Package: python-kwant-doc Source: kwant Version: 1.4.2-1 Architecture: all Maintainer: Christoph Groth Installed-Size: 7831 Depends: libjs-sphinxdoc (>= 1.0), libjs-mathjax Homepage: http://kwant-project.org/ Priority: optional Section: doc Filename: pool/main/k/kwant/python-kwant-doc_1.4.2-1_all.deb Size: 5255580 SHA256: 99e2ef8d553d4b9aa133b61df98a9494efde97cf9e82694454971e385c89f31f SHA1: 1ea2725a23354a43f80ab1a1091a31487a848222 MD5sum: 881b6d5c4ad2a3168af9183a2c532949 Description: Kwant documentation Kwant is a Python package for numerical quantum transport calculations. It exposes the natural concepts of the theory of quantum transport (lattices, symmetries, electrodes, orbital/spin/electron-hole degrees of freedom) in a simple and transparent way. Kwant offers direct support for calculations of transport properties (conductance, noise, scattering matrix), dispersion relations, modes, wave functions, various Green’s functions, and out-of-equilibrium local quantities. Other computations involving tight-binding Hamiltonians can be implemented easily. . This package contains the documentation for Kwant in HTML format. Package: python-tinyarray Source: tinyarray Version: 1.2.2-1 Architecture: i386 Maintainer: Christoph Groth Installed-Size: 145 Depends: python (<< 2.8), python (>= 2.7~), python:any (<< 2.8), python:any (>= 2.7~), libc6 (>= 2.4), libgcc1 (>= 1:4.0), libstdc++6 (>= 5.2) Homepage: http://kwant-project.org/tinyarray/ Priority: optional Section: python Filename: pool/main/t/tinyarray/python-tinyarray_1.2.2-1_i386.deb Size: 42788 SHA256: e2011376a376753474b71c45a07dda9ecfba1fd6405d49e59529859cf13ceaf1 SHA1: cfb78a880b9ece020d6ee263d90c3a0023149928 MD5sum: 0e56da10cd6be0384b66c0f7c3e92949 Description: Arrays of numbers, optimized for small sizes (Python 2) Tinyarray is a numerical array module for Python. The multi-dimensional arrays it provides are best thought of as (possibly nested) tuples of numbers that, unlike Python's built-in tuples, support mathematical operations. Like tuples, tinyarrays are hashable and immutable and thus can be used as dictionary keys. The module's interface is a subset of that of NumPy and hence should be familiar to many Python programmers. Tinyarray has been heavily optimized for small arrays: For example, common operations on 1-d arrays of length 3 run 3-7 times faster than with NumPy. When storing many small arrays, memory consumption is reduced by a factor of 3. In summary, Tinyarray is a more efficient alternative to NumPy when many separate small numerical arrays are to be used. . This package installs the library for Python 2. Package: python-tinyarray-dbgsym Source: tinyarray Version: 1.2.2-1 Auto-Built-Package: debug-symbols Architecture: i386 Maintainer: Christoph Groth Installed-Size: 225 Depends: python-tinyarray (= 1.2.2-1) Priority: optional Section: debug Filename: pool/main/t/tinyarray/python-tinyarray-dbgsym_1.2.2-1_i386.deb Size: 197776 SHA256: 81a486d3be8734f5d0d59bef296507eef809bb0a62d595aad4d181a090317b37 SHA1: 71747c9c140bd91c400753829abffc45d5769123 MD5sum: 703711272becb53bee78bf2cddf5eefa Description: debug symbols for python-tinyarray Build-Ids: ab4347b7b998d670d0be0b6bb9b850d20253ba3b Package: python3-kwant Source: kwant Version: 1.4.2-1 Architecture: i386 Maintainer: Christoph Groth Installed-Size: 3759 Depends: python3 (<< 3.8), python3 (>= 3.7~), python3-numpy (>= 1.11), python3-scipy (>= 0.17), python3-tinyarray (>= 1.2), python3:any (>= 3.5~), libc6 (>= 2.4), libgfortran5 (>= 8), libmumps-5.1.2, libmumps-scotch-5.1.2 Recommends: python3-matplotlib (>= 1.5.1), python3-sympy (>= 0.7.6), python3-qsymm (>= 1.2.6) Suggests: python-kwant-doc, python3-pytest (>= 2.8) Homepage: http://kwant-project.org/ Priority: optional Section: python Filename: pool/main/k/kwant/python3-kwant_1.4.2-1_i386.deb Size: 727948 SHA256: 5bdc42dd15eb5133e4d0b4b317e736c8993401a9d18a6dd12bf5c7f2bcd7ef34 SHA1: 43c0a6ef6b259cdea3ada4e3ccb85f000c771134 MD5sum: f980bdbd33af12a8fca027fdc9eb7345 Description: Python package for numerical quantum transport calculations Kwant is a Python package for numerical quantum transport calculations. It exposes the natural concepts of the theory of quantum transport (lattices, symmetries, electrodes, orbital/spin/electron-hole degrees of freedom) in a simple and transparent way. Kwant offers direct support for calculations of transport properties (conductance, noise, scattering matrix), dispersion relations, modes, wave functions, various Green’s functions, and out-of-equilibrium local quantities. Other computations involving tight-binding Hamiltonians can be implemented easily. . This package contains Kwant for Python 3. Package: python3-kwant-dbgsym Source: kwant Version: 1.4.2-1 Auto-Built-Package: debug-symbols Architecture: i386 Maintainer: Christoph Groth Installed-Size: 3352 Depends: python3-kwant (= 1.4.2-1) Priority: optional Section: debug Filename: pool/main/k/kwant/python3-kwant-dbgsym_1.4.2-1_i386.deb Size: 3097420 SHA256: 257a4fcaee6d06ee239d5d1624b6cf4c2fdf522a741936cadd3b7364ca2c4a95 SHA1: c6a626e18aa77697860df93959350b89c2cdda85 MD5sum: 834ba4c15b090140b9cf92379e77133d Description: debug symbols for python3-kwant Build-Ids: 16e28b6af1fb5f53c70f018df6404376119e95c1 38f5900338d0fd303af1eed471bc1885406ca74d 83ba03c352ea6e72292ebdb2b3a85e471aebe04c 8f6989306d235d491bc8db30a2786719a7438cc5 a561ea0f659289cd3a4b11ff6e75cf1c2a372083 d4ed9537393f09717301a009bb5aae9e9f15b1f5 Package: python3-kwantspectrum Source: kwantspectrum Version: 0.1.0-1 Architecture: all Maintainer: Christoph Groth Installed-Size: 89 Depends: python3-kwant (>= 1.4), python3-numpy, python3-scipy, python3:any (>= 3.5~) Homepage: https://gitlab.kwant-project.org/kwant/kwantspectrum Priority: optional Section: python Filename: pool/main/k/kwantspectrum/python3-kwantspectrum_0.1.0-1_all.deb Size: 20608 SHA256: ba0c2a186786b7ccd239edaa2304e78956cf393925cbf98ff3f7105f7ee2e472 SHA1: 0fde5b9dda08b2358e8d995e8f13547af63f1d78 MD5sum: ac5c01f4e47de9e02ca912c4cdeceeef Description: Adaptive band structure analyzer for Kwant leads Kwantspectrum is an extension to Kwant that adaptively analyzes band structures of infinite quasi-1d systems. The bandstructure is approximated to an arbitrary precision by piecewise cubic polynomials. Functionality to deal with special points, intervals, and the periodic nature of the spectrum is provided. . This package contains kwantspectrum for Python 3. Package: python3-qsymm Source: qsymm Version: 1.2.7-2 Architecture: all Maintainer: Christoph Groth Installed-Size: 336 Depends: python3-numpy (>= 1.13), python3-scipy (>= 1.1.0), python3-sympy (>= 1.1), python3-tinyarray (>= 1.2), python3:any (>= 3.4~) Homepage: https://gitlab.kwant-project.org/qt/qsymm Priority: optional Section: python Filename: pool/main/q/qsymm/python3-qsymm_1.2.7-2_all.deb Size: 68100 SHA256: 11b63895a5399c349761dc97a19afa9104cae1e7e4e1d050c4ea3abd0cb0ba72 SHA1: a3ad3d61b3d47909c0cfdb7897891af47851898d MD5sum: e65bf1d9dbf2863487157fc8b3bf2576 Description: Symmetry finder and symmetric Hamiltonian generator Qsymm is an open-source Python library that makes symmetry analysis of quantum-mechanical Hamiltonians simple. It automatically generates model Hamiltonians from symmetry constraints and finds the full symmetry group of your Hamiltonian. . This package contains Qsymm for Python 3. Package: python3-tinyarray Source: tinyarray Version: 1.2.2-1 Architecture: i386 Maintainer: Christoph Groth Installed-Size: 138 Depends: python3 (<< 3.8), python3 (>= 3.7~), python3:any (>= 3.4~), libc6 (>= 2.4), libgcc1 (>= 1:4.0), libstdc++6 (>= 5.2) Homepage: http://kwant-project.org/tinyarray/ Priority: optional Section: python Filename: pool/main/t/tinyarray/python3-tinyarray_1.2.2-1_i386.deb Size: 39908 SHA256: c0ba82c3093e992576688b817c904b2690640e2a2511247321321cb527622913 SHA1: e1182f79083ca76a2c57044211d122921eb3483c MD5sum: 1350c2860caaad3c6bf18a65354cc484 Description: Arrays of numbers, optimized for small sizes (Python 3) Tinyarray is a numerical array module for Python. The multi-dimensional arrays it provides are best thought of as (possibly nested) tuples of numbers that, unlike Python's built-in tuples, support mathematical operations. Like tuples, tinyarrays are hashable and immutable and thus can be used as dictionary keys. The module's interface is a subset of that of NumPy and hence should be familiar to many Python programmers. Tinyarray has been heavily optimized for small arrays: For example, common operations on 1-d arrays of length 3 run 3-7 times faster than with NumPy. When storing many small arrays, memory consumption is reduced by a factor of 3. In summary, Tinyarray is a more efficient alternative to NumPy when many separate small numerical arrays are to be used. . This package installs the library for Python 3. Package: python3-tinyarray-dbgsym Source: tinyarray Version: 1.2.2-1 Auto-Built-Package: debug-symbols Architecture: i386 Maintainer: Christoph Groth Installed-Size: 229 Depends: python3-tinyarray (= 1.2.2-1) Priority: optional Section: debug Filename: pool/main/t/tinyarray/python3-tinyarray-dbgsym_1.2.2-1_i386.deb Size: 202448 SHA256: 10fae60e52a2722fc5d9e39df2449061ce2a4ab9bd0b0136e90e22cb77f10fda SHA1: c9de38814d4d4d6c405a57f5273b2184532d3c95 MD5sum: e2ddcbcc3a72eb5511d50c23af6d58b2 Description: debug symbols for python3-tinyarray Build-Ids: 7cd90f8b17c8c717a5b75511e650b9ebbfdb76bb