arXiv subjects

Fa Wang

Publications and source records attributed to Fa Wang.

At least 19 recordsLinked to original sources

arXiv2026

Spectroscopic evidence of disorder-induced quantum phase transitions in monolayer Fe(Te,Se) superconductor

The superconductor-insulator transition as a paradigm of quantum phase transitions has attracted tremendous interest over the past three decades. While the magnetic field and carrier density can be tuned to drive the transition, the role of disorder in the transition is not well understood due to the complicated interplay between superconductivity and electron localization. In this work, we controllably introduce disorder in a two-dimensional high-temperature superconductor by depositing iron clusters onto the superconducting monolayer Fe(Te,Se) crystalline film. The spectral evolution from superconducting gaps to insulating gaps with increasing disorder is detected by scanning tunneling spectroscopy measurements. When the disorder is strong, large U-shaped gaps are observed and attributed to the localization-enhanced Cooper pair correlation. Our observations provide the insight into the emergent phases of low-dimensional and high-temperature superconductors with disorder.

cond-mat.supr-con↗

arXiv2026

Learning Rate Engineering: From Coarse Single Parameter to Layered Evolution

Learning rate scheduling has evolved from the single global fixed rate of early SGD to sophisticated layer-wise adaptive strategies. We systematize this evolution into five generations: (Gen1) global fixed learning rates, (Gen2) global scheduling, (Gen3) parameter-level adaptation, (Gen4) layer-level differentiation, and (Gen5) joint layer-time scheduling. We trace the fundamental motivation behind each transition, showing how the shift from one-size-fits-all to tailoring by layer and time addresses the impossible trinity of transfer learning: lower layers require small updates to preserve general knowledge while higher layers need large updates to adapt to new tasks. Building on this taxonomy, we propose Discriminative Adaptive Layer Scaling (DALS), a unified framework that integrates phase-adaptive cosine scheduling, depth-aware Grokfast gradient filtering, and LARS-style trust ratios into a single coherent optimizer. We benchmark 18 strategies including three DALS variants across all five generations on five datasets: synthetic, CIFAR-10 (from scratch), RTE, TREC-6, and IMDb (fine-tuning). On synthetic, DALS achieves the best accuracy at 98.0%, while DALS-Fast reaches 90% in just 3 epochs. The cross-dataset analysis reveals striking regime-dependent patterns -- no single strategy wins across all regimes. Critically, STLR+Discriminative, the ULMFiT champion, catastrophically fails on from-scratch tasks (43.6% on TREC-6 from scratch vs. 96.8% with RAdam), confirming that directional decay biases are harmful without pretrained features. DALS avoids either extreme, achieving the best synthetic result while maintaining competitive fine-tuning performance.

cs.AI↗

arXiv2026

Projected Holstein-Primakoff boson representation of quantum spins for spin wave theory

The Holstein-Primakoff boson representation of quantum spins and associated large-$S$ expansion have been the standard framework for describing the spin wave excitations in magnetically order phases of quantum spin systems. However, we will show that the omission of projection operators and normal-ordering in this representation can produce incorrect magnon hamiltonians for finite $S$. We will present the exact normal-ordered forms of the finite-$S$ projection operators and projected Holstein-Primakoff boson representations of spin and quadrupole operators, which can produce exact two-magnon interaction terms under ferromagnetic or fully polarized states. We will also discuss the difficulties of applying this projected representation to antiferromagnetic spin wave theory.

cond-mat.str-el↗

arXiv2025

Field-induced spin continuum in twin-free Na$_3$Co$_2$SbO$_6$ revealed by magneto-THz spectroscopy

The honeycomb magnet Na$_3$Co$_2$SbO$_6$ recently emerged as a promising candidate for realizing Kitaev quantum spin liquid with relatively low levels of structural disorder. While the precise spin Hamiltonian remains controversial, the potential existence of a quantum spin liquid or other novel quantum magnetic phases continues to stimulate investigation. Here, we study the temperature and magnetic field-dependent spin excitations of Na$_3$Co$_2$SbO$_6$ on a twin-free single crystal using magneto-terahertz (THz) spectroscopy, focusing on magnetic anisotropy and field-induced unusual phases. We observe a low-energy continuum excitation above $T_N$ and a 0.5 THz (2 meV) spin wave excitation in magnetic order under zero field. Upon applying an in-plane magnetic field, the spin waves transform to a magnetic continuum over an intermediate field range, above which the system enters a spin-polarized state. Crucially, the spin excitation spectra reveal striking anisotropy between the $\textbf{a}$ and $\textbf{b}$ crystallographic axes, demanding description by a strongly anisotropic spin model. These findings establish Na$_3$Co$_2$SbO$_6$ as a model system for investigating field-tunable quantum magnetism and potential spin liquid behavior in highly anisotropic systems.

cond-mat.str-el↗

arXiv2025

Optimization and Application of Cloud-based Deep Learning Architecture for Multi-Source Data Prediction

This study develops a cloud-based deep learning system for early prediction of diabetes, leveraging the distributed computing capabilities of the AWS cloud platform and deep learning technologies to achieve efficient and accurate risk assessment. The system utilizes EC2 p3.8xlarge GPU instances to accelerate model training, reducing training time by 93.2% while maintaining a prediction accuracy of 94.2%. With an automated data processing and model training pipeline built using Apache Airflow, the system can complete end-to-end updates within 18.7 hours. In clinical applications, the system demonstrates a prediction accuracy of 89.8%, sensitivity of 92.3%, and specificity of 95.1%. Early interventions based on predictions lead to a 37.5% reduction in diabetes incidence among the target population. The system's high performance and scalability provide strong support for large-scale diabetes prevention and management, showcasing significant public health value.

cs.DC↗

arXiv2024

Quantum Griffiths singularity in a three-dimensional superconductor to Anderson critical insulator transition

Disorder is ubiquitous in real materials and can have dramatic effects on quantum phase transitions. Originating from the disorder enhanced quantum fluctuation, quantum Griffiths singularity (QGS) has been revealed as a universal phenomenon in quantum criticality of low-dimensional superconductors. However, due to the weak fluctuation effect, QGS is very challenging to detect experimentally in three-dimensional (3D) superconducting systems. Here we report the discovery of QGS associated with the quantum phase transition from 3D superconductor to Anderson critical insulator in a spinel oxide MgTi2O4 (MTO). Under both perpendicular and parallel magnetic field, the dynamical critical exponent diverges when approaching the quantum critical point, demonstrating the existence of 3D QGS. Among 3D superconductors, MTO shows a relatively strong fluctuation effect featured as a wide superconducting transition region. The enhanced fluctuation, which may arise from the mobility edge of Anderson localization, finally leads to the occurrence of 3D quantum phase transition and QGS. Our findings offer a new perspective to understand quantum phase transitions in strongly disordered 3D systems.

cond-mat.supr-con↗

arXiv2024

Schwinger boson symmetric spin liquids of Shastry-Sutherland model

Motivated by recent experimental and numerical evidences of deconfined quantum critical point and quantum spin-liquid states in spin-$1/2$ Heisenberg model on Shastry-Sutherland lattice, we studied possible symmetric spin liquid states and their proximate ordered states under Schwinger boson formalism. We found a symmetric gapped $Z_2$ spin-liquid state for intermediate model parameter $0.66 < J_1/J_2 < 0.71$ under mean-field approximation. The Schwinger boson mean-field picture is partially supported by exact-diagonalization and self-consistent spin wave theory results.

cond-mat.str-el↗

arXiv2024

Magnetism and superconductivity in the $t-J$ model of $La_3Ni_2O_7$ under multiband Gutzwiller approximation

The recent discovery of possible high temperature superconductivity in single crystals of $La_3Ni_2O_7$ under pressure renews the interest in research on nickelates. The DFT calculations reveal that both $d_{z^2}$ and $d_{x^2-y^2}$ orbitals are active, which suggests a minimal two-orbital model to capture the low-energy physics of this system. In this work, we study a bilayer two-orbital $t-J$ model within multiband Gutzwiller approximation, and discuss the magnetism as well as the superconductivity over a wide range of the hole doping. Owing to the inter-orbital super-exchange process between $d_{z^2}$ and $d_{x^2-y^2}$ orbitals, the induced ferromagnetic coupling within layers competes with the conventional antiferromagnetic coupling, and leads to complicated hole doping dependence for the magnetic properties in the system. With increasing hole doping, the system transfers to A-AFM state from the starting G-AFM state. We also find the inter-layer superconducting pairing of $d_{x^2-y^2}$ orbitals dominates due to the large hopping parameter of $d_{z^2}$ along the vertical inter-layer bonds and significant Hund's coupling between $d_{z^2}$ and $d_{x^2-y^2}$ orbitals. Meanwhile, the G-AFM state and superconductivity state can coexist in the low hole doping regime. To take account of the pressure, we also analyze the impacts of inter-layer hopping amplitude on the system properties.

cond-mat.supr-con↗

arXiv2023

Estimation and Inference for High Dimensional Factor Model with Regime Switching

This paper proposes maximum (quasi)likelihood estimation for high dimensional factor models with regime switching in the loadings. The model parameters are estimated jointly by the EM (expectation maximization) algorithm, which in the current context only requires iteratively calculating regime probabilities and principal components of the weighted sample covariance matrix. When regime dynamics are taken into account, smoothed regime probabilities are calculated using a recursive algorithm. Consistency, convergence rates and limit distributions of the estimated loadings and the estimated factors are established under weak cross-sectional and temporal dependence as well as heteroscedasticity. It is worth noting that due to high dimension, regime switching can be identified consistently after the switching point with only one observation. Simulation results show good performance of the proposed method. An application to the FRED-MD dataset illustrates the potential of the proposed method for detection of business cycle turning points.

econ.EM↗

arXiv2023

Optical response and nonlinear Hall response of twisted bilayer graphene in the insulating state

In this work, we calculate the optical response and the nonlinear Hall response of twisted bilayer graphene (TBG) in the insulating states. Different insulating states, including spin-valley polarized (SPVP) state, spin-polarized quantum Hall(SPQH) state, spin-polarized valley Hall (SPVH) state, and spin polarized Kramers-intervalley coherence (SPKIVC) state, are considered. We calculate the optical conductivity ($σ_{xx}$) of these four states and we find that the spin-valley polarized state shows a two-peak feature which is different from the other three states. In order to distinguish the other three states, we calculate the nonlinear Hall response which is proportional to Berry curvature dipole, and we find the chemical potential dependence of the Berry curvature dipole can distinguish these three states. Our result can be tested in the spectroscopy and transport experiments and may be helpful to determine the nature of insulating state in TBG.

cond-mat.mes-hall↗

arXiv2023

Neural Network Analytic Continuation for Monte Carlo: Improvement by Statistical Errors

This study explores the use of neural network-based analytic continuation to extract spectra from Monte Carlo data. We apply this technique to both synthetic and Monte Carlo-generated data. The training sets for neural networks are carefully synthesized without ``data leakage". We found that the training set should match the input correlation functions in terms of statistical error properties, such as noise level, noise dependence on imaginary time, and imaginary time-displaced correlations. We have developed a systematic method to synthesize such training datasets. Our improved algorithm outperform the widely used maximum entropy method in highly noisy situations. As an example, our method successfully extracted the dynamic structure factor of the spin-1/2 Heisenberg chain from quantum Monte Carlo simulations.

cond-mat.dis-nn↗

arXiv2021

Rare earth engineering in RMn$_6$Sn$_6$ topological kagome magnets

Exploration of the topological quantum materials with electron correlation is at the frontier of physics, as the strong interaction may give rise to new topological phases and transitions. Here we report that a family of kagome magnets RMn$_6$Sn$_6$ manifest the quantum transport properties analogical to those in the quantum-limit Chern magnet TbMn$_6$Sn$_6$. The topological transport in the family, including quantum oscillations with nontrivial Berry phase and large anomalous Hall effect arising from Berry curvature field, points to the existence of massive Dirac fermions. Our observation demonstrates a close relationship between rare-earth magnetism and topological electron structure, indicating the rare-earth elements can effectively engineer the Chern quantum phase in kagome magnets.

cond-mat.mtrl-sci↗

arXiv2021

A comparison of eigenvalue-based algorithms and the generalized Lanczos trust-region algorithm for Solving the trust-region subproblem

Solving the trust-region subproblem (TRS) plays a key role in numerical optimization and many other applications. Based on a fundamental result that the solution of TRS of size $n$ is mathematically equivalent to finding the rightmost eigenpair of a certain matrix pair of size $2n$, eigenvalue-based methods are promising due to their simplicity. For $n$ large, the implicitly restarted Arnoldi (IRA) and refined Arnoldi (IRRA) algorithms are well suited for this eigenproblem. For a reasonable comparison of overall efficiency of the algorithms for solving TRS directly and eigenvalue-based algorithms, a vital premise is that the two kinds of algorithms must compute the approximate solutions of TRS with (almost) the same accuracy, but such premise has been ignored in the literature. To this end, we establish close relationships between the two kinds of residual norms, so that, given a stopping tolerance for IRA and IRRA, we are able to determine a reliable one that GLTR should use so as to ensure that GLTR and IRA, IRRA deliver the converged approximate solutions with similar accuracy. We also make a convergence analysis on the residual norms by the Generalized Lanczos Trust-Region (GLTR) algorithm for solving TRS directly, the Arnoldi method and the refined Arnoldi method for the equivalent eigenproblem. A number of numerical experiments are reported to illustrate that IRA and IRRA are competitive with GLTR and IRRA outperforms IRA.

math.NA↗

arXiv2020

Classification and Distinction of Possible Insulating Phases in Twisted Bilayer Graphene by Impurity Effects

In this work the effects of impurity in various insulating phases of the twisted bilayer graphene (TBG) are studied. The well-accepted continuum model\cite{b} is employed and the local density of states (DOS) is calculated. It is found that insulating phases breaking different symmetries proposed in previous theories\cite{pa,op1,Lee_2019} are distinguishable via the number and properties of in-gap bound state peaks induced by impurities in local DOS. Insulating phases breaking the same previously proposed symmetries can be further classified by the remaining anti-unitary symmetries and distinguished by the corresponding remaining Kramers degeneracy of bound states. The in-gap bound state peaks in local DOS and the degeneracy of the bound states can in principle be detected in scanning tunnelling microscopy (STM) experiments, and thus can help to the distinction of various insulating phases.

cond-mat.mes-hall↗

arXiv2020

Nodeless $s$-Wave Superconducting Phases in Cuprates with Ba$_2$CuO$_3$-Type Structure

In this work zero-temperature phase diagrams of cuprates with Ba$_2$CuO$_3$-type CuO chain structure is investigated. The projective symmetry group analysis is employed in the strong coupling limit, and renormalization group with bosonization analysis is employed in the weak coupling limit. We find that in both of these two limits, large areas of the phase diagrams are filled with nodeless $s$-wave superconducting phases (with weak $d$-wave components), instead of pure $d$-wave phase mostly found in cuprates. This implies that nodeless $s$-wave phase is the dominant superconducting phase in cuprates with Ba$_2$CuO$_3$-type CuO chain structure in low temperature. Other phases are also found, including $(s+d)$-wave superconducting phases and Luttinger liquid phases.

cond-mat.str-el↗

arXiv2020

Effects of Defects in Superconducting Phase of Twisted Bilayer Graphene

In this work the effects of defects in the superconducting phases of the twisted bilayer graphene (TBG) are investigated. A will-accepted low energy effective model and a non-magnetic impurity potential to mimic defects are employed. Different superconducting pairing symmetries, including $s$-wave, $(d+id)$-wave and $(p+ip)$-wave pairing, are considered. In single impurity case, the local density of states (DOS) are calculated for the pairing symmetries above. For different pairing symmetries the number and property of bound states induced by defects are different. In multi-impurity case, the phase diagrams are calculated in terms of effective gap and the strength and density of impurities. In unconventional superconducting phases, namely $(p+ip)$-wave and $(d+id)$-wave phases, superconductivity will be destroyed by impurities with strong strength or concentration. These results can in principle be detected in scanning tunnelling microscopy (STM) experiments, and therefore the pairing symmetry, at least whether the superconductivity is conventional or unconventional, may be determined.

cond-mat.supr-con↗

arXiv2020

Possible Quantum Paraelectric State in Kitaev Spin Liquid Candidate H$_{3}$LiIr$_{2}$O$_{6}$

A new quantum spin liquid (QSL) candidate material H$_{3}$LiIr$_{2}$O$_{6}$ was synthesized recently and was found not to show any magnetic order or phase transition down to low temperatures. In this work, we study the quantum dynamics of the hydrogen ions, i.e., protons, in this material by combining first-principles calculations and theoretical analysis. We show that each proton and its adjacent oxygen ions form an electric dipole. The dipole interactions and the proton tunneling are captured by a transverse-field Ising model with a quantum disordered paraelectric ground state. The dipole excitations have an energy gap $Δ_{\mathrm{d}}\simeq 60$ meV, and can be probed by the infrared optical spectroscopy and the dielectric response. We argue that the electric dipole fluctuations renormalize the magnetic interactions in H$_{3}$LiIr$_{2}$O$_{6}$ and lead to a Kitaev QSL state.

cond-mat.str-el↗

arXiv2020

Electronic nematicity in FeSe: a first-principles perspective

Electronic nematicity is an important order in most iron-based superconductors, and FeSe represents a unique example, in which nematicity disentangles from spin ordering. It is commonly perceived that this property arises from strong electronic correlation, which can not be properly captured by density functional theory (DFT). Here, we show that by properly considering the paramagnetic condition and carefully searching the energy landscape with symmetry-preconditioned wavefunctions, two nematic solutions stand out at either the DFT+$U$ or hybrid functional level, both of which are lower in energy than the symmetric solution. The ground-state band structure and Fermi surface can be well compared with the recent experimental results. Symmetry analysis assigns these two new solutions to the $B_{1g}$ and $E_u$ irreducible representations of the D$_{4h}$ point group. While the $B_{1g}$ Ising nematicity has been widely discussed in the context of vestigial stripe antiferromagnetic order, the two-component $E_u$ vector nematicity is beyond previous theoretical discussion. Distinct from the $B_{1g}$ order, the $E_u$ order features mixing of the Fe $d$-orbitals and inversion symmetry breaking, which lead to striking experimental consequences, e.g. missing of an electron pocket.

cond-mat.str-el↗