{
  "annotation_id": "56b57028-d39e-48fb-bd0b-5825069a881e",
  "date_created": "2026-02-17T05:53:24.383000Z",
  "date_modified": "2026-02-17T05:53:24.383000Z",
  "file_hash": "16eba9a30a71b1eab6f2d84a1314ed4235c5a15d9de44f4ada0eb6b523301e1d",
  "private": false,
  "record": {
    "abstract": "We study the input-entropy-constrained Gaussian channel capacity problem in the asymptotic high signal-to-noise ratio (SNR) regime. We show that the capacity-achieving distribution as SNR goes to infinity is given by a discrete Gaussian distribution supported on a scaled integer lattice. Further, we show that the gap between the input entropy and the capacity decreases to zero exponentially in SNR, and characterize this exponent.",
    "arxiv_id": "2601.09864",
    "authors": [
      "Adway Girish",
      "Shlomo Shamai",
      "Emre Telatar"
    ],
    "categories": [
      "cs.IT",
      "math.IT",
      "math.PR"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "title": "High signal-to-noise ratio asymptotics of entropy-constrained Gaussian channel capacity",
    "url": "https://arxiv.org/abs/2601.09864",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "ab456071-d4f5-4142-a01d-1084baad661e",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}