Quantum systems are the border between reality and imagination.

"Researchers have unveiled a method for passing fragile quantum states between separate photon sources, a key function for future quantum networks. The result suggests that scalable, tamper-proof communication may be closer than expected. Credit: Shutterstock," (ScitechDaily,  Scientists Teleport Information Between Distant Photons for the First Time)

Researchers made the first long-distance quantum teleportation between two photons. In that type of communication, the system transmits wave movement between two photons. The system creates a channel between those photons, and then the wave movement transports information between them. This type of system provides a secure data transmission method between photons that oscillate at the same frequency. When the wave movement travels through that channel, it puts another photon into resonance. This is called superposition. And quantum entanglement. 

Before data transmission is possible, the system must synchronize those photons. Or, they must be put into superposition. And then. The system starts to transmit data. The biggest problem with long-distance quantum entanglement. And a long-distance quantum  data transmission. It is to keep the quantum channel between those photons open. If that quantum channel is closing. That causes resistance. That destroys data. The system transmits through that channel. This is the thing. That makes quantum networks safer.

One of the reasons that makes quantum teleportation and quantum systems hard to create is the error correlation. For successful error correlation, the system must find the error. And. Check the quantum computers' calculation can take thousands of years. Another thing. That makes quantum networks and quantum computers hard to make. It is: how to calculate quantum states. The quantum computer requires a quantum simulation. So that the system can prepare itself for quantum data transmission and quantum computing. 

When we think about complicated quantum algorithms and calculations. We must realize one thing. The problem can be effective. Or it can be non-effective or virtual. Even if we think that all quantum fields have an effect on quantum computers and quantum networks. The reality is that the field must have an energy level that is high enough. Or, the field’s state must be strong enough that it has an effect. All fields. It does not have a strong enough force. that they can affect the quantum networks. So the system must select only fields that have an effect. Another thing is that the form of the field must be right, so that it can resonate with the system. 

The simulator must know all values. That has an effect on the system. So that it can create a simulation.  The system uses those simulations to adjust the quantum system’s particle energy levels and interactions. Data can travel in quantum entanglement. Only from a higher-energy particle. To a lower energy particle. When those particles reach the same energy level that forms the quantum soliton, that destroys the quantum entanglement. The quantum soliton or standing wave causes energy reflection in the quantum wire, which transports information. 

"Researchers at Swinburne have developed a fast new way to check whether certain quantum computers, specifically Gaussian Boson Samplers, are actually producing the results they claim, without waiting millennia for a supercomputer to verify them. Their method can flag errors in minutes on an ordinary laptop, revealing unexpected noise in a recent experiment that would otherwise take 9,000 years to validate. Credit: Shutterstock." (ScitechDaily, If Quantum Computing Is Solving “Impossible” Questions, How Do We Know They’re Right?)

Quantum versions of derivative and integral calculus will be the holy grail for quantum technology. 

The ability to calculate quantum field interactions with particles. And backward, particle interactions with the quantum field would make it possible to create those quantum systems. The reason why. That is very hard to make. Is the energy lost in that interaction? The particle is not absolutely smooth. There are small hills and valleys. So, the field will be separated from the particle. And that means the oscillation will not transmit perfectly between fields and particles. 

We could compare those calculations.  A little bit with the derivative. And integral calculus functions. The integral function is the mathematical model. That is used to check integrals. The integral function is the formula that is the opposite of the derivative function. Or the way to calculate derivatives is backward. The problem with quantum calculations is that they are not basically mathematical or physical formulas. The physics formula describes particles as stable or static objects, or it describes objects as fields. 

The quantum formula introduces objects as the oscillating entireties called “quantum”. Sometimes the quantum calculations are described as systems that must introduce some kind of foam, which changes its state and form indefinitely. The system must take into account. Things like. The energy level and energy type of the system. The position and direction of the particle in the quantum field make the effect. The system must handle multiple variables, like the internal and external interactions. 

And this makes those algorithms very complicated. The biggest difference between quantum and regular systems is this: in regular systems, Data travels in wave movement. Wave motion can be described as a traveling field. In quantum systems, data is connected to physical particles. 

So, the quantum versions of derivative and integral formulas would be the holy grail for quantum technology. The system must calculate the interface between particles and fields around them. The system must notice things. Like natural. Or artifact quantum field interaction with the data transporters and receivers. Things like changes in quantum fields that things. Like, maybe gravitational waves and cosmic rays can affect quantum systems. 

https://scitechdaily.com/if-quantum-computing-is-solving-impossible-questions-how-do-we-know-theyre-right/

https://scitechdaily.com/scientists-teleport-information-between-distant-photons-for-the-first-time/

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

Quantum computers and nanorobots are coming. And we don't even know all their abilities.

  Quantum computers and nanorobots are coming. And we don't even know all their abilities. 

In the future, we can see nanorobots everywhere. Researchers created artificial bacteria that can create electricity from wastewater. And those bacteria can give electricity to the small nanomachines that clean the water and observe, what type of waste is in that wastewater. Those small machines can look like rice there is a tunnel through them. And the system can pump water through that tunnel where there is an active carbon filter and maybe a UV system that destroys bacteria. 

Those bacteria also can deliver energy into nanotechnical microprocessors. And in some visions, the supercomputer of the future can be a group of nanotanks that flow in wastewater. And the users communicate with those systems by using WLAN. 

The users can use things like quantum computers over the net by using their cell phones. And that thing makes it possible to share the quantum and supercomputer capacity through the internet. That means the large machine can share its power with small machines. 

The shape of the morphing network is not sharp. And that means networked computers, but networked cell phones can also form morphing neural networks. And the morphing neural network can consist of cell phones, computers, and drones that are connected under one entirety.

The nano- and mini-machine swarms are a good example of morphing and scalable networks. If those swarms require new abilities only one member of that swarm must be reprogrammed. And then that member scales that information through the entire swarm. That kind of technology requires new tools. Those tools must be secured and fast-reacting. They require self-development ability. 

Quantum computers are tools that can make the future more complicated than we expected. They are game changers and work as physical layers for highly advanced AI-based systems. Machine learning is the tool used in fusion experiments. However, machine learning gives new abilities to control quantum systems and molecules for nanotechnical applications. 

Researchers are working hard with nanotechnology, biotechnology, morphing neural networks, AI, and quantum computing. Those systems will change the world more than nobody expected. The complex AI requires powerful computers to run those systems. Things like nanorobot swarms require ultra-secure data transmissions. If there are some kind of problems with communication, the nanomachine swarms can do something that they should not do. 

Quantum computers allow systems to create new and complex molecules because they can drive complicated simulations. The system must simulate how atoms and molecules touch each other. And then it must turn that simulation into rea, or physical world.  

ENIAC

While a CAD/CAM (Computer-Aided Design/Computer-Aided Manufacturing) system creates something extremely complicated, like very long molecules that are required in medicines. It must react very fast to non-predicted effects. And that thing requires extremely fast computing. When lasers and microwaves are manipulating sub-atomic scale systems they must send energy impulses with very high accuracy. 

When people are talking about quantum computers they must realize that those systems are weapons themselves. That means quantum computers can break any code that is made by using binary computers. And we know why some nations are interested in that technology. 

We can use the history of binary computers as a model when we try to predict the future of quantum computers. Maybe pocket-size quantum computers will not come next year to the supermarkets. But we must realize that maybe that day is coming sooner than we think. We can compare the quantum computers to ENIAC, the first electronic, and programmable computer from the year 1945. 

Those quantum computers are also the first of their kind. They are powerful systems. And when we are looking at the image of the supercomputer from the 1980s who believes that someday we carry a system with many times higher calculation capacity in our pockets. Same way size of the quantum computers will turn smaller. When the number of those systems is rising the price will decrease. And that's why we must prepare for that thing. 

https://scitechdaily.com/generating-electricity-from-wastewater-bioengineered-bacteria-produce-power/

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