  We show that the numerical strong disorder renormalization group algorithm
(SDRG) of Hikihara et. al. [Phys. Rev. B 60, 12116 (1999)] for the
one-dimensional disordered Heisenberg model naturally describes a tree tensor
network (TTN) with an irregular structure defined by the strength of the
couplings. Employing the holographic interpretation of the TTN in Hilbert
space, we compute expectation values, correlation functions and the
entanglement entropy using the geometrical properties of the TTN. We find that
the disorder averaged spin-spin correlation scales with the average path length
through the tensor network while the entanglement entropy scales with the
minimal surface connecting two regions. Furthermore, the entanglement entropy
increases with both disorder and system size, resulting in an area-law
violation. Our results demonstrate the usefulness of a self-assembling TTN
approach to disordered systems and quantitatively validate the connection
between holography and quantum many-body systems.

Disordered Systems and Neural Networks;Quantum Physics