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61 to 70 of 906 Results
LandauEigensolver.py
Aug 20, 2026 - Replication Data for: Diagonalization of the Landau Hamiltonian with a Periodic Potential via a Galerkin Projection Method and Applications to Topological Band Properties
Python Source Code - 19.7 KB - MD5: 84077f0cd43241b6f808d3109a508837
LICENSE.txt
Aug 20, 2026 - Replication Data for: Diagonalization of the Landau Hamiltonian with a Periodic Potential via a Galerkin Projection Method and Applications to Topological Band Properties
Plain Text - 1.1 KB - MD5: 1a349ef880bd5e5d7ba4ad28673d983c
plotting_tools.py
Aug 20, 2026 - Replication Data for: Diagonalization of the Landau Hamiltonian with a Periodic Potential via a Galerkin Projection Method and Applications to Topological Band Properties
Python Source Code - 22.1 KB - MD5: 4b7bc23ff6f92e547bf4d03048088854
README.md
Aug 20, 2026 - Replication Data for: Diagonalization of the Landau Hamiltonian with a Periodic Potential via a Galerkin Projection Method and Applications to Topological Band Properties
Markdown Text - 1.2 KB - MD5: 2606194aacf72c5a3355d72f71979fba
tutorial_script.py
Aug 20, 2026 - Replication Data for: Diagonalization of the Landau Hamiltonian with a Periodic Potential via a Galerkin Projection Method and Applications to Topological Band Properties
Python Source Code - 8.2 KB - MD5: 2e2c91f233bb42fc0774b6b6f5cd0b53
comment_gext.tar.gz
Jul 17, 2026 - Replication Data for: Comment on “Grassmann extrapolation via direct inversion in the iterative subspace” [J. Chem. Phys. 163, 144114 (2025)]
Gzip Archive - 1.1 GB - MD5: 75ae2035ada350d0d72af451ac4bc8c1
Archive containing the dataset, the code to do the analysis and the code to do the plots.
README.md
Jul 17, 2026 - Replication Data for: Comment on “Grassmann extrapolation via direct inversion in the iterative subspace” [J. Chem. Phys. 163, 144114 (2025)]
Plain Text - 2.9 KB - MD5: c35de91e274379db161fd1fd09a0628c
Description of the content of the archive.
001.dat
Mar 4, 2026 - Replication Data for: Solving Approximation Tasks with Greedy Deep Kernel Methods
Fixed Field Text Data - 7.3 KB - MD5: a9d8cac2430040a3af07d840eb707373
001.raw
Mar 4, 2026 - Replication Data for: Solving Approximation Tasks with Greedy Deep Kernel Methods
Unknown - 3.2 MB - MD5: 0279092d1247ffccf6b4a6b570791f40
2D_test_NN_L12.npy
Mar 4, 2026 - Replication Data for: Solving Approximation Tasks with Greedy Deep Kernel Methods
Unknown - 102.7 KB - MD5: e0d3bd158ce0eb895ef5ffb2526a3675
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