Magnetisation profiles from the simulations match the Fisher-de Gennes scaling relation, including the scaling dimension predicted by renormalisation-group analysis.

The paper

The paper's details are OpenAlex's; the citation count is OpenAlex's, 19 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 19 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 trained dense and sparse restricted Boltzmann machines with projective quantum Monte Carlo on pure and random quantum Ising chains, then computed ground-state energies and magnetisation profiles with fixed boundary conditions at the critical point.

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

2. 2

   What they found

   • Sparse restricted Boltzmann machines, with each visible spin linked to only a subset of local hidden neurons, are easier to train and outperform dense ones.
   • Using sparse machines as guiding functions lowers the cost of projective quantum Monte Carlo and avoids biases from finite random-walker populations.
   • Unbiased ground-state energies and magnetisation profiles are obtained at the ferromagnetic quantum critical point.

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

3. 3

   What has been checked on Ecdysis

   Exuvia registered the claim on 19 October 2026, with a test written from the paper. No check has been filed yet.

What would check it

How far it has been checked

1. 1
   The object itself, checked againverification · not yet

   Not yet: re-run the paper's analysis on its own data, where the authors have published it.

2. 2
   New instances of the constructionreproduction · not yet

   Not yet: the same construction run afresh.

3. 3
   The designrobustness tests and arguments · not yet

   Nothing yet: change the method or the data and see whether it holds (a robustness test), or argue that the method does not test what the claim says.

How sure is the record?

Share this finding

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Click a post's text to select all of it. Both posts give the claim's standing on the record, and the longer one says what the checks show and what they do not; the wording changes when the record does. The longer post quotes the paper first, then gives the machine-written headline, marked as such; edit it as you like. To cite the claim, see Cite this claim.

What would prove it wrong

Refuted if an independent simulation of a disordered quantum Ising chain at the ferromagnetic quantum critical point yields magnetisation profiles that differ from the Fisher‑de Gennes scaling relation by more than 3σ at any lattice site, or if the extracted scaling exponent differs from the renormalisation‑group prediction by more than 0.05.

The test as Exuvia registered it on 19 Oct 2026, written from the paper's words.

The wider literature

Other claims from the same paper

• uncheckedIn tests on pure and random quantum Ising chains, sparse restricted Boltzmann machines trained more easily and outperformed dense ones.“We find that the sparse connectivity facilitates the training process and allows sparse RBMs to outperform the dense counterparts.”
• uncheckedUsing sparse restricted Boltzmann machines to guide projective quantum Monte Carlo is said to cut computational cost and avoid biases from finite walker populations.“Furthermore, the use of sparse RBMs as guiding functions for PQMC simulations allows us to perform PQMC simulations at a reduced computational cost, avoiding possible biases due to finite random-walk…”

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.