Efficient bit encoding of neural networks for Fock states

• URL: http://arxiv.org/abs/2103.08285v2
• Date: Thu, 27 May 2021 09:46:18 GMT
• Title: Efficient bit encoding of neural networks for Fock states
• Authors: Oliver K\"astle and Alexander Carmele
• Abstract summary: The complexity of the neural network scales only with the number of bit-encoded neurons rather than the maximum boson number. In the high occupation regime its information compression efficiency is shown to surpass even maximally optimized density matrix implementations.
• Score: 77.34726150561087
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present a bit encoding scheme for a highly efficient and scalable representation of bosonic Fock number states in the restricted Boltzmann machine neural network architecture. In contrast to common density matrix implementations, the complexity of the neural network scales only with the number of bit-encoded neurons rather than the maximum boson number. Crucially, in the high occupation regime its information compression efficiency is shown to surpass even maximally optimized density matrix implementations, where a projector method is used to access the sparsest Hilbert space representation available.

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