Constraint programming models for depth-optimal qubit assignment and
SWAP-based routing
- URL: http://arxiv.org/abs/2306.08629v1
- Date: Wed, 14 Jun 2023 16:42:36 GMT
- Title: Constraint programming models for depth-optimal qubit assignment and
SWAP-based routing
- Authors: Kyle E. C. Booth
- Abstract summary: We propose constraint programming (CP) models for a qubit assignment and routing problem.
We compare their performance against integer linear programming (ILP) models for circuit depth minimization.
Our empirical analysis indicates that the proposed CP approaches outperform the ILP models both in terms of solution quality and runtime.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Due to the limited connectivity of gate model quantum devices, logical
quantum circuits must be compiled to target hardware before they can be
executed. Often, this process involves the insertion of SWAP gates into the
logical circuit, usually increasing the depth of the circuit, achieved by
solving a so-called qubit assignment and routing problem. Recently, a number of
integer linear programming (ILP) models have been proposed for solving the
qubit assignment and routing problem to proven optimality. These models encode
the objective function and constraints of the problem, and leverage the use of
automated solver technology to find hardware-compliant quantum circuits. In
this work, we propose constraint programming (CP) models for this problem and
compare their performance against ILP for circuit depth minimization for both
linear and two-dimensional grid lattice device topologies on a set of randomly
generated instances. Our empirical analysis indicates that the proposed CP
approaches outperform the ILP models both in terms of solution quality and
runtime.
Related papers
- A Fast and Adaptable Algorithm for Optimal Multi-Qubit Pathfinding in Quantum Circuit Compilation [0.0]
This work focuses on multi-qubit pathfinding as a critical subroutine within the quantum circuit compilation mapping problem.
We introduce an algorithm, modelled using binary integer linear programming, that navigates qubits on quantum hardware optimally with respect to circuit SWAP-gate depth.
We have benchmarked the algorithm across a variety of quantum hardware layouts, assessing properties such as computational runtimes, solution SWAP depths, and accumulated SWAP-gate error rates.
arXiv Detail & Related papers (2024-05-29T05:59:15Z) - Compiler for Distributed Quantum Computing: a Reinforcement Learning Approach [6.347685922582191]
We introduce a novel compiler that prioritizes reducing the expected execution time by jointly managing the generation and routing of EPR pairs.
We present a real-time, adaptive approach to compiler design, accounting for the nature of entanglement generation and the operational demands of quantum circuits.
Our contributions are twofold: (i) we model the optimal compiler for DQC using a Markov Decision Process (MDP) formulation, establishing the existence of an optimal algorithm, and (ii) we introduce a constrained Reinforcement Learning (RL) method to approximate this optimal compiler.
arXiv Detail & Related papers (2024-04-25T23:03:20Z) - Bayesian Parameterized Quantum Circuit Optimization (BPQCO): A task and hardware-dependent approach [49.89480853499917]
Variational quantum algorithms (VQA) have emerged as a promising quantum alternative for solving optimization and machine learning problems.
In this paper, we experimentally demonstrate the influence of the circuit design on the performance obtained for two classification problems.
We also study the degradation of the obtained circuits in the presence of noise when simulating real quantum computers.
arXiv Detail & Related papers (2024-04-17T11:00:12Z) - Improving Quantum and Classical Decomposition Methods for Vehicle Routing [2.4646794072984477]
We propose an elaborate combination of two decomposition methods, namely graph shrinking and circuit cutting.
Our results offer insights into the performance of algorithms for optimization problems within the constraints of current quantum technology.
arXiv Detail & Related papers (2024-04-08T14:19:25Z) - Qubit efficient quantum algorithms for the vehicle routing problem on
NISQ processors [48.68474702382697]
Vehicle routing problem with time windows (VRPTW) is a common optimization problem faced within the logistics industry.
In this work, we explore the use of a previously-introduced qubit encoding scheme to reduce the number of binary variables.
arXiv Detail & Related papers (2023-06-14T13:44:35Z) - Compiling Quantum Circuits for Dynamically Field-Programmable Neutral Atoms Array Processors [5.012570785656963]
Dynamically field-programmable qubit arrays (DPQA) have emerged as a promising platform for quantum information processing.
In this paper, we consider a DPQA architecture that contains multiple arrays and supports 2D array movements.
We show that our DPQA-based compiled circuits feature reduced scaling overhead compared to a grid fixed architecture.
arXiv Detail & Related papers (2023-06-06T08:13:10Z) - Decomposition of Matrix Product States into Shallow Quantum Circuits [62.5210028594015]
tensor network (TN) algorithms can be mapped to parametrized quantum circuits (PQCs)
We propose a new protocol for approximating TN states using realistic quantum circuits.
Our results reveal one particular protocol, involving sequential growth and optimization of the quantum circuit, to outperform all other methods.
arXiv Detail & Related papers (2022-09-01T17:08:41Z) - Adiabatic Quantum Computing for Multi Object Tracking [170.8716555363907]
Multi-Object Tracking (MOT) is most often approached in the tracking-by-detection paradigm, where object detections are associated through time.
As these optimization problems are often NP-hard, they can only be solved exactly for small instances on current hardware.
We show that our approach is competitive compared with state-of-the-art optimization-based approaches, even when using of-the-shelf integer programming solvers.
arXiv Detail & Related papers (2022-02-17T18:59:20Z) - Fidelity-Guarantee Entanglement Routing in Quantum Networks [64.49733801962198]
Entanglement routing establishes remote entanglement connection between two arbitrary nodes.
We propose purification-enabled entanglement routing designs to provide fidelity guarantee for multiple Source-Destination (SD) pairs in quantum networks.
arXiv Detail & Related papers (2021-11-15T14:07:22Z) - Optimal qubit assignment and routing via integer programming [0.22940141855172028]
We consider the problem of mapping a logical quantum circuit onto a given hardware with limited two-qubit connectivity.
We model this problem as an integer linear program, using a network flow formulation with binary variables.
We consider several cost functions: an approximation of the fidelity of the circuit, its total depth, and a measure of cross-talk.
arXiv Detail & Related papers (2021-06-11T15:02:26Z) - 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.