Stochastic Benchmark Tensolver example

examples/TenSolver/README.md

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+# TenSolver Benchmark Example
+
+Benchmarking [TenSolver](https://github.com/SECQUOIA/TenSolver.jl) on 23 QUBO instances from the QpLib subset of QUBOLib (instances 308–330).
+
+## What's included
+
+- **Energy distribution visualizations** — heatmap showing how the sampled energy distribution evolves across DMRG iterations for a representative instance.
+- **Performance ratio** — computed against Gurobi's best-known objectives as the reference minimum and random bitstring sampling as the baseline.
+- **Bootstrap analysis** — performance ratio inferred for 1, 10, 100, and 1000 samples per iteration using the stochastic-benchmark framework.
+- **Resource analysis** — `iterations × samples` used as a proxy for compute; interpolation, train/test split, virtual best baseline, and projection experiments.
+
+## Data files
+
+| File | Description |
+|---|---|
+| `results/energy_history.json` | 1000 energy samples per DMRG iteration for all 23 instances |
+| `results/random_baseline.json` | Mean and min energy from 1000 random bitstrings per instance |
+| `results/gurobi_best.json` | Best objective found by Gurobi (900 s limit) per instance |

examples/TenSolver/results/gurobi_best.json

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+{
+  "308": {
+    "best_objective": -806,
+    "status": 2,
+    "optimal": true
+  },
+  "309": {
+    "best_objective": -440,
+    "status": 2,
+    "optimal": true
+  },
+  "310": {
+    "best_objective": -1686,
+    "status": 9,
+    "optimal": false
+  },
+  "311": {
+    "best_objective": -1542,
+    "status": 9,
+    "optimal": false
+  },
+  "312": {
+    "best_objective": -1844,
+    "status": 9,
+    "optimal": false
+  },
+  "313": {
+    "best_objective": -614,
+    "status": 2,
+    "optimal": true
+  },
+  "314": {
+    "best_objective": -1142,
+    "status": 2,
+    "optimal": true
+  },
+  "315": {
+    "best_objective": -688,
+    "status": 2,
+    "optimal": true
+  },
+  "316": {
+    "best_objective": -514,
+    "status": 2,
+    "optimal": true
+  },
+  "317": {
+    "best_objective": -1402,
+    "status": 2,
+    "optimal": true
+  },
+  "318": {
+    "best_objective": -900,
+    "status": 2,
+    "optimal": true
+  },
+  "319": {
+    "best_objective": -1298,
+    "status": 2,
+    "optimal": true
+  },
+  "320": {
+    "best_objective": -2022,
+    "status": 9,
+    "optimal": false
+  },
+  "321": {
+    "best_objective": -362,
+    "status": 2,
+    "optimal": true
+  },
+  "322": {
+    "best_objective": -1040,
+    "status": 2,
+    "optimal": true
+  },
+  "323": {
+    "best_objective": -23964950,
+    "status": 9,
+    "optimal": false
+  },
+  "324": {
+    "best_objective": -74347446,
+    "status": 2,
+    "optimal": true
+  },
+  "325": {
+    "best_objective": -68476481,
+    "status": 2,
+    "optimal": true
+  },
+  "326": {
+    "best_objective": -86899,
+    "status": 9,
+    "optimal": false
+  },
+  "327": {
+    "best_objective": -25305,
+    "status": 2,
+    "optimal": true
+  },
+  "328": {
+    "best_objective": -50321,
+    "status": 9,
+    "optimal": false
+  },
+  "329": {
+    "best_objective": -71422,
+    "status": 9,
+    "optimal": false
+  },
+  "330": {
+    "best_objective": -256359,
+    "status": 9,
+    "optimal": false
+  }
+}