The paper considers a common operation principle of a quantum rotation sensor based on nuclear magnetic resonance, giving a semi-classical description of processes in the sensor circuit, that is useful for obtaining the analytical representation of a signal at the optical circuit output. The principles of numerical calculation are briefly presented for an optical signal of the rotation sensor based on a one-dimensional quantum model. Comparison of calculations according to classical model and more stringent quantum model has shown that the sensor signal has a more complicated structure than that following from the classical description which shows only some properties of dynamic processes in the circuit. The results are important for the development of methods for demodulating the quantum rotation sensor optical signal and for estimation of expected characteristics of practical devices.
The paper considers a common operation principle of a quantum rotation sensor based on nuclear magnetic resonance, giving a semi-classical description of processes in the sensor circuit, that is useful for obtaining the analytical representation of a signal at the optical circuit output. The principles of numerical calculation are briefly presented for an optical signal of the rotation sensor based on a one-dimensional quantum model. Comparison of calculations according to classical model and more stringent quantum model has shown that the sensor signal has a more complicated structure than that following from the classical description which shows only some properties of dynamic processes in the circuit. The results are important for the development of methods for demodulating the quantum rotation sensor optical signal and for estimation of expected characteristics of practical devices.
As a type of atomic sensor, the residual optical rotation angle during the detection process of the nuclear magnetic resonance (NMR) sensor limits its performance improvement. By establishing the optical rotation detection signal theoretical model of the NMR sensor, the influence of the residual optical rotation angle on the signal output is analyzed. Further, the theoretical analysis indicates that adjusting the detection laser frequency based on the D1 line resonance frequency and resonance linewidth can effectively increase the scale factor and achieve suppression of residual optical rotation angle. The temperature change rate of D1 line resonance frequency and linewidth in the NMR sensor is -15.5 MHz/°C, and the linewidth coefficients are 19.9 MHz/°C, respectively. The experimental results indicate that, following the optimization of probe laser frequency, the sensitivity of the NMR sensor has significantly improved. Furthermore, the residual optical rotation angle suppression method proposed in this study demonstrates potential applicability to other atomic sensors utilizing optical rotation detection.
A scheme of the magnetometer that simultaneously employs M X and M R magnetic resonance signals with the latter signal related to the radial component of the rotating atomic magnetic moment is proposed and tested. With respect to the shape, dynamic characteristics, and metrological parameters, the M R signal is similar to the M X signal that is widely used in magnetometry but the former signal can be detected simultaneously with the M X signal using a common radio optical scheme. The proposed device represents a fast M X magnetometer with the phase in the feedback loop that is controlled by a slow precise M R magnetometer implemented using the same atoms. The device that can be based on a conventional M X sensor simultaneously exhibits a relatively short response time (τ ≤ 0.1 s) and the accuracy that is approximately equal to the resolution of the quantum M X discriminator at times of 10–100 s. The scheme is experimentally tested, and the statistic estimate of reproducibility is (1.2 ± 1.1) pT.
Standard CMOS circuits are expected to be no longer able to satisfy nowadays demand for higher performances and lower power consumption. This commits to look for new solutions. Quantum computation, whose fundamental quantity of information is the qubit, is a thoroughly new way of thinking to electronics. There are at least two main reasons for which quantum computing is expected to broaden computation horizons. First, specific algorithms can be engineered, manipulating the probability amplitudes of different states, to exploit the quantum superposition principle and achieve high parallelism. Second, it is expected to be spontaneously suitable to simulate complex quantum physical systems, as large molecules. Quantum computing requires the cooperation of several scientific fields. The leading idea has been to highlight the operations and algorithms a quantum computer must be able to perform and, then, to propose a hardware solution, providing the rigorous physical treatment mandatory for a deep understanding and for an appropriate modelling, something which is hard to find in nowadays literature. Thus, the first chapters address the quantum algorithms, focusing on Grover's search algorithm and deriving, from fundamentals, the corresponding circuit. The latter is then described in Quantum Assembly (QASM), which can be seen as the quantum equivalent of VHDL, and simulated on IBM Q Experience. The following chapters deal with a possible physical implementation of quantum processors: the encoding of qubits on nuclear spins in diamagnetic molecules. When a static magnetic field is applied to a spin-1/2 nucleus, two well-defined energy eigenstates arise, as a result of the Zeeman effect. Each of them can be associated with a qubit eigenstate. Thanks to nuclear magnetic resonance principles, the probability with which one of the two eigenstates is measured can be handled by the superposition of a radio frequency field at the resonance frequency of the nucleus. This can be interpreted as a rotation of the spin, and so of the qubit, about the RF field and enables the execution of single qubit quantum gates, since they are simple rotations of the state vector. The two-qubit CNOT gate is obtained through the interaction of spins via J-coupling. Considering that these gates constitute a universal set, every quantum algorithm can theoretically be run on an NMR processor. Different nuclei have different resonant frequencies, but the addressing of a specific spin can be achieved also in homonuclear molecules, since the resonant frequency depends also on the nuclear environment (nuclear shielding). While unwanted J-couplings can be removed thanks to refocusing, spin decoherence and relaxation phenomena force an upper limit to the allowed timescale. A main advantage of NMR is that this timescale is long, even at room temperature. Conversely, scalability is still an issue. A simple heteronuclear MATLAB model, based on the relations derived from first principles in the thesis, is proposed to prove the feasibility of NMR quantum processors. The input technological parameters, as chemical shielding and J-coupling, can be computed resorting on ORCA, or obtained from experimental data. The model, able to run a universal set of quantum gates and simple algorithms, can be useful to find an optimal operating point as a compromise between molecule physical properties and the quantities which can be controlled by nowadays NMR instrumentation.
Entangled sensors have been attracting a lot of attention recently because they can achieve the sensitivity beyond that of the classical sensors. To exploit entanglement as a resource, it is important to understand the effect of noise because the entangled state is fragile against noise. Here, we provide a Nuclear Magnetic Resonance (NMR) model of an entangled sensor under engineered noise: one can implement an entangled sensor under various noisy environments. In particular, we experimentally investigate the performance of the entangled sensor under the effect of time-inhomogeneous noisy environment with which the entangled sensor holds potential to beat the classical sensors. Our "entangled sensor" consists of a multi-spin molecule solved in isotropic liquid, and we can perform the quantum sensing by using NMR techniques.
Quantum circuits If the state of a quantum system is a kind of information, then the dynamics of that system is a kind of information processing. This is the basic idea behind quantum computing , which seeks to exploit the physics of quantum systems to do useful information processing. In this chapter we will acquaint ourselves with a few of the ideas of quantum computing, using the idealized quantum circuit model. Then we will turn our attention to an actual quantum process, nuclear magnetic resonance , that can be understood as a realization of quantum information processing. In a quantum circuit, we have a set of n qubit systems whose dynamical evolution is completely under our control. We represent the evolution as a sequence of unitary operators, each of which acts on one or more of the qubits. Graphically, we represent the qubits as a set of horizontal lines, and the various stages of their evolution as a series of boxes or other symbols showing the structure of the sequence of operations. In such a diagram, time runs from left to right (see Fig. 18.1.). The n qubits form a kind of “computer,” and its overall evolution amounts to a “computation.” The key idea is that very complicated unitary operations on the n qubits can be built up step-by-step from many simple operations on one, two or a few qubits.
Nuclear Magnetic Resonance (NMR) plays a central role in developing quantum information sciences and technologies. Key features such as its non-invasive nature and the ability to process information on nuclear spins by versatile quantum control designs with electromagnetic fields, have made NMR to become a powerful technique for sensing systems from atomic and molecular scales with spectroscopy to millimeters in imaging. This brief overview provides quantum sensing tools with which we are contributing from Latin America, by combining quantum dynamical control and estimation strategies with NMR methods to probe physical, chemical, and biological processes. It introduces the basic and key concepts on how controlled spin-sensors can monitor the correlation dynamics of their environment, and selectively and optimally infer its relevant parameters. Then these concepts are illustrated with state-of-the-art implementations for characterizing (i) biological tissue microstructure with diffusion weighting imaging, (ii) quantum information dynamics and scrambling in out-of-equilibrium systems with solid-state NMR quantum simulations, and (iii) molecular structures by selective estimation of spin–spin couplings and online learning control designs with experimental proposals. We expect these concepts will motivate the development of quantum dynamical control of spin sensors to monitor systems in a variety of fields, and in particular to exploit the non-invasive strength of NMR, e.g. in biomedical diagnosis. • Quantum control and estimation tools probe physical, chemical, biological processes. • Efficient quantum sensing for maximizing relevant environmental information. • Biological tissue microstructure characterization with diffusion weighting imaging. • Assessing fragility of quantum information dynamics in out-of-equilibrium systems. • Selective estimation of spin–spin couplings and online learning control designs.