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Necessary and sufficient conditions for arbitrary multimode (pure or mixed) Gaussian states to be equivalent under incoherent Gaussian operations are derived. We show that two Gaussian states are incoherent equivalence if and only if they are related by incoherent unitaries. This builds the counterpart of the celebrated result that two pure entangled states are equivalent under LOCC if and only if they are related by local unitaries. Furthermore, incoherent equivalence of Gaussian states is equivalent to frozen coherence [Phys. Rev. Lett. \textbf{114}, 210401 (2015)]. Basing this as foundation, we find all measures of coherence are frozen for an initial Gaussian state under strongly incoherent Gaussian operations if and only if the relative entropy measure of coherence is frozen for the state. This gives an entropy-based dynamical condition in which the coherence of an open quantum system is totally unaffected by noise., Comment: 7 pages, 59 references, accepted for publication in PRA

A vertical line array can be deployed in deep water below the critical depth, the depth where the sound speed equals the sound speed at the surface, to take advantage of the lower ambient noise level (compared with above the critical depth) for target detection. To differentiate a submerged source from a surface source, a Fourier transform based method [McCargar and Zurk, J. Acoust. Soc. Am. 133, EL320-325 (2013)] was proposed for a narrowband signal that exploits the depth-related harmonic (oscillation) feature of the beam power time series associated with the target arrival. In this paper, incoherent matched beam processing is used to estimate the target depth. Where the replica (calculated) beam intensity or amplitude time series best matches that of the data is used to estimate the source depth. This method is shown, based on simulated data, to provide a better depth resolution in general and better ability to estimate the depth of a very shallow source (say at 10 m) and can be used to complement the Fourier transform based method. It can be extended to process (random) broadband signals and to environments where the Lloyd's mirror theory is not valid.

The coherence resource theory needs to study the operational value and efficiency which can be broadly formulated as the question: when can one coherent state be converted into another under incoherent operations. We answer this question completely for one-mode continuous-variable systems by characterizing conversion of coherent Gaussian states under incoherent Gaussian operations in terms of their first and second moments. The no-go theorem of purification of coherent Gaussian states is also built. The structure of incoherent Gaussian operations of two-mode continuous-variable systems is discussed further and is applied to coherent conversion for pure Gaussian states with standard second moments. The standard second moments are images of all second moments under local linear unitary Bogoliubov operations. As concrete applications, we obtain some peculiarities of a Gaussian system: (1) There does not exist a maximally coherent Gaussian state which can generate all coherent Gaussian states; (2) The conversion between pure Gaussian states is reversible; (3) The coherence of input pure state and the coherence of output pure state are equal., 9 pages,48 references,To appear in Physical Review A

The classification and recognition of underwater target by active sonar echo remains a challenging task due to the complex ocean environment and the multiple interferers in the sea. In this paper, an underwater target recognition method is proposed based on multi-domain active sonar echo images. The active sonar echo is first preprocessed to generate images in multiple domains. Then a deep neural network is constructed which is composed of a shared network and several domain-specific attention modules. The shared network is trained on images in all domains to get the global generalized features. The domain-specific features are then further extracted from the global feature through the attention module in each domain. The co-utilization of images in all domains enlarges the data size for training and enhances the feature representation ability of the model. Experiment results demonstrate that the features extracted from the proposed method get better recognition performance than network trained on images in single domain.

Strictly incoherent operations (SIO) proposed in [Phys. Rev. Lett. 116, 120404 (2016)] are promising to be a good candidate of free operations in the resource theory of quantum coherence, setting against the central role of local operations and classical communication in the resource theory of quantum entanglement. An important open problem is an efficient description for strictly incoherent operations in physical region. Such a description plays key role for axiomatic study of resource theory of quantum coherence. We are aimed to give a structural characterization of bistochastic SIOs in terms of Pauli operators and the Phase operator for one-qubit systems. Some applications of our results are also sketched in reconstructing quantum thermal averages via a quantum computer and in coherence manipulation., 5 pages,46 references

As an important quantum resource, quantum coherence play key role in quantum information processing. It is often concerned with manipulation of families of quantum states rather than individual states in isolation. Given two pairs of coherent states $(\rho_1,\rho_2)$ and $(\sigma_1,\sigma_2)$, we are aimed to study how can we determine if there exists a strictly incoherent operation $\Phi$ such that $\Phi(\rho_i) =\sigma_i,i = 1,2$. This is also a classic question in quantum hypothesis testing. In this note, structural characterization of coherent preorder under strongly incoherent operations is provided. Basing on the characterization, we propose an approach to realize coherence distillation from rank-two mixed coherent states to $q$-level maximally coherent states. In addition, one scheme of coherence manipulation between rank-two mixed states is also presented., Comment: 14 pages,73 references, to appear in Quantum Information & Computation 2020

The spectrum line parameters of underwater target radiated noise are important basis for underwater target recognition. In this paper, the convolution neural network (CNN) is applied to estimate the spectrum line parameters. The low frequency analysis record (LOFAR) spectrum of radiated noise is used as input data, and a suitable convolution neural network is constructed to estimate the spectrum line parameters. The processing results of simulation data show that the estimation sensitivity of convolution neural network reaches 91.6% under the condition of low SNR. It proves the effectiveness of CNN in estimating spectrum line parameters of underwater targets.

Coherence manipulation is fundamental in the study of the resource theory of quantum coherence. It is aimed at identifying when it is possible to convert a given coherent state to another using only incoherent operations. In this paper, it is shown that a finite number of measure conditions are not sufficient to characterize coherence manipulation on general mixed states. Further, a finite number of measure conditions to classify coherence manipulation on subspace-independent states are found. For the input pure state, we also furnish a structural characterization of coherence manipulation in terms of a finite number of measure conditions.

In our previous paper “Coherence measures and optimal conversion for coherent states” [Quantum Information and Computation, Vol. 15(2015), 1307-1316], there is an error in the proof of Theorem 1. Here, we correct the error.

The analysis and optimization for underwater target radiated noise recognition are addressed. The t-SNE (t-distributed stochastic neighbor embedding) algorithm is taken for dimension reduction of the underwater target radiated noise spectrum bands segmented by frequency and the visual results can be obtained. The average distance between classes and coincidence rate are constructed as indicators of the visualization results. By analyzing the separability of each frequency band, the optimal features can be obtained. Then the optimal features are recognized by three classification algorithms which are Random Forest, SVM (Support Vector Machine) and AdaBoost. The processing results of experimental signal spectrum with two types of target are as follows. The separability of the target signal spectrum decreases with the increase of frequency. The spectrum band of 10-150Hz has the best separability. SVM is sensitive to the increase of the data dimension with non optimal separability. Random Forests and AdaBoost can apply separability components in wider frequency bands and have greater tolerance. The overall recognition accuracy of AdaBoost is the highest, but the computation efficiency is the lowest. These analysis results shows that the t-SNE algorithm can be used to optimize the underwater target radiated noise spectrum features for the purpose of improving the accuracy and efficiency of the classification algorithm.

Relative entropy measure quantifying coherence, a key property of quantum system, is proposed recently. In this note, we investigate the maximally coherent state (MCS) with respect to relative entropy measure. %(denoted by $\mathcal C_{RE}$)%. We show that there are not mixed maximally coherent states and give a complete characterization of pure maximally coherent states. Based on this characterization, for a bipartite MCS with $d_A=d_B$, we obtain that the super-additivity equality of relative entropy measure holds if and only if the state is a product state of its reduced states. From the viewpoint of resource in quantum information, we find there exists a MCS with maximal entanglement. Originated from the behaviour of quantum correlation under the influence of noisy operations, we further classify the incoherent operations which send maximally coherent states to themselves., in Quantum Information & Computation 2015

Aiming at the problem that the elastic wave of the elastic target in the water and the specular wave will cause aliasing in time in the low-frequency broadband long pulse excitation, it is difficult to directly observe the elastic wave characteristic. In this paper, a signal processing method is proposed to make the weak elastic wave energy in the strong specular wave be observed and analyzed in the low-frequency broadband long pulse excitation, which can provide clues for the feature extraction and target recognition of low frequency active sonar target echo.

This paper proposes a method to estimate the target velocity using a combination of two hyperbolic frequency-modulated (HFM) signals. The Doppler-shifted time-delay between the two signals compared with the original time-delay is used to estimate the target velocity. One finds that a HFM with an increasing frequency sweep (positive HFM) and one with a decreasing frequency sweep (negative HFM) yield a different time. And a better Doppler estimation can be obtained by using a negative HFM signal followed by a positive HFM signal than the other way around. The method is applied to real data and performance is demonstrated via simulated data.

With the constant research on the anti-capture strategy of Autonomous Underwater Vehicles(AUVs), it is more and more difficult for the AUVs to hunt motion. To this end, a multi-layer annular ambush capture model to improve the success rate of arrest. Based on the multi-layer annular ambush capture model, task-based mission assignment based on different characteristics of heterogeneous AUVs carrying energy is carried out. This distribution method enables heterogeneous AUVs to make full use of their own features better completion of the task. At the same time, considering the problem of uneven energy consumption in the system over time, an energy balance method is proposed to balance the energy consumption of the system. The method not only prolongs the life of the entire system and realizes the system running process dynamic task assignment. Experiments show that the method effectively improves the success rate of arrest and system life.

As we know, identification of echoes from underwater objects is important but difficult. In this paper, we newly propose a feature analysis and extraction method of echoes based on sub-band processing. When the transmitted signal is a linear or hyperbolic frequency modulated signal, three waveform features are extracted using our proposed method which works by processing sub-band filtering and sub-band wave correlating. The three features in some way represent the physical properties of the unknown objects which produced the echoes, and it is possible to identify the object according to these three features. Simulation and sea trial data analysis work is undertaken and the results show that, sub-band processing is an effective way for analyzing FM echo characteristics, and the features we extracted have good performance when used for classification of underwater objects.

Let ℳ, 𝒩 be von Neumann algebras with no central summands of type I1 or I2. If Φ : ℳ → 𝒩 is a multiplicative *-Lie isomorphism, then there is a central projection E ∈ 𝒩 such that modulo a centre-valued map which annihilates commutators, EΦ is a linear Lie *-homomorphism and (I − E)Φ is a conjugate linear Lie *-homomorphism.

NNSF of China [11071201]; YNSF of China [11001230]; Fundamental Research Funds for the Central Universities [2010121001]; YNSF of Fujian [2008F3013]

In this article, we get a complete classification of distance preserving surjective maps Φ between nest algebras acting on separable Hilbert spaces.

A novel sifting method based on the concept of the ‘local centroids’ of a signal is developed for empirical mode decomposition (EMD), with the aim of reducing the mode-mixing effect and decomposing those modes whose frequencies are within an octave. Instead of directly averaging the upper and lower envelopes, as suggested by the original EMD method, the proposed technique computes the local mean curve of a signal by interpolating a set of ‘local centroids’, which are integral averages over local segments between successive extrema of the signal. With the ‘centroid’-based sifting, EMD is capable of separating intrinsic modes of oscillatory components with their frequency ratio ν even up to 0.8, thus greatly mitigating the effect of mode mixing and enhancing the frequency resolving power. Inspection is also made to show that the integral property of the ‘centroid’-based sifting can make the decomposition more stable against noise interference.

The empirical mode decomposition (EMD) is applied to extract information of modulation from signals contaminated by noise. The EMD method is capable of recovering the amplitude-modulated components from strong background noise in an adaptive way, and achieves better performance than traditional methods. We further propose a modified EMD technique by estimating the local mean of a signal via windowed average. This method alleviates the unfavorable influence of noise disturbance effectively in the process of sifting and yields a remarkable improvement for the modulation extraction. Finally, by utilizing this novel technique, we achieve the adaptive and effective extraction of the modulated cavitation noise from ship-radiated noise.

Classification for ship-radiated underwater sound is one of the most important and challenging subjects in underwater acoustical signal processing. An approach to ship classification is proposed in this work based on analysis of ship-radiated acoustical noise in subspaces of intrinsic mode functions attained via the ensemble empirical mode decomposition. It is shown that detection and acquisition of stable and reliable nonlinear features become practically feasible by nonlinear analysis of the time series of individual decomposed components, each of which is simple enough and well represents an oscillatory mode of ship dynamics. Surrogate and nonlinear predictability analysis are conducted to probe and measure the nonlinearity and regularity. The results of both methods, which verify each other, substantiate that ship-radiated noises contain components with deterministic nonlinear features well serving for efficient classification of ships. The approach perhaps opens an alternative avenue in the direction toward object classification and identification. It may also import a new view of signals as complex as ship-radiated sound.

Research work on characteristics of echoes scattered by a cylindrical object located in underwater multi-path is introduced in the paper. A sound scattering experiment of a cylindrical object in water-filled tank is carried out, the purpose of which is to give answers to questions of how the multi-path channel corrupt the characteristics of echoes from an elastic body in underwater multi-path channel and how many target-related features can still be extracted in both time and frequency domain which can be used for classification or feature-based detection. Detailed data processing results are shown and analyzed, which may be useful to research on signal processing method of sonar target detection and classification.

The underwater acoustic channel is a complicated and time-varying multipath channel, and many equalization algorithms have been researched and developed to overcome the difficulties for underwater acoustic communication. Unfortunately, many algorithms are computational intensive and prone to lose convergence due to their sensitiveness to different channel configurations. In this paper, a pulse position modulation (PPM) scheme is proposed, and it uses two M-sequences of low cross-correlation to transfer information, which are modulated on two orthogonal carriers. One is used as a reference sequence, and the other is shifted relative to the reference. Information is carried by the starting time difference between the two sequences in each symbol. Comparing with conventional direct-sequence spread spectrum technique, the proposed scheme is more spectral efficient. Two receiver designs are given, one takes advantages of M-sequences’ auto-correlation properties, and the other is motivated by passive phase conjugation (PPC) to take advantages of the channel. Combined with M-sequence, PPC performance is augmented without a receiving array to cover the water column, and it is far less complex than adaptive equalizers for receivers. Results from lake field trials are analyzed, and they verify potential applications of this PPM scheme.

Modulation analysis is an important issue in target classification and identification for ship-radiated noise. However, the modulated cavitation noise sought for analyzing is always submerged under strong ambient noise and difficult to be separated out. In this paper, an approach is proposed to extract the modulated cavitation noise adaptively by combining empirical mode decomposition and singular value decomposition. The results for both synthetical and practical signals demonstrate the practicability and effectivity of the approach.

In this article, we give a thorough discussion of additive maps between nest algebras acting on Banach spaces which preserve rank-one operators in both directions.

Let M , N be factors. If Φ : M → N is a multiplicative ∗-Lie isomorphism, then Φ is of the form σ + τ , where σ is a linear ∗-isomorphism, or a conjugate linear ∗-isomorphism, or the negative of a linear ∗-anti-isomorphism, or the negative of a conjugate linear ∗-anti-isomorphism of M onto N and τ is a mapping of M into C I = { λ I | λ ∈ C } which maps commutators into zero.

Let B(X) be the space of all bounded linear operators on a Banach space X and let LatA be the lattice of invariant subspaces of the operator A∈B(X). We characterize some maps Φ:B(X)→B(X) with one of the following preserving properties: Lat(Φ(A)+Φ(B))=Lat(A+B), or Lat(Φ(A)Φ(B))=Lat(AB), or Lat(Φ(A)Φ(B)+Φ(B)Φ(A))=Lat(AB+BA), or Lat(Φ(A)Φ(B)Φ(A))=Lat(ABA), or Lat([Φ(A),Φ(B)])=Lat([A,B]).

Let ℛ be a prime ring with 1 containing a nontrivial idempotent E, and let ℛ′ be another prime ring. If Φ:ℛ → ℛ′ is a multiplicative Lie isomorphism, then Φ(T + S) = Φ(T) + Φ(S) + Z′ T,S for all T, S ∈ ℛ, where Z′ T,S is an element in the center 𝒵′ of ℛ′ depending on T and S.

Let H be an infinite-dimensional complex separable Hilbert space and denote the algebra of all bounded linear operators acting on H. We show that an additive continuous surjective map Φ on is asymptotic similarity preserving if and only if it is similarity preserving, and in turn, if and only if there exist a scalar c and an invertible bounded linear or conjugate linear operator A on H such that either Φ(T)=cATA −1 for all T or Φ (T)=cAT*A −1 for all T.

Let X be a real or complex Banach space with dimension at least 3, N 1 ( X ) be the family of all rank one nilpotent operators. We give the concrete form of every bijective map Φ : N 1 ( X ) → N 1 ( X ) such that T + S ∈ N 1 ( X ) ⇔ Φ ( T ) + Φ ( S ) ∈ N 1 ( X ) . Based on this result, we characterize the surjective map Φ : B ( H ) → B ( H ) withT ± S ∼ R ⇔ Φ ( T ) ± Φ ( S ) ∼ Φ ( R ) for all T , S , R ∈ B ( H ) , where H is a Hilbert space (real or complex) with dimension at least 3.

We build the counterpart of the celebrated Nielsen's theorem for coherence manipulation in this paper. This offers an affirmative answer to the open question: whether, given two states $\rho$ and $\sigma$, either $\rho$ can be transformed into $\sigma$ or vice versa under incoherent operations [Phys. Rev. Lett. \textbf{113}, 140401(2014)]. As a consequence, we find that there exist essentially different types of coherence. Moreover, incoherent operations can be enhanced in the presence of certain coherent states. These extra states are coherent catalysts: they allow uncertain incoherent operations to be realized, without being consumed in any way. Our main result also sheds a new light on the construction of coherence measures., Comment: arXiv admin note: text overlap with arXiv:1311.0275 by other authors. 03.65.Ud, 03.67.Ta. in Physical Review A 2015

We found that the Wigner-Yanase skew information, which has been recently proposed as a measure of coherence in [Phys. Rev. Lett. \textbf{113}, 170401(2014)], can increase under a class of operations which may be interpreted as incoherent following the framework of Baumgratz et al., while being phase sensitive.

We discuss a general strategy to construct coherence measures. One can build an important class of coherence measures which cover the relative entropy measure for pure states, the $l_1$-norm measure for pure states and the $\alpha$-entropy measure. The optimal conversion of coherent states under incoherent operations is presented which sheds some light on the coherence of a single copy of a pure state., Comment: in Quantum Information & Computation 2015

Let X be an infinite dimensional complex Banach space and denote B (X) the algebra of all bounded linear operators acting on X. We show that an additive surjective map on B (X) preserves asymptotic similarity in both directions if and only if there exist a nonzero scalar c, an invertible bounded linear or conjugate linear operator A and an asymptotic similarity invariant additive functional φ on B (X) such that either Φ(T)=cATA−1+φ(T)I for all T or Φ(T)=cAT ∗ A −1 +φ(T)I for all T. In the case that X has infinite multiplicity, especially if X is an infinite dimensional Hilbert space, above asymptotic similarity invariant additive functional φ is always zero.

Let H be a separable complex infinite-dimensional Hilbert space. All similarity invariant real linear subspaces of B(H), the Banach algebra of all bounded linear operators on H, are characterized. As an application, all continuous additive surjective maps on B(H) which preserving similarity in both directions are completely classified.