arXiv subjects

Wei Fu

Publications and source records attributed to Wei Fu.

At least 37 records · Page 2Linked to original sources

arXiv2024

Learning Agile Bipedal Motions on a Quadrupedal Robot

Can a quadrupedal robot perform bipedal motions like humans? Although developing human-like behaviors is more often studied on costly bipedal robot platforms, we present a solution over a lightweight quadrupedal robot that unlocks the agility of the quadruped in an upright standing pose and is capable of a variety of human-like motions. Our framework is with a hierarchical structure. At the low level is a motion-conditioned control policy that allows the quadrupedal robot to track desired base and front limb movements while balancing on two hind feet. The policy is commanded by a high-level motion generator that gives trajectories of parameterized human-like motions to the robot from multiple modalities of human input. We for the first time demonstrate various bipedal motions on a quadrupedal robot, and showcase interesting human-robot interaction modes including mimicking human videos, following natural language instructions, and physical interaction. The video is available at https://sites.google.com/view/bipedal-motions-quadruped.

cs.RO↗

arXiv2024

Dielectrics for Two-Dimensional Transition Metal Dichalcogenide Applications

Despite over a decade of intense research efforts, the full potential of two-dimensional transition metal dichalcogenides continues to be limited by major challenges. The lack of compatible and scalable dielectric materials and integration techniques restrict device performances and their commercial applications Conventional dielectric integration techniques for bulk semiconductors are difficult to adapt for atomically thin two-dimensional materials. This review provides a brief introduction into various common and emerging dielectric synthesis and integration techniques and discusses their applicability for 2D transition metal dichalcogenides. Dielectric integration for various applications is reviewed in subsequent sections including nanoelectronics, optoelectronics, flexible electronics, valleytronics, biosensing, quantum information processing, and quantum sensing. For each application, we introduce basic device working principles, discuss the specific dielectric requirements, review current progress, present key challenges, and offer insights into future prospects and opportunities.

cond-mat.mtrl-sci↗

arXiv2023

Ground Calibration Result of the Lobster Eye Imager for Astronomy

We report on results of the on-ground X-ray calibration of the Lobster Eye Imager for Astronomy (LEIA), an experimental space wide-field (18.6*18.6 square degrees) X-ray telescope built from novel lobster eye mirco-pore optics. LEIA was successfully launched on July 27, 2022 onboard the SATech-01 satellite. To achieve full characterisation of its performance before launch, a series of tests and calibrations have been carried out at different levels of devices, assemblies and the complete module. In this paper, we present the results of the end-to-end calibration campaign of the complete module carried out at the 100-m X-ray Test Facility at IHEP. The PSF, effective area and energy response of the detectors were measured in a wide range of incident directions at several X-ray line energies. The distributions of the PSF and effective areas are roughly uniform across the FoV, in large agreement with the prediction of lobster-eye optics. The mild variations and deviations from the prediction of idealized lobster-eye optics can be understood to be caused by the imperfect shapes and alignment of the micro-pores as well as the obscuration by the supporting frames, which can be well reproduced by MC simulations. The spatial resolution of LEIA defined by the FWHM of the focal spot ranges from 4-8 arcmin with a median of 5.7. The measured effective areas are in range of 2-3 $cm^2$ at ~1.25 keV across the entire FoV, and its dependence on photon energy is in large agreement with simulations. The gains of the CMOS sensors are in range of 6.5-6.9 eV/DN, and the energy resolutions in the range of ~120-140 eV at 1.25 keV and ~170-190 eV at 4.5 keV. These results have been ingested into the calibration database and applied to the analysis of the scientific data acquired by LEIA. This work paves the way for the calibration of the Wide-field X-Ray Telescope modules of the Einstein Probe mission.

astro-ph.IM↗

arXiv2023

Open-orbit induced low field extremely large magnetoresistance in graphene/h-BN superlattices

We report intriguing and hitherto overlooked low-field room temperature extremely large magnetoresistance (XMR) patterns in graphene/hexagonal boron nitride (h-BN) superlattices that emerge due to the existence of open orbits within each miniband. This finding is set against the backdrop of the experimental discovery of the Hofstadter butterfly in moir superlattices, which has sparked considerable interest in the fractal quantum Hall regime. To cope with the challenge of deciphering the low magnetic field dynamics of moir minibands, we utilize a novel semi-classical calculation method, grounded in zero-field Fermi contours, to predict the nontrivial behavior of the Landau-level spectrum. This is compared with fully quantum simulations, enabling an in-depth and contrasted analysis of transport measurements in high-quality graphene-hBN superlattices. Our results not only highlight the primary observation of the open-orbit induced XMR in this system but also shed new light on other intricate phenomena. These include the nuances of single miniband dynamics, evident through Lifshitz transitions, and the complex interplay of semiclassical and quantum effects between these minibands. Specifically, we document transport anomalies linked to trigonal warping, a semiclassical deviation from the expected linear characteristics of Landau levels, and magnetic breakdown phenomena indicative of quantum tunneling, all effects jointly contributing to the intricacies of a rich electronic landscape uncovered at low magnetic fields.

cond-mat.mes-hall↗

arXiv2023

Photonic link from single flux quantum circuits to room temperature

Broadband, energy-efficient signal transfer between cryogenic and room-temperature environment has been a major bottleneck for superconducting quantum and classical logic circuits. Photonic links promise to overcome this challenge by offering simultaneous high bandwidth and low thermal load. However, the development of cryogenic electro-optic modulators -- a key component for photonic readout of electrical signals -- has been stifled by the stringent requirements of superconducting circuits. Rapid single flux quantum circuits (RSFQ), for example, operate with a tiny signal amplitude of only a few millivolts (mV), far below the volt-level signal used in conventional circuits. Here, we demonstrate the first direct optical readout of an RSFQ circuit without additional electrical amplification enabled by a novel superconducting electro-optic modulator (SEOM) featuring a record-low half-wave voltage Vπ of 42 mV on a 1 m-long SEOM. Leveraging the low ohmic loss of superconductors, we break the fundamental Vπ-bandwidth trade-off and demonstrate electro-optic bandwidth up to 17 GHz on a 0.2 m-long SEOM at cryogenic temperatures. Our work presents a viable solution toward high-bandwidth signal transfer between future large-scale superconducting circuits and room-temperature electronics.

quant-ph↗

arXiv2023

Iteratively Learn Diverse Strategies with State Distance Information

In complex reinforcement learning (RL) problems, policies with similar rewards may have substantially different behaviors. It remains a fundamental challenge to optimize rewards while also discovering as many diverse strategies as possible, which can be crucial in many practical applications. Our study examines two design choices for tackling this challenge, i.e., diversity measure and computation framework. First, we find that with existing diversity measures, visually indistinguishable policies can still yield high diversity scores. To accurately capture the behavioral difference, we propose to incorporate the state-space distance information into the diversity measure. In addition, we examine two common computation frameworks for this problem, i.e., population-based training (PBT) and iterative learning (ITR). We show that although PBT is the precise problem formulation, ITR can achieve comparable diversity scores with higher computation efficiency, leading to improved solution quality in practice. Based on our analysis, we further combine ITR with two tractable realizations of the state-distance-based diversity measures and develop a novel diversity-driven RL algorithm, State-based Intrinsic-reward Policy Optimization (SIPO), with provable convergence properties. We empirically examine SIPO across three domains from robot locomotion to multi-agent games. In all of our testing environments, SIPO consistently produces strategically diverse and human-interpretable policies that cannot be discovered by existing baselines.

cs.LG↗

arXiv2022

Light-induced dynamic frequency shifting of microwave photons in a superconducting electro-optic converter

Hybrid superconducting-photonic microresonators are a promising platform for realizing microwave-to-optical transduction. However, the absorption of scattered photons by the superconductors leads to unintended microwave resonance frequency variation and linewidth broadening. Here, we experimentally study the dynamics of this effect and its impact on microwave-to-optics conversion in an integrated lithium niobate-superconductor hybrid resonator platform. We unveiled an adiabatic frequency shifting of the intracavity microwave photons induced by the fast photo-responses of the thin-film superconducting resonator. As a result, the temporal and spectral responses of electro-optics transduction are modified and well described by our theoretical model. This work provides important insights on the light-induced conversion dynamics which must be considered in future designs of hybrid superconducting-photonic system.

physics.app-ph↗

arXiv2022

Liquid Metal Printed Ultrathin Oxides for Monolayer WS2 Top-Gate Transistors

Two-dimensional (2D) semiconductors are promising channel materials for continued downscaling of complementary metal-oxide-semiconductor (CMOS) logic circuits. However, their full potential continues to be limited by a lack of scalable high-k dielectrics that can achieve atomically smooth interfaces, small equivalent oxide thicknesses (EOT), excellent gate control, and low leakage currents. Here, we report liquid metal printed ultrathin and scalable Ga2O3 dielectric for 2D electronics and electro-optical devices. We directly visualize the atomically smooth Ga2O3/WS2 interfaces enabled by the conformal nature of liquid metal printing. We demonstrate atomic layer deposition compatibility with high-k Ga2O3/HfO2 top-gate dielectric stacks on chemical vapour deposition grown monolayer WS2, achieving EOTs of ~1 nm and subthreshold swings down to 84.9 mV/dec. Gate leakage currents are well within requirements for ultra-scaled low-power logic circuits. Our results show that liquid metal printed oxides can bridge a crucial gap in scalable dielectric integration of 2D materials for next-generation nano-electronics.

cond-mat.mtrl-sci↗

arXiv2022

On a coupled Kadomtsev--Petviashvili system associated with an elliptic curve

The coupled Kadomtsev--Petviashvili system associated with an elliptic curve, proposed by Date, Jimbo and Miwa [J. Phys. Soc. Jpn., 52:766--771, 1983], is reinvestigated within the direct linearisation framework, which provides us with more insights into the integrability of this elliptic model from the perspective of a general linear integral equation. As a result, we successfully construct for the elliptic coupled Kadomtsev--Petviashvili system not only a Lax pair composed of differential operators in $2\times2$ matrix form but also multi-soliton solutions with phases parametrised by points on the elliptic curve. Dimensional reductions based on the direct linearisation, to the elliptic coupled Korteweg-de Vries and Boussinesq systems, are also discussed. In addition, a novel class of solutions are obtained for the $D_\infty$-type Kadomtsev--Petviashvili equation with nonzero constant background as a byproduct.

nlin.SI↗

arXiv2022

Revisiting Some Common Practices in Cooperative Multi-Agent Reinforcement Learning

Many advances in cooperative multi-agent reinforcement learning (MARL) are based on two common design principles: value decomposition and parameter sharing. A typical MARL algorithm of this fashion decomposes a centralized Q-function into local Q-networks with parameters shared across agents. Such an algorithmic paradigm enables centralized training and decentralized execution (CTDE) and leads to efficient learning in practice. Despite all the advantages, we revisit these two principles and show that in certain scenarios, e.g., environments with a highly multi-modal reward landscape, value decomposition, and parameter sharing can be problematic and lead to undesired outcomes. In contrast, policy gradient (PG) methods with individual policies provably converge to an optimal solution in these cases, which partially supports some recent empirical observations that PG can be effective in many MARL testbeds. Inspired by our theoretical analysis, we present practical suggestions on implementing multi-agent PG algorithms for either high rewards or diverse emergent behaviors and empirically validate our findings on a variety of domains, ranging from the simplified matrix and grid-world games to complex benchmarks such as StarCraft Multi-Agent Challenge and Google Research Football. We hope our insights could benefit the community towards developing more general and more powerful MARL algorithms. Check our project website at https://sites.google.com/view/revisiting-marl.

cs.AI↗

arXiv2022

Superconducting cavity piezo-electromechanics: the realization of an acoustic frequency comb at microwave frequencies

We present a nonlinear multimode superconducting electroacoustic system, where the interplay between superconducting kinetic inductance and piezoelectric strong coupling establishes an effective Kerr nonlinearity among multiple acoustic modes at 10 GHz that could hardly be achieved via intrinsic mechanical nonlinearity. By exciting this multimode Kerr system with a single microwave tone, we further demonstrate a coherent electroacoustic frequency comb and provide theoretical understanding of multimode nonlinear interaction in the superstrong coupling limit. This nonlinear superconducting electroacoustic system sheds light on the active control of multimode resonator systems and offers an enabling platform for the dynamic study of microcombs at microwave frequencies.

physics.app-ph↗

arXiv2022

SmartCut Er:LiNbO3 with high optical coherence enabling optical thickness control

Integrated photonics capable of incorporating rare earth ions with high optical coherence is desirable for realizing efficient quantum transducers, compact quantum memories, and hybrid quantum systems. Here we describe a photonic platform based on the SmartCut erbium-doped lithium niobate thin film, and explore its stable optical transitions at telecom wavelength in a dilution refrigerator. Optical coherence time of up to 180\,$μ$s, rivaling the value of bulk crystals, is achieved in optical ridge waveguides and ring resonators. With this integrated platform, we demonstrate tunable light-ion interaction and flexible control of optical thickness by exploiting long waveguides, whose lengths are in principle variable. This unique ability to obtain high optical density using a low concentration ions further leads to the observation of multi-echo pulse trains in centimeter-long waveguides. Our results establish a promising photonic platform for quantum information processing with rare earth ions.

physics.optics↗

arXiv2022

Integrable semi-discretisation of the Drinfel'd--Sokolov hierarchies

We propose a novel semi-discrete Kadomtsev--Petviashvili equation with two discrete and one continuous independent variables, which is integrable in the sense of having the standard and adjoint Lax pairs, from the direct linearisation framework. By performing reductions on the semi-discrete Kadomtsev--Petviashvili equation, new semi-discrete versions of the Drinfel'd--Sokolov hierarchies associated with Kac--Moody Lie algebras $A_r^{(1)}$, $A_{2r}^{(2)}$, $C_r^{(1)}$ and $D_{r+1}^{(2)}$ are successfully constructed. A Lax pair involving the fraction of $\mathbb{Z}_\mathcal{N}$ graded matrices is also found for each of the semi-discrete Drinfel'd--Sokolov equations. Furthermore, the direct linearisation construction guarantees the existence of exact solutions of all the semi-discrete equations discussed in the paper, providing another insight into their integrability in addition to the analysis of Lax pairs.

nlin.SI↗

arXiv2022

Continuously Discovering Novel Strategies via Reward-Switching Policy Optimization

We present Reward-Switching Policy Optimization (RSPO), a paradigm to discover diverse strategies in complex RL environments by iteratively finding novel policies that are both locally optimal and sufficiently different from existing ones. To encourage the learning policy to consistently converge towards a previously undiscovered local optimum, RSPO switches between extrinsic and intrinsic rewards via a trajectory-based novelty measurement during the optimization process. When a sampled trajectory is sufficiently distinct, RSPO performs standard policy optimization with extrinsic rewards. For trajectories with high likelihood under existing policies, RSPO utilizes an intrinsic diversity reward to promote exploration. Experiments show that RSPO is able to discover a wide spectrum of strategies in a variety of domains, ranging from single-agent particle-world tasks and MuJoCo continuous control to multi-agent stag-hunt games and StarCraftII challenges.

cs.LG↗

arXiv2022

Predicting Health Indicators for Open Source Projects (using Hyperparameter Optimization)

Software developed on public platform is a source of data that can be used to make predictions about those projects. While the individual developing activity may be random and hard to predict, the developing behavior on project level can be predicted with good accuracy when large groups of developers work together on software projects. To demonstrate this, we use 64,181 months of data from 1,159 GitHub projects to make various predictions about the recent status of those projects (as of April 2020). We find that traditional estimation algorithms make many mistakes. Algorithms like $k$-nearest neighbors (KNN), support vector regression (SVR), random forest (RFT), linear regression (LNR), and regression trees (CART) have high error rates. But that error rate can be greatly reduced using hyperparameter optimization. To the best of our knowledge, this is the largest study yet conducted, using recent data for predicting multiple health indicators of open-source projects.

cs.SE↗

arXiv2021

Linear integral equations and two-dimensional Toda systems

The direct linearisation framework is presented for the two-dimensional Toda equations associated with the infinite-dimensional Lie algebras $A_\infty$, $B_\infty$ and $C_\infty$, as well as the Kac--Moody algebras $A_{r}^{(1)}$, $A_{2r}^{(2)}$, $C_{r}^{(1)}$ and $D_{r+1}^{(2)}$ for arbitrary integers $r\in\mathbb{Z}^+$, from the aspect of a set of linear integral equations in a certain form. Such a scheme not only provides a unified perspective to understand the underlying integrability structure, but also induces the direct linearising type solution potentially leading to the universal solution space, for each class of the two-dimensional Toda system. As particular applications of this framework to the two-dimensional Toda lattices, we rediscover the Lax pairs and the adjoint Lax pairs and simultaneously construct the generalised Cauchy matrix solutions.

nlin.SI↗

arXiv2021

Bidirectional electro-optic conversion reaching 1% efficiency with thin-film lithium niobate

Superconducting cavity electro-optics (EO) presents a promising route to coherently convert microwave and optical photons and distribute quantum entanglement between superconducting circuits over long-distance through an optical network. High EO conversion efficiency demands transduction materials with strong Pockels effect and excellent optical transparency. Thin-film Lithium Niobate (TFLN) offers these desired characteristics however so far has only delivered unidirectional conversion with efficiencies on the order of $10^{-5}$, largely impacted by its prominent photorefractive (PR) effect at cryogenic temperatures. Here we show that, by mitigating the PR effect and associated charge-screening effect, the device's conversion efficiency can be enhanced by orders of magnitude while maintaining stable cryogenic operation, thus allowing a demonstration of conversion bidirectionality and accurate quantification of on-chip efficiency. With the optimized monolithic integrated superconducting EO device based on TFLN-on-sapphire substrate, an on-chip conversion efficiency of 1.02% (internal efficiency, 15.2%) is realized. Our demonstration indicates that with further device improvement, it is feasible for TFLN to approach unitary internal conversion efficiency.

physics.optics↗

arXiv2020

On nonautonomous differential-difference AKP, BKP and CKP equations

Based on the direct linearisation framework of the discrete Kadomtsev-Petviashvili-type equations presented in [Proc. R. Soc. A, 473 (2017) 20160915], six novel nonautonomous differential-difference equations are established, including three in the AKP class, two in the BKP class and one in the CKP class. In particular, one in the BKP class and the one in the CKP class are both in (2+2)-dimensional form. All the six models are integrable in the sense of having the same linear integral equation representations as those of their associated discrete Kadomtsev-Petviashvili-type equations, which guarantees the existence of soliton-type solutions and the multi-dimensional consistency of these new equations from the viewpoint of the direct linearisation.

nlin.SI↗