Quantized Single-Ion-Channel Hodgkin-Huxley Model for Quantum Neurons

被引:13
|
作者
Gonzalez-Raya, Tasio [1 ]
Cheng, Xiao-Hang [1 ,2 ,3 ]
Egusquiza, Inigo L. [4 ]
Chen, Xi [1 ,2 ,3 ]
Sanz, Mikel [1 ]
Solano, Enrique [1 ,2 ,3 ,5 ]
机构
[1] Univ Basque Country, Dept Phys Chem, Apartado 644, Bilbao 48080, Spain
[2] Shanghai Univ, Int Ctr Quantum Artificial Intelligence Sci & Tec, Shanghai 200444, Peoples R China
[3] Shanghai Univ, Dept Phys, Shanghai 200444, Peoples R China
[4] Univ Basque Country, Dept Theoret Phys & Hist Sci, Apartado 644, Bilbao 48080, Spain
[5] Basque Fdn Sci, Ikerbasque, Maria Diaz de Haro 3, Bilbao 48013, Spain
来源
PHYSICAL REVIEW APPLIED | 2019年 / 12卷 / 01期
关键词
NOISE-INDUCED SYNCHRONIZATION; COHERENCE RESONANCE; RELIABILITY; BEHAVIOR; NETWORK;
D O I
10.1103/PhysRevApplied.12.014037
中图分类号
O59 [应用物理学];
学科分类号
摘要
The Hodgkin-Huxley model describes the behavior of the cell membrane in neurons, treating each part of it as an electric circuit element; namely, capacitors, memristors, and voltage sources. We focus on the activation channel of potassium ions, due to its simplicity, while keeping most of the features displayed by the original model. This reduced version is essentially a classical memristor, a resistor whose resistance depends on the history of electric signals that have crossed it, coupled to a voltage source and a capacitor. We consider a quantized Hodgkin-Huxley model based on a quantum-memristor formalism. We compare the behavior of the membrane voltage and the potassium-channel conductance when the circuit is subjected to ac sources, in both the classical realm and the quantum realm. Numerical simulations show an expected adaptation of the considered channel conductance depending on the signal history in all regimes. Remarkably, the computation of higher moments of the voltage shows purely quantum features related to the circuit zero-point energy. Finally, we study the implementation of the Hodgkin-Huxley quantum memristor as an asymmetric rf superconducting quantum-interference device in superconducting circuits. This study may allow the construction of quantum neuron networks inspired by the brain function, as well as the design of neuromorphic quantum architectures for quantum machine learning.
引用
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页数:13
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