| viXra.org > Data Structures and Algorithms > 1801 |
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| viXra.org > Data Structures and Algorithms > 1801 |
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[4] viXra:1801.0334 [pdf] submitted on 2018-01-25 10:09:43
Authors: George Rajna
Comments: 54 Pages.
As cloud storage becomes more common, data security is an increasing concern. [34] Scientists of the National Research Nuclear University MEPhI (Russia) have proposed a scheme for optical encoding of information based on the formation of wave fronts, and which works with spatially incoherent illumination. [33] A joint China-Austria team has performed quantum key distribution between the quantum-science satellite Micius and multiple ground stations located in Xinglong (near Beijing), Nanshan (near Urumqi), and Graz (near Vienna). [32] In the race to build a computer that mimics the massive computational power of the human brain, researchers are increasingly turning to memristors, which can vary their electrical resistance based on the memory of past activity. [31] Engineers worldwide have been developing alternative ways to provide greater memory storage capacity on even smaller computer chips. Previous research into two-dimensional atomic sheets for memory storage has failed to uncover their potential— until now. [30] Scientists used spiraling X-rays at the Lab) to observe, for the first time, a property that gives handedness to swirling electric patterns – dubbed polar vortices – in a synthetically layered material. [28] To build tomorrow's quantum computers, some researchers are turning to dark excitons, which are bound pairs of an electron and the absence of an electron called a hole. [27] Concerning the development of quantum memories for the realization of global quantum networks, scientists of the Quantum Dynamics Division led by Professor Gerhard Rempe at the Max Planck Institute of Quantum Optics (MPQ) have now achieved a major breakthrough: they demonstrated the long-lived storage of a photonic qubit on a single atom trapped in an optical resonator. [26] Achieving strong light-matter interaction at the quantum level has always been a central task in quantum physics since the emergence of quantum information and quantum control. [25]
Category: Data Structures and Algorithms
[3] viXra:1801.0279 [pdf] submitted on 2018-01-22 08:16:07
Authors: George Rajna
Comments: 26 Pages.
Behind every self-driving car, self-learning robot and smart building hides a variety of advanced algorithms that control learning and decision making. [17] Quantum computers can be made to utilize effects such as quantum coherence and entanglement to accelerate machine learning. [16] Neural networks learn how to carry out certain tasks by analyzing large amounts of data displayed to them. [15] Who is the better experimentalist, a human or a robot? When it comes to exploring synthetic and crystallization conditions for inorganic gigantic molecules, actively learning machines are clearly ahead, as demonstrated by British Scientists in an experiment with polyoxometalates published in the journal Angewandte Chemie. [14] Machine learning algorithms are designed to improve as they encounter more data, making them a versatile technology for understanding large sets of photos such as those accessible from Google Images. Elizabeth Holm, professor of materials science and engineering at Carnegie Mellon University, is leveraging this technology to better understand the enormous number of research images accumulated in the field of materials science. [13] With the help of artificial intelligence, chemists from the University of Basel in Switzerland have computed the characteristics of about two million crystals made up of four chemical elements. The researchers were able to identify 90 previously unknown thermodynamically stable crystals that can be regarded as new materials. [12] The artificial intelligence system's ability to set itself up quickly every morning and compensate for any overnight fluctuations would make this fragile technology much more useful for field measurements, said co-lead researcher Dr Michael Hush from UNSW ADFA. [11] Quantum physicist Mario Krenn and his colleagues in the group of Anton Zeilinger from the Faculty of Physics at the University of Vienna and the Austrian Academy of Sciences have developed an algorithm which designs new useful quantum experiments. As the computer does not rely on human intuition, it finds novel unfamiliar solutions. [10] Researchers at the University of Chicago's Institute for Molecular Engineering and the University of Konstanz have demonstrated the ability to generate a quantum logic operation, or rotation of the qubit, that-surprisingly—is intrinsically resilient to noise as well as to variations in the strength or duration of the control. Their achievement is based on a geometric concept known as the Berry phase and is implemented through entirely optical means within a single electronic spin in diamond. [9]
Category: Data Structures and Algorithms
[2] viXra:1801.0274 [pdf] replaced on 2022-01-20 20:44:07
Authors: Zhengjun Cao, Lihua Liu
Comments: 7 Pages.
The Deutsch-Jozsa quantum algorithm is of great importance to modern quantum computation, but we find it is flawed. It confuses two unitary transformations: one is performed on a pure state, and the other on a superposition. In the past decades, no constructive specification on the unitary operator performed on involved superposition has been found, and no experimental test on the algorithm has been practically carried out. We think it needs more constructive specifications on the algorithm so as to confirm its correctness.
Category: Data Structures and Algorithms
[1] viXra:1801.0100 [pdf] submitted on 2018-01-08 22:06:09
Authors: Yuly Shipilevsky
Comments: 12 Pages.
We reduce integer factorization problem to the NP-hard problem of minimizing
a quadratic polynomial with integer coefficients over the integer points
in a quadratically constrained two-dimensional region.
Next, we reduce integer factorization problem to the problem of enumeration
of vertices of integer hull of a special two-dimensional rational polyhedron,
solvable in time polynomial by Hartmann's algorithm.
Finally, as we find a polynomial-time algorithm to solve an NP-hard problem,
we conclude that P = NP
Category: Data Structures and Algorithms
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