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DOE OSTI2018

Warm summers during the Younger Dryas cold reversal

The Younger Dryas (YD) cold reversal interrupts the warming climate of the deglaciation with global climatic impacts. The sudden cooling is typically linked to an abrupt slowdown of the Atlantic Meridional Overturning Circulation (AMOC) in response to meltwater discharges from ice sheets. However, inconsistencies regarding the YD-response of European summer temperatures have cast doubt whether the concept provides a sufficient explanation. Here we present results from a high-resolution global climate simulation together with a new July temperature compilation based on plant indicator species and show that European summers remain warm during the YD. Our climate simulation provides robust physical evidence that atmospheric blocking of cold westerly winds over Fennoscandia is a key mechanism counteracting the cooling impact of an AMOC-slowdown during summer. Despite the persistence of short warm summers, the YD is dominated by a shift to a continental climate with extreme winter to spring cooling and short growing seasons.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Global plant trait relationships extend to the climatic extremes of the tundra biome

The majority of variation in six traits critical to the growth, survival and reproduction of plant species is thought to be organised along just two dimensions, corresponding to strategies of plant size and resource acquisition. However, it is unknown whether global plant trait relationships extend to climatic extremes, and if these interspecific relationships are confounded by trait variation within species. We test whether trait relationships extend to the cold extremes of life on Earth using the largest database of tundra plant traits yet compiled. We show that tundra plants demonstrate remarkably similar resource economic traits, but not size traits, compared to global distributions, and exhibit the same two dimensions of trait variation. Three quarters of trait variation occurs among species, mirroring global estimates of interspecific trait variation. Plant trait relationships are thus generalizable to the edge of global trait-space, informing prediction of plant community change in a warming world.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Climate and hydraulic traits interact to set thresholds for liana viability

Lianas, or woody vines, and trees dominate the canopy of tropical forests and comprise the majority of tropical aboveground carbon storage. These growth forms respond differently to contemporary variation in climate and resource availability, but their responses to future climate change are poorly understood because there are very few predictive ecosystem models representing lianas. We compile a database of liana functional traits (846 species) and use it to parameterize a mechanistic model of liana-tree competition. The substantial difference between liana and tree hydraulic conductivity represents a critical source of inter-growth form variation. Here, we show that lianas are many times more sensitive to drying atmospheric conditions than trees as a result of this trait difference. Further, we use our competition model and projections of tropical hydroclimate based on Representative Concentration Pathway 4.5 to show that lianas are more susceptible to reaching a hydraulic threshold for viability by 2100.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Generalization in quantum machine learning from few training data

Modern quantum machine learning (QML) methods involve variationally optimizing a parameterized quantum circuit on a training data set, and subsequently making predictions on a testing data set (i.e., generalizing). In this work, we provide a comprehensive study of generalization performance in QML after training on a limited number N of training data points. We show that the generalization error of a quantum machine learning model with T trainable gates scales at worst as $\sqrt{T/N}$. When only K$\ll$T gates have undergone substantial change in the optimization process, we prove that the generalization error improves to $\sqrt{K/N}$. Our results imply that the compiling of unitaries into a polynomial number of native gates, a crucial application for the quantum computing industry that typically uses exponential-size training data, can be sped up significantly. We also show that classification of quantum states across a phase transition with a quantum convolutional neural network requires only a very small training data set. Other potential applications include learning quantum error correcting codes or quantum dynamical simulation. Our work injects new hope into the field of QML, as good generalization is guaranteed from few training data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Out-of-distribution generalization for learning quantum dynamics

Abstract Generalization bounds are a critical tool to assess the training data requirements of Quantum Machine Learning (QML). Recent work has established guarantees for in-distribution generalization of quantum neural networks (QNNs), where training and testing data are drawn from the same data distribution. However, there are currently no results on out-of-distribution generalization in QML, where we require a trained model to perform well even on data drawn from a different distribution to the training distribution. Here, we prove out-of-distribution generalization for the task of learning an unknown unitary. In particular, we show that one can learn the action of a unitary on entangled states having trained only product states. Since product states can be prepared using only single-qubit gates, this advances the prospects of learning quantum dynamics on near term quantum hardware, and further opens up new methods for both the classical and quantum compilation of quantum circuits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Taxonomic and environmental distribution of bacterial amino acid auxotrophies

Abstract Many microorganisms are auxotrophic—unable to synthesize the compounds they require for growth. With this work, we quantify the prevalence of amino acid auxotrophies across a broad diversity of bacteria and habitats. We predicted the amino acid biosynthetic capabilities of 26,277 unique bacterial genomes spanning 12 phyla using a metabolic pathway model validated with empirical data. Amino acid auxotrophy is widespread across bacterial phyla, but we conservatively estimate that the majority of taxa (78.4%) are able to synthesize all amino acids. Our estimates indicate that amino acid auxotrophies are more prevalent among obligate intracellular parasites and in free-living taxa with genomic attributes characteristic of ‘streamlined’ life history strategies. We predicted the amino acid biosynthetic capabilities of bacterial communities found in 12 unique habitats to investigate environmental associations with auxotrophy, using data compiled from 3813 samples spanning major aquatic, terrestrial, and engineered environments. Auxotrophic taxa were more abundant in host-associated environments (including the human oral cavity and gut) and in fermented food products, with auxotrophic taxa being relatively rare in soil and aquatic systems. Overall, this work contributes to a more complete understanding of amino acid auxotrophy across the bacterial tree of life and the ecological contexts in which auxotrophy can be a successful strategy.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Evidence of isospin-symmetry violation in high-energy collisions of atomic nuclei

Strong interactions preserve an approximate isospin symmetry between up (u) and down (d) quarks, part of the more general flavor symmetry. In the case of K meson production, if this isospin symmetry were exact, it would result in equal numbers of charged (K + and K − ) and neutral (K 0 and ${\overline{K}}^{0}$) mesons produced in collisions of isospin-symmetric atomic nuclei. Here, we report results on the relative abundance of charged over neutral K meson production in argon and scandium nuclei collisions at a center-of-mass energy of 11.9 GeV per nucleon pair. We find that the production of K + and K − mesons at mid-rapidity is (18.4 ± 6.1)% higher than that of the neutral K mesons. Although with large uncertainties, earlier data on nucleus-nucleus collisions in the collision center-of-mass energy range $2.6 \, < \, \sqrt{{s}_{NN}} \, < \, 200$ GeV are consistent with the present result. Using well-established models for hadron production, we demonstrate that known isospin-symmetry breaking effects and the initial nuclei containing more neutrons than protons lead only to a small (few percent) deviation of the charged-to-neutral kaon ratio from unity at high energies. Thus, they cannot explain the measurements. The significance of the flavor-symmetry violation beyond the known effects is 4.7σ when the compilation of world data with uncertainties quoted by the experiments is used. New systematic, high-precision measurements and theoretical efforts are needed to establish the origin of the observed large isospin-symmetry breaking.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Pathfinding quantum simulations of neutrinoless double- β decay

We present results from co-designed quantum simulations of the neutrinoless double- β decay of a simple nucleus in 1+1D quantum chromodynamics using IonQ’s Forte-generation trapped-ion quantum computers. Electrons, neutrinos, and up and down quarks are distributed across two lattice sites and mapped to 32 qubits, with an additional 4 qubits used for flag-based error mitigation. A four-fermion interaction is used to implement weak interactions, and lepton-number violation is induced by a neutrino Majorana mass. Quantum circuits that prepare the initial nucleus and time evolve with the Hamiltonian containing the strong and weak interactions are executed on IonQ Forte Enterprise. Enabled by tuned model parameters, lepton-number violation is observed in real time, providing a clear signal of neutrinoless double- β decay. This was made possible by co-designing the simulation to maximally utilize the all-to-all connectivity and native gate-set available on IonQ’s quantum computers. Quantum circuit compilation techniques and co-designed error-mitigation methods, informed from executing benchmarking circuits with up to 2,356 two-qubit gates, enabled observables to be extracted with high precision. We discuss the potential of future quantum simulations to provide yocto-second resolution of the reaction pathways in these, and other, nuclear processes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Synthesizing efficient circuits for Hamiltonian simulation

Abstract We provide an approach for compiling quantum simulation circuits that appear in Trotter, qDRIFT and multi-product formulas to Clifford and non-Clifford operations that can reduce the number of non-Clifford operations. The total number of gates, especially CNOT, reduce in many cases. We show that it is possible to implement an exponentiated sum of commuting Paulis with at most m (controlled)-rotation gates, where m is the number of distinct non-zero eigenvalues (ignoring sign). Thus we can collect mutually commuting Hamiltonian terms into groups satisfying one of several symmetries identified in this work. This allows an inexpensive simulation of the entire group of terms. We further show that the cost can in some cases be reduced by partially allocating Hamiltonian terms to several groups and provide a polynomial time classical algorithm that can greedily allocate the terms to appropriate groupings.

Mukhopadhyay, Priyanka (ORCID:0000000164639100)↗

DOE OSTI2023

A human antibody epitope map of the malaria vaccine antigen Pfs25

Pfs25 is a leading antigen for a malaria transmission-blocking vaccine and shows moderate transmission-blocking activity and induction of rapidly decreasing antibody titers in clinical trials. A comprehensive definition of all transmission-reducing epitopes of Pfs25 will inform structure-guided design to enhance Pfs25-based vaccines, leading to potent transmission-blocking activity. Here, we compiled a detailed human antibody epitope map comprising epitope binning data and structures of multiple human monoclonal antibodies, including three new crystal structures of Pfs25 in complex with transmission-reducing antibodies from Malian volunteers immunized with Pfs25 conjugated to EPA and adjuvanted with AS01. These structures revealed additional epitopes in Pfs25 capable of reducing transmission and expanded this characterization to malaria-exposed humans. This work informs immunogen design to focus the antibody response to transmission-reducing epitopes of Pfs25, enabling development of more potent transmission-blocking vaccines for malaria.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Dynamical dark energy in light of the DESI DR2 baryonic acoustic oscillations measurements

Understanding whether cosmic acceleration arises from a cosmological constant or a dynamical component is a central goal of cosmology, and the Dark Energy Spectroscopic Instrument (DESI) enables stringent tests with high-precision distance measurements. Here we analyse measurements of baryon acoustic oscillations in DESI Data Release 1 and Data Release 2 and consider type Ia supernovae and a distance prior for the cosmic microwave background. With the larger statistical power and wider redshift coverage of Data Release 2, the preference for dynamical dark energy does not diminish relative to Data Release 1. Using both a shape-function reconstruction and non-parametric approaches with a Horndeski-motivated correlation prior, we find that the equation of state for dark energy w(z) varies with redshift. Baryon acoustic oscillation data alone yield modest constraints, but in combination with independent supernova compilations and the prior for the cosmic microwave background, they strengthen the evidence for dynamics. A Bayesian comparison of models shows moderate support for departures from Λ cold dark matter (ΛCDM) when several degrees of freedom in w(z) are allowed, corresponding to ~3σ tension with ΛCDM (and higher for some datasets). Despite methodological differences, our results are consistent with companion DESI papers, underscoring the complementarity of the approaches. Possible systematics remain under study; forthcoming DESI, Euclid and next-generation cosmic microwave background data will provide decisive tests.

cosmology↗

DOE OSTI2025

Dynamical dark energy in light of the DESI DR2 baryonic acoustic oscillations measurements

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Boreal–Arctic wetland methane emissions modulated by warming and vegetation activity

Abstract Wetland methane (CH 4 ) emissions over the Boreal–Arctic region are vulnerable to climate change and linked to climate feedbacks, yet understanding of their long-term dynamics remains uncertain. Here, we upscaled and analysed two decades (2002–2021) of Boreal–Arctic wetland CH 4 emissions, representing an unprecedented compilation of eddy covariance and chamber observations. We found a robust increasing trend of CH 4 emissions (+8.9%) with strong inter-annual variability. The majority of emission increases occurred in early summer (June and July) and were mainly driven by warming (52.3%) and ecosystem productivity (40.7%). Moreover, a 2 °C temperature anomaly in 2016 led to the highest recorded annual CH 4 emissions (22.3 Tg CH 4 yr −1 ) over this region, driven primarily by high emissions over Western Siberian lowlands. However, current-generation models from the Global Carbon Project failed to capture the emission magnitude and trend, and may bias the estimates in future wetland CH 4 emission driven by amplified Boreal–Arctic warming and greening.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

A global atlas of soil viruses reveals unexplored biodiversity and potential biogeochemical impacts

Historically neglected by microbial ecologists, soil viruses are now thought to be critical to global biogeochemical cycles. However, our understanding of their global distribution, activities and interactions with the soil microbiome remains limited. Here we present the Global Soil Virus Atlas, a comprehensive dataset compiled from 2,953 previously sequenced soil metagenomes and composed of 616,935 uncultivated viral genomes and 38,508 unique viral operational taxonomic units. Rarefaction curves from the Global Soil Virus Atlas indicate that most soil viral diversity remains unexplored, further underscored by high spatial turnover and low rates of shared viral operational taxonomic units across samples. By examining genes associated with biogeochemical functions, we also demonstrate the viral potential to impact soil carbon and nutrient cycling. This study represents an extensive characterization of soil viral diversity and provides a foundation for developing testable hypotheses regarding the role of the virosphere in the soil microbiome and global biogeochemistry.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Plant functional trait change across a warming tundra biome

Trait-based ecology promises to predict community assembly1–3, ecosystem function4–6, and responses to environmental change4,7 across spatial and temporal scales. At the global scale the majority of plant trait variation is explained by just two dimensions8, corresponding to resource acquisition9 and plant size10,11. However, it is unknown whether (1) globally established trait relationships are maintained across biomes, (2) species level relationships could be invalidated by trait variation within species, and (3) trait variation is independent of scale. We tested these questions at the cold extremes of life on earth using the largest tundra plant trait database ever compiled. Here we show we found that tundra plants exhibited a two-axis spectrum consistent with global findings, and demonstrated remarkable consistency in the range of resource acquisition traits, but not size traits, compared to global trait distributions. The majority of trait variation occurred at the species level, but within-species variation comprised an important component of variation at local scales (<10 km2) and at low species richness (<10 species), implying that.... Our findings indicate that the dimensions of functional trait space are maintained in the coldest ecosystems on the planet despite strong environmental filtering of plant size, but that a greater focus on within-species trait variation is required to predict trait change at the community scale.

Bjorkman, Anne D.↗

DOE OSTI2024

Fertilizer management for global ammonia emission reduction

Crop production is a large source of atmospheric ammonia (NH 3 ), which poses risks to air quality, human health and ecosystems. However, estimating global NH 3 emissions from croplands is subject to uncertainties because of data limitations, thereby limiting the accurate identification of mitigation options and efficacy. In this report we develop a machine learning model for generating crop-specific and spatially explicit NH 3 emission factors globally (5-arcmin resolution) based on a compiled dataset of field observations. We show that global NH 3 emissions from rice, wheat and maize fields in 2018 were 4.3 ± 1.0 Tg N yr -1 , lower than previous estimates that did not fully consider fertilizer management practices. Furthermore, spatially optimizing fertilizer management, as guided by the machine learning model, has the potential to reduce the NH3 emissions by about 38% (1.6 ± 0.4 Tg N yr -1 ) without altering total fertilizer nitrogen inputs. Specifically, we estimate potential NH3 emissions reductions of 47% (44–56%) for rice, 27% (24–28%) for maize and 26% (20–28%) for wheat cultivation, respectively. Under future climate change scenarios, we estimate that NH3 emissions could increase by 4.0 ± 2.7% under SSP1–2.6 and 5.5 ± 5.7% under SSP5–8.5 by 2030–2060. However, targeted fertilizer management has the potential to mitigate these increases.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

A global, empirical, harmonised dataset of soil organic carbon changes under perennial crops

A global, unified dataset on Soil Organic Carbon (SOC) changes under perennial crops has not existed till now. We present a global, harmonised database on SOC change resulting from perennial crop cultivation. It contains information about 1605 paired-comparison empirical values (some of which are aggregated data) from 180 different peer-reviewed studies, 709 sites, on 58 different perennial crop types, from 32 countries in temperate, tropical and boreal areas; including species used for food, bioenergy and bio-products. The database also contains information on climate, soil characteristics, management and topography. This is the first such global compilation and will act as a baseline for SOC changes in perennial crops. It will be key to supporting global modelling of land use and carbon cycle feedbacks, and supporting agricultural policy development.

Science & Technology - Other Topics↗

DOE OSTI2019

High-throughput calculations of catalytic properties of bimetallic alloy surfaces

Abstract A comprehensive database of chemical properties on a vast set of transition metal surfaces has the potential to accelerate the discovery of novel catalytic materials for energy and industrial applications. In this data descriptor, we present such an extensive study of chemisorption properties of important adsorbates - e.g., C, O, N, H, S, CH x , OH, NH, and S H - on 2,035 bimetallic alloy surfaces in 5 different stoichiometric ratios, i.e., 0%, 25%, 50%, 75%, and 100%. To our knowledge, it is the first systematic study to compile the adsorption properties of such a well-defined, large chemical space of catalytic interest. We propose that a collection of catalytic properties of this magnitude can assist with the development of machine learning enabled surrogate models in theoretical catalysis research to design robust catalysts with high activity for challenging chemical transformations. This database is made publicly available through the platform www.Catalysis-hub.org for easy retrieval of the data for further scientific analysis.

36 MATERIALS SCIENCE↗