Searcharxiv⌕ Search

arXiv subjects

Qi Zhou

Publications and source records attributed to Qi Zhou.

At least 163 records · Page 9Linked to original sources
arXiv2022

Impact of combining human and analytics feedback on students' engagement with, and performance in, reflective writing tasks

Reflective writing is part of many higher education courses across the globe. It is often considered a challenging task for students as it requires self-regulated learning skills to appropriately plan, timely engage and deeply reflect on learning experiences. Despite an advance in writing analytics and the pervasiveness of human feedback aimed to support student reflections, little is known about how to integrate feedback from humans and analytics to improve students' learning engagement and performance in reflective writing tasks. This study proposes a personalised behavioural feedback intervention based on students' writing engagement analytics utilising time-series analysis of digital traces from a ubiquitous online word processing platform. In a semester-long experimental study involving 81 postgraduate students, its impact on learning engagement and performance was studied. The results showed that the intervention cohort engaged statistically significantly more in their reflective writing task after receiving the combined feedback compared to the control cohort which only received human feedback on their reflective writing content. Further analyses revealed that the intervention cohort reflected more regularly at the weekly level, the regularity of weekly reflection led to better performance grades, and the impact on students with low self-regulated learning skills was higher. This study emphasizes the powerful benefits of implementing combined feedback approaches in which the strengths of analytics and human feedback are synthesized to improve student engagement and performance. Further research should explore the long-term sustainability of the observed effects and their validity in other contexts.

cs.CY↗
arXiv2022

Analogue Black Holes in Reactive Molecules

We show that reactive molecules with a unit probability of reaction naturally provide a simulator of some intriguing black hole physics. The unit reaction at the short distance acts as an event horizon and delivers a one-way traffic for matter waves passing through the potential barrier when two molecules interact by high partial-wave scatterings or dipole-dipole interactions. In particular, the scattering rate as a function of the incident energy exhibits a thermal-like distribution near the maximum of the interaction energy in the same manner as a scalar field scatters with the potential barrier outside the event horizon of a black hole. Such a thermal-like scattering can be extracted from the temperature-dependent two-body loss rate measured in experiments on KRb and other molecules.

cond-mat.quant-gas↗
arXiv2022

Long-term variation of population exposure to PM2.5 in Eastern China: A perspective from SDG 11.6.2

Air pollution (e.g., PM2.5) has a negative effect on human health. Recently, the population-weighted annual mean PM2.5 concentration (PWAM) has been selected as an indicator 11.6.2 in Sustainable Development Goals (SDGs), for various countries to perfrom a long-term monitoring of population exposure to PM2.5 in cities. However, few studies have employed this indicator for a city-level analysis and also in a long-time series (e.g., for decades). To fill this research gap, this study investigates the long-term (2000-2020) variation of population exposure to PM2.5 in Eastern China (including 318 prefecture-level cities). Three categories of open geospatial data (including high-resolution and long-term PM2.5 and population data, and administrative boundary data of cities) are involved for analysis. We found that: 1) A considerable decrease has been observed for the PWAM during 2014-2020. 2) In 2020, the PWAM is for the first time lower than the interim target-1 (35 μg/m3) defined by the World Health Organization for 214 prefecture-level cities in Eastern China, which accounts for 67% of the total population. The results indicates a considerable improvement of air quality in Eastern China. More important, this study illustrates the feasibility of using open geospatial data to monitor the SDG indicator 11.6.2.

cs.CY↗
arXiv2022

Isospectrum of non-self-adjoint almost-periodic Schrodinger operators

For non-self-adjoint almost-periodic Schrödinger operators, a criterion is given to guarantee that they have both the same spectrum and same Lyapunov exponents with the discrete free Laplacian. As a byproduct, we show that the Moser-Pöschel argument for opening gaps may not be valid for non-self-adjoint operators.

math.DS↗
arXiv2022

Nevanlinna class, Dirichlet series and Szegö's problem

This paper is associated with Nevanlinna class, Dirichlet series and Szegö's problem in infinitely many variables. As we will see, there is a natural connection between these topics. The paper first introduces the Nevanlinna class and the Smirnov class in this context, and generalizes the classical theory in finitely many variables to the infinite-variable setting. These results applied to Szegö's problem on Hardy spaces in infinitely many variables. Moreover, this paper is also devoted to the study of the correspondence between the Nevanlinna functions and Dirichlet series.

math.CV↗
arXiv2022

Find Your ASMR: A Perceptual Retrieval Interface for Autonomous Sensory Meridian Response Videos

Autonomous sensory meridian response (ASMR) is a type of video contents designed to help people relax and feel comfortable. Users usually retrieve ASMR contents from various video websites using only keywords. However, it is challenging to examine satisfactory contents to reflect users' needs for ASMR videos using keywords or content-based retrieval. To solve this issue, we propose a perceptual video retrieval system for ASMR videos and provide a novel retrieval user interface that allows users to retrieve content according to watching purpose and anticipated expectations, such as excitement, calmness, stress and sadness. An ASMR video perception dataset is constructed with annotations on affective responses after watching the videos. To verify the proposed video retrieval system, a user study is conducted showing that users can retrieve satisfactory ASMR contents easily and efficiently compared to conventional keywords-based retrieval systems.

cs.HC↗
arXiv2022

Random batch sum-of-Gaussians method for molecular dynamics simulations of particle systems

We develop an accurate, highly efficient and scalable random batch sum-of-Gaussians (RBSOG) method for molecular dynamics simulations of systems with long-range interactions. The idea of the RBSOG method is based on a sum-of-Gaussians decomposition of the Coulomb kernel, and then a random batch importance sampling on the Fourier space is employed for approximating the summation of the Fourier expansion of the Gaussians with large bandwidths (the long-range components). The importance sampling significantly reduces the computational cost, resulting in a scalable algorithm by avoiding the use of communication-intensive fast Fourier transform. Theoretical analysis is present to demonstrate the unbiasedness of the approximate force, the controllability of variance and the weak convergence of the algorithm. The resulting method has $\mathcal{O}(N)$ complexity with low communication latency. Accurate simulation results on both dynamical and equilibrium properties of benchmark problems are reported to illustrate the attractive performance of the method. Simulations on parallel computing are also performed to show the high parallel efficiency. The RBSOG method can be straightforwardly extended to more general interactions with long ranged kernels, and thus is promising to construct fast algorithms of a series of molecular dynamics methods for various interacting kernels.

physics.comp-ph↗
arXiv2022

Almost-periodic ground state of the non-self-adjoint Jacobi operator and its applications

We study the ground states of the one-dimensional non-self-adjoint Jacobi operators in the almost periodic media by using the method of dynamical systems. We show the existence of the ground state. Particularly, in the quasi-periodic media, we show that the lower regularity of coefficients can guarantee the existence of ground states. Besides that, we give two applications: the first application is to show the existence and uniqueness of the positive steady state of the discrete Fisher-KPP type equation; the second application is to investigate the asymptotic behavior of the discrete stationary parabolic equation with large lower order terms.

math.DS↗
arXiv2022

Bose-Einstein Condensate on a Synthetic Topological Hall Cylinder

The interplay between matter particles and gauge fields in physical spaces with nontrivial geometries can lead to novel topological quantum matter. However, detailed microscopic mechanisms are often obscure, and unconventional spaces are generally challenging to construct in solids. Highly controllable atomic systems can quantum simulate such physics, even those inaccessible in other platforms. Here, we realize a Bose-Einstein condensate (BEC) on a synthetic cylindrical surface subject to a net radial synthetic magnetic flux. We observe a symmetry-protected topological band structure emerging on this Hall cylinder but disappearing in the planar counterpart. BEC's transport observed as Bloch oscillations in the band structure is analogous to traveling on a Möbius strip in the momentum space, revealing topological band crossings protected by a nonsymmorphic symmetry. We demonstrate that breaking this symmetry induces a topological transition manifested as gap opening at band crossings, and further manipulate the band structure and BEC's transport by controlling the axial synthetic magnetic flux. Our work opens the door for using atomic quantum simulators to explore intriguing topological phenomena intrinsic in unconventional spaces.

cond-mat.quant-gas↗
arXiv2021

Curving the space by non-Hermiticity

Quantum systems are often classified into Hermitian and non-Hermitian ones. Extraordinary non-Hermitian phenomena, ranging from the non-Hermitian skin effect to the supersensitivity to boundary conditions, have been widely explored. Whereas these intriguing phenomena have been considered peculiar to non-Hermitian systems, we show that they can be naturally explained by a duality between non-Hermitian models in flat spaces and their counterparts, which could be Hermitian, in curved spaces. For instance, prototypical one-dimensional (1D) chains with uniform chiral tunnelings are equivalent to their duals in two-dimensional (2D) hyperbolic spaces with or without magnetic fields, and non-uniform tunnelings could further tailor local curvatures. Such a duality unfolds deep geometric roots of non-Hermitian phenomena, delivers an unprecedented routine connecting Hermitian and non-Hermitian physics, and gives rise to a theoretical perspective reformulating our understandings of curvatures and distance. In practice, it provides experimentalists with a powerful two-fold application, using non-Hermiticity as a new protocol to engineer curvatures or implementing synthetic curved spaces to explore non-Hermitian quantum physics.

cond-mat.quant-gas↗
arXiv2021

Cantor Spectrum for CMV Matrices With Almost Periodic Verblunsky Coefficients

We consider extended CMV matrices with analytic quasi-periodic Verblunsky coefficients with Diophantine frequency vector in the perturbatively small coupling constant regime and prove the analyticity of the tongue boundaries. As a consequence we establish that, generically, all gaps of the spectrum that are allowed by the Gap Labelling Theorem are open and hence the spectrum is a Cantor set. We also prove these results for a related class of almost periodic Verblunsky coefficients and present an application to suitable quantum walk models on the integer lattice.

math.SP↗
arXiv2021

Learning Robust Policy against Disturbance in Transition Dynamics via State-Conservative Policy Optimization

Deep reinforcement learning algorithms can perform poorly in real-world tasks due to the discrepancy between source and target environments. This discrepancy is commonly viewed as the disturbance in transition dynamics. Many existing algorithms learn robust policies by modeling the disturbance and applying it to source environments during training, which usually requires prior knowledge about the disturbance and control of simulators. However, these algorithms can fail in scenarios where the disturbance from target environments is unknown or is intractable to model in simulators. To tackle this problem, we propose a novel model-free actor-critic algorithm -- namely, state-conservative policy optimization (SCPO) -- to learn robust policies without modeling the disturbance in advance. Specifically, SCPO reduces the disturbance in transition dynamics to that in state space and then approximates it by a simple gradient-based regularizer. The appealing features of SCPO include that it is simple to implement and does not require additional knowledge about the disturbance or specially designed simulators. Experiments in several robot control tasks demonstrate that SCPO learns robust policies against the disturbance in transition dynamics.

cs.LG↗
arXiv2021

Sample-Efficient Reinforcement Learning via Conservative Model-Based Actor-Critic

Model-based reinforcement learning algorithms, which aim to learn a model of the environment to make decisions, are more sample efficient than their model-free counterparts. The sample efficiency of model-based approaches relies on whether the model can well approximate the environment. However, learning an accurate model is challenging, especially in complex and noisy environments. To tackle this problem, we propose the conservative model-based actor-critic (CMBAC), a novel approach that achieves high sample efficiency without the strong reliance on accurate learned models. Specifically, CMBAC learns multiple estimates of the Q-value function from a set of inaccurate models and uses the average of the bottom-k estimates -- a conservative estimate -- to optimize the policy. An appealing feature of CMBAC is that the conservative estimates effectively encourage the agent to avoid unreliable "promising actions" -- whose values are high in only a small fraction of the models. Experiments demonstrate that CMBAC significantly outperforms state-of-the-art approaches in terms of sample efficiency on several challenging tasks, and the proposed method is more robust than previous methods in noisy environments.

cs.LG↗
arXiv2021

P-wave contacts of quantum gases in quasi-one-dimensional and quasi-two-dimensional traps

The length scale separation in dilute quantum gases in quasi-one-dimensional or quasi-two-dimensional traps has spatially divided the system into two distinct regimes. Whereas universal relations defined in strict one or two dimensions apply in a scale that is much larger than the characteristic length of the transverse confinements, physical observables in the short distances are inevitably governed by three-dimensional contacts. Here, we show that p-wave contacts defined in different length scales are intrinsically connected by a universal relation, which depends on a simple geometric factor of the transverse confinements. While this universal relation is derived for one of the p-wave contacts, it establishes a concrete example of how dimensional crossover interplays with contacts and universal relations for arbitrary partial wave scatterings.

cond-mat.quant-gas↗
arXiv2021

Exact mobility edges for 1D quasiperiodic models

Mobility edges (ME), i.e. critical energies which separate absolutely continuous spectrum and purely point spectrum, is an important issue in quantum physics. So far there are two experimentally feasible 1D quasiperiodic models that have been discovered to have exact mobility edge. However, all the theoretical studies have remained at the numerical level. In this paper, we rigorously prove the existence and give the precise location of the MEs for these models.

math.DS↗
arXiv2021

Blockchain-Enabled Internet-of-Things Platform for End-to-End Industrial Hemp Supply Chain

After being legalized as an agricultural commodity by the 2018 U.S. Farm Bill, the Industrial Hemp production is moved from limited pilot programs to a regulated agriculture production system, and the market keeps increasing since then. However, Industrial Hemp Supply Chain (IHSC) faces several critical challenges, including high complexity and variability, data tampering, and lack of immutable information tracking system. In this paper, we develop a blockchain enabled internet-of-things (IoT) platform for IHSC to support process tracking, scalability, interoperability, and risk management. Basically, we create a two-layer blockchain with proof-of-authority based smart contract, which can leverage local authorities with state/federal regulators to ensure and accelerate quality control verification and regulatory compliance. Then, we develop a user-friendly mobile app so that each participant can use smart phone to real-time collect and upload their data to the cloud, and further share the process verification and tracking information through the blockchain network. Our study indicates the proposed platform can support interoperability, improve the efficiency of quality control verification, and ensure the safety of regulated IHSC.

cs.CR↗
arXiv2021

Testing DBMS Performance with Mutations

Because database systems are the critical component of modern data-intensive applications, it is important to ensure that they operate correctly. To this end, developers extensively test these systems to eliminate bugs that negatively affect functionality. In addition to functional bugs, however, there is another important class of bugs: performance bugs. These bugs negatively affect the response time of a database system and can therefore affect the overall performance of the system. Despite their impact on end-user experience, performance bugs have received considerably less attention than functional bugs. In this paper, we present AMOEBA, a system for automatically detecting performance bugs in database systems. The core idea behind AMOEBA is to construct query pairs that are semantically equivalent to each other and then compare their response time on the same database system. If the queries exhibit a significant difference in their runtime performance, then the root cause is likely a performance bug in the system. We propose a novel set of structure and predicate mutation rules for constructing query pairs that are likely to uncover performance bugs. We introduce feedback mechanisms for improving the efficacy and computational efficiency of the tool. We evaluate AMOEBA on two widely-used DBMSs, namely PostgreSQL and CockroachDB. AMOEBA has discovered 20 previously-unknown performance bugs, among which developers have already confirmed 14 and fixed 4.

cs.DB↗