Showing posts with label human brains. Show all posts
Showing posts with label human brains. Show all posts

Saturday, July 19, 2025

Ion traps and photons are the tools for next-generation quantum systems.


"By twisting light just right, scientists can now unlock dual hidden images from a single metasurface, ushering in new possibilities for encryption and molecular detection. Credit: Shutterstock" (ScitechDaily, New Tech Uses Twisted Light to Reveal Hidden Images)

The ion traps and twisted light make it possible to create new types of quantum systems. What if researchers can create a particle and trap the twisted light ring around that thing? That could revolutionize quantum technology. If somebody can connect and stabilize twisted light around an ion or electron, that can turn the system into the most accurate scanner that has ever been seen before. The photonic system that can create a “photon smoke ring” and stabilize it around some particle, like an ion or electron, can revolutionize information technology. But that system faces many technical issues. 

But theoretically, artificial brains require ions that play the same role as neurotransmitters. And a photonic system that mimics the brain's electrical actions. Miniature particle accelerators act as axons, and they shoot ions through the axon hole. Information is stored in those ions. 

The ability to create ions, or electrons that twist light orbits, makes it possible to create a system that operates like a human brain. That ion-photon combination can act in the same role as a neurotransmitter in that system. And if the system can trap that combination at a certain moment, that makes it possible to use the photonic data transmission for the messages that require an extra-fast speed. These kinds of systems mimic human brains. The ability to connect photonics and ions makes it possible to use two quantum lines side-by-side in the system. 

One of the most exciting things could be creating the photon ball. Their data transportation photon travels inside this photonic ball. It could be possible to trap the ion-photonic ring inside the fullerene molecule. And that allows the system to transport qubits over a long distance. The long-range qubit will travel in the laser or maser beam. And that thing could make new ways to transport information. The problem is how to make a photonic ring stay around ions? 

The problem is that. Stabilizing twisted light is not a very easy thing. The hollow lasers can make photon rings where the waves or curves are one or zero. The other way is to adjust the hollow laser light’s brightness. The hollow lasers can also protect the data that travels inside them. In those cases, the data transportation laser beams travel inside a hollow laser beam that protects them against outsiders. 


https://scitechdaily.com/harvard-scientists-unveil-tiny-ring-laser-with-giant-potential/


https://scitechdaily.com/lighting-up-the-ion-trap-fiber-optics-built-into-a-chip-for-quantum-computing/


https://scitechdaily.com/new-tech-uses-twisted-light-to-reveal-hidden-images/



Tuesday, February 22, 2022

Researchers are found math neurons in human brains.



Image 1:)

Researchers are found math neurons in human brains. That thing gives new information on how and when the neurons are starting to specify. The discovery of the neurons that are specialized in mathematics is opening new paths for neurosciences. Because there are the math neurons there should be language neurons. 

And maybe there are specialized neurons for every type of skill that people have. So there could be cooking neurons and social neurons that are controlling social activities in the neural network. 

When researchers are finding when the separation of the neurons starts. That thing makes the revolution in the training and education. Learning new skills is rewiring brains. And if that process can be controlled by researchers, that brings the new and powerful educating tools to the hands of the educational processors. 

That kind of research can serve the medical care of brain damages. There is a possibility that in the future. The person whose brain is injured. Can get the neural transplant. That thing can make by using the cloned neurons. But the problem is: How to transfer the skills, that people had to those neurons? Every single skill that a person has is stored in neurons.





Image 2:)


And that thing means that if a neuron is lost. The data includes skills that are stored in those neurons gone forever. 

That is the thing that makes brain damage so hard to recover. Researchers can clone neurons. But the problem is how to recover skills and memories that are gone to the cloned neurons. Skills are memories like all other things. 

The thing is that when we are expanding our understanding of brains and their function we are getting tools how to make more effective neural networks. And those things might consist the hybrid systems where the living neurons are connected with artificial intelligence and non-organic sensors. 

We know why our brains are so effective. Brains are made of billions of neurons and that thing makes them effective. But the thing is that the brains are starting their data handling process same time in multiple locations in neural structure. 

And that increases their effectiveness. When some neuron group is needed for some other mission, that group will store the thing in memory. And that allows that other neuron group will continue with that thing. The internal axon structure can transmit the data that is stored in memory to anywhere in the neural structure. 

The new type of neural computers, networks, and deep-learning AI can use the data that is collected from the sensors. The deep-learning systems are following the success of the robots by using certain parameters. Those parameters can be simply how far a robot can operate without causing damages or getting damaged. 

The fuzzy logic makes that kind of system "quite easy to make". At the first, the AI would operate by using a large number of actors. When some actor will make mistake the AI drops that thing away. If the AI would follow robots that system records how far a robot can travel or how long it can operate. 

Then the parameter can be simple like this: (number of actions/time unit). The best result would be stored in the memory of AI. And then the AI would use mission records to find out where the mistake is made. If a robot falls into the canyon. 

The AI would control those machines to drive farther from the canyon's edge. So the best result is the same thing that makes the AI select a certain route. And of course, if we want to connect the number of actions to the robot. That thing can be picking up the ground samples. 


https://scitechdaily.com/brains-of-cosmonauts-rewired-during-space-missions/


https://scitechdaily.com/hiddenite-a-new-ai-processor-based-on-a-cutting-edge-neural-network-theory/


https://scitechdaily.com/specific-math-neurons-identified-in-the-brain/


Image 1:)https://scitechdaily.com/brains-of-cosmonauts-rewired-during-space-missions/


Image 2:)https://scitechdaily.com/specific-math-neurons-identified-in-the-brain/

Can negative time explain dark energy?

Can time itself turn into quantum? What if time is the four-dimensional superstring? The thin energy tornado. That spins faster than the spe...