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Yingqi Chen

Publications and source records attributed to Yingqi Chen.

7 recordsLinked to original sources

Explainable Coarse-to-Fine Ancient Manuscript Duplicates Discovery

Ancient manuscripts are the primary source of ancient linguistic corpora. However, many ancient manuscripts exhibit duplications due to unintentional repeated publication or deliberate forgery. The Dead Sea Scrolls, for example, include counterfeit fragments, whereas Oracle Bones (OB) contain both republished materials and fabricated specimens. Identifying ancient manuscript duplicates is of great significance for both archaeological curation and ancient history study. In this work, we design a progressive OB duplicate discovery framework that combines unsupervised low-level keypoints matching with high-level text-centric content-based matching to refine and rank the candidate OB duplicates with semantic awareness and interpretability. We compare our model with state-of-the-art content-based image retrieval and image matching methods, showing that our model yields comparable recall performance and the highest simplified mean reciprocal rank scores for both Top-5 and Top-15 retrieval results, and with significantly accelerated computation efficiency. We have discovered over 60 pairs of new OB duplicates in real-world deployment, which were missed by domain experts for decades. Code, model and real-world results are available at: https://github.com/cszhangLMU/OBD-Finder/.

cs.IR

Magnetically disordered ground state in the triangular-lattice antiferromagnets Rb$_3$Yb(VO$_4$)$_2$ and Cs$_3$Yb(VO$_4$)$_2$

Quantum spin liquids~(QSLs) represent a unique quantum disordered state of matter that hosts long-range quantum entanglement and fractional excitations. However, structural disorder resulting from site mixing between different types of ions usually arises in real QSL candidates, which is considered as an obstacle to gain the insight into the intrinsic physics. Here, we have synthesized two new rare-earth compounds Rb$_3$Yb(VO$_4$)$_2$ and Cs$_3$Yb(VO$_4$)$_2$. X-ray diffractions reveal a perfect triangular-lattice structure with no detectable disorder. Magnetic susceptibility measurements do not capture any phase transition or spin freezing down to 1.8~K. A fit to low-temperature data indicates dominant antiferromagnetic interactions with the Curie-Weiss temperature of -1.40~K and -0.43~K for Rb$_3$Yb(VO$_4$)$_2$ and Cs$_3$Yb(VO$_4$)$_2$, respectively. Specific heat results show no sign of long-range magnetic order down to $\sim$0.1~K either, but only a Schottky anomaly that is continuously mediated by the external magnetic fields. Additionally, inelastic neutron scattering is employed to detect low-energy spin excitations in Rb$_3$Yb(VO$_4$)$_2$. The absence of magnetic excitation signals as well as static magnetic order down to 97~mK aligns with the results from magnetic susceptibility and specific heat. Collectively, these findings point to a quantum disordered ground state with persistent spin dynamics, reminiscent of QSL behaviors. Our work provides a promising platform for further exploration of quantum magnetism in this new disorder-free system.

cond-mat.str-el

Possible gapless quantum spin liquid behavior in the triangular-lattice Ising antiferromagnet PrMgAl$_{11}$O$_{19}$

Quantum spin liquids (QSLs) represent a novel state where spins are highly entangled but do not order even at zero temperature due to strong quantum fluctuations. Such a state is mostly studied in Heisenberg models defined on geometrically frustrated lattices. Here, we turn to a new triangular-lattice antiferromagnet PrMgAl$_{11}$O$_{19}$, in which the interactions are believed to be of Ising type. Magnetic susceptibility measured with an external field along the $c$ axis is two orders of magnitude larger than that with a field in the $ab$ plane, displaying an ideal easy-axis behavior. Meanwhile, there is no magnetic phase transition or spin freezing observed down to 1.8 K. Ultralow-temperature specific heat measured down to 50 mK does not capture any phase transition either, but a hump at 4.5 K, below which the magnetic specific heat exhibits a quasi-quadratic temperature dependence that is consistent with a Dirac QSL state. Inelastic neutron scattering technique is also employed to elucidate the nature of its ground state. In the magnetic excitation spectra, there is a gapless broad continuum at the base temperature 55~mK, in favor of the realization of a gapless QSL. Our results provide a scarce example for the QSL behaviors observed in an Ising-type magnet, which can serve as a promising platform for future research on QSL physics based on an Ising model.

cond-mat.str-el

Signatures of a gapless quantum spin liquid in the Kitaev material Na$_3$Co$_{2-x}$Zn$_x$SbO$_6$

The honeycomb-lattice cobaltate Na$_3$Co$_2$SbO$_6$ has recently been proposed to be a proximate Kitaev quantum spin liquid~(QSL) candidate. However, non-Kitaev terms in the Hamiltonian lead to a zigzag-type antiferromagnetic~(AFM) order at low temperatures. Here, we partially substitute magnetic Co$^{2+}$ with nonmagnetic Zn$^{2+}$ and investigate the chemical doping effect in tuning the magnetic ground states of Na$_3$Co$_{2-x}$Zn$_x$SbO$_6$. X-ray diffraction characterizations reveal no structural transition but quite tiny changes on the lattice parameters over our substitution range $0\leq x\leq0.4$. Magnetic susceptibility and specific heat results both show that AFM transition temperature is continuously suppressed with increasing Zn content $x$ and neither long-range magnetic order nor spin freezing is observed when $x\geq0.2$. More importantly, a linear term of the specific heat representing fermionic excitations is captured below 5~K in the magnetically disordered regime, as opposed to the $C_{\rm m}\propto T^3$ behavior expected for bosonic excitations in the AFM state. Based on the data above, we establish a magnetic phase diagram of Na$_3$Co$_{2-x}$Zn$_x$SbO$_6$. Our results indicate the presence of gapless fractional excitations in the samples with no magnetic order, evidencing a potential QSL state induced by doping in a Kitaev system.

cond-mat.str-el

Suppression of the antiferromagnetic order by Zn doping in a possible Kitaev material Na$_2$Co$_2$TeO$_6$

Very recently, a 3$d$ based honeycomb cobaltate Na$_2$Co$_2$TeO$_6$ has garnered tremendous attention due to the proposed proximity to the Kitaev spin-liquid state as its 4$d$/5$d$ counterparts. Here, we use Zn to substitute Co in a broad range and perform systematic studies on Na$_2$Co$_{2-x}$Zn$_x$TeO$_6$ by structural, magnetic, and thermodynamic measurements, and track the doping evolution of its magnetic ground states. Due to the extremely close radii of Zn$^{2+}$ and high-spin Co$^{2+}$ ions, the substitution can be easily achieved. X-ray diffractions reveal no structural transition but only minor changes on the lattice parameter $c$ over a wide substitution range $0 \leq x \leq 1.5$. Magnetic susceptibility and specific heat measurements both suggest an antiferromagnetic ground state which is gradually suppressed with doping. It can survive with $x$ up to $\sim1.0$. Then it evolves into a spin-glass phase with short-range order that is rapidly supplanted by a magnetically disordered state when $x \geq 1.3$. By summarizing all these data, we construct a magnetic phase diagram of Na$_2$Co$_{2-x}$Zn$_x$TeO$_6$. Our results demonstrate that the Zn doping can effectively suppress the magnetic order and induce a possibe quantum paramagnetic state. These may serve as a platform to investigate the Kitaev physics in this system.

cond-mat.str-el

Coded Caching via Federated Deep Reinforcement Learning in Fog Radio Access Networks

In this paper, the placement strategy design of coded caching in fog-radio access networks (F-RANs) is investigated. By considering time-variant content popularity, federated deep reinforcement learning is exploited to learn the placement strategy for our coded caching scheme. Initially, the placement problem is modeled as a Markov decision process (MDP) to capture the popularity variations and minimize the long-term content access delay. The reformulated sequential decision problem is solved by dueling double deep Q-learning (dueling DDQL). Then, federated learning is applied to learn the relatively low-dimensional local decision models and aggregate the global decision model, which alleviates over-consumption of bandwidth resources and avoids direct learning of a complex coded caching decision model with high-dimensional state space. Simulation results show that our proposed scheme outperforms the benchmarks in reducing the content access delay, keeping the performance stable, and trading off between the local caching gain and the global multicasting gain.

cs.IT

Privacy-Preserving Federated Learning on Partitioned Attributes

Real-world data is usually segmented by attributes and distributed across different parties. Federated learning empowers collaborative training without exposing local data or models. As we demonstrate through designed attacks, even with a small proportion of corrupted data, an adversary can accurately infer the input attributes. We introduce an adversarial learning based procedure which tunes a local model to release privacy-preserving intermediate representations. To alleviate the accuracy decline, we propose a defense method based on the forward-backward splitting algorithm, which respectively deals with the accuracy loss and privacy loss in the forward and backward gradient descent steps, achieving the two objectives simultaneously. Extensive experiments on a variety of datasets have shown that our defense significantly mitigates privacy leakage with negligible impact on the federated learning task.

cs.LG