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Impact of increased smoothing by spectral dispersion bandwidth on stimulated Brillouin scattering in laser driven Hohlraums

Experiments were conducted at the National Ignition Facility (NIF) to investigate the impact of increased smoothing by spectral dispersion (SSD) bandwidth on the production of stimulated Brillouin scattering (SBS) within an indirect-drive inertial confinement fusion (ICF) Hohlraum. This was done in a subscale gold Hohlraum driven by 192 laser beams depositing 1.1 MJ of energy. The laser bandwidth was increased from 45 to 118 GHz (before frequency tripling) on the 30° and 50° cones, where backscatter could be measured using the Full Aperture Backscatter Station (FABS). It was expected that this 2.6-fold increase in bandwidth would suppress SBS generated within the Hohlraum plasma and lower the backscattered SBS energy on the 50° cones by over a factor of four. Experimental results, however, show that this SSD change only reduced the 50° cone SBS during the main capsule drive by -18±31% and -4.5±7.8% over the entire pulse. This is small compared to expected shot-to-shot SBS reproducibility (∼30%), such that the result can be considered within normal performance fluctuations. New 3D parallel paraxial code (pF3D) simulations, accounting for beam refractive intensification reproduce this result, suggesting that closer to 300 GHz of bandwidth would have been required to mitigate SBS to the expected level. Delivering such a high bandwidth is not feasible at NIF when operating at high peak power and would potentially prevent NIF’s ability to use cross-beam energy transfer (CBET) for implosion symmetry tuning.

Physics↗

Achieving Higher Order Accuracy in Space in Hydrodynamic Simulations of Self-Gravitating Gas

Modern astrophysical simulation codes employ a variety of numerical algorithms capable of achieving higher-order accuracy in both space and time. Albeit they succeed in achieving an effective higher spatial resolution and in suppressing the numerical damping of waves, to our knowledge, all current astrophysical simulations invoking self-gravity are limited to second-order accuracy in space. If we can devise an algorithm to evaluate self-gravity with a higher-order spatial accuracy, we can better the evaluation of the gravitational acceleration and gravitational energy release which dictate the evolution of many astrophysical systems. Herein, we present a numerical algorithm for self-gravitating hydrodynamics capable of achieving fourth order accuracy for a given density distribution on a Cartesian uniform grid. First, we derive the cell-averaged gravitational potential at fourth-order accuracy from the cell-averaged density by solving the Poisson equation. Next, we obtain the cell average of the product of the density and gravitational acceleration, which differs from the cell-averaged density multiplied by the cell-averaged gravitational acceleration. We then show the verification of the algorithm by applying it to critical test problems: (1) maintaining equilibria of self-gravitating slabs, even upon advection, (2) evolving a polytropic sphere with a massive power-law envelope, and (3) conservation of specific entropy during the propagation of a sound wave.

79 ASTRONOMY AND ASTROPHYSICS↗

FORCE Regression Testing

Via programs including the Light Water Reactor Sustainability and Integrated Energy Systems, the U.S. Department of Energy has invested in the Framework for Optimization of ResourCes and Economics (FORCE) software framework (Idaho National Laboratory 2024a) for the technical and economic analysis of nuclear-integrated energy systems (IES). Nuclear IES expand the use of nuclear from traditional baseload electricity generation to a flexible and adaptive source of combined heat and power. Nuclear heat can be used in the production of a variety of energy currencies such as hydrogen and ammonia as well as other heat applications including water desalination and district heating. FORCE is designed with the intent to provide interconnected analysis tools that enable the accurate technical and economic assessment of specific nuclear IES configurations for individual energy markets. FORCE consists of three main analysis pathways: HYBRID (Idaho National Laboratory 2024b), which contains high-resolution physical models for IES; Holistic Energy Resource Optimization Network (HERON) (Idaho National Laboratory 2024c), which analyzes IES long-term economic viability; and Optimization of Real-time Capacity Allocation (ORCA) (Idaho National Laboratory 2024d), designed for real-time control of IES via digital twins and optimal decision making, including autonomous and remote operation research. Development of the FORCE ecosystem is guided by three pillars: capability, which assures that the computational requirements of IES analysis are met by the software tools; reliability, which provides for consistent code performance and expected behaviors; and accessibility, which lowers the barrier to entry for using the software and accelerates analysis by users beyond the FORCE primary developers. Reliability of the FORCE ecosystem is established according to the American Nuclear Society?s Nuclear Quality Assurance (NQA-1) program [American Society of Mechanical Engineers 1982], with specific levels of software quality assurance (SQA) within NQA-1 applied to each software tool in FORCE. As the tools within FORCE have matured, some integration algorithms to accurately connect the software tools for holistic analysis have been developed and deployed within the FORCE software repository. In accordance with NQA-1 standards, regression tests are required to guarantee the software performs consistently even when new capabilities are added to the software. In this report, we document the deployment of both unit tests, which test the consistent behavior of small pieces of the FORCE code base, as well as integration tests, which test the consistent performance of full use cases for the FORCE integration algorithms. We further document the encapsulation of these tests within a test harness, which collectively checks for each successful test completion on demand. Finally, we document the automation of the test harness using GitHub Actions [GitHub 2024], which require all tests succeed before any new capability or other changes can be added to the FORCE integration software

97 MATHEMATICS AND COMPUTING↗

R&D toward design for a pion-production target for Mu2e-II

The Mu2e experiment at Fermilab will search for evidence of charged lepton flavor violation by observing the conversion of a negative muon into an electron in the Coulomb field of a nucleus without emission of neutrinos and will probe effective new-physics mass scales in the 103-104 TeV range. One of the main parts of the Mu2e experimental setup is its target station in which negative pions are generated in interactions of the 8 GeV primary proton beam with a tungsten target, which will be capable of producing $2\times10^{17}$ negative muons per year. Mu2e can be extended by a next generation experiment, Mu2e-II, with a sensitivity improved by another factor of 10 or more as enabled by the PIP-II accelerator upgrade project. PIP-II is a 250-meter-long linac capable of accelerating a 2 mA proton beam to a kinetic energy of 800 MeV corresponding to 1.6 MW of power. To achieve another factor of ten improvement in sensitivity, Mu2e-II will require about 100 kW of proton beam on target, and the added power requires a new target design. We will present our progress in RD of a target station conceptual design for Mu2e-II, using the MARS15 and G4beamline Monte-Carlo codes toward a selection between granular, conveyor, and rotating cylindrical target options.

Lynch, Kevin Richard↗

Achieving Higher Order Accuracy in Space in Hydrodynamic Simulations of Self-Gravitating Gas

Modern astrophysical simulation codes employ a variety of numerical algorithms capable of achieving higher-order accuracy in both space and time. Albeit they succeed in achieving an effective higher spatial resolution and in suppressing the numerical damping of waves, to our knowledge, all current astrophysical simulations invoking self-gravity are limited to second-order accuracy in space. If we can devise an algorithm to evaluate self-gravity with a higher-order spatial accuracy, we can better the evaluation of the gravitational acceleration and gravitational energy release which dictate the evolution of many astrophysical systems. Herein, we present a numerical algorithm for self-gravitating hydrodynamics capable of achieving fourth-order accuracy for a given density distribution on a Cartesian uniform grid. First, we derive the cell-averaged gravitational potential at fourth-order accuracy from the cell-averaged density by solving the Poisson equation. Next, we obtain the cell average of the product of the density and gravitational acceleration, which differs from the cell-averaged density multiplied by the cell-averaged gravitational acceleration. We then show the verification of the algorithm by applying it to critical test problems: (1) maintaining equilibria of self-gravitating slabs, even upon advection, (2) evolving a polytropic sphere with a massive power-law envelope, and (3) conservation of specific entropy during the propagation of a sound wave.

79 ASTRONOMY AND ASTROPHYSICS↗

Advances in ArborX to support exascale applications

ArborX is a performance portable geometric search library developed as part of the Exascale Computing Project (ECP). In this paper, we explore a collaboration between ArborX and a cosmological simulation code HACC. Large cosmological simulations on exascale platforms encounter a bottleneck due to the in-situ analysis requirements of halo finding, a problem of identifying dense clusters of dark matter (halos). This problem is solved by using a density-based DBSCAN clustering algorithm. With each MPI rank handling hundreds of millions of particles, it is imperative for the DBSCAN implementation to be efficient. In addition, the requirement to support exascale supercomputers from different vendors necessitates performance portability of the algorithm. We describe how this challenge problem guided ArborX development, and enhanced the performance and the scope of the library. We explore the improvements in the basic algorithms for the underlying search index to improve the performance, and describe several implementations of DBSCAN in ArborX. Further, we report the history of the changes in ArborX and their effect on the time to solve a representative benchmark problem, as well as demonstrate the real world impact on production end-to-end cosmology simulations.

97 MATHEMATICS AND COMPUTING↗

Modeling Radionuclide Inventories in MSR Off-Gas Systems with Radiochemical Transport Analysis

Molten salt reactors (MSR) contain unique characteristics that may require enhancements to modeling tools to accurately predict phenomena. One characteristic that may be advantageous to leverage during normal operation is on-line processing of the circulating fuel salt, such as an off-gas system (OGS) to remove volatile fission products. Therefore, new modeling tools must be developed to integrate spatial resolution and chemistry effects into fuel depletion tools to be able to account for these non-core sources of radioactivity. Such types of radiochemical transport analysis tools were used to estimate the removal rates for 12 elements within a flow model of the Molten Salt Reactor Experiment (MSRE) by optimizing against legacy experimental data of the gas-borne (GB) percentages of 12 nuclides. The removal rates were used in a depletion model to calculate the FP inventory that enters the MSRE OGS. Calculations are in good agreement with the empirical GB percentages reported for the 12 nuclides, which validates the approach and verifies each tool’s treatment of the radiochemical flow effects. The OGS inventory is discussed in terms of the largest nuclide contributors to activity, dose consequence, decay heat, and elemental composition. Finally, insights from the study allow recommendations to be made for future code development activities.

Shahbazi, Shayan↗

Enhanced Resistance Pines for Improved Renewable Biofuel and Chemical Production (Technical Report)

We completed phenotyping constitutive and inducible oleoresin flow across two seasons, constitutive resin canal number and density and wood terpene content in our ADEPT2 and CCLONES populations. We completed genetic association between 19 oleoresin phenotypes and a total of 523,192 SNP markers from ADEPT2 and 13,883 SNP markers in CCLONES using four mixed linear models. A total of 293 significant SNPs (FDR = 0.20) were identified. We used the MENTOR tool to mine mechanistic connections from a multiplex network constructed from poplar multi-omic data to construct a conceptual model for a subset of these significant SNPs. Our model contains 6 transcriptional regulators in addition to 3 monoterpene synthases. To generate more lines of evidence for these significant SNPs, we completed a time course RNAseq experiment after inducing vascular zone cells to differentiate into new resin canals with a methyl jasmonate treatment, a single nuclei RNAseq that identified differentiating resin canal epithelial cells and are completing analysis for a QTL study in a hybrid pine population. The time course identified 4634 significantly down and 1890 significantly up regulated transcripts after treatment with methyl jasmonate, an inducer of new resin canal formation in the vascular cambial meristem. To analyze this large set of differentially regulated genes, we created a predictive expression network and analyzed it with random walk restart using 6 seed genes coding for transcription factors regulating xylem differentiation in poplar. Of the top ranked 200 transcripts, 119 transcripts were significant differentially expressed supporting these transcripts as potential candidates regulating resin canal formation. Analysis of single nuclei sequencing of shoot tips that contain differentiating resin canals, identified 10 clusters. One cluster was highly enriched in transcripts coding for 9 of the enzymes in the MEP pathway 3 prenyl synthetases, and 3 monoterpene synthases strongly suggesting that this cluster represents resin canal epithelial cells. We are mining the additional transcripts to create a trajectory analysis. In summary, we have identified > 10 novel genes that are strongly supported candidates for further analysis in breeding lines and for genetic engineering over- and under- expressing lines to increase wood terpene content to improve resistance to insect and fungal pathogens while simultaneously increasing terpene supplies for renewable chemicals and biofuels.

59 BASIC BIOLOGICAL SCIENCES↗

Strategies for thorium fuel cycle transition in the SD-TMSR

Liquid-fueled Molten Salt Reactor (MSR) systems represent advances in safety, economics, and sustainability. The MSR has been designed to operate with a Th/ 233 U fuel cycle with 233 U used as startup fissile material. Since 233 U does not exist in nature, we must examine other available fissile materials to start up these reactor concepts. This work investigates the fuel cycle and neutronics performance of the Single-fluid Double-zone Thorium-based Molten Salt Reactor (SD-TMSR) with different fissile material loadings at startup: High Assay Low Enriched Uranium (HALEU) (19.79%), Pu mixed with HALEU (19.79%), reactor-grade Pu (a mixture of Pu isotopes chemically extracted from Pressurized Water Reactor (PWR) spent nuclear fuel (SNF) with 33 GW d/tHM burnup), transuranic elements (TRU) from Light Water Reactor (LWR) SNF, and 233 U. The MSR burnup routine provided by SERPENT-2 is used to simulate the online reprocessing and refueling in the SD-TMSR. The effective multiplication factor, fuel salt composition evolution, and net production of 233 U are studied in the present work. Additionally, the neutron spectrum shift during the reactor operation is calculated. The results show that the continuous flow of reactorgrade Pu helps transition to the thorium fuel cycle within a relatively short time (≈ 4.5 years) compared to 26 years for 233 U startup fuel. Finally, using TRU as the initial fuel materials offers the possibility of operating the SD-TMSR for an extended period of time (≈ 40 years) without any external feed of 233 U.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Requirements Description of GAMSOR and GAMSRC

This report presents the modeling and simulation capabilities of Argonne National Laboratory’s GAMSOR and GAMSRC code that is used in present reactor analysis activities. These capabilities will then be used to establish the set of verification tasks necessary to verify GAMSOR for use on commercial projects. A similar approach was taken for the PERSENT, REBUS and DIF3D software packages. The GAMSOR program is a modified version of DIF3D used to obtain the coupled neutron gamma flux distributions for a given reactor system. GAMSOR was first developed in the 1980s and its work has progressed in parallel with DIF3D throughout its various development phases. While GAMSOR is compatible with DIF3D-FD and DIF3D-Nodal, DIF3D-VARIANT is most commonly used today and will be the focus of the present verification effort. As covered in [1], GAMSOR was built to provide more accurate heating distributions by explicitly solving for both the gamma and neutron heating distributions. Without this consideration, gamma heat is normally assumed to be deposited locally at the site of gamma production. This is acceptable for modeling some phenomena because the total energy production is preserved, but it can lead to inaccurate approximations of fluence-dependent behaviors such as fuel performance, swelling, cladding embrittlement, radiation induced creep, and power peaking. The outputs from GAMSOR are contained in multiple intermediate and final output files: FIXSRC, VARSRC, GTFLUX, GHFLUX, PWDINT, NPDINT, and GPDINT. DIF3D normally produces a PWDINT file containing power density results, with the assumption that gamma rays are absorbed where they are emitted (i.e., energy deposition is local with no modeled transport). With GAMSOR, neutron power density (NPDINT) and gamma power density (GPDINT) are both produced, with their summed power densities replacing the results in PWDINT for total heating (i.e., recoverable) power density.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Final CRADA Report – NFE-21-08693

TAE Technologies is developing a magnetic fusion energy concept known as the beam-driven field-reversed configuration (FRC) with the ultimate goal of developing a reactor for commercial electricity production capable of burning aneutronic pB11 fuel. To achieve the high plasma temperatures this requires, auxiliary radiofrequency (RF) heating will likely be needed. High Harmonic Fast Wave (HHFW) heating has been identified as a candidate RF heating scheme to overcome the unique challenges posed to RF heating by the FRC, including the large distance from the plasma edge to the last closed flux surface and a magnetic field profile with strength decreasing from edge to core and reversing sign at a null point inside the plasma. The purpose of this project was to develop the experimental capabilities to test HHFW on TAE’s C-2W device through the design of a phased array antenna and accompanying matching network. The design was performed by ORNL and informed by experiments with a prototype four-strap phased antenna-array that was manufactured and installed on the LArge Plasma Device (LAPD) at UCLA and simulations conducted with the Petra-M code under the purview of a previous INFUSE grant. The ORNL team completed the conceptual design of the antenna and matching network which was then handed off to the TAE Mechanical Design team. The design was then iterated on to ensure changes to the mechanical design did not interfere with the RF performance. This process is now complete, and, with mechanical design in hand, TAE is proceeding with plans for final integration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

October 2024 Semiannual Composite Salt Waste Processing Facility (SWPF) Decontaminated Salt Solution (DSS) Toxicity Characteristic Leaching Procedure (TCLP) Results

The aqueous waste from the Salt Waste Processing Facility (SWPF) is sampled semiannually for transfers to the Saltstone Production Facility (SPF). Salt solution is treated at SPF and disposed of in the Saltstone Disposal Facility (SDF). Per request of customer, X-TTR-Z-00027, Revision 0, one SDF waste form (saltstone) sample was prepared in the Savannah River National Laboratory (SRNL) from the SWPF Decontaminated Salt Solution (DSS) Waste Acceptance Criteria (WAC) sample and Z-area premix material for the October 2024 semiannual Toxicity Characteristic Leaching Procedure (TCLP) sample. The sample contained 60:40 (by weight) of slag and fly ash (referred to as the “Cement-Free grout sample”). Results from the technical report support Task 2: ‘Grout Leaching Analyses’ of the Task Technical Request (TTR) prepared by Savannah River Mission Completion (SRMC). At 64 days cured, a sample of the SDF waste form was collected and shipped to a certified laboratory for analysis using the Toxicity Characteristic Leaching Procedure (TCLP). The October 2024 semiannual Cement-Free grout sample met the South Carolina (SC) Code of Regulations for Hazardous Waste Management Regulations (HWMR) 61-79.261.24 and 61-79.268.48 requirements for a non-hazardous waste form with respect to the Resource Conservation and Recovery Act (RCRA) metals and Underlying Hazardous Constituents (UHCs), and met the SPF WAC that was in effect at the time of the sample collection at SWPF.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Application of FARM to an IES scenario within the FORCE ecosystem

The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM supports the HERON software module in the evaluation of the optimal dispatch by evaluating feasible set-points for the different IES unit components. Set-points are required to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). This problem is addressed by adopting a two-stage approach. First, the HERON power dispatcher determines set-points that meet the constraints on the former variables (e.g., power levels and power ramp rate limits). These constraints are called explicit constraints. Then, FARM adjusts these set-points to ensure the respect of the limits on the latter variables given the knowledge of the system physics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). The original version of the FARM software module (FARM-Alpha) was released by Argonne National Laboratory in January 2021. In the latest version of the code released in July 2022 (FARM-Delta), the Reference Governor (RG) algorithm was upgraded to a Multi-Input Multi-Output version from its original Single-Input Single-Output form. The RG algorithm acts to enforce constraints. With this improvement an IES unit is now treated as a single dynamic system from the standpoint of control. The crosstalk among components in an IES unit is now fully considered thereby ensuring a true optimization is obtained for those units that have multiple set-points. In this report, the capabilities of FARM-Delta operating within the FORCE ecosystem are demonstrated for an IES test case. The specific configuration of IES unit for this case was selected by the IES team with consultation from the Advanced Reactor IES Expert Group. A full TEA analysis that invoked HERON, HYBRID, FARM, and RAVEN was performed and serves to demonstrate how the latest modification to FARM algorithms (i.e., state variable selection, state-space matrices derivation, set-point verification) can shape setpoints that might otherwise compromise the health of equipment through accelerated wear and tear. In this specific test case, it was demonstrated that these algorithms ensure a more efficient utilization of steam resources to be shared by two different subsystems, namely Balance of Plant (BOP) and High-Temperature Steam Electrolysis (HTSE). Finally, some code improvements that can further enhance the user-friendliness are suggested.

97 MATHEMATICS AND COMPUTING↗

April 2024 Semiannual Composite Salt Waste Processing Facility (SWPF) Decontaminated Salt Solution (DSS) Toxicity Characteristic Leaching Procedure (TCLP) Results

The aqueous waste from the Salt Waste Processing Facility (SWPF) is sampled semiannually for transfers to the Saltstone Production Facility (SPF). Salt solution is treated at SPF and disposed of in the Saltstone Disposal Facility (SDF). Per request of customer, X-TTR-Z-00027, Revision 0, one SDF waste form (saltstone) sample was prepared in the Savannah River National Laboratory (SRNL) from the SWPF Decontaminated Salt Solution (DSS) Waste Acceptance Criteria (WAC) sample and Z-area premix material for the April 2024 semiannual Toxicity Characteristic Leaching Procedure (TCLP) sample. The sample contained 60:40 (by weight) of slag and fly ash (referred to as the “Cement-Free grout sample”). Results from the technical report support Task 2: ‘Grout Leaching Analyses’ of the Task Technical Request (TTR) prepared by Savannah River Mission Completion (SRMC). After at least 28 days cured, a sample of the SDF waste form was collected and shipped to a certified laboratory for analysis using the Toxicity Characteristic Leaching Procedure (TCLP). The April 2024 semiannual Cement-Free grout sample met the South Carolina (SC) Code of Regulations for Hazardous Waste Management Regulations (HWMR) 61-79.261.24 and 61-79.268.48 requirements for a non-hazardous waste form with respect to the Resource Conservation and Recovery Act (RCRA) metals and Underlying Hazardous Constituents (UHCs), and met the SPF WAC that was in effect at the time of the tank sampling.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Generalizing mkFit and its Application to HL-LHC

mkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both thread- and data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offline workflow of the CMS experiment. The CMS tracking performs a series of iterations, targeting reconstruction of tracks of increasing difficulty after removing hits associated to tracks found in previous iterations. mkFit has been adopted for several of the tracking iterations, which contribute to the majority of reconstructed tracks. When tested in the standard conditions for production jobs, speedups in track pattern recognition are on average of the order of 3.5x for the iterations where it is used (3-7x depending on the iteration). Multiple factors contribute to the observed speedups, including vectorization and a lightweight geometry description, as well as improved memory management and single precision. Efficient vectorization is achieved with both the icc and the gcc (default in CMSSW) compilers and relies on a dedicated library for small matrix operations, Matriplex, which has recently been released in a public repository. While the mkFit geometry description already featured levels of abstraction from the actual Phase-1 CMS tracker, several components of the implementations were still tied to that specific geometry. We have further generalized the geometry description and the configuration of the run-time parameters, in order to enable support for the Phase-2 upgraded tracker geometry for the HL-LHC and potentially other detector configurations. The implementation strategy and high-level code changes required for the HL-LHC geometry are presented. Speedups in track building from mkFit imply that track fitting becomes a comparably time consuming step of the tracking chain.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Unbalancing Symbiotic Nitrogen Fixation: Can We Make Effectiveness More Effective?

One of the most critical uses of carbon fuels is in generating nitrogen fertilizer. Atmospheric dinitrogen is too stable to be used directly by plants, so plants need other chemical forms of nitrogen. Nitrogen fertilizer production uses ~4% of the world’s natural gas. Making N fertilizers leverages methane’s energy content by enabling additional energy to be captured into food and fiber through increased photosynthesis. Manufacturing fertilizer is essential—without it there would only be enough combined nitrogen to feed ~3 billion of the world’s ~7 billion people. How to alter this addiction is not obvious, but the best chance to secure substantial and sustainable amounts of future N might be through symbiotic nitrogen fixation (SNF). SNF describes mutualistic interactions where nitrogen-fixing bacteria provide fixed nitrogen to their plant hosts, freeing them from the need for nitrogen fertilizers. SNF already occurs on a large scale; "biological nitrogen” contributes about 5 Tg N/yr to American agriculture, a quarter of the nitrogen needed. Improving SNF and replacing inorganic fertilizers are both important goals in establishing sustainable and more energy-efficient farming. SNF has been used in agriculture for millennia, largely by using legumes like beans or alfalfa in mixed cropping systems. Legume SNF occurs in root nodules, organs that develop after a growing root is infected by bacteria called rhizobia. In the plant cells of a legume nodule, specialized forms of rhizobia fix nitrogen and can produce enough ammonia to supply the growing plant. The exchange of photosynthetically derived plant carbon compounds for nitrogen reduced by the bacteria is the engine that drives the symbiosis. Important details about the organization of development and metabolism in SNF remain to be determined, such as how plant and bacterial metabolism are coordinated as nitrogen is being fixed and what governs the overall level of nitrogen fixation. Most bacterial mutations that affect SNF completely block fixation (e.g. are Fix – ), providing a limited window into the feedback interactions that must be part of the process. We have investigated an unusual mutant of Sinorhizobium meliloti, a symbiotic partner of alfalfa, that fixes dinitrogen at a normal rate (i.e., it is Fix + ) but is not effective in supporting plant growth (i.e., it is ineffective or Eff – ). We have shown that the mutant has a specific mutation in the glnD gene, which codes for a protein that regulates the bacterial response to nitrogen stress, among other key pathways. A Fix + Eff – phenotype contains an unavoidable puzzle—how is it possible for the bacteria to fix nitrogen at a normal rate and without benefiting the nitrogen starved plant host? After eliminating other possibilities, we proposed that the bacteria synthesize a nitrogen-containing compound that the plant can’t use so that acquiring this compound does not relieve plant nitrogen stress. Extracts of nodules made by glnD mutant strains have high concentrations of pyruvate canaline oxime (PCO), a derivative of the plant defensive compound canaline, a toxic analog of ornithine, an amino acid. Many legumes produce canaline and the related arginine mimic canavanine. For reasons we do not yet understand, the mutation in glnD appears to trigger significant overproduction of canaline in a defense response that leads to substantial synthesis of PCO. We expected the bacteria to be able to use PCO, but we have not been able to grow S. meliloti on PCO under several conditions. PCO thus appears to be a metabolic dead end for both the plant and bacteria. We also examined bacterial catabolic pathways that degrade arginine and canavanine and showed that mutation of these did not alter the symbiosis in an obvious way. In related experiments to examine the metabolic development of root nodules, we carried out an ambitious experiment to simultaneously measure metabolites and protein changes during nodule maturation. For these experiments we used a related symbiotic interaction between S. medicae and Medicago truncatula. M. truncatula has a simpler genome than alfalfa so we could identify plant proteins based on predictions from the DNA sequence. Nodules formed on Medicago grow linearly, with the least mature tissues at the tip. Because development of nitrogen fixation is accompanied by the production of the pigmented plant oxygen carrier protein leghemoglobin, we were able to locate and manually separate the tip, transitional, and mature nitrogen-fixing regions from each other. Advances in proteomic and metabolomic techniques allowed us to analyze these tissues from a pool of as few as 10 nodules. We observed correlated transitions of various enzymes in the plant and bacterial proteomes from those characteristic of free-living metabolism to the microaerobic metabolism of the nitrogen-fixing tissues. The metabolome could not be separated into plant and bacterial domains but was consistent with this overall transition. A subsequent paper examined proteolysis in nodule bacteria. Protein turnover in mature regions of the nodule is significant. We were able to show complexes between various proteins and important proteases, using precipitation capture techniques to isolate the proteases and sensitive proteomic analysis to reveal the associated proteins.

09 BIOMASS FUELS↗

Anomaly inflow, dualities, and quantum simulation of Abelian lattice gauge theories induced by measurements

Previous work [] has demonstrated that quantum simulation of Abelian lattice gauge theories (Wegner models including the toric code in a limit) in general dimensions can be achieved by local adaptive measurements on symmetry-protected topological (SPT) states with higher-form generalized global symmetries. The entanglement structure of the resource SPT state reflects the geometric structure of the gauge theory. In this work we explicitly demonstrate the anomaly inflow mechanism between the deconfining phase of the simulated gauge theory on the boundary and the SPT state in the bulk by showing that the anomalous gauge variation of the boundary state obtained by bulk measurement matches that of the bulk theory. Moreover, we construct the resource state and the measurement pattern for the measurement-based quantum simulation of a lattice gauge theory with a matter field (Fradkin-Shenker model), where a simple scheme to protect gauge invariance of the simulated state against errors is proposed. We further consider taking an overlap between the wave function of the resource state for lattice gauge theories and that of a parameterized product state, and we derive precise dualities between partition functions with insertion of defects corresponding to gauging higher-form global symmetries, as well as measurement-induced phases where states induced by a partial overlap possess different (symmetry-protected) topological orders. Measurement-assisted operators to dualize quantum Hamiltonians of lattice gauge theories and their noninvertibility are also presented. Published by the American Physical Society 2024

Okuda, Takuya↗

Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model

Abstract. Comprehensive assessment of climate datasets is important for communicating model projections and associated uncertainties to stakeholders. Uncertainties can arise not only from assumptions and biases within the model but also from external factors such as computational constraint and data processing. To understand sources of uncertainties in global variable-resolution (VR) dynamical downscaling, we produced a regional climate dataset using the Model for Prediction Across Scales (MPAS; dynamical core version 4.0) coupled to the Community Atmosphere Model (CAM; version 5.4), which we refer to as CAM–MPAS hereafter. This document provides technical details of the model configuration, simulations, computational requirements, post-processing, and data archive of the experimental CAM–MPAS downscaling data. The CAM–MPAS model is configured with VR meshes featuring higher resolutions over North America as well as quasi-uniform-resolution meshes across the globe. The dataset includes multiple uniform- (240 and 120 km) and variable-resolution (50–200, 25–100, and 12–46 km) simulations for both the present-day (1990–2010) and future (2080–2100) periods, closely following the protocol of the North American Coordinated Regional Climate Downscaling Experiment. A deviation from the protocol is the pseudo-warming experiment for the future period, using the ocean boundary conditions produced by adding the sea surface temperature and sea-ice changes from the low-resolution version of the Max Planck Institute Earth System Model (MPI-ESM-LR) in the Coupled Model Intercomparison Project Phase 5 to the present-day ocean state from a reanalysis product. Some unique aspects of global VR models are evaluated to provide background knowledge to data users and to explore good practices for modelers who use VR models for regional downscaling. In the coarse-resolution domain, strong resolution sensitivity of the hydrological cycles exists over the tropics but does not appear to affect the midlatitude circulations in the Northern Hemisphere, including the downscaling target of North America. The pseudo-warming experiment leads to similar responses of large-scale circulations to the imposed radiative and boundary forcings in the CAM–MPAS and MPI-ESM-LR models, but their climatological states in the historical period differ over various regions, including North America. Such differences are carried to the future period, suggesting the importance of the base state climatology. Within the refined domain, precipitation statistics improve with higher resolutions, and such statistical inference is verified to be negligibly influenced by horizontal remapping during post-processing. Limited (≈50 % slower) throughput of the current code is found on a recent many-core/wide-vector high-performance computing system, which limits the lengths of the 12–46 km simulations and indirectly affects sampling uncertainty. Our experience shows that global and technical aspects of the VR downscaling framework require further investigations to reduce uncertainties for regional climate projection.

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