arXiv subjects

Feng Ye

Publications and source records attributed to Feng Ye.

At least 55 records · Page 3Linked to original sources

arXiv2025

Field-Tailoring Quantum Materials via Magneto-Synthesis: Metastable Metallic and Magnetically Suppressed Phases in a Trimer Iridate

We demonstrate that applying modest magnetic fields during high-temperature crystal growth can profoundly alter the structure and ground state of a spin-orbit-coupled, antiferromagnetic trimer lattice. Using BaIrO3 as a model system, whose ground state is intricately dictated by the trimer lattice, we show that magneto-synthesis, a field-assisted synthesis approach, stabilizes a structurally compressed, metastable metallic and magnetically suppressed phases inaccessible via conventional methods. These effects include a 0.85% reduction in unit cell, 4-order-of-magnitude decrease in resistivity, a 10-fold enhancement of the Sommerfeld coefficient, and the collapse of long-range magnetic order -- all intrinsic and bulk in origin. First-principles calculations confirm that the field-stabilized structure lies substantially above the ground state in energy, highlighting its metastable character. These large, coherent and correlated changes across multiple bulk properties, unlike those caused by dilute impurities, defects or off-stoichiometry, point to an intrinsic field-induced mechanism. The findings establish magneto-synthesis as a powerful new pathway for accessing non-equilibrium quantum phases in strongly correlated materials.

cond-mat.str-el↗

arXiv2025

Interacting spin and charge density waves in kagome metal FeGe

Unveiling the interplay between spin density wave (SDW) and charge density wave (CDW) orders in correlated electron materials is important to obtain a comprehensive understanding of their electronic, structural, and magnetic properties. Kagome lattice materials are interesting because their flat electronic bands, Dirac points, and van Hove singularities can enable a variety of exotic electronic and magnetic phenomena. The kagome metal FeGe, which exhibits a CDW order deep within an A-type antiferromagnetic (AFM) phase, was found to respond dramatically to post-growth annealing - with the ability to tune the CDW repeatedly from long-range order to no (or extremely weak) order. Additionally, neutron scattering studies suggest that incommensurate magnetic peaks that onsets at $T_{Canting}$ = $T_{SDW} \approx$ 60 K in the system arise from a SDW order instead of the AFM double cone structure. Here we use inelastic neutron scattering to show two distinct spin excitations exist below $T_{Canting}$ corresponding to two coexisting magnetic orders in the system in both sets of annealed samples with and without CDW. While CDW order or no order can dramatically affect the onset temperature of $T_{Canting}$ and elastic incommensurate magnetic scattering, its impact on low-energy spin fluctuations is more limited. In both samples, a pair of gapless incommensurate spin excitations arising from the SDW order wavevector coexist with gapped commensurate spin waves from the A-type AFM order across $T_{Canting}$. Low-energy spin excitations for both samples couple dynamically to the lattice through enhanced magnetic scattering intensity on cooling below $T_{CDW}$, regardless the status of the static long-range CDW order. The incommensurate SDW order in the long-range CDW ordered sample also induces a tiny in-plane lattice distortion of the kagome lattice that is absent in the no CDW ordered sample.

cond-mat.str-el↗

arXiv2025

Non-Altermagnetic Origin of Exchange Bias Behaviors in Incoherent RuO$_2$/Fe Bilayer Heterostructures

Initially identified as a promising altermagnetic (AM) candidate, rutile RuO$_2$ has since become embroiled in controversy due to contradictory findings of modeling and measurements of the magnetic properties of bulk crystals and thin films. For example, despite observations of a bulk non-magnetic state using density functional theory, neutron scattering, and muon spin resonance measurements, patterned RuO$_2$ Hall bars and film heterostructures display magnetotransport signatures of magnetic ordering. Among the characteristics routinely cited as evidence for AM is the observation of exchange bias (EB) in an intimately contacted Fe-based ferromagnetic (FM) layer, which can arise due to interfacial coupling with a compensated antiferromagnet. Within this work, the origins of this EB coupling in Ru-capped RuO$_2$/Fe bilayers are investigated using polarized neutron diffraction, polarized neutron reflectometry, cross-sectional transmission electron microscopy, and super conducting quantum interference device measurements. These experiments reveal that the EB behavior is driven by the formation of an iron oxide interlayer containing Fe$_3$O$_4$ that undergoes a magnetic transition and pins interfacial moments within Fe at low temperature. These findings are confirmed by comparable measurements of Ni-based heterostructures, which do not display EB coupling, as well as magnetometry of additional Fe/Ru bilayers that display oxide-driven EB coupling despite the absence of the epitaxial RuO$_2$ layer. While these results do not directly refute the possibility of AM ordering in RuO$_2$ thin films, they reveal that EB, and related magnetotransport phenomena, cannot alone be considered evidence of this characteristic in the rutile structure due to interfacial chemical disorder.

cond-mat.mtrl-sci↗

arXiv2025

4D-QENS Analysis of Correlated Ionic Conduction in SrCl$_2$

Methods of elucidating the mechanisms of fast-ion conduction in solid-state materials are pivotal for advancements in energy technologies such as batteries, fuel cells, sensors, and supercapacitors. In this study, we examine the ionic conduction pathways in single crystal SrCl$_2$, which is a fast-ion conductor above 900~K, using four-dimensional Quasi-Elastic Neutron Scattering (4D-QENS). We explore both coherent and incoherent neutron scattering at temperatures above the transition temperature into the superionic phase to explore the correlated motion of hopping anions. Refinements of the incoherent QENS yield residence times and jump probabilities between lattice sites in good agreement with previous studies, confirming that ionic hopping along nearest-neighbor directions is the most probable conduction pathway. However, the coherent QENS reveals evidence of de Gennes narrowing, indicating the importance of ionic correlations in the conduction mechanism. This highlights the need for improvements both in the theory of ionic transport in fluorite compounds and the modeling of coherent 4D-QENS in single crystals.

cond-mat.mtrl-sci↗

arXiv2025

Emergent Inductance from Chiral Orbital Currents in a Bulk Ferrimagnet

We report the discovery of a new form of inductance in the bulk ferrimagnet Mn3Si2Te6, which features strong spin-orbit coupling, large magnetic anisotropy, and pronounced magnetoelastic interactions. Below its Curie temperature, Mn3Si2Te6 hosts chiral orbital currents (COC) that circulate within the crystal lattice and give rise to collective electronic behavior [1]. By applying a magnetic field along the hard c axis and driving the system with low-frequency currents, we uncover a giant inductive response up to millihenry scale, originating from first-order reconfigurations of COC domains. These domains act as coherent mesoscopic inductive elements that resist reversal upon current reduction, producing a large electromotive force and sharply increasing voltage. This emergent inductance defies classical models, occurs without superconductivity or engineered nanostructures, and opens a new frontier in orbital-based quantum functionality and device concepts.

cond-mat.str-el↗

arXiv2025

Average Achievable Rate Analysis of Cell-Free Massive MIMO in the Finite Blocklength Regime with Imperfect CSI

Acquiring perfect channel state information (CSI) introduces substantial challenges in cell-free massive MIMO (CF-mMIMO) systems, primarily due to the large dimensionality of channel parameters, especially under ultra-reliable low-latency communication (uRLLC) constraints. Furthermore, the impact of imperfect CSI on the average achievable rate within the finite blocklength regime remains largely unexplored. Motivated by this gap, this paper proposes a novel analytical framework that provides a closed-form expression for the average achievable rate with imperfect CSI in the Laplace domain. We demonstrate analytically that both the channel dispersion and the expected channel capacity can be expressed explicitly in terms of the Laplace transform of the large-scale fading component. Numerical simulations confirm that the derived expressions match closely with Monte Carlo simulations, verifying their accuracy. Furthermore, we theoretically show that although imperfect CSI degrades performance in the finite blocklength regime, the inherent characteristics of CF-mMIMO architecture effectively mitigates this loss.

cs.IT↗

arXiv2025

Temporal and spatial separations between spin glass and short-range order

Broken-symmetry-induced order parameters account for many phenomena in condensed matter physics. For spin glasses, such a framework dictates its theoretical construction, whereas experiments have only established dynamical behaviors such as frequency dependent magnetic susceptibility and aging but not the thermodynamic phase. Experimental techniques have limitations when the spin glass is probed as an isolated state. To resolve this conundrum, we create an evolution from long-range order using a well-controlled tuning of the disorder on a spinel's sublattice. Cross-referencing a series of specimens at both long (milliseconds to seconds) and short (picosecond) time scales illustrates the relationship between spin glass and long- and short-range orders. The dynamics of short- and long-range order formations are not affected by disorder, as revealed by neutron magnetic diffuse scattering, however the ranges of these orderings are changed by the introduced disorder. Across all specimens, the inflection point of the correlation length's temperature dependence fully matches with the peak in heat capacity, while spin glass can freeze either below or well above this characteristic temperature of spin order formation. Our results identify an uncorrelated coexistence of the two and attribute components of the spin glass to individual spins at domain walls between spin clusters.

cond-mat.dis-nn↗

arXiv2025

Terahertz Spatial Wireless Channel Modeling with Radio Radiance Field

Terahertz (THz) communication is a key enabler for 6G systems, offering ultra-wide bandwidth and unprecedented data rates. However, THz signal propagation differs significantly from lower-frequency bands due to severe free space path loss, minimal diffraction and specular reflection, and prominent scattering, making conventional channel modeling and pilot-based estimation approaches inefficient. In this work, we investigate the feasibility of applying radio radiance field (RRF) framework to the THz band. This method reconstructs a continuous RRF using visual-based geometry and sparse THz RF measurements, enabling efficient spatial channel state information (Spatial-CSI) modeling without dense sampling. We first build a fine simulated THz scenario, then we reconstruct the RRF and evaluate the performance in terms of both reconstruction quality and effectiveness in THz communication, showing that the reconstructed RRF captures key propagation paths with sparse training samples. Our findings demonstrate that RRF modeling remains effective in the THz regime and provides a promising direction for scalable, low-cost spatial channel reconstruction in future 6G networks.

eess.SP↗

arXiv2025

Emerging Advances in Learned Video Compression: Models, Systems and Beyond

Video compression is a fundamental topic in the visual intelligence, bridging visual signal sensing/capturing and high-level visual analytics. The broad success of artificial intelligence (AI) technology has enriched the horizon of video compression into novel paradigms by leveraging end-to-end optimized neural models. In this survey, we first provide a comprehensive and systematic overview of recent literature on end-to-end optimized learned video coding, covering the spectrum of pioneering efforts in both uni-directional and bi-directional prediction based compression model designation. We further delve into the optimization techniques employed in learned video compression (LVC), emphasizing their technical innovations, advantages. Some standardization progress is also reported. Furthermore, we investigate the system design and hardware implementation challenges of the LVC inclusively. Finally, we present the extensive simulation results to demonstrate the superior compression performance of LVC models, addressing the question that why learned codecs and AI-based video technology would have with broad impact on future visual intelligence research.

eess.IV↗

arXiv2025

Anomalous Electrical Transport in the Kagome Magnet YbFe$_6$Ge$_6$

Two-dimensional (2D) kagome metals offer a unique platform for exploring electron correlation phenomena derived from quantum many-body effects. Here, we report a combined study of electrical magnetotransport and neutron scattering on YbFe$_6$Ge$_6$, where the Fe moments in the 2D kagome layers exhibit an $A$-type collinear antiferromagnetic order below $T_{\rm{N}} \approx 500$ K. Interactions between the Fe ions in the layers and the localized Yb magnetic ions in between reorient the $c$-axis aligned Fe moments to the kagome plane below $T_{\rm{SR}} \approx 63$ K. Our magnetotransport measurements show an intriguing anomalous Hall effect (AHE) that emerges in the spin-reorientated collinear state, accompanied by the closing of the spin anisotropy gap as revealed from inelastic neutron scattering. The gapless spin excitations and the Yb-Fe interaction are able to support a dynamic scalar spin chirality, which explains the observed AHE. Therefore, our study demonstrates spin fluctuations may provide an additional scattering channel for the conduction electrons and give rise to AHE even in a collinear antiferromagnet.

cond-mat.str-el↗

arXiv2025

Explicit Performance Bound of Finite Blocklength Coded MIMO: Time-Domain versus Spatiotemporal Channel Coding

In the sixth generation (6G), ultra-reliable low-latency communications (URLLC) will be further developed to achieve TKu extreme connectivity. On the premise of ensuring the same rate and reliability, the spatial domain advantage of multiple-input multiple-output (MIMO) has the potential to further shorten the time-domain code length and is expected to be a key enabler for the realization of TKu. Different coded MIMO schemes exhibit disparities in exploiting the spatial domain characteristics, so we consider two extreme MIMO coding schemes, namely, time-domain coding in which the codewords on multiple spatial channels are independent of each other, and spatiotemporal coding in which multiple spatial channels are jointly coded. By analyzing the statistical characteristics of information density and utilizing the normal approximation, we provide explicit performance bounds for finite blocklength coded MIMO under time-domain coding and spatiotemporal coding. It is found that, different from the phenomenon in time-domain coding where the performance declines as the blocklengths decrease, spatiotemporal coding can effectively compensate for the performance loss caused by short blocklengths by improving the spatial degrees of freedom (DoF). These results indicate that spatiotemporal coding can optimally exploit the spatial dimension advantages of MIMO systems, enabling extremely low error-rate communication under stringent blocklengths constraint.

cs.IT↗

arXiv2025

Stability frontiers in the AM$_6$X$_6$ kagome metals: The LnNb$_6$Sn$_6$ (Ln:Ce-Lu,Y) family and density-wave transition in LuNb$_6$Sn$_6$

The kagome motif is a versatile platform for condensed matter physics, hosting rich interactions between magnetic, electronic, and structural degrees of freedom. In recent years, the discovery of a charge density wave (CDW) in the AV$_3$Sb$_5$ superconductors and structurally-derived bond density waves in FeGe and ScV$_6$Sn$_6$ have stoked the search for new kagome platforms broadly exhibiting density wave (DW) transitions. In this work, we evaluate the known AM$_6$X$_6$ chemistries and construct a stability diagram that summarizes the structural relationships between the $\approx$125 member family. Subsequently we introduce our discovery of the broader LnNb$_6$Sn$_6$ (Ln:Ce-Nd,Sm,Gd-Tm,Lu,Y) family of kagome metals and an analogous DW transition in LuNb$_6$Sn$_6$. Our X-ray scattering measurements clearly indicate a (1/3, 1/3, 1/3) ordering wave vector ($\sqrt{3}\times\sqrt{3}\times3$ superlattice) and diffuse scattering on half-integer $L$-planes. Our analysis of the structural data supports the ``rattling mode'' DW model proposed for ScV$_6$Sn$_6$ and paints a detailed picture of the steric interactions between the rare-earth filler element and the host Nb-Sn kagome scaffolding. We also provide a broad survey of the magnetic properties within the HfFe$_6$Ge$_6$-type LnNb$_6$Sn$_6$ members, revealing a number of complex antiferromagnetic and metamagnetic transitions throughout the family. This work integrates our new LnNb$_6$Sn$_6$ series of compounds into the broader AM$_6$X$_6$ family, providing new material platforms and forging a new route forward at the frontier of kagome metal research.

cond-mat.str-el↗

arXiv2025

Charge density waves and pinning by lattice anisotropy in 214 cuprates

The detection of static charge density waves (CDWs) in La$_{2-x}$Sr$_x$CuO$_4$ (LSCO) with x $\sim$ 0.12 at relatively high temperatures has raised the question of what lattice feature pins the CDWs. Some recent structural studies have concluded that some form of monoclinic distortion, indicated by the appearance of certain weak Bragg peaks (type M peaks) at otherwise forbidden positions, are responsible for CDW pinning. As a test of this idea, we present neutron diffraction results for a single crystal of La$_{2-x}$Ba$_x$CuO$_4$ (LBCO) with x = 1/8, which is known to undergo two structural transitions on cooling, from high-temperature tetragonal (HTT) to low-temperature orthorhombic (LTO) near 240 K, involving a collective tilt pattern of the corner-sharing CuO$_6$ octahedra, and from LTO to low temperature tetragonal (LTT) near 56 K, involving a new tilt pattern and the appearance of intensity at peaks of type T. We observe both type M and type T peaks in the LTT phase, while the type M peaks (but not type T) are still present in the LTO phase. Given that CDW order is observed only in the LTT phase of LBCO, it is apparent that the in-plane Cu-O bond anisotropy associated with the octahedral tilt pattern is responsible for charge pinning. We point out that evidence for a similar, but weaker, bond anisotropy has been observed previously in LSCO and should be responsible for CDW pinning there. In the case of LBCO, the monoclinic distortion may help to explain previously-reported magneto-optical evidence for gyrotropic order.

cond-mat.supr-con↗

arXiv2025

Correlation between Complex Spin Textures and the Magnetocaloric and Hall Effects in Eu(Ga$_{1-x}$Al$_x$)$_4$ ($x$ = 0.9, 1)

Determining the electronic phase diagram of a quantum material as a function of temperature (T) and applied magnetic field (H) forms the basis for understanding the microscopic origin of transport properties, such as the anomalous Hall effect (AHE) and topological Hall effect (THE). For many magnetic quantum materials, including EuAl$_4$, a THE arises from a topologically protected magnetic skyrmion lattice with a non-zero scalar spin chirality. We identified a square skyrmion lattice (sSkL) peak in Eu(Ga$_{1-x}$Al$_x$)$_4$ ($x$ = 0.9) identical to the peak previously observed in EuAl$_4$ by performing neutron scattering measurements throughout the phase diagram. Comparing these neutron results with transport measurements, we found that in both compounds the maximal THE does not correspond to the sSkL area. Instead of the maximal THE, the maximal magnetocaloric effect (MCE) boundaries better identify the sSkL lattice phase observed by neutron scattering measurements. The maximal THE therefore arises from interactions of itinerant electrons with frustrated spin fluctuations in a topologically trivial magnetic state.

cond-mat.str-el↗

arXiv2025

Spiral Spin Liquid State in the Corrugated Honeycomb Lattice of CaMn$_2$P$_2$

CaMn$_2$P$_2$ exemplifies the realization of a frustrated $J_1$-$J_2$-$J_3$ Heisenberg model of a corrugated honeycomb magnetic lattice. Previous studies show that below the Néel temperature ($T_{\rm N}$), the system forms a cycloidal $6\times 6$ $ab$-plane magnetic unit cell that conforms with various magnetic space groups. Here, we present single-crystal neutron-diffraction studies across expansive reciprocal-space volumes, confirming the cycloidal magnetic structure while uncovering further distinctive features. We find evidence for three magnetic domains, the analysis of which narrows the possible magnetic model structures. At $T_{\rm N}$, the insulator exhibits a sharp phase transition, above which the spin structure transforms into a spiral spin liquid state, evident via a continuous ring of scattering with degenerate wavevectors corresponding to a collection of short-range spiral spin configurations. These degenerate states emerge as thermal fluctuations effectively reduce the $J_3$ interaction. The integration of experimental, theoretical, and real-space simulation results reveals the intricate balance of exchange interactions ($J_1$-$J_2$-$J_3$) that stabilizes the ground-state magnetic structure and drives the emergence of a sought-after $U$(1)-symmetric spiral spin-liquid state with easy-plane anisotropy above the transition temperature.

cond-mat.str-el↗

arXiv2024

Structural Properties of Plastically Deformed SrTiO3 and KTaO3

Dislocation engineering has the potential to open new avenues toward the exploration and modification of the properties of quantum materials. Strontium titanate (SrTiO3, STO) and potassium tantalate (KTaO3, KTO) are incipient ferroelectrics that show metallization and superconductivity at extremely low charge carrier concentrations, and have been the subject of resurgent interest. These materials also exhibit remarkable ambient-temperature ductility, and thus represent exceptional platforms for studies of the effects of deformation-induced dislocation structures on electronic properties. Recent work on plastically deformed STO revealed an enhancement of the superconducting transition temperature and the emergence of local ferroelectricity and magnetism near self-organized dislocation walls. Here we present a comprehensive structural analysis of plastically deformed STO and KTO, employing specially designed strain cells, diffuse neutron and x-ray scattering, Raman scattering, and nuclear magnetic resonance (NMR). Diffuse scattering and NMR provide insight into the dislocation configurations and densities and their dependence on strain. As in the prior work on STO, Raman scattering reveals evidence for local ferroelectric order near dislocation walls in plastically deformed KTO. Our findings provide valuable information about the self-organized defect structures in both materials, and they position KTO as a second model system with which to explore the associated emergent physics.

cond-mat.mtrl-sci↗

arXiv2024

Model-based Deep Learning for Wireless Resource Allocation in RSMA Communications Systems

Rate-splitting multiple access (RSMA) has been proven as an effective communication scheme for 5G and beyond. However, current approaches to RSMA resource management require complicated iterative algorithms, which cannot meet the stringent latency requirement by users with limited resources. Recently, data-driven methods are explored to alleviate this issue. However, they suffer from poor generalizability and scarce training data to achieve satisfactory performance. In this paper, we propose a fractional programming (FP) based deep unfolding (DU) approach to address resource allocation problem for a weighted sum rate optimization in RSMA. By carefully designing the penalty function, we couple the variable update with projected gradient descent algorithm (PGD). Following the structure of PGD, we embed a few learnable parameters in each layer of the DU network. Through extensive simulation, we have shown that the proposed model-based neural networks can yield similar results compared to the traditional optimization algorithm for RSMA resource management but with much lower computational complexity, less training data, and higher resilience to out-of-distribution (OOD) data.

cs.IT↗

arXiv2024

Model-based Deep Learning for QoS-Aware Rate-Splitting Multiple Access Wireless Systems

Next generation communications demand for better spectrum management, lower latency, and guaranteed quality-of-service (QoS). Recently, Artificial intelligence (AI) has been widely introduced to advance these aspects in next generation wireless systems. However, such AI applications suffer from limited training data, low robustness, and poor generalization capabilities. To address these issues, a model-driven deep unfolding (DU) algorithm is introduced in this paper to bridge the gap between traditional model-driven communication algorithms and data-driven deep learning. Focusing on the QoS-aware rate-splitting multiple access (RSMA) resource allocation problem in multi-user communications, a conventional fractional programming (FP) algorithm is first applied as a benchmark. The solution is then refined by the application of projection gradient descent (PGD). DU is employed to further speed up convergence procedure, hence improving the efficiency of PGD. Moreover, the feasibility of results is guaranteed by designing a low-complexity projection based on scale factors, plus adding violation control mechanisms into the loss function that minimizes error rates. Finally, we provide a detailed analysis of the computational complexity and analysis design of the proposed DU algorithm. Extensive simulations are conducted and the results demonstrate that the proposed DU algorithm can reach the optimal communication efficiency with a mere $0.024\%$ violation rate for 4 layers DU. The DU algorithm also exhibits robustness in out-of-distribution tests and can be effectively trained with as few as 50 samples.

cs.NI↗