A Note On Quantum Information and Entanglement*
1- Quantum Information
Quantum Information is a way to prove the validity of challenging physical experiments. How should computer scientists benefit from the concept of quantum computing until quantum computers are invented? In fact, Quantum Computing alone is not interested in making new Computing Devices. It is becoming a radical Scientific Industry revolutionary journalist to change our point of view of real problems in the world and to find solutions much faster than the present.
However, since it must be used in many information processing tasks, the production and processing of multilateral quantum entangled systems is at the top of the hot topics of recent years [1–8]. Much of the work in the basic quantum technologies, such as quantum cryptography, communications, and computers, requires multi-partite entangled systems such as GHZ, W [9,10]. It can be suggested that the quantum entanglement criteria reflects the different properties of the systems. Many recent research has been done in entanglement and its related disciplines like entanglement measures and majorization, etc. [11–20].
Some swarm-based solutions are included in the current work to speed up machine learning procedures. An example of these studies is entitled “Entanglement-Based Machine Learning on a Quantum” by Cai et al., [21].
Yamomoto and his group have also carried out various studies on the implementation of artificial neural networks in the perspective of Quantum Knowledge Theory [22].
Some of the problems listed above are concepts introduced by the predictions of quantum computers of the last of the contemporary classical cryptography concepts. For example: Quantum Cryptography. The concept of post-quantum cryptograhy has also been introduced along with the opening of the quantum age in the field of cryptography. The basis of this theoretical background is the concept of linear algebraic lattice. According to the current assumptions, a quantitative solution algorithm of lattice-based encryption algorithms has not yet been found. If one of these algorithms can be broken in a quantum way, the post-quantum cryptography concept will be among the dusty shelves of science history.
As it turns out, there are studies using the Quantum Information Theory infrastructure that are closely related to many current fields of Computer Science and Engineering, or it is foreseen that they can be done in a perspective of 10 years. According to the reports of US-based research institutes, which make a respectable trend analysis like Gartner, it is possible to enter the life of a general commercial Quantum Computer in 10 years technological perspective.
2- History of Quantum Information Theory
In the past centuries, since the world has been viewed as a deterministic view, real-world problems have been dealt with as if to solve a large clock-like system. Along with the spread of computers in our lives, our understanding of science, mathematics, and collecting has also changed. We are no longer using computers to solve problems, we are building, programming and using computers.
For example, for different types of problems, such as DNA analysis, language processing, and cognitive science, data needs to be transformed to optimize concepts such as compression and error correction of information. It is important to consider concepts such as calculation efficiency, game theory and economic problems. Computer Science has also changed the aims of these and similar fields. In mathematical research, more emphasis is given to efficiency and studies in computer-related fields such as InformationTheory, Graph Theory and Statistics have been accelerated. The question of defining P or NP problems defined between Clay Millenium problems is trying to explain the oldest puzzle in mathematics: what makes it difficult to find a proof?
When computers came out for the first time, it was hard to imagine that anyone but a few would turn out to be such a big commercial success. This commercial success also led to an intellectual revolution. For example, the invention of the concept of entropy, which is the theoretical basis for data compression or error correction, has been possible with this revolution. This concept was used for the understanding of thermodynamics and steam machines in the 19th century. Claude Shannon is II. He used the concept of entropy in practice during his work on cryptography in Bell Laboratories during World War II. This situation has not only occurred in computer science problems. For example, Einstein used the concept of clock synchronization in his experiments. The problem of clock synchronization was conceived as one of the major industrial problems for that period in terms of automating the movements of trains. In some instances, science has followed technological developments and changed the point of view of the problems after these discoveries.
The story of Quantum Informatics is similar. Quantum mechanics was invented at the beginning of the 20th century and the modern form currently used is known since 1930. However, the idea that quantum mechanics can provide a computational advantage has been put forward much later. This idea emerged when physicists attempted to simulate the quantum mechanics on computers. When they tried it, they faced another problem. A single system (photon polarization) can be described by two complex numbers (the amplitude values of the vertical and horizontal components of polarization), whereas for n systems the number is represented by 2n rather than 2powerof(n) complex numbers, and additionally the measurement only reveals n bits. Physicists have developed closed-form solutions to overcome this problem and need a variety of estimation techniques in cases where the number of examined states increases.
The exponential system state space of quantum mechanics has helped them to realize how large and interesting environments nature actually has in terms of computing science. Until then, the concepts of quantum mechanics that were difficult to explain were seen as restrictive items and deficiencies. For example, the Heisenberg Uncertainty Principle was often seen as a restriction on measures. The concept of entanglement as “quantum-based” or philosophy of quantum mechanics has not been studied in detail in terms of operation as much as quantum computation and quantum cryptography concepts were invented in the 1970s and 1980s.
In 1982, Richard Feynman introduced the concept of quantum information, or in other words, the use of quantum mechanical concepts in the field of computational science. The idea is that even if a quantum computer can be invented, it can simulate quantum mechanics much more effectively than conventional computers. This model was formalized by David Deutsch in 1985. It has also been shown for the first time by Deutsch (a computation of two-bit XOR values) that a quantum mechanical computer will run faster than a conventional computer. Similar studies have been shown to accelerate over time, for example, by Peter Shor in 1994 when the problem of integers division into multipliers can be done at polynomial time.
In the 1970s, it was suggested by Stephen Wiesner, then a Ph.D. student at that time, that Heisenberg’s restrictions on measurement could be used to prevent the learning of confidential messages, but the important scientific journals at that time rejected this work. This issue was first published in 1984 by Charles Bennett and Gilles Brassard as a quantum cryptographic structure. Until 1991, this study was not taken seriously in the scientific mosque until it was realized by them again. The most important discovery at this point is the formation of the infrastructure of quantum mechanics and quantum cryptography, which are described in the 1950s. It has also been shown that many problems related to the theory of information can be solved much faster by quantum mechanical concepts. Example, Grover’s search algorithm, etc. [1]
Today, studies such as Google, Nasa, and many other prestigious universities and research institutes around the world are at full speed. Work on how to physically generate quantum computers has also accelerated in recent years.
*You can find full text of this survey on arxiv: arXiv preprint arXiv:1704.05058 https://arxiv.org/abs/1704.05058
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