Magnetic fluctuations is the leading candidate for pairing in cuprate, iron-based, and heavy fermion superconductors. This view is challenged by the recent discovery of nodeless superconductivity in CeCu2Si2, and calls for a detailed understanding of the corresponding magnetic fluctuations. Here, we mapped out the magnetic excitations in superconducting (S-type) CeCu2Si2 using inelastic neutron scattering, finding a strongly asymmetric dispersion for E≲1.5meV, which at higher energies evolves into broad columnar magnetic excitations that extend to E≳5meV. While low-energy magnetic excitations exhibit marked three-dimensional characteristics, the high-energy magnetic excitations in CeCu2Si2 are almost two-dimensional, reminiscent of paramagnons found in cuprate and iron-based superconductors. By comparing our experimental findings with calculations in the random-phase approximation,we find that the magnetic excitations in CeCu2Si2 arise from quasiparticles associated with its heavy electron band, which are also responsible for superconductivity. Our results provide a basis for understanding magnetism and superconductivity in CeCu2Si2, and demonstrate the utility of neutron scattering in probing band renormalization in heavy fermion metals.

The parent compounds of iron-based superconductors are magnetically ordered bad metals, with superconductivity appearing near a putative magnetic quantum critical point. The presence of both Hubbard repulsion and Hund's coupling leads to rich physics in these multiorbital systems, and motivated descriptions of magnetism in terms of itinerant electrons or localized spins. The NaFe1-xCuxAs series consists of magnetically ordered bad metal (x=0), superconducting (x≈0.02) and magnetically ordered semiconducing/insulating (x≈0.5) phases, providing a platform to investigate the connection between superconductivity, magnetism and electronic correlations. Here we use x-ray absorption spectroscopy and resonant inelastic x-ray scattering to study the valence state of Fe and spin dynamics in two NaFe1-xCuxAs compounds (x=0 and 0.47). We find that magnetism in both compounds arises from Fe2+ atoms, and exhibits underdamped dispersive spin waves in their respective ordered states. The dispersion of spin excitations in NaFe0.53Cu0.47As is consistent with being quasi-one-dimensional. Compared to NaFeAs, the band top of spin waves in NaFe0.53Cu0.47As is slightly softened with significantly more spectral weight of the spin excitations. Our results indicate the spin dynamics in NaFe0.53Cu0.47As arise from localized magnetic moments and suggest the iron-based superconductors are proximate to a correlated insulating state with localized iron moments.

UNLABELLED: Green spaces may be protective against COVID-19 incidence. They may provide outdoor, ventilated, settings for physical and social activities and therefore decrease transmission risk. We examined the association between neighborhood greenness and COVID-19-like illness incidence using individual-level data. METHODS: The study population includes participants enrolled in the COVID Symptom Study smartphone application in the United Kingdom and the United States (March-November 2020). All participants were encouraged to report their current health condition and suspected risk factors for COVID-19. We used a validated symptom-based classifier that predicts COVID-19-like illness. We estimated the Normalized Difference Vegetation Index (NDVI), for each participants reported neighborhood of residence for each month, using images from Landsat 8 (30 m2). We used time-varying Cox proportional hazards models stratified by age, country, and calendar month at study entry and adjusted for the individual- and neighborhood-level risk factors. RESULTS: We observed 143,340 cases of predicted COVID-19-like illness among 2,794,029 participants. Neighborhood NDVI was associated with a decreased risk of predicted COVID-19-like illness incidence in the fully adjusted model (hazard ratio = 0.965, 95% confidence interval = 0.960, 0.970, per 0.1 NDVI increase). Stratified analyses showed protective associations among U.K. participants but not among U.S. participants. Associations were slightly stronger for White individuals, for individuals living in rural neighborhoods, and for individuals living in high-income neighborhoods compared to individuals living in low-income neighborhoods. CONCLUSIONS: Higher levels of greenness may reduce the risk of predicted COVID-19-like illness incidence, but these associations were not observed in all populations.