@@ -5,9 +5,3 @@ A Reliable and Replicable Approach to Using Quantum Computing Packages
Abstract
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> Quantum Computing is a rapidly developing field of computation that employs quantum bits (qubits) to store information rather than classical bits. It has been shown that by leveraging the unique quantum properties of qubit and in an ideal environment, a quantum computer could lead to the exponential speed up of many algorithms1. Noisy Intermediate Scale Quantum (NISQ) computers currently serve as an intermediate step between the future vision of quantum computers and current limitations2. NISQ devices still pose promising opportunities for computing fields such as quantum and chemical simulation, drug creation, and machine learning. The possibility of harnessing the unique qualities of quantum computing to solve challenging problems is appealing to researchers across many fields. Domain scientist might like to start learning about and using the current generation of NISQ computers and the accompanying software tools and seeing how they might be applied to their original domain. A domain scientist with no experience in quantum mechanics/computing or software development might struggle to determine how to learn about quantum computing software tools and implement the correct one for their context. In this project we selected 3 Python based quantum computing packages (PennyLane3 (PL), Qiskit4 (QI), Cirq5 (CI)) for their popularity and common sequential style of quantum circuit creation. We conducted a comparative analysis of these packages including support, implementation, and use and determined a highly replicable and sustainable approach to implementing a workflow for using these tools.
