Two things, one verified and one that cannot be.
The render budget is now the whole catalogue: 68388 stars, one instanced
draw call, which is what a GPU should be asked to do. The budget itself
stays, because the catalogue is meant to grow past what any machine should
draw at once — Gaia alone could contribute a million — and at that point
the selection is what keeps the field legible rather than a grey wash. A
`?stars=` override handles the machines that cannot, including the
software rasterizer the end-to-end suite runs against, whose frame rate is
two orders of magnitude below a real GPU's and which was measuring the
rasterizer rather than the app.
The aggregation is the second thing, and none of it has run. Every ESA,
NOIRLab, SDSS and Euclid endpoint is unreachable from here — only GitHub
raw is, which is why HYG and OpenNGC are the current sources. So this is
infrastructure and a Gaia query written against the published DR3 schema,
not data.
What the framework encodes is that these surveys are not interchangeable.
The distinction is not size but whether a catalogue knows how far away its
objects are, because a 3D map cannot place a star it only has a direction
for. Gaia is the only one of the five that can add stars here, because it
is the only one that measures parallaxes. DECaPS2 has fifty times Gaia's
object count and photometry alone — not one of its 3.32 billion objects
can be placed in depth. Euclid's bulge is 8 kpc away, where a parallax is
microarcseconds; its contribution would be imagery. SDSS-V and SAGA are
keyed to stars something else already places, so they enrich rather than
extend. Those roles are recorded as data the ETL prints, not as prose that
can drift.
Overlapping catalogues are reconciled on direction rather than on 3D
proximity, which is the one non-obvious part. Two surveys agree on a
star's direction to within an arcsecond and disagree on its distance by
tens of per cent, so a star at 200 pc is 50 pc from itself between
catalogues while being unmistakably the same object. Matching in 3D would
need a tolerance so loose it swallowed real neighbours. The better
parallax wins where both reach; where only one does, the star stays.
Names become dense-with-holes with a source dictionary, because a survey
catalogue has no proper names — writing "Gaia DR3 4472832130942575872"
once per star would cost 25 MB per million to repeat what two adjacent
fields already say. An empty entry costs three bytes and is regenerated on
load. The Sun needed its own case in the merge: it sits at the origin, has
no direction to compare, and appears in every catalogue.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WaySiNst4HhDXBHnMy8p5G
Fifteen bodies here have a real photograph. Every exoplanet does not, and
never will on current instruments — none has ever been imaged — and nor do
several of the solar system's own moons. Those all shared one crude
stand-in: a few noisy bands tinted by category, cached per colour, so
every exoplanet in the app was literally the same picture.
They now get a surface reasoned from what has actually been measured.
The chain is standard at every link. A host star's luminosity comes from
its catalogued apparent magnitude and its parallax distance — that pair is
exactly an absolute magnitude — plus a bolometric correction for its
spectral class. The correction is not optional: an M dwarf radiates most
of its light in the infrared, so its visual magnitude understates it more
than tenfold, and M dwarfs are what most nearby planet hosts are.
Luminosity and the semi-major axis then give an equilibrium temperature,
mass and radius give a bulk density, and size, temperature and density
together give a class of world.
Checked against the solar system the temperatures land on Earth 255 K,
Jupiter 112 K, Neptune 46 K, all within a kelvin or two of published
values, and 51 Pegasi b comes out at 1227 K against a published 1200.
Each class carries a palette reasoned from its chemistry — methane absorbs
red light, which is why the ice giants are blue — and a structure: zonal
bands for a body with a fluid envelope, because a rapidly rotating
atmosphere organises into them, and fractal terrain for one with a solid
surface. Polar caps grow and shrink with the derived temperature, which is
the clearest visible consequence of the whole chain.
The generator samples three-dimensional noise along the sphere rather than
a flat field, so there is no seam to stitch at the antimeridian and no
pinching at the poles, and it writes into a byte array rather than a
canvas — a pure function, testable, with no 2D context to be unavailable.
Two things the derivation cannot do, both stated on screen next to the
measurements it rests on. Equilibrium temperature ignores greenhouse
warming and internal heat, so Venus comes out at 300 K against a real
surface of 737 K and Io, kept molten by tides, classifies as ice. And
these are illustrations: reasoned, but not observations.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WaySiNst4HhDXBHnMy8p5G
Add star-map Angular app, ETL pipeline, and caveman plugin
Angular 3D star map (galaxy/system/body views, Three.js rendering,
navigation store) plus the NASA ETL tooling that builds the star,
exoplanet and solar-system datasets, Playwright e2e suite, and the
cs:caveman Claude Code plugin (command, agent, skill).
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
@
Claude
Senrokai