{
  "id": "oai:papers.qnfo.org:computational-simulation-of-geometric-orientation-codes",
  "slug": "computational-simulation-of-geometric-orientation-codes",
  "title": "Computational Simulation of Geometric Orientation Codes",
  "authors": [
    "Rowan Brad Quni-Gudzinas"
  ],
  "abstract": "Fault-tolerant quantum computing requires robust error correction traditionally met using planar topologies that assume noise is perfectly isotropic. However, recent astrophysical measurements suggest the universe possesses fundamental anisotropic properties. This paper challenges the isotropic assumption in quantum error correction by proposing geometric orientation codes. This novel architecture utilizes 3D spatial orientation as the primary redundancy degree of freedom. It explicitly counteracts highly directional noise by aligning physical qubits along distinct spatial axes. To evaluate this paradigm, we executed extensive Python-based Monte Carlo simulations modeling a highly anisotropic quantum noise channel. We compared the logical error suppression capabilities of an N=4 tetrahedral orientation code against a standard d=3 planar surface code. The simulation swept physical error rates from 1e-4 to 1e-1 across anisotropy bias levels ranging from 1:1 to 100:1. At a 100:1 noise bias and a physical error rate of 0.01, the N=4 orientation code achieved a logical error rate of 5.0e-5. [...]",
  "abstract_markdown": "Fault-tolerant quantum computing requires robust error correction traditionally met using planar topologies that assume noise is perfectly isotropic. However, recent astrophysical measurements suggest the universe possesses fundamental anisotropic properties. This paper challenges the isotropic assumption in quantum error correction by proposing geometric orientation codes. This novel architecture utilizes 3D spatial orientation as the primary redundancy degree of freedom. It explicitly counteracts highly directional noise by aligning physical qubits along distinct spatial axes. To evaluate this paradigm, we executed extensive Python-based Monte Carlo simulations modeling a highly anisotropic quantum noise channel. We compared the logical error suppression capabilities of an N=4 tetrahedral orientation code against a standard d=3 planar surface code. The simulation swept physical error rates from 1e-4 to 1e-1 across anisotropy bias levels ranging from 1:1 to 100:1. At a 100:1 noise bias and a physical error rate of 0.01, the N=4 orientation code achieved a logical error rate of 5.0e-5. [...]",
  "date": "2026-04-01",
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    "titles": [
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        "title": "Computational Simulation of Geometric Orientation Codes"
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        "description": "Fault-tolerant quantum computing requires robust error correction traditionally met using planar topologies that assume noise is perfectly isotropic. However, recent astrophysical measurements suggest the universe possesses fundamental anisotropic properties. This paper challenges the isotropic assumption in quantum error correction by proposing geometric orientation codes. This novel architecture utilizes 3D spatial orientation as the primary redundancy degree of freedom. It explicitly counteracts highly directional noise by aligning physical qubits along distinct spatial axes. To evaluate this paradigm, we executed extensive Python-based Monte Carlo simulations modeling a highly anisotropic quantum noise channel. We compared the logical error suppression capabilities of an N=4 tetrahedral orientation code against a standard d=3 planar surface code. The simulation swept physical error rates from 1e-4 to 1e-1 across anisotropy bias levels ranging from 1:1 to 100:1. At a 100:1 noise bias and a physical error rate of 0.01, the N=4 orientation code achieved a logical error rate of 5.0e-5. [...]",
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