The new particle is so fundamental that it's almost unbelievable.

Scientists have discovered semi-Dirac fermions, quasiparticles that behave as massless in one direction and massive in another, inside a crystal of ZrSiS. This discovery, achieved using advanced magneto-optical spectroscopy, could revolutionize technologies like batteries and sensors while opening new avenues for quantum physics research. (Artist’s concept.) Credit: SciTechDaily.com (ScitechDaily, “Totally Unexpected” – Scientists Stumble Upon a Bizarre Particle That Defies the Rules)

16 years ago researchers predicted a particle that has mass when it travels in another direction. And it has no mass. While it travels in another direction. The particle has mass and no mass at the same time. So particles are massive and massive at the same time. 

The name semi-Dirac particle means that the Dirac equation can introduce that particle when it travels to another direction and the Dirac equation cannot introduce that particle when it travels into another direction. 

The new semi-Dirac particle is one of the most fundamental findings in physics. The new particle has mass when it travels in one direction. But it has no mass when it travels in the opposite direction. The semi-massless particle can answer the question of why photons have no mass. The half-massless particle is also interesting because it can introduce how fields and other wave movements turn into one particle. The term "Dirac-particle" means particles that spin 1/2. And the Dirac equation can introduce them mathematically.  

"Landau levels spectroscopy sheds light on semi-Dirac fermions at the crossing point of two nodal lines within a semi-metal material (Left: Fermi surface of a nodal-line crossing model, Right: Band structure of material). Credit: Yinming Shao/Penn State" ((ScitechDaily, “Totally Unexpected” – Scientists Stumble Upon a Bizarre Particle That Defies the Rules)

The semi-Dirac particle means that the Dirac equation can introduce it when it travels in another direction. But it cannot introduce a particle when it travels in another direction. Dirac equation cannot introduce particles that spin is something else than 1/2 and that don't have mass. The photon spin is 1. That means the photon rotates a full round around its axle. That spin can explain why a photon has no mass. That spin makes it impossible for photons they touch the quantum field and interact with it. Or the photon cannot bound that quantum field inside it. 

The ring-shaped structure in the photon aims energy field over it and that keeps the energy balance in the photon. Because a photon gets as much energy as it delivers it cannot turn older. There is something that denies the semi-Dirac particle mass when it travels to another side. There is the possibility. That kind of ring-shaped quantum field makes the particle massless when it travels in another direction. The interesting thing is the question about the mass of that new particle when it's in a stable position. 

The new semi-Dirac particle causes ideas that maybe the Dark Matter particles the mysterious and hypothetical Axions are similar parts to this semi-Dirac particle. But can the particle have two masses? That means the particle can have mass when it travels in the universe. But the particle can have a different mass. While it travels in another direction. The reason for that can be that the quantum field packs to the other side of the particle. The particle that has mass while it travels in another direction and has no mass while it travels in another direction is the thing. That is a miracle. 

https://scitechdaily.com/totally-unexpected-scientists-stumble-upon-a-bizarre-particle-that-defies-the-rules/

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

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

AI gives superpowers to personal computers.

"Diffeomorphic Mapping Operator Learning, DIMON, a new AI framework, accelerates modeling by solving partial differential equations efficiently, reducing computation times from days to seconds. Tested in heart simulations, it promises transformative applications across engineering and science." (ScitechDaily, AI Breakthrough Solves Supercomputer Math on Desktop PCs in Seconds)

"The adaptable technological solution has the potential to revolutionize engineering designs." (ScitechDaily, AI Breakthrough Solves Supercomputer Math on Desktop PCs in Seconds)

"A breakthrough in artificial intelligence is making it possible to model complex systems—like how cars deform in crashes, how spacecraft endure extreme conditions, or how bridges withstand stress—at speeds thousands of times faster than before. This innovation allows personal computers to tackle massive mathematical problems that once demanded the power of supercomputers." (ScitechDaily, AI Breakthrough Solves Supercomputer Math on Desktop PCs in Seconds)

"The new AI framework offers a versatile and efficient method for predicting solutions to challenging mathematical equations. These equations are crucial for modeling phenomena such as fluid flow or electrical current behavior in various geometries, commonly encountered in engineering and design tests." (ScitechDaily, AI Breakthrough Solves Supercomputer Math on Desktop PCs in Seconds)

New AI gives table computers the supercomputer abilities. The idea is that the system uses the complete and complicated models. 

That makes it unnecessary to begin all modeling processes from the beginning. The system can use models that some other computers have made. 

The idea is similar to the picture. So we can use mosaic pictures as an example. Developers make it by using ready-to-use sub-elements. The ability to use free elements is making data-handling operations more effective. That increases the power of regular computers. But it also fits in use of the supercomputers.

"A Revolutionary AI Framework: DIMON. Details about the research appear in Nature Computational Science. Called DIMON (Diffeomorphic Mapping Operator Learning), the framework solves ubiquitous math problems known as partial differential equations that are present in nearly all scientific and engineering research. Using these equations, researchers can translate real-world systems or processes into mathematical representations of how objects or environments will change over time and space." ((ScitechDaily, AI Breakthrough Solves Supercomputer Math on Desktop PCs in Seconds)

And the thing that can boost that ability is the memory handling tool that cleans memory when the model is ready. The system develops models as layers. Every single layer is an independent model. When the model is ready the computer can store it or give it to another computer. 

Then it can clean its memory. Then that system can receive the model that another computer has worked. And continues to develop or build the new model. In that model, the AI-based systems play ping-pong balls with models that they create as stages. In every stage, the system can connect more and more complicated objects into that layer. The system handles program data like Photoshop handles its layers. 

The image that the developer makes could be an example. The city area image. 

The developer or system can select items for that image from the data library. The system can use things like images of houses. That made for some other purposes. 

And that is the idea of object-oriented programming. The idea in C++ and similar programming languages is simple. 

They involve libraries of commonly repeating operations. That means the user of that language doesn't have to program things like simple calculations from the beginning. They must just load the 

Those libraries (like Stdio.h) deny the need to do basic things every time the programmer starts a new job.  

The programmer can use libraries that involve responses for the orders that the programmer writes. Using the programming language. 

The new AI-based model is a new and very advanced version of the old object-oriented programming. The system can collect complicated models from libraries. 

Oor from the net. And that makes it possible for the table computers to get steroids. The other thing is that the computer can take another computer to its work. The system can make the digital twin and download data to the other computer while it cleans its memory. The ability to clean memory while the system develops the model makes it more powerful. In that model, the model is developing in stages. 

When the system makes the new model it can transfer it to its digital twin. And the system can clean the memory of the first computer. The AI-based system can also call more computers to handle the operation. 

https://scitechdaily.com/ai-breakthrough-solves-supercomputer-math-on-desktop-pcs-in-seconds/

https://www.nature.com/articles/s43588-024-00732-2.pdf

https://pubmed.ncbi.nlm.nih.gov/39653845/

Entropy and wormholes.

The image above this text is the Gemini AI answer for the order to create an entropic room. 

The growing entropy destroys the system. We all hear that. When we think of quantum systems. Entropy is a disorder in which size grows. And the thing that makes entropy is the free space in the system. That allows energy travel in the system. 

The law of entropy is that when there is some entropy. That destroys the system. The growing entropy causes a situation in which even black holes will vaporize sooner or later. The entropy means that there are some kind of whirls also behind the event horizon. 

It's possible. That there is a hole in the singularity. Or maybe there is a tornado-shaped structure in the middle of the black hole event horizon. The thing is that even in the smallest structures in the universe is entropy. The disorder that breaks the system. 

When space around the system grows difference between energy levels between inside and outside grows. That makes energy move faster and faster out of the system. Pressing shell particles away.  

Sooner or later the system lost some of its particles. There comes a hole in the system and then that hole starts to grow. Growing space creates low-pressure and weaker electromagnetic fields. There is more space for the same mass of molecules or the same electromagnetic field. 

When we look at systems we can see that there are also many subsystems. The image of the lobby shows people who walk in there. Those people are subsystems. Their shoes and clothes are subsystems. Sweat droplets and every single atom are subsystems that form the entirety of that image. Steps on the floor cause oscillation and sound effects. The Sun causes heat effects. Sooner or later water can get routed in the concrete and that increases erosion. 

In quantum systems, the energy that goes into the system presses its particles away from their position. The entropy that grows is the problem that destroys quantum entanglements in quantum computers. That is the thing that destroys the universe. 

Mathematicians and other researchers try to develop models that make it easier to predict how entropy behaves in the system. The ability to create models of how the entropy grows in the system makes it possible to create more error-free quantum computers. 

The fractal tree can introduce the entropy spread in the system. Every part of it can include the Mandelbrot set. 

Julia set. Part of the Mandelbrot set. 

Mandelbrot set introduces how the entropy turns dominating. When the scale of the system turns smaller. 

The Sierpinski Carpet introduces how the role of subsystems grows when the scale of the system goes smaller. That means the subsystem's dominance rises over the main system. And that destroys the system. The sub-system turns more dominant. 

Fractals are tools that researchers can benefit from in the R&D process that make entropy prediction more easily and more accurate. The idea is that there is always a similar form in entropy. Entropy is the thing that should always follow a certain form. And maybe fractals can be used to predict the form of that growing disorder. 

The error-free Qauntum computer simply predicts the moment when the system starts to break and makes a backup copy of that thing. The internal parts of the system are not error-free. The system follows a black-box methodology. Outsider observers cannot see what happens in the system. Outsiders see only the solution that the system makes. 

The wormhole or Einstein-Rose bridge requires that the outer side in that system is at a higher energy level than its inner side. The idea of the wormhole is that the outside energy presses the structure and denies the loss of the particles. The wormhole is the quantum channel through space and time if it is long enough. In laboratories, researchers are made of acoustic and electromagnetic wormholes. But real gravitational wormholes are still theoretical. 

Entropy is actually a whirling substructure that forms someplace in the system.  Maybe sometimes those whirls can take position on the top of each other. That means there can be channels through those fractal structures. And if some wave or superstring travels through those whirls it locks them into that position. If that superstring has enough high energy level. 

That substructure makes the asymmetrical space in the system and that causes energy flow that destroys the system. Entropy is the thing. That denies us to see the future. It is one of the things that denies things like quantum teleportation. Or we cannot teleport complex systems. The problem is that when researchers aim things like laser beams to the object that beam can vaporize the object. The problem is that the laser ray is not compact enough. 

That allows some parts of molecules and atoms to jump away from that beam. In complex systems of teleportation, the wall of the quantum channel must be at a higher energy level than the internal structure. That pushes those particles into the form. But the problem is that the sub-particles of the system will change their place. We can vaporize the system, and turn it into a particle cloud. But we cannot know how to sort them back together. 

Or, maybe someday the quantum computer can solve that problem. It's possible that. The quantum computer gives a number for each particle in the quantum system. Then it shoots particles through the quantum channel or wormhole. Then it just collects that puzzle into its original form. Those serial numbers must not be real numbers. The imaginal numbers with multiple mathematical imaginal parts can cause that someday complex system teleportation to be possible. 

https://www.quantamagazine.org/what-is-entropy-a-measure-of-just-how-little-we-really-know-20241213/

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

New systems allow researchers to follow cellular communication wirelessly.

"To improve biosensing techniques that can aid in diagnosis and treatment, MIT researchers developed tiny, wireless antennas that use light to detect minute electrical signals in liquid environments, which are shown in this rendering. Credit: Marta Airaghi and Benoit Desbiolles" (ScitechDaily, MIT Scientists Harness Light To Wirelessly Monitor Cellular Electrical Signals)

The new systems use light to read cellular electric signals. Electric impulses on the cell's protein shell control the ion pumps. Ions are the key element in chemical communication between neurons and other cells. The immune system requires those ions to detect cells. That doesn't work as it should. 

The cell uses them to take in and remove nutrients. Ion pumps play a key role in communication between neurons and other cells. 

It's possible. Neurons can communicate with individual cells benefiting the electric vortex at the ion pumps. Or it can receive and deliver neurotransmitters through those ion pumps. 

That can make it possible to create new types of medical treatments and new ways to control and boost our wealth. In the most interesting ways to think they can exchange information between the cells and computers. And what if you can give orders to bacteria in your stomach that they must transport food straight away and not drive it in your body? That thing can save your life in the case of poisoning. 

The ability to communicate with bacteria will be an incredible advancement in microbiology. That thing might be closer than ever. The bacteria can used to produce virus antigens that can be covered with immune activators. That makes it possible to program the immune system to fight against new diseases. Genetically engineered bacteria can also create cancer cells' shell proteins. 

Those proteins can offer the possibility to activate the immune system to detect harmful cells in the human body. 

That makes immune cells destroy tumors and cancer cells in the early stage of cancer. In that stage cancer is a group of individual cells that are easy to kill. In that stage, they don't form tumors yet. 

In the future, it may even be possible to order bacteria out of the body. But before researchers can communicate with bacteria and give them orders, they must read its messages. That thing requires new tools that can observe 

https://scitechdaily.com/mit-scientists-harness-light-to-wirelessly-monitor-cellular-electrical-signals/

The future of communication.

"Computer scientists have created D-REC, an edge caching optimization method that uses a “digital twin” to forecast and improve data storage in wireless networks, thereby boosting speed and reliability." (ScitechDaily, New Method Improves Wireless Network Speed and Reliability)

"The new edge caching optimization method, called D-REC, makes use of a computational modeling technique called a digital twin. A digital twin is a virtual model of a real object. In the case of D-REC, the digital twin is a virtual model of a defined wireless network – whether that’s a cellular network or a Wi-Fi network." (ScitechDaily, New Method Improves Wireless Network Speed and Reliability)

“The method can be applied to any wireless network, depending on the system administrator or network operator’s needs,” says Liu. “D-REC can be adjusted depending on the needs of the user.” (ScitechDaily, New Method Improves Wireless Network Speed and Reliability)

"In D-REC, the digital twin takes real-time data from the wireless network and uses it to conduct simulations to predict which data are most likely to be requested by users. These predictions are then sent back to the network to inform the network’s edge caching decisions. Because the simulations are performed by a computer that is outside of the network, this does not slow down network performance." (ScitechDaily, New Method Improves Wireless Network Speed and Reliability)

One of the most interesting things that the data storage and transmitting technology is to use the digital twin to simulate the system and its capacity. The digital twin is a complex simulation whose effectiveness depends on the variables that the system can use. The system can calculate its capacity using digital twins. The digital twin also can help to see, if somebody tries to steal information. 

The system can use multiple complex models to uncover attacks. The system can use the digital twin of the environment. And see if the data travels in dangerous routes. This thing is effective if the data transmitters use coherent maser- or laser-based communication. If somebody puts a sensor in a laser or maser ray, that can be a coherent radio wave. That affects the strength of the beam. 

The system calculates how powerful the received signal's strength should be. And then. It compiles that data to the real strength of the received signals. If there are remarkable differences, the system can doubt that something is not right. Then it can choose the other receiver. In that kind of system, the transmitter's power can be one value, which improves security. The transmitting power gives a new dimension to the encryption. It can used as one value for the encryption algorithm.  If the power of the received signal is wrong, the receiving system cannot get the right value for the decryption key. 

This means that if the transmitting power is 340 W, the receiver gets a value of 340 for the decryption algorithm. Or the router routes the message to gate 340. 

There a receiving computer knows the right decryption key.  The receiving system cannot match the decryption key. If the gate is wrong. And cannot open the message. This thing increases the physical key to the information. 

And, if somebody tries to steal information from data cables, that decreases the power of the transmission. The system can give a warning.  If the transmission values are not. What they should be. If somebody wants to eavesdrop on laser or coherent radio waves, the eavesdropper must put the sensor in the laser or maser beam. 

And that's why the system can see if there are some points where the operator can make that thing. That kind of system can transmit information to the data tower or other receivers with high accuracy. The digital twin can see things like particles and weather and calculate their effect on communication. 

Things like structured light, multichannel transmissions, and quantum encryption are tools that should make data transmissions more secure and faster. The system can use multiple channels and frequencies to transmit information. 

In the new types of radio-based communication, the system can share data to multiple frequencies. The system shares data packages between multiple frequencies. And then sends them at the same time. Then receiving system knows how to collect that information from the pieces using the serial numbers. Those serial numbers can contain the serial numbers of the message and their position in the message. 

"Structured light technology, enhanced by spatial dimensions and machine intelligence, boosts information transmission and detection. Researchers have achieved significant advancements in data encoding and transmission, using spatial nonlinear conversion to maintain low error rates and high accuracy under challenging conditions. Credit: Zilong Zhang, Wei He, Suyi Zhao, Yuan Gao, Xin Wang, Xiaotian Li, Yuqi Wang, Yunfei Ma, Yetong Hu, Yijie Shen, Changming Zhao" (ScitechDaily, How Structured Light and AI Are Shaping the Future of Communication)

In standard laser communication, the system switches the laser on and off. When the laser is on, the value is 1. And when the laser is off the value is 0. And that is a standard way to use laser in binary communication. 

Structured light is the way to manipulate light. The system can also use other ways to benefit light than just switching lasers on and off. The structured light also makes it possible to benefit things like the depth of the surface and the point of the surface to transmit information. 

 "Structured light is the process of projecting a known pattern (often grids or horizontal bars) onto a scene. The way that these deform when striking surfaces allows vision systems to calculate the depth and surface information of the objects in the scene, as used in structured light 3D scanners."

The system can be more effective. If a laser can use two or more receiver points on the surface. When the laser system switches the point, where it transmits information, it must not switch on and off. 

Point 1 has a value of 0, and point 2 has a value of 1. The mirror can switch the point where it aims the laser ray. And that makes the system faster and more secure. The system can also benefit the depth or distance of the layer. 

The idea of those new communication systems is that they involve a physical part of the message. Things like the distance between the transmitter and receiver and the point. Where information comes from can mean something to the system. If the distance between the receiver and transmitter is wrong, the system might not open the message. The idea is that the part of the security algorithm is the physical distance between the receiver and the transmitter. 

https://scitechdaily.com/how-structured-light-and-ai-are-shaping-the-future-of-communication/

https://scitechdaily.com/new-method-improves-wireless-network-speed-and-reliability/

The neuroscientists get a new tool, the 1400 terabyte model of human brains.

"Six layers of excitatory neurons color-coded by depth. Credit: Google Research and Lichtman Lab" (SciteechDaily, Harvard and Google Neuroscience Breakthrough: Intricately Detailed 1,400 Terabyte 3D Brain Map)

Harvard and Google created the first comprehensive model of human brains. The new computer model consists of 1400 terabytes of data. That thing would be the model. That consists comprehensive dataset about axons and their connections. And that model is the path to the new models or the human brain's digital twins. 

The digital twin of human brains can mean the AI-based digital model. That consists of data about the blood vessels and neural connections. However, the more advanced models can simulate electric and chemical interactions in the human brain. 

This project was impossible without AI. That can collect the dataset for that model. The human brain is one of the most complicated structures and interactions between neurotransmitters, axons, and the electrochemical interaction between neurons. Making a model of those interactions is an impressive achievement. 

The human brain's digital twin is a useful tool to research neural disorders and how to deal with that thing. The new comprehensive model of the human brain offers new tools for neurosurgeons in practice and simulations about the effect of certain operations and medical treatments, and the system can introduce what effect certain blood vessels have in the brain. 

The structure of the brain and neural connections make it possible that the brain never gets stuck. Even if one route is locked or stuck, brains can pass that point. And that means that even if we think of some problem, brains can still watch the environment. 

But the most interesting thing. That this system can make, is the artificial intelligence that acts like the human brain. The AI can create the needed number of databases and their connections. The modern AI can handle database structure with 200 billion connections. The number of human neurons is a little mystery because neurons can create virtual neurons using their connections. Those virtual neurons act like one neuron. And they can interact with their database. 

If researchers can model this system in the virtual entirety or software-based artificial intelligence on a large scale, that thing can create new types, of more effective AI. 

https://scitechdaily.com/harvard-and-google-neuroscience-breakthrough-intricately-detailed-1400-terabyte-3d-brain-map/

New research tells why mice are so teachable.

 

"Scientists discovered that mice display strategic behavior in learning tasks by engaging in exploratory actions that initially appear as mistakes. Through experiments, the study showed that mice test hypotheses and adjust their strategies based on the outcomes, challenging the traditional view of animal errors as mere mistakes. This insight into animal cognition not only sheds light on how mice think but also draws parallels with nonverbal human learning, paving the way for further studies on the neural basis of strategic thinking. Credit: SciTechDaily.com" (ScitechDaily, Challenging Our Views of Cognition – New Johns Hopkins Test Reveals That Mice Think Like Babies)

New research tells us that mice think like babies. This thing makes us understand why rodents are so maddening. And why they successfully avoid things like traps. That thing makes rodents so successful and harmful. This new research opens a new view of cognition. 

Rodent's brains are not very big. And they are a good example of animals that should not be successful. But their way of using their brains is effective. The effective way to think determines the success of the individual. 

The reason why children's cognitive actions are so effective is that their brains are like empty paper. And everything that they do is new. Because they have no memories their brains have fewer memory blocks or databases. They must connect, and learning means the ability to interconnect databases. In children's brains, there is more free space in memory cells, neurons must not spend as much time finding space from memory cells. 

New EEG systems. Along with AI allows the collection of information from large populations. The neuro-implated microchips allow researchers to observe neural functions deeper in brains. During those missions, the system can observe animals and humans in the natural environment. 

The new systems can also decode the EEG. And maybe, quite soon, R&D teams can see memories from computer screens. The knowledge about brain functions tells about the advancement of thinking. And why children are so productive and creative. But when we turn into adults. We lose our productivity somewhere. 

That is one of the most interesting ways to model the thinking process. The number of neurons is not the only thing that is necessary for successful thinking. Successful operation is conducted from successful thinking. We can say that thinking is the theoretical prediction for physical actions. 

The thing. What determines the success of the thinking process, is if it benefits the species. Babies think otherways than adults. They are more curious and more unprejudiced than adults. And they will test and try things more often than adults. For babies, every day is full of new things. And that thing is making babies successful in learning things. 

The same thing makes mice and probably rats sometimes maddening. Those clever rodents learn how to void traps. And that makes them successful learners. The same models can be used to make intelligent robots to learn things. The robot can try something alone, and then it can estimate if its model is successful. In those cases, there are parameters, that determine if the system has successfully done its missions. 

https://scitechdaily.com/challenging-our-views-of-cognition-new-johns-hopkins-test-reveals-that-mice-think-like-babies/