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Scope, limitations and roadmap: what the released package does and does not, what a dataset needs, what has been validated; the landing page, the ecosystem page and the assistant say Matter runs your data on your computer
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<h1 id="benchmark-compatibility">Benchmark compatibility<a class="headerlink" href="#benchmark-compatibility" title="Permanent link">&para;</a></h1>
<p>Two families of metrics, so that a result here can be read next to results elsewhere.</p>
<h2 id="crystal-generation-quality-the-lemat-genbench-families">Crystal-generation quality: the LeMat-GenBench families<a class="headerlink" href="#crystal-generation-quality-the-lemat-genbench-families" title="Permanent link">&para;</a></h2>
<p><a href="https://github.com/LeMaterial/lemat-genbench">LeMat-GenBench</a> (Siron et al., 2025) evaluates crystal generative models in eight families. <code>meidnet score</code> reports the same families, from a folder of CIF files produced by any model, with the definitions below. Where this implementation differs from LeMat-GenBench, the table says so; for leaderboard-comparable numbers, run LeMat-GenBench itself.</p>
<table>
<thead>
<tr>
<th>family</th>
<th>LeMat-GenBench</th>
<th><code>meidnet score</code></th>
</tr>
</thead>
<tbody>
<tr>
<td>validity</td>
<td>charge neutrality, minimum interatomic distance, coordination environment, physical plausibility</td>
<td>charge neutrality (an oxidation-state assignment that sums to zero), closest pair ≥ max(0.8 Å, 0.6 × the sum of the atomic radii), density 0.5–25 g/cm³, cell lengths 1–60 Å, angles 10–170°. Coordination environments are not checked.</td>
</tr>
<tr>
<td>uniqueness</td>
<td>BAWL fingerprints or StructureMatcher within the set</td>
<td>pymatgen StructureMatcher (ltol 0.2, stol 0.3, angle_tol 5°, primitive cells)</td>
</tr>
<tr>
<td>novelty</td>
<td>fraction not in LeMat-Bulk (BAWL or StructureMatcher)</td>
<td>against a reference you name (<code>--reference</code>: the Perov-5 split, or any CSV with <code>cif</code>/<code>formula</code> columns): by composition (reduced formula) and by structure (StructureMatcher against the reference entries of the same composition)</td>
</tr>
<tr>
<td>diversity</td>
<td>Vendi scores and Shannon entropy of elements, space groups, site numbers, physical size</td>
<td>Shannon entropy (bits) and counts of the elements, space groups (spglib, symprec 0.1) and site numbers; the density's mean and spread</td>
</tr>
<tr>
<td>distribution</td>
<td>JSD of categorical properties, MMD of volume and density, Fréchet distance of MLIP embeddings</td>
<td>Jensen–Shannon distance (base 2) of the element frequencies and of the site numbers against the reference. MMD and Fréchet distances are not computed.</td>
</tr>
<tr>
<td>stability</td>
<td>energy above the convex hull from several MLIPs (stable ≤ 0, metastable ≤ 0.1 eV/atom)</td>
<td>with <code>--mlip</code>: relaxation with MACE-MP and the formation energy per atom against elemental reference phases (<code>meidnet screen</code>'s filter); the report counts a structure as stable when it passes the filter (≤ 0.1 eV/atom). This is a formation-energy filter, not the energy above the hull: its rates are not comparable with LeMat-GenBench's.</td>
</tr>
<tr>
<td>hhi</td>
<td>production and reserve supply risk</td>
<td>not computed</td>
</tr>
<tr>
<td>sun</td>
<td>stable ∧ unique ∧ novel; MetaSUN</td>
<td>passes the formation-energy filter ∧ unique ∧ novel by structure, with <code>--mlip</code> and a reference with CIFs; reported as sun, but not comparable with LeMat-GenBench's hull-based SUN</td>
</tr>
</tbody>
</table>
<h2 id="conditional-inverse-design-quality-the-meidnet-extension">Conditional inverse-design quality: the MEIDNet extension<a class="headerlink" href="#conditional-inverse-design-quality-the-meidnet-extension" title="Permanent link">&para;</a></h2>
<p>A conditional generator is asked for a property; these metrics say whether it delivered. They need <code>targets.csv</code> with a <code>file</code> column (the CIF file name) and, per property, a point target <code>&lt;p&gt;_target</code>, a window <code>&lt;p&gt;_min</code> / <code>&lt;p&gt;_max</code>, or both. A bound such as "formation energy at most 1.0 eV/atom" is a window with only <code>&lt;p&gt;_max</code> = 1.0, not a point target. An optional <code>&lt;p&gt;_value</code> holds the value the submitter reports for the structure, with a <code>source</code> column saying how it was obtained (<code>dft</code>, <code>experiment</code>, <code>predicted</code>). Without a value, <code>--model &lt;checkpoint&gt;</code> predicts it with a MEIDNet model, and the report labels those values model-predicted.</p>
<div class="highlight"><pre><span></span><code>file,dir_gap_target,dir_gap_min,dir_gap_max,dir_gap_value,heat_all_max,heat_all_value,source
cand-001.cif,1.5,1.2,1.8,1.47,1.0,-0.62,dft
</code></pre></div>
<table>
<thead>
<tr>
<th>metric</th>
<th>definition</th>
</tr>
</thead>
<tbody>
<tr>
<td>target success rate</td>
<td>share of structures whose value lies inside the window when one is given, else with |value − target| ≤ tolerance, per property; the tolerance is <code>--tolerance p=…</code> or 5 % of the reference's range</td>
</tr>
<tr>
<td>target error</td>
<td>mean |value − target|, or the distance outside the window for a property with a window and no point target</td>
</tr>
<tr>
<td>multi-property success</td>
<td>share with every targeted property within tolerance</td>
</tr>
<tr>
<td>constraint success</td>
<td>valid structures (the validity family) among the successes</td>
</tr>
<tr>
<td>conditional diversity</td>
<td>distinct compositions among the successes, over the successes</td>
</tr>
<tr>
<td>target coverage</td>
<td>distinct target vectors with at least one success, over the distinct targets</td>
</tr>
<tr>
<td>interpolation share</td>
<td>targets inside the reference's property range (needs property columns in the reference)</td>
</tr>
</tbody>
</table>
<p>Oracle efficiency, the number of candidates evaluated per success, is a property of a run, not of a set of structures: the Perov-5 protocol reports it as the candidate budget and the delivered count.</p>
<h2 id="running-it">Running it<a class="headerlink" href="#running-it" title="Permanent link">&para;</a></h2>
<div class="highlight"><pre><span></span><code>pip<span class="w"> </span>install<span class="w"> </span><span class="s2">&quot;meidnet&gt;=2.3.1&quot;</span><span class="w"> </span><span class="c1"># or: pip install &quot;meidnet[stability]&quot; for --mlip</span>
meidnet<span class="w"> </span>download-data<span class="w"> </span><span class="c1"># Perov-5 as a reference (data/perov5/)</span>
meidnet<span class="w"> </span>score<span class="w"> </span>generated/<span class="w"> </span>--reference<span class="w"> </span>data/perov5
meidnet<span class="w"> </span>score<span class="w"> </span>generated/<span class="w"> </span>--reference<span class="w"> </span>data/perov5<span class="w"> </span>--targets<span class="w"> </span>targets.csv<span class="w"> </span>--tolerance<span class="w"> </span><span class="nv">dir_gap</span><span class="o">=</span><span class="m">0</span>.3
meidnet<span class="w"> </span>score<span class="w"> </span>generated/<span class="w"> </span>--reference<span class="w"> </span>data/perov5<span class="w"> </span>--mlip<span class="w"> </span>--out<span class="w"> </span>report.json
</code></pre></div>
<p><code>generated/</code> is a folder of CIF files (any depth) or a CSV with a <code>cif</code> column. The report prints as a table; <code>--out</code> writes the JSON with the per-structure checks. A run bundle from MEIDNet Matter contains <code>cifs/</code> and <code>targets.csv</code> in this layout.</p>
<p>Example: the 26 candidate structures shipped with the paper (<code>examples/perov5/paper_results</code>) scored against the full Perov-5 set, without MLIP, in three seconds:</p>
<div class="highlight"><pre><span></span><code>| validity | valid (all checks) | 100.0 % |
| uniqueness | unique structures | 24 of 26 (92.3 %) |
| novelty | new compositions vs perov5 | 69.2 % |
| novelty | new structures vs perov5 | 69.2 % |
| diversity | elements (entropy) | 25 (3.48 bits) |
| diversity | space groups (entropy) | 1 (0.00 bits) |
| distribution | element JSD vs reference | 0.717 |
</code></pre></div>
<p>One space group, because every structure is a cubic ABX₃ prototype: the diversity family shows where a prototype-family generator sits next to a free-form one.</p>
<p>Numbers from the metric families go into a submission under <code>results.generation</code>; the <a href="../community/contribute.html">contribute page</a> has the record layout.</p>
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