arXiv subjects

Qiang Zhang

Publications and source records attributed to Qiang Zhang.

At least 451 records · Page 25Linked to original sources

arXiv2021

Coherent optical communications using coherence-cloned Kerr soliton microcombs

Dissipative Kerr soliton microcomb has been recognized as a promising on-chip multi-wavelength laser source for fiber optical communications, as its comb lines possess frequency and phase stability far beyond independent lasers. In the scenarios of coherent optical transmission and interconnect, a highly beneficial but rarely explored target is to re-generate a Kerr soliton microcomb at the receiver side as local oscillators that conserve the frequency and phase property of the incoming data carriers, so that to enable coherent detection with minimized optical and electrical compensations. Here, by using the techniques of pump laser conveying and two-point locking, we implement re-generation of a Kerr soliton microcomb that faithfully clones the frequency and phase coherence of another microcomb sent from 50 km away. Moreover, leveraging the coherence-cloned soliton microcombs as carriers and local oscillators, we demonstrate terabit coherent data interconnect, wherein traditional digital processes for frequency offset estimation is totally dispensed with, and carrier phase estimation is substantially simplified via slowed-down phase estimation rate per channel and joint phase estimation among multiple channels. Our work reveals that, in addition to providing a multitude of laser tones, regulating the frequency and phase of Kerr soliton microcombs among transmitters and receivers can significantly improve coherent communication in terms of performance, power consumption, and simplicity.

eess.SP↗

arXiv2021

Field Test of Twin-Field Quantum Key Distribution through Sending-or-Not-Sending over 428 km

Quantum key distribution endows people with information-theoretical security in communications. Twin-field quantum key distribution (TF-QKD) has attracted considerable attention because of its outstanding key rates over long distances. Recently, several demonstrations of TF-QKD have been realized. Nevertheless, those experiments are implemented in the laboratory, remaining a critical question about whether the TF-QKD is feasible in real-world circumstances. Here, by adopting the sending-or-not-sending twin-field QKD (SNS-TF-QKD) with the method of actively odd parity pairing (AOPP), we demonstrate a field-test QKD over 428~km deployed commercial fiber and two users are physically separated by about 300~km in a straight line. To this end, we explicitly measure the relevant properties of the deployed fiber and develop a carefully designed system with high stability. The secure key rate we achieved breaks the absolute key rate limit of repeater-less QKD. The result provides a new distance record for the field test of both TF-QKD and all types of fiber-based QKD systems. Our work bridges the gap of QKD between laboratory demonstrations and practical applications, and paves the way for intercity QKD network with high-speed and measurement-device-independent security.

quant-ph↗

arXiv2020

Antiferromagnetism and crystalline-electric field excitations in tetragonal NaCeO2

We investigate the crystal structure, magnetic properties, and crystalline-electric field of tetragonal, $I4_1/amd$, NaCeO$_2$. In this compound, Ce$^{3+}$ ions form a tetragonally elongated diamond lattice coupled by antiferromagnetic interactions ($Θ_{CW} = -7.69$ K) that magnetically order below $T_N = 3.18$ K. The Ce$^{3+}$ $J = 5/2$ crystalline-electric field-split multiplet is studied via inelastic neutron scattering to parameterize a $J_{eff} = 1/2$ ground state doublet comprised of states possessing mixed $|m_z \rangle$ character. Neutron powder diffraction data reveal the onset of $A$-type antiferromagnetism with $μ=0.57(2)$ $μ_B$ moments aligned along the $c$-axis. The magnetic structure is consistent with the expectations of a frustrated Heisenberg $J_1$-$J_2$ model on the elongated diamond lattice with effective exchange values $J_1 > 4 J_2$ and $J_1 > 0$.

cond-mat.str-el↗

arXiv2020

Complex magnetic phases in polar tetragonal intermetallic NdCoGe$_3$

Polar materials can host a variety of topologically significant magnetic phases, which often emerge from a modulated magnetic ground state. Relatively few noncentrosymmetric tetragonal materials have been shown to host topological spin textures and new candidate materials are necessary to expand the current theoretical models. This manuscript reports on the anisotropic magnetism in the polar, tetragonal material NdCoGe$_3$ via thermodynamic and neutron diffraction measurements. The previously reported $H$-$T$ phase diagram is updated to include several additional phases, which exist for both $H$ = 0 and with an applied field H$\perp$ c. Neutron diffraction data reveal that the magnetic structures below $T_{N1}$ = 3.70 K and $T_{N2}$ = 3.50 K are incommensurate, with a ground state magnetic order that is incommensurate in all directions with the propagation vector $\vec{k}$ = (0.494, 0.0044, 0.385) at 1.8 K. A unique magnetic structure solution is not achievable, but the possible single and multi-$\vec{k}$ spin models are discussed. These results demonstrate that NdCoGe3 hosts complicated magnetic order derived from modulated magnetic moments.

cond-mat.str-el↗

arXiv2020

Learning Cross-Domain Correspondence for Control with Dynamics Cycle-Consistency

At the heart of many robotics problems is the challenge of learning correspondences across domains. For instance, imitation learning requires obtaining correspondence between humans and robots; sim-to-real requires correspondence between physics simulators and the real world; transfer learning requires correspondences between different robotics environments. This paper aims to learn correspondence across domains differing in representation (vision vs. internal state), physics parameters (mass and friction), and morphology (number of limbs). Importantly, correspondences are learned using unpaired and randomly collected data from the two domains. We propose \textit{dynamics cycles} that align dynamic robot behavior across two domains using a cycle-consistency constraint. Once this correspondence is found, we can directly transfer the policy trained on one domain to the other, without needing any additional fine-tuning on the second domain. We perform experiments across a variety of problem domains, both in simulation and on real robot. Our framework is able to align uncalibrated monocular video of a real robot arm to dynamic state-action trajectories of a simulated arm without paired data. Video demonstrations of our results are available at: https://sjtuzq.github.io/cycle_dynamics.html .

cs.RO↗

arXiv2020

Bloch-type photonic skyrmions in optical chiral multilayers

Magnetic skyrmions are topological quasiparticles in magnetic field. Until recently, as one of their photonic counterparts, Néel-type photonic skyrmion is discovered in surface plasmon polaritons. The deep-subwavelength features of the photonic skyrmions suggest their potentials in quantum technologies and data storage. So far, the Bloch-type photonic skyrmion has yet to be demonstrated in this brand new research field. Here, by exploiting the quantum spin Hall effect of a plasmonic optical vortex in multilayered structure, we predict the existence of photonic twisted-Néel- and Bloch-type skyrmions in chiral materials. Their chirality-dependent features can be considered as additional degrees-of-freedom for future chiral sensing, information processing and storage technologies. In particular, our findings enlarge the family of photonic skyrmions and reveal a remarkable resemblance of the feature of chiral materials in two seemingly distant fields: photonic skyrmions and magnetic skyrmions.

physics.optics↗

arXiv2020

Weakly coupled alternating $S=1/2$ chains in the distorted honeycomb lattice compound Na$_2$Cu$_2$TeO$_6$

Spin-1/2 chains with alternating antiferromagnetic (AF) and ferromagnetic (FM) couplings exhibit quantum entanglement like the integer-spin Haldane chains and might be similarly utilized for quantum computations. Such alternating AF-FM chains have been proposed to be realized in the distorted honeycomb-lattice compound Na$_2$Cu$_2$TeO$_6$, but to confirm this picture a comprehensive understanding of the exchange interactions including terms outside of the idealized model is required. Here we employ neutron scattering to study the spin dynamics in Na$_2$Cu$_2$TeO$_6$ and accurately determine the coupling strengths through the random phase approximation and density functional theory (DFT) approaches. We find the AF and FM intrachain couplings are the dominant terms in the spin Hamiltonian, while the interchain couplings are AF but perturbative. This hierarchy in the coupling strengths and the alternating signs of the intrachain couplings can be understood through their different exchange paths. Our results establish Na$_2$Cu$_2$TeO$_6$ as a weakly-coupled alternating AF-FM chain compound and reveal the robustness of the gapped ground state in alternating chains under weak interchain couplings.

cond-mat.str-el↗

arXiv2020

Scaling Laws for the Propulsive Performance of a Purely Pitching Foil in Ground Effect

Scaling laws for the thrust production and power consumption of a purely pitching hydrofoil in ground effect are presented. For the first time, ground effect scaling laws based on physical insights capture the propulsive performance over a wide range of biologically-relevant Strouhal numbers, dimensionless amplitudes, and dimensionless ground distances. This is achieved by advancing previous scaling laws (Moored & Quinn 2018) with physics-driven modifications to the added mass and circulatory forces to account for ground distance variations. The key physics introduced are the increase in the added mass of a foil near the ground and the reduction in the influence of a wake vortex system due to the influence of its image system. The scaling laws are found to be in good agreement with new inviscid simulations and viscous experiments, and can be used to accelerate the design of bio-inspired hydrofoils that oscillate near a ground plane or two out-of-phase foils in a side-by-side arrangement.

physics.flu-dyn↗

arXiv2020

Machine Learning Assisted Insight to Spin Ice Dy$_2$Ti$_2$O$_7$

Complex behavior poses challenges in extracting models from experiment. An example is spin liquid formation in frustrated magnets like Dy$_2$Ti$_2$O$_7$. Understanding has been hindered by issues including disorder, glass formation, and interpretation of scattering data. Here, we use a novel automated capability to extract model Hamiltonians from data, and to identify different magnetic regimes. This involves training an autoencoder to learn a compressed representation of three-dimensional diffuse scattering, over a wide range of spin Hamiltonians. The autoencoder finds optimal matches according to scattering and heat capacity data and provides confidence intervals. Validation tests indicate that our optimal Hamiltonian accurately predicts temperature and field dependence of both magnetic structure and magnetization, as well as glass formation and irreversibility in Dy$_2$Ti$_2$O$_7$. The autoencoder can also categorize different magnetic behaviors and eliminate background noise and artifacts in raw data. Our methodology is readily applicable to other materials and types of scattering problems.

cond-mat.str-el↗

arXiv2020

Field demonstration of distributed quantum sensing without post-selection

Distributed quantum sensing can provide quantum-enhanced sensitivity beyond the shot-noise limit (SNL) for sensing spatially distributed parameters. To date, distributed quantum sensing experiments have been mostly accomplished in laboratory environments without a real space separation for the sensors. In addition, the post-selection is normally assumed to demonstrate the sensitivity advantage over the SNL. Here, we demonstrate distributed quantum sensing in field and show the unconditional violation (without post-selection) of SNL up to 0.916 dB for the field distance of 240 m. The achievement is based on a loophole free Bell test setup with entangled photon pairs at the averaged heralding efficiency of 73.88%. Moreover, to test quantum sensing in real life, we demonstrate the experiment for long distances (with 10-km fiber) together with the sensing of a completely random and unknown parameter. The results represent an important step towards a practical quantum sensing network for widespread applications.

quant-ph↗

arXiv2020

SNR-Based Teachers-Student Technique for Speech Enhancement

It is very challenging for speech enhancement methods to achieves robust performance under both high signal-to-noise ratio (SNR) and low SNR simultaneously. In this paper, we propose a method that integrates an SNR-based teachers-student technique and time-domain U-Net to deal with this problem. Specifically, this method consists of multiple teacher models and a student model. We first train the teacher models under multiple small-range SNRs that do not coincide with each other so that they can perform speech enhancement well within the specific SNR range. Then, we choose different teacher models to supervise the training of the student model according to the SNR of the training data. Eventually, the student model can perform speech enhancement under both high SNR and low SNR. To evaluate the proposed method, we constructed a dataset with an SNR ranging from -20dB to 20dB based on the public dataset. We experimentally analyzed the effectiveness of the SNR-based teachers-student technique and compared the proposed method with several state-of-the-art methods.

eess.AS↗

arXiv2020

Tuning quantum transport by controlling spin reorientations in Dirac semimetal candidates Eu$_{1-x}$Sr$_{x}$MnSb$_{2}$

Magnetic topological semimetals have attracted intense attention recently since these materials carry a great promise for potential applications in novel spintronic devices. Here, we report an intimate interplay between lattice, Eu magnetic order and topological semimetallic behavior in Eu$_{1-x}$Sr$_{x}$MnSb$_{2}$ driven by nonmagnetic Sr doping on magnetic Eu site. Different types of Eu spin reorientations are controllable by the Sr concentration, temperature or magnetic field, and coupled to the quantum transport properties of Dirac fermions generated by the 2D Sb layers. Our study opens a new pathway to achieving exotic magnetic order and topological semimetallic state via controlling spin reorientation. The effective strategy of substituting rare-earth site by nonmagnetic element demonstrated here may be applicable to the AMnCh$_{2}$ (A=rare-earth elements; Ch=Bi/Sb) family and a wide variation of other layered compounds involving spatially separated rare-earth and transition metal layers.

cond-mat.str-el↗

arXiv2020

Phenomenological theory in reentrant uranium-based superconductors

We develop a phenomenological theory for the family of uranium-based heavy fermion superconductors ($URhGe$, $UCoGe$, and $UTe_2$ ). The theory unifies the understanding of both superconductivity(SC) with a weak magnetic field and reentrant superconductivity(RSC) that appears at the first-order transition line with a high magnetic field. It is shown that the magnetizations along the easy and hard axis have opposite effects on superconductivity. The RSC is induced by the fluctuation parallel to the direction of the magnetic field. The theory makes specific predictions about the variation of triplet superconductivity order parameters $\vec{d}$ with applied external magnetic fields and the existence of a metastable state for the appearance of the RSC.

cond-mat.supr-con↗

arXiv2020

Chromatic interferometry with small frequency differences

By developing a `two-crystal' method for color erasure, we can broaden the scope of chromatic interferometry to include optical photons whose frequency difference falls outside of the 400 nm to 4500 nm wavelength range, which is the passband of a PPLN crystal. We demonstrate this possibility experimentally, by observing interference patterns between sources at 1064.4 nm and 1063.6 nm, corresponding to a frequency difference of about 200 GHz.

quant-ph↗

arXiv2020

Butterfly-like anisotropic magnetoresistance and angle-dependent Berry phase in Type-II Weyl semimetal WP2

Weyl semimetal emerges as a new topologically nontrivial phase of matter, hosting low-energy excitations of massless Weyl fermions. Here, we present a comprehensive study of the type-II Weyl semimetal WP2. Transport studies show a butterfly-like magnetoresistance at low temperature, reflecting the anisotropy of the electron Fermi surfaces. The four-lobed feature gradually evolves into a two-lobed one upon increasing temperature, mainly due to the reduced relative contribution of electron Fermi surfaces compared to hole Fermi surfaces for the magnetoresistance. Moreover, angle-dependent Berry phase is further discovered from the quantum oscillations, which is ascribed to the effective manipulation of the extremal Fermi orbits by the magnetic field to feel the nearby topological singularities in the momentum space. The revealed topological characters and anisotropic Fermi surfaces of WP2 substantially enrich the physical properties of Weyl semimetals and hold great promises in topological electronic and Fermitronic device applications.

cond-mat.mtrl-sci↗

arXiv2020

DEMC: A Deep Dual-Encoder Network for Denoising Monte Carlo Rendering

In this paper, we present DEMC, a deep Dual-Encoder network to remove Monte Carlo noise efficiently while preserving details. Denoising Monte Carlo rendering is different from natural image denoising since inexpensive by-products (feature buffers) can be extracted in the rendering stage. Most of them are noise-free and can provide sufficient details for image reconstruction. However, these feature buffers also contain redundant information, which makes Monte Carlo denoising different from natural image denoising. Hence, the main challenge of this topic is how to extract useful information and reconstruct clean images. To address this problem, we propose a novel network structure, Dual-Encoder network with a feature fusion sub-network, to fuse feature buffers firstly, then encode the fused feature buffers and a noisy image simultaneously, and finally reconstruct a clean image by a decoder network. Compared with the state-of-the-art methods, our model is more robust on a wide range of scenes and is able to generate satisfactory results in a significantly faster way.

cs.MM↗

arXiv2020

Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction

We present a novel method for testing the safety of self-driving vehicles in simulation. We propose an alternative to sensor simulation, as sensor simulation is expensive and has large domain gaps. Instead, we directly simulate the outputs of the self-driving vehicle's perception and prediction system, enabling realistic motion planning testing. Specifically, we use paired data in the form of ground truth labels and real perception and prediction outputs to train a model that predicts what the online system will produce. Importantly, the inputs to our system consists of high definition maps, bounding boxes, and trajectories, which can be easily sketched by a test engineer in a matter of minutes. This makes our approach a much more scalable solution. Quantitative results on two large-scale datasets demonstrate that we can realistically test motion planning using our simulations.

cs.CV↗

arXiv2020

Satellite-based estimates of decline and rebound in China's CO$_2$ emissions during COVID-19 pandemic

Changes in CO$_2$ emissions during the COVID-19 pandemic have been estimated from indicators on activities like transportation and electricity generation. Here, we instead use satellite observations together with bottom-up information to track the daily dynamics of CO$_2$ emissions during the pandemic. Unlike activity data, our observation-based analysis can be independently evaluated and can provide more detailed insights into spatially-explicit changes. Specifically, we use TROPOMI observations of NO$_2$ to deduce ten-day moving averages of NO$_x$ and CO$_2$ emissions over China, differentiating emissions by sector and province. Between January and April 2020, China's CO$_2$ emissions fell by 11.5% compared to the same period in 2019, but emissions have since rebounded to pre-pandemic levels owing to the fast economic recovery in provinces where industrial activity is concentrated.

physics.ao-ph↗