Cosmic Dawn 21-cm Dark Matter Scattering Forecasts

ISEF Category: Physics and Astronomy

Subcategory: Astronomy and Cosmology  ·  Difficulty: Advanced  ·  Setup: University Lab  ·  Time: Full Year

The Hook

The first stars left a faint radio fingerprint on the Universe. Tiny changes in that signal can hint at how dark matter and ordinary matter pulled on each other before galaxies formed. You can test that idea with public cosmology codes and a careful forecasting plan. This project turns early-Universe theory into a measurable prediction.

What Is It?

The cosmic dawn 21-cm signal comes from neutral hydrogen. That gas can absorb or emit radio waves at a wavelength of 21 centimeters. During the first few hundred million years after the Big Bang, that line can shift because the gas temperature, density, and radiation field all changed fast.

Dark matter normally acts like invisible mass that only feels gravity. Some models add a small amount of scattering between dark matter and baryons, which are the particles in normal matter, like protons and electrons. That extra drag can cool the gas more than standard cosmology predicts. If the gas cools more, the 21-cm absorption trough can get deeper or move in time.

Think of it like stirring soup with and without a second spoon in the pot. The two spoons change how fast the soup spreads heat. In this project, you model how much the early Universe signal changes when dark matter and baryons exchange momentum. Then you ask whether a real telescope, like HERA, could still detect that change after foreground contamination and noise.

Why This Is a Good Topic

This is a strong science fair topic because you can turn a big cosmology idea into a clear measurable output, the depth or timing of the 21-cm absorption feature. You can compare a standard model against one with dark matter-baryon scattering, then test how sensitive the result is to model choices and foreground residuals. The real-world link is direct, because the project touches one of the best ways to probe dark matter physics with upcoming radio surveys. You can learn how cosmology codes, parameter sweeps, and forecast logic work without needing a physical lab.

Research Questions

• How does increasing the dark matter-baryon scattering cross section change the depth of the cosmic dawn 21-cm absorption trough?
• What is the effect of varying the dark matter particle mass on the predicted 21-cm global signal?
• Does adding realistic foreground residuals weaken HERA's ability to distinguish scattering models from the standard cosmology?
• To what extent do changes in the baryon temperature history shift the redshift of the minimum 21-cm brightness temperature?
• Which model parameters produce signal changes that remain detectable after adding instrumental noise and foreground subtraction errors?
• How does the predicted 21-cm power spectrum differ between weak-scattering and no-scattering cases at cosmic dawn?

Basic Materials

• Laptop or desktop computer with at least 8 GB RAM.
• Google Colab account with access to Python notebooks.
• CAMB, a public cosmology code for matter power spectra and background evolution.
• CLASS, a public cosmology code for comparison runs and parameter checks.
• 21cmFAST, a semi-numerical code for fast 21-cm signal modeling.
• Spreadsheet software for tracking parameter sets and outputs.
• Internet access for downloading public code and papers.
• External storage or cloud drive for saving large output files.

Advanced Materials

• University or shared workstation with 16 GB RAM or more.
• Python environment with NumPy, SciPy, Matplotlib, and pandas.
• CAMB source build for custom parameter exploration.
• CLASS source build for cross-checking cosmological assumptions.
• 21cmFAST with compiled extensions for larger parameter sweeps.
• Noise and foreground residual model files from published HERA forecast papers.
• High-storage drive for simulation grids and figure outputs.
• Version control software such as Git for reproducible analysis.

Software & Tools

• Google Colab: Runs Python notebooks in the browser and handles small simulation grids.
• Python: Processes model outputs, makes plots, and automates parameter sweeps.
• Matplotlib: Creates figures for the global signal and forecast bands.
• SciPy: Fits curves, computes summary statistics, and helps compare models.
• ImageJ: Not needed here, so skip it unless you also analyze lab images for a side project.

Experiment Steps

1. Define the exact signal metric you will study, such as trough depth, trough timing, or a power spectrum feature.
2. Choose a small set of dark matter-baryon scattering parameters and one standard no-scattering baseline.
3. Run CAMB or CLASS to generate the cosmology inputs that feed the 21-cm model.
4. Build a parameter grid in 21cmFAST and decide which outputs you will compare across models.
5. Add a simple HERA forecast layer with foreground residuals and instrument noise from public literature.
6. Plan the statistical test you will use to decide whether two models are distinguishable.

Common Pitfalls

• Mixing cosmology parameters between CAMB, CLASS, and 21cmFAST, which makes model differences hard to interpret.
• Using too many scattering values at once, which blurs the trend and wastes run time.
• Treating the global signal and the power spectrum as the same output, which leads to confused conclusions.
• Ignoring foreground residuals, which can make a model look detectable when the telescope would not recover it.
• Comparing raw simulation curves without a fixed metric, which makes your results hard to defend.

What Makes This Competitive

A strong version of this project does more than plot a few curves. You would define a clean detection metric, compare multiple scattering strengths, and test whether the signal survives realistic noise and foreground residuals. You could also compare the global signal against the power spectrum, since each one may respond differently to the same physics. That kind of careful forecasting and model testing makes the project feel like real research, not just code output.

Project Variations

• Focus on the global 21-cm absorption trough instead of the full power spectrum.
• Compare dark matter-baryon scattering against another early-Universe heating or cooling mechanism.
• Use a public HERA forecast dataset and test how changing the foreground residual model shifts detectability.

Learn More

• NASA ADS: Search for review papers on 21-cm cosmology, dark matter-baryon scattering, and cosmic dawn forecasts.
• arXiv: Search for preprints on 21-cm global signal modeling and HERA sensitivity forecasts.
• CAMB documentation: Read the public code guide and parameter notes on the CAMB project page.
• CLASS documentation: Use the official code manual and example input files from the CLASS project page.
• 21cmFAST documentation: Find the public user guide and example notebooks on the 21cmFAST project page.
• PubMed: Not a main source for this topic, but useful if you want background on instrumentation methods and signal analysis papers linked from reviews.