Squeezing Operator Research Articles

A quantum heat machine from fast optomechanics

We consider a thermodynamic machine in which the working fluid is a quantized harmonic oscillator that is controlled on timescales that are much faster than the oscillator period. We find that operation in this ‘fast’ regime allows access to a range of quantum thermodynamical behaviors that are otherwise inaccessible, including heat engine and refrigeration modes of operation, quantum squeezing, and transient cooling to temperatures below that of the cold bath. The machine involves rapid periodic squeezing operations and could potentially be constructed using pulsed optomechanical interactions. The prediction of rich behavior in the fast regime opens up new possibilities for quantum optomechanical machines and quantum thermodynamics.

High-fidelity heralded quantum squeezing gate based on entanglement.

Squeezing operation is critical in Gaussian quantum information. A high-fidelity heralded squeezing gate was recently realized using a noiseless linear amplifier with moderate ancillary squeezing. Here we analyze the heralded scheme based on squeezing [J. Zhao, Nat. Photonics, 14, 306 (2020)] and find that its fidelity depends heavily on the purity of auxiliary squeezing, and even the fidelity with a 6 dB pure squeezed state is better than with a 15 dB thermal squeezed state. On this basis, we construct a new heralded squeezing gate based on teleportation, which can overcome the shortcomings of the heralded scheme based on squeezing and is immune to the purity of input squeezing. It can better use the current best available squeezing (15 dB) to realize a perfect squeezing gate for fault-tolerant continuous-variable quantum computation. This scheme is promising to realize other single-mode Gaussian operations and non-classical state squeezing operations.

ADSORPTION-DESORPTION STUDIES OF A COMPLEX-ACTING OILFIELD REAGENT WITH THE PROPERTIES OF A SCALE AND HYDRATE FORMATION INHIBITOR

This work presents the results of laboratory studies of the adsorptiondesorption properties of the developed oilfield reagent with a complex effect, which has the properties of an inhibitor of halite formation, deposits of calcite and gypsum, as well as the properties of an inhibitor of hydrate formation. By the method of dynamic testing, the minimum inhibitory concentration (MIC) of the developed reagent was found for application by the squeeze technology. The results of laboratory experiments were processed using specialized software, and the adsorption isotherm for the developed reagent was obtained. In order to reduce the risks of incompatibility of the developed reagent with highly mineralized formation waters of the field under consideration, additional studies of the compatibility of reagent solutions of different concentrations with formation waters of different salinity and concentration of calcium ions were carried out and a «compatibility matrix» was developed. Based on the work done, a software module has been developed that allows the user to calculate the required volumes of reagent and other process fluids for a particular well to carry out the squeeze operation with the planned period of protection.

Amplification of quadratic Hamiltonians

Speeding up the dynamics of a quantum system is of paramount importance for quantum technologies. However, in finite dimensions and without full knowledge of the details of the system, it is easily shown to be impossible. In contrast we show that continuous variable systems described by a certain class of quadratic Hamiltonians can be sped up without such detailed knowledge. We call the resultant procedure Hamiltonian amplification (HA). The HA method relies on the application of local squeezing operations allowing for amplifying even unknown or noisy couplings and frequencies by acting on individual modes. Furthermore, we show how to combine HA with dynamical decoupling to achieve amplified Hamiltonians that are free from environmental noise. Finally, we illustrate a significant reduction in gate times of cavity resonator qubits as one potential use of HA.

FuSENet: fused squeeze‐and‐excitation network for spectral‐spatial hyperspectral image classification

Deep learning-based approaches have become very prominent in recent years due to its outstanding performance as compared to the hand-extracted feature-based methods. Convolutional neural network (CNN) is a type of deep learning architecture to deal with the image/video data. Residual network and squeeze and excitation network (SENet) are among recent developments in CNN for image classification. However, the performance of SENet depends on the squeeze operation done by global pooling, which sometimes may lead to poor performance. In this study, the authors propose a bilinear fusion mechanism over different types of squeeze operation such as global pooling and max pooling. The excitation operation is performed using the fused output of squeeze operation. They used to model the proposed fused SENet with the residual unit and name it as FuSENet. Here the classification experiments are performed over benchmark hyperspectral image datasets. The experimental results confirm the superiority of the proposed FuSENet method with respect to the state-of-the-art methods. The source code of the complete system is made publicly available at https://github.com/swalpa/FuSENet.

Dynamics of Moments of Arbitrary Order for Stochastic Poisson Compressions

The explicit dynamics of the moments for the GKSL equation is obtained. In our case the GKSL equation corresponds to Poisson stochastic processes which lead to unitary jumps. We consider squeeze operators as the unitary jumps.

Improving brain tumor segmentation on MRI based on the deep U-net and residual units.

BACKGROUNDAccurate segmentation of brain tumor depicting on magnetic resonance imaging (MRI) is an important step for doctors to determine optimal treatment plan of Gliomas, which are the common malignant brain tumors that seriously damage patients' health and life.OBJECTThis study aims to improve accuracy and efficiency of brain tumor segmentation on MRI using the advanced deep learning model.METHODIn this study, an improved model based on the U-net for accurate segmentation of brain tumor MRI images, called Deeper ResU-net, is proposed. First, a deep Deeper U-net is built, which has deeper network depth compared with U-net, uses Squeeze Operator to control network parameters and attempts to enhance the feature extraction ability. Then, Deeper ResU-net is formed to eliminate degradation phenomenon of the deep network, in which residual unit is designed and integrated into the Deeper U-net to keep the number of parameters unchanged.RESULTDeeper ResU-net makes the deep network conduct stable training without degrading. Evaluation result shows that the Deeper ResU-net has achieved competitive result with average DSC metrics of 0.9, 0.82, 0.88 for Complete tumor region, Core tumor region and Enhanced tumor region, respectively.CONCLUSIONBy extending the U-net model to a deeper layer and adding the residual structure to ensure effective and stable training of the model, the experiment results demonstrate that applying the improved Deeper ResU-net can effectively eliminate the degradation phenomenon of deep network and improve segmentation performance.

RESEARCH ON SE-INCEPTION IN HIGH-RESOLUTION REMOTE SENSING IMAGE CLASSIFICATION

Abstract. With the deepening research and cross-fusion in the modern remote sensing image area, the classification of high spatial resolution remote sensing images has captured the attention of the researchers in the field of remote sensing. However, due to the serious phenomenon of “same object, different spectrum” and “same spectrum, different object” of high-resolution remote sensing image, the traditional classification strategy is hard to handle this challenge. In this paper, a remote sensing image scene classification model based on SENet and Inception-V3 is proposed by utilizing the deep learning method and transfer learning strategy. The model first adds a dropout layer before the full connection layer of the original Inception-V3 model to avoid over-fitting. Then we embed the SENet module into the Inception-V3 model for optimizing the network performance. In this paper, global average pooling is used as squeeze operation, and then two fully connected layers are used to construct a bottleneck structure. The model proposed in this paper is more non-linear, can better fit the complex correlation between channels, and greatly reduces the amount of parameters and computation. In the training process, this paper adopts the transfer learning strategy, makes full use of existing models and knowledge, improves training efficiency, and finally obtains scene classification results. The experimental results based on AID high-score remote sensing scene images show that SE-Inception has faster convergence speed and more stable training effect than the original Inception-V3 training. Compared with other traditional methods and deep learning networks, the improved model proposed in this paper has greater accuracy improvement.

Optical complex integration-transform for deriving complex fractional squeezing operator**Project supported by the National Natural Science Foundation of China (Grant No. 11775208) and Key Projects of Huainan Normal University, China (Grant No. 2019XJZD04).

We find a new complex integration-transform which can establish a new relationship between a two-mode operator’s matrix element in the entangled state representation and its Wigner function. This integration keeps modulus invariant and therefore invertible. Based on this and the Weyl–Wigner correspondence theory, we find a two-mode operator which is responsible for complex fractional squeezing transformation. The entangled state representation and the Weyl ordering form of the two-mode Wigner operator are fully used in our derivation which brings convenience.

Squeezing for Bloch four-hyperboloid via the non-compact Hopf map

We explore the hyperbolic geometry of squeezed states in the perspective of the non-compact Hopf map. Based on analogies between the squeeze operation and hyperbolic rotation, two types of the squeeze operators, the (usual) Dirac and the Schwinger types, are introduced. We clarify the underlying hyperbolic geometry and representations of the squeezed states along the line of the first non-compact Hopf map. Following the geometric hierarchy of the non-compact Hopf maps, we extend the analysis to —the isometry of a split-signature four-hyperboloid. We explicitly construct the squeeze operators in the Dirac and Schwinger types and investigate the physical meaning of the four-hyperboloid coordinates in the context of the Schwinger-type squeezed states. It is shown that the Schwinger-type squeezed one-photon state is equal to an entangled superposition state of two squeezed states and the corresponding concurrence has a clear geometric meaning. Taking advantage of the group theoretical formulation, basic properties of the squeezed coherent states are also investigated. In particular, we show that the squeezed vacuum naturally realizes a generalized squeezing in a 4D manner.

Anti-correlated phonons with two-mode Gaussian squeezed state

We study the cross-correlation between two bosonic modes of a two-mode displaced squeezed thermal state. By calculating the equal-time second-order cross-correlation function, we find that strong anticorrelation between the two bosonic modes can be observed. The mechanism of anticorrelation between the two bosonic modes is the interference between two coherent displacements and a squeeze operation. The optimal values of the two displacements and the squeezing parameter for achieving the minimum value of is derived. As an example, we explore the anticorrelation between phonons in a three-mode optomechanical system where two mechanical oscillators are coupled to a single cavity mode. The two-mode displaced squeezed thermal state of the two mechanical oscillators can be achieved if the squeezing amplitude and the mean phonon occupation number of the two mechanical environments are not very large. Furthermore, we find that the two-time second-order correlation function has multiple minima if the frequency difference of the two mechanical oscillators is large. Our results provide us with a tool to generate anticorrelated photons and phonons which may have potential applications in quantum information networks.

Feature Recalibration in Deep Learning via Depthwise Squeeze and Refinement Operations

Feature recalibration is a very effective strategy of further improving performance in deep networks. The commonly used global pooling operation will lose the information of distinguishing features, which requires additional fully connected layers to adjust the relationship between feature maps. In this paper, we propose a novel architectural unit that aims to recalibrate feature maps based on the discriminative feature information contained in each feature map. To achieve this, we use two-layer depthwise convolution instead of global pooling to extract the distinguishing feature information of each feature map. Since convolution can discriminately learn the global information of each feature map, we discard the fully connected layer to ensure independence when adjusting the feature map. After getting the global information of each feature map, the nonlinear function is used directly to implement the refinement of the feature map to enhance the distinguishing feature map and suppress useless ones. Based on the design characteristics of the new unit, we codename it as the “Depthwise Squeeze and Refinement” (DSR) block. And it can be easily embedded into existing state-of-the-art deep structures to significantly improve the performance at a slight computational cost.

Squeezed state, characteristic frequency and quantum noise of a mesoscopic two-loop [formula omitted]–[formula omitted] circuit with capacity coupling

For the first time we employ the method of integration within ordered product of operators to search for quantum squeezing operator and squeezed state for daigonalizing the mesoscopic two-loop L–C circuit with capacity C3 coupling. We also deduce the energy level (characteristic frequecncy) ω±2=C2L2C1+C3+C1L1C3+C22C1C2C3L1L2±12C1+C3C1C3L1−C2+C3C2C3L22+4C32L1L2 and derive the exact quantum noise expression. The way we adopt here is benificial to mesoscopic circuit design for quantum computer.

Fault Diagnosis of High-Speed Train Bogie by Residual-Squeeze Net

Fault diagnosis of high-speed train (HST) bogie is essential in guaranteeing the normal daily operation of an HST. In prior works, feature extraction from multisensor vibration signals mainly relies on signal processing methods, which is independent of the classification process. Based on convolutional neural networks (CNNs), this paper presents a novel fault diagnosis system using the residual-squeeze net (RSNet), which is directly applicable to raw data (time sequences) and does not require any signal transformation or postprocessing. In this network, information fusion is achieved by using the convolutional layer. More specifically, via the squeeze operation, an optimal combination of channels is learnt by training the network. Experimental results obtained by using SIMPACK simulation data demonstrate the effectiveness of the proposed approach in both complete failure case and single failure case, with diagnosis accuracy near 100%. The proposed approach also shows good performance in identifying the locations of faulty components. Comparisons between RSNet and competitive methods shows the advantages of RSNet for fault classification.

Time-evolution of squeezed coherent states of a generalized quantum parametric oscillator

Time evolution of squeezed coherent states for a quantum parametric oscillator with the most general self-adjoint quadratic Hamiltonian is found explicitly. For this, we use the unitary displacement and squeeze operators in coordinate representation and the evolution operator obtained by the Wei-Norman Lie algebraic approach. Then, we analyze squeezing properties of the wave packets according to the complex parameter of the squeeze operator and the time-variable parameters of the Hamiltonian. As an application, we construct all exactly solvable generalized quantum oscillator models classically corresponding to a driven simple harmonic oscillator. For each model, defined according to the frequency modification in position space, we describe explicitly the squeezing and displacement properties of the wave packets. This allows us to see the exact influence of all parameters and make a basic comparison between the different models.

Dynamics of squeezed states of a generalized quantum parametric oscillator

Time-evolution of squeezed coherent states of a generalized Caldirola-Kanai type quantum parametric oscillator is found explicitly using the exact evolution operator obtained by the Wei-Norman algebraic approach. Properties of these states are investigated according to the parameters of the unitary squeeze operator and the time-variable parameters of the generalized quadratic Hamiltonian. As an application, we consider exactly solvable quantum models with specific frequency modification for which the corresponding classical oscillator is in underdamping case and driving forces are of sinusoidal type. For each model we explicitly provide the evolution of the squeezed coherent states and discuss their behavior.

Ground state and thermal entanglement between two two-level atoms interacting with a nondegenerate parametric amplifier: Different sub-spaces

In this paper, a Hamiltonian model that includes interaction of two coupled two-level atoms with a nondegenerate parametric amplifier in a cavity is introduced. By using the two-mode squeezing operator and under a certain condition, the introduced Hamiltonian is reduced to a generalized Jaynes–Cummings Hamiltonian. The constants of motion of system imply the existence of a decomposition of the system’s Hilbert space [Formula: see text] into a direct sum of three infinite dimensional sub-spaces, as [Formula: see text]. This decomposition enables us to study ground and thermally induced entanglement between the atoms in each of the sub-spaces as well as whole Hilbert space. The effect of atom–atom and atom–photon couplings on the degree of ground state and thermal entanglement are also investigated using the concurrence measure. It is found that in the subspaces [Formula: see text] and [Formula: see text] for all experimental values of parameters of the system, the atoms are disentangled. It is also observed that in the total space [Formula: see text] the ground state entanglement is always zero, while in the subspace [Formula: see text] it is at its maximum value. Moreover, it is found that in the subspace [Formula: see text] thermal entanglement between the atoms is robust against temperature.

Squeeze Operators in Classical Scenarios

We analyse the paraxial field propagation in the realm of classical optics, showing that it can be written as the action of the fractional Fourier transform, followed by the squeeze operator applied to the initial field. Secondly, we show that a wavelet transform may be viewed as the application of a displacement and squeeze operator onto the mother wavelet function.

Means and covariances of photon numbers in multimode Gaussian states

In the field of continuous variables and particularly of Gaussian states an important role is played by the statistics of photon numbers. This issue has been considered in pioneering works for the one- and two-mode cases, but a systematic approach seems not to be available. In this paper, the most general multimode mixed Gaussian state, which is generated starting from a multimode thermal state and processed by the most general Gaussian unitary, is considered. In the $N$-mode the photon numbers are represented by $N$ random variables, one for each mode, and the target is the evaluation of the means and of the covariances. The means describe statistically the amount of photon numbers in each mode, while the covariances give the correlations between the photon numbers in the different modes. For both means and covariances a closed-form result is obtained, expressed in simple and compact formulas. The main tools are provided by the representation of Gaussian unitaries (given by a cascade of an $N$-mode squeeze operator, an $N$-mode rotation operator, and a parallel set of $N$ single-mode displacement operators) and by the corresponding Bogoliubov transformations.

Structure invariant wave packets

We show that by adding a quadratic phase to an initial arbitrary wave function, its free evolution maintains an invariant structure which it spreads by the action of a squeeze operator. Although such invariance is an approximation, we show that it perfectly matches the exact evolution.