NMR Quantum Computer Research Articles

From computing to quantum mechanics: accessible and hands-on quantum computing education for high school students

This paper outlines an alternative approach to teaching quantum computing at the high school level, tailored for students with limited prior knowledge in advanced mathematics and physics. This approach diverges from traditional methods by building upon foundational concepts in classical computing before gradually introducing quantum mechanics, thereby simplifying the entry into this complex field. The course was initially implemented in a program for gifted high school students under the Hong Kong Education Bureau and received encouraging feedback, indicating its potential effectiveness for a broader student audience. A key element of this approach is the practical application through portable NMR quantum computers, which provides students with hands-on experience. The paper describes the structure of the course, including the organization of the lectures, the integration of the hardware of the portable nuclear magnetic resonance (NMR) quantum computers, the Gemini/Triangulum series, and detailed lecture notes in Additional file 1. The initial success in the specialized program and ongoing discussions to expand the course to regular high schools in Hong Kong and Shenzhen suggest the viability of this approach for wider educational application. By focusing on accessibility and student engagement, this approach presents a valuable perspective on introducing quantum computing concepts at the high school level, aiming to enhance student understanding and interest in the field.

Dynamic Cooling on Contemporary Quantum Computers

We study the problem of dynamic cooling whereby a target qubit is cooled at the expense of heating up N−1 further identical qubits by means of a global unitary operation. A standard back-of-the-envelope high-temperature estimate establishes that the target qubit temperature can be dynamically cooled by at most a factor of 1/N. Here we provide the exact expression for the minimum temperature to which the target qubit can be cooled and reveal that there is a crossover from the high initial temperature regime, where the scaling is 1/N, to a low initial temperature regime, where a much faster scaling of 1/N occurs. This slow, 1/N scaling, which was relevant for early high-temperature NMR quantum computers, is the reason dynamic cooling was dismissed as ineffectual around 20 years ago; the fact that current low-temperature quantum computers fall in the fast, 1/N scaling regime, reinstates the appeal of dynamic cooling today. We further show that the associated work cost of cooling is exponentially more advantageous in the low-temperature regime. We discuss the implementation of dynamic cooling in terms of quantum circuits and examine the effects of hardware noise. We successfully demonstrate dynamic cooling in a three-qubit system on a real quantum processor. Since the circuit size grows quickly with N, scaling dynamic cooling to larger systems on noisy devices poses a challenge. We therefore propose a suboptimal cooling algorithm, whereby relinquishing a small amount of cooling capability results in a drastically reduced circuit complexity, greatly facilitating the implementation of dynamic cooling on near-future quantum computers. Published by the American Physical Society 2024

NMR Quantum Computer for Education

NMR Quantum Computer for Education

Uniquely identifying topological order based on boundary-bulk duality and anyon condensation.

Topological order is a new quantum phase that is beyond Landau's symmetry-breaking paradigm. Its defining features include robust degenerate ground states, long-range entanglement and anyons. It was known that R and F matrices, which characterize the fusion-braiding properties of anyons, can be used to uniquely identify topological order. In this article, we explore an essential question: how can the R and F matrices be experimentally measured? We show that the braidings, i.e. the R matrices, can be completely determined by the half braidings of boundary excitations due to the boundary-bulk duality and the anyon condensation. The F matrices can also be measured by comparing the quantum states involving the fusion of three anyons in two different orders. Thus we provide a model-independent experimental protocol to uniquely identify topological order. By using quantum simulations based on a toric code model with boundaries encoded in three- and four-qubit systems and state-of-the-art technology, we obtain the first experimental measurement of R and F matrices by means of an NMR quantum computer at room temperature.

Optically induced nuclear spin–spin couplings in GaAs manifested by spin echo decays under optical pumping

Optically induced nuclear spin–spin coupling in semiconductors is expected to serve for gate operations in nuclear-magnetic-resonance (NMR) quantum computations. However, not much is known about its characteristics. In this study, we investigate optically induced couplings in GaAs via double-resonance spin-echo decay experiments under optical pumping. The squared echo decay rate left( {1/T_2} right)^2 of 71Ga measured under various light powers revealed that optically induced couplings increase with increasing light power, and the sign of heteronuclear couplings between Ga–As pairs is opposite to that of dipolar couplings, which cancel each other out. Under higher light power, the optically induced “controllable” coupling is expected to eventually surpass the “uncontrollable” nuclear dipolar coupling, becoming dominant, which is preferable for the gate operation in NMR quantum computation.

Extending NMR Quantum Computation Systems by Employing Compounds with Several Heavy Metals as Qubits

Nuclear magnetic resonance (NMR) is a spectroscopic method that can be applied to several areas. Currently, this technique is also being used as an experimental quantum simulator, where nuclear spins are employed as quantum bits or qubits. The present work is devoted to studying heavy metal complexes as possible candidates to act as qubit molecules. Nuclei such 113Cd, 199Hg, 125Te, and 77Se assembled with the most common employed nuclei in NMR-QIP implementations (1H, 13C, 19F, 29Si, and 31P) could potentially be used in heteronuclear systems for NMR-QIP implementations. Hence, aiming to contribute to the development of future scalable heteronuclear spin systems, we specially designed four complexes, based on the auspicious qubit systems proposed in our previous work, which will be explored by quantum chemical calculations of their NMR parameters and proposed as suitable qubit molecules. Chemical shifts and spin–spin coupling constants in four complexes were examined using the spin–orbit zeroth-order regular approximation (ZORA) at the density functional theory (DFT) level, as well as the relaxation parameters (T1 and T2). Examining the required spectral properties of NMR-QIP, all the designed complexes were found to be promising candidates for qubit molecules.

Quantum imaginary time evolution steered by reinforcement learning

The quantum imaginary time evolution is a powerful algorithm for preparing the ground and thermal states on near-term quantum devices. However, algorithmic errors induced by Trotterization and local approximation severely hinder its performance. Here we propose a deep reinforcement learning-based method to steer the evolution and mitigate these errors. In our scheme, the well-trained agent can find the subtle evolution path where most algorithmic errors cancel out, enhancing the fidelity significantly. We verified the method’s validity with the transverse-field Ising model and the Sherrington-Kirkpatrick model. Numerical calculations and experiments on a nuclear magnetic resonance quantum computer illustrate the efficacy. The philosophy of our method, eliminating errors with errors, sheds light on error reduction on near-term quantum devices.

Quantum Computing: Fundamentals, Implementations and Applications

Quantum Computing is a technology, which promises to overcome the drawbacks of conventional CMOS technology for high density and high performance applications. Its potential to revolutionize today's computing world is attracting more and more researchers towards this field. However, due to the involvement of quantum properties, many beginners find it difficult to follow the field. Therefore, in this research note an effort has been made to introduce the various aspects of quantum computing to researchers, quantum engineers and scientists. The historical background and basic concepts necessary to understand quantum computation and information processing have been introduced in a lucid manner. Various physical implementations and potential application areas of quantum computation have also been discussed in this paper. Recent developments in each realization, in the context of the DiVincenzo criteria, including ion traps based quantum computing, superconducting quantum computing, nuclear magnetic resonance (NMR) quantum computing, spintronics and semiconductor based quantum computing have been discussed.

Learning temporal data with a variational quantum recurrent neural network

We propose a method for learning temporal data using a parametrized quantum circuit. We use the circuit that has a similar structure as the recurrent neural network which is one of the standard approaches employed for this type of machine learning task. Some of the qubits in the circuit are utilized for memorizing past data, while others are measured and initialized at each time step for obtaining predictions and encoding a new input datum. The proposed approach utilizes the tensor product structure to get nonlinearity with respect to the inputs. Fully controllable, ensemble quantum systems such as an NMR quantum computer is a suitable choice of an experimental platform for this proposal. We demonstrate its capability with Simple numerical simulations, in which we test the proposed method for the task of predicting cosine and triangular waves and quantum spin dynamics. Finally, we analyze the dependency of its performance on the interaction strength among the qubits in numerical simulation and find that there is an appropriate range of the strength. This work provides a way to exploit complex quantum dynamics for learning temporal data.

Quantum simulation dynamics and circuit synthesis of FMO complex on an NMR quantum computer

Recently, the dynamics simulation of light-harvesting complexes as an open quantum system, in the weak and strong coupling regimes, has received much attention. In this paper, we investigate a digital quantum simulation approach of the Fenna–Matthews–Olson (FMO) photosynthetic pigment-protein complex surrounded with a Markovian bath, i.e. memoryless, based on a nuclear magnetic resonance (NMR) quantum computer. For this purpose, we apply the decoupling (recoupling) method, which is turn off (on) the couplings, and also Solovay–Kitaev techniques to decompose Hamiltonian and Lindbladians into efficient elementary gates on an NMR simulator. Finally, we design the quantum circuits for the unitary and nonunitary part due to the system-environment interactions of the open system dynamics.

Enhancing NMR Quantum Computation by Exploring Heavy Metal Complexes as Multiqubit Systems: A Theoretical Investigation.

Assembled together with the most common qubits used in nuclear resonance magnetic (NMR) quantum computation experiments, spin-1/2 nuclei, such as 113Cd, 199Hg, 125Te, and 77Se, could leverage the prospective scalable quantum computer architectures, enabling many and heteronuclear qubits for NMR quantum information processing (QIP) implementations. A computational design strategy for prescreening recently synthesized complexes of cadmium, mercury, tellurium, selenium, and phosphorus (called MRE complexes) as suitable qubit molecules for NMR QIP is reported. Chemical shifts and spin-spin coupling constants (SSCCs) in five MRE complexes were examined using the spin-orbit zeroth order regular approximation (ZORA) at the density functional theory level and the four-component relativistic Dirac-Kohn-Sham approach. In particular, the influence of different conformers, basis sets, exchange-correlation functionals, and methods to treat the relativistic as well as solvent effects were studied. The differences in the chemical shifts and SSCCs between different low energy conformers of the studied complexes were found to be very small. The TZ2P basis set was found to be the optimum choice for the studied chemical shifts, while the TZ2P-J basis set was the best for the couplings studied in this work. The PBE0 exchange-correlation functional exhibited the best performance for the studied MRE complexes. The addition of solvent effects has not improved on the gas phase results in comparison to the experiment, with the exception of the phosphorus chemical shift. The use of MRE complexes as qubit molecules for NMR QIP could face the challenges in single qubit control and multiqubit operations. They exhibit chemical shifts appropriately dispersed, allowing qubit addressability and exceptionally large spin-spin couplings, which could reduce the time of quantum gate operations and likely preserve the coherence.

Time optimal control of coupled spin dynamics: A global analysis

In this paper, we study some control problems that derive from time optimal control of coupled spin dynamics in NMR spectroscopy and quantum information and computation. Time optimal control helps to minimize relaxation losses. In a two qubit system, the ability to synthesize local unitaries much more rapidly than evolution of couplings, gives a natural time scale separation in these problems. The generators of unitary evolution g, are decomposed into fast generators k, (local Hamiltonians) and slow generators p, (couplings) as a Cartan decomposition g=p⊕k. Using this decomposition, we exploit some convexity ideas to completely characterize the reachable set and time optimal control for these problems. The main contribution of the paper is that we carry out a second order analysis of time optimality.

Time-optimal implementations of quantum algorithms

In this paper, we briefly discuss the methodology for simulating a quantum computer which performs Shor's algorithm on a 7-qubit system to factorise 15. Using this simulation and the overlooked quantum brachistochrone method, we devised a Monte Carlo algorithm to calculate the expected time a theoretical quantum computer could perform this calculation under the same energy conditions as current working quantum computers. We found that, experimentally, a nuclear magnetic resonance quantum computer would take $1.59 \pm 0.04$ s to perform our simulated computation, whereas the expected optimal time under the same energy conditions is $0.955 \pm 0.004$ ms. Moreover, we found that the expected time is inversely proportional to the energy variance of our qubit states (as expected). Finally, we propose this theoretical method for analysing the time-efficiency of future quantum computing experiments.

Exploring Through-Space Spin-Spin Couplings for Quantum Information Processing: Facing the Challenge of Coherence Time and Control Quantum States.

Nuclear magnetic resonance (NMR) is a powerful tool for studying quantum information processing (QIP). Recently quantum technologies have been proposed to overcome the challenges in large-scale NMR QIP. Furthermore, computational chemistry can promote its improvement. Nuclear spins-1/2 are natural qubits and have been used in most NMR quantum computation experiments. However, molecules that enable many qubits NMR QIP implementations should meet some requirements regarding their spectroscopic properties. Exceptionally large through-space (TS) P-P spin-spin coupling constants (SSCC or J) observed in 1,8-diphosphanaphthalenes (PPN) and in naphtho[1,8- cd]-1,2-dithiole phenylphosphines (NTP) were proposed and investigated to provide more accurate control within large-scale NMR QIP. Spectroscopic properties of PPN and NTP derivatives were explored by theoretical strategies using locally dense basis sets (LDBS). 31P chemical shifts (δ) calculated at the B3LYP/aug-cc-pVTZ-J level and TS P-P SSCCs at the PBE1PBE/pcJ-2 (LDBS-1) level are very close to the experimental data for the PPN molecule. Differently, for the NTP dimer, PBE1PBE/pcJ-2 (LDBS-2) predicts more accurate 31P δ, whereas PBE1PBE/Def2-TZVP (LDBS-1) forecasts more accurate TS P-P SSCCs. From our results, PPNo-F, PPNo-ethyl, and PPNo-NH2 were the best candidates for NMR QIP, in which the large TS SSCCS could face the need of long-time quantum gates implementations. Therefore, it could overcome natural limitations concerning the development of large-scale NMR.

Reliability of Digitized Quantum Annealing and the Decay of Entanglement

We performed a banged-digital-analog simulation of a quantum annealing protocol in a two-qubit Nuclear Magnetic Resonance (NMR) quantum computer. Our experimental simulation employed up to 235 Trotter steps, with more than 2000 gates (pulses), and we obtained a protocol success above 80%. Given the exquisite control of the NMR quantum computer, we performed the simulation with different noise levels. We thus analyzed the reliability of the quantum annealing process, and related it to the level of entanglement produced during the protocol. Although the presence of entanglement is not a sufficient signature for a better-than-classical simulation, the level of entanglement achieved relates to the fidelity of the protocol.

New research progress of nuclear magnetic resonance quantum information processing

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.

NMRCloudQ: a quantum cloud experience on a nuclear magnetic resonance quantum computer

Cloud-based quantum computing is anticipated to be the most useful and reachable form for public users to experience with the power of quantum. As initial attempts, IBM Q has launched influential cloud services on a superconducting quantum processor in 2016, but no other platforms has followed up yet. Here, we report our new cloud quantum computing service – NMRCloudQ (http://nmrcloudq.com/zh-hans/), where nuclear magnetic resonance, one of the pioneer platforms with mature techniques in experimental quantum computing, plays as the role of implementing computing tasks. Our service provides a comprehensive software environment preconfigured with a list of quantum information processing packages, and aims to be freely accessible to either amateurs that look forward to keeping pace with this quantum era or professionals that are interested in carrying out real quantum computing experiments in person. In our current version, four qubits are already usable with in average 99.10% single-qubit gate fidelity and 97.15% two-qubit fidelity via randomized benchmaking tests. Improved control precisions as well as a new seven-qubit processor are also in preparation and will be available later.

Robust techniques for polarization and detection of nuclear spin ensembles

Highly sensitive nuclear spin detection is crucial in many scientific areas including nuclear magnetic resonance spectroscopy (NMR), imaging (MRI) and quantum computing. The tiny thermal nuclear spin polarization represents a major obstacle towards this goal which may be overcome by Dynamic Nuclear Spin Polarization (DNP) methods. The latter often rely on the transfer of the thermally polarized electron spins to nearby nuclear spins, which is limited by the Boltzmann distribution of the former. Here we demonstrate the polarization and read out of a nuclear spin bath consisting of $^{13}$C nuclear spins in diamond by using a single nitrogen-vacancy (NV) center. Our method utilizes microwave dressed states to transfer the NV's high ($>$~92~\%) non-equilibrium electron spin polarization induced by short laser pulses to the surrounding carbon nuclear spins, where the NV is repeatedly repolarized optically, thus providing an effectively infinite polarization reservoir. A saturation of the polarization in the nuclear "frozen core" is achieved, which is confirmed by the decay of the polarization transfer signal and shows an excellent agreement with theoretical simulations. Hereby we introduce the Polarization Read Out by Polarization Inversion (PROPI) method as a quantitative magnetization measure of the nuclear spin bath. Moreover, we show that using the integrated solid effect both for single and double quantum transitions a nuclear spin polarization can be achieved even when the static magnetic field is not aligned along the NV's crystal axis. This opens a path for the application of our DNP technique to spins in and outside of nanodiamonds, enabling their application as MRI tracers.

21pCC-2 NMR量子コンピューターのための卓上NMR装置

21pCC-2 NMR量子コンピューターのための卓上NMR装置

Selective-pulse-network compilation on a liquid-state nuclear-magnetic-resonance system

In creating a large-scale quantum information processor, the ability to construct control pulses for implementing an arbitrary quantum circuit in a scalable manner is an important requirement. For liquid-state nuclear magnetic resonance (NMR) quantum computing, a circuit is generally realized through a sequence of selective soft pulses, in which various control imperfections exist and are to be corrected. In this work, we present a comprehensive analysis of the errors arisen in a selective pulse network by using the zeroth and first order average Hamiltonian theory. Effective correction rules are derived for adjusting important pulse parameters such as irradiation frequencies, rotational angles and transmission phases of the selective pulses to increase the control fidelity. Simulations show that applying our compilation procedure for a given circuit is efficient and can greatly reduce the error accumulation.