Thanks to the quantum simulation, more and more problems in quantum mechanics which were previously inaccessible are now open to us. Capitalizing on the state-of-the-art techniques on quantum coherent control developed in past few decades, e.g., the high-precision quantum gate manipulating, the time-reversal harnessing, the high-fidelity state preparation and tomography, the nuclear magnetic resonance (NMR) system offers a unique platform for quantum simulation of many-body physics and high-energy physics. Here, we review the recent experimental progress and discuss the prospects for quantum simulation realized on NMR systems.
Thanks to the quantum simulation, more and more problems in quantum mechanics which were previously inaccessible are now open to us. Capitalizing on the state-of-the-art techniques on quantum coherent control developed in past few decades, e.g., the high-precision quantum gate manipulating, the time-reversal harnessing, the high-fidelity state preparation and tomography, the nuclear magnetic resonance (NMR) system offers a unique platform for quantum simulation of many-body physics and high-energy physics. Here, we review the recent experimental progress and discuss the prospects for quantum simulation realized on NMR systems.
Rapid developments in quantum information processing have been made, and remarkable achievements have been obtained in recent years, both in theory and experiments. Coherent control of nuclear spin dynamics is a powerful tool for the experimental implementation of quantum schemes in liquid and solid nuclear magnetic resonance (NMR) system, especially in liquid-state NMR. Compared with other quantum information processing systems, the NMR platform has the advantages such as the long coherence time, the precise manipulation, and well-developed quantum control techniques, which make it possible to accurately control a quantum system with up to 12-qubits. Extensive applications of liquid-state NMR spectroscopy in quantum information processing such as quantum communication, quantum computing, and quantum simulation have been thoroughly studied over half a century. This article introduces the general principles of NMR quantum information processing, and reviews the new-developed techniques. The review will also include the recent achievements of the experimental realization of quantum algorithms for machine learning, quantum simulations for high energy physics, and topological order in NMR. We also discuss the limitation and prospect of liquid-state NMR spectroscopy and the solid-state NMR systems as quantum computing in the article.
In the last 20 years, there have been lots of novel developments and remarkable achievements in quantum information processing theoretically and experimentally. Among them, the coherent control of nuclear spin dynamics is a powerful tool for the experimental implementation of quantum schemes in liquid and solid nuclear magnetic resonance (NMR) system, especially in liquid-state NMR. Compared with other quantum information processing systems, NMR platform has many advantages such as the long coherence time, the precise manipulation and well-developed quantum control techniques, which make it possible to accurately control a quantum system with up to 12-qubits. Extensive applications of liquid-state NMR spectroscopy in quantum information processing such as quantum communication, quantum computing and quantum simulation have been thoroughly studied over half a century. There are also many outstanding researches in the recent several years. So we focus on the recent researches in this review article. First, we introduce the basic principle of the liquid-state NMR quantum computing and two new methods reported in the pseudo-pure state preparation which has more advantages than the traditional methods. The quantum noise-injection methods and the quantum tomography technology in liquid-state NMR are also mentioned. Then we overview Horrow-Hassidim-Lioyd algorithm, quantum support vector machine algorithm, duality quantum computing and their implementations in liquid-state NMR system. Also, we report recent researches about quantum simulations, including quantum tunneling, high-energy physics and topological sequences. Then we display the quantum cloud platform of our group. In order to let more people, either amateurs or professionals, embrace and more importantly participate in the tidal wave of quantum science, we launch our NMR quantum cloud computing (NMRCloudQ) service. Through NMRCloudQ, we offer a direct access to a real, physical spectrometer in our laboratory and encourage users to explore quantum phenomena and demonstrate quantum algorithms. Finally, we discuss the development prospects and development bottlenecks of NMR, and point out the prospects for the future development direction.
Solid-state nuclear magnetic resonance (NMR) has emerged as an important technique for material characterization, finding extensive applications across a diverse range of disciplines including physics, materials science, chemistry, and biology. Its utility stems from the ability to probe the local atomic environments and molecular dynamics within solid materials, which provides information on the composition of the material. In recent years, the scope of solid-state NMR has expanded into the realm of quantum information science and technology, where its abundant many-body interactions pulse control methodologies make it have significant research value and application potential. This paper offers a comprehensive overview of the research objects and theoretical underpinnings of solid-state NMR, delving into the critical nuclear spin interaction mechanisms and their corresponding Hamiltonian forms. These interactions, which include dipolar coupling, chemical shift anisotropy, and quadrupolar interactions, are fundamental to the interpretation of NMR spectra and the understanding of material properties at the atomic level. Moreover, the paper introduces typical dynamical control methods employed in the manipulation of solid-state nuclear spins. Techniques such as dynamical decoupling, which mitigates the effects of spin-spin interactions to extend coherence times, and magic-angle spinning, which averages out anisotropic interactions to yield high-resolution spectra. These methods are essential for enhancing the sensitivity and resolution of NMR experiments, enabling the extraction of detailed structural and dynamic information from complex materials. Then we introduce some recent advancements in quantum control based on solid-state NMR, such as nuclear spin polarization enhancement techniques, which include dynamic nuclear polarization (DNP) and cross polarization (CP), significantly boost the sensitivity of NMR measurements. Additionally, the control techniques of Floquet average Hamiltonians are mentioned, showcasing their role in the precise manipulation of quantum states and the realization of quantum dynamics. Finally, the paper presents a series of seminal research works that illustrate the application of solid-state NMR quantum control technologies in the field of quantum simulation. These studies demonstrate how solid-state NMR can be leveraged to simulate and investigate quantum many-body systems, providing valuable insights into quantum phase transitions, entanglement dynamics, and other phenomena relevant to quantum information science. By bridging the gap between fundamental research and practical applications, solid-state NMR continues to play a crucial role in advancing our understanding of quantum materials and technologies.
We review recent progress made in quantum information processing (QIP) which can be applied in the simulation of quantum systems and chemical phenomena. The review is focused on quantum algorithms which are useful for quantum simulation of chemistry and advances in nuclear magnetic resonance (NMR) and electron spin resonance (ESR) QIP. Discussions also include a number of recent experiments demonstrating the current capabilities of the NMR QIP for quantum simulation and prospects for spin-based implementations of QIP.
Nuclear Magnetic Resonance (NMR) has provided a valuable experimental testbed for quantum information processing (QIP). Here, we briefly review the use of nuclear spins as qubits, and discuss the current status of NMR-QIP. Advances in the techniques available for control are described along with the various implementations of quantum algorithms and quantum simulations that have been performed using NMR. The recent application of NMR control techniques to other quantum computing systems are reviewed before concluding with a description of the efforts currently underway to transition to solid state NMR systems that hold promise for scalable architectures.
With the development of quantum information science, the active manipulation of quantum systems is becoming an important research frontier. To build realistic quantum information processors, one of the challenges is to implement arbitrary desired operations with high precision on quantum systems. A large number of quantum control methods and relevant numerical techniques have been put forward in recent years, such as quantum optimal control and quantum feedback control. Nuclear magnetic resonance (NMR) spin systems offer an excellent testbed to develop benchmark tools and techniques for controlling quantum systems. In this review paper, we briefly introduce some of the basic control ideas developed for NMR systems in recent years. We first explain, for the liquid spin systems, the physics of various couplings and the causes of relaxation effects. These mechanisms govern the system dynamics, and thus are crucial for constructing rigorous and efficient control models. We also identify three types of available control means: 1) raido-frequency fields as coherent controls; 2) phase cycling, gradient fields and relaxation effects as non-unitary controls; 3) radiation damping effect as feedback control mechanism. Then, we elucidate some important control tasks, which may arise from the conventional NMR spectroscopy (e.g., pulse design and polarization transfer) or from quantum information science (e.g., algorithmic cooling and pseudo-pure state preparation). In the last part, we review some of the most important control methods that are applicable to NMR control tasks. For systems with a relatively small number of spins, it is possible to use analytic optimal control theory to realize the target unitary operations. However, for larger systems, numerical methods are necessary. The gradient ascent pulse engineering algorithm and pulse compiler techniques are the most successful techniques for implementing complicated quantum networks currently. There are some interesting topics of utilizing radiation damping and relaxation effects to achieve more powerful controls. Finally, we give an outline of the possible future work.