arXiv subjects

Fan Wu

Publications and source records attributed to Fan Wu.

At least 235 records · Page 13Linked to original sources

arXiv2024

Vertical Federated Learning: Challenges, Methodologies and Experiments

Recently, federated learning (FL) has emerged as a promising distributed machine learning (ML) technology, owing to the advancing computational and sensing capacities of end-user devices, however with the increasing concerns on users' privacy. As a special architecture in FL, vertical FL (VFL) is capable of constructing a hyper ML model by embracing sub-models from different clients. These sub-models are trained locally by vertically partitioned data with distinct attributes. Therefore, the design of VFL is fundamentally different from that of conventional FL, raising new and unique research issues. In this paper, we aim to discuss key challenges in VFL with effective solutions, and conduct experiments on real-life datasets to shed light on these issues. Specifically, we first propose a general framework on VFL, and highlight the key differences between VFL and conventional FL. Then, we discuss research challenges rooted in VFL systems under four aspects, i.e., security and privacy risks, expensive computation and communication costs, possible structural damage caused by model splitting, and system heterogeneity. Afterwards, we develop solutions to addressing the aforementioned challenges, and conduct extensive experiments to showcase the effectiveness of our proposed solutions.

cs.LG↗

arXiv2024

Topological Transitions in a Kerr Nonlinear Oscillator

A Kerr nonlinear oscillator (KNO) supports a pair of steady eigenstates, coherent states with opposite phases, that are good for the encoding of continuous variable qubit basis states. Arbitrary control of the KNO confined within the steady state subspace allows extraction of the Berry curvature through the linear response of the physical observable to the quench velocity of the system, providing an effective method for the characterization of topology in the KNO. As an alternative, the control adopting the "shortcut to adiabaticity" to the KNO enables the exploration of the topology through accelerated adiabatic eigenstate evolution to measure all three physical observables. Topological transitions are revealed by the jump of the first Chern number, obtained respectively from the integral of the Berry curvature and of the new polar angle relation, over the whole parameter space. Our strategy paves the way for measuring topological transitions in continuous variable systems.

quant-ph↗

arXiv2024

Scheme for measuring topological transitions in a continuous variable system

We propose a scheme for measuring topological properties in a two-photon-driven Kerr-nonlinear resonator (KNR) subjected to a single-photon modulation. The topological properties are revealed through the observation of the Berry curvature and hence the first Chern number, as a nonadiabatic response of the physical observable to the change rate of the control parameter of the modulated drive. The parameter manifold, constructed from the system's Hamiltonian that determines its dynamics constrained in the state space spanned by the even and odd cat states as two basis states, is adjusted so that the degeneracy crossing the manifold indicates a topological transition. The scheme, with such continuous variable states in mesoscpic systems, provides a new perspective for exploration of the geometry and the related topology with complex systems.

quant-ph↗

arXiv2024

Revolutionizing Battery Disassembly: The Design and Implementation of a Battery Disassembly Autonomous Mobile Manipulator Robot(BEAM-1)

The efficient disassembly of end-of-life electric vehicle batteries(EOL-EVBs) is crucial for green manufacturing and sustainable development. The current pre-programmed disassembly conducted by the Autonomous Mobile Manipulator Robot(AMMR) struggles to meet the disassembly requirements in dynamic environments, complex scenarios, and unstructured processes. In this paper, we propose a Battery Disassembly AMMR(BEAM-1) system based on NeuralSymbolic AI. It detects the environmental state by leveraging a combination of multi-sensors and neural predicates and then translates this information into a quasi-symbolic space. In real-time, it identifies the optimal sequence of action primitives through LLM-heuristic tree search, ensuring high-precision execution of these primitives. Additionally, it employs positional speculative sampling using intuitive networks and achieves the disassembly of various bolt types with a meticulously designed end-effector. Importantly, BEAM-1 is a continuously learning embodied intelligence system capable of subjective reasoning like a human, and possessing intuition. A large number of real scene experiments have proved that it can autonomously perceive, decide, and execute to complete the continuous disassembly of bolts in multiple, multi-category, and complex situations, with a success rate of 98.78%. This research attempts to use NeuroSymbolic AI to give robots real autonomous reasoning, planning, and learning capabilities. BEAM-1 realizes the revolution of battery disassembly. Its framework can be easily ported to any robotic system to realize different application scenarios, which provides a ground-breaking idea for the design and implementation of future embodied intelligent robotic systems.

cs.RO↗

arXiv2024

The Nature of the High-energy Gamma-Ray Radiation Associated with the High-redshift Blazar B3 1343+451

High-redshift blazars are the most powerful extragalactic astrophysical sources ever detected in the high-energy gamma-ray band. In this study, we present a temporal and spectral analysis of the high-redshift blazar B3 1343+451 based on 14 years of Fermi-LAT observations, spanning from 2008 August 4 to 2022 June 6 (MJD 54686-59733). We extract a seven-day binned $γ$-ray light curve in the energy range 0.1--500 GeV and identify seven outburst periods with a peak flux of $>4.32\times10^{-7} \rm ph \cdot cm^{-2} \cdot s^{-1}$. The highest seven day flux (above 100 MeV) reaches $(8.06\pm0.56)\times10^{-7} \rm erg \ cm^{-2} \ s^{-1}$ on MJD = 56,177.16, which is 10 times higher than the flux in the quiescent period. To understand the properties of distant blazar jets, we employ a standard one-zone leptonic scenario and model the multiwavelength spectral energy distributions of one quiescent and seven flaring periods. We find that the $γ$-ray spectrum is better reproduced if we assume that the dissipation region of the jet, $R_{\rm diss}$, is located within the molecular torus, where infrared emission is the dominant external photon field. We infer that the jets in higher-redshift blazars have larger power and kinetic energy, where the kinetic energy is significantly greater than the radiation power, and the jet production efficiency suggests that we need to lower the accretion efficiency. These results imply that B3 1343+451 may have a standard thin disk surrounding its massive black hole, and the jets of B3 1343+451 may not be fully explained by the Blandford--Payne process.

astro-ph.HE↗

arXiv2024

Generative Monoculture in Large Language Models

We introduce {\em generative monoculture}, a behavior observed in large language models (LLMs) characterized by a significant narrowing of model output diversity relative to available training data for a given task: for example, generating only positive book reviews for books with a mixed reception. While in some cases, generative monoculture enhances performance (e.g., LLMs more often produce efficient code), the dangers are exacerbated in others (e.g., LLMs refuse to share diverse opinions). As LLMs are increasingly used in high-impact settings such as education and web search, careful maintenance of LLM output diversity is essential to ensure a variety of facts and perspectives are preserved over time. We experimentally demonstrate the prevalence of generative monoculture through analysis of book review and code generation tasks, and find that simple countermeasures such as altering sampling or prompting strategies are insufficient to mitigate the behavior. Moreover, our results suggest that the root causes of generative monoculture are likely embedded within the LLM's alignment processes, suggesting a need for developing fine-tuning paradigms that preserve or promote diversity.

cs.CL↗

arXiv2024

Experimental observation of spontaneous symmetry breaking in a quantum phase transition

Spontaneous symmetry breaking (SSB) plays a central role in understanding a large variety of phenomena associated with phase transitions, such as superfluid and superconductivity. So far, the transition from a symmetric vacuum to a macroscopically ordered phase has been substantially explored. The process bridging these two distinct phases is critical to understanding how a classical world emerges from a quantum phase transition, but so far remains unexplored in experiment. We here report an experimental demonstration of such a process with a quantum Rabi model engineered with a superconducting circuit. We move the system from the normal phase to the superradiant phase featuring two symmetry-breaking field components, one of which is observed to emerge as the classical reality. The results demonstrate that the environment-induced decoherence plays a critical role in the SSB.

quant-ph↗

arXiv2024

Quantum Geometric Tensor and Critical Metrology in the Anisotropic Dicke Model

We investigate the quantum phase transition in the anisotropic Dicke model through an examination of the quantum geometric tensor of the ground state. In this analysis, two distinct classical limits exhibit their unique anisotropic characteristics. The classical spin limit demonstrates a preference for the rotating-wave coupling, whereas the classical oscillator limit exhibits symmetry in the coupling strength of the bias. The anisotropic features of the classical spin limit persist at finite scales. Furthermore, we observe that the interplay among the anisotropic ratio, spin length, and frequency ratio can collectively enhance the critical behaviors. This critical enhancement without trade-off between these factors provides a flexible method for quantum precision measurement.

quant-ph↗

arXiv2024

Mott insulating phase and coherent-incoherent crossover across magnetic phase transition in 2D antiferromagnetic CrSBr

In two-dimensional van der Waals magnetic materials, the interplay between magnetism and electron correlation can give rise to new ground states and lead to novel transport and optical properties. A fundamental question in these materials is how the electron correlation manifests and interacts with the magnetic orders. In this study, we demonstrate that the recently discovered 2D antiferromagnetic material, CrSBr, is a Mott insulator, through the combined use of resonant and temperature-dependent angle-resolved photoemission spectroscopy techiniques, supplemented by dynamical mean-field theory analysis. Intriguingly, we found that as the system transitions from the antiferromagnetic to the paramagnetic phases, its Mott bands undergo a reconfiguration, and a coherent-incoherent crossover, driven by the dissolution of the magnetic order. Our findings reveal a distinctive evolution of band structure associated with magnetic phase transitions, shedding light on the investigation of intricate interplay between correlation and magnetic orders in strongly correlated van der Waals magnetic materials.

cond-mat.str-el↗

arXiv2024

DSDL: Data Set Description Language for Bridging Modalities and Tasks in AI Data

In the era of artificial intelligence, the diversity of data modalities and annotation formats often renders data unusable directly, requiring understanding and format conversion before it can be used by researchers or developers with different needs. To tackle this problem, this article introduces a framework called Dataset Description Language (DSDL) that aims to simplify dataset processing by providing a unified standard for AI datasets. DSDL adheres to the three basic practical principles of generic, portable, and extensible, using a unified standard to express data of different modalities and structures, facilitating the dissemination of AI data, and easily extending to new modalities and tasks. The standardized specifications of DSDL reduce the workload for users in data dissemination, processing, and usage. To further improve user convenience, we provide predefined DSDL templates for various tasks, convert mainstream datasets to comply with DSDL specifications, and provide comprehensive documentation and DSDL tools. These efforts aim to simplify the use of AI data, thereby improving the efficiency of AI development.

cs.AI↗

arXiv2024

Brightened Optical Transition as Indicator of Multiferroicity in a Layered Antiferromagnet

Two-dimensional van der Waals magnets show strong interconnection between their electrical, magnetic, and structural properties. Here we reveal the emergence of a luminescent transition upon crossing the Néel transition temperature of CrPS$_4$, a layered antiferromagnetic semiconductor. This luminescent transition occurs above the lowest absorption level. We attribute the optical transitions to excited states of the t$_{\rm 2g}$ orbitals of the Cr$^{3+}$ ions, which are influenced by the distortion of the octahedral crystal field. Specifically, we find at the crossing of the Néel temperature changes the distortion from an anti-polar to polar arrangement, thereby not only activating an additional luminescent pathway but also inducing a significant in-plane static dipole moment detected by a marked enhancement in the intensity of the second harmonic generation. Our findings suggest the presence of a multiferroic state in CrPS$_4$ below the Néel temperature.

cond-mat.mtrl-sci↗

arXiv2024

Non-adiabatic holonomic quantum operations in continuous variable systems

Quantum operations by utilizing the underlying geometric phases produced in physical systems are favoured due to its potential robustness. When a system in a non-degenerate eigenstate undergoes an adiabatically cyclic evolution dominated by its Hamiltonian, it will get a geometric phase, referred to as the Berry Phase. While a non-adiabatically cyclic evolution produces an Aharonov-Anandan geometric phase. The two types of Abelian geometric phases are extended to the non-Abelian cases, where the phase factors become matrix-valued and the transformations associated with different loops are non-commutable. Abelian and non-Abelian (holonomic) operations are prevalent in discrete variable systems, whose limited (say, two) energy levels, form the qubit. While their developments in continuous systems have also been investigated, mainly due to that, bosonic modes (in, such as, cat states) with large Hilbert spaces, provide potential advantages in fault-tolerant quantum computation. Here we propose a feasible scheme to realize non-adiabatic holonomic quantum logic operations in continuous variable systems with cat codes. We construct arbitrary single-qubit (two-qubit) gates with the combination of single- and two-photon drivings applied to a Kerr Parametric Oscillator (KPO) (the coupled KPOs). Our scheme relaxes the requirements of the previously proposed quantum geometric operation strategies in continuous variable systems, providing an effective way for quantum control.

quant-ph↗

arXiv2024

Two person non-zero-sum linear-quadratic differential game with Markovian jumps in infinite horizon

This paper investigates an inhomogeneous non-zero-sum linear-quadratic (LQ, for short) differential game problem whose state process and cost functional are regulated by a Markov chain. Under the $L^2$ stabilizability framework, we first provide a sufficient condition to ensure the $L^2$-integrability of the state process and study a class of linear backward stochastic differential equation (BSDE, for short) in infinite horizon. Then, we seriously discuss the LQ problem and show that the closed-loop optimal control is characterized by the solutions to coupled algebra Riccati equations (CAREs, for short) with some stabilizing conditions and a linear BSDE. Based on those results, we further analyze the non-zero-sum stochastic differential game problem and give the closed-loop Nash equilibrium through the solution to a system of two cross-coupled CAREs and two cross-coupled BSDEs. Finally, some related numerical

math.OC↗

arXiv2024

A family of air-stable chalcogenide solid electrolytes in Li$_2$BMQ$_4$ (B = Ca, Sr and Ba; M = Si, Ge and Sn; Q = O, S and Se) systems

Combining high-throughput first-principles calculations and experimental measurements, we have identified a novel family of fast lithium-ion chalcogenide conductors in Li$_2$BMQ$_4$ (2114, B = Ca, Sr and Ba; M = Si, Ge and Sn; Q = O, S and Se) systems. Our calculations demonstrate that most of the thermodynamically and kinetically stable sulfides and selenides in this new system exhibit ultralow Li$^+$ ion migration activation energy (0.16 eV ~ 0.56 eV) and considerable bandgaps varying between ~ 2 eV and 3.5 eV. We have successfully synthesized Li$_2$BaSnS$_4$ and Li$_2$SrSiS$_4$, and they exhibit excellent moisture stability through H$_2$S gas measurements. Electrochemical impedance measurements indicate 2114 systems show the typical features of solid ionic conductors, with a room-temperature Li$^+$ conductivity close to 5$\times$10$^{-4}$ mS/cm aligning with our molecular dynamics simulations. Furthermore, we have theoretically investigated the substitution of Cl$^-$ at S$^{2-}$ site. The doped compounds display significantly higher conductivity, with an increase of about three orders of magnitude (up to a maximum of 0.72 mS/cm) compared to the undoped compounds. These findings offer valuable insights for the further exploration of potential chalcogenide solid electrolyte materials with robust air stability and enhanced ionic conductivity for practical applications in lithium-ion batteries.

cond-mat.mtrl-sci↗

arXiv2024

Privately Aligning Language Models with Reinforcement Learning

Positioned between pre-training and user deployment, aligning large language models (LLMs) through reinforcement learning (RL) has emerged as a prevailing strategy for training instruction following-models such as ChatGPT. In this work, we initiate the study of privacy-preserving alignment of LLMs through Differential Privacy (DP) in conjunction with RL. Following the influential work of Ziegler et al. (2020), we study two dominant paradigms: (i) alignment via RL without human in the loop (e.g., positive review generation) and (ii) alignment via RL from human feedback (RLHF) (e.g., summarization in a human-preferred way). We give a new DP framework to achieve alignment via RL, and prove its correctness. Our experimental results validate the effectiveness of our approach, offering competitive utility while ensuring strong privacy protections.

cs.LG↗

arXiv2024

Trajectory-wise Iterative Reinforcement Learning Framework for Auto-bidding

In online advertising, advertisers participate in ad auctions to acquire ad opportunities, often by utilizing auto-bidding tools provided by demand-side platforms (DSPs). The current auto-bidding algorithms typically employ reinforcement learning (RL). However, due to safety concerns, most RL-based auto-bidding policies are trained in simulation, leading to a performance degradation when deployed in online environments. To narrow this gap, we can deploy multiple auto-bidding agents in parallel to collect a large interaction dataset. Offline RL algorithms can then be utilized to train a new policy. The trained policy can subsequently be deployed for further data collection, resulting in an iterative training framework, which we refer to as iterative offline RL. In this work, we identify the performance bottleneck of this iterative offline RL framework, which originates from the ineffective exploration and exploitation caused by the inherent conservatism of offline RL algorithms. To overcome this bottleneck, we propose Trajectory-wise Exploration and Exploitation (TEE), which introduces a novel data collecting and data utilization method for iterative offline RL from a trajectory perspective. Furthermore, to ensure the safety of online exploration while preserving the dataset quality for TEE, we propose Safe Exploration by Adaptive Action Selection (SEAS). Both offline experiments and real-world experiments on Alibaba display advertising platform demonstrate the effectiveness of our proposed method.

cs.LG↗

arXiv2024

Comparative Efficacy of Commercial Wearables for Circadian Rhythm Home Monitoring from Activity, Heart Rate, and Core Body Temperature

Circadian rhythms govern biological patterns that follow a 24-hour cycle. Dysfunctions in circadian rhythms can contribute to various health problems, such as sleep disorders. Current circadian rhythm assessment methods, often invasive or subjective, limit circadian rhythm monitoring to laboratories. Hence, this study aims to investigate scalable consumer-centric wearables for circadian rhythm monitoring outside traditional laboratories. In a two-week longitudinal study conducted in real-world settings, 36 participants wore an Actigraph, a smartwatch, and a core body temperature sensor to collect activity, temperature, and heart rate data. We evaluated circadian rhythms calculated from commercial wearables by comparing them with circadian rhythm reference measures, i.e., Actigraph activities and chronotype questionnaire scores. The circadian rhythm metric acrophases, determined from commercial wearables using activity, heart rate, and temperature data, significantly correlated with the acrophase derived from Actigraph activities (r=0.96, r=0.87, r=0.79; all p<0.001) and chronotype questionnaire (r=-0.66, r=-0.73, r=-0.61; all p<0.001). The acrophases obtained concurrently from consumer sensors significantly predicted the chronotype (R2=0.64; p<0.001). Our study validates commercial sensors for circadian rhythm assessment, highlighting their potential to support maintaining healthy rhythms and provide scalable and timely health monitoring in real-life scenarios.

eess.SP↗

arXiv2024

Teaching DevOps Security Education with Hands-on Labware: Automated Detection of Security Weakness in Python

The field of DevOps security education necessitates innovative approaches to effectively address the ever-evolving challenges of cybersecurity. In adopting a student-centered ap-proach, there is the need for the design and development of a comprehensive set of hands-on learning modules. In this paper, we introduce hands-on learning modules that enable learners to be familiar with identifying known security weaknesses, based on taint tracking to accurately pinpoint vulnerable code. To cultivate an engaging and motivating learning environment, our hands-on approach includes a pre-lab, hands-on and post lab sections. They all provide introduction to specific DevOps topics and software security problems at hand, followed by practicing with real world code examples having security issues to detect them using tools. The initial evaluation results from a number of courses across multiple schools show that the hands-on modules are enhancing the interests among students on software security and cybersecurity, while preparing them to address DevOps security vulnerabilities.

cs.CR↗