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At least 163 records · Page 9

Horizon constraints on holographic Green’s functions

We explore a new class of general properties of thermal holographic Green’s functions that can be deduced from the near-horizon behaviour of classical perturbations in asymptotically anti-de Sitter spacetimes. We show that at negative imaginary Matsubara frequencies and appropriate complex values of the wavenumber the retarded Green’s functions of generic operators are not uniquely defined, due to the lack of a unique ingoing solution for the bulk perturbations. From a boundary perspective these ‘pole-skipping’ points correspond to locations in the complex frequency and momentum planes at which a line of poles of the retarded Green’s function intersects with a line of zeroes. As a consequence the dispersion relations of collective modes in the boundary theory at energy scales ω ~ T are directly constrained by the bulk dynamics near the black-brane horizon. For the case of conserved U(1) current and energy-momentum tensor operators we give examples where the dispersion relations of hydrodynamic modes pass through a succession of poleskipping points as real wavenumber is increased. We discuss implications of our results for transport, hydrodynamics and quantum chaos in holographic systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The age and potential causes of the giant Green Lake Landslide, Fiordland, New Zealand

Abstract Landslide deposits preserved in the geological record afford opportunities to better inform hillslope and seismic hazard and risk models, particularly in regions where observational records are short. In the Southern Alps of New Zealand, small coseismic landslides are frequent, but the geological record preserves several instances of more substantial (> 1 km 3 ) but infrequent mass failures. With an estimated volume of 27 km 3 , the giant Green Lake Landslide represents one of the largest subaerial landslides on Earth. Previous work has suggested this deep-seated mass movement was most likely triggered by high-intensity seismic shaking, but that local structural weakness and/or glacial debuttressing may help to explain the anomalously large failure volume. Resolving the potential contribution of the latter is important given predictions concerning alpine deglaciation in the coming decades to centuries. Key to resolution are secure chronologies of landslide emplacement and past glacier change. Here we present in situ cosmogenic 10 Be exposure ages from the Green Lake Landslide that suggest an emplacement age of 15.5 ± 0.7 ka. Recent work shows that glacial retreat in the region was underway by 19 ka, indicating that the Green Lake Landslide was emplaced 3–4 kyr after the onset of glacier retreat. Given the geometry of the former confining valley glacier, we expect that the deglaciation-landslide age gap is closer to the upper end of this estimate. If correct, this conclusion places greater weight on the roles of local geological structure and/or a great earthquake as factors contributing to the exceptionally large volume of this event.

58 GEOSCIENCES↗

COVID-19 pandemic underscores role of green space in urban carbon dynamics

For Detroit Michigan the arrival of COVID-19 led to intensive measures to prevent further spread of the virus resulting in consequent changes in traffic and energy use. Here, we take advantage of these different emission scenarios to explore CO 2 dynamics in a postindustrial city with a declining population and increasing green space. We present atmospheric CO 2 concentration and net urban ecosystem exchange of CO 2 (NUE) from a typical eddy covariance system and canopy greenness from a field camera on the Wayne State University campus in midtown Detroit. We categorized our study period (January 18, 2020–July 31, 2020) into three subperiods associated with the state-wide shelter-in-place order. Our results support that the city was a net carbon source throughout the period, particularly during the shelter-in-place period, although reduced traffic lowered CO 2 concentrations and NUE. However, during the post-order period when traffic was highest, atmospheric CO 2 concentrations and NUE were lowest, suggesting that the greening of urban vegetation may have greater carbon mitigation potential than lowering anthropogenic carbon emissions through traffic reductions.

54 ENVIRONMENTAL SCIENCES↗

Exploring Micro-Environmental Conditions of Urban Agrivoltaics: Advancing Sustainable Green Spaces and Agriculture in Temperate Cities

Agrivoltaics, the integrated land use combining renewable energy production and agriculture, can potentially address key challenges faced by urban communities, including limited access to vacant land, fresh produce, and electricity. However, urban agrivoltaics has rarely been considered a viable solution, primarily due to a lack of experimental systems demonstrating the functionality of urban food production or green spaces alongside solar energy production. To evaluate the potential of solar photovoltaics to help mitigate heat stress on urban agriculture and green spaces in a temperate climate, we examined the microclimatic changes introduced by an urban agrivoltaics system (UrAV) when combined with vegetable crops and turfgrass, respectively. Accordingly, we installed an experimental setup instrumented with environmental sensors to compare full-sun conditions with those of an agrivoltaics system designed for urban environments. We found minimal differences for both land cover types between the control and agrivoltaics sites in air and soil temperature. However, during periods of intensified summer heat, temperatures beneath the panels cooled due to reductions in wind speed and relative humidity, which impeded the movement of hot, moist air and reduced reference evapotranspiration. Further, soil moisture in UrAV was highly spatially heterogeneous, influenced by the layout of the photovoltaic panels and their support structure, which redistributed rainfall and controlled where solar radiation could penetrate and drive evapotranspiration. Overall, our results suggest that PV-induced environmental changes in temperate climates are compatible with cultivating turfgrass or appropriate crops. These findings can help planners and designers integrate agrivoltaics into community gardens, farms, and green spaces in temperate cities.

14 SOLAR ENERGY↗

Real-time coupled-cluster approach for the cumulant Green's function

Green’s function methods within many-body perturbation theory provide a general framework for treating electronic correlations in excited states. Here we investigate the cumulant form of the one-electron Green’s function based on the coupled-cluster equation of motion approach in an extension of our previous study. The approach yields a non-perturbative expression for the cumulant in terms of the solution to a set of coupled first order, non-linear differential equations. The method thereby adds non-linear corrections to traditional cumulant methods linear in the self energy. The approach is applied to the core-hole Green’s function and illustrated for a number of small molecular systems. For these systems we find that the non-linear contributions lead to significant improvements both for quasiparticle properties such as core-level binding energies, as well as the satellites corresponding to inelastic losses observed in photoemission spectra.

Vila, Fernando D.↗

Emergent Chemical Behavior in Mixed Food and Lignocellulosic Green Waste Hydrothermal Liquefaction

Hydrothermal liquefaction (HTL) is a promising strategy for the conversion of energy-dense waste streams to fuels. Mixed-feed HTL aggregates multiple feed streams to achieve greater scales that capitalize on local resources, hence lowering costs. The potential for new pathways and products upon feedstock blending becomes a compounding level of complexity when unlocking emergent chemistries. Here, food and green waste streams were evaluated under HTL conditions (300 °C, 1 h) to understand the effect of feed molecular composition on product distributions and mechanisms. Thousands of emergent chemical compounds were detected via Fourier transform ion cyclotron resonance mass spectrometry, ultimately leading to the emergence of two dominant outcomes. First, the presence of small amounts of food waste into green waste results in substantial decarboxylation and subsequent polymerization to biocrude than chars. Second, in the other limit, small amounts of green waste promote the capping of oxygenates into the biodiesel range, such as with the emergence of fatty acid methyl esters.

09 BIOMASS FUELS↗

The Green's Function Model Intercomparison Project (GFMIP) Protocol

The atmospheric Green's function method is a technique for modeling the response of the atmosphere to changes in the spatial field of surface temperature. While early studies applied this method to changes in atmospheric circulation, it has also become an important tool to understand changes in radiative feedbacks due to evolving patterns of warming, a phenomenon called the “pattern effect.” To better study this method, this paper presents a protocol for creating atmospheric Green's functions to serve as the basis for a model intercomparison project, GFMIP. The protocol has been developed using a series of sensitivity tests performed with the HadAM3 atmosphere-only general circulation model, along with existing and new simulations from other models. Our preliminary results have uncovered nonlinearities in the response of the atmosphere to surface temperature changes, including an asymmetrical response to warming versus cooling patch perturbations, and a change in the dependence of the response on the magnitude and size of the patches. These nonlinearities suggest that the pattern effect may depend on the heterogeneity of warming as well as its location. These experiments have also revealed tradeoffs in experimental design between patch size, perturbation strength, and the length of control and patch simulations. The protocol chosen on the basis of these experiments balances scientific utility with the simulation time and setup required by the Green's function approach. Running these simulations will further our understanding of many aspects of atmospheric response, from the pattern effect and radiative feedbacks to changes in circulation, cloudiness, and precipitation.

54 ENVIRONMENTAL SCIENCES↗

The role of mixed vibronic Q y -Q x states in green light absorption of light-harvesting complex II

The importance of green light for driving natural photosynthesis has long been underappreciated, however, under the presence of strong illumination, green light actually drives photosynthesis more efficiently than red light. This green light is absorbed by mixed vibronic Q y -Q x states, arising from chlorophyll (Chl)-Chl interactions, although almost nothing is known about these states. Here, we employ polarization-dependent two-dimensional electronic-vibrational spectroscopy to study the origin and dynamics of the mixed vibronic Q y -Q x states of light-harvesting complex II. We show the states in this region dominantly arise from Chl b and demonstrate how it is possible to distinguish between the degree of vibronic Q y versus Q x character. We find that the dynamics for states of predominately Chl b Q y versus Chl b Q x character are markedly different, as excitation persists for significantly longer in the Q x states and there is an oscillatory component to the Q x dynamics, which will be discussed. Our findings demonstrate the central role of electronic-nuclear mixing in efficient light-harvesting and the different functionalities of Chl a and Chl b .

59 BASIC BIOLOGICAL SCIENCES↗

Future increase in compound soil drought-heat extremes exacerbated by vegetation greening

Compound soil drought and heat extremes are expected to occur more frequently with global warming, causing wide-ranging socio-ecological repercussions. Vegetation modulates air temperature and soil moisture through biophysical processes, thereby influencing the occurrence of such extremes. Global vegetation cover is broadly expected to increase under climate change, but it remains unclear whether vegetation greening will alleviate or aggravate future increases in compound soil drought-heat events. Here, using a suite of state-of-the-art model simulations, we show that the projected vegetation greening will increase the frequency of global compound soil drought-heat events, equivalent to 12-21% of the total increment at the end of 21st century. This increase is predominantly driven by reduced albedo and enhanced transpiration associated with increased leaf area. Although greening-induced transpiration enhancement has counteracting cooling and drying effects, the excessive water loss in the early growing season can lead to later soil moisture deficits, amplifying compound soil drought-heat extremes during the subsequent warm season. These changes are most pronounced in northern high latitudes and are dominated by the warming effect of CO 2 . Our study highlights the necessity of integrating vegetation biophysical effects into mitigation and adaptation strategies for addressing compound climate risks.

54 ENVIRONMENTAL SCIENCES↗

Ozone mitigates extended growing season and enhanced vegetation greenness driven by environmental change

Rising temperature and elevated CO 2 concentrations lead to extended growing seasons and enhanced vegetation greenness in terrestrial ecosystems, especially across the Northern Hemisphere. However, whether and to what extent surface ozone, an anthropogenic environmental factor, affects vegetation phenology and greenness remains unexplored at a large scale. Integrating ground-based ozone observations with multiple satellite observations, we demonstrate that surface ozone significantly shortened the growing season by delaying start of season and advancing end of season. Additionally, ozone reduced growing-season vegetation greenness, as reflected in decreased annual accumulated Enhanced Vegetation Index and maximum Enhanced Vegetation Index. These impacts show pronounced spatial heterogeneity, varying in magnitude across the United States, Europe, and China over the past decade, highlighting ozone’s diverse impact on vegetation across regions. Our study predicts that continuously increasing surface ozone concentration will mitigate warming-driven lengthening the growing season by 2 to 4 days, reduce maximum Enhanced Vegetation Index by 0.4% to 8.3%, and reduce annual accumulated Enhanced Vegetation Index by 1.0% to 5.6% in 2050 under Shared Socioeconomic Pathway 5-8.5 scenario. Our findings highlight the imperative need for strategic surface ozone regulation to optimize vegetation health and maximize the capacity for carbon sequestration.

Yin, Hao [Vanderbilt Univ., Nashville, TN (United ↗

Ab initio calculation of X-ray and related core-level spectroscopies: Green's function approaches

X-Ray and related spectroscopies are powerful probes of atomic, vibrational, and electronic structure. In order to unlock the full potential of such experimental techniques, accurate and efficient theoretical and computational approaches are essential. Here we review the status of a variety of first-principles and nearly first principles techniques for X-ray spectroscopies such as X-ray absorption, X-ray emission, and X-ray photoemission, with a focus on Green's function based methods. In particular, we describe the current state of multiple scattering Green's function techniques available in the FEFF10 code and cumulant Green's function techniques for including the effects of many-body electronic excitations. Furthermore, illustrative examples are shown for a variety of materials and compared with other theoretical and experimental results.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Green mechanochemical synthesis of imine-linked covalent organic frameworks for high iodine capture

Covalent organic frameworks (COFs) have emerged as promising adsorbents for radioiodine capture. However, the conventional solvothermal synthesis contradicts the principles of green chemistry due to the use of hazardous solvents, long reaction times (typically 3 days), and high reaction temperatures. Here, to address these issues, we demonstrate for the first time the green, efficient, liquid-assisted mechanochemical synthesis of COF adsorbents for high iodine capture. The ball milling synthesis was performed with various liquid additives at ambient temperature, yielding six imine-linked COFs of diverse pore sizes and functionalities in merely 1 hour. Notably, one representative COF exhibited high crystallinity and a remarkable surface area of 1387 m 2 g –1 in just 1 minute of ball milling. When tested as adsorbents for static iodine vapor capture at 75 °C, four mechanochemically synthesized COFs exhibited outstanding iodine adsorption capacities of 6.4–7.1 g g –1 , comparable to or exceeding those of solvothermally synthesized COF and most reported COF adsorbents. Furthermore, Fourier transform infrared and X-ray photoelectron spectroscopy corroborated the charge transfer between iodine and COF adsorbents. This mechanochemical methodology will pave the path for green, rapid, facile, and scalable synthesis of COFs, revealing great prospects for applications in environmental remediation and beyond.

36 MATERIALS SCIENCE↗

Efficiency droop contributors in InGaN green light emitting diodes

Here, efficiency droop contributors (i.e., inherent Auger–Meitner recombination, polarization-induced effects, thermal effects, and light extraction) in InGaN green light emitting diodes (LEDs) are decoupled and quantified. First, a modified ABC model is developed, and external quantum efficiency measurements are taken under constant and pulsed currents (⁠ EQE Constant and EQE Pulsed ⁠, respectively). The LED internal quantum efficiency with and without thermal effects (⁠ IQE$^{ABC}_{Constant}$ and IQE$^{ABC}_{Pulsed}$⁠, respectively) is extracted using the modified model. Then, using Raman spectroscopy, the LED junction temperature is extracted. Finally, using the optical-electrical model (OEM), the polarization- and temperature-independent LED internal quantum efficiency (⁠ IQE OEM ) is calculated from the modified ABC model and the extracted junction temperature. By comparing external (⁠ EQE Constant ⁠) and the three internal quantum efficiencies (⁠ IQE$^{ABC}_{Constant}$, IQE$^{ABC}_{Pulsed}$⁠, and IQE OEM ), the impacts of inherent Auger–Meitner recombination, polarization-induced effects, thermal effects, and light extraction on the efficiency droop are decoupled and quantified. It is found that inherent Auger–Meitner recombination-induced droop is approximately 49% of the total efficiency droop in commercial green LEDs, while polarization-induced effects contribute about 35%, and thermal droop accounts for nearly 16%. Lastly, these findings suggest, to quash the green gap, it is critical to search for materials and device designs with low inherent Auger–Meitner coefficients and polarization fields, respectively.

42 ENGINEERING↗

Predicting nonequilibrium Green’s function dynamics and photoemission spectra via nonlinear integral operator learning

Understanding the dynamics of nonequilibrium quantum many-body systems is an important research topic in a wide range of fields across condensed matter physics, quantum optics, and high-energy physics. However, numerical studies of large-scale nonequilibrium phenomena in realistic materials face serious challenges due to intrinsic high-dimensionality of quantum many-body problems and the absence of time-invariance. The nonequilibrium properties of many-body systems can be described by the dynamics of the correlator, or the Green's function of the system, whose time evolution is given by a high-dimensional system of integro-differential equations, known as the Kadanoff–Baym equations (KBEs). The time-convolution term in KBEs, which needs to be recalculated at each time step, makes it difficult to perform long-time numerical simulation. In this paper, we develop an operator-learning framework based on recurrent neural networks (RNNs) to address this challenge. We utilize RNNs to learn the nonlinear mapping between Green's functions and convolution integrals in KBEs. By using the learned operators as a surrogate model in the KBE solver, we obtain a general machine-learning scheme for predicting the dynamics of nonequilibrium Green's functions. Besides significant savings per each time step, the new methodology reduces the temporal computational complexity from $O(N_t^3)$ to $O(N_t)$ where N t is the number of steps taken in a simulation, thereby making it possible to study large many-body problems which are currently infeasible with conventional KBE solvers. Through various numerical examples, we demonstrate the effectiveness of the operator-learning based approach in providing accurate predictions of physical observables such as the reduced density matrix and time-resolved photoemission spectra. Moreover, our framework exhibits clear numerical convergence and can be easily parallelized, thereby facilitating many possible further developments and applications.

97 MATHEMATICS AND COMPUTING↗

Purple is the new green: biopigments and spectra of Earth-like purple worlds

ABSTRACT With more than 5500 detected exoplanets, the search for life is entering a new era. Using life on Earth as our guide, we look beyond green landscapes to expand our ability to detect signs of surface life on other worlds. While oxygenic photosynthesis gives rise to modern green landscapes, bacteriochlorophyll-based anoxygenic phototrophs can also colour their habitats and could dominate a much wider range of environments on Earth-like exoplanets. Here, we characterize the reflectance spectra of a collection of purple sulfur and purple non-sulfur bacteria from a variety of anoxic and oxic environments. We present models for Earth-like planets where purple bacteria dominate the surface and show the impact of their signatures on the reflectance spectra of terrestrial exoplanets. Our research provides a new resource to guide the detection of purple bacteria and improves our chances of detecting life on exoplanets with upcoming telescopes. Our biological pigment data base for purple bacteria and the high-resolution spectra of Earth-like planets, including ocean worlds, snowball planets, frozen worlds, and Earth analogues, are available online, providing a tool for modellers and observers to train retrieval algorithms, optimize search strategies, and inform models of Earth-like planets, where purple is the new green.

Coelho, Lígia Fonseca (ORCID:0000000150081249)↗

Detecting Multipartite Entanglement Patterns Using Single-Particle Green’s Functions

Here, we present a protocol for detecting multipartite entanglement in itinerant many-body electronic systems using single-particle Green’s functions. To achieve this, we first establish a connection between the quantum Fisher information and single-particle Green’s functions by constructing a set of witness operators built out of single electron creation and destruction operators in a doubled system. This set of witness operators is indexed by a momentum k. We compute the quantum Fisher information for these witness operators and show that for thermal ensembles it can be expressed as an autoconvolution of the single-particle spectral function. We then apply our framework to a one-dimensional fermionic system to showcase its effectiveness in detecting entanglement in itinerant electron models. We observe that the detected entanglement level is sensitive to the wave vector associated with witness operator. Our protocol will permit detecting entanglement in many-body systems using scanning tunneling microscopy and angle-resolved photoemission spectroscopy, two spectroscopies that measure the single-particle Green’s function. It offers the prospect of the experimental detection of entanglement through spectroscopies beyond the established route of measuring the dynamical spin response.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Barriers to carrier transport in multiple quantum well nitride-based c -plane green light emitting diodes

The presence of alloy disorder in III-nitride materials has been demonstrated to play a significant role in device performance through effects such as carrier localization and carrier transport. Relative to blue light emitting diodes (LEDs), these effects become more severe at green wavelengths. Because of the potential fluctuations that arise due to alloy disorder, full three-dimensional (3D) simulations are necessary to accurately relate materials properties to device performance. We demonstrate experimentally and through simulation that increased quantum well (QW) number in c-plane green LEDs contributes to excess driving voltage, and therefore reduced electrical efficiency. Experimentally, we grew an LED series with the number of QWs varying from one to seven and observed a systematic increase in voltage with the addition of each QW. Trends in LED electrical properties obtained from 3D simulations, which account for the effects of random alloy fluctuations, are in agreement with experimental data. Agreement is achieved without the need for adjusting polarization parameters from their known values. Finally, from these results, we propose that the polarization induced barriers at the GaN/InGaN (lower barrier/QW) interfaces and the sequential filling of QWs both contribute significantly to the excess forward voltage in multiple QW c-plane green LEDs.

42 ENGINEERING↗

Green's functions applied to the theory of spectroscopy

Green’s functions are a powerful analytical and computational tool for ab initio calculations of X-ray spectra. For example, Green’s functions provide an efficient means for calculations over broad energy ranges since many-body effects can be incorporated naturally in terms of the electron self-energy. Here, their role in the theory of X-ray absorption and related spectroscopies is discussed, with particular focus on many-body effects such as quasi-particle energy shifts and lifetimes, core-hole interactions and electron–phonon interactions. Additionally, the cumulant expansion for the Green’s function is reviewed and compared with the usual GW Dyson equation approach for including multielectron excitations that produce satellite features in X-ray spectra.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗