Distributing Quantum Computations, Shot-Wise

Giuseppe Bisicchia, Giuseppe Clemente, Jose Garcia-Alonso, Juan Manuel Murillo, Massimo D’Elia and Antonio Brogi ()
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Giuseppe Bisicchia: Department of Computer Science, University of Pisa, 56127 Pisa, Italy
Giuseppe Clemente: Dipartimento di Fisica, Istituto Nazionale di Fisica Nucleare (INFN)—Sezione di Pisa, Università di Pisa, 56127 Pisa, Italy
Jose Garcia-Alonso: Quercus Software Engineering Group, University of Extremadura, 10003 Cáceres, Spain
Juan Manuel Murillo: Quercus Software Engineering Group, University of Extremadura, 10003 Cáceres, Spain
Massimo D’Elia: Dipartimento di Fisica, Istituto Nazionale di Fisica Nucleare (INFN)—Sezione di Pisa, Università di Pisa, 56127 Pisa, Italy
Antonio Brogi: Department of Computer Science, University of Pisa, 56127 Pisa, Italy

Future Internet, 2025, vol. 17, issue 11, 1-28

Abstract: NISQ (Noisy Intermediate-Scale Quantum) era constraints, high sensitivity to noise and limited qubit count, impose significant barriers on the usability of QPUs (Quantum Process Units) capabilities. To overcome these challenges, researchers are exploring methods to maximize the utility of existing QPUs despite their limitations. Building upon the idea that the execution of a quantum circuit’s shots does not need to be treated as a singular monolithic unit, we propose a methodological framework, termed shot-wise , which enables the distribution of shots for a single circuit across multiple QPUs. Our framework features customizable policies to adapt to various scenarios. Additionally, it introduces a calibration method to pre-evaluate the accuracy and reliability of each QPU’s output before the actual distribution process and an incremental execution mechanism for dynamically managing the shot allocation and policy updates. Such an approach enables flexible and fine-grained management of the distribution process, taking into account various user-defined constraints and (contrasting) objectives. Demonstration results show that shot-wise distribution consistently and significantly improves the execution performance, with no significant drawbacks and additional qualitative advantages. Overall, the shot-wise methodology improves result stability and often outperforms single QPU runs, offering a robust and flexible approach to managing variability in quantum computing.

Keywords: quantum computing; quantum software engineering; shot-wise distribution (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2025
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