About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
DAC 2023
Poster
CuKnit: Optimized Partitioning of Quantum Circuits using Knitting and Cutting
Abstract
The limited number of qubits is a major challenge for effective near-term quantum computations. Prior art proposed partitioning a quantum computation into a set of sub-circuits using a lower number of qubits than the original computation. These partitioning techniques resolve dependencies within a quantum computation, given either by a qubit-wire or an n-qubit gate, by executing exponential numbers of sub-circuits and classical post-processing. In this work we address the partitioning of quantum circuits by resolving qubit-wire dependencies using circuit knitting and by developing a formal model that allows optimal selection of gate and qubit-wire cuts for dependency resolution.