Computers reduce human effort and also focus on increasing the performance to push the technology forward. Many approaches have been devised to increase the performance of the computers. One such way is to reduce the size of the transistors used in the systems. Another very significant tactic is to use quantum computers. It proved to be very effective when used to factor large numbers. It was found that it could decrypt codes in 20 minutes which took billions of years with classical computers. This was a great motivation for focusing on this topic. A quantum computer allows a ‘quantum bit’ or qubit to have three states − 0, 1, and 0 or 1. The last state is the coherent state. This enables an operation to be performed on two diverse values at the same time. However, this brings out a problem of decoherence. It becomes difficult to perform the computation using quantum computers. A quantum computer is desired to have five capabilities - scalable system, initializable state, long decoherence time, universal set of quantum gates, high efficiency measurements. Architecture of the quantum computer is the new research area. It is affected by quantum arithmetic, error management, and cluster-state computing. Without it, the quantum algorithms would not prove to be as efficient. To fully utilize the power of a quantum computer, the algorithms used should be based on quantum parallelism. This paper discusses a few of the basic concepts used in quantum computing briefly. The paper also focuses on different architectures of quantum computer available in literature. However, the problem of a practical large-scale quantum computer still persists.
Computers reduce human effort and also focus on increasing the performance to push the technology forward. Many approaches have been devised to increase the performance of the computers. One such way is to reduce the size of the transistors used in the systems. Another very significant tactic is to use quantum computers. It proved to be very effective when used to factor large numbers. It was found that it could decrypt codes in 20 minutes which took billions of years with classical computers. This was a great motivation for focusing on this topic. A quantum computer allows a ‘quantum bit’ or qubit to have three states − 0, 1, and 0 or 1. The last state is the coherent state. This enables an operation to be performed on two diverse values at the same time. However, this brings out a problem of decoherence. It becomes difficult to perform the computation using quantum computers. A quantum computer is desired to have five capabilities - scalable system, initializable state, long decoherence time, universal set of quantum gates, high efficiency measurements. Architecture of the quantum computer is the new research area. It is affected by quantum arithmetic, error management, and cluster-state computing. Without it, the quantum algorithms would not prove to be as efficient. To fully utilize the power of a quantum computer, the algorithms used should be based on quantum parallelism. This paper discusses a few of the basic concepts used in quantum computing briefly. The paper also focuses on different architectures of quantum computer available in literature. However, the problem of a practical large-scale quantum computer still persists.
Computers reduce human effort and also focus on increasing the performance to push the technology forward. Many approaches have been devised to increase the performance of the computers. One such way is to reduce the size of the transistors used in the systems. Another very significant tactic is to use quantum computers. It proved to be very effective when used to factor large numbers. It was found that it could decrypt codes in 20 minutes which took billions of years with classical computers. This was a great motivation for focusing on this topic. A quantum computer allows a `quantum bit' or qubit to have three states - 0, 1, and 0 or 1. The last state is the coherent state. This enables an operation to be performed on two diverse values at the same time. However, this brings out a problem of decoherence. It becomes difficult to perform the computation using quantum computers. A quantum computer is desired to have five capabilities - scalable system, initialized state, long decoherence time, universal set of quantum gates, high efficiency measurements. Architecture of the quantum computer is the new research area. It is affected by quantum arithmetic, error management, and cluster-state computing. Without it, the quantum algorithms would not prove to be as efficient. To fully utilize the power of a quantum computer, the algorithms used should be based on quantum parallelism.
Computers minimise human effort while also focusing on improving efficiency in order to advance technology. To improve machine efficiency, a variety of methods have been invented. Reducing the size of the transistors used in the systems is one such process. The use of quantum computers is another important strategy. When used to factor large numbers, it proved to be very accurate. It was discovered that it could decode codes in 20 minutes, while traditional computers took billions of years. This provided excellent motivation for concentrating on this topic. A quantum machine may have three states for a quantum bit, or qubit: 0, 1, and 0 or 1.The coherent state is the final state. This allows you to perform an operation on two different values at the same time. This, however, raises the issue of decoherence. Using quantum computers to perform the computation becomes difficult. A quantum computer should have five features: a scalable device, an initializable state, a long decoherence time, a universal set of quantum gates, and high measurement efficiency. The architecture of quantum computers is a new field of research. Quantum arithmetic, error management, and cluster-state computing also have an effect on it. The quantum algorithms would not be as effective without it. The algorithms used should be based on quantum parallelism to completely harness the power of a quantum computer. This paper briefly explores a few of the fundamental principles in quantum computing. The paper also looks at the various quantum computer architectures that have been proposed in the literature. The problem of building a functional large-scale quantum computer, however, remains unsolved.
Quantum algorithms for problems such as integer factorization and database search have spurred great interest in quantum computation. However, the construction of scalable quantum computers has proved to be extremely difficult. Among the challenging requirements that must be fulfilled in the “standard model” of quantum computation, one must be able to initialize qubits into known pure states. In addition, quantum computers must be protected from noise due to unwanted interactions with their environment.
This work is concerned with two theoretical issues motivated by these difficulties. First, I analyze the efficiency of an algorithm for an alternate model for quantum computation that is motivated by bulk nuclear magnetic resonance. In such ensemble systems, the initial state is not a fiducial pure state, but is instead a maximally-mixed density operator. The algorithm that I consider allows one to estimate the free energy of arbitrary spin-1/2 lattice models. To determine the efficiency of this algorithm, I calculate the computation time required to estimate the free energy to bounded error as a function of the lattice size. In the absence of stochastic fluctuations in the measurement output, it is found that the algorithm is efficient. However, evidence is presented that suggests that the algorithm becomes exponentially sensitive to fluctuations as the lattice size increases.
While techniques such as quantum error-correcting codes and decoherence-free subsystem encodings have been devised to mitigate errors due to unwanted environmental couplings, these methods require many additional qubits or complicated encodings. Here, I investigate a simple approach to reduce errors in the quantum search algorithm due to a collective decoherence model. This method takes advantage of the freedom inherent in compiling the search algorithm into fundamental gates. Transition rate calculations and more rigorous quantum master equation simulations are carried out for small-qubit instances to contrast the performance of the original and modified algorithm. It is shown that the expected computational effort can be reduced by 22% for selected five-bit instances of the quantum search algorithm. While this approach does not constitute a general strategy for quantum error-correction, it illustrates the importance of judicious gate design in mitigating decoherence.
Quantum computing is emerging as a revolutionary paradigm in the field of computing, promising an exponential leap in computing power and problemsolving that challenges even the most advanced supercomputers of the classical era.At the heart of this revolution lies the peculiarity of the quantum world, where subatomic particles can exist in multiple states simultaneously, a phenomenon known as superposition, and entangle their states in a way that defies classical logic.It is this capacity for superposition and entanglement that gives quantum computing its disruptive power.One of the most intriguing properties of quantum computing is its ability to process information using Qubits, the quantum analogues of classical bits.While a classical bit can only be in a single 0 or 1 state, a Qubit can simultaneously represent a 0, a 1, or any superposition of these states, allowing multiple calculations to be performed in parallel.This massively parallel processing capability is the basis for the potential superiority of quantum computers over their classical counterparts in a wide range of applications.The architecture of quantum computers is inherently different from classical computers.While the latter use transistors to store and manipulate information in bits, quantum computers use Qubits, which can be implemented in a variety of physical systems, such as atoms, ion traps, photons, superconductors or nuclear magnetic resonance.The manipulation of the Qubits is carried out through quantum gates, fundamental operations that transform the quantum state of the Qubits and allow quantum calculations to be carried out.Furthermore, to maintain quantum coherence, the control and isolation of the quantum system from its environment is crucial, posing significant challenges in terms of designing and building scalable and robust quantum systems.
In recent years, quantum computing (QC) research has moved from the realm of theoretical physics and mathematics into real implementations. With many different potential hardware implementations, quantum computer architecture is a rich field with an opportunity to solve interesting new problems and to revisit old ones. This paper presents a QC architecture tailored to physical implementations with highly mobile and persistent quantum bits (qubits). Implementations with qubit coherency times that are much longer than operation times and qubit transportation times that are orders of magnitude faster than operation times lend greater flexibility to the architecture. This is particularly true in the placement and locality of individual qubits. For concreteness, we assume a physical device model based on electron-spin qubits on liquid helium (eSHe). Like many conventional computer architectures, QCs focus on the efficient exposure of parallelism.We present here a QC microarchitecture that enjoys increasing computational parallelism with size and latency scaling only linearly with the number of operations. Although an efficient and high level of parallelism is admirable, quantum hardware is still expensive and difficult to build, so we demonstrate how the software may be optimized to reduce an application's hardware requirements by 25% with no performance loss. Because the majority of a QC's time and resources are devoted to quantum error correction, we also present noise modeling results that evaluate error correction procedures. These results demonstrate that idle qubits in memory need only be refreshedapproximately once every one hundred operation cycles.
The pace with which technology is developing is increasing day by day. Depending on the various types of computer architecture different types of computers are being developed every day which are used as smart computers nowadays. In this paper, we are going to focus on Quantum computers along with their architectures. Quantum computers are like supercomputers that can solve a lot of problems in a very short span of time which is not possible by standard computers. In comparison to microcomputers, it is hundred times quicker. Its foundation is quantum physics.