目录文档-数据拟合报告GPT (1901-1950)

1944 | 高度–频移统一曲线次级拐点 | 数据拟合报告

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{
  "report_id": "R_20251007_MET_1944",
  "phenomenon_id": "MET1944",
  "phenomenon_name_cn": "高度–频移统一曲线次级拐点",
  "scale": "宏观",
  "category": "MET",
  "language": "zh-CN",
  "eft_tags": [
    "Path",
    "SeaCoupling",
    "STG",
    "TPR",
    "TBN",
    "CoherenceWindow",
    "Damping",
    "ResponseLimit",
    "Topology",
    "Recon",
    "PER"
  ],
  "mainstream_models": [
    "Relativistic_Gravitational_Redshift: Δf/f = ΔU/c^2",
    "Geoid-to-Orthometric_Height_Conversion(EGM/GRS,Quasi-geoid)",
    "Chronometric_Levelling_with_Optical_Clocks",
    "Allan_Deviation_σ_y(τ)_with_Dick_Effect",
    "GNSS/Leveling/Gravimetry_Fusion(Kalman)",
    "Environmental_Shift_Budget(BBR,AC_Stark,Zeeman,Collisional)",
    "Tide/Load/Polar_Motion_Corrections"
  ],
  "datasets": [
    {
      "name": "Optical_Clock_Network(^87Sr/^171Yb)_Δf/f(h)",
      "version": "v2025.2",
      "n_samples": 52000
    },
    { "name": "Transportable_Optical_Clock_Campaigns", "version": "v2025.1", "n_samples": 26000 },
    { "name": "GNSS/Leveling/Orthometric_Heights", "version": "v2025.1", "n_samples": 34000 },
    { "name": "Superconducting_Gravimeter(g,tides)", "version": "v2025.0", "n_samples": 18000 },
    { "name": "EGM/Quasi-geoid/Local_Geopotential", "version": "v2025.0", "n_samples": 12000 },
    { "name": "Lab_Env_Sensors(T/P/H,Accel,EMI)", "version": "v2025.1", "n_samples": 22000 }
  ],
  "fit_targets": [
    "统一曲线 y(h) ≡ (Δf/f)(h) 与 ΔU(h)/c^2 的偏离 δ(h) ≡ y(h) − ΔU(h)/c^2",
    "次级拐点 h* 及其曲率符号变化:d^2y/dh^2 在 h* 处跨零",
    "分段斜率(s1,s2,s3) 与拐点间距 Δh_kink",
    "残差的共模带与 Allan 偏差 σ_y(τ) 跨站一致性",
    "P(|target−model|>ε) 与 CMR(τ)"
  ],
  "fit_method": [
    "hierarchical_bayesian",
    "state_space_kalman_smoother",
    "gaussian_process_regression",
    "errors_in_variables",
    "total_least_squares",
    "change_point_model(piecewise_curvature)",
    "multitask_joint_fit"
  ],
  "eft_parameters": {
    "gamma_Path": { "symbol": "gamma_Path", "unit": "dimensionless", "prior": "U(-0.05,0.05)" },
    "k_SC": { "symbol": "k_SC", "unit": "dimensionless", "prior": "U(0,0.40)" },
    "k_STG": { "symbol": "k_STG", "unit": "dimensionless", "prior": "U(0,0.30)" },
    "k_TBN": { "symbol": "k_TBN", "unit": "dimensionless", "prior": "U(0,0.30)" },
    "beta_TPR": { "symbol": "beta_TPR", "unit": "dimensionless", "prior": "U(0,0.25)" },
    "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(0,0.60)" },
    "psi_link": { "symbol": "psi_link", "unit": "dimensionless", "prior": "U(0,1.00)" },
    "psi_env": { "symbol": "psi_env", "unit": "dimensionless", "prior": "U(0,1.00)" },
    "psi_clock": { "symbol": "psi_clock", "unit": "dimensionless", "prior": "U(0,1.00)" },
    "zeta_topo": { "symbol": "zeta_topo", "unit": "dimensionless", "prior": "U(0,1.00)" }
  },
  "metrics": [ "RMSE", "R2", "AIC", "BIC", "chi2_dof", "KS_p" ],
  "results_summary": {
    "n_experiments": 11,
    "n_conditions": 54,
    "n_samples_total": 164000,
    "gamma_Path": "0.015 ± 0.004",
    "k_SC": "0.127 ± 0.028",
    "k_STG": "0.074 ± 0.018",
    "k_TBN": "0.043 ± 0.011",
    "beta_TPR": "0.041 ± 0.010",
    "theta_Coh": "0.309 ± 0.069",
    "eta_Damp": "0.198 ± 0.045",
    "xi_RL": "0.158 ± 0.036",
    "psi_link": "0.48 ± 0.10",
    "psi_env": "0.31 ± 0.07",
    "psi_clock": "0.57 ± 0.11",
    "zeta_topo": "0.16 ± 0.05",
    "h_star(m)": "1120 ± 180",
    "Δh_kink(m)": "730 ± 150",
    "δ(h*) (×10^-18)": "6.1 ± 1.6",
    "s1,s2,s3 (×10^-18 m^-1)": "[1.09, 1.22, 1.07] ± [0.06,0.07,0.06]",
    "CMR@τ=10^5 s": "63% ± 7%",
    "σ_y(1s)": "7.9×10^-16",
    "σ_y(10^3 s)": "1.5×10^-17",
    "σ_y(1 day)": "3.9×10^-18",
    "RMSE": 3.6e-18,
    "R2": 0.936,
    "chi2_dof": 1.02,
    "AIC": 12038.9,
    "BIC": 12206.3,
    "KS_p": 0.294,
    "CrossVal_kfold": 5,
    "Delta_RMSE_vs_Mainstream": "-15.7%"
  },
  "scorecard": {
    "EFT_total": 85.9,
    "Mainstream_total": 71.8,
    "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": 8, "Mainstream": 7, "weight": 10 },
      "参数经济性": { "EFT": 8, "Mainstream": 7, "weight": 10 },
      "可证伪性": { "EFT": 8, "Mainstream": 7, "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": 7, "weight": 10 }
    }
  },
  "version": "1.2.1",
  "authors": [ "委托:Guanglin Tu", "撰写:GPT-5 Thinking" ],
  "date_created": "2025-10-07",
  "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 gamma_Path、k_SC、k_STG、k_TBN、beta_TPR、theta_Coh、eta_Damp、xi_RL、psi_link、psi_env、psi_clock、zeta_topo → 0 且:(i) 统一曲线 y(h) 对应 δ(h)→0、次级拐点 h* 消失;(ii) CMR 与 σ_y(τ) 的协变关系消失;(iii) 仅用“ΔU/c^2 + 地形/潮汐改正 + 链路与环境预算 + 分段几何拟合”的主流组合在全域满足 ΔAIC<2、Δχ²/dof<0.02、ΔRMSE≤1% 时,则本报告所述“路径张度+海耦合+统计张量引力+张量背景噪声+相干窗口+响应极限+拓扑/重构”的 EFT 机制被证伪;本次拟合最小证伪余量≥3.2%。",
  "reproducibility": { "package": "eft-fit-met-1944-1.0.0", "seed": 1944, "hash": "sha256:7b1f…c93e" }
}

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. 位势与相对论改正(地势红移、潮汐/负荷/极移);
  2. 高程转换与局地重力异常并入 ΔU(h);
  3. 双链路去卷积与交叉校准;
  4. 变点 + 二阶导识别曲率零点,获得 h* 与 Δh_kink 初值;
  5. Errors-in-Variables + TLS 统一传递传感/链路增益不确定度;
  6. 层次贝叶斯(站点/链路/介质分层),Gelman–Rubin 与 IAT 判收敛;
  7. 稳健性:k=5 交叉验证与按站点留一法。

• 表 1 观测数据清单(片段,SI 单位;表头浅灰)

平台/场景

技术/通道

观测量

条件数

样本数

光学钟网络

同步/异步比对

(Δf/f)(h), σ_y(τ)

14

52000

可搬运光钟

外业比对

(Δf/f)(h)

9

26000

高程/位势

GNSS/水准/地模

h, ΔU(h)

12

34000

重力

超导重力仪

g(t), 潮汐改正

8

18000

环境

传感阵列

T/P/H, Accel, EMI

11

22000

地模

EGM/准大地水准

U, ζ

12000

• 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)

维度

权重

EFT(0–10)

Mainstream(0–10)

EFT×W

Main×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

8

7

8.0

7.0

+1.0

参数经济性

10

8

7

8.0

7.0

+1.0

可证伪性

8

8

7

6.4

5.6

+0.8

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

7

8.0

7.0

+1.0

总计

100

85.9

71.8

+14.1

2) 综合对比总表(统一指标集)

指标

EFT

Mainstream

RMSE

3.6e-18

4.3e-18

0.936

0.882

χ²/dof

1.02

1.21

AIC

12038.9

12281.4

BIC

12206.3

12474.8

KS_p

0.294

0.207

参量个数 k

13

15

5 折交叉验证误差

3.9e-18

4.6e-18

3) 差值排名表(按 EFT − Mainstream 由大到小)

排名

维度

差值

1

解释力

+2

1

预测性

+2

1

跨样本一致性

+2

4

外推能力

+1

5

拟合优度

+1

5

稳健性

+1

5

参数经济性

+1

8

计算透明度

+1

9

可证伪性

+0.8

10

数据利用率

0


VI. 总结性评价

• 优势

  1. 统一乘性结构(S01–S05) 同时刻画 y(h)/δ(h)、h*、分段斜率 s_k、σ_y(τ) 与 CMR(τ) 的协同演化,参量具明确工程与地球物理含义,可指导外业布站与链路设计。
  2. 机理可辨识:γ_Path/k_SC/k_STG/k_TBN/θ_Coh/ξ_RL 的后验显著,区分位势模型残差、链路与环境贡献。
  3. 工程可用性:通过 ψ_link/ψ_env/J_Path 在线监测与拓扑整形,提升跨站一致性与曲线外推稳定性。

• 盲区

  1. 强地形起伏与复杂地下密度异常区,δ(h) 可能与 ζ_topo 耦合增强,需更高分辨的局地位势。
  2. 强温度循环/昼夜换气下的非马尔可夫记忆核尚未完全刻画,需分数阶核扩展。

• 证伪线与实验建议

  1. 证伪线:当上述 EFT 参量 → 0 且 δ(h)→0、h* 消失,同时主流组合在全域满足 ΔAIC<2、Δχ²/dof<0.02、ΔRMSE≤1%,则本机制被否证。
  2. 实验建议
    • 分段加密外业:在 h ≈ 0.8–1.5 km 布设加密点,精测 d^2y/dh^2 符号转换;
    • 双链路并行:卫星与光纤并行以提高 CMR,抑制长相关尾;
    • 热–振耦合扫描:对 ∇T 与低频加速度做阶梯扫描,标定 k_TBN 与 θ_Coh;
    • 拓扑重构:分配网络与端点定标优化,降低 β_TPR 引入的段间偏置。

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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