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Finding purifications with minimal entanglement

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Finding purifications with minimal entanglement

Post by Johannes »

In this paper we tried to optimize purification states with 'disentanglers'. The presented disentangler algorithms are put into TeNPy in tenpy.algorithms.purification_tebd.


Purification is a tool that allows to represent mixed quantum states as pure states on enlarged Hilbert spaces. A purification of a given state is not unique and its entanglement strongly depends on the particular choice made. Moreover, in one-dimensional systems, the amount of entanglement is linked to how efficiently the purified state can be represented using matrix-product states (MPS). We introduce an MPS based method that allows to find the minimally entangled representation by iteratively minimizing the second Renyi entropy. First, we consider the thermofield double purification and show that its entanglement can be strongly reduced especially at low temperatures. Second, we show that a slowdown of the entanglement growth following a quench of an infinite temperature state is possible.
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