Set of N integers between -30 and 30 with sum and cubic sum up to zero for 4<N<13
<p><strong>Anomalies</strong></p> <p>Solutions obtained with the python package: <a href="http://doi.org/10.5281/zenodo.5526558">anomalies</a> based on the method to find anomaly free solutions of the standard model extended with an Abelian Dark Symmetry with <em>N</em> right-handed singlet chiral fields described in <a href="https://arxiv.org/abs/1905.13729">arXiv:1905.13729</a> [PRL]:</p> <p><strong>Data scheme</strong></p> <ul> <li>'l': integer lists → input to obtain the 'solution' by using the <a href="http://doi.org/10.5281/zenodo.5526558">anomalies</a> package</li> <li>'k': integer lists → input to obtain the 'solution' by using hte <a href="http://doi.org/10.5281/zenodo.5526558">anomalies</a> package</li> <li>'solution': list → of integers, <span class="math-tex">\(\large z_i\)</span><sub> </sub>which satisfy <span class="math-tex">\(\large\displaystyle{ \sum_{i=1}^N z_i=0}\)</span> and <span class="math-tex">\(\large\displaystyle{ \sum_{i=1}^N z_i^3=0}\)</span> .</li> <li>'n': integer → number of integers in 'solution', <em>N</em>.</li> </ul> <pre> <strong>USAGE</strong></pre> <pre><code class="language-python">#Example of JSON file usage in Python with pandas (see also json module) >>> import pandas as pd >>> df=pd.read_json('solutions.json.gz') >>> df[:2] l k solution gcd n 0 [1, 2] [0, -3] [1, 5, -7, -8, 9] 1 5 1 [-2, -1] [0, -1] [2, 4, -7, -9, 10] 1 5</code></pre> <p><strong>Data:</strong><br> 2 296 615 solutions with <span class="math-tex">\(\large 5\le N\le 12\)</span> integers until `|32|` [JSON]</p>
ShareScore
48/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 8
- Access
- 20
- Reuse readiness
- 8
- Engagement
- 4