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Xiaomin Liu

Publications and source records attributed to Xiaomin Liu.

At least 19 recordsLinked to original sources
arXiv2026

Relaxing Coherence Requirements on Laser Sources for Nanoscopy through Optical Fiber Technique

High numerical-aperture (NA) focusing of cylindrical vector beams (CVBs) typically requires costly, high-quality lasers to supply a stable vector pupil field. Here, we introduce fiber-conditioned vectorial nanofocusing, in which an optical-fiber-based mode-selective coupler projects a strongly distorted beam of a diode that costs two orders of magnitude less than the reference laser into radially or azimuthally polarized CVBs. A three-tolerance analysis clarifies its operating principle by establishing separate requirements for spatial state, temporal coherence and residual wavefront error. The resulting fields reproduce expected high-NA focal signatures and generate orientation-sensitive single-molecule excitation patterns consistent with reference-laser measurements, lowering the barrier to structured-light experiments.

physics.optics↗
arXiv2026

Manipulation of diverse quantum correlations based on a hybrid optomagnomechanical system

Flexible manipulation of quantum correlation resources enables the implementation of diverse quantum tasks based on hybrid quantum networks, where atom-magnon and optomagnonic entanglements and steerings play important roles. In this work, we propose an effective scheme to generate and manipulate quantum entanglements and steerings based on a hybrid optomagnomechanical system, which is composed of a polarizer, an optical cavity with YIG bridge as one end, and an atomic ensemble in it. According to the results of the parameter dependence of various quantum correlations, we can selectively generate bipartite and genuine tripartite entanglements and deterministically manipulate the concrete situation of bipartite, multipartite steerings, and collective pentapartite steering, by adjusting the polarization direction of the driving laser and the Tavis-Cummings coupling strength. Our all-optical controlled scheme is flexible, convenient, compact, and experimentally feasible, because multiple coupling channels can be tuned simultaneously. This work provides a new perspective for implementing specialized quantum tasks, such as hierarchical ultra-secure multi-user quantum communications.

quant-ph↗
arXiv2025

Complete characterization of beam deflection based on double weak value amplification system

The precise measurement of spatial attitude parameters is critical for applications in inertial navigation, industrial monitoring, instrument calibration, quantum metrology, etc. In this work, we theoretically investigate and experimentally realize the simultaneous measurement of the yaw and pitch angles using a Hermite-Gaussian-postselected double weak value system integrated with two sets of high-order-mode balanced homodyne detections, thereby achieving a complete characterization of the beam deflection. Signals of the yaw and pitch angles that are involved in TEM$_{10}$ and TEM$_{01}$ modes output from two dark ports of the system can be measured independently. As a result, the obtained minimum measurable yaw and pitch angles of beam deflection are 83 prad and 89 prad, respectively. Meanwhile, the corresponding displacements are 0.79 pm and 0.85 pm, respectively. This work expands the beam deflection measurement to two dimensions, which provides a new insight for future high-precision multi-parameter spatial precise detection.

quant-ph↗
arXiv2025

Three-dimensional optical characterization of magnetostrictive deformation in magnomechanical systems

Magnomechanical systems with YIG spheres have been proven to be an ideal system for studying magnomechanically induced transparency, dynamical backaction, and rich nonlinear effects, such as the magnon-phonon cross-Kerr effect. Accurate characterization of the magnetostriction induced deformation displacement is important as it can be used for, e.g., estimating the magnon excitation number and the strength of the dynamical backaction. Here we propose an optical approach for detecting the magnetostrictive deformation of a YIG sphere in three dimensions (3Ds) with high precision. It is based on the deformation induced spatial high-order modes of the scattered field, postselection, and balanced homodyne detection. With feasible parameters, we show that the measurement precision of the deformation in $x$, $y$, and $z$ directions can reach the picometer level. We further reveal the advantages of our scheme using a higher-order probe beam and balanced homodyne detection by means of quantum and classical Fisher information. The real-time and high-precision measurement of the YIG sphere's deformation in 3Ds can be used to determinate specific mechanical modes, characterize the magnomechanical dynamical backaction and the 3D cooling of the mechanical vibration, and thus finds a wide range of applications in magnomechanics.

quant-ph↗
arXiv2025

Flexible generation of optomagnonic quantum entanglement and quantum coherence difference in double-cavity-optomagnomechanical system

Quantum entanglement and quantum coherence generated from the optomagnomechanical system are important resources in quantum information and quantum computation. In this paper, a scheme for flexibly generating optomagnonic quantum entanglement and quantum coherence difference is proposed, based on a double-cavity-optomagnomechanical system. The parameter dependencies of the bipartite optomagnonic entanglement, the genuine tripartite optomagnonic entanglement, the quantum coherence difference, and the stability of the system, are investigated intensively. The results show that this scheme endows the magnon more flexibility to choose different mechanisms, under the condition of maintaining the system stable. This work is valuable for connecting different nodes in quantum networks and manipulating the magnon states with light in the future.

quant-ph↗
arXiv2025

Generation of optomicrowave and optomagnonic entanglements in cascaded optomagnomechanical systems

The optomagnomechanical system, which involves flexible nonlinearities, is one of the promising physical platforms for studying the preparation and manipulation of quantum entanglements, as well as the construction of hybrid quantum networks. A scheme for entanglement enhancement and quadripartite entanglement generation is proposed, based on a cascaded optomagnomechanical system. On the one hand, optomicrowave and optomagnonic entanglements within the two subsystems are investigated, and their parameter dependence, such as detuning, decay, coupling strength, and transmission efficiency, is discussed. On the other hand, the parameter conditions for achieving optimal optomicrowave and optomagnonic quadripartite entanglements are also obtained. The results show that significant enhancement of optomicrowave and optomagnonic entanglements in the second cavity can be obtained in a certain range of parameters. Under optimized parameter conditions, optomicrowave and optomagnonic quadripartite entanglements can be generated throughout the entire cascaded system. This research provides a theoretical basis for the manipulation of quantum entanglement, the transmission of the magnon's state, and the construction of hybrid quantum networks involving different physical systems.

quant-ph↗
arXiv2023

Building a digital twin of EDFA: a grey-box modeling approach

To enable intelligent and self-driving optical networks, high-accuracy physical layer models are required. The dynamic wavelength-dependent gain effects of non-constant-pump erbium-doped fiber amplifiers (EDFAs) remain a crucial problem in terms of modeling, as it determines optical-to-signal noise ratio as well as the magnitude of fiber nonlinearities. Black-box data-driven models have been widely studied, but it requires a large size of data for training and suffers from poor generalizability. In this paper, we derive the gain spectra of EDFAs as a simple univariable linear function, and then based on it we propose a grey-box EDFA gain modeling scheme. Experimental results show that for both automatic gain control (AGC) and automatic power control (APC) EDFAs, our model built with 8 data samples can achieve better performance than the neural network (NN) based model built with 900 data samples, which means the required data size for modeling can be reduced by at least two orders of magnitude. Moreover, in the experiment the proposed model demonstrates superior generalizability to unseen scenarios since it is based on the underlying physics of EDFAs. The results indicate that building a customized digital twin of each EDFA in optical networks become feasible, which is essential especially for next generation multi-band network operations.

eess.SP↗
arXiv2023

Generation of multipartite entangled states based on double-longitudinal-mode cavity optomechanial system

Optomechanical system is a promising platform to connect different notes of quantum networks, therefore, entanglement generated from it is also of great importance. In this paper, the parameter dependence of optomechanical and optical-optical entanglements generated from the double-longitudinal-mode cavity optomechanical system are discussed and two quadrapartite entanglement generation schemes based on such a system are proposed. Furthermore, 2N or 4N-partite entangled states can be obtained by coupling N cavities with N-1 beamsplitter(BS)s, and these schemes are scalable in increasing the partite number of entanglement. Certain ladder or linear structures are contained in the finally obtained entanglement structure, which can be applied in quantum computing or quantum networks in the future.

quant-ph↗
arXiv2022

A Grey-box Launch-profile Aware Model for C+L Band Raman Amplification

Based on the physical features of Raman amplification, we propose a three-step modelling scheme based on neural networks (NN) and linear regression. Higher accuracy, less data requirements and lower computational complexity are demonstrated through simulations compared with the pure NN-based method.

cs.LG↗
arXiv2022

Physics-informed EDFA Gain Model Based on Active Learning

We propose a physics-informed EDFA gain model based on the active learning method. Experimental results show that the proposed modelling method can reach a higher optimal accuracy and reduce ~90% training data to achieve the same performance compared with the conventional method.

eess.SP↗
arXiv2020

A Data-Fusion-Assisted Telemetry Layer for Autonomous Optical Networks

For further improving the capacity and reliability of optical networks, a closed-loop autonomous architecture is preferred. Considering a large number of optical components in an optical network and many digital signal processing modules in each optical transceiver, massive real-time data can be collected. However, for a traditional monitoring structure, collecting, storing and processing a large size of data are challenging tasks. Moreover, strong correlations and similarities between data from different sources and regions are not properly considered, which may limit function extension and accuracy improvement. To address abovementioned issues, a data-fusion-assisted telemetry layer between the physical layer and control layer is proposed in this paper. The data fusion methodologies are elaborated on three different levels: Source Level, Space Level and Model Level. For each level, various data fusion algorithms are introduced and relevant works are reviewed. In addition, proof-of-concept use cases for each level are provided through simulations, where the benefits of the data-fusion-assisted telemetry layer are shown.

eess.SP↗
arXiv2019

Application of Machine Learning in Fiber Nonlinearity Modeling and Monitoring for Elastic Optical Networks

Fiber nonlinear interference (NLI) modeling and monitoring are the key building blocks to support elastic optical networks (EONs). In the past, they were normally developed and investigated separately. Moreover, the accuracy of the previously proposed methods still needs to be improved for heterogenous dynamic optical networks. In this paper, we present the application of machine learning (ML) in NLI modeling and monitoring. In particular, we first propose to use ML approaches to calibrate the errors of current fiber nonlinearity models. The Gaussian-noise (GN) model is used as an illustrative example, and significant improvement is demonstrated with the aid of an artificial neural network (ANN). Further, we propose to use ML to combine the modeling and monitoring schemes for a better estimation of NLI variance. The following contents are the listed errors as mentioned in the comments for reasons of withdrawal. (1) The works, as mentioned as the title, should be addressed is about the elastic optical networks(EON), however, the simulation setup and the results section are focused on the conventional wavelength division multiplexing(WDM) networks. This error may confuse some researcher, getting the misleading decision for the researches about the elastic optical networks. (2) There exists some errors in the results rection, such as, Fig.9(b) and (c) with the wrong captions may result in misleading decision. (3) The split-step-Fourier-method(SSFM) presents good accuracy if the sufficiently small steps are adopted in the calculation, however this paper has not necessary contents and efforts to optimise the step-length of SSFM. This error may confuse the accuracy of simulation results. Therefore, we decide to withdraw this paper from arXiv. The correct and complete paper with the same title was published in journal of lightwave technology with doi: 10.1109/JLT.2019.2910143.

eess.SP↗