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Practical learning method for multi-scale entangled states
We describe a method for reconstructing multi-scale entangled states from a
small number of efficiently-implementable measurements and fast
post-processing. The method only requires single particle measurements and the
total number of measurements is polynomial in the number of particles. Data
post-processing for state reconstruction uses standard tools, namely matrix
diagonalisation and conjugate gradient method, and scales polynomially with the
number of particles. Our method prevents the build-up of errors from both
numerical and experimental imperfections
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