Design and Optimization of a Low‐Cost 5‐m Radio Telescope at Princess Nourah University (PNU), Saudi Arabia
Bibliographic record
Abstract
Abstract This paper presents the design and optimization of a low‐cost, 5‐m radio telescope developed at Princess Nourah University (PNU), focusing on the 1,420 MHz spectral line of neutral hydrogen (HI) for studying the structure and dynamics of the Milky Way galaxy. The design process integrates key principles of radio telescope engineering, including the optimization of the parabolic dish's geometry, reflectivity, and feed horn design and positioning. Key design outcomes include achieving a sensitivity of and an angular resolution of 2.94° providing our telescope with the ability to detect faint cosmic signals. Additionally, the focal length was optimized at 1.75 m with conical feed horn of circular aperture radius of 81.7 mm providing a directivity of 6.47 dB and an aperture efficiency of 51% achieving semi‐optimal illumination for the designed reflector to minimize the signal loss. The resulting telescope gain of approximately 35 dB supports clear signal capture within the required frequency range. These performance metrics were verified through both simulations and experimental observations, confirming the high performance of our proposed radio telescope design. The advantages of this design include its affordability, replicability, and suitability for educational and research purposes, making it an accessible tool for radio astronomy studies in developing regions. The proposed radio telescope offers a cost‐effective solution for institutions seeking to engage in astronomical research and develop hands‐on learning experiences in antenna design and signal processing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".