Quantum Computing for Discrete Optimization: A Highlight of Three Technologies

• URL: http://arxiv.org/abs/2409.01373v1
• Date: Mon, 2 Sep 2024 17:04:47 GMT
• Title: Quantum Computing for Discrete Optimization: A Highlight of Three Technologies
• Authors: Alexey Bochkarev, Raoul Heese, Sven Jäger, Philine Schiewe, Anita Schöbel,
• Abstract summary: This paper focuses on interdisciplinary research between the Operations Research (OR) and Quantum Computing communities. We consider three quantum-powered optimization approaches that make use of different types of quantum hardware available on the market. We illustrate these approaches with experiments on three types of quantum computers: a neutral atom machine from QuEra, a quantum annealer from D-Wave, and a gate-based device from IBM.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Quantum optimization has emerged as a promising frontier of quantum computing, providing novel numerical approaches to mathematical optimization problems. The main goal of this paper is to facilitate interdisciplinary research between the Operations Research (OR) and Quantum Computing communities by providing an OR scientist's perspective on selected quantum-powered methods for discrete optimization. To this end, we consider three quantum-powered optimization approaches that make use of different types of quantum hardware available on the market. To illustrate these approaches, we solve three classical optimization problems: the Traveling Salesperson Problem, Weighted Maximum Cut, and Maximum Independent Set. With a general OR audience in mind, we attempt to provide an intuition behind each approach along with key references, describe the corresponding high-level workflow, and highlight crucial practical considerations. In particular, we emphasize the importance of problem formulations and device-specific configurations, and their impact on the amount of resources required for computation (where we focus on the number of qubits). These points are illustrated with a series of experiments on three types of quantum computers: a neutral atom machine from QuEra, a quantum annealer from D-Wave, and a gate-based device from IBM.

Related papers

• Evaluation of Quantum and Hybrid Solvers for Combinatorial Optimization [2.4186604326116874]
  This work comprehensively evaluating the technologies provided by D-Wave Systems. A model for the energy optimization of data centers is proposed as a benchmark. D-Wave quantum and hybrid solvers are compared, in order to identify the most suitable one for the considered application.
  arXiv  Detail & Related papers  (2024-03-15T16:43:21Z)
• Quantum Optimization: Potential, Challenges, and the Path Forward [14.7608536260003]
  Recent advances in quantum computers are demonstrating the ability to solve problems at a scale beyond brute force classical simulation. Across computer science and physics, there are different approaches for major optimization problems.
  arXiv  Detail & Related papers  (2023-12-04T19:00:44Z)
• Randomized Benchmarking of Local Zeroth-Order Optimizers for Variational Quantum Systems [65.268245109828]
  We compare the performance of classicals across a series of partially-randomized tasks. We focus on local zeroth-orders due to their generally favorable performance and query-efficiency on quantum systems.
  arXiv  Detail & Related papers  (2023-10-14T02:13:26Z)
• Quantum algorithms: A survey of applications and end-to-end complexities [90.05272647148196]
  The anticipated applications of quantum computers span across science and industry. We present a survey of several potential application areas of quantum algorithms. We outline the challenges and opportunities in each area in an "end-to-end" fashion.
  arXiv  Detail & Related papers  (2023-10-04T17:53:55Z)
• A Practitioner's Guide to Quantum Algorithms for Optimisation Problems [0.0]
  NP-hard optimisation problems are common in industrial areas such as logistics and finance. This paper aims to provide a comprehensive overview of the theory of quantum optimisation techniques. It focuses on their near-term potential for noisy intermediate scale quantum devices.
  arXiv  Detail & Related papers  (2023-05-12T08:57:36Z)
• Quantum Computing Techniques for Multi-Knapsack Problems [1.0136953995598361]
  We investigate some of the most prominent and state-of-the-art quantum algorithms using different quantum software and hardware tools. We consider several gate-based quantum algorithms, such as QAOA and VQE, and present an exhaustive study of the solutions and the estimation of runtimes.
  arXiv  Detail & Related papers  (2023-01-13T20:21:24Z)
• Assessing requirements to scale to practical quantum advantage [56.22441723982983]
  We develop a framework for quantum resource estimation, abstracting the layers of the stack, to estimate resources required for large-scale quantum applications. We assess three scaled quantum applications and find that hundreds of thousands to millions of physical qubits are needed to achieve practical quantum advantage. A goal of our work is to accelerate progress towards practical quantum advantage by enabling the broader community to explore design choices across the stack.
  arXiv  Detail & Related papers  (2022-11-14T18:50:27Z)
• Feature Selection for Recommender Systems with Quantum Computing [7.8851236034886645]
  Small but functional quantum computers have become available to the broader research community. One of the tasks that most naturally fits in this mathematical formulation is feature selection. We represent the feature selection as an optimization problem and solve it on a real quantum computer, provided by D-Wave.
  arXiv  Detail & Related papers  (2021-10-11T08:52:50Z)
• Realization of arbitrary doubly-controlled quantum phase gates [62.997667081978825]
  We introduce a high-fidelity gate set inspired by a proposal for near-term quantum advantage in optimization problems. By orchestrating coherent, multi-level control over three transmon qutrits, we synthesize a family of deterministic, continuous-angle quantum phase gates acting in the natural three-qubit computational basis.
  arXiv  Detail & Related papers  (2021-08-03T17:49:09Z)
• On exploring the potential of quantum auto-encoder for learning quantum systems [60.909817434753315]
  We devise three effective QAE-based learning protocols to address three classically computational hard learning problems. Our work sheds new light on developing advanced quantum learning algorithms to accomplish hard quantum physics and quantum information processing tasks.
  arXiv  Detail & Related papers  (2021-06-29T14:01:40Z)
• Electronic structure with direct diagonalization on a D-Wave quantum annealer [62.997667081978825]
  This work implements the general Quantum Annealer Eigensolver (QAE) algorithm to solve the molecular electronic Hamiltonian eigenvalue-eigenvector problem on a D-Wave 2000Q quantum annealer. We demonstrate the use of D-Wave hardware for obtaining ground and electronically excited states across a variety of small molecular systems.
  arXiv  Detail & Related papers  (2020-09-02T22:46:47Z)

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.