Simulations on a quantum computer composed of 6 rubidium atoms show it may perform a basic algorithm inspired by the human brain. Lasers can manipulate atoms, mimicking brain connections.
An multinational team of scientists headed by Rodrigo Araiza Bravo from Harvard University, in the U.S., has designed a quantum computer model with large atoms controlled by laser light that, according to testing, might duplicate certain brain functions, such as memory and decision making. Quantum machine learning is used (QML).
Quantum computing promises to integrate machine learning with quantum computing capability, according to a new ArXiv study. Machine learning is an area of AI that develops algorithms for self-learning computers.
Quantum machine learning might be a breakthrough if combined with quantum computers. The qubit is the equivalent of the bit in quantum computers. Its key benefit is that it can employ quantum superposition to combine two states linearly, boosting its bit potential.
Quantum devices provide technical hurdles to harness quantum machine learning and make it practical. They are vulnerable to “noise” and the surroundings, causing malfunctions that have become quantum computing’s bottleneck.
Bravo and his colleagues have designed a quantum artificial neural network model that uses 6 rubidium atoms, which have a large diameter because some of their electrons orbit nuclei at a greater distance, to create a theoretical quantum computer that can replicate the learning of cognitive tasks typical of the human brain, such as multitasking, decision-making, and long-term memory.
According to New Scientist, the device can be controlled by lasers as rubidium atoms are light sensitive. The researchers proved the quantum computer can make basic judgments by training the neural network to pick between two laser pulses.
Researchers performed the decision-making exercise with a 10-microsecond delay between the two lasers to drive the quantum computer to remember the first pulse until confronted with the second. This proved he could improve his memory.
