Abstract This research is focused on the development of precision methods for evaluation and forecasting the performance and fidelity characteristics of quantum information technologies based on noisy quantum systems. The approaches based on complete information matrix are considered in applications to optical polarization states and trapped ion quantum computing.
Abstract This research is focused on the development of precision methods for evaluation and forecasting the performance and fidelity characteristics of quantum information technologies based on noisy quantum systems. The approaches based on complete information matrix are considered in applications to optical polarization states and trapped ion quantum computing.
In recent years, quantum information systems have attracted increasing attention of researchers in the field of computer science and physics. However, the introduction and practical application of quantum computing is limited by the influence of noise and errors that occur in quantum systems. To implement effective control and improve the reliability of quantum information systems, it is necessary to develop methods that can suppress and correct errors in the process of quantum computing. The purpose of this work is to develop and study a control model based on noise-immune quantum computing, as well as methods for suppressing and correcting errors in quantum computing. The paper proposes a combination of different approaches, including the use of error correction codes, noise suppression algorithms, and methods for optimal control of quantum information systems. In the course of the study, a control model was developed that allows efficient processing of information in quantum systems, taking into account the presence of noise and errors. Experiments were carried out using real quantum devices to evaluate the effectiveness of the proposed model. The experimental results show that the developed method can significantly improve the reliability and accuracy of quantum computing. The proposed control model based on noise-immune quantum computing and methods for suppressing and correcting errors represent a significant contribution to the development of quantum information systems. Further development and optimization of the proposed approach can lead to the creation of more reliable and efficient quantum systems capable of solving complex computational problems.
Abstract : This project aimed to address the most significant challenge facing the development of large-scale quantum computers: suppressing hardware error. Through this work we focused on the realization of a robust, high-fidelity Quantum Control Toolkit that is fully transportable between different quantum computing technology platforms. The techniques encapsulated herein were designed to provide qubit robustness to decoherence during memory (dynamical decoupling DD), and increase the fidelity of qubit operations undertaken in the presence of random environmental noise and control imperfections (dynamically corrected gates DCGs, and composite pulses CPs). This project has seen the demonstration of significant hardware-based improvements in quantum control fidelity along with the full experimental validation of an engineering-inspired filter-transfer function framework for quantum control.
Abstract Effectively manipulating quantum computing (QC) hardware in the presence of imperfect devices and control systems is a central challenge in realizing useful quantum computers. Susceptibility to noise critically limits the performance and capabilities of today’s so-called noisy intermediate-scale quantum devices, as well as any future QC technologies. Fortunately, quantum control enables efficient execution of quantum logic operations and quantum algorithms with built-in robustness to errors, and without the need for complex logical encoding. In this manuscript we introduce software tools for the application and integration of quantum control in QC research, serving the needs of hardware R&D teams, algorithm developers, and end users. We provide an overview of a set of Python-based classical software tools for creating and deploying optimized quantum control solutions at various layers of the QC software stack. We describe a software architecture leveraging both high-performance distributed cloud computation and local custom integration into hardware systems, and explain how key functionality is integrable with other software packages and quantum programming languages. Our presentation includes a detailed mathematical overview of key features including a flexible optimization toolkit, engineering-inspired filter functions for analyzing noise susceptibility in high-dimensional Hilbert spaces, and new approaches to noise and hardware characterization. Pseudocode is presented in order to elucidate common programming workflows for these tasks, and performance benchmarking is reported for numerically intensive tasks, highlighting the benefits of the selected cloud-compute architecture. Finally, we present a series of case studies demonstrating the application of quantum control solutions derived from these tools in real experimental settings using both trapped-ion and superconducting quantum computer hardware.
A general approach to the provision of the quality and efficiency of quantum information technologies is proposed. The approach is based on the analysis of quantum noise generated on the implementation of quantum operations. The method of precision quantum measurements of logic quantum gates based on superconducting phase qubits is developed. The universal method of quantum state and process tomography is used to carry out a comprehensive analysis of the fidelity of the tomography of two-qubit SQiSW, CNOT, and CZ gates arising from the capacitive coupling between qubits. The method of optimization of quantum process tomography is proposed to provide a substantially higher degree of adequacy and fidelity compared to those attained by previously known methods. The examples of simulation of depolarizing quantum noise and amplitude- and phase-relaxation processes on the implementation of quantum operations in registers are considered.
Quantum technologies harness the properties of controlled quantum mechanical systems for applications in computation, communication and metrology, and enable us to further our understanding of fundamental physics. Quantum hardware is designed to manipulate complex and fragile many-particle quantum states, which requires exquisite control machinery, advanced software and near-complete isolation from the surrounding environment. With sufficient capabilities, quantum computers with large registers of quantum bits will perform classically intractable calculations such as quantum chemistry simulations. Quantum key distribution will provide completely secure communications across the world and quantum metrology will enable measurement precision beyond today's capabilities. While quantum technologies are far from surpassing classical hardware today, the vision and potential impact has sparked a world-wide research effort, both theoretical and experimental, to develop a quantum computer. The most sophisticated current quantum technologies have control over small numbers of quantum bits and are limited by environmental decoherence processes. While progress in developing quantum hardware is ongoing, designing and demonstrating new algorithms and protocols for quantum information is a thriving research field. Photonics provides an ideal platform for small-scale proof-of-concept quantum experiments, which are the focus of this thesis. In the coming decades, we will see the realisation of quantum hardware capable of applications that outperform any classical computer. In this thesis, I present several protocols and algorithms for quantum information science and technology, which are implemented in quantum photonic experiments. The applications of these works include robust quantum tomography, quantum state relocation, quantum enhanced data recovery and probing fundamental causality in quantum mechanics. The works presented here are based on two photon experiments from a prototypical spontaneous parametric down-conversion source, which provides an excellent test-bed for quantum information experiments. Photons can be used to encode quantum information in a range of different degrees of freedom. This versatility, along with compatibility with existing technology gives photonics a great advantage in the development of quantum hardware.
The report presents a general approach for estimating quantum information technologies by means of fuzzy quantum measurements. The developed methods are used for precision reconstruction of quantum states under conditions of significant influence of decoherence and quantum noise. Monitoring of the amount of information about quantum states and their parameters, including the loss of information caused by the effect of quantum noise, is considered. Examples of the developed approach as applied to readout errors and phase relaxation are presented.