Reconfigurable qubit states and quantum trajectories in a synthetic artificial neuron network with a process to direct information generation from co-integrated burst-mode spiking under non-Markovianity

TL;DR

This paper introduces a reconfigurable quantum neuron network that integrates superconducting memories and burst-mode spiking to enhance neuromorphic AI capabilities with quantum coherence, entanglement, and secure information routing.

Contribution

It presents a novel synthetic neuron system combining superconducting ionic memories with quantum states, enabling reconfigurable qubits and quantum trajectories driven by burst-mode spiking.

Findings

Demonstrated burst-mode driven reconfigurable qubit states.

Analyzed quantum trajectories with a Hamiltonian considering rotational dependence.

Explored quantum information packet generation with entangled artificial neuron qubits.

Abstract

A synthetic artificial neuron network functional in a regime where quantum information processes are co-integrated with spiking computation provides significant improvement in the capabilities of neuromorphic systems in performing artificial intelligence and autonomy tasks. This provides the ability to execute with the qubit coherence states and entanglement as well as in tandem to perform functions such as read out and basic arithmetic with conventional spike-encoding. Ultimately, this enables the generation and computational processing of information packets with advanced capabilities and an increased level of security in their routing. We now use the dynamical pulse sequences generated by a memristive spiking neuron to drive synthetic neurons with built-in superconductor-ionic memories built in a lateral layout with integrated Niobium metal electrodes as well as a gate terminal and an atomic layer deposited ionic barrier. The memories operate at very low voltage and with direct, and hysteretic Josephson tunneling and provide enhanced coherent properties enabling qubit behavior. We operated now specifically in burst mode to drive its built-in reconfigurable qubit states and direct the resulting quantum trajectory. We analyze the new system with a Hamiltonian that considers an integrated rotational dependence, dependent on the unique co-integrated bursting mode spiking- and where the total above threshold spike count is adjustable with variation of the level of coupling between the neurons. We then examined the impact of key parameters with a longer-term non-Markovian quantum memory and finally explored a process and algorithm for the generation of information packets with a coupled and entangled set of these artificial neuron qubits that provides for a quantum process to define the level of regularity or awareness of the information packets.