arXiv subjects

Ying Ren

Publications and source records attributed to Ying Ren.

5 recordsLinked to original sources

arXiv2026

Near-Perfect Single-Photon Source via Ultrastrong Coupling

Deterministic single-photon sources are indispensable core devices for quantum information technology, yet high-performance implementation remains a long-standing bottleneck for linear optical quantum computing. We propose a feasible scheme for deterministic single-photon emission based on a $\triangle$-type three-level atom coupled to a single-mode cavity, driven by two classical external fields, which is adaptable to both strong and ultrastrong cavity-atom coupling regimes. Under continuous-wave driving, the system achieves excellent single-photon characteristics: the normalized equal-time second-order correlation function reaches $g^{(2)}(0)\sim10^{-6}$, with a photon indistinguishability of $98.73\%$ and a state purity of $99.95\%$ in the strong coupling regime, while the ultrastrong coupling regime further suppresses $G^{(2)}(0)\sim10^{-8}$, yielding an indistinguishability of $99.10\%$ and a purity of $99.99\%$. For pulsed driving in the ultrastrong coupling regime, the source realizes superior performance, with an emission efficiency, indistinguishability, and purity of $99.96\%$, $98.98\%$, and $99.99\%$ under resonant conditions, and $100\%$, $95.91\%$, and $99.93\%$ under detuned conditions, respectively. The near-ideal optical performance of the proposed scheme provides a viable route for constructing high-quality deterministic single-photon sources, which offers a promising solution to the limitations of conventional single-photon devices and facilitates the further development of quantum information science and fundamental quantum optical research.

quant-ph↗

arXiv2023

EventTrojan: Manipulating Non-Intrusive Speech Quality Assessment via Imperceptible Events

Non-Intrusive speech quality assessment (NISQA) has gained significant attention for predicting speech's mean opinion score (MOS) without requiring the reference speech. Researchers have gradually started to apply NISQA to various practical scenarios. However, little attention has been paid to the security of NISQA models. Backdoor attacks represent the most serious threat to deep neural networks (DNNs) due to the fact that backdoors possess a very high attack success rate once embedded. However, existing backdoor attacks assume that the attacker actively feeds samples containing triggers into the model during the inference phase. This is not adapted to the specific scenario of NISQA. And current backdoor attacks on regression tasks lack an objective metric to measure the attack performance. To address these issues, we propose a novel backdoor triggering approach (EventTrojan) that utilizes an event during the usage of the NISQA model as a trigger. Moreover, we innovatively provide an objective metric for backdoor attacks on regression tasks. Extensive experiments on four benchmark datasets demonstrate the effectiveness of the EventTrojan attack. Besides, it also has good resistance to several defense methods.

cs.SD↗

arXiv2019

Highly fluorescent copper nanoclusters for sensing and bioimaging

Metal nanoclusters (NCs), typically consisting of a few to tens of metal atoms, bridge the gap between organometallic compounds and crystalline metal nanoparticles. As their size approaches the Fermi wavelength of electrons, metal NCs exhibit discrete energy levels, which in turn results in the emergence of intriguing physical and chemical (or physicochemical) properties, especially strong fluorescence. In the past few decades, dramatic growth has been witnessed in the development of different types of noble metal NCs (mainly AuNCs and AgNCs). However, compared with noble metals, copper is a relatively earth-abundant and cost-effective metal. Theoretical and experimental studies have shown that copper NCs (CuNCs) possess unique catalytic and photoluminescent properties. In this context, CuNCs are emerging as a new class of nontoxic, economic, and effective phosphors and catalysts, drawing significant interest across the life and medical sciences. To highlight these achievements, this review begins by providing an overview of a multitude of factors that play central roles in the fluorescence of CuNCs. Additionally, a critical perspective of how the aggregation of CuNCs can efficiently improve the florescent stability, tunability, and intensity is also discussed. Following, we present representative applications of CuNCs in detection and bioimaging. Finally, we outline current challenges and our perspective on the development of CuNCs.

q-bio.BM↗

arXiv2013

Exploring the mechanisms of protein folding

Neither of the two prevalent theories, namely thermodynamic stability and kinetic stability, provides a comprehensive understanding of protein folding. The thermodynamic theory is misleading because it assumes that free energy is the exclusive dominant mechanism of protein folding, and attributes the structural transition from one characteristic state to another to energy barriers. Conversely, the concept of kinetic stability overemphasizes dominant mechanisms that are related to kinetic factors. This article explores the stability condition of protein structures from the viewpoint of meso-science, paying attention to the compromise in the competition between minimum free energy and other dominant mechanisms. Based on our study of complex systems, we propose that protein folding is a meso-scale, dissipative, nonlinear and non-equilibrium process that is dominated by the compromise between free energy and other dominant mechanisms such as environmental factors. Consequently, a protein shows dynamic structures, featuring characteristic states that appear alternately and dynamically, only one of which is the state with minimum free energy. To provide evidence for this concept, we analyzed the time series of energetic and structural changes of three simulations of protein folding/unfolding. Our results indicate that thorough consideration of the multiple dynamic characteristic structures generated by multiple mechanisms may be the key to understanding protein folding.

physics.bio-ph↗

arXiv2010

Molecular Dynamics Simulation of Macromolecules Using Graphics Processing Unit

Molecular dynamics (MD) simulation is a powerful computational tool to study the behavior of macromolecular systems. But many simulations of this field are limited in spatial or temporal scale by the available computational resource. In recent years, graphics processing unit (GPU) provides unprecedented computational power for scientific applications. Many MD algorithms suit with the multithread nature of GPU. In this paper, MD algorithms for macromolecular systems that run entirely on GPU are presented. Compared to the MD simulation with free software GROMACS on a single CPU core, our codes achieve about 10 times speed-up on a single GPU. For validation, we have performed MD simulations of polymer crystallization on GPU, and the results observed perfectly agree with computations on CPU. Therefore, our single GPU codes have already provided an inexpensive alternative for macromolecular simulations on traditional CPU clusters and they can also be used as a basis to develop parallel GPU programs to further speedup the computations.

physics.comp-ph↗