The self-compensating compound of Y1-χ CaχBa2-χLaχ Cu3Oy is synthesized through a solid-state reaction method with χ from 0.25 to 0.55. Structural and superconducting properties have been investigated by χ-ray d...The self-compensating compound of Y1-χ CaχBa2-χLaχ Cu3Oy is synthesized through a solid-state reaction method with χ from 0.25 to 0.55. Structural and superconducting properties have been investigated by χ-ray diffraction, Rietveld refinement, and dc magnetization measurement, respectively. The impure peaks appear when χ is more than 0.5 in the diffraction pattern. Orthorhombic-tetragonal transition occurs at χ = 0.45. Some local structural parameters, such as Cu（1）-O（4）, Cu（2）-O（4） bond lengths, change randomly in a narrow range. The relationship between the character of （Ba/La）-O plane and Tc is rather interesting. We attribute the behaviour of superconductivity to the joint effects of these local structural parameters. The results give the evidence that the influence of the structural change on superconductivity is essential and independent of carrier concentration.展开更多
In recent years,iridium oxides have attracted intensive research interests both in experiments and theories due to their comparable energy scales of the Coulomb repulsion and strong spin-orbit coupling(SOC)[1,2],where...In recent years,iridium oxides have attracted intensive research interests both in experiments and theories due to their comparable energy scales of the Coulomb repulsion and strong spin-orbit coupling(SOC)[1,2],where a plenty of novel quantum states such as Weyl semimetal,topological insulator and quantum spin liquid have been studied[3–7].Among the iridates,the layered-perovskite Sr2IrO4(SIO)is a Jeff=1/2 Mott insulating antiferromagnet caused by the interplay of the SOC and electronic correlations[8,9].展开更多
The recent discovery of possible high temperature superconductivity in single crystals of La_(3)Ni_(2)O_(7) under pressure renews the interest in research on nickelates.The density functional theory calculations revea...The recent discovery of possible high temperature superconductivity in single crystals of La_(3)Ni_(2)O_(7) under pressure renews the interest in research on nickelates.The density functional theory calculations reveal that both d_(z^(2)) and d_(x^(2)-y^(2)) orbitals are active,which suggests a minimal two-orbital model to capture the low-energy physics of this system.In this work,we study a bilayer two-orbital t–J model within multiband Gutzwiller approximation,and discuss the magnetism as well as the superconductivity over a wide range of the hole doping.Owing to the inter-orbital super-exchange process between d_(z^(2)) and d_(x^(2)-y^(2)) orbitals,the induced ferromagnetic coupling within layers competes with the conventional antiferromagnetic coupling,and leads to complicated hole doping dependence for the magnetic properties in the system.With increasing hole doping,the system transfers to A-type antiferromagnetic state from the starting G-type antiferromagnetic(G-AFM)state.We also find the inter-layer superconducting pairing of d_(x^(2)-y^(2)) orbitals dominates due to the large hopping parameter ofd_(z^(2)) along the vertical inter-layer bonds and significant Hund’s coupling between d_(z^(2)) and d_(x^(2)-y^(2)) orbitals.Meanwhile,the G-AFM state and superconductivity state can coexist in the low hole doping regime.To take account of the pressure,we also analyze the impacts of inter-layer hopping amplitude on the system properties.展开更多
This study explores the use of neural network-based analytic continuation to extract spectra from Monte Carlo data.We apply this technique to both synthetic and Monte Carlo-generated data.The training sets for neural ...This study explores the use of neural network-based analytic continuation to extract spectra from Monte Carlo data.We apply this technique to both synthetic and Monte Carlo-generated data.The training sets for neural networks are carefully synthesized without“data leakage”.We find that the training set should match the input correlation functions in terms of statistical error properties,such as noise level,noise dependence on imaginary time,and imaginary time-displaced correlations.We have developed a systematic method to synthesize such training datasets.Our improved algorithm outperforms the widely used maximum entropy method in highly noisy situations.As an example,our method successfully extracted the dynamic structure factor of the spin-1/2 Heisenberg chain from quantum Monte Carlo simulations.展开更多
文摘The self-compensating compound of Y1-χ CaχBa2-χLaχ Cu3Oy is synthesized through a solid-state reaction method with χ from 0.25 to 0.55. Structural and superconducting properties have been investigated by χ-ray diffraction, Rietveld refinement, and dc magnetization measurement, respectively. The impure peaks appear when χ is more than 0.5 in the diffraction pattern. Orthorhombic-tetragonal transition occurs at χ = 0.45. Some local structural parameters, such as Cu（1）-O（4）, Cu（2）-O（4） bond lengths, change randomly in a narrow range. The relationship between the character of （Ba/La）-O plane and Tc is rather interesting. We attribute the behaviour of superconductivity to the joint effects of these local structural parameters. The results give the evidence that the influence of the structural change on superconductivity is essential and independent of carrier concentration.
基金the support from the National Key Research and Development Program of China(2016YFA0302300)CAS Interdisciplinary Innovation Team+2 种基金the support from the National Natural Science Foundation of China(11974052)Beijing Natural Science Foundation(Z190008)the beamline 1W1A of Beijing Synchrotron Radiation Facility。
文摘In recent years,iridium oxides have attracted intensive research interests both in experiments and theories due to their comparable energy scales of the Coulomb repulsion and strong spin-orbit coupling(SOC)[1,2],where a plenty of novel quantum states such as Weyl semimetal,topological insulator and quantum spin liquid have been studied[3–7].Among the iridates,the layered-perovskite Sr2IrO4(SIO)is a Jeff=1/2 Mott insulating antiferromagnet caused by the interplay of the SOC and electronic correlations[8,9].
基金supported by the National Natural Science Foundation of China (Grant Nos. 12274004 and 11888101)。
文摘The recent discovery of possible high temperature superconductivity in single crystals of La_(3)Ni_(2)O_(7) under pressure renews the interest in research on nickelates.The density functional theory calculations reveal that both d_(z^(2)) and d_(x^(2)-y^(2)) orbitals are active,which suggests a minimal two-orbital model to capture the low-energy physics of this system.In this work,we study a bilayer two-orbital t–J model within multiband Gutzwiller approximation,and discuss the magnetism as well as the superconductivity over a wide range of the hole doping.Owing to the inter-orbital super-exchange process between d_(z^(2)) and d_(x^(2)-y^(2)) orbitals,the induced ferromagnetic coupling within layers competes with the conventional antiferromagnetic coupling,and leads to complicated hole doping dependence for the magnetic properties in the system.With increasing hole doping,the system transfers to A-type antiferromagnetic state from the starting G-type antiferromagnetic(G-AFM)state.We also find the inter-layer superconducting pairing of d_(x^(2)-y^(2)) orbitals dominates due to the large hopping parameter ofd_(z^(2)) along the vertical inter-layer bonds and significant Hund’s coupling between d_(z^(2)) and d_(x^(2)-y^(2)) orbitals.Meanwhile,the G-AFM state and superconductivity state can coexist in the low hole doping regime.To take account of the pressure,we also analyze the impacts of inter-layer hopping amplitude on the system properties.
基金support from the National Natural Science Foundation of China (Grant Nos. 12274004 and 11888101)
文摘This study explores the use of neural network-based analytic continuation to extract spectra from Monte Carlo data.We apply this technique to both synthetic and Monte Carlo-generated data.The training sets for neural networks are carefully synthesized without“data leakage”.We find that the training set should match the input correlation functions in terms of statistical error properties,such as noise level,noise dependence on imaginary time,and imaginary time-displaced correlations.We have developed a systematic method to synthesize such training datasets.Our improved algorithm outperforms the widely used maximum entropy method in highly noisy situations.As an example,our method successfully extracted the dynamic structure factor of the spin-1/2 Heisenberg chain from quantum Monte Carlo simulations.
