CF6 Dark Energy and Cosmic Acceleration: Complementarity of Probes and New Facilities [Slides]
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72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Complementarity between neutrinoless double beta decay and collider searches for heavy neutrinos in composite-fermion models
Composite-fermion models predict excited quarks and leptons with mass scales which can potentially be observed at high-energy colliders like the LHC; the most recent exclusion limits from the CMS and ATLAS Collaborations corner excited-fermion masses and the compositeness scale to the multi-TeV range. At the same time, hypothetical composite Majorana neutrinos would lead to observable effects in neutrinoless double beta decay ($0\nu \beta \beta$) experiments. In this work, we show that the current composite-neutrino exclusion limit $M_N>4.6$ TeV, as extracted from direct searches at the LHC, can indeed be further improved to $M_N>8.8$ TeV by including the bound on the nuclear transition $^{136}$Xe $\to ^{136}$Ba + $2e^-$. Looking ahead, the forthcoming HL-LHC will allow probing a larger portion of the parameter-space, nevertheless, it will still benefit from the complementary limit provided by $0 \nu \beta \beta$ future detectors to explore composite-neutrino masses up to $12.6$ TeV.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Hadronic Physics in Neutrino Interactions and Complementarities to the EIC
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Atomic, Nuclear and Particle Physics↗
Complementarity Between Neutrino Neutral and Charged Current Events in the Search for New Physics
At long-baseline neutrino experiments, neutral-current (NC) events accumulate in large numbers but are seldom exploited for new physics searches. We demonstrate their potential using non-standard neutrino interactions (NSI) with quarks as a case study. Charged-current (CC) analyses constrain NSI through matter effects on neutrino propagation, which probe almost exclusively the isoscalar combination of up- and down-quark couplings; the orthogonal isovector combination is suppressed by a factor of $\sim$100. Because NSI also modify NC cross sections in a flavor-dependent way, NC events become sensitive to oscillations: the far-to-near detector ratio acquires a dependence on the beam's flavor composition that probes both isoscalar and isovector couplings with comparable weight. Using existing NOvA data and DUNE projections, we derive the first bounded constraints on isovector NSI from a long-baseline experiment and show that combining CC and NC measurements resolves the individual quark couplings, breaking a degeneracy that persists in either analysis alone.
Gehrlein, Julia [Colorado State U.] (ORCID:0000000↗
Scalable Techniques for Stochastic Power Flow Problems (Final Report)
The proposed research focuses on developing scalable algorithms for two-stage security-constrained OPF problems with AC power flow constraints, a class of problems complicated by (i) scale arising from a scenario representation; and (ii) the presence of nonlinearity, nonconvexity, and possibly second-stage discreteness or complementarity. Unfortunately, most existing solvers cannot contend with both challenges simultaneously; accordingly, the proposed research focuses on developing solution techniques that can both scale with the number of scenarios and contend with nonconvexity and second-stage complementarity. We consider three avenues for addressing such problems: (i) Variable sample-size SQP (VS-SQP) methods that combine sparse Quasi-Newton updates with a scalable variance-reduced stochastic gradient scheme for stochastic QP subproblems, allowing for contending with second-stage complementarity via regularization; (ii) Variable sample-size stochastic Interior-point (VS-sIP) schemes that propose a sampling-based regularized (to allow for contending with complementarity) interior-point schemes in which a Schur-complement technique is employed for decomposing the Newton direction computation step; (iii) Variable sample-size tractable ADMM (VS-tADMM) schemes combine variable sample-sizes with carefully designed techniques for resolving each of the nonconvex updates (by leveraging the QCQP structures). We intend to compare the three schemes using performance profiles in terms of solution quality, scalability, etc. and then select one scheme which will then be developed and further refined in Python for purposes of the GO competition.
42 ENGINEERING↗
Bound Constrained Partial DifferentialEquation Inverse Problem Solution by theSemi-Smooth Newton Method
We present the mathematical derivation, software implementation details, and computational results for a semi-smooth Newton method applied to two inverse problems governed by partial differential equations with bound constraints. The two problems share mathematical structural similarities to density-based topology optimization problems. The semi-smooth Newton method provides a mesh independent solution computation for the two test problems. A key step is that the complementarity part of the necessary optimality conditions are reformulated with the use of a complementarity functionφsuch that the complementarity conditions are satisfied if and only if a zero of a nonsmooth function has been obtained. The modular finite element package MFEM is utilized for the software implementation. In addition we constructed a matrix-free Operator to enable the use of efficient Krylov subspace IterativeSolver of MFEM for the solution of our two target problems.
97 MATHEMATICS AND COMPUTING↗
Wind and Solar Hybrid Power Plants for Energy Resilience
Wind-solar-storage hybrid power plants represent a significant and growing share of new proposed projects in the United States (U.S.). Their uptake is supported by increasing renewable energy market share, technical abilities for dispatch and control, and decreasing wind, solar, and battery storage costs. Simultaneously, generation and storage resources are increasingly used in distributed power systems. While concerns around the reliability of the aging, transforming U.S. electric grid are growing, diversifying energy resources through hybridization or spatial distribution provides an opportunity to enhance power system resilience compared to single-source generation. Understanding where to build hybrids for resilience value, rather than bulk power supply, has not been fully explored in previous studies. Therefore, in this study, we complete a national complementarity analysis to identify areas in the U.S. that are particularly suited for wind-solar hybrid power plant development. We show the importance of seasonal and diurnal patterns in assessing complementarity, and identify that regions in the Great Plains, Midwest, and Southeast are particularly suited for hybrid power plants. We demonstrate the resilience value of hybridization for a reference system based near Memphis, Tennessee, and show optimal sizing of wind, solar, and storage assets given 1.0 and 0.9 critical load factors. Results indicate that pairing wind and solar assets better meet constant load demand and reduce storage requirements compared to solar alone. These results enable future work integrating complementarity metrics in resilience frameworks and indicate a need for more finer resolution of local resource, demand, and hazard data.
14 SOLAR ENERGY↗
The effects of mixed-species root zones on the resistance of soil bacteria and fungi to long-term experimental and natural reductions in soil moisture
Mixed forest stands tend to be more resistant to drought than species-specific stands partially due to complementarity in root ecology and physiology. For this work, we asked whether complementary differences in the drought resistance of soil microbiomes might contribute to this phenomenon. We experimented on the effects of reduced soil moisture on bacterial and fungal community composition in species-specific (single species) and mixed-species root zones of Norway spruce and European beech forests in a 5-year-old throughfall-exclusion experiment and across seasonal (spring-summer-fall) and latitudinal moisture gradients. Bacteria were most responsive to changes in soil moisture, especially members of Rhizobiales, while fungi were largely unaffected, including ectomycorrhizal fungi (EMF). Community resistance was higher in spruce relative to beech root zones, corresponding with the proportions of drought-favored (more in spruce) and drought-sensitive bacterial taxa (more in beech). The spruce soil microbiome also exhibited greater resistance to seasonal changes between spring (wettest) and fall (driest). Mixed-species root zones contained a hybrid of beech- and spruce-associated microbiomes. Several bacterial populations exhibited either enhanced resistance or greater susceptibility to drought in mixed root zones. Overall, patterns in the relative abundances of soil bacteria closely tracked moisture in seasonal and latitudinal precipitation gradients and were more predictive of soil water content than other environmental variables. We conclude that complementary differences in the drought resistance of soil microbiomes can occur and the likeliest form of complementarity in mixed-root zones coincides with the enrichment of drought-tolerant bacteria associated with spruce and the sustenance of EMF by beech.
54 ENVIRONMENTAL SCIENCES↗
Exploring the Grid Value Potential of Offshore Wind Energy in Oregon
The grid value of Oregon's offshore wind resource is considered through the lenses of (i) resource complementarity with the hydroelectric system and other Variable Renewable Energy resources, (ii) load complementarity with the four balancing authorities with territory in Oregon, and (iii) spatial value to regional and coastal grids as represented through a Production Cost Model of the WECC system. Capacity implications of the interactions between offshore wind and the historical east-to-west power flows of the region are reviewed. The existing system is shown to accommodate 2GW of offshore wind interconnections without curtailment.
17 WIND ENERGY↗
Understanding Economic and Deployment Benefits of Wind-PV Hybrid Power Plants
The least-cost approach to decarbonizing the U.S. electricity supply will likely involve a significantly expanded share of variable renewable energy (VRE) generation. Many strategies and approaches have been identified to address integration challenges in a VRE-dominated system, including standalone and coupled battery systems. In this study, we explored the current and future potential of utility-scale hybrid energy systems comprising PV, wind, and lithium-ion battery technologies (PV-wind-battery systems). Analysis results include temporal complementarity of wind and PV resources across the contiguous United States, with an emphasis on metrics that quantify reductions in variability that can be achieved through hybridization. We further use a price-taker model with simulated hourly energy and capacity prices to determine the revenue-maximizing dispatch of a range of PV-wind-battery configurations across Texas, from the present through 2050. We find that coupling PV, wind, and battery technologies allows for more effective utilization of interconnection capacity by increasing capacity factors to 60-80%+ and capacity credits to close to 100%, depending on battery capacity. We also compared the energy and capacity values of PV-wind and PV-wind-battery systems to the corresponding stability coefficient metric, which describes the location-and configuration-specific complementarity of PV and wind resources. Our results show that the stability coefficient effectively predicts the configuration-location combinations in which a smaller battery component can provide comparable economic performance in a PV-wind-battery system (compared to a PV-battery system). These PV-wind-battery hybrids can help integrate more VRE by providing smoother, more predictable generation and greater flexibility. Finally, capacity expansion modeling of PV-wind systems indicates that hybridization can reduce transmission expansion requirements associated with a heavily decarbonized U.S. electricity system.
complementarity↗
Phage-specific metabolic reprogramming of virocells
Ocean viruses are abundant and infect 20–40% of surface microbes. Infected cells, termed virocells, are thus a predominant microbial state. Yet, virocells and their ecosystem impacts are understudied, thus precluding their incorporation into ecosystem models. Here we investigated how unrelated bacterial viruses (phages) reprogram one host into contrasting virocells with different potential ecosystem footprints. We independently infected the marine Pseudoalteromonas bacterium with siphovirus PSA-HS2 and podovirus PSA-HP1. Time-resolved multi-omics unveiled drastically different metabolic reprogramming and resource requirements by each virocell, which were related to phage–host genomic complementarity and viral fitness. Namely, HS2 was more complementary to the host in nucleotides and amino acids, and fitter during infection than HP1. Functionally, HS2 virocells hardly differed from uninfected cells, with minimal host metabolism impacts. HS2 virocells repressed energy-consuming metabolisms, including motility and translation. Contrastingly, HP1 virocells substantially differed from uninfected cells. They repressed host transcription, responded to infection continuously, and drastically reprogrammed resource acquisition, central carbon and energy metabolisms. Ecologically, this work suggests that one cell, infected versus uninfected, can have immensely different metabolisms that affect the ecosystem differently. Finally, we relate phage–host genome complementarity, virocell metabolic reprogramming, and viral fitness in a conceptual model to guide incorporating viruses into ecosystem models.
Environmental Sciences & Ecology↗
Crystallization and self-assembly of shape-complementary sequence-defined peptoids
Shape complementarity between polymers is a hallmark of biological systems ( e.g. DNA base pairing and protein binding interactions). Here we explore the role of shape complementarity between sequence-defined N -alkyl peptoids in crystal lattices.
Xuan, Sunting↗
The role of complementary shape in protein dimerization
Shape guides colloidal nanoparticles to form complex assemblies, but its role in defining interfaces in biomolecular complexes is less clear. In this work, we isolate the role of shape in protein complexes by studying the reversible binding processes of 46 protein dimer pairs, and investigate when entropic effects from shape complementarity alone are sufficient to predict the native protein binding interface. We employ depletants using a generic, implicit depletion model to amplify the magnitude of the entropic forces arising from lock-and-key binding and isolate the effect of shape complementarity in protein dimerization. For 13% of the complexes studied here, protein shape is sufficient to predict native complexes as equilibrium assemblies. We elucidate the results by analyzing the importance of competing binding configurations and how it affects the assembly. Furthermore, a machine learning classifier, with a precision of 89.14% and a recall of 77.11%, is able to identify the cases where shape alone predicts the native protein interface.
36 MATERIALS SCIENCE↗
Divide and conquer: broadly neutralizing antibody combinations for improved HIV-1 viral coverage
Successful HIV-1 prevention and therapy will require broad and potent coverage of within-host and global viral diversity. Broadly neutralizing antibody (bNAb) combination and multispecific therapeutics provide an opportunity to meet this challenge due to the complementary activity of individual antibody components. Here, we review the principles and applications of this concept. The Antibody Mediated Prevention (AMP) trials have demonstrated the high bar for neutralization potency and breadth that bNAb-mediated prevention modalities will need to achieve to have a meaningful impact on the HIV-1 epidemic. Additional clinical studies have recently shown that an even higher bar may be required for therapeutic inhibition of the diverse within-host quasispecies present in viremic and aviremic people with HIV-1 (PWH). We discuss how the complementarity of bNAbs in terms of neutralization profiles, resistance mutations and coverage of within-host quasispecies may overcome these stringent requirements and lead to effective bNAb combination or multispecific antibody based prophylactic and therapeutic strategies. The design of next-generation bNAb-based combination or multispecific therapeutics for the prevention and/or treatment of HIV-1 infection will need to leverage the complementarity of component bNAbs to maximize the potency and breadth that will be required for clinical success.
60 APPLIED LIFE SCIENCES↗
A Century of Synergy in Termite Symbiosis Research: Linking the Past with New Genomic Insights
Termites have long been studied for their symbiotic associations with gut microbes. In the late nineteenth century, this relationship was poorly understood and captured the interest of parasitologists such as Joseph Leidy; this research led to that of twentieth-century biologists and entomologists including Cleveland, Hungate, Trager, and Lüscher. Early insights came via microscopy, organismal, and defaunation studies, which led to descriptions of microbes present, descriptions of the roles of symbionts in lignocellulose digestion, and early insights into energy gas utilization by the host termite. Focus then progressed to culture-dependent microbiology and biochemical studies of host–symbiont complementarity, which revealed specific microhabitat requirements for symbionts and noncellulosic mechanisms of symbiosis (e.g., N 2 fixation). Today, knowledge on termite symbiosis has accrued exponentially thanks to omic technologies that reveal symbiont identities, functions, and interdependence, as well as intricacies of host–symbiont complementarity. Moving forward, the merging of classical twentieth-century approaches with evolving omic tools should provide even deeper insights into host–symbiont interplay.
Entomology↗
Earth System Reanalysis in Support of Climate Model Improvements
Recent climate model developments, established through increased model resolution, have led to substantial improvements in model simulations of the time-evolving, coupled Earth system and its subcomponents. However, regardless of resolution, climate models will always produce climate features and variability that differ from the real world and will be prone to biases. This is due to many remaining uncertainties, such as in parametric and structural model uncertainty, in the initial conditions prescribed, and in the prescribed (scenario) forcing which varies on decadal to centennial timescales. Further model improvements are expected to arise specifically from improved representation of physical processes realized through model-data fusion. This will create an unprecedented opportunity to better exploit a large array of Earth observations, from in situ measurements to weather radars and satellite observations, as the resolved scales of the models approach those of the observations. For this, climate DA will be the central tool to bring models and observations into consistency, by improving initial conditions, inferring uncertain model parameters and structure, and quantifying uncertainty. Generally, there will be advantages and complementarities of adjoint-based smoother approaches, ensemble-based filter approaches, or new ML-inspired approaches. Yet, the ever-increasing model resolution will present growing challenges arising from computational cost, calling for new ways of performing data assimilation and model optimization. Using the complementarity in a hybrid approach, blending tools and concepts from variational, ensemble and ML methods might be what is required in the future. In this context ML could be important to handle non-linear responses, and to better approximate non-Gaussian distributions.
54 ENVIRONMENTAL SCIENCES↗
Modeling design and control problems involving neural network surrogates
Here, we consider nonlinear optimization problems that involve surrogate models represented by neural networks. We demonstrate first how to directly embed neural network evaluation into optimization models, highlight a difficulty with this approach that can prevent convergence, and then characterize stationarity of such models. We then present two alternative formulations of these problems in the specific case of feedforward neural networks with ReLU activation: as a mixed-integer optimization problem and as a mathematical program with complementarity constraints. For the latter formulation we prove that stationarity at a point for this problem corresponds to stationarity of the embedded formulation. Each of these formulations may be solved with state-of-the-art optimization methods, and we show how to obtain good initial feasible solutions for these methods. We compare our formulations on three practical applications arising in the design and control of combustion engines, in the generation of adversarial attacks on classifier networks, and in the determination of optimal flows in an oil well network.
97 MATHEMATICS AND COMPUTING↗
Detection of early-universe gravitational-wave signatures and fundamental physics
Detection of a gravitational-wave signal of non-astrophysical origin would be a landmark discovery, potentially providing a significant clue to some of our most basic, big-picture scientific questions about the Universe. In this white paper, we survey the leading early-Universe mechanisms that may produce a detectable signal—including inflation, phase transitions, topological defects, as well as primordial black holes—and highlight the connections to fundamental physics. We review the complementarity with collider searches for new physics, and multimessenger probes of the large-scale structure of the Universe.
79 ASTRONOMY AND ASTROPHYSICS↗