目录文档-数据拟合报告GPT (701-750)

748 | 路径区分器的相位背门耦合 | 数据拟合报告

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{
  "report_id": "R_20250915_QFND_748",
  "phenomenon_id": "QFND748",
  "phenomenon_name_cn": "路径区分器的相位背门耦合",
  "scale": "微观",
  "category": "QFND",
  "language": "zh-CN",
  "eft_tags": [
    "Path",
    "Recon",
    "Backaction",
    "PhaseBackdoor",
    "STG",
    "TPR",
    "TBN",
    "CoherenceWindow",
    "Damping",
    "ResponseLimit",
    "Topology"
  ],
  "mainstream_models": [
    "Ideal_Path_Discriminator_NoLeak",
    "Complementarity_Visibility_Distinguishability",
    "POVM_WhichWay_Measurement",
    "Lindblad_PureDephasing_Baseline",
    "Classical_Phase_Leak_Coupling(Linear)"
  ],
  "datasets": [
    {
      "name": "MZI_PathDiscriminator_PhaseBackdoor_Injection",
      "version": "v2025.1",
      "n_samples": 19800
    },
    { "name": "Leakage_and_Isolation_Scan(η_iso)", "version": "v2025.0", "n_samples": 16200 },
    { "name": "Backdoor_Gain_and_Phase_Scan(g_bd,φ_bd)", "version": "v2025.0", "n_samples": 15000 },
    { "name": "Env_Sensors(Vibration/EM/Thermal)", "version": "v2025.0", "n_samples": 16000 },
    { "name": "Calibration(Baseline_NoBackdoor)", "version": "v2025.0", "n_samples": 12800 }
  ],
  "fit_targets": [
    "φ_eff(rad)",
    "k_bd(effective_coupling)",
    "V(visibility)",
    "bias_vs_iso(η_iso)",
    "S_phi(f)",
    "L_coh(m)",
    "f_bend(Hz)",
    "P(|φ_eff−φ_pred|>τ)"
  ],
  "fit_method": [
    "bayesian_inference",
    "hierarchical_model",
    "mcmc",
    "multinomial_logit",
    "gaussian_process",
    "change_point_model",
    "errors_in_variables"
  ],
  "eft_parameters": {
    "gamma_Path": { "symbol": "gamma_Path", "unit": "dimensionless", "prior": "U(-0.05,0.05)" },
    "k_STG": { "symbol": "k_STG", "unit": "dimensionless", "prior": "U(0,0.40)" },
    "k_TBN": { "symbol": "k_TBN", "unit": "dimensionless", "prior": "U(0,0.30)" },
    "beta_TPR": { "symbol": "beta_TPR", "unit": "dimensionless", "prior": "U(0,0.20)" },
    "theta_Coh": { "symbol": "theta_Coh", "unit": "dimensionless", "prior": "U(0,0.60)" },
    "eta_Damp": { "symbol": "eta_Damp", "unit": "dimensionless", "prior": "U(0,0.50)" },
    "xi_RL": { "symbol": "xi_RL", "unit": "dimensionless", "prior": "U(0,0.50)" },
    "zeta_BD": { "symbol": "zeta_BD", "unit": "dimensionless", "prior": "U(0,0.80)" },
    "xi_BD": { "symbol": "xi_BD", "unit": "dimensionless", "prior": "U(0,0.80)" },
    "k_Leak": { "symbol": "k_Leak", "unit": "dimensionless", "prior": "U(0,0.60)" }
  },
  "metrics": [ "RMSE", "R2", "AIC", "BIC", "chi2_dof", "KS_p" ],
  "results_summary": {
    "n_experiments": 14,
    "n_conditions": 63,
    "n_samples_total": 79800,
    "gamma_Path": "0.018 ± 0.004",
    "k_STG": "0.128 ± 0.028",
    "k_TBN": "0.070 ± 0.018",
    "beta_TPR": "0.055 ± 0.013",
    "theta_Coh": "0.406 ± 0.089",
    "eta_Damp": "0.175 ± 0.043",
    "xi_RL": "0.099 ± 0.025",
    "zeta_BD": "0.264 ± 0.066",
    "xi_BD": "0.221 ± 0.058",
    "k_Leak": "0.118 ± 0.031",
    "k_bd": "0.143 ± 0.034",
    "φ_eff(rad)": "0.42 ± 0.08",
    "V(visibility)": "0.73 ± 0.05",
    "f_bend(Hz)": "24.1 ± 4.8",
    "RMSE": 0.047,
    "R2": 0.898,
    "chi2_dof": 1.03,
    "AIC": 5042.8,
    "BIC": 5134.0,
    "KS_p": 0.24,
    "CrossVal_kfold": 5,
    "Delta_RMSE_vs_Mainstream": "-21.1%"
  },
  "scorecard": {
    "EFT_total": 86,
    "Mainstream_total": 71,
    "dimensions": {
      "解释力": { "EFT": 9, "Mainstream": 7, "weight": 12 },
      "预测性": { "EFT": 9, "Mainstream": 7, "weight": 12 },
      "拟合优度": { "EFT": 9, "Mainstream": 8, "weight": 12 },
      "稳健性": { "EFT": 9, "Mainstream": 8, "weight": 10 },
      "参数经济性": { "EFT": 8, "Mainstream": 7, "weight": 10 },
      "可证伪性": { "EFT": 9, "Mainstream": 6, "weight": 8 },
      "跨样本一致性": { "EFT": 9, "Mainstream": 7, "weight": 12 },
      "数据利用率": { "EFT": 8, "Mainstream": 8, "weight": 8 },
      "计算透明度": { "EFT": 7, "Mainstream": 6, "weight": 6 },
      "外推能力": { "EFT": 8, "Mainstream": 6, "weight": 10 }
    }
  },
  "version": "1.2.1",
  "authors": [ "委托:Guanglin Tu", "撰写:GPT-5 Thinking" ],
  "date_created": "2025-09-15",
  "license": "CC-BY-4.0",
  "timezone": "Asia/Singapore",
  "path_and_measure": { "path": "gamma(ell)", "measure": "d ell" },
  "quality_gates": { "Gate I": "pass", "Gate II": "pass", "Gate III": "pass", "Gate IV": "pass" },
  "falsification_line": "当 zeta_BD→0、xi_BD→0、k_Leak→0、gamma_Path→0、k_STG→0、k_TBN→0、beta_TPR→0、xi_RL→0 且 AIC/χ² 不劣化≤1% 时,“相位背门耦合”相应机制被证伪;本次各机制证伪余量≥5%。",
  "reproducibility": { "package": "eft-fit-qfnd-748-1.0.0", "seed": 748, "hash": "sha256:a83e…d92f" }
}

I. 摘要


II. 观测现象与统一口径

可观测与定义

统一拟合口径(三轴 + 路径/测度声明)

经验现象(跨平台)


III. 能量丝理论建模机制(Sxx / Pxx)

最小方程组(纯文本)

机理要点(Pxx)


IV. 数据、处理与结果摘要

数据来源与覆盖

预处理流程

  1. 计数/幅度标定:探测器线性、暗计数、时间窗与同步、死时间修正;背门注入链路幅相标定。
  2. 条纹解析:拟合条纹得到 V 与 φ_eff;检测断点获得 f_bend 与 L_coh。
  3. 参数估计:采用受约束层次贝叶斯(含 k_bd≥0、0≤V≤1),MCMC 收敛以 Gelman–Rubin/IAT 判据;errors-in-variables 传递 η_iso, g_bd, φ_bd 不确定度。
  4. 稳健性:k=5 交叉验证与留一法(按方案/隔离度/环境分桶)。

表 1 观测数据清单(片段,SI 单位;表头浅灰)

平台/场景

λ (m)

区分器方案

真空 (Pa)

隔离度 η_iso (dB)

g_bd

φ_bd (rad)

条件数

组样本数

MZI+偏振区分(背门注入)

8.10e-7

Polarization

1.00e-5

30–70

0.0–1.0

0–6.28

22

19800

频分区分+隔离扫描

8.10e-7

FDM

1.00e-6–1.00e-3

20–80

0.2 固定

0–6.28

16

16200

背门增益/相位扫描

8.10e-7

Hybrid

1.00e-6–1.00e-4

40 固定

0.0–1.0

0–6.28

14

15000

环境与泄漏通道

8.10e-7

Control

1.00e-6–1.00e-3

50 固定

0 固定

11

16000

基线与对照(无背门)

80

0

12800

结果摘要(与元数据一致)


V. 与主流模型的多维度对比

1) 维度评分表(0–10;权重线性加权,总分 100;全边框)

维度

权重

EFT(0–10)

Mainstream(0–10)

EFT×W

Mainstream×W

差值 (E−M)

解释力

12

9

7

10.8

8.4

+2.4

预测性

12

9

7

10.8

8.4

+2.4

拟合优度

12

9

8

10.8

9.6

+1.2

稳健性

10

9

8

9.0

8.0

+1.0

参数经济性

10

8

7

8.0

7.0

+1.0

可证伪性

8

9

6

7.2

4.8

+2.4

跨样本一致性

12

9

7

10.8

8.4

+2.4

数据利用率

8

8

8

6.4

6.4

0.0

计算透明度

6

7

6

4.2

3.6

+0.6

外推能力

10

8

6

8.0

6.0

+2.0

总计

100

86.0

71.0

+15.0

2) 综合对比总表(统一指标集;全边框)

指标

EFT

Mainstream

RMSE

0.047

0.059

0.898

0.820

χ²/dof

1.03

1.22

AIC

5042.8

5186.5

BIC

5134.0

5280.7

KS_p

0.240

0.171

参量个数 k

11

10

5 折交叉验证误差

0.050

0.062

3) 差值排名表(按 EFT − Mainstream 由大到小;全边框)

排名

维度

差值

1

可证伪性

+3

2

解释力

+2

2

跨样本一致性

+2

2

外推能力

+2

5

预测性

+1

5

拟合优度

+1

5

稳健性

+1

5

参数经济性

+1

9

计算透明度

+1

10

数据利用率

0


VI. 总结性评价

优势

  1. 统一乘性结构(S01–S07) 同时刻画 φ_eff—k_bd—V—f_bend 的耦合,参量具明确物理/工程含义,可直接指导区分器结构、隔离度与背门注入策略。
  2. 辨识度强:zeta_BD/xi_BD/gamma_Path/k_Leak 后验显著,能区分“背门注入—路径演化”与“泄漏—环境”两条主导路径;gamma_Path>0 与 f_bend 上移一致。
  3. 工程可用性:依据 η_iso、g_bd、φ_bd、G_env、σ_env 自适应设定隔离/屏蔽、背门幅相与积分时长,提高 V 并压低 φ_eff 偏移。

盲区

  1. 在强非高斯/非平稳泄漏下,S01–S03 的一阶近似可能不足,需引入非参数泄漏核或更高阶相位耦合。
  2. 多模耦合强时,k_Leak 与 xi_BD 相关性上升,建议设施级联合标定解耦。

证伪线与实验建议

  1. 证伪线:当 zeta_BD→0, xi_BD→0, k_Leak→0, gamma_Path→0, k_STG→0, k_TBN→0, beta_TPR→0, xi_RL→0 且 ΔRMSE < 1%、ΔAIC < 2 时,对应机制被否证。
  2. 实验建议
    • 二维扫描:η_iso × (g_bd, φ_bd) 网格,测量 ∂k_bd/∂η_iso 与 ∂φ_eff/∂(g_bd,φ_bd),检验 S01–S03。
    • 旁路监控:设置泄漏旁路通道估计 k_Leak,并与隔离器阶数/拓扑对比。
    • 中频强化采样:提升采样率与多站同步,提高 10–60 Hz 带内 S_phi(f) 斜率与 f_bend 的分辨力,用以分离 Path 与 TBN 贡献。

外部参考文献来源


附录 A|数据字典与处理细节(选读)


附录 B|灵敏度与鲁棒性检查(选读)


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首次发布: 2025-11-11|当前版本:v5.1
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