Automated Double-Slit Interference Database for Cross-Disciplinary Insights
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| Title: | Automated Double-Slit Interference Database for Cross-Disciplinary Insights |
|---|---|
| Authors: | Ayebare.B, Gyavira, orcid:0009-0005-5547- |
| Publisher Information: | Zenodo |
| Publication Year: | 2025 |
| Collection: | Zenodo |
| Subject Terms: | Double-slit experiment, interference patterns, wavelength database, optical physics, quantum optics, intersymbol interference, OFDM, machine learning in physics, open science |
| Description: | This proposal outlines the creation of the first automated, parameter-swept database of double-slit interference patterns. While the double-slit experiment has been central to physics since Thomas Young’s 1801 demonstration, most studies remain fragmented—focusing on narrow cases of wavelength, slit separation, or screen distance. The proposed database consolidates this knowledge through automation and systematic variation across: Wavelengths (visible spectrum and extensions into infrared and ultraviolet), Slit separations and widths, and Source-to-screen distances (capturing Fresnel and Fraunhofer regimes). By combining automation, high-resolution imaging, and structured data storage, the project envisions a living, open-access resource that benefits multiple disciplines: Fundamental Physics & Quantum Optics: testing models of coherence, decoherence, and entanglement. Telecommunications & Signal Processing: exploring analogies with Nyquist intersymbol interference (ISI) and OFDM spectrum shaping. Optical Engineering & Metrology: validating interferometry, microscopy, and materials analysis. Education & Outreach: providing a reproducible and interactive digital atlas of interference for students and teachers worldwide. The impact extends beyond physics, offering a benchmark for reproducibility, a platform for machine learning–driven pattern recognition, and a bridge between optical science and communication technologies. The database will be openly licensed and hosted on repositories like Zenodo, inviting community collaboration, extensions, and interdisciplinary applications. |
| Document Type: | text |
| Language: | English |
| Relation: | https://zenodo.org/records/17145139; oai:zenodo.org:17145139; https://doi.org/10.5281/zenodo.17145139 |
| DOI: | 10.5281/zenodo.17145139 |
| Availability: | https://doi.org/10.5281/zenodo.17145139 https://zenodo.org/records/17145139 |
| Rights: | Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode |
| Accession Number: | edsbas.CA4AB5DD |
| Database: | BASE |
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