Student Scholar Symposium Abstracts and Posters

Document Type

Presentation

Publication Date

Fall 12-4-2025

Faculty Advisor(s)

Dr. Andrew Jordan

Abstract

A crucial aspect of validating quantum protocols is understanding the noise produced by quantum computing devices. Using simulations that can replicate this noise allows for a lower-cost alternative to hardware experiments. Stochastic, so-called "trajectory" methods are often used as a quadratically reduced approximation to density matrix simulations, but traditional implementations have limited sampling capacity and provide no error-based metadata. The Pre-Trajectory Sampling with Batched Execution (PTSBE) [Patti et al., 2025] algorithm provides a solution by combining fine-tuned, well-documented noise sampling with computational intermediate caching.

While the original work is effective on quantum error correction circuits, its performance on general circuits has yet to be explored. This project gauges PTSBE on random quantum circuits to understand convergence behavior and accuracy compared to traditional methods. To accomplish this, an automated simulation pipeline was developed by using Apache Airflow and CUDA-Q to generate a collection of noisy circuits, run both exact and approximate simulations, and analyze error criteria across various qubit counts and circuit depths.

Early tests have confirmed the system's ability to scale to 20-qubit circuits and produce accurate comparison data. Our work aims to provide guidance for researchers using PTSBE in noisy simulation environments, expanding its use beyond specific cases.

Comments

Presented at the Fall 2025 Student Scholar Symposium at Chapman University.

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This work is licensed under a Creative Commons Attribution 4.0 License.

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