arXiv subjects

Wei Yi

Publications and source records attributed to Wei Yi.

At least 73 records · Page 4Linked to original sources

arXiv2022

Manipulating non-reciprocity in a two-dimensional magnetic quantum walk

Non-reciprocity is an important topic in fundamental physics and quantum-device design, as much effort has been devoted to its engineering and manipulation. Here we experimentally demonstrate non-reciprocal transport in a two-dimensional quantum walk of photons, where the directional propagation is highly tunable through dissipation and synthetic magnetic flux. The non-reciprocal dynamics hereof is a manifestation of the non-Hermitian skin effect, with its direction continuously adjustable through the photon-loss parameters. By contrast, the synthetic flux originates from an engineered geometric phase, which competes with the non-Hermitian skin effect through magnetic confinement. We further demonstrate how the non-reciprocity and synthetic flux impact the dynamics of the Floquet topological edge modes along an engineered boundary. Our results exemplify an intriguing strategy for achieving tunable non-reciprocal transport, highlighting the interplay of non-Hermiticity and gauge fields in quantum systems of higher dimensions.

cond-mat.mes-hall↗

arXiv2022

Engineering Non-Hermitian Skin Effect with Band Topology in Ultracold Gases

Non-Hermitian skin effect(NHSE) describes a unique non-Hermitian phenomenon that all eigen-modes are localized near the boundary, and has profound impact on a wide range of bulk properties. In particular, topological systems with NHSE have stimulated extensive research interests recently, given the fresh theoretical and experimental challenges therein. Here we propose a readily implementable scheme for achieving NHSE with band topology in ultracold gases. Specifically, the scheme realizes the one-dimensional optical Raman lattice with two types of spin-orbit coupling (SOC) and an additional laser-induced dissipation. By tuning the dissipation and the SOC strengths, NHSE and band topology can be individually controlled such that they can coexist in a considerable parameter regime. To identify the topological phase in the presence of NHSE, we have restored the bulk-boundary correspondence by invoking the non-Bloch band theory, and discussed the dynamic signals for detection. Our work serves as a guideline for engineering topological lattices with NHSE in the highly tunable environment of cold atoms, paving the way for future studies of exotic non-Hermitian physics in a genuine quantum many-body setting.

cond-mat.quant-gas↗

arXiv2022

Topology and its detection in a dissipative Aharonov-Bohm chain

In a recent experiment, a dissipative Aharaonov-Bohm (AB) chain was implemented in the momentum space of a Bose-Einstein condensate. Formed by a series of dissipative AB rings threaded by synthetic magnetic flux, the chain exhibits the non-Hermitian skin effect, necessitating the non-Bloch band theory to account for its topology. In this work, we systematically characterize topological features of the dissipative AB chain, particularly beyond the experimentally realized parameter regime. Further, we show that an atom-injection spectroscopy is not only capable of revealing topological edge states, as has been demonstrated in the experiment, but also the general band structure of the system. We then discuss alternative dynamic detection schemes for the topological edge states. Given the generality of the model and the detection schemes, our work is helpful to future study of topological models with non-Hermitian skin effects across a variety of quantum simulators.

cond-mat.quant-gas↗

arXiv2022

Non-Hermitian skin effect in a spin-orbit-coupled Bose-Einstein condensate

We study a Bose-Einstein condensate of ultracold atoms subject to a non-Hermitian spin-orbit coupling, where the system acquires non-Hermitian skin effect under the interplay of spin-orbit coupling and laser-induced atom loss. The presence of the non-Hermitian skin effect is confirmed through its key signatures in term of the spectral winding under the periodic boundary condition, the accumulation of eigen wavefunctions at boundaries under an open boundary condition, as well as bulk dynamics signaled by a directional flow. We show that the bulk dynamics in particular serves as a convenient signal for experimental detection. The impact of interaction and trapping potentials are also discussed based on non-Hermitian Gross-Pitaevskii equations. Our work demonstrates that the non-Hermitian skin effect and its rich implications in topology, dynamics and beyond are well within reach of current cold-atom experiments.

cond-mat.quant-gas↗

arXiv2022

Non-Hermitian skin effect in a single trapped ion

Non-Hermitian skin effect (NHSE) describes the exponential localization of all eigenstates toward boundaries in non-Hermitian systems, and has attracted intense research interest of late. Here we theoretically propose a scheme in which the NHSE significantly impacts the external motion of a single trapped ion through complex spin-motion dynamics. On the one hand, we show the competition between the NHSE and the coherent Bloch dynamics. On the other hand, since the NHSE manifests as a non-reciprocal flow in occupied phonon modes, we demonstrate that such dynamics can have potential applications in cooling and sensing. Our proposal can be readily implemented using existing experimental techniques, and offers a scalable (in terms of the available ions and phonon modes) simulation platform for relevant non-Hermitian physics.

quant-ph↗

arXiv2022

Observation of Non-Hermitian Skin Effect and Topology in Ultracold Atoms

The non-Hermitian skin effect (NHSE), the accumulation of eigen wavefunctions at boundaries of open systems, underlies a variety of exotic properties that defy conventional wisdom. While NHSE and its intriguing impact on band topology and dynamics have been observed in classical or photonic systems, their demonstration in a quantum many-body setting remains elusive. Here we report the experimental realization of a dissipative Aharonov-Bohm chain -- a non-Hermitian topological model with NHSE -- in the momentum space of a two-component Bose-Einstein condensate. We identify unique signatures of NHSE in the condensate dynamics, and perform Bragg spectroscopy to resolve topological edge states against a background of localized bulk states. Our work sets the stage for further investigation on the interplay of many-body statistics and interactions with NHSE, and is a significant step forward in the quantum control and simulation of non-Hermitian physics.

cond-mat.quant-gas↗

arXiv2022

Angular topological superfluid and topological vortex in an ultracold Fermi gas

We show that pairing in an ultracold Fermi gas under spin-orbital-angular-momentum coupling (SOAMC) can acquire topological characters encoded in the quantized angular degrees of freedom. The resulting topological superfluid is the angular analog of its counterpart in a one-dimensional Fermi gas with spin-orbit coupling, but characterized by a Zak phase defined in the angular-momentum space. Upon tuning the SOAMC parameters, a topological phase transition occurs, which is accompanied by the closing of the quasiparticle excitation gap. Remarkably, a topological vortex state can also be stabilized by deforming the Fermi surface, which is topologically non-trivial in both the coordinate and angular-momentum space, offering interesting potentials for applications in quantum information and quantum control. We discuss how the topological phase transition and the exotic vortex state can be detected experimentally.

cond-mat.quant-gas↗

arXiv2022

Recent Advances for Quantum Neural Networks in Generative Learning

Quantum computers are next-generation devices that hold promise to perform calculations beyond the reach of classical computers. A leading method towards achieving this goal is through quantum machine learning, especially quantum generative learning. Due to the intrinsic probabilistic nature of quantum mechanics, it is reasonable to postulate that quantum generative learning models (QGLMs) may surpass their classical counterparts. As such, QGLMs are receiving growing attention from the quantum physics and computer science communities, where various QGLMs that can be efficiently implemented on near-term quantum machines with potential computational advantages are proposed. In this paper, we review the current progress of QGLMs from the perspective of machine learning. Particularly, we interpret these QGLMs, covering quantum circuit born machines, quantum generative adversarial networks, quantum Boltzmann machines, and quantum autoencoders, as the quantum extension of classical generative learning models. In this context, we explore their intrinsic relation and their fundamental differences. We further summarize the potential applications of QGLMs in both conventional machine learning tasks and quantum physics. Last, we discuss the challenges and further research directions for QGLMs.

quant-ph↗

arXiv2022

Simulating non-Hermitian quasicrystals with single-photon quantum walks

Non-Hermiticity significantly enriches the properties of topological models, leading to exotic features such as the non-Hermitian skin effects and non-Bloch bulk-boundary correspondence that have no counterparts in Hermitian settings. Its impact is particularly illustrating in non-Hermitian quasicrystals where the interplay between non-Hermiticity and quasiperiodicity results in the concurrence of the delocalization-localization transition, the parity-time (PT)-symmetry breaking, and the onset of the non-Hermitian skin effects. Here we experimentally simulate non-Hermitian quasicrystals using photonic quantum walks. Using dynamic observables, we demonstrate that the system can transit from a delocalized, PT-symmetry broken phase that features non-Hermitian skin effects, to a localized, PT-symmetry unbroken phase with no non-Hermitian skin effects. The measured critical point is consistent with the theoretical prediction through a spectral winding number, confirming the topological origin of the phase transition. Our work opens the avenue of investigating the interplay of non-Hermiticity, quasiperiodicity, and spectral topology in open quantum systems.

cond-mat.mes-hall↗

arXiv2022

Observation of three superconducting transitions in the pressurized CDW-bearing compound TaTe2

Transition metal dichalcogenides host a wide variety of lattice and electronic structures, as well as corresponding exotic physical properties, especially under certain tuning conditions. Here, we are the first to report the observation of pressure-induced three superconducting transitions in TaTe2, a charge density wave (CDW) - bearing layered transition-metal dichalcogenide that is metallic but not superconducting at ambient pressure. We find that its CDW state can be easily suppressed upon increasing pressure up to ~ 1 GPa. A superconducting state then emerges from the suppressed CDW state and persists to the pressure about 7 GPa. Unexpectedly, another superconducting state appears at ~ 11 GPa within the same monoclinic (M) structure of its ambient-pressure one. Upon further compression to 21 GPa, a third superconducting state with higher Tc appears from a high-pressure (HP) phase. Our experimental results suggest that the pressure-induced three superconducting transitions in TaTe2 are respectively driven by the suppression of the CDW state, the change of the angle in the M phase and the transition of M-to-HP phase. These results demonstrate not only the versatile nature of this correlated electron system, but also the first experimental example that shows the pressure-induced evolution from a CDW state to three superconducting states driven by different mechanisms.

cond-mat.supr-con↗

arXiv2022

Subspace-Based Detection and Localization in Distributed MIMO Radars

In this paper, we consider a distributed multiple-input multiple-output (MIMO) radar which radiates waveforms with non-ideal cross- and auto-correlation functions and derive a novel subspace-based procedure to detect and localize multiple prospective targets. The proposed solution solves a sequence of composite binary hypothesis testing problems by resorting to the generalized information criterion (GIC); in particular, at each step, it aims to detect and localize one additional target, upon removing the interference caused by the previously-detected targets. An illustrative example is provided.

eess.SP↗

arXiv2022

Synthetic topology and Floquet dynamic quantum phase transition in a periodically driven Raman lattice

Stimulated by the recent progress in engineering topological band structures in cold atomic gases, we study the dynamic topological phenomena for atoms loaded in a periodically driven optical lattice. When the frequency of the periodic modulation is low, the time-dependent Hamiltonian can be mapped to a two-dimensional topological insulator, with the discretized frequency components playing the role of an additional, synthetic dimension. In the high-frequency limit, we derive the effective Floquet Hamiltonian of the system, and reveal the occurrence of Floquet dynamic quantum phase transitions -- an emergent topological phenomenon in the micromotion of the Floquet dynamics. Addressing the relation between the topology of the effective Floquet Hamiltonian and the presence of dynamic topological phenomena, we demonstrate that the topologically non-trivial nature of the Floquet Hamiltonian is a sufficient but not necessary condition for the onset of the Floquet dynamic quantum phase transition. We further discuss the relation of the topology of the Floquet Hamiltonian with the existence of dynamic skyrmion structures in the emergent momentum-time manifold of the micromotion, as well as the fate of these dynamic topological phenomena when the modulation frequency decreases away from the high-frequency limit. Finally, making use of the rich level structures of $^{171}$Yb atoms, we show that the system under study can be implemented in a one-dimensional Raman lattice where states in the $^1S_0$ ground-state manifold are coupled by Raman beams with periodically modulated amplitudes.

cond-mat.quant-gas↗

arXiv2022

Molecular state in a spin-orbital-angular-momentum coupled Fermi gas

We study the two-body bound states in a spin-orbital-angular-momentum (SOAM) coupled quantum gas of fermions. Two different configurations are considered: an attractive $s$-wave interaction exists between two spin species that are SOAM coupled; and an atom with SOAM coupled internal spins interacts state-selectively with another atom. For both cases, we identify the condition for the emergence of molecular states with finite total angular momenta.These molecular states with quantized total angular momenta correspond to the SOAM-coupling-induced vortices in the corresponding Fermi superfluid. We propose to detect the molecules through Raman spectroscopy with Laguerre-Gaussian lasers. As the molecular states can form above the superfluid temperature, they offer an experimentally more accessible route toward the study of the underlying pairing mechanism under SOAM coupling.

cond-mat.quant-gas↗

arXiv2022

Experimental realization of a quantum image classifier via tensor-network-based machine learning

Quantum machine learning aspires to overcome intractability that currently limits its applicability to practical problems. However, quantum machine learning itself is limited by low effective dimensions achievable in state-of-the-art experiments. Here we demonstrate highly successful classifications of real-life images using photonic qubits, combining a quantum tensor-network representation of hand-written digits and entanglement-based optimization. Specifically, we focus on binary classification for hand-written zeroes and ones, whose features are cast into the tensor-network representation, further reduced by optimization based on entanglement entropy and encoded into two-qubit photonic states. We then demonstrate image classification with a high success rate exceeding 98%, through successive gate operations and projective measurements. Although we work with photons, our approach is amenable to other physical realizations such as nitrogen-vacancy centers, nuclear spins and trapped ions, and our scheme can be scaled to efficient multi-qubit encodings of features in the tensor-product representation, thereby setting the stage for quantum-enhanced multi-class classification.

quant-ph↗

arXiv2021

Engineering Dissipative Quasicrystals

We discuss the systematic engineering of quasicrystals in open quantum systems where quasiperiodicity is introduced through purely dissipative processes. While the resulting short-time dynamics is governed by non-Hermitian variants of the Aubry-Andre-Harper model, we demonstrate how phases and phase transitions pertaining to the non-Hermitian quasicrystals fundamentally change the long-time, steady-state-approaching dynamics under the Lindblad master equation. Our schemes are based on an exact mapping between the eigenspectrum of the Liouvillian superoperator with that of the non-Hermitian Hamiltonian, under the condition of quadratic fermionic systems subject to linear dissipation. Our work suggests a systematic route toward engineering exotic quantum dynamics in open systems, based on insights of non-Hermitian physics.

cond-mat.quant-gas↗

arXiv2021

Trajectory PHD and CPHD Filters with Unknown Detection Profile

Compared to the probability hypothesis density (PHD) and cardinalized PHD (CPHD) filters, the trajectory PHD (TPHD) and trajectory CPHD (TCPHD) filters are for sets of trajectories, and thus are able to produce trajectory estimates with better estimation performance. In this paper, we develop the TPHD and TCPHD filters which can adaptively learn the history of the unknown target detection probability, and therefore they can perform more robustly in scenarios where targets are with unknown and time-varying detection probabilities. These filters are referred to as the unknown TPHD (U-TPHD) and unknown TCPHD (U-TCPHD) filters.By minimizing the Kullback-Leibler divergence (KLD), the U-TPHD and U-TCPHD filters can obtain, respectively, the best Poisson and independent identically distributed (IID) density approximations over the augmented sets of trajectories. For computational efficiency, we also propose the U-TPHD and U-TCPHD filters that only consider the unknown detection profile at the current time. Specifically, the Beta-Gaussian mixture method is adopted for the implementation of proposed filters, which are referred to as the BG-U-TPHD and BG-U-TCPHD filters. The L-scan approximations of these filters with much lower computational burden are also presented. Finally, various simulation results demonstrate that the BG-U-TPHD and BG-U-TCPHD filters can achieve robust tracking performance to adapt to unknown detection profile. Besides, it also shows that usually a small value of the L-scan approximation can achieve almost full efficiency of both filters but with a much lower computational costs.

eess.SP↗

arXiv2021

Multi-target Joint Tracking and Classification Using the Trajectory PHD Filter

To account for joint tracking and classification (JTC) of multiple targets from observation sets in presence of detection uncertainty, noise and clutter, this paper develops a new trajectory probability hypothesis density (TPHD) filter, which is referred to as the JTC-TPHD filter. The JTC-TPHD filter classifies different targets based on their motion models and each target is assigned with multiple class hypotheses. By using this strategy, we can not only obtain the category information of the targets, but also a more accurate trajectory estimation than the traditional TPHD filter. The JTC-TPHD filter is derived by finding the best Poisson posterior approximation over trajectories on an augmented state space using the Kullback-Leibler divergence (KLD) minimization. The Gaussian mixture is adopted for the implementation, which is referred to as the GM-JTC-TPHD filter. The L-scan approximation is also presented for the GM-JTC-TPHD filter, which possesses lower computational burden. Simulation results show that the GM-JTC-TPHD filter can classify targets correctly and obtain accurate trajectory estimation.

eess.SP↗

arXiv2021

Trajectory PHD Filter with Unknown Detection Profile and Clutter Rate

In this paper, we derive the robust TPHD (R-TPHD) filter, which can adaptively learn the unknown detection profile history and clutter rate. The R-TPHD filter is derived by obtaining the best Poisson posterior density approximation over trajectories on hybrid and augmented state space by minimizing the Kullback-Leibler divergence (KLD). Because of the huge computational burden and the short-term stability of the detection profile, we also propose the R-TPHD filter with unknown detection profile only at current time as an approximation. The Beta-Gaussian mixture model is proposed for the implementation, which is referred to as the BG-R-TPHD filter and we also propose a L-scan approximation for the BG-R-TPHD filter, which possesses lower computational burden.

eess.SP↗