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March 23, 20260 citationsOpen Access

Designing a Research Data Pipeline for Quantum Computing Experiments

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SSShreyas Sonwane

Key Points

  • The aim is to create a scalable and reproducible data infrastructure for managing quantum computing research data.
  • Designed a research data pipeline integrating various components for storage, retrieval, and analysis
  • Utilized a quantum circuit simulator for managing experimental data
  • Implemented a REST API for efficient data ingestion and accessibility
  • Developed a structured metadata database alongside a statistical analysis module
  • Containerized the platform using Docker for enhanced deployment and validation
  • Successfully established a functional data pipeline that supports quantum computing experiments
  • Demonstrated the platform's ability to streamline data management processes for smaller research groups
  • Validated the system through automated tests ensuring reliability and scalability

Abstract

Quantum computing research generates large volumes of experimental data that require systematic storage, retrieval, and analysis. However, lightweight and accessible infrastructure for managing such data remains underexplored outside of large research institutions. This paper presents the design and implementation of a research data pipeline for quantum computing experiments. The system integrates a quantum circuit simulator, a REST API for data ingestion and retrieval, a structured metadata database, a statistical analysis module, and an automated PDF report generation system. The platform is containerized using Docker and validated through automated tests. The goal is to demonstrate how modern backend engineering tools can be applied to build reproducible and scalable research data infrastructure accessible to individual researchers and small teams.

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Cite This Study

Shreyas Sonwane (2026) studied this question.

synapsesocial.com/papers/69c0e007fddb9876e79c1810https://doi.org/10.5281/zenodo.19151043
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