The new type of binary star can be behind the strange radio bursts.

"Artistic illustration showing the radio pulses emitted by the binary star system: a white dwarf in orbit around a red dwarf. Credit: Daniëlle Futselaar/artsource.nl" (ScitechDaily, Mysterious Space Signals Went Unexplained for Years – Astronomers Just Found the Star System Behind Them)

The binary star the red dwarf orbits the white dwarf is behind the mysterious long-period transients, LPT. The LPT signal is similar to a fast radio burst, FRB. But it has less energy. And it lasts longer. Now the white dwarf is the reason for that kind of radio burst that lasts in minutes. A white dwarf is a remnant of a solar-type star. Its gravity and magnetic fields are weaker than neutron stars. 

The magnetic field around that star remnant is forming of the plasma interaction. The plasma that rotates around the white dwarf creates a magnetic field around that planet-size but more massive object. The dwarf planet Quaoar forms its magnetic field similar way. And that magnetic field forms a system around that dwarf planet in the Kuiper belt. 

If Quaoar were closer to the Sun. That ring system would not exist because the solar wind blows those bites away. In that case, the weak magnetic field that plasma forms around Quaoar can trap those particles around it only because the solar wind is so weak. 

This kind of phenomenon is possible. Only in stable conditions at the edge of the solar system. We cannot make models about asteroids and their rings using the same models all the time. In an asteroid belt, that kind of ring system is not possible. Asteroids can have rings in the very far away from the Sun. 

A similar effect can be possible around neutron stars. In those cases, the effect is much more powerful than around dwarf planet Quaoar because neutron stars' gravity is more powerful than Quaoars weak gravity. 

For a long time, researchers have wondered why objects that must be solid and dead have an extremely strong magnetic field. The answer can be in the plasma around the object. The plasma whirls around the object. In that case, the plasma acts as a rotor. And the object itself acts as the stator. 

"Artist impress of Quaoar rings. Credit: Paris Observatory" (ScitechDaily, Space Mystery: Unexpected New Ring System Discovered in Our Own Solar System)

There is the possibility. In neutron stars. The neutrons that spin in the same direction participate in the magnetic field's formation. Lightweight neutron stars also have things like "neutron liquid" between their core and shell. That thing makes the strong endemic magnetic field that surrounds the magnetars. 

But it's possible. Heavy neutron stars may not involve that "neutron liquid". The neutron liquid viscosity is the same as iron. The structure of that material is pure neutrons. Those neutrons act like quantum balls in ball seas. And that makes the neutron star's shell move faster or in another direction than the neutron star's core. 

Those neutrons form the quantum rolls that make magnetar's extremely powerful magnetic field possible. In magnetar, the plasma and internal structure form the double field that breaks any records in the power of those fields. The outside energy pushes those neutrons on its shell into the neutron net or neutron lattice. 

Heavy neutron stars might not have that neutron liquid. The lack of neutron liquid makes the heavy neutron star's structure solid. So, that means the heavy neutron star's magnetic field forms similarly. As dwarf planet Qauaoar magnetic field. There is exotic quark material inside the neutron stars. We can think that this exotic material is like powder, that cannot move those neutrons. The quark material's particle size is too small. That neutron shell cannot freely orbit around it. And gravity pushes that shell against the quark material. 

The whirling plasma around the structure creates the plasma generator. In a plasma generator, the plasma pike forms the plasma axle or stator. And plasma whirls around it. Form a structure, that acts as a generator. 

That causes questions about those heavy neutron stars. That is: can the neutron star exist without a magnetic field? If a neutron star with a solid structure is in a cosmic bubble that causes a situation that the plasma generator around it is gone. But then if that happens pressure against that structure ends. And it can explode neutron stars. 

Asteroid, or dwarf planet Quaoar shows that the plasma whirls around the object can have the same effect as Earth's core. The black hole's magnetic field forms also in the same way as Quaoar's magnetic field. That dwarf planet is too small that it can have a liquid core. The plasma that its weak gravity traps forms a magnetic field that traps very small particles around them. 

Same way. A black hole's only known interaction is gravitational. 

If we think of the interactions with black holes themselves. The plasma around the black hole forms its magnetic field. 

Magnetic fields accelerate particles inside them. When a red dwarf faces a white dwarf's magnetic field it causes interaction where particles from the red dwarf impact with particles in white dwarfs magnetic fields. That causes a very strong energy release. Those energy releases are always similar. But their strength and length can be different. 

https://www.helsinki.fi/en/news/mathematics-and-science/finnish-researchers-have-discovered-new-type-matter-inside-neutron-stars

https://sciencesprings.wordpress.com/2024/01/04/from-the-university-of-helsinki-helsingin-yliopisto-fi-via-phys-org-further-evidence-for-quark-matter-cores-in-massive-neutron-stars/

https://scitechdaily.com/mysterious-space-signals-went-unexplained-for-years-astronomers-just-found-the-star-system-behind-them/

https://scitechdaily.com/space-mystery-unexpected-new-ring-system-discovered-in-our-own-solar-system/

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

The AI requires powerful microchips.

"By directly leveraging light signals received from distributed acoustic sensing systems, the proposed photonic neural network architecture provides massive gains in accuracy and efficiency over conventional electronic computations. Credit: N. Zou (Nanjing University), edited

Imagine fiber optic cables acting as vast sensor networks, detecting vibrations for everything from earthquake warnings to railway monitoring. The challenge? Processing the enormous data flow in real-time."(ScitechDaily, This AI Uses Light Instead of Electricity and It’s Mind-Blowingly Fast)

"Traditional electronic computing struggles, but researchers have merged machine learning with photonic neural networks, using light instead of electricity to process distributed acoustic sensing data at incredible speeds." (ScitechDaily, This AI Uses Light Instead of Electricity and It’s Mind-Blowingly Fast)

AI is an algorithm and physical platform combination just like all other computer solutions. Running computer programs is impossible without microchips. The problem with complicated algorithms is that they require so much computer power that the system requires truck-sized systems. And those systems require lots of energy. The system can use morphing neural networks that make the algorithms lighter for individual computers. But the paradox is this. 

The more powerful computers make those morphing neural networks more powerful. That is important for data security. 

More powerful computers can break codes that weaker computers make. And that causes the weapon race in microchip research. Fast microchips make those systems more effective. Another paradox is that effective systems make it possible to run more complex algorithms. So advances in AI and algorithms follow the same route as other computer programs. More effective microchips allow developers to develop more complicated programs that require more calculation power. 

That kind of system uses lots of power. In electricity-based microchips, resistance causes very big problems. Resistance causes vibration and data loss. The answer can be superconducting computers but those systems require very big coolers. Or material that can be superconducting at room temperature. It's possible to make room-temperature superconductors. Using very high pressure. 

But if the pressure system's shell is broken. Pressure causes terrible danger. In pressure superconducting systems. Pressure anchors those particles in their places. 

Maybe, nanotechnical, small-size tubes where the nano-diameter wire travels can allow researchers to create a safe pressure system. That system removes vibrations from the wire that goes inside it. 

Another way to make the system is to use the photons. The photonic neural network where light replaces electricity can sense if something touches the light fiber or cuts the laser ray. Outside effects. Pressure causes curves in laser ray trajectories if they travel in optic fiber. And the sensor sees that thing. That improves data security. The system can also sense things like seismic wires and changes in electromagnetic fields. 

The binary system can use photons in two ways. The different light wavelengths like blue, and red can be zero and one. The system can determine that a certain lux level is one.

Below a certain lux level is zero. The photonic computer can use CCD chips or photovoltaic cells as receivers. The photonic microchip keeps the temperature in the system lower. 

"Distributed Acoustic Sensing (DAS) is an advanced technology used for infrastructure monitoring. It detects tiny vibrations along fiber optic cables that can stretch for tens of kilometers. DAS has become essential for applications like earthquake detection, oil exploration, railway monitoring, and submarine cable surveillance. However, these systems generate vast amounts of data, creating a major challenge: processing it quickly enough for real-time use. Without rapid data processing, DAS loses effectiveness in scenarios where immediate responses are crucial."(ScitechDaily, This AI Uses Light Instead of Electricity and It’s Mind-Blowingly Fast)

"To tackle this, researchers have turned to machine learning, particularly neural networks, as a way to speed up DAS data processing. While traditional electronic computing with CPUs and GPUs has greatly improved over time, it still struggles with limitations in speed and energy efficiency. Photonic neural networks, computing systems that use light instead of electricity, offer a breakthrough solution. They have the potential to process data far faster while using significantly less power. However, integrating photonic computing with DAS has proven difficult, mainly due to the complexity of DAS data and the need for precise signal processing." (ScitechDaily, This AI Uses Light Instead of Electricity and It’s Mind-Blowingly Fast)

https://scitechdaily.com/this-ai-uses-light-instead-of-electricity-and-its-mind-blowingly-fast/

From weather broadcasts to social algorithms.

"Aardvark Weather is an AI-driven system that dramatically reduces the time and computing power needed for accurate forecasts. Unlike hybrid models, it replaces the entire forecasting pipeline with machine learning, outperforming traditional systems using a fraction of the data. Credit: SciTechDaily.com" (ScitechDaily, Scientists Just Built an AI That Predicts Weather in Minutes – And It’s Beating the Best)

Researchers created an algorithm that predicts whether to beat the best.

The AI can handle thousands or even billions of objects at the same time. That makes it the ultimate tool for predicting things like solar storms and weather. The system can collect databases from certain things. Then it compiles observations about the thing that it should predict. 

If the AI should predict solar storms. It must collect information about solar activity like changes in its luminosity, and whirls and particle flow that predict solar storms. 

In the same way, weather prediction requires information about the airflows, temperature, and all other things that we can connect to storms and other types of weather.  The new AI- or algorithm makes it possible to create models with a very high accuracy. Those high-accurate AI-based systems can make models about magnetic fields, air flows, and many other things that can help to make the material, and other types of research. 

And then what about "Psychohistory"? That is a mathematical model of the human behavior. The system could predict a large human group's behavior. 

But maybe. Someday that hypothetical system could turn so accurate that it can predict a single person's behavior. 

The requirement for that kind of algorithm is that the system can collect trusted and confirmed data freely. 

Isaac Asimov introduced "Psychohistory" in his SciFi novel "Foundation". 

We can think. That Psychohistory is the mathematical model of social behavior. The idea is that similar algorithms that are used to predict weather can be used to predict human behavior. In this model. The system can predict the large human group's behavior in certain situations.

The system uses the Boltzmann constant and some other types of formulas to create models about human group's behavior. The system compiles things that it sees with data that it found from the net. The prediction forms when data. The system collects from sources, like historical documents is compiled with information that the sensors send to the large language model LLM. 

Then it can compile that behavior with data that it collects from the news and environment. The idea is that the system acts like an astronomical or weather-predicting AI that can calculate large gas mass behavior. The system cannot predict the single gas atoms place in the universe. But it can predict large gas masses like galactic supergroup behavior. 

But then we must realize that our knowledge of neural networks is higher than in Asimov's time. The system can collect data about neural connections in the human nervous system. Then it can compile that thing with people's nervous system that the system knows. The idea is that a person with a certain social background should behave in similar ways. If those social backgrounds are identical that means the nervous connections must be identical. 

But the fact is that. The system must also follow the social behavior that it can make profiles of people. That profile tells about the person's way of behaving in certain situations. So the system must collect data matrix about people. 

Then it must compile that data matrix with people who it observes. The problem with this type of behavior prediction cannot be trusted it must have the full and confirmed dataset that it can compile. Social algorithms are new things that can predict things like riots.  

https://scitechdaily.com/scientists-just-built-an-ai-that-predicts-weather-in-minutes-and-its-beating-the-best/

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

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

Does dark energy turn weaker?

"In physical cosmology and astronomy, dark energy is a proposed form of energy that affects the universe on the largest scales. Its primary effect is to drive the accelerating expansion of the universe. It also slows the rate of structure formation. Assuming that the lambda-CDM model of cosmology is correct, dark energy dominates the universe, contributing 68% of the total energy in the present-day observable universe while dark matter and ordinary (baryonic) matter contribute 26% and 5%, respectively, and other components such as neutrinos and photons are nearly negligible." (Wikipedia, Dark energy)

Does dark energy turn weaker? New evidence supports that model. What does that mean? That means that dark energy could have formed during the Big Bang. And the second thing is that dark energy can have a source in the material itself. The reason for that is when a particle's distance turns longer the dark energy turns weaker. So what could dark energy be? It could be energy that forms when some subatomic particles turn into wave movement. 

Or, it can be wave movement or radiation. Reflected in some subatomic structures. One suggestion is that dark energy forms in some short-living particles that turn wave movement just after forming. Those particles can be Higgs bosons that can form in a black hole's jets. Or they can be gluons that are released from atoms. Those particles turn into wave movement just after they are released. And it's possible that dark energy forms in those reactions. 

Or, it can be wave movement or radiation. Reflected in some subatomic structures. 

Sometimes its source is introduced as the strings between quarks. 

The dark energy mystery is one of the most important things in the cosmology. Dark energy is like cosmic hum without a visible source. 

That energy rips the universe into pieces. 

But when we think about dark energy and the universe's expansion. We face one very important thing. 

When the universe expands. The distance between the particles and objects grows. 

That means that the gravity effect between objects turns weaker. Some parts of the universe's accelerating expansion formed because the gravitational effect between galaxy superclusters turns weaker. Another thing is that. The interaction between galaxies in local- and superclusters and the interaction between superclusters is not similar. 

(Quanta)

In the universe: 

1) The universe itself expands. Because the distance between galaxy superclusters turns longer. 

2) The galaxy superclusters turn smaller because in those clusters gravity wins. 

3) When those galaxy superclusters turn smaller. That causes the effect. That the galaxy superclusters seem to move further away from each other. 

That causes the gravity effect between those clusters to turn into another type. The gravity field turns stronger. 

That turns the space's curvature steeper. 

And gravity potholes always turn deeper. The material will pack a denser form in the superclusters. And the distance between those material centers turns longer. The material between superclusters turns thinner but superclusters make the material denser. Also, those galaxies pump energy into the material. That is in galaxies. And especially between them.

 When galaxies are closer to each other the energy level in the galaxy supercluster is higher. But the space between superclusters turns colder. 

And that raises energy levels's difference. In and out of the galaxy superclusters and clusters. 

In a cluster. The energy level rises. And outside it, energy level decreases.

Superclusters turn hotter and space between those clusters turns colder. That increases energy flow out from those galaxy clusters. 

Galaxies are in collision course in the local galaxy clusters and sooner or later superclusters also fall into one giant galaxy. The expansion of the universe is the thing. What we see, when we observe interactions between superclusters.

But can some part of the universe's expansion be virtual? Inside galaxy clusters, gravitation wins. That means the galaxy clusters and superclusters turn smaller. That causes an effect where galaxies really move further away from each other. That means that the superclusters seem to be at a longer distance because galaxies inside travel into their gravity center. 

And that gravity center is not always in the middle of the cluster. The giant galaxy in the corner of the cluster can also be the gravitational center. And that means the gravity center is not always in the middle of the cluster. 

https://www.quantamagazine.org/is-dark-energy-getting-weaker-new-evidence-strengthens-the-case-20250319/

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

There is fear that the Chinese practice satellite dogfights.

Satellites play an important role in the military world. They can send target data to troops. And those systems allow commanders to control battles from another side of the world. 

That's why those military satellites are good targets for opponents. The ground-based anti-satellite missiles can destroy low-flying satellites. The radar satellites show their capacity. And those satellites are attractive targets for large-size anti-radiation missiles. Those missiles can be like the maximum-size version of the high-speed anti-radiation missiles HARM. 

That is normally used against radars and ECM systems. Also, photo-recon and communication satellites are good targets. The systems might have multiple optical, active radar, and semi-active homing systems that help them find their targets.  

Things like miniature shuttles, tell that the war is going to space. Those small, remote, or AI-controlled systems along with satellite swarms that are spaceborne drone swarms are tools that can endanger the regular satellites in space if war begins. 

And that's why. Those missiles and other systems are things, why some satellites will be equipped with anti-missile systems. Those weapons are planned to destroy incoming missiles. But they are useful against other satellites. 

We should know that China is interested in space military exploitation. Chinese satellites practiced at the Earth orbiter maneuvering in situations where they planned to use as killer satellites. Those satellites might use manipulator arms to throw targeted satellites into the atmosphere. 

But there is also quite good evidence that the Chinese test also things like centrifugal, or conventional machine guns, lasers, EMP weapons, and other types of tools to destroy other satellites. Laser weapons are things that make satellites effective tools against other satellites.

There are also tested capsules that close targeted satellites inside them. And then those capsules can carry satellites into the atmosphere. Or those capsules can have a small gun that pushes the captured satellite to Earth. Those capsules can also steal satellites from orbiters and return them to Earth. Those systems can return space junk or they can steal hostile satellites for research. 

The kill systems must not use things like recoil weapons. And that's why lasers are suitable for military satellites. The laser- or EMP systems can damage targeted satellites very badly. Those systems can also leave the targeted satellites in one piece. And that leaves those trajectories free for their own operations. If the ASAT weapon breaks a satellite it leaves thousands of small objects to orbiter. 

https://breakingdefense.com/2025/03/5-chinese-satellites-practiced-dogfighting-in-space-space-force-says/

https://www.defenseone.com/threats/2025/03/china-practicing-dogfighting-space-space-force-says/403863/

Image: 

https://www.tekniikkatalous.fi/uutiset/usan-avaruusvoimat-varoittaa-kiina-harjoittelee-satelliittien-lahitaisteluita-avaruudessa/8fb351f8-b72e-4854-b5fb-2ffbebbe4fbb

Quantum algorithm vs. binary algorithms.

Image: Quanta Magazine

The biggest difference between quantum and regular algorithms is that in quantum algorithms or in quantum networks data is connected to physical items. Sometimes people misunderstand the terms algorithms and networks. Networks are things. That transport data. 

Algorithms are programs that compute data. The term quantum algorithm can mean the calculation program that handles very long decimal numbers. That can involve tens of millions of numbers. The biggest problem with quantum computers is temperature. 

Those systems require so powerful coolers that they are factory-size systems. The compact-size quantum computers are on the door. But that means they are room-size monsters. Those systems require supercomputers that can operate their operational systems. A good and powerful alternative for supercomputers is the morphing neural network. 

That makes it possible that the qubit's values can be zero and one. This allows the system can make many operations at the same time. The binary network's values can be 0 or 1. The things called morphing neural networks can also make binary computers make many things at the same time. The system shares missions between different computers. 

The question is what is the most powerful computer in the world? The answer is interesting. The most powerful or fastest computer depends on the formula that the system should make. If we want to calculate simple calculations like 1+1 the most effective system is the credit-card size calculator. 

The thing. That decreases the quantum computer's power is that making the quantum entanglement there data travel in those systems takes time. That makes the quantum computer slower in the simple algorithms. Quantum computers are most powerful when the system must handle multiple variables and complicated formulas. 

The thing is that the quantum computer is not the best tool in the world. If we want to make simple calculations. 

There are calculations that the that the normal computer makes the universe's entire lifetime. 

And the quantum system makes that thing in minutes.

But then the morphing neural networks are tools that can make many things faster than the regular computer. The morphing neural network is a group of binary computers. That means they can share complicated series. With each other. 

The AI-based binary systems can jump over the zero points of Riemann's conjecture. So AI is the game changer in all of those things. 

Another thing is that. The new high-power binary systems are not like traditional binary systems. 

There the data goes in different wires. And that solves the "zero" problem. 

The zero problem means that the system must separate breaks in the data row from zero. 

And the system must also know. If the system is switched off. 

The system must also separate two zeros from each other. That's why there can be a different wire that shows when power is on and off. And data can travel in different wires.  The system must give serial numbers to ones and zeros. If they travel through different wires. It can sort them into the right order. 

Or there can be two low states in one wire. That allows the system to separate zeros from breaks. Low states like  3-5V are zeros. And 3-0 V is the break. And it accelerates the system's speed. 

And then the final question: which system breaks the RSA algorithm fastest? The morphing neural network or quantum computer? The RSA encryption uses Riemann zeta function. The morphing neural network can begin the code-breaking in the many points in the number series that Riemann zeta function creates. The system can use a number row that was created before. 

The code-breaking operation is not the same as calculating more numbers to the Riemann's series. Or a series of binary numbers. The idea of Riemann zeta function is that the formula generates only binary numbers. That thing means that it should protect the data. 

But if there are zero points that formula can generate also other than binary numbers. And the AI-based encryption systems can jump over those points. The Riemann's series can be programmed to the morphing neural network. Each computer takes the bite or sequence of that number row under the handle. 

https://www.quantamagazine.org/quantum-speedup-found-for-huge-class-of-hard-problems-20250317/

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

Researchers made the record-breaking breakthrough in Schrödinger's cat state.

Above is the image of the Schrödinger's cat state. A cat that is alive and carries information is closed in the cube that protects it. The cube itself doesn't carry information. And that makes Schrödinger's cat state seem dead. The outside observer cannot see the information that the cat carries in the hidden USB stick. 

Schrödinger's cat state is a thought experiment about a creature that is alive and dead, at the same time. That state can turn into a model where the particle or creature carries information and doesn't. That makes Schrödinger's cat state interesting. In quantum networks, data is stored in physical things called qubits. 

We can replace the words dead and alive. Using the words interesting and boring states. Interesting states carry interesting information. And boring states don't carry information. 

How do we protect physical information like letters? We simply put them inside the envelope. So that nobody sees it from the outside. So we can put the qubit into another particle so that outsiders cannot see the message transporter from the outside. The qubit can have both states 0 and 1 at the same time. That means. We can cover the qubit with zero and that makes it dead. Dead particles are not interesting. 

Because it doesn't carry information. Particles are alive when they are interesting. And interesting particles carry information. In the quantum system, the ability to steal information is physically denied. If somebody wants to read information from the qubit that destroys it. And the information will not reach the receiver. 

The model can be the qubit that is stored in another particle. The particle that carries qubit can seem "dead". So it doesn't carry information and the catcher will not see that particle as interesting. But the interesting or "alive" particle is inside that outside particle. The problem is to separate the right particles from the flow. The system must remove the particle or shell that covers the information carrier. 

The qubit is safe because it's single-use. If somebody tries to transfer data out from qubit that erases data immediately. Data that qubit carries is also encrypted for the receiving system's that it can route data to the right points. And if the wrong qubit transfers data in the wrong gate that destroys the information. 

The answer can be that the system knows what the right particle or information carrier looks like. When we think about cats that carry USB sticks we can use many cats in that work. But all of those cats don't carry important information. We can have workers who capture those cats and take the USB sticks. But then only. The most trusted workers can get the USB stick with ultra-high secure data. 

So the cat must have details like black and white fur. That the worker recognizes the cat that carries important data. The idea is that if the wrong worker takes the unauthorized USB stick it destroys the data immediately. Same way when a quantum system tries to download data from the qubit that destroys the data. The receivers must not try to download the wrong data types because that erases data from the qubit.

 https://scitechdaily.com/quantum-breakthrough-scientists-create-schrodinger-cat-state-with-record-long-lifetime/

https://en.wikipedia.org/wiki/Schr%C3%B6dinger%27s_cat