# Simultaneous execution of quantum circuits on current and near-future NISQ systems

arXiv: https://arxiv.org/abs/2112.07091 · HTML: https://mlsanity.com/paper/2112.07091/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Dec 2021.

## Built on by (most cited first, 5 of 5)

- [Anomaly Detection for Real-World Cyber-Physical Security using Quantum Hybrid Support Vector Machines](https://mlsanity.com/paper/2409.04935/) (2024)
- [Architectural Vision for Quantum Computing in the Edge-Cloud Continuum](https://mlsanity.com/paper/2305.05238/) (2023)
- [Quantum Hybrid Support Vector Machines for Stress Detection in Older Adults](https://mlsanity.com/paper/2501.04831/) (2025)
- [Computational Performance Bounds Prediction in Quantum Computing with Unstable Noise](https://mlsanity.com/paper/2507.17043/) (2025)
- [Quantum Reinforcement Learning for Cost and Delay Tradeoffs in Quantum Cloud Orchestration](https://mlsanity.com/paper/2609.27446/) (2026)

## Abstract (arXiv)

In the NISQ era, multi-programming of quantum circuits (QC) helps to improve the throughput of quantum computation. Although the crosstalk, which is a major source of noise on NISQ processors, may cause performance degradation of concurrent execution of multiple QCs, its characterization cost grows quadratically in processor size. To address these challenges, we introduce palloq (parallel allocation of QCs) for improving the performance of quantum multi-programming on NISQ processors while paying attention to the combination of QCs in parallel execution and their layout on the quantum processor, and reducing unwanted interference between QCs caused by crosstalk. We also propose a software-based crosstalk detection protocol that efficiently and successfully characterizes the hardware's suitability for multi-programming. We found a trade-off between the success rate and execution time of the multi-programming. This would be attractive not only to quantum computer service but also to users around the world who want to run algorithms of suitable scale on NISQ processors that have recently attracted great attention and are being enthusiastically investigated.