Physical reservoir computing using finitely-sampled quantum systems
- URL: http://arxiv.org/abs/2110.13849v2
- Date: Fri, 5 Nov 2021 17:38:07 GMT
- Title: Physical reservoir computing using finitely-sampled quantum systems
- Authors: Saeed Ahmed Khan and Fangjun Hu and Gerasimos Angelatos and Hakan E.
T\"ureci
- Abstract summary: Reservoir computing exploits the nonlinear dynamics of a physical reservoir to perform complex time-series processing tasks.
Here we describe a framework for reservoir computing with nonlinear quantum reservoirs under continuous measurement.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The paradigm of reservoir computing exploits the nonlinear dynamics of a
physical reservoir to perform complex time-series processing tasks such as
speech recognition and forecasting. Unlike other machine-learning approaches,
reservoir computing relaxes the need for optimization of intra-network
parameters, and is thus particularly attractive for near-term
hardware-efficient quantum implementations. However, the complete description
of practical quantum reservoir computers requires accounting for their
placement in a quantum measurement chain, and its conditional evolution under
measurement. Consequently, training and inference has to be performed using
finite samples from obtained measurement records. Here we describe a framework
for reservoir computing with nonlinear quantum reservoirs under continuous
heterodyne measurement. Using an efficient truncated-cumulants representation
of the complete measurement chain enables us to sample stochastic measurement
trajectories from reservoirs of several coupled nonlinear bosonic modes under
strong excitation. This description also offers a mathematical basis to
directly compare the computational capabilities of a given physical reservoir
operated across classical and quantum regimes. Applying this framework to the
classification of quantum states of systems that are part of the same
measurement chain as the quantum reservoir computer, we assess and explain
measurement-contingent advantages and disadvantages of reservoir processing in
quantum regimes. Our results also identify the vicinity of bifurcation points
as presenting optimal nonlinear processing regimes of an oscillator-based
quantum reservoir. The considered models are directly realizable in modern
circuit QED experiments, while the framework is applicable to more general
quantum nonlinear reservoirs.
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