High-dimensional counterdiabatic quantum computing
- URL: http://arxiv.org/abs/2410.10622v1
- Date: Mon, 14 Oct 2024 15:29:01 GMT
- Title: High-dimensional counterdiabatic quantum computing
- Authors: Diego Tancara, Francisco Albarrán-Arriagada,
- Abstract summary: We consider qutrits in the context of quadratic problems, obtaining the qutrit Hamiltonian codifications and the counterdiabatic drivings.
Our findings show that the use of qutrits can improve the quality of the solution up to 90 times compared to qubits counterpart.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The digital version of adiabatic quantum computing enhanced by counterdiabatic driving, known as digitized counterdiabatic quantum computing, has emerged as a paradigm that opens the door to fast and low-depth algorithms. In this work, we explore the extension of this paradigm to high-dimensional systems. Specifically, we consider qutrits in the context of quadratic problems, obtaining the qutrit Hamiltonian codifications and the counterdiabatic drivings. Our findings show that the use of qutrits can improve the quality of the solution up to 90 times compared to qubits counterpart. We test our proposal on 1000 random instances of the multi-way number partitioning, max 3-cut, and portfolio optimization problems, demonstrating that, in general, without prior knowledge, it is always better to use high-dimensional systems instead of qubits. Finally, considering the state-of-the-art in quantum platforms, we show the experimental feasibility of our high-dimensional counterdiabatic quantum algorithms at least in a full digital form. This work paves the way for the efficient codification of optimization problems in high-dimensional spaces and their efficient implementation using counterdiabatic quantum computing.
Related papers
- Symmetry-enhanced Counterdiabatic Quantum Algorithm for Qudits [2.8606554662852846]
We propose a symmetry-enhanced digitized counterdiabatic quantum algorithm utilizing qudits instead of qubits.
First, compression in the circuit depth is achieved by counterdiabatic protocols.
Second, information about the problem is compressed by replacing qubits with qudits, allowing for a more efficient representation of the problem.
arXiv Detail & Related papers (2024-10-09T09:30:25Z) - Bias-field digitized counterdiabatic quantum optimization [39.58317527488534]
We call this protocol bias-field digitizeddiabatic quantum optimization (BF-DCQO)
Our purely quantum approach eliminates the dependency on classical variational quantum algorithms.
It achieves scaling improvements in ground state success probabilities, increasing by up to two orders of magnitude.
arXiv Detail & Related papers (2024-05-22T18:11:42Z) - A quantum annealing approach to the minimum distance problem of quantum codes [0.0]
We introduce an approach to compute the minimum distance of quantum stabilizer codes by reformulating the problem as a Quadratic Unconstrained Binary Optimization problem.
We demonstrate practical viability of our method by comparing the performance of purely classical algorithms with the D-Wave Advantage 4.1 quantum annealer.
arXiv Detail & Related papers (2024-04-26T21:29:42Z) - Benchmarking Quantum Optimization for the Maximum-Cut Problem on a Superconducting Quantum Computer [0.3518016233072556]
A superconducting quantum computer is used to investigate the performance of a hybrid quantum-classical algorithm.
We benchmark the quantum solver against similarly high-performing classicals.
A run-time analysis shows that the quantum solver on large-scale problems is competitive against Gurobi but short of others on a projected 100-qubit quantum computer.
arXiv Detail & Related papers (2024-04-26T17:59:22Z) - Generalized quantum Arimoto-Blahut algorithm and its application to
quantum information bottleneck [55.22418739014892]
We generalize the quantum Arimoto-Blahut algorithm by Ramakrishnan et al.
We apply our algorithm to the quantum information bottleneck with three quantum systems.
Our numerical analysis shows that our algorithm is better than their algorithm.
arXiv Detail & Related papers (2023-11-19T00:06:11Z) - A Universal Quantum Algorithm for Weighted Maximum Cut and Ising
Problems [0.0]
We propose a hybrid quantum-classical algorithm to compute approximate solutions of binary problems.
We employ a shallow-depth quantum circuit to implement a unitary and Hermitian operator that block-encodes the weighted maximum cut or the Ising Hamiltonian.
Measuring the expectation of this operator on a variational quantum state yields the variational energy of the quantum system.
arXiv Detail & Related papers (2023-06-10T23:28:13Z) - Quantum Annealing for Single Image Super-Resolution [86.69338893753886]
We propose a quantum computing-based algorithm to solve the single image super-resolution (SISR) problem.
The proposed AQC-based algorithm is demonstrated to achieve improved speed-up over a classical analog while maintaining comparable SISR accuracy.
arXiv Detail & Related papers (2023-04-18T11:57:15Z) - Quantum-Enhanced Greedy Combinatorial Optimization Solver [12.454028945013924]
We introduce an iterative quantum optimization algorithm to solve optimization problems.
We implement the quantum algorithm on a programmable superconducting quantum system using up to 72 qubits.
We find the quantum algorithm systematically outperforms its classical greedy counterpart, signaling a quantum enhancement.
arXiv Detail & Related papers (2023-03-09T18:59:37Z) - Quantum Worst-Case to Average-Case Reductions for All Linear Problems [66.65497337069792]
We study the problem of designing worst-case to average-case reductions for quantum algorithms.
We provide an explicit and efficient transformation of quantum algorithms that are only correct on a small fraction of their inputs into ones that are correct on all inputs.
arXiv Detail & Related papers (2022-12-06T22:01:49Z) - Complexity-Theoretic Limitations on Quantum Algorithms for Topological
Data Analysis [59.545114016224254]
Quantum algorithms for topological data analysis seem to provide an exponential advantage over the best classical approach.
We show that the central task of TDA -- estimating Betti numbers -- is intractable even for quantum computers.
We argue that an exponential quantum advantage can be recovered if the input data is given as a specification of simplices.
arXiv Detail & Related papers (2022-09-28T17:53:25Z) - Surviving The Barren Plateau in Variational Quantum Circuits with
Bayesian Learning Initialization [0.0]
Variational quantum-classical hybrid algorithms are seen as a promising strategy for solving practical problems on quantum computers in the near term.
Here, we introduce the fast-and-slow algorithm, which uses gradients to identify a promising region in Bayesian space.
Our results move variational quantum algorithms closer to their envisioned applications in quantum chemistry, optimization, and quantum simulation problems.
arXiv Detail & Related papers (2022-03-04T17:48:57Z) - Adiabatic Quantum Graph Matching with Permutation Matrix Constraints [75.88678895180189]
Matching problems on 3D shapes and images are frequently formulated as quadratic assignment problems (QAPs) with permutation matrix constraints, which are NP-hard.
We propose several reformulations of QAPs as unconstrained problems suitable for efficient execution on quantum hardware.
The proposed algorithm has the potential to scale to higher dimensions on future quantum computing architectures.
arXiv Detail & Related papers (2021-07-08T17:59:55Z) - Imaginary Time Propagation on a Quantum Chip [50.591267188664666]
Evolution in imaginary time is a prominent technique for finding the ground state of quantum many-body systems.
We propose an algorithm to implement imaginary time propagation on a quantum computer.
arXiv Detail & Related papers (2021-02-24T12:48:00Z) - Space-efficient binary optimization for variational computing [68.8204255655161]
We show that it is possible to greatly reduce the number of qubits needed for the Traveling Salesman Problem.
We also propose encoding schemes which smoothly interpolate between the qubit-efficient and the circuit depth-efficient models.
arXiv Detail & Related papers (2020-09-15T18:17:27Z)
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.