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The Dark Energy Spectrographic Instrument (DESI) Optical Fiber System

The specific research of the DESI project is to study in detail the expansion history of the Universe over the past 10 billion years. In order to do this, the project designed, fabricated, tested and commissioned the DESI instrument which has been deployed at the Mayall Telescope at the Kitt Peak National Observatory near Tucson, Arizona. The DESI project was conducted by approximately 30 US and foreign national laboratories. The complete instrument includes a prime focus corrector assembly, a focal plane with 5,000 optical fibers whose position can be set by robotic positioners, and ten spectrographs. Each spectrograph can accommodate the light from 500 fibers and include three color channels that are illuminated by a common collimator mirror and other planar transfer optics. In order for this entire system to work, optical fibers are required to connect each positioner to the spectrographs. Our CRADA with Durham University in the UK provided the 10 crucial fiber cables required to connect the DESI focal plane to the 10 spectrographs. The key major goals of this CRADA were achieved. Survey planning was another key component to the Durham contribution. Drs. Frenk, Baugh, Cole, Edge, Lacey, Li, Lucey, Massey, Metcalfe, Norberg and Shanks were all important contributors to the working groups to which they were assigned. Their work to implement emission lines and QSO in lightcone mocks, mocks for non-standard cosmologies/modified gravity, optimization of completeness of BGS in crowded regions and extended source photometry have been vital in the early planning for targets during commissioning. The major role in the project involved Dr. Ray Sharples and his team. They provided a significant portion of the design, fabrication and testing of the optical fiber system. In particular, they were responsible for the design, production of engineering drawings, component procurements, and fabrication of the 10 DESI Science fiber cables. Working in close collaboration with Dr. Claire Poppett, they also designed and fabricated the slit assemblies, the specialized termination of the groups of 500 fibers which plug into the spectrographs.

47 OTHER INSTRUMENTATION↗

Advanced modeling and simulation of research reactors using dynamic mode decomposition

Full text of publication follows. Due to the ever-increasing safety requirements, the current trend of nuclear reactor analysis is shifting towards high-fidelity multi-physics models, which have a very high computational cost and modelling complexity. As the cost of even a single model run makes it impossible to analyse the behaviour and performance of these models on large-scale commercial plants, it has become even more significant to provide suitable benchmarks to validate and test them extensively. In this sense, research reactors offer a promising solution for the initial validation of high-fidelity models, as they are significantly smaller than commercial reactors and their characteristics are well known. In particular, the reactors of the TRIGA family have been used to assess and validate models and methods for Generation-IV designs, as they have some similar features (such as the dominance of natural convection as cooling mechanism and the difficulties in performing sub-channel analysis using standard codes). Still, the computational requirements of high-fidelity models make them unsuitable for real-time analysis, even following their assessment on research reactors. In this sense, Model Order Reduction (MOR) techniques give an additional strategy to reduce the computational cost of high-fidelity models (whilst preserving sufficient accuracy). In particular, this work focuses on Dynamic Mode Decomposition (DMD), a non-intrusive MOR technique that aims at representing models with explicit temporal dynamics by extracting the time-varying characteristics and the governing structures based only on a set of available data, thus without needing any underlying knowledge of the governing equations. In addition, DMD also computes a low-dimensional surrogate of the dynamic matrix of the system, making it suited for stability analysis and real-time evaluations. This work focuses on the application and validation of the DMD method on the Computational Fluid-Dynamics (CFD) model TRIGA Mark II reactor, also discussing in detail the potentiality of this algorithm as an advanced modelling tool for nuclear reactor analysis. (author)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Removing the Cloak of Secrecy from Legacy Cleanup at Los Alamos national Laboratory - 20395

With the establishment in 2018 of the Los Alamos Legacy Cleanup Contract, the Department of Energy's (DOE) Environmental Management Los Alamos Field Office (EM-LA) and its contractor Newport News Nuclear BWXT Los Alamos (N3B) embarked on an expansive program to engage a broad range of local and regional stakeholders in the decision-making process for cleanup of legacy wastes (pre-1999) at the Los Alamos National Laboratory (LANL). From the inception of LANL during the Manhattan Project until the issuance of the new cleanup contract, the site was managed by a single management and operations (M and O) contactor whose main focus was national security. Segmenting from laboratory operations a separate cleanup contract managed by DoE's Office of Environmental Management (EM) brought new opportunities for the cleanup of legacy waste. That change likewise has opened new opportunities for engaging the community on legacy cleanup decisions. The new legacy cleanup contract - an unclassified contract - emphasizes public outreach, marking a cultural shift in how stakeholders in Los Alamos and throughout northern New Mexico are engaged. Without the constraints of classified work, EM-LA and N3B have increased the level of transparency with the public regarding cleanup activities. EM-LA and N3B have crafted an approach that best meets the values, priorities and needs of the neighboring communities by adapting the model successfully employed at Rocky Flats. Through enhanced stakeholder involvement, EM-LA will implement decisions that have considered broad input and deliver a safe and efficient cleanup of the site. EM-LA and N3B began the expanded stakeholder outreach program in January 2019, leading up to four Environmental Management Cleanup Forums held in the summer of 2019. EM-LA and N3B are now in the process of initiating a series of meetings with various stakeholder groups to determine their 'values' as they relate to cleanup using a novel approach that elicits and records values. The entire process is documented, ensuring that should questions arise about how, when and why decisions were made, they can be easily addressed. In addition to other public meetings to present cleanup scenarios and solicit active public involvement in cleanup decisions, the EM-LA and N3B approach involves discussions with stakeholders who want to explore specific technical issues and cleanup discussions in depth. EM-LA and N3B are also evaluating and implementing a variety of communications tools to help ensure the engagement plan sets the gold standard for transparency in legacy cleanup and stakeholder involvement. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Field retrieved photovoltaic backsheet survey from diverse climate zones: Analysis of degradation patterns and phenomena

Understanding the impact of climate stressors on photovoltaic (PV) backsheet degradation in real-use conditions is critical to improve the accelerated testing exposures, extend the backsheet lifetime, and increase the confidence in PV reliability. Here, in this work, a total of 33 PV module backsheets were retrieved from six climatic zones worldwide with 2 - 28 years of exposure. These modules included five types of backsheet air-side materials (or outer layer): poly(vinylidene fluoride) (PVDF), poly(tetrafluoroethylene-co-hexafluoropropylene-co-vinylidene fluoride) (THV), poly(vinyl fluoride) (PVF), poly(ethylene terephthalate) (PET), and polyamide (PA). Attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR) was used to identify air-side materials. The degradation induced color change, gloss loss, and chemical material changes analyzed using optical microscopy, differential scanning calorimetry (DSC), scanning electron microscopy (SEM), colorimetry (yellowness index (YI)), and gloss measurements. PVDF, THV, and PVF air-side layer backsheets, in particular PVF, had minimal degradation in the air-side layer appearance and chemical structures after exposure in different climatic zones. The PET air-side backsheets exhibited obvious color increase (22.55 YI units after about 9 years exposure) and the PA/PA/PA backsheets showed large gloss loss (up to 76.4 %) relative to the unexposed backsheets. Severe cracks between cells that penetrated through the entire thickness of backsheets are observed on PA/PA/PA backsheets after 4-6 years of exposure in 6 climatic zones. The current indoor exposure standards were not sufficient to identify this degradation type. However, fluoropolymer based PV backsheets showed lower levels of degradation predictors and increased climatic resistance. Specific samples (PVF) showed little change from baseline after 28 years of outdoor exposure.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

High-dimensional isotomics, part 2: Observations of over 100 constraints on methionine's isotome

The abundances of different isotopic forms of a compound, or isotopologues, will vary based on its physical and chemical history. The number of isotopologues increases combinatorically with the size of a molecule, and even small molecules such as amino acids have thousands of potentially observable isotopic variants. However, due to the analytical challenges of separating and observing isotopologues, only a few dimensions of isotopic diversity are routinely measured. Overcoming these challenges requires both an experimental method to observe many isotopic properties and a theoretical framework for interpreting these experiments. In Part 1, we presented such a theoretical framework; here, we demonstrate an experimental method, which we apply to methionine. Our approach uses a Q Exactive HF Orbitrap to perform several “M + N experiments”, where a sample is ionized, a subset of its isotopologues with cardinal mass N daltons greater than the unsubstituted isotopologue is selected and fragmented, and the proportions of all detectable isotopic forms of those fragment ions are quantified. We perform M + 1, M + 2, M + 3, and M + 4 experiments of a methionine sample and standard where the sample has a 100 ‰ enrichment of 13C at the methyl carbon relative to the natural 13C abundance at that position in the standard, and is otherwise identical to the standard. We observe isotopic forms of 8 fragment ion species for each version of the M + N experiment. With the assistance of a forward model of expected mass spectra, we identify isotopic peaks for each fragment ion based on observed mass and abundance, screen these for data quality, and quantify abundances for 146 unique isotopic peaks at precisions of ≈ 0.3–3 ‰. We present our direct observations and use them to reconstruct the concentrations of 19 individual singly, doubly, and triply-substituted isotopologues; doing so gives fewer constraints and broader error bars than working with the direct observations, but may be more interpretable for some applications. We also examine possibilities for measuring additional peaks, which are primarily limited by the detection limit of the Orbitrap-IRMS method. We then suggest some possible uses of our direct measurements for chemical forensics and hypothesis testing. Furthermore, our results demonstrate the diversity of isotopic constraints currently observable and interpretable for organic molecules.

58 GEOSCIENCES↗

Accelerated computation of lattice thermal conductivity using neural network interatomic potentials

We report with the development of the density functional theory (DFT) and ever-increasing computational capacity, an accurate prediction of lattice thermal conductivity based on the Boltzmann transport theory becomes computationally feasible, contributing to a fundamental understanding of thermal conductivity as well as a choice of the optimal materials for specific applications. However, steep costs in evaluating third-order force constants limit the theoretical investigation to crystals with high symmetry and few atoms in the unit cell. Currently, machine learning potentials are garnering attention as a computationally efficient high-fidelity model of DFT, and several studies have demonstrated that the lattice thermal conductivity could be computed accurately via the machine learning potentials. However, test materials were mostly crystals with high symmetries, and the applicability of machine learning potentials to a wide range of materials has yet to be demonstrated. Furthermore, establishing a standard training set that provides consistent accuracy and computational efficiencies across a wide range of materials would be useful. To address these issues, herein we compute lattice thermal conductivities at 300 K using neural network interatomic potentials. As test materials, we select 25 materials with diverse symmetries and a wide range of lattice thermal conductivities between 10 -1 and 10 3 Wm -1 K -1 . Among various choices of training sets, we find that molecular dynamics trajectories at 50–700 K consistently provide results at par with DFT for the test materials. In contrast to pure DFT approaches, the computational cost in the present approach is uniform over the test materials, yielding a speed gain of 2–10 folds. When a smaller reduced training set is used, the relative efficiency increases by up to ~50 folds without sacrificing accuracy significantly. The current work will broaden the application scope of machine learning potentials by establishing a robust framework for accurately computing lattice thermal conductivity with machine learning potentials.

36 MATERIALS SCIENCE↗

Development of Direct Injection/Ionization Mass Spectrometry Methods for Whole Molecule Characterization

The objective of this work is to adapt ambient ionization mass spectrometry (AMS) techniques for the rapid analysis of intact uranium complexes, stable strontium, cerium, and explosive compounds. The methods used were “soft ionization” techniques, which facilitate the detection of whole molecule complexes. The soft ionization mass spectrometry (MS) techniques that were investigated include paper spray ionization (PSI), matrix-assisted ionization (MAI), electrospray ionization (ESI) and direct analysis in real time (DART). For the first time, PSI-MS methods were successfully developed for whole molecule uranium-containing analytes (uranyl acetate, uranyl nitrate, and uranyl-tributylphosphate complexes). This was also the first demonstration of uranium complex detection and characterization and one of the few examples of inorganic analysis using MAI techniques. Proof of concept experiments also putatively identified matrix-derived ions and ion complexes that have not previously been described in the literature. Additionally, PSI-MS on cotton swipe samples doped with a multi-element standard containing μg levels of U, Bi, Pb, Cd, Fe, and Zn were directly analyzed without purification, representing a major improvement over existing methods. Both PSI and MAI methods demonstrated limits of detection (LODs) in the 10 - 100’s ng for various uranyl species within a range of 10’s ppm - 100’s ppb, dependent on analytical method and analyte species. AMS methods were also developed for other inorganics, including Ce and Sr, and organic explosive residues to address specific challenges in environmental monitoring and forensics. Further refinement and qualification of the AMS techniques developed within this effort would lead to significant cost reduction and timeliness by facilitating the triage and queueing of samples for subsequent more sensitive and time-consuming analyses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The Role of Strong Magnetic Fields in Stabilizing Highly Luminous Thin Disks

Abstract We present and analyze a set of three-dimensional, global, general relativistic radiation magnetohydrodynamic simulations of thin, radiation-pressure-dominated accretion disks surrounding a nonrotating, stellar-mass black hole. The simulations are initialized using the Shakura–Sunyaev model with a mass accretion rate of M ̇ = 3 L Edd / c 2 (corresponding to L = 0.17 L Edd ). Our previous work demonstrated that such disks are thermally unstable when accretion is driven by an α -viscosity. In the present work, we test the hypothesis that strong magnetic fields can both drive accretion through magnetorotational instability and restore stability to such disks. We test four initial magnetic field configurations: (1) a zero-net-flux case with a single, radially extended set of magnetic field loops (dipole), (2) a zero-net-flux case with two radially extended sets of magnetic field loops of opposite polarity stacked vertically (quadrupole), (3) a zero-net-flux case with multiple radially concentric rings of alternating polarity (multiloop), and (4) a net-flux, vertical magnetic field configuration (vertical). In all cases, the fields are initially weak, with a gas-to-magnetic pressure ratio ≳100. Based on the results of these simulations, we find that the dipole and multiloop configurations remain thermally unstable like their α -viscosity counterpart, in our case collapsing vertically on the local thermal timescale and never fully recovering. The vertical case, on the other hand, stabilizes and remains so for the duration of our tests (many thermal timescales). The quadrupole case is intermediate, showing signs of both stability and instability. The key stabilizing factor is the ability of specific field configurations to build up and sustain strong, P mag ≳ 0.5 P tot , toroidal fields near the midplane of the disk. We discuss the reasons why certain configurations are able to do this effectively and others are not. We then compare our stable simulations to the standard Shakura–Sunyaev disk.

79 ASTRONOMY AND ASTROPHYSICS↗

Lessons from the IEC Durability of Adhesion Accelerated Test Sequence

The IEC 62788-1-1 and IEC 63209-2 standards use aging sequences for durability of adhesion in photovoltaic (PV) modules, which may be evaluated using the single cantilever beam (SCB) test. Because the encapsulant forms critical interfaces with the front glass and solar cells, degradation at those interfaces under ultraviolet (UV) exposure, elevated temperature, and humidity can lead to interfacial delamination - compromising the long-term reliability. In this work, adhesion durability of UV-transmitting poly(ethylene-co-vinyl acetate) (EVA) encapsulant to glass and to silicon solar cells is evaluated after sequenced UV and damp heat aging (85C/85%RH). Laminates were prepared using StarPhire solar front glass with thin glass or PERC cells, and two EVA formulations with different concentrations of siloxane coupling agent. Adhesion was quantified by measuring critical debond energy using the SCB method. Both formulations exhibit similar qualitative trends, while different adhesion is observed at the periphery despite the use of low-shrink manufacturing. The results show that while glass/EVA adhesion remains stable or increases after UV exposure and shows only moderate changes after damp heat, the EVA/cell interface exhibits an irreversible loss of adhesion following UV and then damp heat exposure. Although glass/EVA interfaces generally exhibit lower debond energies, the EVA/cell interface is significantly more vulnerable to UV-driven degradation, identifying it as the dominant reliability risk location through early- and intermediate-module life. These results demonstrate that accelerated aging sequences can expose large, interface-specific losses in adhesion durability and underscore the importance of interface engineering for long-term PV module reliability.

14 SOLAR ENERGY↗

Restoration Hydro: A Watershed Approach to Standard Modular New Hydropower

The objectives of FOA DE- FOA-0001836- “Standard Modular Hydropower” included designing a standardized, modular, and environmentally compatible hydropower schematic for implementation in greenfield sites that generate up to 10 MW of capacity. Utilizing funds competitively awarded under DOE’s Water Power Technologies Office, the Natel Energy team developed a concept for modular new stream reach (NSR) hydropower that incorporates multi species upstream and downstream fish passage, improved river channel connectivity, and recreational modules. The in-stream design of the collective modules minimized site specific design and maximized the opportunities for modularity. Financial data was also presented using actual costs from regional suppliers, with figures provided in 2022 dollars. While the project team did not address potential permitting process improvements, the site selection criteria did consider established barriers to hydropower development such as tribal and preserved lands, interconnection proximity, and endangered species to exclude or deprioritize. The project’s design schematic met the objectives of the FOA, and presented a unique solution that targets alluvial pockets as natural features for sustainable development. Natel’s concept also incorporated the company's fish-safe Restoration Hydro Turbine for safe downstream passage, while featuring a rock arch that integrates fish passage, water, recreation, and grade control modules (including sediment). Alignment with the Department of Energy Office of Energy Efficiency and Renewable Energy (EERE) “Innovative Design Concepts for Standard Modular Hydropower and Pumped-Storage Hydropower” Program: According to the Hydropower Vision (DOE, 2016), approximately 16 GW of hydropower growth is possible with the development of technology solutions that balance efficiency, economics, and environmental sustainability. The desired outcome of the SMH program is transformational innovation specifically in the site identification, conceptual, and detailed design phases of technology development lifecycles (DOE, 2018). In developing the SMH design schematic, the team aimed to address the opportunities outlined in the Vision through an inverted design philosophy; rather than singularly prioritizing efficiency and power production, the team focused on integrating hydropower with restoration of degraded streams to optimal ecosystem function and provision of exceptional recreation value as design criteria. To achieve this, Restoration Hydro incorporates the principles of nature-based engineering (WWAP, 2018) and biomimicry (Biomimicry NL.) to strategically deploy complementary combinations of permanent, semi-permanent, and ephemeral low-head structures - such as natural and engineered log jams - that harness geomorphological and hydrological processes at the landscape-scale. Primary applications of Restoration Hydro include: 1) restoration of degraded watersheds’ natural ecological function and enhancement of hydrological connectivity; and 2) creation of associated co-benefits to hydro production, including increased groundwater recharge, improved sediment transport and management, improved water security and water quality. Restoration Hydro projects build upon proven watershed restoration engineering techniques by integrating hydropower turbines into low-head structures using innovative and evolving civil works concepts that facilitate fish and sediment passage, and in some cases create additional revenue-generating recreational opportunities. Powering low-head structures creates a directly monetizable layer of economic value in the form of flexible, reliable, renewable energy on top of the already high-value water, environmental and recreational benefits of watershed and river restoration. The approach aims to create a virtuous, self-reinforcing cycle whereby Restoration Hydro projects support the scaling of ecosystem restoration activities, creating a water-energy-carbon multiplier effect that, through the principles of adaptive change management: 1) improves the resilience of landscapes and downstream population centers for changing hydrological cycles; 2) creates a reliable energy resource that facilitates the integration of intermittent renewable power sources into grids; and 3) supports climate change mitigation through grid decarbonization and enhanced ecosystem carbon capture and retention.

13 HYDRO ENERGY↗

Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads

Abstract. Floating wind turbines must withstand a unique and challenging set of loads from the wind and ocean environment. To de-risk development, accurate predictions of these loads are necessary. Uncertainty in modeling predictions leads to larger required safety factors, increasing project costs and the levelized cost of energy. Complex aero-hydro-elastic modeling tools use many input parameters to represent the wind, waves, current, aerodynamic loads, hydrodynamic loads, and structural properties. It is helpful to understand which of these parameters ultimately drives a design. In this work, an ultimate and fatigue-proxy load sensitivity analysis was performed with 35 different input parameters, using an elementary effects approach to identify the most influential parameters for a case study involving the National Renewable Energy Laboratory (NREL) 5 MW baseline wind turbine atop the OC4-DeepCwind semisubmersible during normal operation. The importance of each parameter was evaluated using 14 response quantities of interest across three operational wind speed conditions. The study concludes that turbulent wind velocity standard deviation is the parameter with the strongest sensitivity; this value is important not just for turbine loads, but also for the global system response. The system center of mass in the wind direction is found to have the highest impact on the system rotation and tower loads. The current velocity is found to be the most dominating parameter for the system global motion and consequently the mooring loads. All tested wind turbulence parameters in addition to the standard deviation are also found to be influential. Wave characteristics are influential for some fatigue-proxy loading but do not significantly impact the extreme ultimate loads in these operational load cases. The required number of random seeds for stochastic environmental conditions is considered to ensure that the sensitivities are due to the input parameters and not due to the seed. The required number of analysis points in the parameter space is identified so that the conclusions represent a global sensitivity. The results are specific to the platform, turbine, and choice of parameter ranges, but the demonstrated approach can be applied widely to guide focus in parameter uncertainty.

17 WIND ENERGY↗

The scale of superpartner masses and electroweakino searches at the high-luminosity LHC

Searches for weakly interacting particles is one of the main goals of the high luminosity LHC run. In this work we study the well motivated cases of electroweakinos with mostly Wino and Bino components. We show the relevance of squark induced t-channel production in defining the production cross section and hence the LHC reach. Moreover, a realistic evaluation of the decay branching ratios show a strong dependence on the sign of μ and, for negative values of μ, on the relative size of the ratio of μ to the gaugino masses compared with tan β. Overall, unless it is kinematically suppressed, or specific conditions are fulfilled, the Higgs decay channel is the most significant one, and the trilepton channel becomes subdominant with respect to final states including bottom quarks. Although the properties are different than in the Higgsino-Bino case, also in this case the discovery reach extends to mass values that are significantly larger than the ones probed at current luminosities, leading to a strong motivation for the search for electroweakinos in the high luminosity LHC run.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Energy and exergy analysis of multi-stage vacuum membrane distillation integrated with mechanical vapor compression

Membrane distillation (MD) is a promising candidate for desalinating hypersaline brine, but its poor energy efficiency has remained a major barrier for widespread application. One possible solution to this issue is to recover the latent heat in the process. In this work, a multi-stage vacuum MD (MSVMD) was integrated with a mechanical vapor compressor (MVC) to enhance the latent heat recovery, and the energetic and exergetic performance of this integrated process was examined. A comprehensive energy and exergy analysis is provided to compare MSVMD and MSVMD-MVC processes for desalination of hypersaline brine. This analysis was conducted by examining the effect of the compression ratio on the energetic and exergetic performance, and the findings are reported in terms of specific thermal energy consumption (STEC), specific electricity consumption (SEC), and exergetic efficiency. The energy analysis shows that thermal energy consumption can be reduced as the compression ratio increases, due to the enhancement of latent heat recovery. The MSVMD-MVC process can be operated in a steady-state condition, without the need for thermal heat input; with STEC and SEC of 0 and 49 kWh/m 3 at the feed temperature of 50 °C and MVC compression ratio of 2.14. Moreover, exergy analysis demonstrates the efficacy of the eNRTL model in exergy calculation. Exergy destruction can be greatly reduced by increasing the compression ratio to an optimal value. For high salinity brine (124 g/L), MSVMD-MVC achieved a higher exergetic efficiency of 6.85%, compared to 2.42% in MSVMD. Furthermore, the result suggests that the application of MVC can intensify the energy efficiency and exergetic efficiency of the MSVMD system, although this process cannot outperform the current desalination technologies from the standard primary energy point of view.

42 ENGINEERING↗

Uniform Mechanical Loading Can Test for Nonuniform Loading Durability

In this work, we present a method to evaluate the equivalency between any module mechanical loading conditions. The method is developed to address the specific failure mode of glass fracture and is based on Weibull analysis and weakest link theory. It considers the varying stress profile across the module to calculate the probability of glass fracture, which is used as the metric of equivalency. An idealized nonuniform loading scheme is employed to demonstrate the method and introduce the concept of the equivalent uniform load factor: a factor applied to the maximum pressure of the nonuniform load to obtain the equivalent uniform load value. It is demonstrated that this factor is less than unity for all nonuniform load cases considered, including snow and various characters of wind loading. These significant results suggest that uniform loading may be reliably, and practically, employed to evaluate photovoltaic module glass for nonuniform loading durability.

14 SOLAR ENERGY↗

Clifford Circuit-Based Heuristic Optimization of Fermion-To-Qubit Mappings

Simulation of interacting Fermionic Hamiltonians is one of the most promising applications of quantum computers. However, the feasibility of analyzing Fermionic systems with a quantum computer hinges on the efficiency of Fermion-to-qubit mappings that encode nonlocal Fermionic degrees of freedom in local qubit degrees of freedom. While recent studies have highlighted the importance of designing Fermion-to-qubit mappings that are tailored to specific problem Hamiltonians, the methods proposed so far either are restricted to a narrow class of mappings or they use computationally expensive and unscalable brute-force search algorithms. Here, in this work, we address this challenge by designing a heuristic numerical optimization framework for Fermion-to-qubit mappings. To this end, we first translate the Fermion-to-qubit mapping problem to a Clifford circuit optimization problem and then use simulated annealing to optimize the average Pauli weight of the problem Hamiltonian. For all Fermionic Hamiltonians we have considered, the numerically optimized mappings outperform their conventional counterparts, including ternary-tree-based mappings that are known to be optimal for single creation and annihilation operators. We find that our optimized mappings yield between 15% and 40% improvements on the average Pauli weight when the simulation Hamiltonian has an intermediate level of complexity. Most remarkably, the optimized mappings improve the average Pauli weight for 6 × 6 nearest-neighbor hopping and Hubbard models by more than 40% and 20%, respectively. Surprisingly, we also find specific interaction Hamiltonians for which the optimized mapping outperforms any ternary-tree-based mapping. Our results establish heuristic numerical optimization as an effective method for obtaining mappings tailored for specific Fermionic Hamiltonian.

Hamiltonians↗

Surface Water Quality Data from Beaver-Impacted Streams; Trail Creek and East River, Colorado 2025

This data package contains surface water chemistry measurements collected in 2025 to evaluate how beaver damming and low-tech process-based stream restoration influence water quality and metal mobility in mountainous headwater systems of the Upper Colorado River Basin. Sampling was conducted at Trail Creek (Taylor Park watershed, Colorado), a tributary undergoing restoration through installation of low-tech process-based structures (i.e., beaver dam analogs), and at off-channel beaver ponds within the East River floodplain (East River watershed, Colorado). Samples were collected along longitudinal transects spanning upstream control reaches, beaver-influenced ponded reaches, and downstream segments. Additional samples were collected from near-surface pore waters within a beaver dam seepage face. The dataset includes concentrations of major and trace elements measured by inductively coupled plasma–mass spectrometry (ICP-MS) and inductively coupled plasma–optical emission spectrometry (ICP-OES), major anions measured by ion chromatography (IC), and dissolved organic carbon (DOC; reported as non-purgeable organic carbon, NPOC). Samples were size-fractionated at 0.45 micrometers (µm), 0.22 µm, and 0.02 µm to distinguish particulate (>0.45 µm), colloidal (0.22–0.02 µm), and dissolved (<0.02 µm) fractions. The data package consists of comma-separated value (.csv) files containing tabulated chemical concentration data, sample metadata (site identifiers, geographic coordinates, sampling dates, fraction type), and quality control flags. All files are provided in open, non-proprietary formats that can be accessed using standard data analysis software such as Microsoft Excel, R, Python, MATLAB, or other programs capable of reading .csv files. Units, detection limits, and analytical methods are documented in accompanying metadata files. The dataset is designed to support analyses of (1) how beaver impoundment and restoration structures alter elemental partitioning and transport, (2) the role of iron and organic carbon in mediating trace metal mobility, and (3) reach-scale changes in water quality across restoration gradients. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

Anions↗

The Twins Embedding of Type Ia Supernovae. I. The Diversity of Spectra at Maximum Light

In this work, we study the spectral diversity of Type Ia supernovae (SNe Ia) at maximum light using high signal-to-noise spectrophotometry of 173 SNe Ia from the Nearby Supernova Factory. We decompose the diversity of these spectra into different extrinsic and intrinsic components, and we construct a nonlinear parameterization of the intrinsic diversity of SNe Ia that preserves pairings of "twin"SNe Ia. We call this parameterization the "Twins Embedding."Our methodology naturally handles highly nonlinear variability in spectra, such as changes in the photosphere expansion velocity, and uses the full spectrum rather than being limited to specific spectral line strengths, ratios, or velocities. We find that the time evolution of SNe Ia near maximum light is remarkably similar, with 84.6% of the variance in common to all SNe Ia. After correcting for brightness and color, the intrinsic variability of SNe Ia is mostly restricted to specific spectral lines, and we find intrinsic dispersions as low as ~0.02 mag between 6600 and 7200 Å. With a nonlinear three-dimensional model plus one dimension for color, we can explain 89.2% of the intrinsic diversity in our sample of SNe Ia, which includes several different kinds of "peculiar"SNe Ia. A linear model requires seven dimensions to explain a comparable fraction of the intrinsic diversity. We show how a wide range of previously established indicators of diversity in SNe Ia can be recovered from the Twins Embedding. In a companion article, we discuss how these results can be applied to the standardization of SNe Ia for cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗

Leveraging Hamiltonian simulation techniques to compile operations on bosonic devices

Circuit quantum electrodynamics enables the combined use of qubits and oscillator modes. Despite a variety of available gate sets, many hybrid qubit-boson (i.e. qubit-oscillator) operations are realizable only through optimal control theory, which is oftentimes intractable and uninterpretable. We introduce an analytic approach with rigorously proven error bounds for realizing specific classes of operations via two matrix product formulas commonly used in Hamiltonian simulation, the Lie–Trotter–Suzuki and Baker–Campbell–Hausdorff product formulas. We show how this technique can be used to realize a number of operations of interest, including polynomials of annihilation and creation operators, namely (a) p (a † ) q for integer p, q. We show examples of this paradigm including obtaining universal control within a subspace of the entire Fock space of an oscillator, state preparation of a fixed photon number in the cavity, simulation of the Jaynes–Cummings Hamiltonian, and simulation of the Hong-Ou-Mandel effect. This work demonstrates how techniques from Hamiltonian simulation can be applied to better control hybrid qubit-boson devices.

bosonic qubits↗