Orbit Dynamics¶

The astrojax.orbit_dynamics module provides force models for orbit propagation with perturbation modelling. All functions are JAX-traceable and compatible with jax.jit, jax.vmap, and jax.grad.

Overview¶

Component	Functions	Description
Ephemerides	`sun_position`, `moon_position`	Low-precision analytical Sun/Moon positions
Gravity	`accel_point_mass`, `accel_gravity`	Point-mass gravitational acceleration
Spherical Harmonics	`GravityModel`, `accel_gravity_spherical_harmonics`	Spherical harmonic gravity field
Third body	`accel_third_body_sun`, `accel_third_body_moon`	Sun/Moon gravitational perturbations
Density	`density_harris_priester`, `density_nrlmsise00`	Atmospheric density models (Harris-Priester, NRLMSISE-00)
Drag	`accel_drag`	Atmospheric drag acceleration
SRP	`accel_srp`	Solar radiation pressure acceleration
Eclipse	`eclipse_conical`, `eclipse_cylindrical`	Shadow models for SRP modulation
Polyhedral Gravity	`polyhedral_gravity`, `accel_polyhedral_gravity`	Full gravity field of irregular polyhedral bodies

JAX Compatibility¶

All orbit dynamics functions use JAX primitives and are fully compatible with jax.jit for compilation and jax.grad for automatic differentiation:

import jax
import jax.numpy as jnp
from astrojax.orbit_dynamics import accel_third_body_sun, accel_gravity
from astrojax import Epoch

epc = Epoch(2024, 6, 15, 12, 0, 0)
r = jnp.array([6878e3, 0.0, 0.0])

# JIT-compiled force computation
jit_sun = jax.jit(accel_third_body_sun)
a = jit_sun(epc, r)

# Gradient of acceleration magnitude w.r.t. position
def accel_mag(r):
    return jnp.linalg.norm(accel_gravity(r))

grad_accel = jax.grad(accel_mag)(r)

Float precision

At float32 (default), ephemeris positions are accurate to ~10 m and accelerations to ~1e-6 relative error. For reference-quality comparisons, use set_dtype(jnp.float64) before any JIT compilation.