On Some Aspects of Quantum Computational Models
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Abstract
Quantum computing is concerned with computer technology based on the principles
of quantum mechanics, in which operations are performed at the quantum level.
Quantum computational models make it possible to analyze the resources required
for computations. Quantum automata can be classified thusly: quantum finite
automata, quantum sequential machine, quantum pushdown automata, quantum
Turing machine, and orthomodular lattice-valued automata. These models are useful for determining the expressive power and boundaries of various computational
features. In many cases, quantum models are more superior to classical models
in terms of language recognition. Thus, mathematical models of quantum computation can be view as generalizations of its physical models. Motivated from the
above-mentioned facts, we proposed a variant of two-way quantum finite automata
named two-way multihead quantum finite automata and determined its language
recognition capability.
Moreover, we have proposed a quantum analogue of classical queue automata by
using the definition of the quantum Turing machine and quantum finite-state automata. Further, we have also introduced a generalization of real-time deterministic
queue automata, the real-time quantum queue automata which work in real-time
i.e., the input head can move towards the right direction only and takes precisely one
step per input symbol. We have proved that real-time quantum queue automaton
is more superior than its real-time classical variants by using quantum transitions.
Classical systems are not robust and capable of describing quantum systems.
Some tasks that are impossible in classical systems can be realized in quantum systems. The most significant property ‘entanglement’ separates the classical world
from the quantum world. It is one of the most central topics in quantum information theory. In fact, quantum many-body systems cannot be simulated by classical
systems because of the increase in size of Hilbert space. In this Thesis, we have efficiently simulated well-known examples of matrix product state and designed their
quantum finite-state machines (QFSMs) using unitary criteria. Furthermore, the
proposed unitary criterion is used to analyze the dynamic behavior of matrix product states with quantum weightless neural networks.
The relationship between the theory of automata and logic had a great influence
on computer science. Linear temporal logic is a widely used method for verification
of model checking and expressing the system specifications. We have investigated
the relationship between quantum finite automata and linear temporal logic. It has
a variable free compact syntax, intuitive semantics, and it can be transformed into
automata more efficiently. Further, we have characterized the class of languages
accepted by quantum finite automata using linear temporal logic formulas.
In the past few years, the research has been focused on applying assets of quantum computing in various areas such as quantum cryptography, quantum machine
learning, quantum neural computation, tensor network theory, quantum dynamics to study behavior of biological sequences, weather forecasting, quantum optics,
quantum chemistry as well as others. We have modeled various ribonucleic acid (RNA) secondary structure loops such as hairpin loop, internal loop, and double
helix using two-way quantum finite automata. It has been proved that two-way
quantum finite automata can be designed for such structure loops in linear time
with bounded error.
Next, we have explored and examined the implications of the most successful
McEliece cryptosystem in post-quantum cryptography. The proposed cryptosystem
is based on extended Golay code in place of the usual Goppa code. Furthermore,
we have implemented a McEliece cryptosystem based on extended Golay code using
MATLAB.
In recent years, quantum computation is receiving much attention for its capability to solve difficult problems efficiently contrast to classical computers. Specifically,
some well-known public-key cryptosystems depend on the difficulty of factoring of
large numbers takes a long time. Furthermore, a quantum variant of classical factorization algorithm named Quadratic Sieve has been designed and its simulation
framework using high-level programming language Mathematica is constructed. Further, its simulation results are examined on a classical computer to get a feel of the
quantum system.
