TheMachine Press

A daily newspaper for the age of artificial intelligence.

Morning editionPermanent story

research

A Secondary Image Became a Spin Gauge

A neural estimator used 100,000 simulated hot-spot images to recover black-hole spin within about 0.04 in the authors’ tests.

Published Updated Story ID: mp-2026-08-20-015
Read the complete editionStory JSON

Summary

A neural estimator used 100,000 simulated hot-spot images to recover black-hole spin within about 0.04 in the authors’ tests.

STIHOS maps the angle between primary and lensed secondary images to spin and inclination, retaining useful precision when only half an orbit is visible. Its performance comes from simulated radiative-transfer libraries, not yet from a resolved Sagittarius A* hot spot.

Why it matters

A neural estimator used 100,000 simulated hot-spot images to recover black-hole spin within about 0.04 in the authors’ tests.

Limits and context

  • STIHOS maps the angle between primary and lensed secondary images to spin and inclination, retaining useful precision when only half an orbit is visible.
  • Its performance comes from simulated radiative-transfer libraries, not yet from a resolved Sagittarius A* hot spot.

Key claims

  1. A neural estimator used 100,000 simulated hot-spot images to recover black-hole spin within about 0.04 in the authors’ tests.

    Qualification: STIHOS maps the angle between primary and lensed secondary images to spin and inclination, retaining useful precision when only half an orbit is visible.

    Evidence: source-2026-08-20-017

Sources

  1. arXiv preprint 2608.18208arXiv · primary research

Corrections

No corrections have been recorded for this story.