Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

arXiv:2504.08598 · Quantum Science and Technology

Graph coloring via quantum optimization on a Rydberg-qudit atom array

Toonyawat Angkhanawin, Aydin Deger, Jonathan D. Pritchard, Charles S. Adams

Published Jan 21, 2026• 1 citation
arXivHTMLPDF

Abstract

Abstract Neutral atom arrays have emerged as a versatile candidate for the embedding of hard classical optimization problems. Prior work has focused on mapping problems onto finding the maximum independent set of weighted or unweighted unit disk graphs. In this paper we introduce a new approach to solving natively-embedded vertex graph coloring problems by performing coherent annealing with Rydberg-qudit atoms, where different same-parity Rydberg levels represent a distinct label or color. We demonstrate the ability to robustly find optimal graph colorings for chromatic numbers up to the number of distinct Rydberg states used, in our case k = 3. We analyze the impact of both the long-range potential tails and residual inter-state interactions, proposing encoding strategies that suppress errors in the resulting ground states. We discuss the experimental feasibility of this approach and propose extensions to solve higher chromatic number problems, providing a route towards direct solution of a wide range of real-world integer optimization problems using near-term neutral atom hardware.

DOI
10.1088/2058-9565/ae3b6d

Related papers

Sparse-graph optimization using weighted quantum wires in Rydberg-atom arrays

André Gonçalves de Oliveira, Johannes Kombe, G. Pelegrí +5 more

Neutral atom arrays provide a versatile platform to implement coherent quantum annealing as an approach to solving hard combinatorial optimization problems. Here we present and experimentally demonstrate an efficient encoding scheme based on chains of Rydberg-blockaded atoms, which we call quantum wires, to natively embed maximum weighted independent set (MWIS) and quadratic unconstrained binary optimization (QUBO) problems on a neutral atom architecture. For graphs with quasi-unit-disk connectivity, in which only a few long-range edges are required, our approach requires a significantly lower overhead in the number of ancilla qubits than previous proposals, facilitating the implementation on currently available hardware. To demonstrate the approach, we perform annealing of weighted graphs on a programmable atom array using local light shifts to encode problem-specific weights across graphs of varying sizes. This approach successfully identifies the solutions to the original MWIS and QUBO graph instances. Our work expands the operational toolkit of near-term neutral atom arrays, enhancing their potential for scalable quantum optimization.

arXiv:2503.17115•Physical Review Applied•Jul 6, 2026•0 citations

Demonstration of Weighted-Graph Optimization on a Rydberg-Atom Array Using Local Light Shifts

André Gonçalves de Oliveira, E. Diamond-Hitchcock, D. M. Walker +7 more

Neutral-atom arrays have emerged as a versatile platform toward scalable quantum computation and optimization. In this paper, we present demonstrations of solving maximum-weighted independent-set problems on a Rydberg-atom array using annealing with local light shifts. We verify the ability to prepare weighted graphs in one-dimensional (1D) and two-dimensional (2D) arrays, including embedding a five-vertex nonunit-disk graph using nine physical qubits and demonstration of a simple crossing gadget. We find common annealing ramps leading to preparation of the target ground state robustly over a substantial range of different graph weightings. This work provides a route to exploring large-scale optimization of nonplanar weighted graphs relevant for solving relevant real-world problems.

arXiv:2404.02658•PRX Quantum•Jan 2, 2025•24 citations

Error-Corrected Quantum Optimization via Rydberg Atom Array Embeddings

Andrew Byun, Berend Klaver, Arinjoy De +5 more

Rydberg atom quantum optimizers naturally encode the maximum independent set problem on geometric graphs. However, to solve general combinatorial optimization problems on more complex topologies, an embedding is required to overcome the limited-range native interactions. Such embeddings use gadgets, specific arrangements of atoms, which inevitably introduce ancillary atoms. Here, we show that this apparent overhead instead provides an intrinsic resource for error correction. Specifically, we demonstrate that the Parity Architecture-based Rydberg embedding naturally forms a classical error-correcting code, a principle that extends to other Rydberg blockade-based embeddings. Within superatom substructures, exact Rydberg-excitation-number constraints provide local error syndromes at no additional hardware cost and give rise to a strictly nonlinear code. To correct bit-flip errors, we introduce the precisely tailored Cluster decoder, which exploits these local constraints and the underlying gadget structure. Numerically, this approach achieves an error threshold of $p_{\text{th}}\gtrsim26 \%$ across different layout geometries. Experimentally, on the QuEra Aquila QPU, the Cluster decoder recovers exact optimization solutions with an average success rate of $\gtrsim8\%$ for systems of up to 107 atoms, even when bare hardware and standard greedy post-processing find none. A Rydberg atom array embedding is therefore not merely a hardware mapping of an optimization problem, but a co-designed architecture for quantum optimization in which embedding, computation, and error correction emerge from the same physical structure.

quant-pharXiv:2610.39670•Oct 30, 2026•0 citations

Quantum Optimization with Arbitrary Connectivity Using Rydberg Atom Arrays

Minh-Thi Nguyen, Jin-Guo Liu, Jonathan Wurtz +3 more

Programmable quantum systems based on Rydberg atom arrays have recently been used for hardwareefficient tests of quantum optimization algorithms [Ebadi et al., Science, 376, 1209 (2022)] with hundreds of qubits.In particular, the maximum independent set problem on so-called unit-disk graphs, was shown to be efficiently encodable in such a quantum system.Here, we extend the classes of problems that can be efficiently encoded in Rydberg arrays by constructing explicit mappings from a wide class of problems to maximum-weighted independent set problems on unit-disk graphs, with at most a quadratic overhead in the number of qubits.We analyze several examples, including maximum-weighted independent set on graphs with arbitrary connectivity, quadratic unconstrained binary optimization problems with arbitrary or restricted connectivity, and integer factorization.Numerical simulations on small system sizes indicate that the adiabatic time scale for solving the mapped problems is strongly correlated with that of the original problems.Our work provides a blueprint for using Rydberg atom arrays to solve a wide range of combinatorial optimization problems with arbitrary connectivity, beyond the restrictions imposed by the hardware geometry.

arXiv:2209.03965•PRX Quantum•Feb 14, 2023•119 citations

Quantum Optimization for Maximum Independent Set Using Rydberg Atom Arrays

Hannes Pichler, Sheng-Tao Wang, Leo Zhou +2 more

We describe and analyze an architecture for quantum optimization to solve maximum independent set (MIS) problems using neutral atom arrays trapped in optical tweezers. Optimizing independent sets is one of the paradigmatic, NP-hard problems in computer science. Our approach is based on coherent manipulation of atom arrays via the excitation into Rydberg atomic states. Specifically, we show that solutions of MIS problems can be efficiently encoded in the ground state of interacting atoms in 2D arrays by utilizing the Rydberg blockade mechanism. By studying the performance of leading classical algorithms, we identify parameter regimes, where computationally hard instances can be tested using near-term experimental systems. Practical implementations of both quantum annealing and variational quantum optimization algorithms beyond the adiabatic principle are discussed.

arXiv:1808.10816•Aug 31, 2018•34 citations

Exploring the impact of graph locality for the resolution of the maximum- independent-set problem with neutral atom devices

Constantin Dalyac, Louis-Paul Henry, Minhyuk Kim +2 more

In the past years, many quantum algorithms have been proposed to tackle hard combinatorial problems. In particular, the maximum independent set (MIS) is a known NP-hard problem that can be naturally encoded in Rydberg atom arrays. By representing a graph with an ensemble of neutral atoms one can leverage Rydberg dynamics to naturally encode the constraints and the solution to MIS. However, the classes of graphs that can be directly mapped ``vertex-to-atom'' on standard devices with two-dimensional capabilities are currently limited to Unit-Disk graphs. In this setting, the inherent spatial locality of the graphs can be leveraged by classical polynomial-time approximation schemes (PTAS) that guarantee an $\ensuremath{\epsilon}$-approximate solution. In this work, we build upon recent progress made for using three-dimensioanl arrangements of atoms to embed more complex classes of graphs. We report experimental and theoretical results which represent important steps towards tackling combinatorial tasks on quantum computers for which no classical efficient $\ensuremath{\varepsilon}$-approximation scheme exists.

Physical Review A•Nov 21, 2023•15 citations
Abstract Neutral atom arrays have emerged as a versatile candidate for the embedding of hard classical optimization problems. Prior work has focused on mapping problems onto finding the maximum independent set of weighted or unweighted unit disk graphs. In this paper we introduce a new approach to solving natively-embedded vertex graph coloring problems by performing coherent annealing with Rydberg-qudit atoms, where different same-parity Rydberg levels represent a distinct label or color. We demonstrate the ability to robustly find optimal graph colorings for chromatic numbers up to the number of distinct Rydberg states used, in our case k = 3. We analyze the impact of both the long-range potential tails and residual inter-state interactions, proposing encoding strategies that suppress errors in the resulting ground states. We discuss the experimental feasibility of this approach and propose extensions to solve higher chromatic number problems, providing a route towards direct solution of a wide range of real-world integer optimization problems using near-term neutral atom hardware.
Neutral atom arrays provide a versatile platform to implement coherent quantum annealing as an approach to solving hard combinatorial optimization problems. Here we present and experimentally demonstrate an efficient encoding scheme based on chains of Rydberg-blockaded atoms, which we call quantum wires, to natively embed maximum weighted independent set (MWIS) and quadratic unconstrained binary optimization (QUBO) problems on a neutral atom architecture. For graphs with quasi-unit-disk connectivity, in which only a few long-range edges are required, our approach requires a significantly lower overhead in the number of ancilla qubits than previous proposals, facilitating the implementation on currently available hardware. To demonstrate the approach, we perform annealing of weighted graphs on a programmable atom array using local light shifts to encode problem-specific weights across graphs of varying sizes. This approach successfully identifies the solutions to the original MWIS and QUBO graph instances. Our work expands the operational toolkit of near-term neutral atom arrays, enhancing their potential for scalable quantum optimization.
Neutral-atom arrays have emerged as a versatile platform toward scalable quantum computation and optimization. In this paper, we present demonstrations of solving maximum-weighted independent-set problems on a Rydberg-atom array using annealing with local light shifts. We verify the ability to prepare weighted graphs in one-dimensional (1D) and two-dimensional (2D) arrays, including embedding a five-vertex nonunit-disk graph using nine physical qubits and demonstration of a simple crossing gadget. We find common annealing ramps leading to preparation of the target ground state robustly over a substantial range of different graph weightings. This work provides a route to exploring large-scale optimization of nonplanar weighted graphs relevant for solving relevant real-world problems.
Rydberg atom quantum optimizers naturally encode the maximum independent set problem on geometric graphs. However, to solve general combinatorial optimization problems on more complex topologies, an embedding is required to overcome the limited-range native interactions. Such embeddings use gadgets, specific arrangements of atoms, which inevitably introduce ancillary atoms. Here, we show that this apparent overhead instead provides an intrinsic resource for error correction. Specifically, we demonstrate that the Parity Architecture-based Rydberg embedding naturally forms a classical error-correcting code, a principle that extends to other Rydberg blockade-based embeddings. Within superatom substructures, exact Rydberg-excitation-number constraints provide local error syndromes at no additional hardware cost and give rise to a strictly nonlinear code. To correct bit-flip errors, we introduce the precisely tailored Cluster decoder, which exploits these local constraints and the underlying gadget structure. Numerically, this approach achieves an error threshold of pth≳26%p_{\text{th}}\gtrsim26 \%pth​≳26% across different layout geometries. Experimentally, on the QuEra Aquila QPU, the Cluster decoder recovers exact optimization solutions with an average success rate of ≳8%\gtrsim8\%≳8% for systems of up to 107 atoms, even when bare hardware and standard greedy post-processing find none. A Rydberg atom array embedding is therefore not merely a hardware mapping of an optimization problem, but a co-designed architecture for quantum optimization in which embedding, computation, and error correction emerge from the same physical structure.
Programmable quantum systems based on Rydberg atom arrays have recently been used for hardwareefficient tests of quantum optimization algorithms [Ebadi et al., Science, 376, 1209 (2022)] with hundreds of qubits.In particular, the maximum independent set problem on so-called unit-disk graphs, was shown to be efficiently encodable in such a quantum system.Here, we extend the classes of problems that can be efficiently encoded in Rydberg arrays by constructing explicit mappings from a wide class of problems to maximum-weighted independent set problems on unit-disk graphs, with at most a quadratic overhead in the number of qubits.We analyze several examples, including maximum-weighted independent set on graphs with arbitrary connectivity, quadratic unconstrained binary optimization problems with arbitrary or restricted connectivity, and integer factorization.Numerical simulations on small system sizes indicate that the adiabatic time scale for solving the mapped problems is strongly correlated with that of the original problems.Our work provides a blueprint for using Rydberg atom arrays to solve a wide range of combinatorial optimization problems with arbitrary connectivity, beyond the restrictions imposed by the hardware geometry.
We describe and analyze an architecture for quantum optimization to solve maximum independent set (MIS) problems using neutral atom arrays trapped in optical tweezers. Optimizing independent sets is one of the paradigmatic, NP-hard problems in computer science. Our approach is based on coherent manipulation of atom arrays via the excitation into Rydberg atomic states. Specifically, we show that solutions of MIS problems can be efficiently encoded in the ground state of interacting atoms in 2D arrays by utilizing the Rydberg blockade mechanism. By studying the performance of leading classical algorithms, we identify parameter regimes, where computationally hard instances can be tested using near-term experimental systems. Practical implementations of both quantum annealing and variational quantum optimization algorithms beyond the adiabatic principle are discussed.
In the past years, many quantum algorithms have been proposed to tackle hard combinatorial problems. In particular, the maximum independent set (MIS) is a known NP-hard problem that can be naturally encoded in Rydberg atom arrays. By representing a graph with an ensemble of neutral atoms one can leverage Rydberg dynamics to naturally encode the constraints and the solution to MIS. However, the classes of graphs that can be directly mapped ``vertex-to-atom'' on standard devices with two-dimensional capabilities are currently limited to Unit-Disk graphs. In this setting, the inherent spatial locality of the graphs can be leveraged by classical polynomial-time approximation schemes (PTAS) that guarantee an $\ensuremath{\epsilon}$-approximate solution. In this work, we build upon recent progress made for using three-dimensioanl arrangements of atoms to embed more complex classes of graphs. We report experimental and theoretical results which represent important steps towards tackling combinatorial tasks on quantum computers for which no classical efficient $\ensuremath{\varepsilon}$-approximation scheme exists.