  Reconstructing quantum states is an important task for various emerging
quantum technologies. The process of reconstructing the density matrix of a
quantum state is known as quantum state tomography. Conventionally, tomography
of arbitrary quantum states is challenging as the paradigm of efficient
protocols has remained in applying specific techniques for different types of
quantum states. Here we introduce a quantum state tomography platform based on
the framework of reservoir computing. It forms a quantum neural network, and
operates as a comprehensive device for reconstructing an arbitrary quantum
state (finite dimensional or continuous variable). This is achieved with only
measuring the average occupation numbers in a single physical setup, without
the need of any knowledge of optimum measurement basis or correlation
measurements.
