arXiv subjects

Lin Lin

Publications and source records attributed to Lin Lin.

At least 73 records · Page 4Linked to original sources

arXiv2025

High-resolution and ultra-low power nonlinear image processing with passive high-quality factor metasurfaces

Image processing is both one of the most exciting domains for applying artificial intelligence and the most computationally expensive. Nanostructured metasurfaces have opened the door to the ultimate energy saving by directly processing ambient image data via ultra-thin layers before detection. However, a key ingredient of universal computation - nonlinear thresholding functions - have yet to be demonstrated for low intensities without an external power source. Here, we present a passive, all-optical method for nonlinear image processing using Silicon nanoantenna arrays. We experimentally demonstrate an intensity thresholding filter capable of processing one-dimensional images with only Watt-level power. By leveraging the opto-thermal Kerr nonlinearity through high-Q guided mode resonance, we achieve an experimental threshold as low as 0.1 mW/{\mu}m^2 with a spatial resolution of 1.85 {\mu}m. Additional simulations indicate that the threshold can be further reduced while maintaining high spatial selectivity. Analog, pixel-wise, smoothed leaky ReLU activation filters promise to revolutionize image sensing.

physics.optics↗

arXiv2025

The Many-Body Ground State Manifold of Flat Band Interacting Hamiltonian for Magic Angle Twisted Bilayer Graphene

At a magic relative twist angle, magic angle twisted bilayer graphene (MATBG) has an octet of flat bands that can host strong correlation physics when partially filled. A key theoretical discovery in MATBG is the existence of ferromagnetic Slater determinants as exact ground states of the corresponding flat band interacting (FBI) Hamiltonian. The FBI Hamiltonian describes the behavior of electrons that interact with each other in a high-dimensional space, and is constructed from the band structure of the non-interacting Bistritzer--MacDonald model at the chiral limit. A key property of the FBI Hamiltonian for MATBG is that it is frustration free and can be written as a sum of non-commuting terms. In this work, we provide a complete characterization of the ground state manifold of the FBI Hamiltonian, proving that it is precisely the linear span of such ferromagnetic Slater determinants.

math-ph↗

arXiv2025

Rapid quantum ground state preparation via dissipative dynamics

Inspired by natural cooling processes, dissipation has become a promising approach for preparing low-energy states of quantum systems. However, the potential of dissipative protocols remains unclear beyond certain commuting Hamiltonians. This work provides significant analytical and numerical insights into the power of dissipation for preparing the ground state of noncommuting Hamiltonians. For quasi-free dissipative dynamics, including certain 1D spin systems with boundary dissipation, our results reveal a new connection between the mixing time in trace distance and the spectral properties of a non-Hermitian Hamiltonian, leading to an explicit and sharp bound on the mixing time that scales polynomially with system size. For more general spin systems, we develop a tensor network-based algorithm for constructing the Lindblad jump operator and for simulating the dynamics. Using this algorithm, we demonstrate numerically that dissipative ground state preparation protocols can achieve rapid mixing for certain 1D local Hamiltonians under bulk dissipation, with a mixing time that scales logarithmically with the system size. We then prove the rapid mixing result for certain weakly interacting spin and fermionic systems in arbitrary dimensions, extending recent results for high-temperature quantum Gibbs samplers to the zero-temperature regime. Together, these results show that dissipation can be a powerful tool for ground state preparation, with potential applications across condensed matter physics, quantum materials science, and beyond.

quant-ph↗

arXiv2025

New perspectives on Density-Matrix Embedding Theory

Quantum embedding methods enable the study of large, strongly correlated quantum systems by (usually self-consistent) decomposition into computationally manageable subproblems, in the spirit of divide-and-conquer methods. Among these, Density Matrix Embedding Theory (DMET) is an efficient approach that enforces self-consistency at the level of one-particle reduced density matrices (1-RDMs), facilitating applications across diverse quantum systems. However, conventional DMET is constrained by the requirement that the global 1-RDM (low-level descriptor) be an orthogonal projector, limiting flexibility in bath construction and potentially impeding accuracy in strongly correlated regimes. In this work, we introduce a generalized DMET framework in which the low-level descriptor can be an arbitrary 1-RDM and the bath construction is based on optimizing a quantitative criterion related to the maximal disentanglement between different fragments. This yields an alternative yet controllable bath space construction for generic 1-RDMs, lifting a key limitation of conventional DMET. We demonstrate its consistency with conventional DMET in appropriate limits and exploring its implications for bath construction, downfolding (impurity Hamiltonian construction), low-level solvers, and adaptive fragmentation. We expect that this more flexible framework, which leads to several new variants of DMET, can improve the robustness and accuracy of DMET.

cond-mat.str-el↗

arXiv2025

MathMistake Checker: A Comprehensive Demonstration for Step-by-Step Math Problem Mistake Finding by Prompt-Guided LLMs

We propose a novel system, MathMistake Checker, designed to automate step-by-step mistake finding in mathematical problems with lengthy answers through a two-stage process. The system aims to simplify grading, increase efficiency, and enhance learning experiences from a pedagogical perspective. It integrates advanced technologies, including computer vision and the chain-of-thought capabilities of the latest large language models (LLMs). Our system supports open-ended grading without reference answers and promotes personalized learning by providing targeted feedback. We demonstrate its effectiveness across various types of math problems, such as calculation and word problems.

cs.AI↗

arXiv2025

DietGlance: Dietary Monitoring and Personalized Analysis at a Glance with Knowledge-Empowered AI Assistant

Growing awareness of wellness has prompted people to consider whether their dietary patterns align with their health and fitness goals. In response, researchers have introduced various wearable dietary monitoring systems and dietary assessment approaches. However, these solutions are either limited to identifying foods with simple ingredients or insufficient in providing an analysis of individual dietary behaviors with domain-specific knowledge. In this paper, we present DietGlance, a system that automatically monitors dietary behaviors in daily routines and delivers personalized analysis from knowledge sources. DietGlance first detects ingestive episodes from multimodal inputs using eyeglasses, capturing privacy-preserving meal images of various dishes being consumed. Based on the inferred food items and consumed quantities from these images, DietGlance further provides nutritional analysis and personalized dietary suggestions, empowered by the retrieval-augmented generation module on a reliable nutrition library. A short-term user study (N=33) and a four-week longitudinal study (N=16) demonstrate the usability and effectiveness of DietGlance, offering insights and implications for future AI-assisted dietary monitoring and personalized healthcare intervention systems using eyewear.

cs.HC↗

arXiv2025

Worth Their Weight: Randomized and Regularized Block Kaczmarz Algorithms without Preprocessing

Due to the ever growing amounts of data leveraged for machine learning and scientific computing, it is increasingly important to develop algorithms that sample only a small portion of the data at a time. In the case of linear least-squares, the randomized block Kaczmarz method (RBK) is an appealing example of such an algorithm, but its convergence is only understood under sampling distributions that require potentially prohibitively expensive preprocessing steps. To address this limitation, we analyze RBK when the data is sampled uniformly, showing that its iterates converge in a Monte Carlo sense to a $\textit{weighted}$ least-squares solution. Unfortunately, for general problems the bias of the weighted least-squares solution and the variance of the iterates can become arbitrarily large. We show that these quantities can be rigorously controlled by incorporating regularization into the RBK iterations, yielding the regularized algorithm ReBlocK. Numerical experiments including examples arising from natural gradient optimization demonstrate that ReBlocK can outperform both RBK and minibatch stochastic gradient descent for inconsistent problems with rapidly decaying singular values.

cs.LG↗

arXiv2025

Constructing Cell-type Taxonomy by Optimal Transport with Relaxed Marginal Constraints

The rapid emergence of single-cell data has facilitated the study of many different biological conditions at the cellular level. Cluster analysis has been widely applied to identify cell types, capturing the essential patterns of the original data in a much more concise form. One challenge in the cluster analysis of cells is matching clusters extracted from datasets of different origins or conditions. Many existing algorithms cannot recognize new cell types present in only one of the two samples when establishing a correspondence between clusters obtained from two samples. Additionally, when there are more than two samples, it is advantageous to align clusters across all samples simultaneously rather than performing pairwise alignment. Our approach aims to construct a taxonomy for cell clusters across all samples to better annotate these clusters and effectively extract features for downstream analysis. A new system for constructing cell-type taxonomy has been developed by combining the technique of Optimal Transport with Relaxed Marginal Constraints (OT-RMC) and the simultaneous alignment of clusters across multiple samples. OT-RMC allows us to address challenges that arise when the proportions of clusters vary substantially between samples or when some clusters do not appear in all the samples. Experiments on more than twenty datasets demonstrate that the taxonomy constructed by this new system can yield highly accurate annotation of cell types. Additionally, sample-level features extracted based on the taxonomy result in accurate classification of samples.

q-bio.GN↗

arXiv2025

The timing and spectral properties of the 2022 outburst of SGR J1935+2154 observed with NICER

The magnetar SGR J1935+2154 entered a new active episode on October 10, 2022, with X-ray bursts and enhanced persistent emission. At the tail of high burst rate interval, lasting several hours, radio bursts were detected, revealing the connection between the X-ray activities and radio emissions. We analyzed observations of SGR J1935+2154 for nearly three months, using data from Neutron Star Interior Composition Explorer (NICER). We report the timing and spectral results following the onset of this outburst. In general, the X-ray flux of the persistent emission decays exponentially. While a flare is evident on the light curve, a fast radio burst (FRB) was detected immediately following the peak of this flare. We found a phase jump of pulse profile, with a deviation of $0.16\pm0.03$ phase, which is related to the glitch. The spectra are well fit with the combination of a blackbody and a power law model. The decay of the outburst is dominated by the drop of the non-thermal component, which also leads to the increase of thermal proportion. The photon index of the power law is inversely correlated with both the unabsorbed flux and the burst rate. We find that unlike the large variety of the persistent emission around FRB 221014, the X-ray properties are very stable when FRBs 221021 and 221201 happened. These results manifest the connection between glitch, phase jump, X-ray burst, and radio burst, crucial for studying the mutation in twisted magnetic fields and constraining the trigger mechanism of radio bursts.

astro-ph.HE↗

arXiv2024

Metal-strong Inflows at the Outer-galactic-scale of a Quasar

We present an analysis of the absorption-line system in the Very Large Telescope/Ultraviolet and Visual Echelle Spectrograph spectrum at a redshift of $z_{\rm a}={3.1448}$ associated with the quasar SDSS J122040.23+092326.96, whose systematic redshift is $z_{\rm e}=3.1380\pm0.0007$, measured from the ${\rm H}\beta$+[O III] emission lines in our newly acquired NIR P200/TripleSpec data. This absorbing system, detected in numerous absorption lines including the N V, N III, C IV, C III, Si IV, Si III, and H I Lyman series, can be resolved into seven kinematic components with red-shifted velocities ranging from 200 to $900\,\rm km\,s^{-1}$. The high-ionization N V doublet detected and the rather narrow Lyman series measured ($b\approx14\,\rm km\,s^{-1}$) suggest that the absorption gas is photo ionized, possibly by the quasar. A low density is inferred by the fact that N III $\lambda989.80$ is significantly detected while N III* $\lambda991.51$ (${\rm log}\,n_{\rm c}=3.3\,\rm cm^{-3}$) is undetectably weak. A firm lower limit of a solar value to the abundance of the gas can be set based on the measurements of Si IV and H I column densities, as first proposed by F. Hamann. Detailed photoionization simulations indicate that $T1$, and possibly the absorber as a whole, has metallicities of $Z\sim1.5-6.0\,Z\rm\,sun$, and is located at $\sim15\,\rm kpc$ from the quasar nucleus. The metal-strong absorption inflows at the outskirt of the quasar host galaxy is most likely originated in situ and were driven by stellar processes, such as stellar winds and/or supernova explosions. Such a relatively rare system may hold important clues to understanding the baryonic cycling of galaxies, and more cases could be picked out using relatively strong Si IV and weak Lyman absorption lines.

astro-ph.GA↗

arXiv2024

Dosimetry study of high repetition rate MeV electron beam from a continuous-wave photocathode gun

DC-SRF-II gun, a high-brightness continuous-wave photocathode gun, has greater potential in electron beam irradiation applications. This paper presents the in-vacuum and in-air irradiation dosimetry study of the high repetition rate electron beam from the DC-SRF-II gun with both Monte Carlo simulations and experiments. Especially, high-dose uniform irradiations with flexible and accurate tuning of dose rate across orders of magnitude are demonstrated. Good stability and repeatability of the doses are also shown. The ultra-wide tuning range and precise control of irradiation time and dose rate are expected to pave the way for innovative applications across a wide range of fields.

physics.acc-ph↗

arXiv2024

Unified error bounds for perturbations of non-Markovian open quantum systems in Gaussian environments

We present perturbative error bounds for the non-Markovian dynamics of observables in open quantum systems interacting with Gaussian environments, governed by a general Liouville dynamics. This extends the work of [Mascherpa et al., Phys. Rev. Lett. 118, 100401, 2017], which demonstrated qualitatively tighter bounds over the standard Gr\"onwall-type inequality for unitary system-bath evolution. Our results apply to systems with both bosonic and fermionic environments. Our approach utilizes a superoperator formalism, which avoids the need for formal coherent state path integral calculations, or the dilation of Lindblad dynamics into an equivalent unitary framework with infinitely many degrees of freedom. This enables a unified treatment of a wide range of open quantum systems. These findings provide a solid theoretical basis for various recently developed pseudomode methods in simulating open quantum system dynamics.

quant-ph↗

arXiv2024

Laplace transform based quantum eigenvalue transformation via linear combination of Hamiltonian simulation

Eigenvalue transformations, which include solving time-dependent differential equations as a special case, have a wide range of applications in scientific and engineering computation. While quantum algorithms for singular value transformations are well studied, eigenvalue transformations are distinct, especially for non-normal matrices. We propose an efficient quantum algorithm for performing a class of eigenvalue transformations that can be expressed as a certain type of matrix Laplace transformation. This allows us to significantly extend the recently developed linear combination of Hamiltonian simulation (LCHS) method [An, Liu, Lin, Phys. Rev. Lett. 131, 150603, 2023; An, Childs, Lin, arXiv:2312.03916] to represent a wider class of eigenvalue transformations, such as powers of the matrix inverse, $A^{-k}$, and the exponential of the matrix inverse, $e^{-A^{-1}}$. The latter can be interpreted as the solution of a mass-matrix differential equation of the form $A u'(t)=-u(t)$. We demonstrate that our eigenvalue transformation approach can solve this problem without explicitly inverting $A$, reducing the computational complexity.

quant-ph↗

arXiv2024

Quantum Linear System Solvers: A Survey of Algorithms and Applications

Solving linear systems of equations plays a fundamental role in numerous computational problems from different fields of science. The widespread use of numerical methods to solve these systems motivates investigating the feasibility of solving linear systems problems using quantum computers. In this work, we provide a survey of the main advances in quantum linear systems algorithms, together with some applications. We summarize and analyze the main ideas behind some of the algorithms for the quantum linear systems problem in the literature. The analysis begins by examining the Harrow-Hassidim-Lloyd (HHL) solver. We note its limitations and reliance on computationally expensive quantum methods, then highlight subsequent research efforts which aimed to address these limitations and optimize runtime efficiency and precision via various paradigms. We focus in particular on the post-HHL enhancements which have paved the way towards optimal lower bounds with respect to error tolerance and condition number. By doing so, we propose a taxonomy that categorizes these studies. Furthermore, by contextualizing these developments within the broader landscape of quantum computing, we explore the foundational work that have inspired and informed their development, as well as subsequent refinements. Finally, we discuss the potential applications of these algorithms in differential equations, quantum machine learning, and many-body physics.

quant-ph↗

arXiv2024

Dissipative ground state preparation in ab initio electronic structure theory

Dissipative engineering is a powerful tool for quantum state preparation, and has drawn significant attention in quantum algorithms and quantum many-body physics in recent years. In this work, we introduce a novel approach using the Lindblad dynamics to efficiently prepare the ground state for general ab initio electronic structure problems on quantum computers, without variational parameters. These problems often involve Hamiltonians that lack geometric locality or sparsity structures, which we address by proposing two generic types of jump operators for the Lindblad dynamics. Type-I jump operators break the particle number symmetry and should be simulated in the Fock space. Type-II jump operators preserves the particle number symmetry and can be simulated more efficiently in the full configuration interaction space. For both types of jump operators, we prove that in a simplified Hartree-Fock framework, the spectral gap of our Lindbladian is lower bounded by a universal constant. For physical observables such as energy and reduced density matrices, the convergence rate of our Lindblad dynamics with Type-I jump operators remains universal, while the convergence rate with Type-II jump operators only depends on coarse grained information such as the number of orbitals and the number of electrons. To validate our approach, we employ a Monte Carlo trajectory-based algorithm for simulating the Lindblad dynamics for full ab initio Hamiltonians, demonstrating its effectiveness on molecular systems amenable to exact wavefunction treatment.

quant-ph↗

arXiv2024

Radial Profiles of $\Sigma_{\ast}$, $\Sigma_{\rm SFR}$, Gas Metallicity and Their Correlations Across the Galactic Mass-Size Plane

We analyzed the global and resolved properties of approximately 1,240 nearby star-forming galaxies from the MaNGA survey, comparing compact and extended galaxies -- those with smaller and larger radii ($R_{\rm e}$), respectively -- at a fixed stellar mass ($M_{\ast}$). Compact galaxies typically exhibit lower HI gas fractions, higher dust extinction, higher metallicity, greater mass concentration, and lower angular momentum on a global scale. Radial profiles of stellar mass surface density ($\Sigma_{\ast}$) and star formation rate surface density ($\Sigma_{\rm SFR}$), as functions of the effective radius ($R/$$R_{\rm e}$), reveal that compact galaxies display steeper gradients and higher values, resulting in elevated specific star formation rates (sSFR) in their inner regions compared to their outskirts. At a given $\Sigma_{\ast}$, compact galaxies have higher sSFR than extended galaxies, particularly in low-mass galaxies (log($M_{\ast}$/$M_{\odot}$)$\,\leq\,$10$^{10}$). Additionally, their metallicity profiles differ significantly: extended galaxies have steeper metallicity gradients, while compact galaxies exhibit flatter slopes and higher metallicity at a given $R/$$R_{\rm e}$. After accounting for the dependence of metallicity on $M_{\ast}$ and $\Sigma_{\ast}$, no further correlation with SFR is observed. The combination of higher sSFR and potentially higher star formation efficiency in compact galaxies suggests that their central gas is being rapidly consumed, leading to older stellar populations, as indicated by D$_{n}$(4000) and EW(H$\delta_A$), and resulting in faster central growth. Our results reveal that radial SFR profiles cannot be fully determined by $M_{\ast}$ and $\Sigma_{\ast}$ alone; other factors, such as galaxy size or angular momentum, must be considered to fully understand the observed trends.

astro-ph.GA↗

arXiv2024

RAG4ITOps: A Supervised Fine-Tunable and Comprehensive RAG Framework for IT Operations and Maintenance

With the ever-increasing demands on Question Answering (QA) systems for IT operations and maintenance, an efficient and supervised fine-tunable framework is necessary to ensure the data security, private deployment and continuous upgrading. Although Large Language Models (LLMs) have notably improved the open-domain QA's performance, how to efficiently handle enterprise-exclusive corpora and build domain-specific QA systems are still less-studied for industrial applications. In this paper, we propose a general and comprehensive framework based on Retrieval Augmented Generation (RAG) and facilitate the whole business process of establishing QA systems for IT operations and maintenance. In accordance with the prevailing RAG method, our proposed framework, named with RAG4ITOps, composes of two major stages: (1) Models Fine-tuning \& Data Vectorization, and (2) Online QA System Process. At the Stage 1, we leverage a contrastive learning method with two negative sampling strategies to fine-tune the embedding model, and design the instruction templates to fine-tune the LLM with a Retrieval Augmented Fine-Tuning method. At the Stage 2, an efficient process of QA system is built for serving. We collect enterprise-exclusive corpora from the domain of cloud computing, and the extensive experiments show that our method achieves superior results than counterparts on two kinds of QA tasks. Our experiment also provide a case for applying the RAG4ITOps to real-world enterprise-level applications.

cs.AI↗

arXiv2024

Monte Carlo Simulation of Angular Response of GRID Detectors for GRID Mission

The Gamma-Ray Integrated Detectors (GRID) are a space science mission that employs compact gamma-ray detectors mounted on NanoSats in low Earth orbit (LEO) to monitor the transient gamma-ray sky. Owing to the unpredictability of the time and location of gamma-ray bursts (GRBs), obtaining the photon responses of gamma-ray detectors at various incident angles is important for the scientific analysis of GRB data captured by GRID detectors. For this purpose, a dedicated Monte Carlo simulation framework has been developed for GRID detectors. By simulating each GRID detector and the NanoSat carrying it, the spectral energy response, detection efficiency, and other angular responses of each detector for photons with different incident angles and energies can be obtained within this framework. The accuracy of these simulations has been corroborated through on-ground calibration, and the derived angular responses have been successfully applied to the data analysis of recorded GRBs.

astro-ph.IM↗