Zenith is an engineering-focused astronomy toolkit designed for SH1003 Introductory Astronomy for Engineers. Unlike standard astronomy libraries that focus on catalog queries, Zenith emphasizes the instrumentation and physics required to design observation campaigns.

It provides a "first-principles" implementation of celestial mechanics, telescope optics, and signal processing, allowing engineers to simulate the performance of ground-based observatories.

This project implements the maximal syllabus, focusing on the mathematical models behind the physical concepts:

git clone https://github.com/dhruvhaldar/zenith.git
cd zenith
pip install -r requirements.txt

Calculates the integration time required to achieve a specific Signal-to-Noise Ratio for a given magnitude, considering read noise, dark current, and sky background.

Code:

from zenith.optics import Telescope, CCD

# Define an 8-inch amateur telescope
scope = Telescope(aperture=0.203, focal_length=2.0)
camera = CCD(pixel_size=3.76e-6, read_noise=1.5, dark_current=0.01)

# Calculate SNR for a Mag 12 star with 60s exposure
snr = scope.calculate_snr(target_mag=12, exposure=60, ccd=camera)
print(f"SNR: {snr:.2f}")

# Plot SNR vs Exposure Time
scope.plot_performance_curve(mag_range=[10, 15], ccd=camera)

Artifact Output:

Figure 1: Performance curve for an 8" SCT Telescope. The plot demonstrates the non-linear relationship between exposure time and SNR, helping engineers optimize observing schedules for fainter targets.

Simulates the dip in brightness (light curve) caused by a planet transiting a host star.

Code:

from zenith.exoplanets import TransitSimulator

# Simulate a "Hot Jupiter" around a Sun-like star
sim = TransitSimulator(R_star_solar=1.0, R_planet_earth=11.2, period_days=4)
flux, time = sim.generate_light_curve(duration_hours=6)

sim.plot_light_curve()

Artifact Output:

Figure 2: Simulated light curve. The depth of the dip ($\delta \approx (R_p/R_)^2$) allows for the determination of planetary radius, a key learning outcome of the Planetary Astrophysics module.*

Determines if a target is visible from a specific location (e.g., KTH Campus) on a given night.

Artifact Output:

Figure 3: Altitude vs. Time plot for Sirius viewed from Stockholm. The horizontal line represents the horizon (0 deg) and the airmass limit (30 deg). The plot verifies coordinate transformation algorithms.

Located in tests/unit/. These validate fundamental physical constants and formulas.

Example: tests/unit/test_cosmology.py

def test_hubble_law():
    """Verifies recession velocity calculation v = H0 * d"""
    from zenith.cosmology import recession_velocity
    # For d = 10 Mpc and H0 = 70 km/s/Mpc
    v = recession_velocity(d_mpc=10, H0=70)
    assert abs(v - 700.0) < 1e-5

Located in tests/e2e/. These simulate complex engineering workflows.

Example: tests/e2e/test_observation.py

def test_observation_feasibility():
    """
    E2E Test: Can we observe the Andromeda Galaxy tonight?
    Checks:
    1. Is it above horizon?
    2. Is the resolution sufficient?
    """
    stockholm = Observer(lat=59.3293, lon=18.0686) # Concept only
    # See actual implementation in tests/e2e/test_observation.py

This project is Vercel-deployable. The API provides endpoints for simulation:

• /api/snr: Calculate Signal-to-Noise Ratio.
• /api/transit: Simulate Exoplanet Transit.
• /api/hubble: Calculate Recession Velocity.

Visit the live demo or run locally with python api/index.py.

MIT License

Copyright (c) 2026 Jules