Showing 1–20 of 20 results for author: Jin, H

Extracting Universal Entanglement Scaling from Mixed Fermionic Gaussian States via Entanglement Projected Entropy

Authors: Jia-Wen Tao, Hui-Ke Jin

Abstract: Identifying spatial quantum correlations in mixed states is challenging because thermal mixed-state contributions obscure the entanglement encoded in subsystem entropy. Here, we introduce the entanglement projected entropy (EPE), a purification-independent Gaussian spatial filter for mixed fermionic states. By resolving subsystem entropy into Gaussian entropy channels and projecting their purifica… ▽ More Identifying spatial quantum correlations in mixed states is challenging because thermal mixed-state contributions obscure the entanglement encoded in subsystem entropy. Here, we introduce the entanglement projected entropy (EPE), a purification-independent Gaussian spatial filter for mixed fermionic states. By resolving subsystem entropy into Gaussian entropy channels and projecting their purification partners onto the physical complement, we obtain a closed-form expression in terms of the physical covariance matrix. In a one-dimensional free-fermion chain, it removes the volume-law mixed-state background and recovers the zero-temperature conformal scaling with the $c/3$ coefficient. In a two-dimensional half-filled $π$-flux model, it reveals a universal finite-temperature scaling collapse governed by a Dirac infrared length fixed by the low-energy velocity. These results establish EPE as an entropy-channel filter that exposes boundary-sensitive universal scaling hidden beneath mixed-state entropy. △ Less

Submitted 2 June, 2026; v1 submitted 24 May, 2026; originally announced May 2026.

Comments: 4 pages with 3 figures + SM

A Survey of OAM-Encoded High-Dimensional Quantum Key Distribution: Foundations, Experiments, and Recent Trends

Authors: Huan Zhang, Zhenyu Cao, Yu Sun, Hu Jin

Abstract: High-dimensional quantum key distribution (HD-QKD) enhances information efficiency and noise tolerance by encoding data in large Hilbert spaces. The orbital angular momentum (OAM) of light provides a scalable basis for such encoding and supports high-dimensional photonic communication. Practical OAM-based implementations remain constrained by challenges in state generation, transmission, and detec… ▽ More High-dimensional quantum key distribution (HD-QKD) enhances information efficiency and noise tolerance by encoding data in large Hilbert spaces. The orbital angular momentum (OAM) of light provides a scalable basis for such encoding and supports high-dimensional photonic communication. Practical OAM-based implementations remain constrained by challenges in state generation, transmission, and detection. This survey offers a consolidated overview of OAM-encoded HD-QKD, outlining fundamental principles, representative experiments, and system-level limitations. Recent progress in hybrid encodings, mode sorting, adaptive optics, and TF, CV, MDI, and DI frameworks is summarized with emphasis on practical feasibility. △ Less

Submitted 28 May, 2026; v1 submitted 12 December, 2025; originally announced December 2025.

Comments: 24 pages, 6 figures. In Press, ICT Express (2026)

MSC Class: 81P94

Efficient simulation of low-entanglement bosonic Gaussian states in polynomial time

Authors: Tong Liu, Hui-Ke Jin, Tao Xiang, Hong-Hao Tu

Abstract: Bosonic Gaussian states are ubiquitous in quantum optics and condensed matter physics. While they are efficiently handled within the Gaussian formalism, sampling requires calculating amplitudes in the boson occupation basis. This step, however, is hindered by a significant bottleneck due to the hafnian. We present an efficient algorithm that converts pure bosonic Gaussian states into matrix produc… ▽ More Bosonic Gaussian states are ubiquitous in quantum optics and condensed matter physics. While they are efficiently handled within the Gaussian formalism, sampling requires calculating amplitudes in the boson occupation basis. This step, however, is hindered by a significant bottleneck due to the hafnian. We present an efficient algorithm that converts pure bosonic Gaussian states into matrix product states (MPSs), thereby establishing a versatile tool for probing bosonic Gaussian systems in settings where direct Gaussian-formalism-based calculations become inefficient. Our method combines a Gaussian singular value decomposition with a projected-creation-operator mapping that constructs local MPS tensors without computing hafnians. Benchmarking on covariance matrices from the Jiuzhang 2.0 and Jiuzhang 4.0 Gaussian boson sampling experiments demonstrates substantial speedups over previous tensor-network approaches in the low-entanglement regime relevant to lossy devices. The method provides a scalable classical simulation framework for bosonic Gaussian states with limited entanglement. In this regime, a target accuracy can be achieved with a bond dimension that remains computationally tractable, thereby extending the applicability of MPS-based methods to a broad range of bosonic systems. △ Less

Submitted 11 May, 2026; v1 submitted 11 December, 2025; originally announced December 2025.

Comments: 17 pages, 5 figures

Journal ref: npj Quantum Inf. 12, 110 (2026)

Floquet Superheating

Authors: Yang Hou, Andrea Pizzi, Huike Jin, Johannes Knolle, Roderich Moessner, Hongzheng Zhao

Abstract: Periodically driven many-body systems generally heat towards a featureless 'infinite-temperature' state. As an alternative to uniform heating in a clean system, here we establish a Floquet superheating regime, where fast heating nucleates at ''hot spots" generated by rare fluctuations in the local energy with respect to an appropriate effective Hamiltonian. Striking macroscopic consequences includ… ▽ More Periodically driven many-body systems generally heat towards a featureless 'infinite-temperature' state. As an alternative to uniform heating in a clean system, here we establish a Floquet superheating regime, where fast heating nucleates at ''hot spots" generated by rare fluctuations in the local energy with respect to an appropriate effective Hamiltonian. Striking macroscopic consequences include exceptionally long-lived prethermalization and non-ergodic bimodal distributions of macroscopic observables. Superheating is predicated on a heating rate depending strongly on the local fluctuation; in our example, this is supplied by a sharp state-selective spin-echo, where the energy absorption is strongly suppressed for low-energy states, while thermal fluctuations open up excessive heating channels. A simple phenomenological theory is developed to show the existence of a critical droplet size, which incorporates heating by the driving field as well as the heat current out of the droplet. Our results shine light on a new heating mechanism and suggest new routes towards stabilizing non-equilibrium phases of matter in driven systems. △ Less

Submitted 16 November, 2025; originally announced November 2025.

Coherence Fraction in Grover Search Algorithm

Authors: Si-Qi Zhou, Hai Jin, Jin-Min Liang, Shao-Ming Fei, Yunlong Xiao, Zhihao Ma

Abstract: The question of which resources drive the advantages in quantum algorithms has long been a fundamental challenge. While entanglement and coherence are critical to many quantum algorithms, our results indicate that they do not fully explain the quantum advantage achieved by the Grover search algorithm. By introducing a generalized Grover search algorithm, we demonstrate that the success probability… ▽ More The question of which resources drive the advantages in quantum algorithms has long been a fundamental challenge. While entanglement and coherence are critical to many quantum algorithms, our results indicate that they do not fully explain the quantum advantage achieved by the Grover search algorithm. By introducing a generalized Grover search algorithm, we demonstrate that the success probability depends not only on the querying number of oracles but also on the coherence fraction, which quantifies the fidelity between an arbitrary initial quantum state and the equal superposition state. Additionally, we explore the role of the coherence fraction in the quantum minimization algorithm, which offers a framework for solving complex problems in quantum machine learning. These findings offer insights into the origins of quantum advantage and open pathways for the development of new quantum algorithms. △ Less

Submitted 10 November, 2025; originally announced November 2025.

Comments: 9 pages, 6 figures. Published in Physical Review A 110, 062429 (2024)

Improving GANs by leveraging the quantum noise from real hardware

Authors: Hongni Jin, Kenneth M. Merz Jr

Abstract: We propose a novel approach to generative adversarial networks (GANs) in which the standard i.i.d. Gaussian latent prior is replaced or hybridized with a quantum-correlated prior derived from measurements of a 16-qubit entangling circuit. Each latent sample is generated by grouping repeated shots per qubit into a binary fraction, applying the inverse Gaussian CDF to obtain a 16-dimensional Gaussia… ▽ More We propose a novel approach to generative adversarial networks (GANs) in which the standard i.i.d. Gaussian latent prior is replaced or hybridized with a quantum-correlated prior derived from measurements of a 16-qubit entangling circuit. Each latent sample is generated by grouping repeated shots per qubit into a binary fraction, applying the inverse Gaussian CDF to obtain a 16-dimensional Gaussian vector whose joint copula reflects genuine quantum entanglement, and then projecting into the high-dimensional space via a fixed random matrix. By pre-sampling tens of millions of bitstrings, either from a noiseless simulator or from IBM hardware, we build large pools of independent but internally quantum-correlated latents. We integrate this prior into three representative architectures (WGAN, SNGAN, BigGAN) on CIFAR-10, making no changes to the neural network structure or training hyperparameters. The hybrid latent representations incorporating hardware-derived noise consistently lower the FID relative to both the classical baseline and the simulator variant, especially when the quantum component constitutes a substantial fraction of the prior. In addition, we execute on the QPU in parallel to not only save computing time but also further decrease the FID up to 17% in BigGAN. These results indicate that intrinsic quantum randomness and device-specific imperfections can provide a structured inductive bias that enhances GAN performance. Our work demonstrates a practical pipeline for leveraging noisy quantum hardware to enrich deep-generative modeling, opening a new interface between quantum information and machine learning. All code and data are available at https://github.com/Neon8988/GAN_QN.git. △ Less

Submitted 2 July, 2025; originally announced July 2025.

Generation of 95-qubit genuine entanglement and verification of symmetry-protected topological phases

Authors: Tao Jiang, Jianbin Cai, Junxiang Huang, Naibin Zhou, Yukun Zhang, Jiahao Bei, Guoqing Cai, Sirui Cao, Fusheng Chen, Jiang Chen, Kefu Chen, Xiawei Chen, Xiqing Chen, Zhe Chen, Zhiyuan Chen, Zihua Chen, Wenhao Chu, Hui Deng, Zhibin Deng, Pei Ding, Xun Ding, Zhuzhengqi Ding, Shuai Dong, Bo Fan, Daojin Fan , et al. (130 additional authors not shown)

Abstract: Symmetry-protected topological (SPT) phases are fundamental features of cluster states, serving as key resources for measurement-based quantum computation (MBQC). Generating large-scale cluster states and verifying their SPT phases are essential steps toward practical MBQC, which however still presents significant experimental challenges. In this work, we address these challenges by utilizing adva… ▽ More Symmetry-protected topological (SPT) phases are fundamental features of cluster states, serving as key resources for measurement-based quantum computation (MBQC). Generating large-scale cluster states and verifying their SPT phases are essential steps toward practical MBQC, which however still presents significant experimental challenges. In this work, we address these challenges by utilizing advanced superconducting hardware with optimized gate operations, enhanced readout fidelity, and error mitigation techniques. We successfully generate and verify 95-qubit one-dimensional and 72-qubit two-dimensional genuine entangled cluster states, achieving fidelities of $0.5603 \pm 0.0084$ and $0.5519 \pm 0.0054$, respectively. Leveraging these high-fidelity cluster states, we investigate SPT phases through quantum teleportation across all 95 qubits and demonstrate input-state-dependent robustness against symmetry-breaking perturbations, highlighting the practicality and intrinsic robustness of MBQC enabled by the SPT order. Our results represent a significant advancement in large-scale entanglement generation and topological phase simulation, laying the foundation for scalable and practical MBQC using superconducting quantum systems. △ Less

Submitted 3 May, 2025; originally announced May 2025.

Comments: Main text: 15 pages, 4 figures; supplementary materials: 42 pages, 19 figures. Total: 57 pages, 23 figures

Journal ref: Nat. Phys. 22 (2026) 430-438

QFGN: A Quantum Approach to High-Fidelity Implicit Neural Representations

Authors: Hongni Jin, Gurinder Singh, Kenneth M. Merz Jr

Abstract: Implicit neural representations have shown potential in various applications. However, accurately reconstructing the image or providing clear details via image super-resolution remains challenging. This paper introduces Quantum Fourier Gaussian Network (QFGN), a quantum-based machine learning model for better signal representations. The frequency spectrum is well balanced by penalizing the low-fre… ▽ More Implicit neural representations have shown potential in various applications. However, accurately reconstructing the image or providing clear details via image super-resolution remains challenging. This paper introduces Quantum Fourier Gaussian Network (QFGN), a quantum-based machine learning model for better signal representations. The frequency spectrum is well balanced by penalizing the low-frequency components, leading to the improved expressivity of quantum circuits. The results demonstrate that with minimal parameters, QFGN outperforms the current state-of-the-art (SOTA) models. Despite noise on hardware, the model achieves accuracy comparable to that of SIREN, highlighting the potential applications of quantum machine learning in this field. △ Less

Submitted 26 April, 2025; originally announced April 2025.

Benchmarking MedMNIST dataset on real quantum hardware

Authors: Gurinder Singh, Hongni Jin, Kenneth M. Merz Jr

Abstract: Quantum machine learning (QML) has emerged as a promising domain to leverage the computational capabilities of quantum systems to solve complex classification tasks. In this work, we present the first comprehensive QML study by benchmarking the MedMNIST-a diverse collection of medical imaging datasets on a 127-qubit real IBM quantum hardware, to evaluate the feasibility and performance of quantum… ▽ More Quantum machine learning (QML) has emerged as a promising domain to leverage the computational capabilities of quantum systems to solve complex classification tasks. In this work, we present the first comprehensive QML study by benchmarking the MedMNIST-a diverse collection of medical imaging datasets on a 127-qubit real IBM quantum hardware, to evaluate the feasibility and performance of quantum models (without any classical neural networks) in practical applications. This study explores recent advancements in quantum computing such as device-aware quantum circuits, error suppression, and mitigation for medical image classification. Our methodology is comprised of three stages: preprocessing, generation of noise-resilient and hardware-efficient quantum circuits, optimizing/training of quantum circuits on classical hardware, and inference on real IBM quantum hardware. Firstly, we process all input images in the preprocessing stage to reduce the spatial dimension due to quantum hardware limitations. We generate hardware-efficient quantum circuits using backend properties expressible to learn complex patterns for medical image classification. After classical optimization of QML models, we perform inference on real quantum hardware. We also incorporate advanced error suppression and mitigation techniques in our QML workflow, including dynamical decoupling (DD), gate twirling, and matrix-free measurement mitigation (M3) to mitigate the effects of noise and improve classification performance. The experimental results showcase the potential of quantum computing for medical imaging and establish a benchmark for future advancements in QML applied to healthcare. △ Less

Submitted 19 March, 2025; v1 submitted 18 February, 2025; originally announced February 2025.

Establishing a New Benchmark in Quantum Computational Advantage with 105-qubit Zuchongzhi 3.0 Processor

Authors: Dongxin Gao, Daojin Fan, Chen Zha, Jiahao Bei, Guoqing Cai, Jianbin Cai, Sirui Cao, Xiangdong Zeng, Fusheng Chen, Jiang Chen, Kefu Chen, Xiawei Chen, Xiqing Chen, Zhe Chen, Zhiyuan Chen, Zihua Chen, Wenhao Chu, Hui Deng, Zhibin Deng, Pei Ding, Xun Ding, Zhuzhengqi Ding, Shuai Dong, Yupeng Dong, Bo Fan , et al. (129 additional authors not shown)

Abstract: In the relentless pursuit of quantum computational advantage, we present a significant advancement with the development of Zuchongzhi 3.0. This superconducting quantum computer prototype, comprising 105 qubits, achieves high operational fidelities, with single-qubit gates, two-qubit gates, and readout fidelity at 99.90%, 99.62% and 99.18%, respectively. Our experiments with an 83-qubit, 32-cycle r… ▽ More In the relentless pursuit of quantum computational advantage, we present a significant advancement with the development of Zuchongzhi 3.0. This superconducting quantum computer prototype, comprising 105 qubits, achieves high operational fidelities, with single-qubit gates, two-qubit gates, and readout fidelity at 99.90%, 99.62% and 99.18%, respectively. Our experiments with an 83-qubit, 32-cycle random circuit sampling on Zuchongzhi 3.0 highlight its superior performance, achieving one million samples in just a few hundred seconds. This task is estimated to be infeasible on the most powerful classical supercomputers, Frontier, which would require approximately $6.4\times 10^9$ years to replicate the task. This leap in processing power places the classical simulation cost six orders of magnitude beyond Google's SYC-67 and SYC-70 experiments [Nature 634, 328(2024)], firmly establishing a new benchmark in quantum computational advantage. Our work not only advances the frontiers of quantum computing but also lays the groundwork for a new era where quantum processors play an essential role in tackling sophisticated real-world challenges. △ Less

Submitted 16 December, 2024; originally announced December 2024.

Integrating Machine Learning and Quantum Circuits for Proton Affinity Predictions

Authors: Hongni Jin, Kenneth M. Merz Jr

Abstract: A key step in interpreting gas-phase ion mobility coupled with mass spectrometry (IM-MS) data for unknown structure prediction involves identifying the most favorable protonated structure. In the gas phase, the site of protonation is determined using proton affinity (PA) measurements. Currently, mass spectrometry and ab initio computation methods are widely used to evaluate PA; however, both metho… ▽ More A key step in interpreting gas-phase ion mobility coupled with mass spectrometry (IM-MS) data for unknown structure prediction involves identifying the most favorable protonated structure. In the gas phase, the site of protonation is determined using proton affinity (PA) measurements. Currently, mass spectrometry and ab initio computation methods are widely used to evaluate PA; however, both methods are resource-intensive and time-consuming. Therefore, there is a critical need for efficient methods to estimate PA, enabling the rapid identification of the most favorable protonation site in complex organic molecules with multiple proton binding sites. In this work, we developed a fast and accurate method for PA prediction by using multiple descriptors in combination with machine learning (ML) models. Using a comprehensive set of 186 descriptors, our model demonstrated strong predictive performance, with an R2 of 0.96 and a MAE of 2.47kcal/mol, comparable to experimental uncertainty. Furthermore, we designed quantum circuits as feature encoders for a classical neural network. To evaluate the effectiveness of this hybrid quantum-classical model, we compared its performance with traditional ML models using a reduced feature set derived from the full set. The result showed that this hybrid model achieved consistent performance comparable to traditional ML models with the same reduced feature set on both a noiseless simulator and real quantum hardware, highlighting the potential of quantum machine learning for accurate and efficient PA predictions. △ Less

Submitted 26 November, 2024; originally announced November 2024.

Exploring van der Waals cuprate superconductors using a hybrid microwave circuit

Authors: Haolin Jin, Giuseppe Serpico, Yejin Lee, Tommaso Confalone, Christian N. Saggau, Flavia Lo Sardo, Genda Gu, Berit H. Goodge, Edouard Lesne, Domenico Montemurro, Kornelius Nielsch, Nicola Poccia, Uri Vool

Abstract: The advent of two-dimensional van der Waals materials is a frontier of condensed matter physics and quantum devices. However, characterizing such materials remains challenging due to the limitations of bulk material techniques, necessitating the development of specialized methods. In this study, we investigate the superconducting properties of Bi2Sr2CaCu2O8+x flakes by integrating them with a hybr… ▽ More The advent of two-dimensional van der Waals materials is a frontier of condensed matter physics and quantum devices. However, characterizing such materials remains challenging due to the limitations of bulk material techniques, necessitating the development of specialized methods. In this study, we investigate the superconducting properties of Bi2Sr2CaCu2O8+x flakes by integrating them with a hybrid superconducting microwave resonator. The hybrid resonator is significantly modified by the interaction with the flake while maintaining a high quality factor. We also observe a significant upshift of the resonator frequency with increasing temperature, as well as a positive nonlinearity. These effects originate from a presently unknown microscopic mechanism within the flake, and can be modeled as a two-level system bath interacting with the resonant mode. Our findings open a path for high quality hybrid circuits with van der Waals flakes for exploring novel materials and developing new devices for quantum technology. △ Less

Submitted 29 January, 2025; v1 submitted 22 August, 2024; originally announced August 2024.

Comments: 5 pages, 4 figures with a supplementary material of 10 pages and 9 figures

Twisting the Dirac cones of the SU(4) spin-orbital liquid on the honeycomb lattice

Authors: Hui-Ke Jin, W. M. H. Natori, Johannes Knolle

Abstract: By combining the density matrix renormalization group (DMRG) method with Gutzwiller projected wave functions, we study the SU(4) symmetric spin-orbital model on the honeycomb lattice. We find that the ground states can be well described by a Gutzwiller projected $π$-flux state with Dirac-type gapless excitations at one quarter filling. Although these Dirac points are gapped by emergent gauge fluxe… ▽ More By combining the density matrix renormalization group (DMRG) method with Gutzwiller projected wave functions, we study the SU(4) symmetric spin-orbital model on the honeycomb lattice. We find that the ground states can be well described by a Gutzwiller projected $π$-flux state with Dirac-type gapless excitations at one quarter filling. Although these Dirac points are gapped by emergent gauge fluxes on finite cylinders, they govern the critical behavior in the thermodynamic limit. By inserting a $θ=π$ spin flux to twist the boundary condition, we can shift the gapless sector to the ground state, which provides compelling evidence for the presence of a gapless Dirac spin-orbital liquid. △ Less

Submitted 5 July, 2022; originally announced July 2022.

Comments: 4 pages, 2 figures, and 1 table in the main text + 3 pages supplemental material

Physics-Informed Neural Networks for Quantum Eigenvalue Problems

Authors: Henry Jin, Marios Mattheakis, Pavlos Protopapas

Abstract: Eigenvalue problems are critical to several fields of science and engineering. We expand on the method of using unsupervised neural networks for discovering eigenfunctions and eigenvalues for differential eigenvalue problems. The obtained solutions are given in an analytical and differentiable form that identically satisfies the desired boundary conditions. The network optimization is data-free an… ▽ More Eigenvalue problems are critical to several fields of science and engineering. We expand on the method of using unsupervised neural networks for discovering eigenfunctions and eigenvalues for differential eigenvalue problems. The obtained solutions are given in an analytical and differentiable form that identically satisfies the desired boundary conditions. The network optimization is data-free and depends solely on the predictions of the neural network. We introduce two physics-informed loss functions. The first, called ortho-loss, motivates the network to discover pair-wise orthogonal eigenfunctions. The second loss term, called norm-loss, requests the discovery of normalized eigenfunctions and is used to avoid trivial solutions. We find that embedding even or odd symmetries to the neural network architecture further improves the convergence for relevant problems. Lastly, a patience condition can be used to automatically recognize eigenfunction solutions. This proposed unsupervised learning method is used to solve the finite well, multiple finite wells, and hydrogen atom eigenvalue quantum problems. △ Less

Submitted 24 February, 2022; originally announced March 2022.

Microwave Amplification in a PT -symmetric-like Cavity Magnomechanical System

Authors: Hua Jin, Zhi-Bo Yang, Jing-Wen Jin, Jian-Yu Liu, Hong-Yu Liu, Rong-Can Yang

Abstract: We propose a scheme that can generate tunable magnomechanically induced amplification in a double-cavity parity-time-(PT -) symmetric-like magnomechanical system under a strong control and weak probe field. The system consists of a ferromagnetic-material yttrium iron garnet (YIG) sphere placed in a passive microwave cavity which is connected with another active cavity. We reveal that ideally induc… ▽ More We propose a scheme that can generate tunable magnomechanically induced amplification in a double-cavity parity-time-(PT -) symmetric-like magnomechanical system under a strong control and weak probe field. The system consists of a ferromagnetic-material yttrium iron garnet (YIG) sphere placed in a passive microwave cavity which is connected with another active cavity. We reveal that ideally induced amplification of the microwave probe signal may reach the maximum value 1000000 when cavity-cavity, cavity-magnon and magnomechanical coupling strengths are nonzero simultaneously. The phenomenon might have potential applications in the field of quantum information processing and quantum optical devices. Besides, we also find the phenomena of slow-light propagation. In this case, group speed delay of the light can achieve 0.000035s, which can enhance some nonlinear effect. Moreover, due to the relatively flat dispersion curve, the proposal may be applied to sensitive optical switches, which plays an important role in storing photons and quantum optical chips. △ Less

Submitted 3 December, 2021; originally announced December 2021.

Comments: 6 pages,6 figures

MSC Class: 81-10 ACM Class: J.2

Matrix product states for Hartree-Fock-Bogoliubov wave functions

Authors: Hui-Ke Jin, Rong-Yang Sun, Yi Zhou, Hong-Hao Tu

Abstract: We provide an efficient and accurate method for converting Hartree-Fock-Bogoliubov wave functions into matrix product states (MPSs). These wave functions, also known as Bogoliubov vacua, exhibit a peculiar entanglement structure that the eigenvectors of the reduced density matrix are also Bogoliubov vacua. We exploit this important feature to obtain their optimal MPS approximation and derive an ex… ▽ More We provide an efficient and accurate method for converting Hartree-Fock-Bogoliubov wave functions into matrix product states (MPSs). These wave functions, also known as Bogoliubov vacua, exhibit a peculiar entanglement structure that the eigenvectors of the reduced density matrix are also Bogoliubov vacua. We exploit this important feature to obtain their optimal MPS approximation and derive an explicit formula for corresponding MPS matrices. The performance of our method is benchmarked with the Kitaev chain and the Majorana-Hubbard model on the honeycomb lattice. The approach facilitates the applications of Hartree-Fock-Bogoliubov wave functions and is ideally suited for combining with the density-matrix renormalization group method. △ Less

Submitted 1 February, 2022; v1 submitted 17 November, 2021; originally announced November 2021.

Comments: 5 pages, 3 figures, published version

Journal ref: Phys. Rev. B 105, L081101 (2022)

Generating lightwave-photon-and-magnon entanglement with a mechanical oscillator as a "cold reservoir"

Authors: Zhi-Bo Yang, Jin-Song Liu, Hua Jin, Qing-Hao Zhu, Hong-Yu Liu, Ai-Dong Zhu, Rong-Can Yang

Abstract: We present a scheme to implement a steady lightwave-photon-and-magnon entanglement in a hybrid photon-magnon system by adiabatically eliminating the auxiliary microwave cavity and effectively laser cooling a delocalized Bogoliubov mode. The system consists of magnons, lightwave and microwave photons, and phonons. The magnons are embodied by a collective motion of a large number of spins in a macro… ▽ More We present a scheme to implement a steady lightwave-photon-and-magnon entanglement in a hybrid photon-magnon system by adiabatically eliminating the auxiliary microwave cavity and effectively laser cooling a delocalized Bogoliubov mode. The system consists of magnons, lightwave and microwave photons, and phonons. The magnons are embodied by a collective motion of a large number of spins in a macroscopic ferrimagnet. To achieve an entangling interaction between magnons and lightwave photons, we drive optical cavity and magnon at the red and blue sideband associated with the mechanical resonator. In particular, optimizing the relative ratio of effect couplings, rather than simply increasing their magnitudes, is essential for achieving strong entanglement. Unlike typical dissipative entanglement schemes, our results cannot be described by treating the effects of the entangling reservoir via a Linblad master equation. △ Less

Submitted 27 February, 2020; v1 submitted 23 February, 2020; originally announced February 2020.

Comments: There are some great mistakes and problems on the contents, languages and references

Reconfigurable on-chip entangled sources based on lithium-niobate waveguide circuits

Authors: H. Jin, F. M. Liu, P. Xu, J. L. Xia, M. L. Zhong, Y. Yuan, Y. X. Gong, W. Wang, S. N. Zhu

Abstract: Integrated quantum optics becomes a consequent tendency towards practical quantum information processing. Here, we report the on-chip generation and manipulation of photonic entanglement based on reconfigurable lithium niobate waveguide circuits. By introducing periodically poled structure into the waveguide interferometer, two individual photon-pair sources with controllable phase-shift are produ… ▽ More Integrated quantum optics becomes a consequent tendency towards practical quantum information processing. Here, we report the on-chip generation and manipulation of photonic entanglement based on reconfigurable lithium niobate waveguide circuits. By introducing periodically poled structure into the waveguide interferometer, two individual photon-pair sources with controllable phase-shift are produced and cascaded by a quantum interference, resulting in a deterministically separated identical photon pair. The state is characterized by 92.9% visibility Hong-Ou-Mandel interference. Continuous morphing from two-photon separated state to bunched state is further demonstrated by on-chip control of electro-optic phase-shift. The photon flux reaches ~1.4*10^7 pairs nm-1 mW-1. Our work presents a scenario for on-chip engineering of different photon sources and paves a way to the fully integrated quantum technologies. △ Less

Submitted 1 April, 2014; originally announced April 2014.

Compact engineering of path-entangled sources from a monolithic quadratic nonlinear photonic crystal

Authors: H. Jin, P. Xu, X. W. Luo, H. Y. Leng, Y. X. Gong, S. N. Zhu

Abstract: Photonic entangled states lie at the heart of quantum science for the demonstrations of quantum mechanics foundations and supply as a key resource for approaching various quantum technologies. An integrated realization of such states will certainly guarantee a high-degree of entanglement and improve the performance like portability, stability and miniaturization, hence becomes an inevitable tenden… ▽ More Photonic entangled states lie at the heart of quantum science for the demonstrations of quantum mechanics foundations and supply as a key resource for approaching various quantum technologies. An integrated realization of such states will certainly guarantee a high-degree of entanglement and improve the performance like portability, stability and miniaturization, hence becomes an inevitable tendency towards the integrated quantum optics. Here, we report the compact realization of steerable photonic path-entangled states from a monolithic quadratic nonlinear photonic crystal. The crystal acts as an inherent beam splitter to distribute photons into coherent spatial modes, producing the heralded single-photon even appealing beamlike two-photon path-entanglement, wherein the entanglement is characterized by quantum spatial beatings. Such multifunctional entangled source can be further extended to high-dimensional fashion and multi-photon level as well as involved with other degrees of freedom, which paves a desirable way to engineer miniaturized quantum light source. △ Less

Submitted 1 February, 2013; originally announced February 2013.

Journal ref: Phys. Rev. Lett. 111, 023603 (2013)

Improved Eavesdropping Detection Strategy in Quantum Direct Communication Protocol Based on Four-particle GHZ State

Authors: Jian Li, Haifei Jin, Bo Jing

Abstract: In order to improve the eavesdropping detection efficiency in two-step quantum direct communication protocol, an improved eavesdropping detection strategy using four-particle GHZ state is proposed, in which four-particle GHZ state is used to detect eavesdroppers. During the security analysis, the method of the entropy theory is introduced, and two detection strategies are compared quantitatively b… ▽ More In order to improve the eavesdropping detection efficiency in two-step quantum direct communication protocol, an improved eavesdropping detection strategy using four-particle GHZ state is proposed, in which four-particle GHZ state is used to detect eavesdroppers. During the security analysis, the method of the entropy theory is introduced, and two detection strategies are compared quantitatively by using the constraint between the information which eavesdropper can obtain and the interference introduced. If the eavesdroppers intend to obtain all information, the eavesdropping detection rate of the original two-step quantum direct communication protocol by using EPR pair block as detection particles is 50%; while the proposed strategy's detection rate is 88%. In the end, the security of the proposed protocol is discussed. The analysis results show that the eavesdropping detection strategy presented is more secure. △ Less

Submitted 25 October, 2011; originally announced October 2011.

Comments: 14 pages, 3 figures. arXiv admin note: substantial text overlap with arXiv:quant-ph/0308173 by different authors