A quantum computer is expected to solve some problems far faster than today's computers and may be a promising device with low power consumption.This computer is based on the physical theory of quantum mechanics.In the theory of quantum mechanics, quantum states and evolutions of quantum states are represented by vectors in a Hilbert space and unitary operators, respectively.A unitary matrix can then be regarded as an algorithm in the conventional computer.Since it is generally difficult to develop an arbitrary unitary matrix in a quantum system, quantum computation is carried out by combining elementary operations such as one-or two-qubit operations, where a qubit is the smallest unit of information in quantum computation.A unitary matrix is said to be performed effectively if there exists a quantum circuit composed of a polynomial number of elementary gates.Therefore, translating a unitary matrix into an efficient sequence of elementary gates is a fundamental problem in designing quantum circuits.In this dissertation, the problem involved in synthesizing minimal quantum circuits for carrying out any (large) quantum operation is described.The author considers two quantum systems, namely, the two-level quantum system and the d-level quantum system, where d is any integer greater than two.Here, the two-level quantum system can be regarded as a quantum mechanical analogue of conventional computation, and the d-level quantum system can be regarded as a quantum mechanical analogue of conventional multilevel logic.
A quantum computer is expected to solve some problems far faster than today's computers and may be a promising device with low power consumption.This computer is based on the physical theory of quantum mechanics.In the theory of quantum mechanics, quantum states and evolutions of quantum states are represented by vectors in a Hilbert space and unitary operators, respectively.A unitary matrix can then be regarded as an algorithm in the conventional computer.Since it is generally difficult to develop an arbitrary unitary matrix in a quantum system, quantum computation is carried out by combining elementary operations such as one-or two-qubit operations, where a qubit is the smallest unit of information in quantum computation.A unitary matrix is said to be performed effectively if there exists a quantum circuit composed of a polynomial number of elementary gates.Therefore, translating a unitary matrix into an efficient sequence of elementary gates is a fundamental problem in designing quantum circuits.In this dissertation, the problem involved in synthesizing minimal quantum circuits for carrying out any (large) quantum operation is described.The author considers two quantum systems, namely, the two-level quantum system and the d-level quantum system, where d is any integer greater than two.Here, the two-level quantum system can be regarded as a quantum mechanical analogue of conventional computation, and the d-level quantum system can be regarded as a quantum mechanical analogue of conventional multilevel logic.
The last two decades have seen an enormous increase in the computational power of digital computers. This was due to the rapid technical development in manufacturing processes and controlling semiconducting structures on submicron scale. Concurrently, the electric circuits have encountered the first signs of the realm of quantum mechanics. Those effects may induce noise and thus they are typically considered harmful. However, the manipulation of the coherent quantum states might turn out be the basis of powerful computers – quantum computers. There, the computation is encoded into the unitary time evolution of a quantum mechanical state vector. Eventually, quantum mechanics could enable one, for example, to read secret electronic messages which are encrypted by the widely employed RSA cryptosystem – a task which is extremely laborious for the current digital computers. This thesis presents a theoretical study of the coherent manipulations of pure quantum states in a quantum register, that is, quantum algorithms. An implementation of a quantum algorithm involves the initialization of the input state and its manipulation with quantum gates followed by the measurements. The physical implementation of each gate requires that it is decomposed into low-level gates whose physical realizations are explicitly known. Here, the problem is examined from two directions. Firstly, the numerical optimization scheme for controlling time-evolution of a closed quantum system is discussed. This yields a method for implementing quantum gates acting on up to three quantum bits, qubits. The approach is independent of the physical realization of the quantum computer, but it is considered explicitly for a proposed inductively coupled Josephson charge qubit register. Secondly, the techniques of numerical matrix computation are utilized to find a general method for decomposing an arbitrary n-qubit gate into a sequence of elementary gates, which act on one or two qubits. The results of this thesis help to improve the implementation of quantum algorithms. The quantum circuit construction developed in the thesis is the first one to achieve the asymptotically minimal complexity in the number of elementary gates. In context of acceleration of quantum algorithms we present a gate-level study of Shor's algorithm and show how to accelerate the algorithm by merging several elementary gates into multiqubit gates. Finally, the requirements set by the resulting gate array are compared to the properties of superconducting qubits. This allows us to discuss the feasibility of the Josephson charge qubit register, for instance, as hardware for breaking the RSA cryptosystem.
Simulating quantum mechanical evolutions in general is difficult on classical computers because the size of the Hilbert space grows exponentially with the number of particles involved in the simulations. However, a quantum computer, which obeys the laws of quantum mechanics, is believed to perform such simulations more efficiently. The time evolution operator, a unitary matrix, of a quantum system acts as a quantum gate changing the state of the system in time. Therefore, any computation on quantum computers can be interpreted as a unitary transformation on quantum state vectors. Generally, quantum gates are sufficiently simple operations so as to avoid difficulty in the physical implementation. The implementation of a general given computation represented by a unitary matrix on quantum computers requires finding an array of elementary quantum gates describing the desired computation. This describes a matrix decomposition problem known as the quantum circuit design problem. In this dissertation, we address the following questions concerning quantum circuit designs: How hard is it to find suitable quantum circuits for a given computation? What are the possible circuit design methods? How do we apply these to simulations of quantum problems, in particular quantum chemistry problems? To answer these questions, we categorize methods for designing quantum circuits as evolutionary algorithms and deterministic methods. We apply our developed group leaders optimization algorithm, an evolutionary algorithm, to find quantum circuits for known quantum algorithms and the simulation of molecular Hamiltonians. Then, we present a deterministic circuit design approach to produce universal circuits, which can be programmable. Moreover, we show how to use these programmable circuit designs within the quantum phase estimation algorithm to find eigenvalues of nonunitary matrices and study resonances in quantum systems. Finally, the quantum phase estimation algorithm is employed to efficiently solve ranking problems: in particular, multiple network alignment is considered to find the similarities between protein-protein interaction networks and molecular networks.
Diagonal unitary operators are commonly found in many quantum algorithms. They find application as analytical potential operators for quantum simulation, as well as for complex oracles used in quantum searches. However, in order to implement a quantum algorithm on a given quantum device, each operator must be decomposed into a sequence of fault-tolerant, device-level instructions. In general, to implement an n-qubit diagonal unitary {\\em exactly} on a quantum computer generally requires 2n+1−3 one- and two-qubit gates. However, for most practical implementations of diagonal unitaries, some degree of approximation will be necessary if the circuit is to be efficient. In this thesis we develop two complementary methods for the approximate synthesis of quantum circuits for diagonal unitaries. We show how to apply these techniques to real-space quantum simulation and show how efficient high fidelity quantum simulations can be implemented with low-depth quantum circuits.
Quantum computing and quantum information science are two recently discovered and rapidly growing fields of physics that show substantial promise in providing new and valuable technologies in the foreseeable future. Large-scale quantum computers, if ever realized experimentally, are likely to outperform their classical counterparts in a number of important computational tasks, the most important of which may be the accurate simulation of many-body quantum systems such as the ones encountered in physics, chemistry and life sciences. This thesis investigates the problem of controlling quantum systems for the purpose of performing quantum information processing tasks. The problem is approached from a theoretical and simulational viewpoint. The work contained here encompasses a range of levels of abstraction. Firstly, we discuss the decomposition of abstract multiqubit logic gates into sequences of simple elementary gates. Secondly, we study the local commutational properties of two-qubit gates using local gate invariants. Thirdly, we develop methods for the physical implementation of the elementary gates through the control of specific quantum systems, possibly in the presence of noise and decoherence. We present a new, almost optimal n-qubit gate decomposition based on the cosine-sine decomposition, which utilizes a likewise new intermediate quantum circuit structure we call a uniformly controlled gate. We then show how they can be used in constructing a general state transformation circuit. Both of the resulting circuits can be efficiently implemented using nearest-neighbor gates which makes their physical realization simpler. A local gate invariant is introduced which can be used to assess the suitability of two-qubit gates for serving as the entangling gate in elementary gate libraries. Finally, we develop numerical optimization methods for finding near-optimal control sequences for generating oneand two-qubit gates, both in closed quantum systems and in the presence of Markovian noise.
Quantum mechanics has proven its position as the primary theory for accurately describing microscopic domains. Numerous fields in physics utilize quantum mechanics to great effects, with one prominent application being quantum computing. Quantum computing extends the field of quantum mechanics to information theory, striving to perform computational tasks utilizing quantum phenomena with notably greater efficiency compared to classical alternatives. In this thesis, I will go through the basics required in the field of quantum computing. To understand quantum computing demands adapting a new type of matrix mechanical view. This involves considering Hilbert spaces, which are linear vector space having a well defined inner product. Hilbert spaces contain state vectors describing quantum states, as well as operators for altering and measuring these states. The dynamics of quantum systems are governed by three quantum postulates. These specify Hilbert spaces and state vectors as the fundamental components of quantum systems, Hermitian operators as providing the physical manifestation of these systems, and finally, the Schrödinger's equation to describe the time evolution of such systems. These notions are required in producing quantum computing. Quantum computing uses qubits as the computational basis, analogous to classical bits but with the added capability of quantum superposition. Qubits are represented as two-state vectors, and can be physically realized with any quantum-behaving binary-valued system, like the electron spins. Qubits can be combined into higher dimensional states with the use of tensor products, causing the system's Hilbert space to expand as 2^n with n being the number of qubits, allowing for exponential computational speedup. Computational logic can be constructed by acting on the qubits using unitary operators, known as quantum gates. The combinations of qubits and quantum gates can be visualized as quantum circuits, depicted using specialized circuit diagram notations. An essential part of quantum computing, and the phenomena enabling exponential computational speedup, is quantum entanglement. Entanglement arises in interacting qubits, intertwining them so that the individual states become correlated. Entanglement can be characterized by being unable to reduce a combined state into its pure constituents. The amount of entanglement in a system can be measured using von Neumann entropy, analogous to Shannon entropy in classical information theory. Entanglement serves various purposes in quantum computing and is a defining feature distinguishing it from the classical domain. In this thesis, the entanglement properties of a periodic four-qubit circuit with alternating quantum gates were simulated. The simulation was performed computationally, and measured entanglement entropy as a function of the amount of circuit periods. The results demonstrated different characteristics of entanglement depending on the parameters used for the quantum gates, with the entanglement either being periodic, non-occurring or chaotic in nature.
Although the concept of quantum computing has existed for decades, the technology needed to successfully implement a quantum computing system has not yet reached the level of sophistication, reliability, and scalability necessary for commercial viability until very recently. Significant progress on this front was made in the past few years, with IBM planning to create a 1000-qubit chip by the end of 2023, and Google already claiming to have achieved quantum supremacy. Other major industry players such as Intel and Microsoft have also invested significant amounts of resources into quantum computing research. Any viable computing system requires both hardware and software to work together harmoniously in order to perform useful computations. While the achievements of IBM and other companies represent a large step forward for quantum hardware, many gaps remain to be filled with respect to the corresponding software. Specifically, there is currently no clear path towards a complete process for translating quantum algorithms into physical operations that are directly executable on quantum hardware. Such a process is analogous to a compiler that translates programs written in a high-level language into executable machine instructions on a conventional digital computer, and it is necessary if quantum computers are to be harnessed to perform practically useful computations. Existing work has addressed individual components of this process, but so far no unified method for translating the whole of a quantum algorithm into executable operations has been described. I make substantial progress towards filling this gap by describing a set of high-level and low-level quantum circuit design techniques, which when taken together reduce the need of a circuit designer to be concerned with low-level details. On the high-level side, I describe an approach or strategy to designing quantum oracles for Grover's algorithm that allows it to be applied to several types of problems. This approach involves designing oracles in terms of high-level blocks such as counters, multiplexers, comparators, and arbitrary Boolean functions. The implementations of these blocks in terms of lower-level quantum gates are demonstrated in a way that makes it clear that scaled-up versions of them can be generated in a completely automated fashion. For a specific class of problems, which I call state-space path planning problems, I also introduce a paradigm for quantum oracle design that involves representing the problem in terms of individual states and moves. Problems of this sort have applications in robotics and games. Low-level techniques that I introduce