Low-energy states obeying the Marshall sign rule are the likely reason neural-network variational methods fail to reach true ground states of frustrated antiferromagnets.

The paper

The paper's details are OpenAlex's; the citation count is OpenAlex's, 23 Oct 2026. The line on the paper is machine-written, as noted under Why it matters.

Why it matters

Written by Claude (claude-sonnet-5-5) on 23 Oct 2026 from the paper's abstract (as arXiv publishes it) and its OpenAlex record. Machine-written context to help a reader: it is not evidence, it moves no number, and it may be wrong. The quoted sentence is the claim; where it stands is computed from the record. If it misreads the paper, tell the stewards.

The story so far

1. 1

   What the authors did

   They designed a neural network architecture with a simple, explicit and interpretable phase ansatz and used it in variational calculations on lattice models, both conventional and frustrated antiferromagnets.

   Machine-written from the paper's abstract, as noted under Why it matters.

2. 2

   What they found

   • Convolutional networks struggle to converge to ground states with a nontrivial sign structure.
   • The proposed architecture with an explicit phase ansatz represents such states robustly and gives state-of-the-art variational energies for conventional and frustrated antiferromagnets.
   • In the frustrated case it finds low-energy states obeying the Marshall sign rule, which is inconsistent with the expected ground state.

   Machine-written from the paper's abstract, as noted under Why it matters.

3. 3

   What has been checked on Ecdysis

   Exuvia registered it on 23 October 2026. Its credence, the record's estimate that it holds, is 0.55 on a scale from 0 (refuted) to 1 (established): where it started, as every claim from the literature does. Only independent evidence moves it.

What would check it

How sure is the record?

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What would prove it wrong

Refuted if an independent study demonstrates that the obstruction to accessing true ground states in NQS‑based variational Monte Carlo is caused by a mechanism other than the presence of Marshall sign rule low‑energy states, e.g. by showing successful convergence to the true ground state despite such states being present, or by identifying a different source of bias or sampling inefficiency that dominates.

The test as Exuvia registered it on 23 Oct 2026, written from the paper's words. A conceptual claim's test names its refuter in words: it is checked by argument.

The wider literature

Other claims from the same paper

• uncheckedIn the latter case, our approach uncovers low-energy states that exhibit the Marshall sign rule and are therefore inconsistent with the expected ground state.
• uncheckedA neural network with an explicit, interpretable phase ansatz is reported to reach state-of-the-art variational energies for conventional and frustrated antiferromagnets.“We tackle this problem by proposing a neural network architecture with a simple, explicit, and interpretable phase ansatz, which can robustly represent such states and achieve state-of-the-art variat…”

Headlines are machine-written from the paper's abstract, or from the quote and the paper's title where no abstract is open; each claim's own words are quoted beneath its headline.