# Benchmark Results

<!-- AUTO-GENERATED by scripts/extract_notebook_plots.py. -->
<!-- Re-run after executing notebooks; do not edit ledgers by hand. -->

This generated page displays embedded benchmark plots and text outputs from the classical-baseline benchmark notebooks.

## Current Status

- Source notebooks: `notebooks/benchmarks/`
- Notebooks displayed: `4`
- Embedded plot artefacts displayed: `8`
- Plain-text notebook results displayed: `6`
- Plot manifest: [`results/tables/benchmark_plot_manifest.csv`](../../results/tables/benchmark_plot_manifest.csv)

## Related Pages

- [Results summary](results.md)
- [Notebook index](notebooks.md)
- [Tutorial notebook outputs](tutorial_results.md)
- [Real-example notebook outputs](real_example_results.md)

## Regeneration

Execute notebooks, extract their embedded outputs, and refresh this page with:

```bash
python scripts/extract_notebook_plots.py --preset benchmarks --execute --write-docs
```

## Notebook Results

### `01_linear_system_classical_vs_qsvt_proxy.ipynb`

Source: [`notebooks/benchmarks/01_linear_system_classical_vs_qsvt_proxy.ipynb`](../../notebooks/benchmarks/01_linear_system_classical_vs_qsvt_proxy.ipynb)

```{image} ../../results/plots/benchmarks/01_linear_system_classical_vs_qsvt_proxy-plot-01.png
:alt: Linear-System Classical Baselines vs QSVT Resource Proxies plot 1
:width: 520px
```

```{image} ../../results/plots/benchmarks/01_linear_system_classical_vs_qsvt_proxy-plot-02.png
:alt: Linear-System Classical Baselines vs QSVT Resource Proxies plot 2
:width: 520px
```

Output 1 (cell 7):

```text
Poisson system
--------------
Dimension : 12
Condition number : 67.83
Scaled spectral gap gamma : 0.01474
Inverse polynomial degree : 9
```

Output 2 (cell 11):

```text
Benchmark readout
-----------------
Dense relative residual : 2.78e-15
CGS relative residual : 7.68e-15
CGS iterations : 1
QSVT signal calls : 9
```

### `02_matrix_functions_spectral_baselines.ipynb`

Source: [`notebooks/benchmarks/02_matrix_functions_spectral_baselines.ipynb`](../../notebooks/benchmarks/02_matrix_functions_spectral_baselines.ipynb)

```{image} ../../results/plots/benchmarks/02_matrix_functions_spectral_baselines-plot-01.png
:alt: Matrix-Function Spectral Baselines plot 1
:width: 520px
```

```{image} ../../results/plots/benchmarks/02_matrix_functions_spectral_baselines-plot-02.png
:alt: Matrix-Function Spectral Baselines plot 2
:width: 520px
```

Output 1 (cell 8):

```text
Matrix-function benchmark readout
---------------------------------
Spectral baseline problem   : exponential-matrix-function
Thermal polynomial degree : 10
Filter polynomial degree : 10
Filter QSVT signal calls : 10
```

### `03_scaling_sweeps.ipynb`

Source: [`notebooks/benchmarks/03_scaling_sweeps.ipynb`](../../notebooks/benchmarks/03_scaling_sweeps.ipynb)

```{image} ../../results/plots/benchmarks/03_scaling_sweeps-plot-01.png
:alt: Scaling Sweeps For Classical Baselines And QSVT Proxies plot 1
:width: 520px
```

```{image} ../../results/plots/benchmarks/03_scaling_sweeps-plot-02.png
:alt: Scaling Sweeps For Classical Baselines And QSVT Proxies plot 2
:width: 520px
```

Output 1 (cell 8):

```text
Scaling sweep readout
---------------------
Reports : 6
Matrix dimensions : 6, 10, 14
Max QSVT signal calls : 9
```

### `04_classical_baseline_assumptions.ipynb`

Source: [`notebooks/benchmarks/04_classical_baseline_assumptions.ipynb`](../../notebooks/benchmarks/04_classical_baseline_assumptions.ipynb)

```{image} ../../results/plots/benchmarks/04_classical_baseline_assumptions-plot-01.png
:alt: Classical Baseline Assumptions plot 1
:width: 520px
```

```{image} ../../results/plots/benchmarks/04_classical_baseline_assumptions-plot-02.png
:alt: Classical Baseline Assumptions plot 2
:width: 520px
```

Output 1 (cell 8):

```text
Linear-system baseline readout
==============================
Case  Classical algorithm                       Condition  Relative residual  QSVT degree [polynomial degree]  Signal calls [operator calls]
----  ----------------------------------------  ---------  -----------------  -------------------------------  -----------------------------
DLS   numpy.linalg.solve                        4          8.86e-17           9                                9
CGS   qsvt.benchmarks.conjugate_gradient_solve  4          1.77e-16           9                                9

DLS times a dense direct solve. CGS reports iterative-solver diagnostics, but this educational benchmark still uses dense NumPy matrix-vector products.
```

Output 2 (cell 10):

```text
Matrix-function baseline readout
================================
Case  Classical algorithm             QSVT degree [polynomial degree]  Signal calls [operator calls]  Best time (s)
----  ------------------------------  -------------------------------  -----------------------------  -------------
DSMF  dense-spectral-matrix-function  n/a                              n/a                            1.30e-04
PME   spectral-polynomial-evaluation  2                                2                              1.43e-04

DSMF is the exact dense spectral reference. PME applies the supplied polynomial classically and is the closest fixed-polynomial comparison to a QSVT sequence.
```