arXiv subjects

Feng Zhou

Publications and source records attributed to Feng Zhou.

At least 145 records · Page 8Linked to original sources

arXiv2022

Design a Sustainable Micro-mobility Future: Trends and Challenges in the United States and European Union Using Natural Language Processing Techniques

Micro-mobility is promising to contribute to sustainable cities in the future with its efficiency and low cost. To better design such a sustainable future, it is necessary to understand the trends and challenges. Thus, we examined people's opinions on micro-mobility in the US and the EU using Tweets. We used topic modeling based on advanced natural language processing techniques and categorized the data into seven topics: promotion and service, mobility, technical features, acceptance, recreation, infrastructure and regulations. Furthermore, using sentiment analysis, we investigated people's positive and negative attitudes towards specific aspects of these topics and compared the patterns of the trends and challenges in the US and the EU. We found that 1) promotion and service included the majority of Twitter discussions in the both regions, 2) the EU had more positive opinions than the US, 3) micro-mobility devices were more widely used for utilitarian mobility and recreational purposes in the EU than in the US, and 4) compared to the EU, people in the US had many more concerns related to infrastructure and regulation issues. These findings help us understand the trends and challenges and prioritize different aspects in micro-mobility to improve their safety and experience across the two areas for designing a more sustainable micro-mobility future.

cs.CL↗

arXiv2022

Fractional optical angular momentum and multi-defect-mediated mode re-normalization and orientation control in photonic crystal microring resonators

Whispering gallery modes (WGMs) in circularly symmetric optical microresonators exhibit integer quantized angular momentum numbers due to the boundary condition imposed by the geometry. Here, we show that incorporating a photonic crystal pattern in an integrated microring can result in WGMs with fractional optical angular momentum. By choosing the photonic crystal periodicity to open a photonic bandgap with a band-edge momentum lying between that of two WGMs of the unperturbed ring, we observe hybridized WGMs with half-integer quantized angular momentum numbers ($m \in \mathbb{Z}$ + 1/2). Moreover, we show that these modes with fractional angular momenta exhibit high optical quality factors with good cavity-waveguide coupling and an order of magnitude reduced group velocity. Additionally, by introducing multiple artificial defects, multiple modes can be localized to small volumes within the ring, while the relative orientation of the de-localized band-edge states can be well-controlled. Our work unveils the renormalization of WGMs by the photonic crystal, demonstrating novel fractional angular momentum states and nontrivial multi-mode orientation control arising from continuous rotational symmetry breaking. The findings are expected to be useful for sensing/metrology, nonlinear optics, and cavity quantum electrodynamics.

physics.optics↗

arXiv2022

Rod and slit photonic crystal microrings for on-chip cavity quantum electrodynamics

Micro-/nanocavities that combine high quality factor ($Q$) and small mode volume ($V$) have been used to enhance light-matter interactions for cavity quantum electrodynamics (cQED). Whispering gallery mode (WGM) geometries such as microdisks and microrings support high-$Q$ and are design- and fabrication-friendly, but $V$ is often limited to tens of cubic wavelengths to avoid WGM radiation. The stronger modal confinement provided by either one-dimensional or two-dimensional photonic crystal defect geometries can yield sub-cubic-wavelength $V$, yet the requirements on precise design and dimensional control are typically much more stringent to ensure high-$Q$. Given their complementary features, there has been sustained interest in geometries that combine the advantages of WGM and photonic crystal cavities. Recently, a `microgear' photonic crystal ring (MPhCR) has shown promise in enabling additional defect localization ($>$ 10$\times$ reduction of $V$) of a WGM, while maintaining high-$Q$ ($\approx10^6$) and other WGM characteristics in ease of coupling and design. However, the unit cell geometry used is unlike traditional PhC cavities, and etched surfaces may be too close to embedded quantum nodes (quantum dots, atomic defect spins, etc.) for cQED applications. Here, we report two novel PhCR designs with `rod' and `slit' unit cells, whose geometries are more traditional and suitable for solid-state cQED. Both rod and slit PhCRs have high-$Q$ ($>10^6$) with WGM coupling properties preserved. A further $\approx$~10$\times$ reduction of $V$ by defect localization is observed in rod PhCRs. Moreover, both fundamental and 2nd-order PhC modes co-exist in slit PhCRs with high $Q$s and good coupling. Our work showcases that high-$Q/V$ PhCRs are in general straightforward to design and fabricate and are a promising platform to explore for cQED.

physics.optics↗

arXiv2022

Accelerated Linearized Laplace Approximation for Bayesian Deep Learning

Laplace approximation (LA) and its linearized variant (LLA) enable effortless adaptation of pretrained deep neural networks to Bayesian neural networks. The generalized Gauss-Newton (GGN) approximation is typically introduced to improve their tractability. However, LA and LLA are still confronted with non-trivial inefficiency issues and should rely on Kronecker-factored, diagonal, or even last-layer approximate GGN matrices in practical use. These approximations are likely to harm the fidelity of learning outcomes. To tackle this issue, inspired by the connections between LLA and neural tangent kernels (NTKs), we develop a Nystrom approximation to NTKs to accelerate LLA. Our method benefits from the capability of popular deep learning libraries for forward mode automatic differentiation, and enjoys reassuring theoretical guarantees. Extensive studies reflect the merits of the proposed method in aspects of both scalability and performance. Our method can even scale up to architectures like vision transformers. We also offer valuable ablation studies to diagnose our method. Code is available at \url{https://github.com/thudzj/ELLA}.

cs.LG↗

arXiv2022

Hourglass Charge-Three Weyl Phonons

Unconventional Weyl point with nonlinear dispersion features higher topological charge $|{\cal{C}}|>1$ and multiple topologically protected Fermi arc states at its boundary. As a novel topological state, it has been attracting widespread attention. However, the unconventional Weyl point with $|{\cal{C}}|=3$ has not yet been reported in realistic materials, even though it has been theoretically proposed for more than a decade. In this work, based on first-principles calculations and theoretical analysis, we predict the existing material, $\rmα$-LiIO$_3$ as the first realistic example with this unconventional Weyl point. Particularly, in the phonon spectra of $\rmα$-LiIO$_3$, two Weyl points with ${\cal{C}}=-3$, connected by time-reversal symmetry, appear at the neck crossing-point of a hourglass-type band, leading to two hourglass charge-3 Weyl phonons. The symmetry protection and the associated novel triple- and sextuple-helicoid surface arc states of the hourglass charge-3 Weyl phonons are revealed. Our results uncover a hidden topological character of $\rmα$-LiIO$_3$ and also show that the phonon spectra is a great platform for exploring unconventional topological states.

cond-mat.mtrl-sci↗

arXiv2022

High-performance microresonator optical parametric oscillator on a silicon chip

Optical parametric oscillation (OPO) is distinguished by its wavelength access, that is, the ability to flexibly generate coherent light at wavelengths that are dramatically different from the pump laser, and in principle bounded solely by energy conservation between the input pump field and the output signal/idler fields. As society adopts advanced tools in quantum information science, metrology, and sensing, microchip OPO may provide an important path for accessing relevant wavelengths. However, a practical source of coherent light should additionally have high conversion efficiency and high output power. Here, we demonstrate a silicon photonics OPO device with unprecedented performance. Our OPO device, based on the third-order ($χ^{(3)}$) nonlinearity in a silicon nitride microresonator, produces output signal and idler fields widely separated from each other in frequency ($>$150 THz), and exhibits a pump-to-idler conversion efficiency up to 29 $\%$ with a corresponding output idler power of $>$18 mW on-chip. This performance is achieved by suppressing competitive processes and by strongly overcoupling the output light. This methodology can be readily applied to existing silicon photonics platforms with heterogeneously-integrated pump lasers, enabling flexible coherent light generation across a broad range of wavelengths with high output power and efficiency.

physics.optics↗

arXiv2022

Highly-twisted states of light from a high quality factor photonic crystal ring

Twisted light with orbital angular momentum (OAM) has been extensively studied for applications in quantum and classical communications, microscopy, and optical micromanipulation. Ejecting the naturally high angular momentum whispering gallery modes (WGMs) of an optical microresonator through a grating-assisted mechanism, where the generated OAM number ($l$) is the difference of the angular momentum of the WGM and that of the grating, provides a scalable, chip-integrated solution for OAM generation. However, demonstrated OAM microresonators have exhibited a much lower quality factor ($Q$) than conventional WGM resonators (by $>100\times$), and an understanding of the ultimate limits on $Q$ has been lacking. This is crucial given the importance of $Q$ in enhancing light-matter interactions, such as single emitter coupling and parametric nonlinear processes, that underpin many important microresonator applications. Moreover, though high-OAM states are often desirable, the limits on what is achievable in a microresonator configuration are not well understood. Here, we provide new physical insight on these two longstanding questions, through understanding OAM from the perspective of mode coupling in a photonic crystal ring, and linking it to the commonly studied case of coherent backscattering between counter-propagating WGMs. In addition to demonstrating high-$Q$ ($10^5$ to $10^6$), high estimated OAM ejection efficiency (up to $90~\%$), and high-OAM number (up to $l$ = 60), our empirical model is supported by experiments and provides a quantitative explanation for the behavior of $Q$ and OAM ejection efficiency with $l$ for the first time. The state-of-the-art performance and new understanding of the physics of microresonator OAM generation will open new opportunities for realizing OAM applications using chip-integrated technologies.

physics.optics↗

arXiv2022

De-biased Representation Learning for Fairness with Unreliable Labels

Removing bias while keeping all task-relevant information is challenging for fair representation learning methods since they would yield random or degenerate representations w.r.t. labels when the sensitive attributes correlate with labels. Existing works proposed to inject the label information into the learning procedure to overcome such issues. However, the assumption that the observed labels are clean is not always met. In fact, label bias is acknowledged as the primary source inducing discrimination. In other words, the fair pre-processing methods ignore the discrimination encoded in the labels either during the learning procedure or the evaluation stage. This contradiction puts a question mark on the fairness of the learned representations. To circumvent this issue, we explore the following question: \emph{Can we learn fair representations predictable to latent ideal fair labels given only access to unreliable labels?} In this work, we propose a \textbf{D}e-\textbf{B}iased \textbf{R}epresentation Learning for \textbf{F}airness (DBRF) framework which disentangles the sensitive information from non-sensitive attributes whilst keeping the learned representations predictable to ideal fair labels rather than observed biased ones. We formulate the de-biased learning framework through information-theoretic concepts such as mutual information and information bottleneck. The core concept is that DBRF advocates not to use unreliable labels for supervision when sensitive information benefits the prediction of unreliable labels. Experiment results over both synthetic and real-world data demonstrate that DBRF effectively learns de-biased representations towards ideal labels.

cs.LG↗

arXiv2022

Towards Privacy-Preserving, Real-Time and Lossless Feature Matching

Most visual retrieval applications store feature vectors for downstream matching tasks. These vectors, from where user information can be spied out, will cause privacy leakage if not carefully protected. To mitigate privacy risks, current works primarily utilize non-invertible transformations or fully cryptographic algorithms. However, transformation-based methods usually fail to achieve satisfying matching performances while cryptosystems suffer from heavy computational overheads. In addition, secure levels of current methods should be improved to confront potential adversary attacks. To address these issues, this paper proposes a plug-in module called SecureVector that protects features by random permutations, 4L-DEC converting and existing homomorphic encryption techniques. For the first time, SecureVector achieves real-time and lossless feature matching among sanitized features, along with much higher security levels than current state-of-the-arts. Extensive experiments on face recognition, person re-identification, image retrieval, and privacy analyses demonstrate the effectiveness of our method. Given limited public projects in this field, codes of our method and implemented baselines are made open-source in https://github.com/IrvingMeng/SecureVector.

cs.CV↗

arXiv2022

Cause-and-Effect Analysis of ADAS: A Comparison Study between Literature Review and Complaint Data

Advanced driver assistance systems (ADAS) are designed to improve vehicle safety. However, it is difficult to achieve such benefits without understanding the causes and limitations of the current ADAS and their possible solutions. This study 1) investigated the limitations and solutions of ADAS through a literature review, 2) identified the causes and effects of ADAS through consumer complaints using natural language processing models, and 3) compared the major differences between the two. These two lines of research identified similar categories of ADAS causes, including human factors, environmental factors, and vehicle factors. However, academic research focused more on human factors of ADAS issues and proposed advanced algorithms to mitigate such issues while drivers complained more of vehicle factors of ADAS failures, which led to associated top consequences. The findings from these two sources tend to complement each other and provide important implications for the improvement of ADAS in the future.

cs.CL↗

arXiv2022

Kerr optical parametric oscillation in a photonic crystal microring for accessing the infrared

Continuous wave optical parametric oscillation (OPO) provides a flexible approach for accessing mid-infrared wavelengths between 2 $μ$m to 5 $μ$m, but has not yet been integrated into silicon nanophotonics. Typically, Kerr OPO uses a single transverse mode family for pump, signal, and idler modes, and relies on a delicate balance to achieve normal (but close-to-zero) dispersion near the pump and the requisite higher-order dispersion needed for phase- and frequency-matching. Within integrated photonics platforms, this approach results in two major problems. First, the dispersion is very sensitive to geometry, so that small fabrication errors can have a large impact. Second, the device is susceptible to competing nonlinear processes near the pump. In this letter, we propose a flexible solution to infrared OPO that addresses these two problems, by using a silicon nitride photonic crystal microring (PhCR). The frequency shifts created by the PhCR bandgap enable OPO that would otherwise be forbidden. We report an intrinsic optical quality factor up to (1.2 $\pm$ 0.1)$\times$10$^6$ in the 2 $μ$m band, and use a PhCR ring to demonstrate an OPO with threshold power of (90 $\pm$ 20) mW dropped into the cavity, with the pump wavelength at 1998~nm, and the signal and idler wavelengths at 1937 nm and 2063 nm, respectively. We further discuss how to extend OPO spectral coverage in the mid-infrared. These results establish the PhCR OPO as a promising route for integrated laser sources in the infrared.

physics.optics↗

arXiv2022

On semilinear elliptic equation with negative exponent arising from a closed MEMS model

This paper is concerned with the elliptic equation $-Δu=\frac{λ}{(a-u)^p}$ in a connected, bounded $C^2$ domain $Ω$ of $\mathbb{R}^N$ subject to zero Dirichlet boundary conditions, where $λ>0$, $N\geq 1$, $p>0$ and $a:\barΩ\to[0,1]$ vanishes at the boundary with the rate ${\rm dist}(x,\partialΩ)^γ$ for $γ>0$. When $p=2$ and $N=2$, this equation models the closed Micro-Electromechanical Systems devices, where the elastic membrane sticks the curved ground plate on the boundary, but insulating on the boundary. The function $a$ shapes the curved ground plate. Our aim in this paper is to study qualitative properties of minimal solutions of this equation when $λ>0$, $p>0$ and to show how the boundary decaying of $a$ works on the minimal solutions and the pull-in voltage. Particularly, we give a complete analysis for the stability of the minimal solutions.

math.AP↗

arXiv2022

Investigating Explanations in Conditional and Highly Automated Driving: The Effects of Situation Awareness and Modality

With the level of automation increases in vehicles, such as conditional and highly automated vehicles (AVs), drivers are becoming increasingly out of the control loop, especially in unexpected driving scenarios. Although it might be not necessary to require the drivers to intervene on most occasions, it is still important to improve drivers' situation awareness (SA) in unexpected driving scenarios to improve their trust in and acceptance of AVs. In this study, we conceptualized SA at the levels of perception (SA L1), comprehension (SA L2), and projection (SA L3), and proposed an SA level-based explanation framework based on explainable AI. Then, we examined the effects of these explanations and their modalities on drivers' situational trust, cognitive workload, as well as explanation satisfaction. A three (SA levels: SA L1, SA L2 and SA L3) by two (explanation modalities: visual, visual + audio) between-subjects experiment was conducted with 340 participants recruited from Amazon Mechanical Turk. The results indicated that by designing the explanations using the proposed SA-based framework, participants could redirect their attention to the important objects in the traffic and understand their meaning for the AV system. This improved their SA and filled the gap of understanding the correspondence of AV's behavior in the particular situations which also increased their situational trust in AV. The results showed that participants reported the highest trust with SA L2 explanations, although the mental workload was assessed higher in this level. The results also provided insights into the relationship between the amount of information in explanations and modalities, showing that participants were more satisfied with visual-only explanations in the SA L1 and SA L2 conditions and were more satisfied with visual and auditory explanations in the SA L3 condition.

cs.HC↗

arXiv2022

Anticipated emotions associated with trust in autonomous vehicles

Trust in automation has been mainly studied in the cognitive perspective, though some researchers have shown that trust is also influenced by emotion. Therefore, it is essential to investigate the relationships between emotions and trust. In this study, we explored the pattern of 19 anticipated emotions associated with two levels of trust (i.e., low vs. high levels of trust) elicited from two levels of autonomous vehicles (AVs) performance (i.e., failure and non-failure) from 105 participants from Amazon Mechanical Turk (AMT). Trust was assessed at three layers i.e., dispositional, initial learned, and situational trust. The study was designed to measure how emotions are affected with low and high levels of trust. Situational trust was significantly correlated with emotions that a high level of trust significantly improved participants' positive emotions, and vice versa. We also identified the underlying factors of emotions associated with situational trust. Our results offered important implications on anticipated emotions associated with trust in AVs.

cs.HC↗

arXiv2022

Quantifying Wetting Dynamics with Triboelectrification

Wetting is often perceived as an intrinsic surface property of materials, but determining its evolution is complicated by its complex dependence on roughness across the scales. The Wenzel state, where liquids have intimate contact with the rough substrate, and the Cassie-Baxter state, where liquids sit onto air pockets formed between asperities, are only two states among the plethora of wetting behaviors. Furthermore, transitions from the Cassie-Baxter to the Wenzel state dictate completely different surface performance, such as anti-contamination, anti-icing, drag reduction etc.; however, little is known about how transition occurs during time between the several wetting modes. In this paper, we show that wetting dynamics can be accurately quantified and tracked using solid-liquid triboelectrification. Theoretical underpinning reveals how surface micro-/nano-geometries regulate stability/infiltration, also demonstrating the generality of our theoretical approach in understanding wetting transitions.

cond-mat.soft↗

arXiv2022

Intrinsically accurate sensing with an optomechanical accelerometer

We demonstrate a microfabricated optomechanical accelerometer that is capable of percent-level accuracy without external calibration. To achieve this capability, we use a mechanical model of the device behavior that can be characterized by the thermal noise response along with an optical frequency comb readout method that enables high sensitivity, high bandwidth, high dynamic range, and SI-traceable displacement measurements. The resulting intrinsic accuracy was evaluated over a wide frequency range by comparing to a primary vibration calibration system and local gravity. The average agreement was found to be 2.1 % for the calibration system between 0.1 kHz and 15 kHz and better than 0.2 % for the static acceleration. This capability has the potential to replace costly external calibrations and improve the accuracy of inertial guidance systems and remotely deployed accelerometers. Due to the fundamental nature of the intrinsic accuracy approach, it could be extended to other optomechanical transducers, including force and pressure sensors.

physics.ins-det↗

arXiv2022

Single Pair of Weyl Points in Nonmagnetic Crystals

Topological semimetal states having the minimal number, i.e., only a single pair, of Weyl points are desirable for the study of effects associated with chiral topological charges. So far, the search for such states is focused on magnetic spinful systems. Here, we find that nonmagnetic spinless systems can host a class of single-pair-Weyl-point (SP-WP) states, where the two Weyl points are located at two high-symmetry time-reversal-invariant momenta. We identify 32 candidate space groups that host such states, and we show that the chiral charge of each Weyl point in the SP-WP state must be an even integer. Besides achieving the minimal number, Weyl points in SP-WP states are far separated in momentum space, making the physics of each individual point better exposed. The large separation combined with the even topological charge lead to extended surface Fermi loops with a non-contractible winding topology on the surface Brillouin zone torus, distinct from conventional Weyl semimetals. We confirm our proposal in the phonon spectra of two concrete materials TlBO$_2$ and KNiIO$_6$. Our finding applies to a wide range of systems, including electronic, phononic, and various artificial systems. It offers a new direction for the search of ideal platforms to study chiral particles.

cond-mat.mtrl-sci↗

arXiv2022

Isolated singularities for fractional Lane-Emden equations in the Serrin's supercritical case

In this paper, we give a classification of the isolated singularities of positive solutions to the semilinear fractional elliptic equations $$(E) \quad\quad (-Δ)^s u = |x|^θ u^{p}\quad {\rm in}\ \ B_1\setminus\{0\},\quad u= h\quad{\rm in}\ \ \mathbb{R}^N\setminus B_1,\quad $$ where $s\in(0,1)$, $θ>-2s$, $p>\frac{N+θ}{N-2s}$, $B_1$ is the unit ball centered at the origin of $\mathbb{R}^N$ with $N>2s$. $h$ is a nonnegative Hölder continuous function in $\mathbb{R}^N\setminus B_1$. Our analysis of isolated singularities of $(E)$ is based on an integral upper bounds and the study of the Poisson problem with the fractional Hardy operators. It is worth noting that our classification of isolated singularity holds in the Sobolev super critical case $p>\frac{N+2s+2θ}{N-2s}$ for $s\in(0,1]$ under suitable assumption of $h$.

math.AP↗