arXiv subjects

Qinghong Yang

Publications and source records attributed to Qinghong Yang.

13 recordsLinked to original sources

arXiv2026

Supercurrent Growth in Nonequilibrium Superconductors

In ultrafast experiments on superconductors, a pump laser pulse often heats up the electronic system and suppresses the density of superfluid electrons. Subsequently, the electrons undergo a cooling process because of electron-phonon thermalization so that the superfluid density recovers in time. We study the nonequilibrium electromagnetic response of the system in this cooling process. We show that if a supercurrent is initiated by a probe electric field pulse, an intriguing phenomenon of `supercurrent growth' occurs, meaning that the net current grows in time with the increasing superfluid density. Using the Boltzmann kinetic equation, we uncover its microscopic origin as the momentum-relaxing scattering of Bogoliubov quasiparticles by impurities and phonons, in stark contrast to the widely accepted intuition that impurities always attenuate currents. We further show that supercurrent growth has important experimental manifestations, including the ultrafast Meissner effect and an optical reflectivity exceeding unity.

cond-mat.supr-con↗

arXiv2025

Distinguishing quantum dynamics via Markovianity and Non-Markovianity

To study various quantum dynamics, it is important to develop effective methods to detect and distinguish different quantum dynamics. A common non-demolition approach is to couple an auxiliary system (ancilla) to the target system, and to measure the ancilla only. By doing so, the target system becomes an environment for the ancilla. Thus, different quantum dynamics of target systems will correspond to different environment properties. Here, we analytically study XX spin chains presenting different kinds of quantum dynamics, namely localized, delocalized, and dephasing dynamics, and build connections between Markovianity and non-Markovianity-the two most common properties of an environment. For a qubit coupled to the XX chain, we derived the reduced density matrix of the qubit through the projection method. Furthermore, when dephasing noise was introduced to the XX chain, we generalized the projection method by introducing an open-system interaction picture - a modification of the Dirac interaction picture. By calculating the reduced density matrix for the qubit analytically and numerically, we found that the delocalized (localized) chain corresponds to the Markovian (non-Markovian) bath when boundary effects are not considered, and the feature of the chain with dephasing noise as a bath is dependent on the dephasing strength. The three kinds of quantum dynamics can be distinguished by measuring the qubit only.

quant-ph↗

arXiv2024

Enhanced localization in the prethermal regime of continuously measured many-body localized systems

Many-body localized systems exhibit a unique characteristic of avoiding thermalization, primarily attributed to the presence of a local disorder potential in the Hamiltonian. In recent years there has been an interest in simulating these systems on quantum devices. However, actual quantum devices are subject to unavoidable decoherence that can be modeled as coupling to a bath or continuous measurements. The quantum Zeno effect is also known to inhibit thermalization in a quantum system, where repeated measurements suppress transport. In this work we study the interplay of many-body localization and the many-body quantum Zeno effect. In a prethermal regime, we find that signatures of many-body localization are enhanced when the system is coupled to a bath that contains measurements of local fermion population, subject to the appropriate choice of system and bath parameters.

cond-mat.dis-nn↗

arXiv2023

Work Statistics and Adiabatic Assumption in Nonequilibrium Many-Body Theory

Keldysh field theory, based on adiabatic assumptions, serves as an widely used framework for addressing nonequilibrium many-body systems. Nonetheless, the validity of such adiabatic assumptions when addressing interacting Gibbs states remains a topic of contention. We use the knowledge of work statistics developed in nonequilibrium thermodynamics to study this problem. Consequently, we deduce a universal theorem delineating the characteristics of evolutions that transition an initial Gibbs state to another. Based on this theorem, we analytically ascertain that adiabatic evolutions fail to transition a non-interacting Gibbs state to its interacting counterpart. However, this adiabatic approach remains a superior approximation relative to its non-adiabatic counterpart. Numerics verifying our theory and predictions are also provided. Furthermore, our findings render insights into the preparation of Gibbs states within the domain of quantum computation.

quant-ph↗

arXiv2023

Keldysh Nonlinear Sigma Model for a Free-Fermion Gas under Continuous Measurements

Quantum entanglement phase transitions have provided new insights to quantum many-body dynamics. Both disorders and measurements are found to induce similar entanglement transitions. Here, we provide a theoretical framework that unifies these two seemingly disparate concepts and discloses their internal connections. Specifically, we analytically analyze a $d$-dimension free-fermion gas subject to continuous projective measurements. By mapping the Lindblad master equation to the functional Keldysh field theory, we develop an effective theory termed as the time-local Keldysh nonlinear sigma model, which enables us to analytically describe the physics of the monitored system. Our effective theory resembles to that used to describe the disordered fermionic systems. As an application of the effective theory, we study the transport property and obtain a Drude-form conductivity where the elastic scattering time is replaced by the inverse measurement strength. According to these similarities, two different concepts, measurements and disorders, are unified in the same theoretical framework. A numerical verification of our theory and predictions is also provided.

quant-ph↗

arXiv2023

Thermodynamically consistent master equation based on subsystem eigenstates

Master equations under appropriate assumptions are efficient tools for the study of open quantum systems. For many-body systems, subsystems of which locally couple to thermal baths and weakly interact with each other, the local approach provides a more convenient description than the global approach. However, these local master equations are believed to generate inconsistencies with the laws of thermodynamics when intersubsystem interactions exist. Here we develop an alternative local master equation by virtue of similar approximations used in deriving the traditional Gorini-Kossakowski-Lindblad-Sudarshan master equation. In particular, we stick to using eigenstates of each subsystem to construct quantum jump operators, and the secular approximation is also employed to modify the intersubsystem interactions. Our results show that violations of thermodynamic laws will be avoided after correcting intersubsystem interactions. Finally, We study a two-qubit heat transfer model and this further shows the validity of our modified master equation.

quant-ph↗

arXiv2022

AltCLIP: Altering the Language Encoder in CLIP for Extended Language Capabilities

In this work, we present a conceptually simple and effective method to train a strong bilingual/multilingual multimodal representation model. Starting from the pre-trained multimodal representation model CLIP released by OpenAI, we altered its text encoder with a pre-trained multilingual text encoder XLM-R, and aligned both languages and image representations by a two-stage training schema consisting of teacher learning and contrastive learning. We validate our method through evaluations of a wide range of tasks. We set new state-of-the-art performances on a bunch of tasks including ImageNet-CN, Flicker30k-CN, COCO-CN and XTD. Further, we obtain very close performances with CLIP on almost all tasks, suggesting that one can simply alter the text encoder in CLIP for extended capabilities such as multilingual understanding. Our models and code are available at https://github.com/FlagAI-Open/FlagAI.

cs.CL↗

arXiv2022

Phonemic Adversarial Attack against Audio Recognition in Real World

Recently, adversarial attacks for audio recognition have attracted much attention. However, most of the existing studies mainly rely on the coarse-grain audio features at the instance level to generate adversarial noises, which leads to expensive generation time costs and weak universal attacking ability. Motivated by the observations that all audio speech consists of fundamental phonemes, this paper proposes a phonemic adversarial tack (PAT) paradigm, which attacks the fine-grain audio features at the phoneme level commonly shared across audio instances, to generate phonemic adversarial noises, enjoying the more general attacking ability with fast generation speed. Specifically, for accelerating the generation, a phoneme density balanced sampling strategy is introduced to sample quantity less but phonemic features abundant audio instances as the training data via estimating the phoneme density, which substantially alleviates the heavy dependency on the large training dataset. Moreover, for promoting universal attacking ability, the phonemic noise is optimized in an asynchronous way with a sliding window, which enhances the phoneme diversity and thus well captures the critical fundamental phonemic patterns. By conducting extensive experiments, we comprehensively investigate the proposed PAT framework and demonstrate that it outperforms the SOTA baselines by large margins (i.e., at least 11X speed up and 78% attacking ability improvement).

cs.SD↗

arXiv2022

Exploiting Global and Local Hierarchies for Hierarchical Text Classification

Hierarchical text classification aims to leverage label hierarchy in multi-label text classification. Existing methods encode label hierarchy in a global view, where label hierarchy is treated as the static hierarchical structure containing all labels. Since global hierarchy is static and irrelevant to text samples, it makes these methods hard to exploit hierarchical information. Contrary to global hierarchy, local hierarchy as a structured labels hierarchy corresponding to each text sample. It is dynamic and relevant to text samples, which is ignored in previous methods. To exploit global and local hierarchies,we propose Hierarchy-guided BERT with Global and Local hierarchies (HBGL), which utilizes the large-scale parameters and prior language knowledge of BERT to model both global and local hierarchies.Moreover,HBGL avoids the intentional fusion of semantic and hierarchical modules by directly modeling semantic and hierarchical information with BERT.Compared with the state-of-the-art method HGCLR,our method achieves significant improvement on three benchmark datasets.

cs.CL↗

arXiv2022

Effect of quantum error correction on detection-induced coherent errors

We study the performance of quantum error correction codes (QECCs) under the detection-induced coherent error due to the imperfectness of practical implementations of stabilizer measurements, after running a quantum circuit. Considering the most promising surface code, we find that the detection-induced coherent error will result in undetected error terms, which will accumulate and evolve into logical errors. However, we show that such errors will be alleviated by increasing the code size, akin to eliminating other types of errors discussed previously. We also find that with detection-induced coherent errors, the exact surface code becomes an approximate QECC.

quant-ph↗

arXiv2021

Intrinsic dissipative Floquet superconductors beyond mean-field theory

We study the intrinsic superconductivity in a dissipative Floquet electronic system in the presence of attractive interactions. Based on the functional Keldysh theory beyond the mean-field treatment, we find that the system shows a time-periodic bosonic condensation and reaches an intrinsic dissipative Floquet superconducting (SC) phase. Due to the interplay between dissipations and periodic modulations, the Floquet SC gap becomes "soft" and contains the diffusive fermionic modes with finite lifetimes. However, bosonic modes of the bosonic condensation are still propagating even in the presence of dissipations.

cond-mat.supr-con↗

arXiv2021

Dissipative Floquet Majorana modes in proximity-induced topological superconductors

We study a realistic Floquet topological superconductor, a periodically driven nanowire proximitized to an equilibrium s-wave superconductor. Due to both strong energy and density fluctuations caused from the superconducting proximity effect, the Floquet Majorana wire becomes dissipative. We show that the Floquet band structure is still preserved in this dissipative system. In particular, we find that both the Floquet Majorana zero and pi modes can no longer be simply described by the Floquet topological band theory. We also propose an effective model to simplify the calculation of the lifetime of these Floquet Majoranas, and find that the lifetime can be engineered by the external driving field.

cond-mat.mes-hall↗

arXiv2019

An anomaly prediction framework for financial IT systems using hybrid machine learning methods

In financial field, a robust software system is of vital importance to ensure the smooth operation of financial transactions. However, many financial corporations still depend on operators to identify and eliminate the system failures when financial software systems break down. This traditional operation method is time consuming and extremely inefficient. To improve the efficiency and accuracy of system failure detection and thereby reduce the impact of system failures on financial services, we propose a novel machine learning-based framework to predict the occurrence of system exceptions and failures in a financial software system. In particular, we first extract rich information from system logs and eliminate noises in the data. Then the cleaned data is leveraged as the input of our proposed anomaly prediction framework which consists of three modules: key performance indicator(KPI) data prediction module, anomaly identification module and severity classification module. Notably, we design a hierarchical architecture of alarm classifiers and try to alleviate the influence of class-imbalance problem on the overall performance. Empirically, the experimental results demonstrate the superior performance of our proposed method on a real-world financial software system log data set.

cs.LG↗