Hierarchically controlled remote preparation of an arbitrary single-qubit state by using a four-qubit $$|\chi \rangle $$ entangled state

In this paper, we present a scheme for Hierarchically controlled remote preparation of an arbitrary single-qubit state via a four-qubit \(|\chi \rangle \) state as the quantum channel. In this scheme, a sender wishes to help three agents to remotely prepare a quantum state, respectively. The three agents are divided into two grades, that is, an agent is in the upper grade and other two agents are in the lower grade. It is shown that the agent of the upper grade only needs the assistance of any one of the other two agents for recovering the sender’s original state, while an agent of the lower grade needs the collaboration of all the other two agents. In other words, the agents of two grades have different authorities to recover sender’s original state.     

Quantum private comparison protocol based on the entanglement swapping between $$\chi ^+$$ state and W-Class state

Quantum private comparison (QPC) protocol, including Alice, Bob and the third party Charlie, aims at comparing Alice and Bob’s secret inputs correctly without leaking them. Firstly, \(\chi ^+\) state and W-Class state are used to conduct the entanglement swapping in this protocol. Either the basis \(\{|\phi ^\pm \rangle ,|\psi ^\pm \rangle \}\) or the basis \(\{|\chi ^\pm \rangle ,|\omega ^\pm \rangle \}\) is chosen by Alice and Bob based on the predetermined value to measure the particle pairs. And three bits of secret inputs can be compared in this protocol in every comparison time, while most of previous QPC protocols can only compare one or two bits. The qubit efficiency of this protocol is 60% more than others, which are 50% at most. Secondly, if the eavesdropper intends to obtain the secret inputs, it is important and primary to get the measurement results of particle pairs. In this protocol, even if the eavesdropper gets the accurate particle pairs, he cannot get the right measurement results without the right basis. Finally, this protocol is analyzed to be able to defend the secret inputs against various kinds of attack.     

Multi-party quantum state sharing of an arbitrary multi-qubit state via \chi -type entangled states

By using the \(\chi \) -type entangled states, a novel scheme for multi-party quantum state sharing (MQSTS) of an arbitrary multi-qubit state is investigated. It is shown that the MQSTS scheme can be faithfully realized by performing appropriate Bell state measurements, Z basis measurements and local unitary operations, rather than multi-qubit entanglement or multi-particle joint measurements. Thus, our MQSTS scheme is more convenient in a practical application than some previous schemes. Furthermore, its intrinsic efficiency for qubits approaches 100 %, and the total efficiency really approaches the maximal value, which is higher than those of the previous MQSTS schemes. Finally, we analyze the security from the views of participant attack and outside attack in detail.     

$$H_\infty $$ state estimation of stochastic neural networks with mixed time-varying delays

This paper is concerned with \(H_\infty \) state estimation problem of stochastic neural networks with discrete interval and distributed time-varying delays. The time-varying delay is need to be bounded and continuous. By constructing a suitable Lyapunov–Krasovskii functional with triple integral terms and linear matrix inequality technique, the delay-dependent criteria are conferred so that the error system is stochastically asymptotically mean-square stable with \(H_\infty \) performance. The desired estimator gain matrix can be characterized in terms of the solution to linear matrix inequalities, which can be easily solved by some standard numerical algorithms. Numerical simulations are given to demonstrate the effectiveness of the proposed method. The results are also compared with existing methods.     

Indicator Selection of Index Construction by Adaptive Lasso with a Generic $$\varepsilon $$ -Insensitive Loss

Computational Economics - A successful index helps policy decision makers identify benchmark performances and trends and set policy priorities. Selecting representative variables from a large...     

Generation of an arbitrary four-photon polarization-entangled decoherence-free state with cross-Kerr nonlinearity

We present a new scheme to provide an arbitrary four-photon polarization-entangled state, which enables the encoding of single logical qubit information into a four-qubit decoherence-free subspace robustly against collective decoherence. With the assistance of the cross-Kerr nonlinearities, a spatial entanglement gate and a polarization entanglement gate are inserted into the circuit, where the X-quadrature homodyne measurement is properly performed. According to the outcomes of homodyne measurement in the spatial entanglement process, some swap gates are inserted into the corresponding paths of the photons to swap their spatial modes. Apart from Kerr media, some basic linear optical elements are necessary, which make it feasible with current experimental techniques.     

Ordering states with Tsallis relative $$\alpha $$-entropies of coherence

In this paper, we study the ordering states with Tsallis relative \(\alpha \)-entropies of coherence and \(l_{1}\) norm of coherence for single-qubit states. Firstly, we show that any Tsallis relative \(\alpha \)-entropies of coherence and \(l_{1}\) norm of coherence give the same ordering for single-qubit pure states. However, they do not generate the same ordering for some high-dimensional states, even though these states are pure. Secondly, we also consider three special Tsallis relative \(\alpha \)-entropies of coherence for \(\alpha =2, 1, \frac{1}{2}\) and show these three measures and \(l_{1}\) norm of coherence will not generate the same ordering for some single-qubit mixed states. Nevertheless, they may generate the same ordering if we only consider a special subset of single-qubit mixed states. Furthermore, we find that any two of these three special measures generate different ordering for single-qubit mixed states. Finally, we discuss the degree of violation of between \(l_{1}\) norm of coherence and Tsallis relative \(\alpha \)-entropies of coherence. In a sense, this degree can measure the difference between these two coherence measures in ordering states.     

Quantum teleportation of a generic two-photon state with weak cross-Kerr nonlinearities

We present a scheme for teleporting a generic two-photon polarization state by using two EPR states as quantum channel based on weak cross-Kerr nonlinearities. As the core component of the present framework, the quantum nondemolition detector based on the weak cross-Kerr nonlinearity acts as an EPR entangler as well as the Bell-state analyzer. This makes the teleportation protocol be achieved near deterministically and be feasible in the current experimental technology.     

Approximate conditional teleportation of a $$\varLambda $$-type three-level atomic state based on cavity QED method beyond Bell-state measurement

Inspiring from the scheme proposed in (Zheng in Phys Rev A 69:064,302 2004), our aim is to teleport an unknown qubit atomic state using the cavity QED method without using the explicit Bell-state measurement, and so the additional atom is not required. Two identical \(\varLambda \)-type three-level atoms are interacted separately and subsequently with a two-mode quantized cavity field where each mode is expressed with a single-photon field state. The interaction between atoms and field is well described via the Jaynes–Cummings model. It is then shown that how if the atomic detection results a particular state of atom 1, an unknown state can be appropriately teleported from atom 1 to atom 2. This teleportation procedure successfully leads to the high fidelity F (success probability \(P_g\)) in between \(69\%\lesssim F\lesssim 100\%\) (\(0.14\lesssim P_g\lesssim 0.56\)). At last, we illustrated that our scheme considerably improves similar previous proposals.     

The preparation of organic light-emitting diode encapsulation barrier layer by low-temperature plasma-enhanced chemical vapor deposition: a study on the $$\hbox {SiO}_\mathrm{x}\hbox {N}_\mathrm{y}$$ film parameter optimization

This study prepared \(\hbox {SiO}_\mathrm{x}\hbox {N}_\mathrm{y}\) film by using plasma-enhanced chemical vapor deposition in organic light-emitting diode (OLED) encapsulation to prevent the invasion of moisture and oxygen for longer light-emitting lifetime of OLED components. It applied high density inductively coupled plasma for the coating of film on polyethersulfone, silicon and glass substrate, and discussed the relevance between process parameters and quality characteristics including coating uniformity, coating thickness and moisture permeation. This study used Taguchi method to plan the experiment and calculated the optimal parameters of each quality, used technique for order preference by similarity to ideal solution and grey relational analysis to determine the optimal parameter of all qualities. The back-propagation neural network was combined with Levenberg–Marquardt algorithm to construct the simulation and prediction system. Based on the quality optimization design, the single layer film’s moisture permeation rate was 0.02 g/m\(^{2}\)/day, the maximum coating thickness reached 420 nm, and the fastest rate was 21 nm/min, which was higher than the industrial standard specification (10 nm/min) by 110 %.     

High granular and short term time series forecasting of $$\hbox {PM}_{2.5}$$ PM 2.5 air pollutant - a comparative review

Forecasting time series has acquired immense research importance and has vast applications in the area of air pollution monitoring. This work attempts to investigate the abilities of various existing techniques when applied for short term, high granular time series forecasting of PM_2.5. More specifically, a comparative study has been provided, taking into account both popularly used models and lesser-used models in this area. The study has been carried out considering ten well defined models that are ARIMA (auto-regressive integrated moving average), SARIMA (seasonal ARIMA), SES (single exponential smoothing), DES (double exponential smoothing), TES (triple exponential smoothing), ANN (artificial neural network), DT (decision tree), kNN (k-nearest neighbor), LSTM (long short-term memory) and MCFO (markov chain first order). A framework has been built that categories the models, implements them under identical execution environment and forecasts succeeding values. Implementation has been carried out over five data sets of real-world air pollution time series, that are collected from five differently located government setup monitoring stations over a period of 1 year (July 2018-June 2019). Rigorous statistical analysis has been performed that yields an insight to the nature and variability of these time series data. Forecasting has been carried out on short term basis, focusing on high granularity whereas, three different lengths of forecast horizon (1 day, 1 week, and 1 month) have been tested. Eventually, the models have been compared in terms of their associated performance measuring units namely, RMSE (root mean of squared error), MAE (mean absolute error) and MAPE (mean absolute percentage error). The comparative results verified with multiple datasets show that all the models posses less error for a shorter forecast horizon, where LSTM providing the best performance. Superiority of machine learning and deep learning models are found in case of longer length of forecast horizon with kNN achieving best accuracy whereas, significant performance degradation of ARIMA is found for longer forecast horizon. Moreover, TES, DT, kNN, LSTM, MCFO are found to be well adopted in relation with shape and variability of the data. Note that the performance on various length of high granular forecast horizon have been studied over multiple datasets that give an added value to this work.

     

Dyamic modelig ad trackig cotrol of a car with $$ trailers

Tractor–trailer systems as multibody modular robotic systems have been widely used to increase load transportation capacity. Control of these systems started from motion aid facilities in human-driven vehicles to fully autonomous mobile robots in recent years. The mobility of these systems is restricted due to the presence of nonholonomic constraints of wheels and also to the system severe underactuated nature. Several control problems are under research for autonomous navigation of such systems. Trajectory tracking is one of the main problems in the context of autonomous nonholonomic systems. In this paper, dynamic modeling and control of a car with \(n\) trailers have been developed. First, a dynamic model of the system is obtained. Next, an output feedback kinematic controller and a feedback linearization kinetic controller have been used for tracking control of the system. Finally, experimental results are presented to show the merits of the proposed method.     

Discrete p-robust $$\varvec{H}({{\mathrm{div}}})$$-liftings and a posteriori estimates for elli ptic problems with $$H^{-1}$$H-1 source terms

We establish the existence of liftings into discrete subspaces of \(\varvec{H}({{\mathrm{div}}})\) of piecewise polynomial data on locally refined simplicial partitions of polygonal/polyhedral domains. Our liftings are robust with respect to the polynomial degree. This result has important applications in the a posteriori error analysis of parabolic problems, where it permits the removal of so-called transition conditions that link two consecutive meshes. It can also be used in the a posteriori error analysis of elliptic problems, where it allows the treatment of meshes with arbitrary numbers of hanging nodes between elements. We present a constructive proof based on the a posteriori error analysis of an auxiliary elliptic problem with \(H^{-1}\) source terms, thereby yielding results of independent interest. In particular, for such problems, we obtain guaranteed upper bounds on the error along with polynomial-degree robust local efficiency of the estimators.     

Goal-oriented state control of a cognitive linear model with a bounded state space

Representing the basic concept of this paper, cognitive map is used to construct a cognitive linear dynamic model with a bounded state space. We consider the problem of transferring this model from an arbitrary initial state to some asymptotically stable state belonging to a neighborhood of a given state. We suggest two classes of controls and introduce the transfer “quality” as the proximity of the resulting steady state to the desired state. And finally, an illustrative example is provided.     

Ground state solutions of Pohoz̆aev type for fractional Choquard equations with general nonlinearities

In this paper, we study the fractional Choquard equation

${(?\Delta )}^{s}u+u=\left(\right|x{|}^{?\mu }1F\left(u\right))f\left(u\right),\text{in}{\mathbb{R}}^N,$

where $N\ge 3$, $0<s<1$, $0<\mu <min\{N,4s\}$, and $f\in C(\mathbb{R},\mathbb{R})$ satisfies the general Berestycki–Lions conditions. Combining constrained variational method with deformation lemma, we obtain a ground state solution of Pohoz?aev type for the above equation. The result improves some ones in Shen et al. (2016).     

Global state feedback stabilisation for a class of high-order nonlinear systems with quantised input and state

In this paper, we aim at addressing the problem of global state feedback stabilisation for a class of high-order nonlinear systems with quantised input and state. The nonlinear functions of the system are bounded by both low-order and high-order terms multiplied by a polynomial-type incremental rate. With the combination of homogeneous domination approach and sector bound approach, a quantised controller computed from quantised state is constructed and a guideline is derived for selecting the parameters of the quantisers. Further, it is proved that, with the proposed scheme, the closed-loop system is globally asymptotically stable.     

An interpretation of typed OOP in a language with state

In this paper we give semantics toLoop, an expressive typed object-oriented programming language with updatable instance variables.Loop has a rich type system that allows for the typing of methods operating over an open-ended self type. We prove the type system given is sound;i.e., well-typed programs do not experience message not understood errors. The semantics ofLoop is given by a translation into a state-based language,Soop, that contains reference cells, records, and a form of F-bounded polymorphic type.Partially supported by NSF grant CCR-9109070Partially supported by AFOSR grant F49620-93-1-0169