Catálogo de publicaciones - revistas

<jats:p>The quantum entanglement, discord, and coherence dynamics of two spins in the model of a spin coupled to a spin bath through an intermediate spin are studied. The effects of the important physical parameters including the coupling strength of two spins, the interaction strength between the intermediate spin and the spin bath, the number of bath spins and the temperature of the system on quantum coherence and correlation dynamics are discussed in different cases. The frozen quantum discord can be observed whereas coherence does not when the initial state is the Bell-diagonal state. At finite temperature, we find that coherence is more robust than quantum discord, which is better than entanglement, in terms of resisting the influence of environment. Therefore, quantum coherence is more tenacious than quantum correlation as an important resource.</jats:p>

<jats:p>Recently, a scheme for deterministic remote preparation of arbitrary multi-qubit equatorial states was proposed by Wei <jats:italic>et al.</jats:italic> [<jats:italic>Quantum Inf. Process.</jats:italic> <jats:bold>17</jats:bold> 70 (2018)]. It is worth mentioning that the construction of mutual orthogonal measurement basis plays a key role in quantum remote state preparation. In this paper, a simple and feasible remote preparation of arbitrary <jats:italic>n</jats:italic>-qubit equatorial states scheme is proposed. In our scheme, the success probability will reach unit. Moreover, there are no coefficient constraint and auxiliary qubits in this scheme. It means that the success probabilities are independent of the coefficients of the entangled channel. The advantage of our scheme is that the mutual orthogonal measurement basis is devised. To accomplish the quantum remote state preparation (RSP) schemes, some new sets of mutually orthogonal measurement basis are introduced.</jats:p>

<jats:p>We explore the entropy uncertainty for qutrit system under non-Markov noisy environment and discuss the effects of the quantum memory system and the spontaneously generated interference (SGI) on the entropy uncertainty in detail. The results show that, the entropy uncertainty can be reduced by using the methods of quantum memory system and adjusting of SGI. Particularly, the entropy uncertainty can be decreased obviously when both the quantum memory system and the SGI are simultaneously applied.</jats:p>

<jats:p>We study a simplified (3+1)-dimensional model equation and construct a lump solution for the special case of <jats:italic>z</jats:italic> = <jats:italic>y</jats:italic> using the Hirota bilinear method. Then, a more general form of lump solution is constructed, which contains more arbitrary autocephalous parameters. In addition, a lumpoff solution is also derived based on the general lump solutions and a stripe soliton. Furthermore, we figure out instanton/rogue wave solutions via introducing two stripe solitons. Finally, one can better illustrate these propagation phenomena of these solutions by analyzing images.</jats:p>

<jats:p>We propose a joint exponential function and Woods–Saxon stochastic resonance (EWSSR) model. Because change of a single parameter in the classical stochastic resonance model may cause a great change in the shape of the potential function, it is difficult to obtain the optimal output signal-to-noise ratio by adjusting one parameter. In the novel system, the influence of different parameters on the shape of the potential function has its own emphasis, making it easier for us to adjust the shape of the potential function. The system can obtain different widths of the potential well or barrier height by adjusting one of these parameters, so that the system can match different types of input signals adaptively. By adjusting the system parameters, the potential function model can be transformed between the bistable model and the monostable model. The potential function of EWSSR has richer shapes and geometric characteristics. The effects of parameters, such as the height of the barrier and the width of the potential well, on SNR are studied, and a set of relatively optimal parameters are determined. Moreover, the EWSSR model is compared with other classical stochastic resonance models. Numerical experiments show that the proposed EWSSR model has higher SNR and better noise immunity than other classical stochastic resonance models. Simultaneously, the EWSSR model is applied to the detection of actual bearing fault signals, and the detection effect is also superior to other models.</jats:p>

<jats:p>The energy efficiency and output power of a quantum thermoelectric system with multiple electric currents and only one heat current are studied. The system is connected to the hot heat bath (cold bath) through one terminal (multiple terminals). In such configurations, there are multiple thermoelectric effects coexisting in the system. Using the Landauer–Büttiker formalism, we show that the cooperation between the two thermoelectric effects in the three-terminal thermoelectric systems can lead to markedly improved performance of the heat engine. Such improvement also occurs in four-terminal thermoelectric heat engines with three output electric currents. Cooperative effects in these multi-terminal thermoelectric systems can considerably enlarge the physical parameter region that realizes high energy efficiency and output power. For refrigeration, we find that the energy efficiency can also be substantially improved by exploiting the cooperative effects in multi-terminal thermoelectric systems. All these results reveal a useful approach toward high-performance thermoelectric energy conversion in multi-terminal mesoscopic systems.</jats:p>

<jats:p>Holter usually monitors electrocardiogram (ECG) signals for more than 24 hours to capture short-lived cardiac abnormalities. In view of the large amount of Holter data and the fact that the normal part accounts for the majority, it is reasonable to design an algorithm that can automatically eliminate normal data segments as much as possible without missing any abnormal data segments, and then take the left segments to the doctors or the computer programs for further diagnosis. In this paper, we propose a preliminary abnormal segment screening method for Holter data. Based on long short-term memory (LSTM) networks, the prediction model is established and trained with the normal data of a monitored object. Then, on the basis of kernel density estimation, we learn the distribution law of prediction errors after applying the trained LSTM model to the regular data. Based on these, the preliminary abnormal ECG segment screening analysis is carried out without R wave detection. Experiments on the MIT-BIH arrhythmia database show that, under the condition of ensuring that no abnormal point is missed, 53.89% of normal segments can be effectively obviated. This work can greatly reduce the workload of subsequent further processing.</jats:p>

<jats:p>Magnetocardiography (MCG) measurement is important for investigating the cardiac biological activities. Traditionally, the extremely weak MCG signal was detected by using superconducting quantum interference devices (SQUIDs). As a room-temperature magnetic-field sensor, optically pumped magnetometer (OPM) has shown to have comparable sensitivity to that of SQUIDs, which is very suitable for biomagnetic measurements. In this paper, a synthetic gradiometer was constructed by using two OPMs under spin-exchange relaxation-free (SERF) conditions within a moderate magnetically shielded room (MSR). The magnetic noise of the OPM was measured to less than 70 fT/Hz<jats:sup>1/2</jats:sup>. Under a baseline of 100 mm, noise cancellation of about 30 dB was achieved. MCG was successfully measured with a signal to noise ratio (SNR) of about 37 dB. The synthetic gradiometer technique was very effective to suppress the residual environmental fields, demonstrating the OPM gradiometer technique for highly cost-effective biomagnetic measurements.</jats:p>

<jats:p>The further development of traditional von Neumann-architecture computers is limited by the breaking of Moore’s law and the von Neumann bottleneck, which make them unsuitable for future high-performance artificial intelligence (AI) systems. Therefore, new computing paradigms are desperately needed. Inspired by the human brain, neuromorphic computing is proposed to realize AI while reducing power consumption. As one of the basic hardware units for neuromorphic computing, artificial synapses have recently aroused worldwide research interests. Among various electronic devices that mimic biological synapses, synaptic transistors show promising properties, such as the ability to perform signal transmission and learning simultaneously, allowing dynamic spatiotemporal information processing applications. In this article, we provide a review of recent advances in electrolyte- and ferroelectric-gated synaptic transistors. Their structures, materials, working mechanisms, advantages, and disadvantages will be presented. In addition, the challenges of developing advanced synaptic transistors are discussed.</jats:p>