Limitations to the performance of a quantum computer arising from direct interaction between qubits are considered, and the basic scaling laws (with the computation time and the number of qubits) are established for the specific example of the quantum Fourier transform algorithm. These results should be relevant for several of the currently proposed quantum computer systems, where the dominant interaction is of the magnetic dipole-dipole type, in the limit of many qubits and long computation times.
Limitations to the performance of a quantum computer arising from direct interaction between qubits are considered, and the basic scaling laws (with the computation time and the number of qubits) are established for the specific example of the quantum Fourier transform algorithm. These results should be relevant for several of the currently proposed quantum computer systems, where the dominant interaction is of the magnetic dipole-dipole type, in the limit of many qubits and long computation times.
This paper explores the limitations that interaction between the physical qubits making up a quantum computer may impose on the computer's performance. For computers using atoms as qubits, magnetic dipole-dipole interactions are likely to be dominant; various types of errors which they might introduce are considered here. The strength of the interaction may be reduce by increasing the distance between qubits, which in general will make the computer slower. For ion-chain based quantum computers the slowing down due to this effect is found to be generally more sever than that due to other causes. In particular, this effect alone would be enough to make these systems unacceptably slow for large-scale computation, whether they use the center of mass motion as the 'bus' or whether they do this via an optical cavity mode.
The effect of off-diagonal interactions between quantum bits is studied in a simple quantum computer algorithm designed to calculate the sum of two n-bit numbers. Scaling laws are derived numerically for the dependence of the error on the number n of bits, the strength of the interaction, and the calculation time. The case of diagonal interactions, previously studied in the context of the quantum Fourier transform algorithm, is also considered. No substantial differences are found between the off-diagonal and diagonal forms of the interaction: in both cases, the errors accumulate almost coherently, despite the fact that the system's free evolution is constantly being interrupted by the logical gates, which scramble the coefficients of the wave function. Some comments on the possibility of using ``field-insensitive'' atomic states in ion-chain quantum computers are also given.
In many candidate designs of solid-state quantum computers, interactions between qubits are limited to a small number of neighboring qubits. Taking into account this limitation we describe how quantum algorithms can be executed efficiently on these designs. We illustrate our results with the quantum Fourier transform for which linear depth networks are obtained. The concepts presented in this work can be applied to all quantum algorithms to reduce considerably the coherence time needed for their execution.
A methodical analysis of the basic problem related to quantum calculations of parameters of physical systems was made. Emphasis is placed on the physical principles of the operation of a quantum computer, with an emphasis on the fact that simultaneous access to all quantum states is important in quantum computing, which allows the simultaneous change of the quantum state from all superpositions in the qubit system. Emphasis is placed on the fact that in quantum algorithms the Fourier transform and the Hadamard transform are the basic operations - as a simple discrete Fourier transform. The reader's attention is drawn to the fact that quantum computing is primarily implemented in quantum objects with the properties of elementary NOT gates and controlled CNOT, which can be implemented on a Mach-Zehnder interferometer using the phenomena of photon interference and rotation of its polarization vector. Despite the progress of conventional computers, the need for the development of quantum computing is due to the technological limitation due to the dimensional quantization of the electronic spectrum and the exponential increase in the time of calculations by classical algorithms when the volume of data increases. However, the widespread use of quantum computers is limited by a number of problems. This is, first of all, insufficient accuracy and high sensitivity to external influences that can destroy the quantum state. Therefore, to increase the accuracy of calculations on a quantum computer, the calculation algorithm must be repeated a certain number of times, and to avoid the destruction of the quantum states of the qubit, low temperatures are used.
Quantum computing tries to exploit entanglement and interference to process information more efficiently than the best known classical solutions. Experiments demonstrating the feasibility of this approach have already been performed. However, finding a really scalable and robust quantum computing architecture remains a challenge for both, experimentalists and theoreticians. In most setups decoherence becomes non-negligible when one tries to perform entangling gate operations using the coherent control of qubit-qubit interactions. However, in this proceedings we show that two-qubit gate operations can be implemented even without qubit-qubit interactions and review a recent quantum computing scheme by Lim et al. [Phys. Rev. Lett. 95, 030505 (2005)] using only single photon sources (e.g. atom-cavity systems, NV colour centres or quantum dots) and photon pair measurements.
Synthetic Aperture Radar (SAR) has played an important role in Earth observation, with applications in disaster monitoring, agriculture, forestry, ice surveillance, defense, and planetary exploration. The reconstruction of SAR images is a costly operation that uses Fourier Transform, while quantum computing has some key advantages that potentially enhance the algorithm to make it faster. Therefore, in the first part of the thesis, a major image processing method used in SAR systems is studied, known as the Range Doppler Algorithm (RDA). RDA is implemented on a simulated data set and a real data set from ICEYE Oy. In the second half of the thesis, quantum computing basic is studied and reviewed, including qubits, 1-qubit gate and 2-qubits gates, as well as the Quantum Fourier Transform (QFT) that are specific to replace the classical Fourier Transform. A framework for implementing the Range Doppler Algorithm (RDA) on a quantum computer, referred to as the Quantum Range Doppler Algorithm (QRDA), is proposed. In addition, the required resources under ideal quantum-computing assumptions are analyzed, including time complexity (algorithmic scaling) and space complexity (the number of qubits required). Lastly, the potential applicability of the proposed. QRDA in the context of current quantum device, Noisy Intermediate-Scale Quantum (NISQ) machine, is discussed.