Reference
Reference#
Autogenerated summary of the modules, functions and classes in quimb
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Core functions for manipulating quantum objects. |
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Functions for more advanced calculations of quantities and properties of quantum objects. |
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Easy and efficient time evolutions. |
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Miscellenous |
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Functions for generating quantum objects. |
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Functions for generating quantum states. |
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Functions for generating quantum operators. |
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Functions for generating random quantum objects and states. |
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Linear algebra routines to solve quantum systems for example. |
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Backend agnostic functions for solving matrices either fully or partially. |
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Numpy base linear algebra. |
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Scipy based linear algebra. |
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Interface to slepc4py for solving advanced eigenvalue problems. |
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Manages the spawning of mpi processes to send to the various solvers. |
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Use stochastic Lanczos quadrature to approximate spectral function sums of any operator which has an efficient representation of action on a vector. |
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Randomized iterative methods for decompositions. |
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Core tensor network tools. |
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Generate specific tensor network states and operators. |
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Classes and algorithms related to 1D tensor networks. |
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DMRG-like variational algorithms, but in tensor network language. |
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Classes and algorithms related to 2D tensor networks. |
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Approximating spectral functions with tensor networks. |
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Support for optimizing tensor networks using automatic differentiation to automatically derive gradients for input to scipy optimizers. |