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Quantum information and many-body library.

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quimb is an easy but fast python library for quantum information and many-body calculations. The main docs are hosted on readthedocs. It is also thoroughly unit-tested and the tests are probably the best place to look for detailed documentation.

The core quimb module:

  • Uses numpy and scipy.sparse matrices as quantum objects
  • Accelerates many operations using numba and numexpr
  • Makes it easy to construct operators in large tensor spaces (e.g. 2D lattices).
  • Uses efficient methods to compute various quantities including entanglement measures
  • Can generate a variety of random states and operators
  • Can perform evolutions with several methods, computing quantities on the fly
  • Has an optional slepc4py interface for easy distributed (MPI) linear algebra. This can massively increase the performance when seeking, for example, mid-spectrum eigenstates.

The tensor network module quimb.tensor:

  • Uses a geometry free representation of tensor networks
  • Uses opt_einsum to find efficient contraction orders for hundreds of tensors, and perform those contractions potentially on the GPU
  • Can plot any network, color-coded, with bond size represented
  • Can treat any network as a scipy LinearOperator, allowing many decompositions
  • Can perform DMRG1, DMRG2 and DMRGX, in matrix product state language.
  • Has tools to efficiently address periodic problems (transfer matrix compression and pseudo-orthogonalization)
  • MPS time evolutions with TEBD.

The full documentation can be found at: http://quimb.readthedocs.io/en/latest/.

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