arXiv subjects

Ming-Chiang Chung

Publications and source records attributed to Ming-Chiang Chung.

At least 19 recordsLinked to original sources

arXiv2026

Multiple Softening Q-vectors Driving a Cascade of CDW Phases in $\mathrm{1T-VSe}_{2}$

Charge density wave (CDW) formation in two-dimensional materials is governed by complex competing lattice instabilities that remain incompletely understood. Here, we investigate the structural evolution of monolayer $\mathrm{1T-VSe}_{2}$ using first-principles electronic and phonon calculations. The pristine phase exhibits several imaginary-frequency phonon modes associated with dominant instability wave vectors $\mathrm{Q}_{CDW}$, which generate the first-generation CDW phases. Subsequent phonon analyses reveal that several of these intermediate structures remain dynamically unstable and undergo further symmetry-lowering distortions into larger superstructures. Through iterative phonon-driven relaxations, we identify multiple transformation pathways that converge toward the same low-energy $2\sqrt{3}\times4$ CDW configuration. Although these pathways originate from distinct intermediate CDW states, they ultimately reach nearly degenerate energetically stable phases, demonstrating that different phonon-driven routes can lead to the same ground-state configuration. The results establish a unified phonon-driven cascade mechanism for hierarchical CDW formation in monolayer $\mathrm{1T-VSe}_{2}$ and provide a systematic framework for understanding competing ordered phases in low-dimensional quantum materials.

cond-mat.mtrl-sci↗

arXiv2025

High-Throughput GW Calculations via Machine Learning

We present a machine learning (ML) framework that predicts $G_0W_0$ quasiparticle energies across molecular dynamics (MD) trajectories with high accuracy and efficiency. Using only DFT-derived mean-field eigenvalues and exchange-correlation potentials, the model is trained on 25\% of MD snapshots and achieves RMSEs below 0.1 eV. It accurately reproduces k-resolved quasiparticle band structures and density of states, even for BN polymorphs excluded from the training data. This approach bypasses the computational bottlenecks of $G_0W_0$ simulations over dynamic configurations, offering a scalable route to excited-state electronic structure simulations with many-body accuracy.

cond-mat.mtrl-sci↗

arXiv2023

Deep Learning of Phase Transitions for Quantum Spin Chains from Correlation Aspects

Using machine learning (ML) to recognize different phases of matter and to infer the entire phase diagram has proven to be an effective tool given a large dataset. In our previous proposals, we have successfully explored phase transitions for topological phases of matter at low dimensions either in a supervised or an unsupervised learning protocol with the assistance of quantum information related quantities. In this work, we adopt our previous ML procedures to study quantum phase transitions of magnetism systems such as the XY and XXZ spin chains by using spin-spin correlation functions as the input data. We find that our proposed approach not only maps out the phase diagrams with accurate phase boundaries, but also indicates some new features that have not observed before. In particular, we define so-called relevant correlation functions to some corresponding phases that can always distinguish between those and their neighbors. Based on the unsupervised learning protocol we proposed [Phys. Rev. B 104, 165108 (2021)], the reduced latent representations of the inputs combined with the clustering algorithm show the connectedness or disconnectedness between neighboring clusters (phases), just corresponding to the continuous or disrupt quantum phase transition, respectively.

cond-mat.stat-mech↗

arXiv2023

Tomography Scan of Charge Density Wave in NbSe2

Charge density wave (CDW) resulted from a small distortion in the lattice is able to create new orders beyond the original lattice. In 2H-NbSe2, one of the layered transition metal dichalcogenides (TMD), the 3x3 charge order appears in two-dimensional (2D) layers. Although CDW is usually described by a sine wave, the spatial distribution within a 2D layer has never been systematically visualized. Here by using scanning tunneling microscopy (STM) and density functional theory (DFT), we have monitored the evolution of 3x3 CDW along c-axis and realized a nearly tomography scan of CDW of the topmost layer. The results show that the strength of 3x3 charge order varies while increasing the tunneling current. The 3x3 charge order is relatively strong at the outermost Se level and decreases while probing in between Se and Nb levels. Interestingly, the 3x3 charge order gets strong again as reaching Nb level but along with a phase shift. We further calculated the orbital charge distributions and found that both CDW intensity modulation and phase shift are strongly correlated with the distribution of Se p orbitals and Nb d orbitals.

physics.app-ph↗

arXiv2022

Revealing the Charge Density Wave caused by Peierls instability in two-dimensional NbSe$_{2}$

The formation of a charge density wave (CDW) in two-dimensional (2D) materials caused by Peierls instability is a controversial topic. This study investigates the extensively debated role of Fermi surface nesting in causing the CDW state in 2H-NbSe$_{2}$ materials. Four NbSe$_{2}$ structures (i.e., normal, stripe, filled, and hollow structures) are identified on the basis of the characteristics in scanning tunneling microscopy images and first-principles simulations. The calculations reveal that the filled phase corresponds to Peierls' description; that is, it exhibits fully opened gaps at the CDW Brillouin zone boundary, resulting in a drop at the Fermi level in the density of states and the scanning tunneling spectroscopy spectra. The electronic susceptibility and phonon instability in the normal phase indicate that the Fermi surface nesting is triggered by two nesting vectors, whereas the involvement of only one nesting vector leads to the stripe phase. This comprehensive study demonstrates that the filled phase of NbSe$_{2}$ can be categorized as a Peierls-instability-induced CDW in 2D systems.

cond-mat.mtrl-sci↗

arXiv2021

Deep learning of topological phase transitions from entanglement aspects for two-dimensional chiral p-wave superconductors

Applying deep learning to investigate topological phase transitions (TPTs) becomes a useful method due to not only its ability to recognize patterns but also its statistical excellency to examine the amount of information carried by different types of data inputs. Among possible data types, entanglement-related quantities, such as Majorana correlation matrices (MCMs), one-particle entanglement spectra (OPES), and entanglement eigenvectors (OPEEs), have been proved effective, however, are to date mostly restricted to one dimension. Here, we propose practical input data forms based on those quantities to study TPTs and to compare the efficiency of each form on classic two-dimensional chiral $p$-wave superconductors via the deep learning approach. First, we find that different input forms, either matrices or tensors both originated from real MCMs, can affect the precise locations of the predicted transition points. Next, due to the complex nature of OPEEs, we extract three spatially dependent quantities from OPEEs, one related to the "intensity", and the other two related to "phases" of particle and hole components. We show that similar to taking OPES directly as inputs, solely using "intensity" quantity can only distinguish topological phases from trivial ones, whereas using either whole MCMs or complete OPEE-extracted quantities can provide sufficient information for deep learning to distinguish between phases of matter with different $U(1)$ gauges or Chern numbers. Finally, we discuss certain characteristic features in the deep learning approach and, in particular, they reveal that our trained models indeed learn physically meaningful features, which confirms the potential use even at high dimensions.

cond-mat.supr-con↗

arXiv2021

Deep learning of topological phase transitions from entanglement aspects: An unsupervised way

Machine learning techniques have been shown to be effective to recognize different phases of matter and produce phase diagrams in the parameter space interested, while they usually require prior labeled data to perform well. Here, we propose a machine learning procedure, mainly in an unsupervised manner, which can first identify topological/non-topological phases and then refine the locations of phase boundaries. By following this proposed procedure, we expand our previous work on the one-dimensional $p$-wave superconductor [Phys. Rev. B 102, 054512 (2020)] and further on the Su-Schrieffer-Heeger model, with an emphasis on using the quantum entanglement-based quantities as the input features. We find that our method not only reproduces similar results to the previous work with sharp phase boundaries but importantly it also does not rely on prior knowledge of the phase space, e.g., the number of phases present. We conclude with a few remarks about its potential, limitations, and explainabilities.

cond-mat.supr-con↗

arXiv2019

Deep learning of topological phase transitions from entanglement aspects

The one-dimensional $p$-wave superconductor proposed by Kitaev has long been a classic example for understanding topological phase transitions through various methods, such as examining Berry phase, edge states of open chains and, in particular, aspects from quantum entanglement of ground states. In order to understand the amount of information carried in the entanglement-related quantities, here we study topological phase transitions of the model with emphasis of using the deep learning approach. We feed different quantities, including Majorana correlation matrices (MCMs), entanglement spectra (ES) or entanglement eigenvectors (EE) originated from Block correlation matrices (BCMs), into the deep neural networks for training, and investigate which one could be the most useful input format in this approach. We find that ES is indeed too compressed information compared to MCM or EE. MCM and EE can provide us abundant information to recognize not only the topological phase transitions in the model but also phases of matter with different $U$(1) gauges, which is not reachable by using ES only.

cond-mat.stat-mech↗

arXiv2017

Relaxation of the entanglement spectrum in quench dynamics of topological systems

We study how the entanglement spectrum relaxes to its steady state in one-dimensional quadratic systems after a quantum quench. In particular we apply the saddle point expansion to the dimerized chains and 1-D p-wave superconductors. We find that the entanglement spectrum always exhibits a power-law relaxation superimposed with oscillations at certain characteristic angular frequencies. For the dimerized chains, we find that the exponent $ν$ of the power-law decay is always $3/2$. For 1-D p-wave superconductors, however, we find that depending on the initial and final Hamiltonian, the exponent $ν$ can take value from a limited list of values. The smallest possible value is $ν=1/2$, which leads to a very slow convergence to its steady state value.

cond-mat.mes-hall↗

arXiv2015

Damping of Confined Excitations Modes of 1D Condensates in an Optical Lattice

We study the damping of the collective excitations of Bose-Einstein condensates in a harmonic trap potential loaded in an optical lattice. In the presence of a confining potential the system is non-homogeneous and the collective excitations are characterized by a set of discrete confined phonon-like excitations. We derive a general convenient analytical description for the damping rate, which takes into account, the trapping potential and the optical lattice, for the Landau and Beliaev processes at any temperature, $T$. At high temperature or weak spatial confinement, we show that both mechanisms display linear dependence on $T$. In the quantum limit, we found that the Landau damping is exponentially suppressed at low temperatures and the total damping is independent of $T$. Our theoretical predictions for the damping rate under thermal regime is in completely correspondence with the experimental values reported for 1D condensate of sodium atoms. We show that the laser intensity can tune the collision process, allowing a \textit{resonant effect} for the condensate lifetime. Also, we study the influence of the attractive or repulsive non-linear terms on the decay rate of the collective excitations. A general expression of the renormalized Goldstone frequency has been obtained as a function of the 1D non-linear self-interaction parameter, laser intensity and temperature.

cond-mat.quant-gas↗

arXiv2015

Entanglement in composite free-fermion systems

We consider fermionic chains where the two halves are either metals with different bandwidths or a metal and an insulator. Both are coupled together by a special bond. We study the ground-state entanglement entropy between the two pieces, its dependence on the parameters and its asymptotic form. We also discuss the features of the entanglement Hamiltonians in both subsystems and the evolution of the entanglement entropy after joining the two parts of the system.

cond-mat.stat-mech↗

arXiv2015

Network topology transition at criticality

Many-body systems when continuous phase transition occurs are mainly built in the interrelationship between particles, implemented through many-body correlations. Some of them may exhibit so-called topological order hardly measured by experiments. Therefore we need, beyond mean-field theory, the complex-systems approach that stresses the systemic complexity of many-body network at criticality. According to our previous study, network space experiences the homogeneous-heterogeneous transition invisible in traditional phase transitions. The network robustness can be a useful indicator to capture the critical phenomena of phase transitions with/without symmetry breaking. In this work, we demonstrate the idea of the change of robust networks is successfully applied to the well-known 1D quantum and 2D classical XY models.

cond-mat.stat-mech↗

arXiv2015

Extracting entangled qubits from Majorana fermions in quantum dot chains through the measurement of parity

We propose a scheme for extracting entangled charge qubits from quantum-dot chains that support zero-energy edge modes. The edge mode is composed of Majorana fermions localized at the ends of each chain. The qubit, logically encoded in double quantum dots, can be manipulated through tunneling and pairing interactions between them. The detailed form of the entangled state depends on both the parity measurement (an even or odd number) of the boundary-site electrons in each chain and the teleportation between the chains. The parity measurement is realized through the dispersive coupling of coherent-state microwave photons to the boundary sites, while the teleportation is performed via Bell measurements. Our scheme illustrates \emph{localizable entanglement} in a fermionic system, which serves feasibly as a quantum repeater under realistic experimental conditions, as it allows for finite temperature effect and is robust against disorders, decoherence and quasi-particle poisoning.

cond-mat.mes-hall↗

arXiv2015

Breakdown of local convertibility through Majorana modes in a quantum quench

The local convertibility of quantum states, measured by the Rényi entropy, is concerned with whether or not a state can be transformed into another state, using only local operations and classical communications. We found that in the one-dimensional Kitaev chain with quenched chemical potential $μ$, the convertibility between the state for $μ$ and that for $μ+δμ$, depends on the quantum phases of the system ($δμ$ is a perturbation). This is similar to the adiabatic case where the ground state is considered. Specifically, when the quenched system has edge modes and the subsystem size for the partition is much larger than the correlation length of the Majorana fermions which forms the edge modes, the quenched state is locally inconvertible. We give a physical interpretation for the result, based on analyzing the interactions between the two subsystems for various partitions. Our work should help to better understand the many-body phenomena in topological systems and also the entanglement properties in the Majorana fermionic quantum computation.

cond-mat.mes-hall↗

arXiv2015

Quantum Critical Spin-2 Chain with Emergent SU(3) Symmetry

We study the quantum critical phase of a SU(2) symmetric spin-2 chain obtained from spin-2 bosons in a one-dimensional lattice. We obtain the scaling of the entanglement entropy and finite-size energies by exact diagonalization and density-matrix renormalization group methods. From the numerical results of the energy spectrum, central charge, and scaling dimension we identify the conformal field theory describing the whole critical phase to be the SU(3)$_1$ Wess-Zumino-Witten model. We find that while in the whole critical phase the Hamiltonian is only SU(2) invariant, there is an emergent SU(3) symmetry in the thermodynamic limit.

cond-mat.str-el↗

arXiv2014

Network topology: detecting topological phase transitions in the Kitaev chain and the rotor plane

We propose a novel network measure of topological invariants, called small-worldness, for identifying topological phase transitions of quantum and classical spin models. Small-worldness is usually defined in the study of social networks based on the best known discovery that one can find a short chain of acquaintances connecting almost any two people on the planet. Here we demonstrate that the small-world effect provides a useful description to distinguish topologically trivial and non-trivial phases in the Kitaev chain and accurately capture the Kosterlitz-Thouless transition in the rotor plane. Our results further suggest that the small-worldness containing both locality and non-locality of the network topology can be a practical approach to extract characteristic quantities of topological states of matter.

cond-mat.stat-mech↗

arXiv2014

A Memory of Majorana Fermions through Quantum Quench

We study the sudden quench of a one-dimensional p-wave superconductor through its topological signature in the entanglement spectrum. The long-time evolution of the system and its topological characterization depend on a pseudomagnetic field ${\bs R}_{\mbox{\text eff}}(k)$, which connects both the initial and the final Hamiltonians, hence exhibiting a memory effect. In particular, we explore the robustness of the Majorana zero-mode associated with the entanglement cut in the topologically nontrivial phase and identify the parameter space in which the mode can survive in the infinite-time limit.

cond-mat.mes-hall↗

arXiv2013

Entanglement entropy scaling of the XXZ chain

We study the entanglement entropy scaling of the XXZ chain. While in the critical XY phase of the XXZ chain the entanglement entropy scales logarithmically with a coefficient that is determined by the associated conformal field theory, at the ferromagnetic point, however, the system is not conformally invariant yet the entanglement entropy still scales logarithmically albeit with a different coefficient. We investigate how such an nontrivial scaling at the ferromagnetic point influences the estimation of the central charge $c$ in the critical XY phase. In particular we use the entanglement scaling of the finite or infinite system, as well as the finite-size scaling of the ground state energy to estimate the value of $c$. In addition, the spin-wave velocity and the scaling dimension are also estimated. We show that in all methods the evaluations are influenced by the nearby ferromagnetic point and result in crossover behavior. Finally we discuss how to determine whether the central charge estimation is strongly influenced by the crossover behavior and how to properly evaluate the central charge.

cond-mat.str-el↗