Rydberg-atom graphs for quadratic unconstrained binary optimization problems

• URL: http://arxiv.org/abs/2309.14847v1
• Date: Tue, 26 Sep 2023 11:22:38 GMT
• Title: Rydberg-atom graphs for quadratic unconstrained binary optimization problems
• Authors: Andrew Byun, Junwoo Jung, Kangheun Kim, Minhyuk Kim, Seokho Jeong, Heejeong Jeong and Jaewook Ahn
• Abstract summary: We present an experimental demonstration of how the quadratic unconstrained binary optimization problem can be effectively addressed using Rydbergatom graphs. The Rydberg-atom graphs are configurations of neutral atoms into mathematical graphs facilitated by programmable optical tweezers.
• Score: 0.3562485774739681
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: There is a growing interest in harnessing the potential of the Rydberg-atom system to address complex combinatorial optimization challenges. Here we present an experimental demonstration of how the quadratic unconstrained binary optimization (QUBO) problem can be effectively addressed using Rydberg-atom graphs. The Rydberg-atom graphs are configurations of neutral atoms organized into mathematical graphs, facilitated by programmable optical tweezers, and designed to exhibit many-body ground states that correspond to the maximum independent set (MIS) of their respective graphs. We have developed four elementary Rydberg-atom subgraph components, not only to eliminate the need of local control but also to be robust against interatomic distance errors, while serving as the building blocks sufficient for formulating generic QUBO graphs. To validate the feasibility of our approach, we have conducted a series of Rydberg-atom experiments selected to demonstrate proof-of-concept operations of these building blocks. These experiments illustrate how these components can be used to programmatically encode the QUBO problems to Rydberg-atom graphs and, by measuring their many-body ground states, how their QUBO solutions are determined subsequently.

Related papers

• Generation of quantum phases of matter and finding a maximum-weight independent set of unit-disk graphs using Rydberg atoms [4.619601221994331]
  We study the problem of a maximum-weight independent set of unit-disk graphs using Rydberg excitation. We consider driving the quantum system of interacting atoms to the many-body ground state using a non-linear quasi-adiabatic profile for sweeping the Rydberg detuning. We also investigate the quantum phases of matter realizing commensurate and incommensurate phases in one- and two-dimensional spatial arrangements of the atomic array.
  arXiv  Detail & Related papers  (2024-05-16T04:23:17Z)
• Solving optimization problems with local light shift encoding on Rydberg quantum annealers [0.0]
  We provide a non-unit disk framework to solve optimization problems on a Rydberg quantum annealer. Our setup consists of a many-body interacting Rydberg system where locally controllable light shifts are applied to individual qubits. Our numerical simulations implement the local-detuning protocol while globally driving the Rydberg annealer to the desired many-body ground state.
  arXiv  Detail & Related papers  (2023-08-15T14:24:45Z)
• Exploring the impact of graph locality for the resolution of MIS with neutral atom devices [0.755972004983746]
  We build upon recent progress made for using 3D arrangements to embed more complex classes of graphs. We report experimental and theoretical results which represent important steps towards tackling hard problems on quantum computers.
  arXiv  Detail & Related papers  (2023-06-23T08:53:16Z)
• One-step Bipartite Graph Cut: A Normalized Formulation and Its Application to Scalable Subspace Clustering [56.81492360414741]
  We show how to enforce a one-step normalized cut for bipartite graphs, especially with linear-time complexity. In this paper, we first characterize a novel one-step bipartite graph cut criterion with normalized constraints, and theoretically prove its equivalence to a trace problem. We extend this cut criterion to a scalable subspace clustering approach, where adaptive anchor learning, bipartite graph learning, and one-step normalized bipartite graph partitioning are simultaneously modeled.
  arXiv  Detail & Related papers  (2023-05-12T11:27:20Z)
• Graph Signal Sampling for Inductive One-Bit Matrix Completion: a Closed-form Solution [112.3443939502313]
  We propose a unified graph signal sampling framework which enjoys the benefits of graph signal analysis and processing. The key idea is to transform each user's ratings on the items to a function (signal) on the vertices of an item-item graph. For the online setting, we develop a Bayesian extension, i.e., BGS-IMC which considers continuous random Gaussian noise in the graph Fourier domain.
  arXiv  Detail & Related papers  (2023-02-08T08:17:43Z)
• Embedding the MIS problem for non-local graphs with bounded degree using 3D arrays of atoms [0.0]
  The Maximum Independent Set (MIS) is a known NP-hard problem that can be naturally encoded in Rydberg atom arrays. We present a deterministic and efficient construction to embed a large family of non-local graphs in 3D atomic arrays. This construction is a first crucial step towards tackling tasks on quantum computers for which no classical efficient epsilon-approximation scheme exists.
  arXiv  Detail & Related papers  (2022-09-12T11:46:10Z)
• Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations [57.15855198512551]
  We propose a novel score-based generative model for graphs with a continuous-time framework. We show that our method is able to generate molecules that lie close to the training distribution yet do not violate the chemical valency rule.
  arXiv  Detail & Related papers  (2022-02-05T08:21:04Z)
• Rydberg Quantum Wires for Maximum Independent Set Problems with Nonplanar and High-Degree Graphs [0.7046417074932257]
  We present experiments with Rydberg atoms to solve non-deterministic-time hard (NP-hard) problems. We introduce the Rydberg quantum wire scheme with auxiliary atoms to engineer long-ranged networks of qubit atoms. Three-dimensional (3D) Rydberg-atom arrays are constructed, overcoming the intrinsic limitations of two-dimensional arrays.
  arXiv  Detail & Related papers  (2021-09-08T09:37:18Z)
• Spatial-spectral Hyperspectral Image Classification via Multiple Random Anchor Graphs Ensemble Learning [88.60285937702304]
  This paper proposes a novel spatial-spectral HSI classification method via multiple random anchor graphs ensemble learning (RAGE) Firstly, the local binary pattern is adopted to extract the more descriptive features on each selected band, which preserves local structures and subtle changes of a region. Secondly, the adaptive neighbors assignment is introduced in the construction of anchor graph, to reduce the computational complexity.
  arXiv  Detail & Related papers  (2021-03-25T09:31:41Z)
• Taxonomy of Dual Block-Coordinate Ascent Methods for Discrete Energy Minimization [96.1052289276254]
  We consider the maximum-a-posteriori inference problem in discrete graphical models and study solvers based on the dual block-coordinate ascent rule. We map all existing solvers in a single framework, allowing for a better understanding of their design principles.
  arXiv  Detail & Related papers  (2020-04-16T15:49:13Z)
• Block-Approximated Exponential Random Graphs [77.4792558024487]
  An important challenge in the field of exponential random graphs (ERGs) is the fitting of non-trivial ERGs on large graphs. We propose an approximative framework to such non-trivial ERGs that result in dyadic independence (i.e., edge independent) distributions. Our methods are scalable to sparse graphs consisting of millions of nodes.
  arXiv  Detail & Related papers  (2020-02-14T11:42:16Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.