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Errors are inevitable during all kinds quantum informational tasks and quantum error-correcting codes (QECCs) are powerful tools to fight various quantum noises. For standard QECCs physical systems have the same number of energy levels.…

Quantum Physics · Physics 2015-06-05 Zhuo Wang , Sixia Yu , Heng Fan , C. H. Oh

A constant weight binary code consists of $n$-bit binary codewords, each with exactly $w$ bits equal to 1, such that any two codewords are at least Hamming distance $d$ apart. $A(n,d,w)$ is the maximum size of a constant weight binary code…

Information Theory · Computer Science 2026-03-03 Christopher D. Rosin

Graph clustering involves the task of dividing nodes into clusters, so that the edge density is higher within clusters as opposed to across clusters. A natural, classic and popular statistical setting for evaluating solutions to this…

Machine Learning · Statistics 2016-11-17 Yudong Chen , Sujay Sanghavi , Huan Xu

We show how, given any set of generators of the stabilizer of a quantum code, an efficient gate array that computes the codewords can be constructed. For an n-qubit code whose stabilizer has d generators, the resulting gate array consists…

Quantum Physics · Physics 2009-10-30 Richard Cleve , Daniel Gottesman

A crucial insight for practical quantum error correction is that different types of errors, such as single-qubit Pauli operators, typically occur with different probabilities. Finding an optimal quantum code under such biased noise is a…

Quantum Physics · Physics 2026-01-05 Junyu Fan , Matthew Steinberg , Alexander Jahn , Chunjun Cao , Sebastian Feld

Quantum computers are a revolutionary class of computational platforms with applications in combinatorial and global optimization, machine learning, and other domains involving computationally hard problems. While these machines typically…

Quantum Physics · Physics 2026-04-21 Aditya Sodhani , Keshab K. Parhi

We construct explicitly two infinite families of genuine nonadditive 1-error correcting quantum codes and prove that their coding subspaces are 50% larger than those of the optimal stabilizer codes of the same parameters via the linear…

Quantum Physics · Physics 2009-01-15 Sixia Yu , Qing Chen , C. H. Oh

An error avoiding quantum code is presented which is capable of stabilizing Grover's quantum search algorithm against a particular class of coherent errors. This error avoiding code consists of states only which are factorizable in the…

Quantum Physics · Physics 2009-11-06 Michael Mussinger , Aldo Delgado , Gernot Alber

Recent advancements in quantum computing have enabled practical use of quantum error detecting and correcting codes. However, current architectures and future proposals of quantum computer design suffer from limited qubit counts,…

Quantum Physics · Physics 2026-04-14 Cordell Mazzetti , Sayam Sethi , Rich Rines , Pranav Gokhale , Jonathan Mark Baker

Entangled qubit can increase the capacity of quantum error correcting codes based on stabilizer codes. In addition, by using entanglement quantum stabilizer codes can be construct from classical linear codes that do not satisfy the…

Quantum Physics · Physics 2015-05-30 Jeonghwan Shin , Jun Heo , Todd A. Brun

Graph spanners are sparse subgraphs that faithfully preserve the distances in the original graph up to small stretch. Spanner have been studied extensively as they have a wide range of applications ranging from distance oracles, labeling…

Data Structures and Algorithms · Computer Science 2018-05-16 Merav Parter , Eylon Yogev

Quantum annealers can be used to solve many (possibly NP-hard) combinatorial optimization problems, by formulating them as quadratic unconstrained binary optimization (QUBO) problems or, equivalently, using the Ising formulation. In this…

Quantum Physics · Physics 2024-06-13 Alessandro Gherardi , Alberto Leporati

We give a simple deterministic constant-round algorithm in the congested clique model for reducing the number of edges in a graph to $n^{1+\varepsilon}$ while preserving the minimum spanning forest, where $\varepsilon > 0$ is any constant.…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-05-09 Janne H. Korhonen

Let $\mathcal{H}(k,n,p)$ be the distribution on $k$-uniform hypergraphs where every subset of $[n]$ of size $k$ is included as an hyperedge with probability $p$ independently. In this work, we design and analyze a simple spectral algorithm…

Data Structures and Algorithms · Computer Science 2022-05-16 Venkatesan Guruswami , Pravesh K. Kothari , Peter Manohar

In a distinguishing problem, the input is a sample drawn from one of two distributions and the algorithm is tasked with identifying the source distribution. The performance of a distinguishing algorithm is measured by its advantage, i.e.,…

Computational Complexity · Computer Science 2025-07-22 Ansh Nagda , Prasad Raghavendra

The qubit-mapping problem aims to assign and route qubits of a quantum circuit onto a NISQ device in an optimized fashion, with respect to some cost function. Finding an optimal solution to this problem is known to scale exponentially in…

The maximum clique problem (MCP) is to find the largest complete subgraph in an undirected graph, that is, the subgraph in which there are edges between every two different vertices. It is an NP-Hard problem with wide applications,…

Quantum Physics · Physics 2025-09-03 Wenmin Han , Shiqi Zheng , Peian Chen , Yukun Wang

We design a deterministic compiler that makes any computation in the Congested Clique model robust to a constant fraction $\alpha<1$ of adversarial crash faults. In particular, we show how a network of $n$ nodes can compute any circuit of…

Data Structures and Algorithms · Computer Science 2025-08-13 Keren Censor-Hillel , Orr Fischer , Ran Gelles , Pedro Soto

Graph states are generalized from qubits to collections of $n$ qudits of arbitrary dimension $D$, and simple graphical methods are used to construct both additive and nonadditive quantum error correcting codes. Codes of distance 2…

Quantum Physics · Physics 2008-11-11 Shiang Yong Looi , Li Yu , Vlad Gheorghiu , Robert B. Griffiths

Numerous graph neural network (GNN)-based algorithms have been proposed to solve graph-based combinatorial optimization problems (COPs), but methods to explain their predictions remain largely undeveloped. We introduce ARM-Explainer, a…

Machine Learning · Computer Science 2025-12-01 Bharat Sharman , Elkafi Hassini