{
  "abstract": "We map the transport regimes of a wave packet evolving under the one-dimensional discrete nonlinear Schrödinger (Gross-Pitaevskii) equation with a quasiperiodic Aubry-André potential and a static (Stark) field, as a function of self-interaction $g$, field $F$, and quasiperiodic strength $λ$, for two initial states (delta and Gaussian). Instead of one expensive long-time simulation per grid point, we run 3600 short simulations, reduce each to eight dynamical features, and cluster parameter space with a Gaussian mixture model. Clustering finds the boundaries between regimes unsupervised; each cluster's name is then assigned by a hand-calibrated rule, and an ablation shows clustering measurably smooths those boundaries rather than merely relabeling them. The five resulting regimes (ballistic, localized, oscillatory-localized, subdiffusive, and self-trapped) are validated against 100 long runs on a lattice eight times larger than the short sweep, so the validation window is longer than the training window even for the fastest-spreading regime. The short-time clusters predict the long-time asymptotic spreading exponent ($α_\\infty = 2.01\\pm0.07$ ballistic, $0.28\\pm0.16$ subdiffusive, consistent with the weak-chaos prediction $α=1/3$) and, independently, a long-time retention $Π_0=0.72\\pm0.32$ for the self-trapped cluster, whose exponent alone is not diagnostic. The initial-state contrast is striking: the delta state develops a broad self-trapping wedge (onset at $g=3.907\\pm0.017$ at $λ=0$) that invades the ballistic and localized regions as $g$ grows, while the Gaussian state shows no self-trapping, instead opening a subdiffusive corridor along the Aubry-André critical line that widens with $g$. The scheme yields a full $15\\times15$ phase map in minutes per slice, where direct asymptotic simulation ($t\\gtrsim10^6$ per point) is prohibitive.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.10045",
  "author_total": 1,
  "authors": [
    {
      "name": "Marcos Pérez"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/93ppn1dvfc93d.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.10045",
  "fulltext_url": null,
  "id": "93ppn1dvfc93d",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.10045",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cond-mat.quant-gas"
    ],
    [
      "openalex",
      "3109|Nonlinear Photonic Systems"
    ]
  ],
  "openalex": "W7212135249",
  "pdf_url": "https://arxiv.org/pdf/2609.10045",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-11",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/93ppn1dvfc93d.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:21:07Z",
      "native_id": "2609.10045",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.10045"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:cond-mat.quant-gas",
      "subfield": "amo"
    },
    {
      "field": "physics",
      "origin": "arxiv:cond-mat.quant-gas",
      "subfield": "condensed-matter"
    }
  ],
  "title": "A machine-learned dynamical phase diagram of the one-dimensional nonlinear Schrödinger equation with quasiperiodic disorder and a static field",
  "title_text": "A machine-learned dynamical phase diagram of the one-dimensional nonlinear Schrödinger equation with quasiperiodic disorder and a static field",
  "type": "preprint",
  "updated_at": "2026-10-30T12:21:07Z",
  "url": "https://research.draconitic.com/paper/93ppn1dvfc93d",
  "venue": "arXiv",
  "versions": []
}