{
  "id": "kmpm19-tuple-unrestricted",
  "categoryId": "svp-quantum-heuristic",
  "paperId": "kirshanova-et-al-2019",
  "date": "2019-09-10",
  "year": 2019,
  "time": {
    "coefficient": 0.29893,
    "expression": "2^{0.29893 n + o(n)}"
  },
  "space": {
    "coefficient": 0.1395,
    "expression": "2^{0.1395 n + o(n)}"
  },
  "tags": [
    "heuristic",
    "QRAM",
    "tuple sieving",
    "memory tradeoff"
  ],
  "review": {
    "status": "source-checked"
  },
  "certificate": {
    "status": "not-provided",
    "lean": null
  },
  "notes": "Quantum approximate k-list search supplies a new low-memory tuple-sieving framework. The representative k=30 point is included without claiming an improvement over the unrestricted quantum pair-sieve record. Heuristic low-memory tuple sieve in the QRAM model. Audit: Correctly classified as sequential time, not parallel depth. Added precision .29893 is not a new milestone.",
  "extra": {
    "model": "Sequential QRAM time; representative tuple size k=30; classical memory 2^{0.1395n+o(n)} and poly(n) qubits",
    "qram": "Coherent access to classical memory; exponent 0.1395",
    "preprocessing": "Included",
    "reference": "Table 2, k=28–30; Algorithms 4.1/4.2",
    "qubits": "2^{o(n)}; see the source’s access model"
  },
  "evidence": {
    "url": "https://elenakirshanova.github.io/Papers/quantum_sieving.pdf",
    "locator": "Abstract; Table 2, k=28–30; Section 4 QRAM model",
    "sourceVersion": "ePrint 2019/1016, 10 September 2019"
  }
}