George Karypis , Srinivasan Sengamedu

We propose a systematic procedure for the construction of graphs associated with binary quantum stabilizer codes. The procedure is characterized by means of the following three step process. First, the stabilizer code is realized as a…

Quantum Physics · Physics 2022-06-29 Carlo Cafaro

Graphcodes were recently introduced as a technique to employ two-parameter persistence modules in machine learning tasks (Kerber and Russold, NeurIPS 2024). We show in this work that a compressed version of graphcodes yields a description…

Algebraic Topology · Mathematics 2025-03-11 Michael Kerber , Florian Russold

In the absence of fault tolerant quantum error correction for analog, Hamiltonian quantum computation, error suppression via energy penalties is an effective alternative. We construct families of distance-$2$ stabilizer subsystem codes we…

Quantum Physics · Physics 2025-08-06 Phattharaporn Singkanipa , Zihan Xia , Daniel A. Lidar

We introduce a high-level graphical framework for designing and analysing quantum error correcting codes, centred on what we term the coherent parity check (CPC). The graphical formulation is based on the diagrammatic tools of the…

Quantum Physics · Physics 2023-08-21 Nicholas Chancellor , Aleks Kissinger , Joschka Roffe , Stefan Zohren , Dominic Horsman

We study the notion of $k$-stabilizer universal quantum state, that is, an $n$-qubit quantum state, such that it is possible to induce any stabilizer state on any $k$ qubits, by using only local operations and classical communications.…

Transformers are increasingly employed for graph data, demonstrating competitive performance in diverse tasks. To incorporate graph information into these models, it is essential to enhance node and edge features with positional encodings.…