Entanglement-assisted operator codeword stabilized quantum codes

In this paper, we introduce a unified framework to construct entanglement-assisted quantum error-correcting codes (QECCs), including additive and nonadditive codes, based on the codeword stabilized (CWS) framework on subsystems. The CWS framework is a scheme to construct QECCs, including both additive and nonadditive codes, and gives a method to construct a QECC from a classical error-correcting code in standard form. Entangled pairs of qubits (ebits) can be used to improve capacity of quantum error correction. In addition, it gives a method to overcome the dual-containing constraint. Operator quantum error correction (OQEC) gives a general framework to construct QECCs. We construct OQEC codes with ebits based on the CWS framework. This new scheme, entanglement-assisted operator codeword stabilized (EAOCWS) quantum codes, is the most general framework we know of to construct both additive and nonadditive codes from classical error-correcting codes. We describe the formalism of our scheme, demonstrate the construction with examples, and give several EAOCWS codes     

Entanglement-assisted quantum MDS codes constructed from negacyclic codes

Recently, entanglement-assisted quantum codes have been constructed from cyclic codes by some scholars. However, how to determine the number of shared pairs required to construct entanglement-assisted quantum codes is not an easy work. In this paper, we propose a decomposition of the defining set of negacyclic codes. Based on this method, four families of entanglement-assisted quantum codes constructed in this paper satisfy the entanglement-assisted quantum Singleton bound, where the minimum distance satisfies \(q+1 \le d\le \frac{n+2}{2}\). Furthermore, we construct two families of entanglement-assisted quantum codes with maximal entanglement.     

Entanglement-assisted quantum MDS codes from negacyclic codes

The entanglement-assisted formalism generalizes the standard stabilizer formalism, which can transform arbitrary classical linear codes into entanglement-assisted quantum error-correcting codes (EAQECCs) by using pre-shared entanglement between the sender and the receiver. In this work, we construct six classes of q-ary entanglement-assisted quantum MDS (EAQMDS) codes based on classical negacyclic MDS codes by exploiting two or more pre-shared maximally entangled states. We show that two of these six classes q-ary EAQMDS have minimum distance more larger than \(q+1\). Most of these q-ary EAQMDS codes are new in the sense that their parameters are not covered by the codes available in the literature.     

Entanglement-assisted quantum MDS codes constructed from constacyclic codes

Recently, entanglement-assisted quantum error-correcting codes (EAQECCs) have been constructed by cyclic codes and negacyclic codes. In this paper, by decomposing the defining set of constacyclic codes, we construct four classes of new EAQECCs, which satisfy the entanglement-assisted quantum Singleton bound.     

量子力学系统的输出反馈控制

研究量子系统输出反馈控制问题建模以及控制律设计问题.首先讨论了量子力学VonNeumann测量原理与连续测量模型的一致性;然后在连续测量模型的基础上总结了已有量子反馈模型的结果,归纳出量子输出反馈控制系统模型;最后针对单比特振幅退相干抑制问题,利用线性直接输出反馈控制设计反馈控制律,指出利用最优控制的方法设计线性输出反馈控制的比例系数,可以得到较好的结果.     

On the quantum master equation under feedback control

The nature of the quantum trajectories, described by stochastic master equations, may be jump-like or diffusive, depending upon different measurement processes. There are many different unravelings corresponding to different types of stochastic master equations for a given master equation. In this paper, we study the relationship between the quantum stochastic master equations and the quantum master equations in the Markovian case under feedback control. We show that the corresponding unraveling no longer exists when we further consider feedback control besides measurement. It is due to the fact that the information gained by the measurement plays an important role in the control process. The master equation governing the evolution of ensemble average cannot be restored simply by eliminating the noise term unlike the case without a control term. By establishing a fundamental limit on performance of the master equation with feedback control, we demonstrate the differences between the stochastic master equation and the master equation via theoretical proof and simulation, and show the superiority of the stochastic master equation for feedback control.     

随机开放量子系统的纯态开关反馈控制EI北大核心CSCD

针对目标态为纯态的情况,本文对有限维随机开放量子系统,提出一种同时适用于本征态和叠加态的开关控制,它是由常量控制和基于李雅普诺夫方法设计的控制律组成,实现随机开放量子系统的状态转移和收敛控制,其中,李雅普诺夫函数为系统的状态距离,常量控制用来驱动系统状态从初始状态进入含有目标态的收敛域中,李雅普诺夫控制用来使进入收敛域中的状态继续收敛到期望的目标态.将所提出的控制方法,应用于2比特随机开放量子系统进行了数值仿真实验,并与本征态开关控制律方法进行了性能对比,实验结果表明了所提出的控制律的优越性.     

State space modelling of the quantum feedback control system in interacting fock space

In this paper we introduce a formulation of the quantum mechanical feedback system in order to understand the quantum system in interacting Fock space which generalizes the transfer function approach to the quantum mechanical feedback system studied in bosonic mode. A mathematical model of the feedback control of the cavity quantum electrodynamic system in the interacting Fock space with the second cavity in the feedback path is described using a beam splitter.     

Discrete-time controllability for feedback quantum dynamics

Controllability properties for discrete-time, Markovian quantum dynamics are investigated. We find that, while in general the controlled system is not finite-time controllable, feedback control allows for arbitrary asymptotic state-to-state transitions. Under further assumptions on the form of the measurement, we show that finite-time controllability can be achieved in a time that is twice the dimension of the system, and we provide an iterative procedure to design the unitary control actions.     

Cascade cavity realization for a class of complex transfer functions arising in coherent quantum feedback control

This paper presents a realization algorithm for a class of complex transfer function matrices corresponding to physically realizable linear quantum systems. The aim of the realization algorithm is to enable a coherent quantum feedback controller, which has been synthesized using methods such as quantum H^∞ control or quantum LQG control, to be constructed using optical components such as cavities and phase-shifters. The class of linear quantum systems under consideration are passive linear quantum systems which can be described purely in terms of annihilation operators. The proposed algorithm enables a complex transfer function matrix to be realized as a pure cascade connection involving only cavities and phase-shifters.     

Eigensystem assignment by feedback control

A design method is introduced for regulators using state feedback with specified stability margin and gain constraints. The method offers design parameters which may be used in enhancing the system robustness as well as modifying the maximum absolute values of selected variables, such as control inputs, state variables, or output variables. An illustrative example is included.     

Reinforcement learning in feedback control

Technical process control is a highly interesting area of application serving a high practical impact. Since classical controller design is, in general, a demanding job, this area constitutes a highly attractive domain for the application of learning approaches??in particular, reinforcement learning (RL) methods. RL provides concepts for learning controllers that, by cleverly exploiting information from interactions with the process, can acquire high-quality control behaviour from scratch. This article focuses on the presentation of four typical benchmark problems whilst highlighting important and challenging aspects of technical process control: nonlinear dynamics; varying set-points; long-term dynamic effects; influence of external variables; and the primacy of precision. We propose performance measures for controller quality that apply both to classical control design and learning controllers, measuring precision, speed, and stability of the controller. A second set of key-figures describes the performance from the perspective of a learning approach while providing information about the efficiency of the method with respect to the learning effort needed. For all four benchmark problems, extensive and detailed information is provided with which to carry out the evaluations outlined in this article. A close evaluation of our own RL learning scheme, NFQCA (Neural Fitted Q Iteration with Continuous Actions), in acordance with the proposed scheme on all four benchmarks, thereby provides performance figures on both control quality and learning behavior.     

Policy iteration based feedback control

It is well known that stochastic control systems can be viewed as Markov decision processes (MDPs) with continuous state spaces. In this paper, we propose to apply the policy iteration approach in MDPs to the optimal control problem of stochastic systems. We first provide an optimality equation based on performance potentials and develop a policy iteration procedure. Then we apply policy iteration to the jump linear quadratic problem and obtain the coupled Riccati equations for their optimal solutions. The approach is applicable to linear as well as nonlinear systems and can be implemented on-line on real world systems without identifying all the system structure and parameters.     

Optimal control during feedback failure

The problem of controlling a perturbed open loop system so as to keep its performance errors within bounds is considered. The objective is to maximise the time during which performance errors remain below a prescribed ceiling, while the controlled system's parameters are within a specified neighbourhood of their nominal values. It is shown that there is an optimal open loop controller that achieves this objective. Conditions under which the optimal controller generates a bang-bang control input signal are characterised. In general, it is shown that the performance of the optimal controller can always be approximated by a bang-bang signal.     

Periodicity in Delta-modulated feedback control

The Delta-modulated feedback control of a linear system introduces nonlinearity into the system through switchings between two input values. It has been found that Delta-modulation gives rise to periodic orbits. The existence of periodic points of all orders of Sigma-Delta modulation with ＂leaky＂ integration is completely characterized by some interesting groups of polynomials with ＂sign＂ coefficients. The results are naturally generalized to Sigma-Delta modulations with multiple delays, Delta-modulations in the ＂downlink＂, unbalanced Delta-modulations and systems with two-level quantized feedback. Further extensions relate to the existence of periodic points arising from Delta-modulated feedback control of a stable linear system in an arbitrary direction, for which some necessary and sufficient conditions are given.     

Dynamics of nonlinear feedback control

Feedback control in neural systems is ubiquitous. Here we study the mathematics of nonlinear feedback control. We compare models in which the input is multiplied by a dynamic gain (multiplicative control) with models in which the input is divided by a dynamic attenuation (divisive control). The gain signal (resp. the attenuation signal) is obtained through a concatenation of an instantaneous nonlinearity and a linear low-pass filter operating on the output of the feedback loop. For input steps, the dynamics of gain and attenuation can be very different, depending on the mathematical form of the nonlinearity and the ordering of the nonlinearity and the filtering in the feedback loop. Further, the dynamics of feedback control can be strongly asymmetrical for increment versus decrement steps of the input. Nevertheless, for each of the models studied, the nonlinearity in the feedback loop can be chosen such that immediately after an input step, the dynamics of feedback control is symmetric with respect to increments versus decrements. Finally, we study the dynamics of the output of the control loops and find conditions under which overshoots and undershoots of the output relative to the steady-state output occur when the models are stimulated with low-pass filtered steps. For small steps at the input, overshoots and undershoots of the output do not occur when the filtering in the control path is faster than the low-pass filtering at the input. For large steps at the input, however, results depend on the model, and for some of the models, multiple overshoots and undershoots can occur even with a fast control path.