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Stellar Spectroscopy Using Diffraction Grating, CMOS Monochrome Sensor and Reflecting Telescopes

This paper presents the design, calibration, and successful testing of a low-cost, 3D-printed stellar spectrometer using a diffraction grating and CMOS sensor, demonstrating that meaningful spectroscopy of stars across spectral types A through M can be achieved with standard educational reflecting telescopes and custom Python data processing.

Original authors: Abhinav Roy, Niti Singh

Published 2026-08-05

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CC BY 4.0

Original authors: Abhinav Roy, Niti Singh

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine the night sky not just as a collection of twinkling lights, but as a cosmic library where every star holds a secret book written in light. For over a century, astronomers have learned to read these books using a technique called spectroscopy. Think of starlight like a beam of white light passing through a prism; it doesn't just stay white but splits into a rainbow of colors. However, this isn't a perfect, smooth rainbow. It's more like a barcode, with dark gaps and lines where specific elements in the star's atmosphere have "eaten" certain colors of light. By studying these missing colors, scientists can tell us what a star is made of, how hot it is, and even how it is moving. While professional observatories use massive, million-dollar machines to read these cosmic barcodes with extreme precision, a big question has remained: Can regular people, using simpler tools, still read the story written in the stars?

This paper tells the story of a team of students and researchers who decided to build their own "star-reader" to find out. They didn't use a supercomputer or a space telescope; instead, they built a compact spectrometer using a 3D-printed mount, a standard camera sensor, and a diffraction grating (a special piece of plastic with thousands of tiny lines that acts like a prism) attached to a reflecting telescope. Their goal was to see if this low-cost, homemade setup could capture the unique "barcodes" of different types of stars, from hot blue ones to cool red giants.

The team successfully pointed their custom-built device at five famous stars: Vega, Sirius, Procyon, Capella, and Betelgeuse. They managed to record clear spectra for all of them, covering a wide range of stellar types. The results were impressive: the hot stars (like Vega and Sirius) showed strong hydrogen lines, the medium-temperature stars (like Procyon and Capella) displayed a mix of metal lines, and the cool, giant star (Betelgeuse) revealed bands of molecules like titanium oxide. The data matched well with what professional space telescopes have seen, proving that meaningful stellar spectroscopy is possible without a massive budget.

However, the paper is also very honest about the limits of their "toy" telescope. Because they didn't have a way to perfectly subtract the glow of Earth's atmosphere (which adds its own "noise" to the picture), some of the lines in their data were actually caused by our own air, not the stars. Also, because their camera sensor is small and the telescope isn't a giant professional one, the images of very bright stars got a bit "saturated" or washed out, making it hard to see fine details in the blue part of the spectrum. For instance, they couldn't perfectly measure the strength of a specific hydrogen line in Sirius because the star was just too bright for their sensor.

Despite these hiccups, the project demonstrates that you don't need a billion-dollar observatory to do real science. By using a clever Python program to clean up the data and stack many images together, they turned a simple camera and a 3D-printed part into a tool that can teach us about the life cycles of stars. It's a proof that with a little creativity and the right tools, anyone can start reading the cosmic library, one star at a time.

Technical Summary: Stellar Spectroscopy Using Diffraction Grating, CMOS Monochrome Sensor and Reflecting Telescopes

Problem Statement
High-resolution stellar spectroscopy is a cornerstone of modern astrophysics, yet it typically relies on expensive, complex instrumentation (e.g., cross-dispersed echelle spectrographs) found only at major professional observatories. While amateur and educational institutions often possess reflecting telescopes, they frequently lack the specialized, low-cost modules required to convert these telescopes into functional spectrographs. The challenge addressed by this work is to design, construct, and validate a compact, low-cost spectrometer module that can be integrated with existing institutional telescope infrastructure to enable meaningful stellar spectroscopy for undergraduate education and outreach, without requiring the capital investment of professional-grade equipment.

Methodology
The authors developed a custom spectrometer module comprising three primary components:

Optical Dispersion: A 600 lines/mm transmission diffraction grating operating in the first order ( $n=1$ ).
Detection: A Skyris 236M CMOS monochrome sensor (5.44 mm $\times$ 3.67 mm active area).
Mechanical Interface: A custom 3D-printed mount (fabricated via Fused Deposition Modeling using PLA) designed to attach to standard 1.25-inch telescope eyepiece adapters.

The system was coupled with two reflecting telescopes available at the National Institute of Science Education and Research (NISER): an 8-inch f/4 and an 11-inch f/11 Schmidt-Cassegrain telescope. To address the issue of broadened spectral lines caused by atmospheric seeing and telescope optics, an adjustable precision-blade entrance slit (1.0–1.5 mm) was implemented.

Data Reduction and Calibration
A custom Python-based pipeline was developed for data processing, including:

Preprocessing: Dark frame subtraction to remove thermal noise. Notably, sky subtraction was omitted due to educational constraints, a limitation explicitly acknowledged in the analysis.
Wavelength Calibration: Performed using a helium emission lamp in the laboratory. A quadratic polynomial fit was derived to map pixel columns to wavelengths, accounting for minor optical misalignments and asymmetric pixel-to-angle projections.
Flux Calibration: Vega (A0V) was used as a spectrophotometric standard to correct for instrument sensitivity, utilizing HST CALSPEC reference data.
Alignment and Stacking: Sequential exposures were aligned using $\chi^2$ minimization on spectral markers (H- $\alpha$ and H- $\beta$ ) to correct for tracking errors and atmospheric seeing. Spectra were binned into 1 Å intervals and stacked to improve the signal-to-noise ratio (SNR).

Key Results
The system successfully recorded and calibrated spectra for five bright stars spanning spectral types A through M:

A-Type (Vega, Sirius): Showed strong hydrogen Balmer absorption lines (H- $\alpha$ , H- $\beta$ , H- $\gamma$ ). Comparison with HST reference data showed good agreement in major features, though the H- $\beta$ line in Sirius was severely underestimated due to sensor saturation in the blue-green continuum.
F-Type (Procyon): Displayed weakening hydrogen lines and the emergence of metallic absorption lines, including Ca-II H & K and Fe-I features.
G-Type (Capella): Characterized by dominant metallic lines (Fe I, Fe II, Ca I) and further weakened hydrogen features. The spectrum represents a flux-weighted composite of the unresolved binary components.
M-Type (Betelgeuse): Exhibited the coolest spectrum with weak hydrogen lines, prominent Na I doublet (in emission/partial absorption), and broad molecular absorption bands consistent with Titanium Oxide (TiO).

The instrument achieved a wavelength-dependent resolving power ( $R = \lambda/\Delta\lambda$ ) ranging from approximately $R \approx 16$ in the blue (447 nm) to $R \approx 142$ in the red (706 nm). The wavelength calibration accuracy was determined to be $\pm 2\text{--}3$ nm.

Limitations and Systematic Effects
The authors explicitly identify several constraints inherent to the setup:

Telluric Contamination: Due to the lack of sky subtraction, atmospheric absorption features (e.g., H $_2$ O, O $_2$ , O-I/II) appear in the spectra and were distinguished from intrinsic stellar features using the HITRAN2020 database.
Sensor Saturation: Extremely bright targets like Sirius caused saturation in the blue-green region, suppressing line contrast and leading to systematic underestimation of equivalent widths for lines in that region.
Resolution: The low resolving power results in the blending of narrow spectral lines, particularly in the blue region, though broad continuum trends and molecular bands remain preserved.
Flux Units: Spectra are presented in procedure-defined units (p.d.u.) normalized to continuum peaks, as absolute flux calibration is not reliable across different observing conditions without sky subtraction.

Significance and Claims
The paper claims that meaningful stellar spectroscopy covering spectral types A through M can be achieved using a modest-cost spectrometer module integrated with existing institutional telescopes. The work demonstrates that:

Accessibility: Educational institutions can perform hands-on stellar spectroscopy without specialized, high-cost instrumentation, provided they have access to suitable telescopes.
Pedagogical Value: The project offers a practical framework for undergraduate students to engage in wavelength calibration, spectral classification, uncertainty estimation, and Python-based data reduction.
Scientific Validity: Despite lower resolution and the absence of sky subtraction, the calibrated spectra of Vega and Sirius show excellent correspondence with HST reference data for major absorption features, validating the calibration methodology and data reduction pipeline.

The authors conclude that while the instrument cannot perform high-precision radial velocity measurements or resolve fine spectral structures, it successfully captures the essence of stellar physics (temperature, composition, and evolutionary stage) suitable for educational and introductory research applications.

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