H-R Diagram Stellar Evolution Simulator

🌌Stellar Evolution and H-R Diagram

⚖️H-R Diagram Fundamentals

The Hertzsprung-Russell diagram maps stellar luminosity against effective temperature (or spectral class).

\( \log(L/L_\odot)\ \text{vs}\ \log(T_{\mathrm{eff}}) \)

Main sequence, giants, and white dwarfs occupy distinct regions and encode stellar structure/evolution status.

Radius Relation

\( L = 4\pi R^2 \sigma T_{\mathrm{eff}}^4 \)

At fixed luminosity, hotter stars are smaller; at fixed temperature, larger stars are more luminous.

🔢Stellar Structure and Lifetime Scaling

Mass-Luminosity Approximation

\( L \propto M^{3\text{ to }4} \)

Higher mass stars burn fuel rapidly due to steep luminosity dependence.

Main-Sequence Lifetime

\( t_{\mathrm{MS}} \propto \frac{M}{L} \approx M^{-2.5} \)

Massive stars evolve faster despite larger fuel reservoirs.

Compact Remnant Thresholds

Low/intermediate masses tend toward white dwarfs; higher masses can produce neutron stars/black holes after core collapse pathways.

🧮Astrophysical Diagnostics in Unit 3

Saha Ionization Context

\( \frac{n_{i+1}n_e}{n_i} \propto T^{3/2}e^{-\chi/(kT)} \)

Ionization balance links spectra to atmospheric temperature and electron pressure.

Distance Indicators

Use calibrated relationships (e.g., Wilson-Bappu style trends) with caution regarding scatter and metallicity dependence.

Evolutionary Tracks

Track motion in HR space from protostar through giant phases to compact remnant outcomes.

🪐Formula Sheet and Physical Constants

Use SI units unless stated. Constants and relations shown above are preloaded for lab work.

Switch to the Simulation tab to explore the same relationships numerically under this unit topic.

🔍Unit 3 Guided Scenarios

Mass Track Comparison

Compare low-mass and high-mass tracks on the HR plane and identify divergence points.

Lifetime Contrast

Estimate relative main-sequence lifetimes for 1, 5, and 15 solar-mass stars.

Remnant Outcomes

Map initial mass bins to expected final states and discuss physical uncertainties.

Socratic Reflection

Use the quiz and tutor to justify each phase transition with core-physics arguments.

Presets

Inputs

Mass (M☉)

1.0 M☉

Age (Myr)

0.0 Myr

Metallicity Z

0.0140

Phase mode: auto from mass and age (scientific mode)

Show track Log data

Evolution

Evolution speed (Myr / s)

200.0 Myr/s

Age: 0.0 Myr

Phase: Main Sequence

Star: 1.0 M☉

How data logging works: When the Log data checkbox is enabled in the Simulation tab, the simulator records stellar evolutionary state at configurable intervals. Download the data in standard formats for analysis in Python, MATLAB, or Excel.

0

Recorded rows

0

Stars tracked

0.0

Time span (Myr)

Every 1 step

Sampling interval

⚙️Logging Settings

Sample every N simulation steps

Max rows (memory cap)

💾Download Simulation Data

CSV columns: sapid, student_name, age_myr, phase, log10_teff, log10_lum, teff_k, lum_lsun, radius_rsun, metallicity_z, mass_msun, timestamp_iso. JSON includes full metadata and full evolutionary log. The Python script uses matplotlib to reproduce an H-R track from the exported data.

📋Live Data Preview (last 20 rows)

Age (Myr)	Phase	log10(Teff)	log10(L)	Teff (K)	L/L☉	R/R☉
No data yet — run the simulation with "Log data" checked.

🎯Module: Stellar Evolution

This interactive module targets Unit 3 of PHYS4022P. Students connect H-R diagram structure, stellar lifetimes, and final evolutionary outcomes through computational exploration.

📌Learning Objectives

After completing this module, students will be able to:

✓Interpret H-R diagram axes and major stellar populations.
✓Relate mass, luminosity, and lifetime using approximate scaling laws.
✓Explain transitions from main sequence to giant and remnant phases.
✓Use diagnostic relations to infer stellar parameters from observables.
✓Compare low-mass and high-mass evolutionary pathways.
✓Use LLM prompts for Socratic self-testing on stellar evolution.
✓Export data/figures and present evidence-based evolutionary interpretations.

📦Deliverables

Students are expected to submit:

1.Lab Report (PDF) — Annotated H-R screenshots showing at least three evolutionary stages.
2.Exported Data File — Exported dataset from track exploration with parameter notes.
3.Python analysis script — Python script plotting HR points/tracks and labeled regions.
4.Comparison table — Comparison table of mass bins, lifetimes, and probable remnants.
5.Bonus investigation — Short Socratic transcript summarizing conceptual corrections.

📅Suggested Lab Workflow

Step-by-step guide

1.Review theory blocks and identify the governing scaling laws.
2.Set multiple mass cases and observe HR position changes.
3.Estimate lifetime trends using mass-luminosity relations.
4.Trace transitions toward giant branch and remnant outcomes.
5.Record key diagnostics that support each interpretation.
6.Export run data for at least three mass cases.
7.Reproduce HR trends with a Python plotting workflow.
8.Use AI tutor prompts to challenge and refine your explanations.

📐Assessment Criteria

◈Understanding (30%) — Correct interpretation of HR and stellar-evolution theory.
◈Simulation (25%) — Parameter exploration and methodological rigor.
◈Data Analysis (25%) — Quality of quantitative tables and plotted evidence.
◈Method comparison (15%) — Consistency of physical reasoning across scenarios.
◈Bonus (5%) — Depth of reflective AI-assisted learning.

LMS Note: Submit PDF, exported data, and analysis script under Lab 3 — Stellar Evolution.

🧠Concept Check Quiz

10 questions per round. Pass a round to unlock the next level with a stronger difficulty mix.

No attempts yet.

🎮Level Progress

Level 1/10

Mastery 0%

Questions 0/0

Answer 10 questions to complete a level. Passing scores unlock the next level with harder questions.

📝Quiz Attempt Log

Attempts: 0

📚Bibliography & Further Reading

References used to ensure scientific accuracy of this module. Open-access links are provided where available.

1

Kippenhahn, R., Weigert, A., Weiss, A. — Stellar Structure and Evolution

Springer, 2nd ed. Comprehensive framework for stellar interiors and evolutionary tracks.

↗ Source link

2

Hansen, C. J., Kawaler, S. D., Trimble, V. — Stellar Interiors

Springer, 2004. Core principles of stellar structure, transport, and evolutionary behavior.

↗ Source link

3

Carroll, B. W. & Ostlie, D. A. — An Introduction to Modern Astrophysics

Cambridge University Press. Detailed treatment of H-R diagrams and stellar populations.

4

Salaris, M. & Cassisi, S. — Evolution of Stars and Stellar Populations

Wiley, 2005. Practical interpretation of isochrones and stellar evolution diagnostics.

↗ Source link

5

Gray, D. F. — The Observation and Analysis of Stellar Photospheres

Cambridge University Press, 3rd ed. Links spectra, atmosphere parameters, and stellar classification.

6

Gaia Collaboration (DR3)

High-precision astrometric and photometric catalog widely used for empirical H-R diagrams.

↗ Source link

7

Saha, M. N. (1920) — Ionization in the Solar Chromosphere

Classic reference underlying ionization-balance diagnostics used in stellar atmosphere interpretation.

↗ Source link

🛠Software & Tools Used

▸HTML5 Canvas API — Interactive HR-plane exploration and stellar evolutionary diagnostics.
▸Vanilla JavaScript (ES2020) — Simulation engine and UI logic. No external runtime dependencies.
▸Google Fonts (CDN) — Space Grotesk, IBM Plex Mono (falls back to system fonts offline).
▸Project Leadership — Created and maintained by Dr. Nitesh Kumar, UPES.