On compression rate of quantum autoencoders: Control design, numerical and experimental realization

Quantum autoencoders which aim at compressing quantum information in a low-dimensional latent space lie in the heart of automatic data compression in the field of quantum information. In this paper, we establish an upper bound of the compression rate for a given quantum autoencoder and present a learning control approach for training the autoencoder to achieve the maximal compression rate. The upper bound of the compression rate is theoretically proven using eigen-decomposition and matrix differentiation, which is determined by the eigenvalues of the density matrix representation of the input states. Numerical results on 2-qubit and 3-qubit systems are presented to demonstrate how to train the quantum autoencoder to achieve the theoretically maximal compression, and the training performance using different machine learning algorithms is compared. Experimental results of a quantum autoencoder using quantum optical systems are illustrated for compressing two 2-qubit states into two 1-qubit states

Power Allocation and Time-Domain Artificial Noise Design for Wiretap OFDM with Discrete Inputs

Optimal power allocation for orthogonal frequency division multiplexing (OFDM) wiretap channels with Gaussian channel inputs has already been studied in some previous works from an information theoretical viewpoint. However, these results are not sufficient for practical system design. One reason is that discrete channel inputs, such as quadrature amplitude modulation (QAM) signals, instead of Gaussian channel inputs, are deployed in current practical wireless systems to maintain moderate peak transmission power and receiver complexity. In this paper, we investigate the power allocation and artificial noise design for OFDM wiretap channels with discrete channel inputs. We first prove that the secrecy rate function for discrete channel inputs is nonconcave with respect to the transmission power. To resolve the corresponding nonconvex secrecy rate maximization problem, we develop a low-complexity power allocation algorithm, which yields a duality gap diminishing in the order of O(1/\sqrt{N}), where N is the number of subcarriers of OFDM. We then show that independent frequency-domain artificial noise cannot improve the secrecy rate of single-antenna wiretap channels. Towards this end, we propose a novel time-domain artificial noise design which exploits temporal degrees of freedom provided by the cyclic prefix of OFDM systems {to jam the eavesdropper and boost the secrecy rate even with a single antenna at the transmitter}. Numerical results are provided to illustrate the performance of the proposed design schemes.Comment: 12 pages, 7 figures, accepted by IEEE Transactions on Wireless Communications, Jan. 201

Arbitrary Convergence Time Control for Aerial Manipulator with TSK Estimator

This paper investigates the stable control problem of unmanned aerial manipulator (UAM) in the presence of lumped disturbance, including modelling uncertainties and external inferences. These disturbances typically involve limited prior knowledge and change rapidly, presenting considerable challenges to real-time control accuracy. To address this issue, a Takagi-Sugeno-Kang estimator (TSKE) with K-closest fuzzy rules interpolation (K-FRI) is proposed to derive an approximation for the uncertain disturbances. The incorporation of K-FRI enhances the accuracy and convergence rate of the estimation under the conditions of a sparse fuzzy rule base with an incomplete fuzzy quantity space. Subsequently, a backstepping controller with arbitrary convergence time is introduced to guarantee the rapid and precise control of the UAM. The stability of both the TSKE and the controller with arbitrary convergence time is analysed through Lyapunov theory. The feasibility and performance of the proposed control strategy are validated via comparative experimental simulations, demonstrating its ability for robust estimation capability with stable control performance, at any convergence time of the UAM working under lumped disturbance

A Methylene Blue-Selective Membrane Electrode Using Methylene Blue-Phosphotungstate as Electroactive Material and its Pharmaceutical Applications

A methylene blue poly (vinyl chloride) membrane electrode based on methylene blue-phosphotungstate ion-pair complex as electroactive material is described. The linear response covered the range of 1 × 10–3 – 1 × 10–6 mol dm–3 methylene blue solution, with a slope of 51.5 ±0.8 mV/decade (pH range 3.0–10.0). The detection limit was 6.79 × 10–7 mol dm–3. The electrode showed stability, good reproducibility and a fast response. Interferences from common inorganic cations and some organic bases were negligible. These characteristics of the electrode enabled its successful use for determination of methylene blue in injection. There was good agreement for the results of methylene blue content in injection between the potentiometric method and the United States Pharmacopoeia standard procedure

Arbitrary Convergence Time Control for Aerial Manipulator with TSK Estimator

This paper investigates the stable control problem of unmanned aerial manipulator (UAM) in the presence of lumped disturbance, including modelling uncertainties and external inferences. These disturbances typically involve limited prior knowledge and change rapidly, presenting considerable challenges to real-time control accuracy. To address this issue, a Takagi-Sugeno-Kang estimator (TSKE) with K-closest fuzzy rules interpolation (K-FRI) is proposed to derive an approximation for the uncertain disturbances. The incorporation of K-FRI enhances the accuracy and convergence rate of the estimation under the conditions of a sparse fuzzy rule base with an incomplete fuzzy quantity space. Subsequently, a backstepping controller with arbitrary convergence time is introduced to guarantee the rapid and precise control of the UAM. The stability of both the TSKE and the controller with arbitrary convergence time is analysed through Lyapunov theory. The feasibility and performance of the proposed control strategy are validated via comparative experimental simulations, demonstrating its ability for robust estimation capability with stable control performance, at any convergence time of the UAM working under lumped disturbance