Single-minus graviton tree amplitudes are nonzero

Alfredo Guevara, Alexandru Lupsasca, David Skinner, Andrew Strominger, Kevin Weil (on behalf of OpenAI)

The paper derives nonzero single-minus n-graviton tree amplitudes supported on half-collinear configurations in Klein signature or for complexified momenta. A Berends–Giele recursion has a sum-over-trees solution; in a restricted decay chamber it reduces to a product of soft factors. The Ward-identity reconstruction additionally assumes the stated analyticity conditions.

Sources for this record

What was already known

Generic-kinematics vanishing statements and the earlier single-minus gluon result did not supply this gravitational construction. The model was given the gluon paper as context. The later root-cone/cut-test reformulation already in the catalog is a different, subsequent contribution.

AI involvement AI-led

Lupsasca reports that GPT-5.2 Pro was asked to extend the gluon result to gravity and supplied the solution using the directed matrix-tree theorem plus a preliminary paper draft. The primary paper also credits an internal OpenAI model. Humans supplied the gluon context and continued checking and revision; task-only autonomy is not established.

Importance Notable

Supplies explicit amplitudes and recursion/symmetry relations in a specified non-generic gravitational scattering regime.

Limitations

This concerns tree-level amplitudes on restricted kinematics, not generic physical 3+1-dimensional scattering, quantum-loop corrections or experimental confirmation of quantum gravity. Ward reconstruction uses chamber/analyticity assumptions. Later root-cone results retain separate credit.

Technical verification Partial

Alexandru Lupsasca’s research account reports analytical verification of the final formulas and checks against known physical limits. It does not provide a named, complete proof-checking record for every distributional and Ward-identity step; the scoped result is rated Partial.

Human understanding Few

The paper and research account explain the physical setting and name the matrix-tree technique, but no sufficiently specific named human explanation of the central distributional tree construction, separate from the model-produced draft, was established. Few is the documentation default.

Correction and publication history

2026-10-21 · publication

Added the sourced contribution with its stated hypotheses, AI role, prior work and checking limits.

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