Photonic and hybrid neural computers are coming.

   Photonic and hybrid neural computers are coming. 

The photonic computers can transfer binary data to qubits. 

There are two types of photonic computers. The photonic binary computer. And quantum computer that uses quantum entanglement between photons to transport information. 

The binary photonic computer requires photonic versions of the well-known electric components. In that computer, the key elements are the light transistors. The light transistor is an optical system where laser rays replace transistor electric parts, stock, collector, and emitter.

The light transistor is the system where the data laser transfers information into the carrier wave. Or oppositely. The laser beam that transports information between stock and collector will get more power from the emitter laser. 

In photonic computers, lasers are used as diodes. The electric computer transforms information into photonic form simply transferring it into communication lasers. The researchers can adjust those lasers' power or brightness by shooting those laser rays into the small light cells that pump energy in the lasers' electric circuit. That thing adjusts the brightness of the laser ray. 

The laser resistors can be nano technical components. There could be small hatches in the graphene net. And then the laser just opens those hatches by pressing them. Or a laser can transfer energy into the frame. When energy transfer continues long enough, that causes a photo-electric reaction which opens the hatch and lets that laser ray travel through this system. The mirrors can act as routers in that system. 

Image 1) Ring topology or token ring. The data travels in this ring. And every computer processes the answer. The hybrid network where the star topology and ring topology are connected would be more effective in hard data operations

Image 2) Star topology. The point of a single computer can be some kind of subnetwork. The neural computer can use this topology along with the ring model topology. The data travels between computers or sub-networks in a ring. The central unit can calculate how many times that data flow traveled around that system. The printer point can be data storage or the input and output point for data. 

The system requires internal data storage because there is a possibility. That there are some kind of errors in the system. The star topology can also introduce how quantum computers operate. The central unit cuts data that the system must process, sending those data bites to those sub-systems. In that system, those sub-systems simultaneously work with that mission. These kinds of systems are most effective when they are operating with long mathematical inductions where those systems can find recursions or the points where the function gets its zero points between certain value series. 

The photonic computer can be the step to drive information into qubits. Normal quantum computers use superpositioned and entangled photons. Photons are neutral and electromagnetic fields do not affect them. That makes their control easier. The photon is a "hard particle". The electron could also be possible to use in that mission. 

But making quantum entanglement between electrons is not without problems because the electron is larger, and there is more space than a photon. And that makes the electron act like a softball. And that makes it hard to synchronize two electron's oscillations. 

When computers act united, they work very effectively. The reason why quantum computers are dangerous is that they can calculate long induction series like Riemann's conjecture more effectively than regular computers. 

The quantum computer is similar to the binary computer group. The difference is that information is packed in physical particles called qubits in quantum computers. And its base is in the particle's superposition. The reason, why a quantum computer requires superposition and quantum entanglement is it must drive information from point A to point B without changes in that information. 

The neural computer, or binary computer group can operate as a virtual quantum computers. The AI-based central processing unit can share parts of the calculations with those binary computers. And each of them is handling part of the mission. The simplest example where engineers can use that virtual quantum system is to calculate linear calculations like series. 

The difference between a quantum and a neural computer is that a quantum computer calculates calculations simultaneously. The neural computer makes one part of the mission but then it sends the result forward. We can use computers in star topology networks as an example of simple neural and quantum computers. In the neural version, data travels through the network. And each computer breeds or processes the result that the computer gets. That thing makes this system the ultimate tool for calculating induction series and finding recursion in them. 

If we use network star topology as an example of a quantum computer. The central unit cuts the formula into pieces. And then it sends those parts to other computers. Those computers operate simultaneously with their bite. And then send that data back to the central unit. That makes this system an ultimate tool when calculating long induction series. Those series are easy to cut into pieces. 

But hybrid systems are even more effective. The term neural-quantum computer means. That in the single computer's place is a subnetwork or another network of computers. In that system, the multiple subnetworks are operating with the same problem. The neural networks can consist of quantum computers or the quantum network can involve the neural rings. 

The difference is that the quantum computer can calculate multiple calculations simultaneously. And that ability makes the quantum computer a powerful tool for calculating long series like Riemann's conjecture. The AI-based system can cut the calculations by using known points in the number line that the formula has given. 

The operating system just cuts the number line between known results that researchers got using a certain mathematical formula like Riemann's conjecture. That allows the computers can calculate simultaneously that series between thousand values. That makes this type of computer group faster than regular monolithic computers. 

https://en.wikipedia.org/wiki/Mathematical_induction

https://en.wikipedia.org/wiki/Recursion

https://en.wikipedia.org/wiki/Qubit