Spin-valley magnetism on the triangular moir\'e lattice with SU(4) breaking interactions

The discovery of correlated insulating states in moir\'e heterostructures has renewed the interest in strongly-coupled electron systems where spin and valley (or layer) degrees of freedom are intertwined. In the strong-coupling limit, such systems can be effectively described by SU(4) spin-valley models akin to Kugel-Khomskii models long studied in the context of spin-orbit coupled materials. However, typical moir\'e heterostructures also exhibit interactions that break the SU(4) symmetry down to SU(2)${}_{\mathrm{spin}}\otimes$U(1)${}_{\mathrm{valley}}$. Here we investigate the impact of such symmetry-breaking couplings on the magnetic phase diagram for triangular superlattices considering a filling of two electrons (or holes) per moir\'e unit cell. We explore a broad regime of couplings -- including XXZ anisotropies, Dzyaloshinskii-Moriya exchange and on-site Hund's couplings -- using semi-classical Monte Carlo simulations. We find a multitude of classically ordered phases, including (anti-)ferromagnetic, incommensurate, and stripe order, manifesting in different sectors of the spin-valley model's parameter space. Zooming in on the regimes where quantum fluctuations are likely to have an effect, we employ pseudo-fermion functional renormalization group (pf-FRG) calculations to resolve quantum disordered ground states such as spin-valley liquids, which we indeed find for certain parameter regimes. As a concrete example, we discuss the case of trilayer graphene aligned with hexagonal boron nitride using material-specific parameters.Comment: 20 pages, 16 figure

TMDs as a platform for spin liquid physics: A strong coupling study of twisted bilayer WSe2_2

The advent of twisted moir\'e heterostructures as a playground for strongly correlated electron physics has led to a plethora of experimental and theoretical efforts seeking to unravel the nature of the emergent superconducting and insulating states. Amongst these layered compositions of two dimensional materials, transition metal dichalcogenides (TMDs) are by now appreciated as highly-tunable platforms to simulate reinforced electronic interactions in the presence of low-energy bands with almost negligible bandwidth. Here, we focus on the twisted homobilayer WSe$_2$ and the insulating phase at half-filling of the flat bands reported therein. More specifically, we explore the possibility of realizing quantum spin liquid (QSL) physics on the basis of a strong coupling description, including up to second nearest neighbor Heisenberg couplings $J_1$ and $J_2$, as well as Dzyaloshinskii-Moriya (DM) interactions. Mapping out the global phase diagram as a function of an out-of-plane displacement field, we indeed find evidence for putative QSL states, albeit only close to SU$(2)$ symmetric points. In the presence of finite DM couplings and XXZ anisotropy, long-range order is predominantly present, with a mix of both commensurate and incommensurate magnetic phases.Comment: 12 pages, 5 figures, supplemental material (3 pages, 1 figure

Basin‐scale estimates of greenhouse gas emissions from the Mara River, Kenya: Importance of discharge, stream size, and land use/land cover

Greenhouse gas fluxes (CO$_2$, CH$_4$, and N$_2$O) from African streams and rivers are under-represented in global datasets, resulting in uncertainties in their contributions to regional and global budgets. We conducted year-long sampling of 59 sites in a nested-catchment design in the Mara River, Kenya in which fluxes were quantified and their underlying controls assessed. We estimated annual basin-scale greenhouse gas emissions from measured in-stream gas concentrations, modeled gas transfer velocities, and determined the sensitivity of up-scaling to discharge. Based on the total annual CO$_2$-equivalent emissions calculated from global warming potentials (GWP), the Mara basin was a net greenhouse gas source (294 ± 35 Gg CO$_2$ eq yr$^{-1}$). Lower-order streams (1–3) contributed 81% of the total fluxes, and higher stream orders (4–8) contributed 19%. Cropland-draining streams also exhibited higher fluxes compared to forested streams. Seasonality in stream discharge affected stream widths (and stream area) and gas exchange rates, strongly influencing the basin-wide annual flux, which was 10 times higher during the high and medium discharge periods than the low discharge period. The basin-wide estimate was underestimated by up to 36% if discharge was ignored, and up to 37% for lower stream orders. Future research should therefore include seasonality in stream surface areas in upscaling procedures to better constrain basin-wide fluxes. Given that agricultural activities are a major factor increasing riverine greenhouse gas fluxes in the study region, increased conversion of forests and agricultural intensification has the possibility of increasing the contribution of the African continent to global greenhouse gas sources

Dynamic simulation of management events for assessing impacts of climate change on pre-alpine grassland productivity

The productivity of permanent temperate cut grasslands is mainly driven by weather, soil characteristics, botanical composition and management. To adapt management to climate change, adjusting the cutting dates to reflect earlier onset of growth and expansion of the vegetation period is particularly important. Simulations of cut grassland productivity under climate change scenarios demands management settings to be dynamically derived from actual plant development rather than using static values derived from current management operations. This is even more important in the alpine region, where the predicted temperature increase is twice as high as compared to the global or Northern Hemispheric average. For this purpose, we developed a dynamic management module that provides timing of cutting and manuring events when running the biogeochemical model LandscapeDNDC. We derived the dynamic management rules from long-term harvest measurements and monitoring data collected at pre-alpine grassland sites located in S Germany and belonging to the TERENO monitoring network. We applied the management module for simulations of two grassland sites covering the period 2011–2100 and driven by scenarios that reflect the two representative concentration pathways (RCP) 4.5 and 8.5 and evaluated yield developments of different management regimes. The management module was able to represent timing of current management operations in high agreement with several years of field observations (r2 > 0.88). Even more, the shift of the first cutting dates scaled to a +1 ◦C temperature increase simulated with the climate change scenarios (− 9.1 to − 17.1 days) compared well to the shift recorded by the German Weather Service (DWD) in the study area from 1991− 2016 (− 9.4 to − 14.0 days). In total, the shift in cutting dates and expansion of the growing season resulted in 1− 2 additional cuts per year until 2100. Thereby, climate change increased yields of up to 6 % and 15 % in the RCP 4.5 and 8.5 scenarios with highest increases mainly found for dynamically adapted grassland management going along with increasing fertilization rates. In contrast, no or only minor yield increases were associated with simulations restricted to fertilization rates of 170 kg N ha− 1 yr− 1 as required by national legislations. Our study also shows that yields significantly decreased in drought years, when soil moisture is limiting plant growth but due to comparable high precipitation and water holding capacity of soils, this was observed mainly in the RCP 8.5 scenario in the last decades of the century

Precursors of Cytochrome Oxidase in Cytochrome-Oxidase-Deficient Cells of Neurospora crassa

Three different cell types of Neurospora crassa deficient in cytochrome oxidase were studied: the nuclear mutant cni-1, the cytoplasmic mutant mi-1 and copper-depleted wild-type cells. * 1. The enzyme-deficient cells have retained a functioning mitochondrial protein synthesis. It accounted for 12–16% of the total protein synthesis of the cell. However, the analysis of mitochondrial translation products by gel electrophoresis revealed that different amounts of individual membrane proteins were synthesized. Especially mutant cni-1 produced large amounts of a small molecular weight translation product, which is barely detectable in wild-type. * 2. Mitochondrial preparations of cytochrome-oxidase-deficient cells were examined for precursors of cytochrome oxidase. The presence of polypeptide components of cytochrome oxidase in the mitochondria was established with specific antibodies. On the other hand, no significant amounts of heme a could be extracted. * 3. Radioactively labelled components of cytochrome oxidase were isolated by immunoprecipitation and analysed by gel electrophoresis. All three cell types contained the enzyme components 4–7, which are translated on cytoplasmic ribosomes. The mitochondrially synthesized components 1–3 were present in mi-1 mutant and in copper-depleted wild-type cells. In contrast, components 2 and 3 were not detectable in the nuclear mutant cni-1. Both relative and absolute amounts of these polypeptides in the enzyme-deficient cells were quite different from those in wild-type cells. * 4. The components of cytochrome oxidase found in the enzyme-deficient cells were tightly associated with the mitochondrial membranes. * 5. Processes, which affect and may control the production of enzyme precursors or their assembly to a functional cytochrome oxidase are discussed

Dinitrogen emissions: an overlooked key component of the N balance of montane grasslands

While emissions of nitric oxide (NO), ammonia (NH₃) and nitrous oxide (N₂O) from grassland soils have been increasingly well constrained, soil dinitrogen (N₂) emissions are poorly understood. However, N₂ losses might dominate total gaseous nitrogen (N) losses. Knowledge on N losses is key for the development of climate-adapted management that balances agronomic and environmental needs. Hence, we quantified all gaseous N losses from a montane grassland in Southern Germany both for ambient climatic conditions and for a climate change treatment (+ 2°C MAT, - 300 mm MAP). Monthly measurements of soil N₂ emissions of intact soil cores revealed that those exceeded by far soil N₂O emissions and averaged at 350 ± 101 (ambient climate) and 738 ± 197 lg N m¯²h¯¹ (climate change). Because these measurements did not allow to quantify emission peaks after fertilization, an additional laboratory experiment was deployed to quantify the response of NH₃, NO, N₂O, and N₂ emissions in sub daily temporal resolution to a typical slurry fertilization event (51 kg N ha¯¹). Our results revealed that total N gas losses amounted to roughly half of applied slurry-N. Surprisingly, N₂ but not NH₃ dominated fertilizer N losses, with N₂ emissions accounting for 16–21 kg or 31–42% of the applied slurry-N, while NH₃ volatilization (3.5 kg), N2O (0.2–0.5 kg) and NO losses (0–0.2 kg) were of minor importance. Though constraining annual N₂ loss remained uncertain due to high spatiotemporal variability of fluxes, we show that N₂ losses are a so far overlooked key component of the N balance in montane grasslands, which needs to be considered for developing improved grassland management strategies targeted at increasing N use efficiency

How to adequately represent biological processes in modeling multifunctionality of arable soils

Essential soil functions such as plant productivity, C storage, nutrient cycling and the storage and purification of water all depend on soil biological processes. Given this insight, it is remarkable that in modeling of these soil functions, the various biological actors usually do not play an explicit role. In this review and perspective paper we analyze the state of the art in modeling these soil functions and how biological processes could more adequately be accounted for. We do this for six different biologically driven processes clusters that are key for understanding soil functions, namely i) turnover of soil organic matter, ii) N cycling, iii) P dynamics, iv) biodegradation of contaminants v) plant disease control and vi) soil structure formation. A major conclusion is that the development of models to predict changes in soil functions at the scale of soil profiles (i.e. pedons) should be better rooted in the underlying biological processes that are known to a large extent. This is prerequisite to arrive at the predictive models that we urgently need under current conditions of Global Change

Compressing the two-particle Green's function using wavelets: Theory and application to the Hubbard atom

Precise algorithms capable of providing controlled solutions in the presence of strong interactions are transforming the landscape of quantum many-body physics. Particularly exciting breakthroughs are enabling the computation of non-zero temperature correlation functions. However, computational challenges arise due to constraints in resources and memory limitations, especially in scenarios involving complex Green's functions and lattice effects. Leveraging the principles of signal processing and data compression, this paper explores the wavelet decomposition as a versatile and efficient method for obtaining compact and resource-efficient representations of the many-body theory of interacting systems. The effectiveness of the wavelet decomposition is illustrated through its application to the representation of generalized susceptibilities and self-energies in a prototypical interacting fermionic system, namely the Hubbard model at half-filling in its atomic limit. These results are the first proof-of-principle application of the wavelet compression within the realm of many-body physics and demonstrate the potential of this wavelet-based compression scheme for understanding the physics of correlated electron systems.Comment: 25 pages, 16 figures, 2 table