{
  "abstract": "Programmable metasurfaces---arrays of elements whose electromagnetic response can be tuned electronically---can process signals as a wave propagates through or reflects off them, a paradigm known as wave-domain analog computing. The design strategy is typically indirect: the surface is fitted to a prescribed linear operator, such as a discrete Fourier transform, and the result is read from output power measurements. Using direction-of-arrival (DoA) estimation as a canonical benchmark, we study what this indirection costs across analog computing topologies, namely reflective reconfigurable intelligent surfaces (RIS), beyond-diagonal RIS (BD-RIS), and stacked intelligent metasurfaces (SIM). We first derive Cramér--Rao bounds for the complete physical estimation chain, including one that accounts for output detectors measuring only intensity. We then formulate a goal-oriented alternative where the surfaces are trained directly through the deployed readout, with no operator target. We observe that goal-oriented training lets sparsely connected or shallower surfaces reach the task performance of their more complex operator-fitted counterparts---despite nearly identical Fisher information---and that the advantage persists under coarsely quantized (1--3 bit) control. From 16 to 64 elements, the depth saving persists, while the connectivity a beyond-diagonal RIS needs grows with the aperture. Under tuner and per-layer loss, the goal-oriented designs keep their advantage.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.06839",
  "author_total": 1,
  "authors": [
    {
      "name": "Mert Kalfa"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6wm2j24gz4qvn.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.06839",
  "fulltext_url": null,
  "id": "6wm2j24gz4qvn",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.06839",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "eess.SP"
    ],
    [
      "arxiv",
      "physics.app-ph"
    ],
    [
      "openalex",
      "2208|Advanced Wireless Communication Technologies"
    ]
  ],
  "openalex": "W7220743039",
  "pdf_url": "https://arxiv.org/pdf/2610.06839",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-05",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/6wm2j24gz4qvn.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:27:05Z",
      "native_id": "2610.06839",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.06839"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:physics.app-ph",
      "subfield": "applied-instrumentation"
    }
  ],
  "title": "Goal-Oriented Wave Computing for Direction-of-Arrival Estimation",
  "title_text": "Goal-Oriented Wave Computing for Direction-of-Arrival Estimation",
  "type": "preprint",
  "updated_at": "2026-10-30T12:27:05Z",
  "url": "https://research.draconitic.com/paper/6wm2j24gz4qvn",
  "venue": "arXiv",
  "versions": []
}