About: Neural network quantum states

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Neural Network Quantum States (NQS or NNQS) is a general class of variational quantum states parameterized in terms of an artificial neural network. It was first introduced in 2017 by the physicists Giuseppe Carleo and to approximate wave functions of many-body quantum systems. Given a comprising degrees of freedom and a choice of associated quantum numbers , then an NQS parameterizes the wave-function amplitudes where is an artificial neural network of parameters (weights) , input variables and one complex-valued output corresponding to the wave-function amplitude.

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  • Neural Network Quantum States (NQS or NNQS) is a general class of variational quantum states parameterized in terms of an artificial neural network. It was first introduced in 2017 by the physicists Giuseppe Carleo and to approximate wave functions of many-body quantum systems. Given a comprising degrees of freedom and a choice of associated quantum numbers , then an NQS parameterizes the wave-function amplitudes where is an artificial neural network of parameters (weights) , input variables and one complex-valued output corresponding to the wave-function amplitude. This variational form is used in conjunction with specific approaches to approximate quantum states of interest. (en)
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  • Neural Network Quantum States (NQS or NNQS) is a general class of variational quantum states parameterized in terms of an artificial neural network. It was first introduced in 2017 by the physicists Giuseppe Carleo and to approximate wave functions of many-body quantum systems. Given a comprising degrees of freedom and a choice of associated quantum numbers , then an NQS parameterizes the wave-function amplitudes where is an artificial neural network of parameters (weights) , input variables and one complex-valued output corresponding to the wave-function amplitude. (en)
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  • Neural network quantum states (en)
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