Anna Rosen, Ph.D.Computational Astrophysicist

Software

Differentiable astrophysics, built as instruments

I build JAX-native scientific software where every step — from a cluster's birth to its survey observables — is a smooth, differentiable function. The pipeline returns not just a prediction, but its exact sensitivity to each physical parameter.

Jaxstro is the spine of that program: a family of packages that each own one scientific stage and remain independently useful. It powers current work on star-cluster identifiability, and it is built to outlast any single project — a foundation for questions I haven't asked yet.

Six panels in two columns. Top row: a simulated g-band image of a crowded cluster, first as an expected source-limited scene and then as a nominal 30-second Rubin-like exposure with sky and noise. Middle row: maps of how much information each pixel carries about the IMF slope. Bottom row: the same for the binary mass-ratio slope. The information maps are concentrated on a sparse subset of stars, and differ between the two parameters.
PreliminaryThis is what differentiable codes buy you. Fisher information per pixel — IMF slope (middle), mass-ratio slope (bottom).fluxax

The Jaxstro Ecosystem

  1. Birth populationsprogenax
  2. Dynamicsgravax
  3. Stellar evolutionstartrax
  4. Observablesfluxax
  5. Inference & designinformax
The Jaxstro ecosystem: a differentiable model from a cluster's birth to its survey observables, returning the gradients that reveal what the data can recover. Every stage composes on the shared jaxstro foundation. Select any stage for detail.

The packages

  1. 00Foundation

    jaxstro

    The shared numerical substrate.

    Units and constants, coordinate transforms, numerical methods, derivative contracts, and provenance — so every package composes without silent inconsistencies.

    MatureMature · methods paper in prep
  2. 01Birth populations

    progenax

    Truth-known cluster birth conditions.

    Differentiable IMFs (including environment-dependent forms), mass-dependent multiplicity, and true-equilibrium King/EFF/LIMEPY structure with anisotropy and primordial mass segregation.

    MatureMature · methods paper in prep
  3. 02Dynamics

    gravax

    Differentiable collisional dynamics.

    A three-tier MSM ⊕ Hermite ⊕ SDAR engine that resolves close encounters exactly while accelerating cluster-wide gravity — mapping how dynamics preserves, transforms, or erases birth structure.

    In developmentIn active development
  4. 03Stellar evolution

    startrax

    From birth mass to stellar state and remnants.

    A differentiable map from (initial mass, age, metallicity) to full stellar state — winds, mass loss, lifetimes, remnants — with a differentiable binary-evolution layer in progress.

    In developmentIn active development
  5. 04Observables

    fluxax

    Physical states → survey observables.

    Differentiable Gaia and Rubin/LSST photometry, astrometry, and images, propagated through selection, crowding, PSFs, backgrounds, and noise.

    Far along
  6. 05Inference & design

    informax

    What the data can actually recover.

    Fisher information geometry and optimal experimental design, simulation-based calibration and coverage, and refusal contracts that decline false precision for unconstrained parameters.

    Far alongFar along · substantively validated

No package is publicly released yet; methods papers come first. The readiness meter is the honest signal — everything here is under active development, and they differ in how far along they are. Each package has its own page with the demos that show it working, and what its methods paper will establish.