Genetic Quantum Algorithms Vixra-Books Pdf

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The more a quantum state is entangled with its partner the better the states. will perform in quantum information applications Unfortunately quantifying. entanglement is a difficult process involving complex optimization problems. that give even physicists headaches 7, A trio of physicists in Europe has come up with an idea that they believe would. allow a person to actually witness entanglement Valentina Caprara Vivoli. with the University of Geneva Pavel Sekatski with the University of Innsbruck. and Nicolas Sangouard with the University of Basel have together written a. paper describing a scenario where a human subject would be able to witness. an instance of entanglement they have uploaded it to the arXiv server for. review by others 6, The accelerating electrons explain not only the Maxwell Equations and the. Special Relativity but the Heisenberg Uncertainty Relation the Wave Particle. Duality and the electron s spin also building the Bridge between the Classical. and Quantum Theories, The Planck Distribution Law of the electromagnetic oscillators explains the. electron proton mass rate and the Weak and Strong Interactions by the. diffraction patterns The Weak Interaction changes the diffraction patterns by. moving the electric charge from one side to the other side of the diffraction. pattern which violates the CP and Time reversal symmetry. The diffraction patterns and the locality of the self maintaining. electromagnetic potential explains also the Quantum Entanglement giving it. as a natural part of the relativistic quantum theory. Genetic algorithms can improve quantum simulations 4. First Experimental Demonstration of a Quantum Enigma Machine 5. The first quantum enigma machine 6, Computing a secret unbreakable key 7. Physicists are putting themselves out of a job using artificial intelligence to run a complex. experiment 8, Quantum experiments designed by machines 9.
Moving electrons around loops with light A quantum device based on geometry 9. Quantum geometry 10, A light touch 10, A noisy path 11. Researchers demonstrate quantum surrealism 11, Physicists discover easy way to measure entanglement on a sphere 13. An idea for allowing the human eye to observe an instance of entanglement 14. Quantum entanglement 15, The Bridge 15, Accelerating charges 15. Relativistic effect 15, Heisenberg Uncertainty Relation 16. Wave Particle Duality 16, Atomic model 16, The Relativistic Bridge 16.
The weak interaction 17, The General Weak Interaction 18. Fermions and Bosons 18, Van Der Waals force 18, Electromagnetic inertia and mass 18. Electromagnetic Induction 18, Relativistic change of mass 19. The frequency dependence of mass 19, Electron Proton mass rate 19. Gravity from the point of view of quantum physics 19. The Gravitational force 19, The Higgs boson 20, Higgs mechanism and Quantum Gravity 20.
What is the Spin 21, The Graviton 21, The Secret of Quantum Entanglement 21. Conclusions 22, References 22, Author George Rajna. Physicists are continually looking for ways to unify the theory of relativity which describes large. scale phenomena with quantum theory which describes small scale phenomena In a new. proposed experiment in this area two toaster sized nanosatellites carrying entangled condensates. orbit around the Earth until one of them moves to a different orbit with different gravitational field. strength As a result of the change in gravity the entanglement between the condensates is. predicted to degrade by up to 20 Experimentally testing the proposal may be possible in the near. Quantum entanglement is a physical phenomenon that occurs when pairs or groups of particles are. generated or interact in ways such that the quantum state of each particle cannot be described. independently instead a quantum state may be given for the system as a whole 4. I think that we have a simple bridge between the classical and quantum mechanics by understanding. the Heisenberg Uncertainty Relations It makes clear that the particles are not point like but have a. dx and dp uncertainty, Genetic algorithms can improve quantum simulations. For the first time researchers have used genetic algorithms to reduce quantum errors in digital. quantum simulations Inspired by natural selection and the concept of survival of the fittest. genetic algorithms are flexible optimization techniques that can find the best solution to a problem. by repeatedly selecting for and breeding ever fitter generations of solutions. Now for the first time researchers Urtzi Las Heras et al at the University of the Basque Country in. Bilbao Spain have applied genetic algorithms to digital quantum simulations and shown that. genetic algorithms can reduce quantum errors and may even outperform existing optimization. techniques The research which is published in a recent issue of Physical Review Letters was led by. Ikerbasque Prof Enrique Solano and Dr Mikel Sanz in the QUTIS group. In general quantum simulations can provide a clearer picture of the dynamics of systems that are. impossible to understand using conventional computers due to their high degree of complexity. Whereas computers calculate the behavior of these systems quantum simulations approximate or. simulate the behavior, As a quantum technology digital quantum simulations face many of the same challenges that. confront the quantum computing field in general One such challenge is information loss due to. decoherence which occurs when a quantum system interacts with its environment. In order to protect quantum simulations against this loss scientists use quantum error correction. protocols which provide a kind of back up by storing information in entangled states of multiple. qubits using quantum gates, Storing information in an entangled state is a highly complex undertaking in the context of quantum.
error correction For a system with just 4 qubits and 7 gates the number of possible gate. arrangements climbs into the trillions Optimization techniques are used to sift through all of these. designs and find the architecture that minimizes the error. In the new study the researchers demonstrated that genetic algorithms can identify gate designs for. digital quantum simulations that outperform designs identified by standard optimization techniques. resulting in the lowest levels of digital quantum errors achieved so far. Besides reducing errors due to decoherence genetic algorithms can also reduce two other types of. errors in digital quantum simulations One type is the digital error created by the reduced number of. steps used for approximating the algorithms Another type of error arises from the imperfections in. the construction of each of the gates, As the researchers explain one reason why genetic algorithms perform so well is their adaptability. Just like natural selection adapts to changes in environmental conditions genetic algorithms. continually adapt to different constraints imposed by different quantum technologies. Genetic algorithms are characterized by different features adaptability and robustness Solano. told Phys org Their adaptability allows for a flexible and clever technique to solve different. problems in different quantum technologies and platforms The robustness of the algorithm yields. solutions that are resilient against errors which allows us to cancel different error sources Due to. these characteristics our work provides a new flexible tool in quantum simulations that allows us to. reduce the required physical resources while keeping the operation precision It also reduces the. total decoherence and digital error by seizing on the different unavoidable error sources to mutually. cancel each other, Genetic algorithms already have been used in a wide variety of applications such as finding the most. efficient electrical circuit design finding the mirror orientation that focuses the maximum amount of. sunlight onto a solar collector and designing antennas that are optimally tuned for detecting specific. types of signals, With help from genetic algorithms future quantum simulations are expected to be useful for gaining. a better understanding of complex physics designing novel materials and chemicals and solving. problems in machine learning and artificial intelligence. These techniques could be used to solve problems that require resources unaffordable for present. and future digital quantum simulations and gate based quantum computing by reducing and. optimizing them Solano said Also these techniques could easily decompose a problem into. quantum gates adapted to different quantum platforms and quantum technologies Finally these. techniques could also be applied to different problems in quantum computation and quantum. information such as the design of improved qubits for instance Needless to say quantum. simulations and quantum computing aim at the big picture artificial intelligence pattern. recognition design of new materials and chemicals solving complex problems in aerodynamics and. quantum field theories among many others 14, First Experimental Demonstration of a Quantum Enigma Machine. One of the great unsung heroes of 20th century science was a mathematician and engineer at the. famous Bell Laboratories in New Jersey called Claude Shannon. During the 1940s 50s and 60s Shannon laid the mathematical foundations for modern. communications and computing while building some of the first intelligent machines. Along the way he also made a major contribution to the theory of cryptography with a paper. entitled Communication Theory of Secrecy Systems published in 1949. In it he proved it possible to send a perfectly secure message provided that the encryption key is. entirely random and used only once Shannon s work is the mathematical proof that the one time. pad is a truly unbreakable form of encryption A critical condition is that the encryption key must be. at least as long as the message itself, The first quantum enigma machine.
Shannon s work assumes that the message is sent using conventional forms of transmission But in. the last 10 years quantum physicists have shown that it is possible to do better if the message is. encrypted using quantum rules In particular they have shown that in the quantum world a secure. message can be sent with a key that is significantly shorter than the message itself At least in. Researchers have christened this device a quantum enigma machine after the Nazi encryption. device that codebreakers led by Alan Turing cracked during the Second World War But the device. has been entirely theoretical, Until now Today Daniel Lum at the University of Rochester in New York State and a few pals unveil. an actual working quantum enigma machine for the first time. Their proof of principle device is capable of sending perfectly secure messages using a key that is. shorter than the message itself, A one time pad works by adding a random number to each digit in a message That makes the. message indistinguishable from a randomness It can only be read by subtracting the same random. numbers to produce the original message, The secrecy depends on the transmitter and receiver being the only people with the list of random. numbers And of course this list must be longer than the message itself. The quantum version of this process works by encoding information in a quantum object such as a. photon and then altering the state of the photon with a random operation The information can only. be retrieved by reversing the random operation So as long as only the transmitter and receiver. know the sequence of random operations the quantum key and that this key is used only once. the message is perfectly secure, However quantum theorists have shown that the quantum key can be exponentially shorter than. the message itself, Now Lum and co have built a transmitter and receiver that exploits this mechanism Their device.
consists of a photon gun that fires single photons through a kind of mask called a spatial light. modulator which superimposes information onto the photon s wavefront If this modulator consists. of an 8 x 8 array it can encode 64 bits of information At the same time the spatial light modulator. adds a random signal to the information it transmits. The important point is that all the information encoded on the photon is randomized by a random. signal So the sequence of random signals used for encryption can be significantly shorter than the. message itself, That allows an important twist Because the message is shorter than the key it is also possible to. send a new key for encoding the next message In this way the message and the new key are sent at. the same time and both are kept entirely secret, The receiver detects each photon using a light sensitive array that can pick out the pattern. superimposed on the photon It then subtracts the random signal leaving the original message. Lum and co have done exactly this We demonstrated the phenomenon with a proof of principle. experiment to lock 6 bits per photon while using less than 6 bits per photon of secret key says the. team In other words these guys have built the first proof of principle quantum enigma machine. That s an interesting result that has immediate application Physicists already use quantum. mechanics to send perfectly secure messages using a technique called quantum key distribution The. techniques for doing this are becoming increasingly advanced Indeed there are already commercial. Genetic Quantum Algorithms In the new study the researchers demonstrated that genetic algorithms can identify gate designs for digital quantum simulations that outperform designs identified by standard optimization techniques resulting in the lowest levels of digital quantum errors achieved so far 14 Quantum physicists have long thought it possible to send a perfectly secure message using

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