arXiv subjects

Jianqiao Wang

Publications and source records attributed to Jianqiao Wang.

6 recordsLinked to original sources

arXiv2026

Rare-earth Bilayer Triangular Lattice as a Platform for Tunable Ground States and Field-induced Magnetic Phases

Rare-earth bilayer triangular lattice (TL) antiferromagnets provide a versatile platform for realizing diverse magnetic states by combining geometric frustration, interlayer coupling, and strong single-ion anisotropy. Here, we report a family of R2O2Se (R = Sm, Eu, Tb-Lu; ROSe) single crystals featuring bilayer equilateral TLs. Magnetic susceptibility and specific-heat measurements reveal predominantly antiferromagnetic (AFM) interactions and diverse magnetic ground states across the series, including successive AFM transitions in TbOSe and single AFM transitions in SmOSe, DyOSe, HoOSe, and YbOSe. Notably, DyOSe and HoOSe exhibit pronounced 1/2 magnetization plateau-like features for fields along the c-axis, revealing field-induced magnetic states. In HoOSe, complementary thermodynamic and magnetization measurements resolve three critical fields and a rich field-temperature phase diagram containing five distinct magnetic phases. These results establish rare-earth bilayer TLs as a chemically tunable materials platform for accessing novel quantum spin states through the interplay of lattice geometry, single-ion anisotropy, and competing magnetic interactions.

cond-mat.mtrl-sci↗

arXiv2026

Heritability estimation using genetic similarity representation

We introduce a similarity representation framework for robust heritability estimation in Genome-Wide Association Studies (GWAS). This problem parallels the signal-to-noise ratio estimation problem in linear models with a large number of predictors. Traditional fixed- and random-effects methods for heritability estimation often impose restrictive assumptions on regression coefficients or the design (genotype) matrix. These assumptions are usually violated by the heterogeneous effects of genetic variants (regression coefficients) that depend on the genotype distribution and the correlation among genotypes due to linkage disequilibrium. This leads to the non-robust estimation of heritability in practice. To overcome these limitations, we propose a SiMILarity rEpresentation method (SMILE) which models the relationship between the outcome similarity and genetic similarity through Gram matrices. SMILE represents genetic similarity using a weighted Gram matrix of genotypes, where a data-dependent weight matrix is used to disentangle the heterogeneous variant effects from the genotype distribution. SMILE includes the classical random-effects model as a special case and improves the fixed-effects model by not requiring accurate estimation of the precision matrix or the regression coefficients. We develop a scalable implementation for efficient analysis of large biobank GWAS data. Extensive simulations and the analysis of the UK Biobank data demonstrate the robustness of the proposed method over the existing methods across a range of genetic architectures, and show that SMILE provides a versatile approach for heritability estimation.

stat.ME↗

arXiv2026

Dolomite Mineral-Inspired Equilateral Triangular-Lattice Magnets for Quantum Magnetism

Equilateral triangular lattice magnets provide a versatile materials platform for exploring exotic quantum spin phenomena, while their field-tunable magnetic entropy offers opportunities for low-temperature adiabatic demagnetization refrigeration. Inspired by the natural mineral, we proposed a chemical strategy to achieve equilateral TL magnets, leveraging the high crystal symmetry of a large family of dolomite-type materials. As typical examples, the dolomite-type materials SnM(BO3)2 (M = Co, Mn) were synthesized, and structural analysis reveals that Co2+ and Mn2+ ions form equilateral triangular lattices with an A-B-C stacking fashion. The magnetic susceptibilities and specific heat measurements reveal dominant antiferromagnetic interactions, with Neel temperatures of 0.49K for SnCo(BO3)2 and 0.96K for SnMn(BO3)2, respectively. Our results establish the dolomite-type M'M(X)2 (M'and M sites allow various valence states, e.g., +4/+2 or +3/+3; X = CO32- or BO33-) system as a chemically flexible and structurally perfect material platform for exploring frustrated magnetism and low-temperature magnetocaloric applications.

cond-mat.mtrl-sci↗

arXiv2025

Tunable Multistage Refrigeration via Geometrically Frustrated Triangular Lattice Antiferromagnet for Space Cooling

Low-temperature refrigeration technology constitutes a crucial component in space exploration. The small-scale, low-vibration Stirling-type pulse tube refrigerators hold significant application potential for space cooling. However, the efficient operation of current Stirling-type pulse tube cryocoolers in space cooling applications remains challenging due to the rapid decay of the heat capacity of regenerative materials below 10 K. This study adopts a novel material strategy: using a novel high-spin S = 7/2 magnetic regenerative material, Gd2O2Se, we construct a multistage tunable regenerative material structure to achieve an efficient cooling approach to the liquid helium temperature range. Under substantial geometric frustration from a double-layered triangular lattice, it exhibits two-step specific heat transition peaks at 6.22 K and 2.11 K, respectively. Its ultrahigh specific heat and broad two-step transition temperature range effectively bridge the gap between commercially used high-heat-capacity materials. Experimental verification shows that when Gd2O2Se is combined with Er3Ni and HoCu2 in the Stirling-type pulse tube cryocooler, the cooling efficiency of the pulse tube increases by 66.5 % at 7 K, and the minimum achievable temperature reaches 5.85 K. These results indicate that Gd2O2Se is an ideal magnetic regenerative material for space cooling

cond-mat.mtrl-sci↗

arXiv2025

Quantum Fluctuation-enhanced Milli-Kelvin Magnetic Refrigeration in Triangular Lattice Magnet GdBO3

Rare-earth-based triangular lattice antiferromagnets, with strong quantum fluctuations and weak magnetic interactions, can often retain large magnetic entropy down to very low temperatures, making them excellent candidates for magnetic refrigeration at ultra-low temperatures. These materials exhibit a substantial magnetocaloric effect (MCE) due to enhanced spin fluctuations, particularly near quantum critical points, which leads to significant changes in magnetic entropy. This study reports on the crystal growth, structure, magnetism, and MCE of a Gd-based triangular lattice material, GdBO3, characterized by a large spin quantum number (S = 7/2). Successive phase transitions (T1 = 0.52 K, T2 = 0.88 K, and T3 = 1.77 K) were observed in zero-field specific heat measurements. Furthermore, thermal dynamic analysis under external magnetic fields identified five distinct phase regions and three quantum critical points for GdBO3. Due to its broad specific heat features and the high density of magnetic Gd3+ ions, we achieved a minimum temperature of 50 mK near the field-induced quantum critical point, using a custom-designed GdBO3-based adiabatic demagnetization refrigerator. Our findings reveal significant quantum fluctuations below 2 K, demonstrating GdBO3's potential for milli-Kelvin magnetic cooling applications.

cond-mat.str-el↗

arXiv2023

A Regression-based Approach to Robust Estimation and Inference for Genetic Covariance

Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with complex traits, and some variants are shown to be associated with multiple complex traits. Genetic covariance between two traits is defined as the underlying covariance of genetic effects and can be used to measure the shared genetic architecture. The data used to estimate such a genetic covariance can be from the same group or different groups of individuals, and the traits can be of different types or collected based on different study designs. This paper proposes a unified regression-based approach to robust estimation and inference for genetic covariance of general traits that may be associated with genetic variants nonlinearly. The asymptotic properties of the proposed estimator are provided and are shown to be robust under certain model mis-specification. Our method under linear working models provides a robust inference for the narrow-sense genetic covariance, even when both linear models are mis-specified. Numerical experiments are performed to support the theoretical results. Our method is applied to an outbred mice GWAS data set to study the overlapping genetic effects between the behavioral and physiological phenotypes. The real data results reveal interesting genetic covariance among different mice developmental traits.

stat.ME↗