Skip to content
aiqbench takeQuantum Computing

aiqbench analysis

This research introduces a noise-aware framework to optimize quantum resource allocation by mathematically determining the precise number of shots needed for reliable algorithm execution. By distributing shot budgets across circuit partitions based on error minimization, the approach reduces required executions and energy consumption significantly compared to standard practices. This advancement directly addresses critical efficiency challenges in near-term noisy intermediate-scale quantum (NISQ) device utilization.
Source coveringarXiv
What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

How Many Shots Does It Take? A Noise-Aware Quantum Resource Allocation Framework

arXiv2 min read

arXiv:2607.24704v1 Announce Type: new Abstract: Any algorithm execution on quantum computers requires several repeated and costly executions (known as shots) to obtain reliable results. In this work, we propose a closed-form accurate analytical expression to determine optimal number of shots required for reliable execution of any algorithm on a quantum computer. We also present a theoretically grounded technique to distribute fixed shot budget across different partitions in a quantum circuit minimizing the total error. Our proposed analytical model helps to reduce the shots associated with reliable execution of quantum algorithms by about 58\% compared to current practice, in turn reducing the energy consumption by upto 62\%. Furthermore, our proposed optimal shot allocation technique across different partitions reduces total error by up to 73\% compared to conventional approaches.

Title:How Many Shots Does It Take? A Noise-Aware Quantum Resource Allocation Framework

Abstract:Any algorithm execution on quantum computers requires several repeated and costly executions (known as shots) to obtain reliable results. In this work, we propose a closed-form accurate analytical expression to determine optimal number of shots required for reliable execution of any algorithm on a quantum computer. We also present a theoretically grounded technique to distribute fixed shot budget across different partitions in a quantum circuit minimizing the total error. Our proposed analytical model helps to reduce the shots associated with reliable execution of quantum algorithms by about 58\% compared to current practice, in turn reducing the energy consumption by upto 62\%. Furthermore, our proposed optimal shot allocation technique across different partitions reduces total error by up to 73\% compared to conventional approaches.

Quantum Physics (quant-ph); Emerging Technologies (cs.ET)

arXiv:2607.24704 [quant-ph]

(or arXiv:2607.24704v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2607.24704 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

https://doi.org/10.1145/3816440.3818544 Focus to learn more DOI(s) linking to related resources

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Full text under the publisher's open licence · 241 words

Related coverage