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NASA NTRS1994

Merged interaction regions and large-scale magnetic field fluctuations during 1991: Voyager 2 observations

This paper analyzes Voyager 2 observations of the magnetic field between 33.6 AU and 36.2 AU during 1991 when extraordinary events were observed on the Sun and in the heliosphere. The magnetic field strength signal B(t) has the unusual form of two large transient merged interaction regions (MIRs) on a fluctuating background. The two MIRs moved past the spacecraft in 32 days and 18 days, respectively. The mean field strength in each transient MIR was approx. equals 2.6 times the mean field during the remaining part of the year (0.11 nT). Each of the MIRs is related to a fast stream. The magnetic field is strong throughout each stream, suggesting that the strong fields are carried by the streams as well as produced by shock and stream compression. The fluctuations in B(t) during 1991 are not multifractal, and the MIRs cannot be approximated as multifractal clusters of intense magnetic fields. The distribution of the hour-averaged magnetic field strengths is approximately lognormal over 90% of its intermediate range, and it has an exponential tail for B greater than the average magnetic field strength. The elevation angles of B have a normal distribution with a standard deviation of 16 deg +/- 4 deg. The distributions of the azimuthal angles of B in the ranges 1 deg - 180 deg and 180 deg - 360 deg are approximately normal over a more limited range, and non-Gaussian tails associated with nearly radial magnetic fields; the standard deviations are approx. equal to 40 deg. Individual sectors are present throughout most of the interval, even in the MIRs, but there is no recurrent sector pattern. A model of the large-scale fluctuations in 1991 will have to include both determinaistic and statistical factors.

Burlaga, L. F.↗

NASA NTRS1987

A photometric search for solar giant convection cells

The photometric contrast of solar giant convection cells is limited using 526.6 nm continuum images obtained on 15 days in May 1985. The rms of the giant cell intensity pattern must be less than or equal to the observed rms on spatial scales of 80 to 240 Mm, which is 0.023 percent or, equivalently, 0.33 K. However, the spatial scale and time-scale dependence of the variance demonstrate that giant cells are not the source of the observed variance. Consequently, a tighter constraint on the rms of the giant cell pattern may be placed, namely 0.016 percent or 0.23 K. This limit is consistent with temperature perturbations estimated from recent nonlinear simulations of global-scale solar convection. This limit on the rms of the giant cell pattern is used to estimate that the contribution of giant cells to the fluctuation of the solar irradiance on a one-month time-scale is less than 0.00003 S.

Chiang, W.-H.↗

NASA NTRS2019

Characteristics of Total Column CO2 Retrievals from the OCO Missions: Biases, Information Content and Implications for Flux Inversions

The Orbiting Carbon Observatory-2 and Orbiting Carbon Observatory-3, launched in 2015 and 2019, respectively, are intended to collect and deliver high-resolution observations of CO2 with unprecedented space and time coverage. Observations of CO2 from these remote-sensing missions (also known as XCO2, or column-based average, dry air mole fraction of CO2) are then used by the global carbon cycle community to answer a wide range of science questions, from the distribution and quantification of global and regional CO2 source-sink patterns to quantification of anthropogenic sources at urban scales. Even though we have had the OCO-2 mission flying for a few years now, the retrieval algorithms are continuously evolving and improving to deliver XCO2 retrievals with very high precision and high accuracy (or low biases). In this presentation, we will discuss a simple yet effective quantitative framework that has been developed by the OCO-2 flux team to evaluate the information content of these XCO2 retrievals as soon as they are released, i.e., with lower latency than full-scale flux inversions. This framework serves as a precursor to advanced inverse modeling frameworks and is intended to provide an early but accurate assessment of the signal present in the satellite retrievals, the robustness of that signal, and the ability of these retrievals to resolve patterns in CO2 surface fluxes that cannot be resolved by our current network of surface sites. Specific results will tackle a tiered set of questions that are being addressed using this framework: (a) what are the distribution of retrievals in the different modes of operation and how do they vary in space and time? (b) what is the information that is being given to the inverse modeling frameworks from the space-based data, information above and beyond what is provided by the in-situ data? and (c) how do these factors influence our choices for doing flux inversions with the satellite retrievals? While the primary focus of the results will be on application of this technique to mature OCO-2 retrievals, we will show early results for a couple of months of OCO-3 retrievals. For the time-period that the retrievals from the two missions overlap, we will highlight how this framework allows us to effortlessly put the information from OCO-3 and OCO-2 on an equal footing, thus enabling easy comparison between the two pioneering missions.

Chatterjee, Abhishek↗

DOE OSTI2021

Understanding collective human movement dynamics during large-scale events using big geosocial data analytics

Conventional approaches for modeling human mobility pattern often focus on human activity and movement dynamics in their regular daily lives and cannot capture changes in human movement dynamics in response to large-scale events. With the rapid advancement of information and communication technologies, many researchers have adopted alternative data sources (e.g., cell phone records, GPS trajectory data) from private data vendors to study human movement dynamics in response to large-scale natural or societal events. Big geosocial data such as georeferenced tweets are publicly available and dynamically evolving as real-world events are happening, making it more likely to capture the real-time sentiments and responses of populations. However, precisely-geolocated geosocial data is scarce and biased toward urban population centers. In this research, we developed a big geosocial data analytical framework for extracting human movement dynamics in response to large-scale events from publicly available georeferenced tweets. The framework includes a two-stage data collection module that collects data in a more targeted fashion in order to mitigate the data scarcity issue of georeferenced tweets; in addition, a variable bandwidth kernel density estimation(VB-KDE) approach was adopted to fuse georeference information at different spatial scales, further augmenting the signals of human movement dynamics contained in georeferenced tweets. To correct for the sampling bias of georeferenced tweets, we adjusted the number of tweets for different spatial units (e.g., county, state) by population. To demonstrate the performance of the proposed analytic framework, we chose an astronomical event that occurred nationwide across the United States, i.e., the 2017 Great American Eclipse, as an example event and studied the human movement dynamics in response to this event. Finally, this analytic framework can easily be applied to other types of large-scale events such as hurricanes or earthquakes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

A network approach for multiscale catchment classification using traits

Abstract. The classification of river catchments into groups with similar biophysical characteristics is useful to understand and predict their hydrological behavior. The increasing availability of remote sensing and other large-scale geospatial datasets has enabled the use of advanced data-driven approaches to classify catchments using traits such as topography, geology, climate, land cover, land use, and human influence. Unsupervised clustering algorithms based on the Euclidean distance are commonly used for trait-based classification but are not suitable for highly dimensional data. In this study we present a new network-based method for multi-scale catchment classification, which can be applied to large datasets and used to determine the traits associated with different catchment groups. In this framework, two networks are analyzed in parallel: the first being where the nodes are traits and the second being where the nodes are catchments. In both cases, edges represent pairwise similarity, and a network cluster detection algorithm is used for the classification. The trait network is used to investigate redundancy in the trait data and to condense this information into a small number of interpretable categories. The catchments network is used to classify the catchments into clusters and to identify representative catchments for the different groups using the degree centrality metric. We apply this method to classify 9067 river catchments across the contiguous United States at both regional and continental scales using 274 non-categorical traits. At the continental scale, we identify 25 interpretable trait categories and 34 catchment clusters of sizes greater than 50. We find that catchments with similar trait categories are typically located in the same region, with different spatial patterns emerging among clusters dominated by natural and anthropogenic traits. We also find that the catchment clusters exhibit distinct hydrological behavior based on an analysis of streamflow indices. This network approach provides several advantages over traditional means of classification, including better separation of clusters, the use of alternate similarity metrics that are more suitable for highly dimensional data, and reducing redundancy in the trait information. The paired catchment–trait networks enable analysis of hydrological behavior using the dominant trait categories for each catchment cluster. The approach can be used at multiple spatial scales since the network topologies adjust automatically to reflect the trait patterns at the scale of investigation. Finally, the representative catchments identified as hub nodes in the network can be used to guide transferable observational and modeling strategies. The method is broadly applicable beyond hydrology for classification of other complex systems that utilize different types of trait datasets.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1993

Planetary circulations in the presence of transient and self-induced heating

The research program focuses on large-scale circulations and their interaction with the global convective pattern. An 11-year record of global cloud imagery and contemporaneous fields of motion and temperature have been used to investigate organized convection and coherent variability of the tropical circulation operating on intraseasonal time scales. This study provides a detailed portrait of tropical variability associated with the so-called Madden-Julian Oscillation (MJO). It reveals the nature, geographical distribution, and seasonality of discrete convective signal, which is a measure of feedback between the circulation and the convective pattern. That discrete spectral behavior has been evaluated in light of natural variability of the ITCZ associated with climatological convection. A composite signature of the MJO, based on cross-covariance statistics of cloud cover, motion, and temperature, has been constructed to characterize the lifecycle of the disturbance in terms of these properties. The composite behavior has also been used to investigate the influence the MJO exerts on the zonal-mean circulation and the involvement of the MJO in transfers of momentum between the atmosphere and the solid Earth. The aforementioned observational studies have led to the production of two animations. One reveals the convective signal in band-pass filtered OLR and compares it to climatological convection. The other is a 3-dimensional visualization of the composite lifecycle of the MJO. With a clear picture of the MJO in hand, feedback between the circulation and the convective pattern can be diagnosed meaningfully in numerical simulations. This process is being explored in calculations with the linearized primitive equations on the sphere in the presence of realistic stability and shear. The numerical framework represents climatological convection as a space-time stochastic process and wave-induced convection in terms of the vertically-integrated moisture flux convergence. In these calculations, frictional convergence near the equator emerges as a key to feedback between the circulation and the convective pattern. At low latitudes, nearly geostrophic balance in the boundary layer gives way to frictional balance. This shifts the wave-induced convection into phase with the temperature anomaly and allows the attending heating to feed back positively onto the circulation. The calculations successfully reproduce the salient features of the MJO. They are being used to understand the growth and decay phases of the composite lifecycle and the conditions that favor amplification of the MJO.

Salby, Murry L.↗

NASA NTRS1985

The observed life cycle of a baroclinic instability

Medium-scale waves (zonal wavenumbers 4-7) frequently dominate Southern Hemisphere summer circulation patterns. Randel and Stanford have studied the dynamics of these features, demonstrating that the medium-scale waves result from baroclinic excitation and exhibit well-defined life cycles. This study details the evolution of the medium-scale waves during a particular life cycle. The specific case chosen exhibits a high degree of zonal symmetry, prompting study based upon zonally averaged diagnostics. An analysis of the medium-scale wave energetics reveals a well-defined life cycle of baroclinic growth, maturity, and barotropic decay. Eliassen-Palm flux diagrams detail the daily wave structure and its interaction with the zonally-averaged flow.

Randel, W. J.↗

NASA NTRS1993

GCM simulations of intraseasonal variability in the Pacific/North American region

General circulation model (GCM) simulations of low-frequency variability with time scales of 20 to 70 days are analyzed for the Pacific sector during boreal winter. The GCM's leading mode in the upper-tropospheric zonal wind is associated with fluctuations of the East Asian jet; this mode resembles, in both structure and amplitude, the Pacific/North American (PNA) pattern found in the observations on these time scales. In both the model and observations, the PNA anomaly is characterized by: (1) a linear balance in the upper-tropospheric vorticity budget with no significant Rossby wave source in the tropics, (2) a barotropic conversion of kinetic energy from the time mean Pacific jet, and (3) a north/south displacement of the Pacific storm track. In the GCM, the latter is associated with synoptic eddy heat flux and latent heat anomalies that appear to contribute to a strong lower-tropospheric source of wave activity over the North Pacific. This is in contrast to the observations, which show only a weak source of wave activity in this region.

Schubert, Siegfried↗

DOE OSTI2020

Self-assembly for electronics

Self-assembly, a process in which molecules, polymers, and particles are driven by local interactions to organize into patterns and functional structures, is being exploited in advancing silicon electronics and in emerging, unconventional electronics. Additionally, silicon electronics has relied on lithographic patterning of polymer resists at progressively smaller lengths to scale down device dimensions. Yet, this has become increasingly difficult and costly. Assembly of block copolymers and colloidal nanoparticles allows resolution enhancement and the definition of essential shapes to pattern circuits and memory devices. As we look to a future in which electronics are integrated at large numbers and in new forms for the Internet of Things and wearable and implantable technologies, we also explore a broader material set. Semiconductor nanoparticles and biomolecules are prized for their size-, shape-, and composition-dependent properties and for their solution-based assembly and integration into devices that are enabling unconventional manufacturing and new device functions.

36 MATERIALS SCIENCE↗

DOE OSTI2021

A high solids field-to-fuel research pipeline to identify interactions between feedstocks and biofuel production

Abstract Background Environmental factors, such as weather extremes, have the potential to cause adverse effects on plant biomass quality and quantity. Beyond adversely affecting feedstock yield and composition, which have been extensively studied, environmental factors can have detrimental effects on saccharification and fermentation processes in biofuel production. Only a few studies have evaluated the effect of these factors on biomass deconstruction into biofuel and resulting fuel yields. This field-to-fuel evaluation of various feedstocks requires rigorous coordination of pretreatment, enzymatic hydrolysis, and fermentation experiments. A large number of biomass samples, often in limited quantity, are needed to thoroughly understand the effect of environmental conditions on biofuel production. This requires greater processing and analytical throughput of industrially relevant, high solids loading hydrolysates for fermentation, and led to the need for a laboratory-scale high solids experimentation platform. Results A field-to-fuel platform was developed to provide sufficient volumes of high solids loading enzymatic hydrolysate for fermentation. AFEX pretreatment was conducted in custom pretreatment reactors, followed by high solids enzymatic hydrolysis. To accommodate enzymatic hydrolysis of multiple samples, roller bottles were used to overcome the bottlenecks of mixing and reduced sugar yields at high solids loading, while allowing greater sample throughput than possible in bioreactors. The roller bottle method provided 42–47% greater liquefaction compared to the batch shake flask method for the same solids loading. In fermentation experiments, hydrolysates from roller bottles were fermented more rapidly, with greater xylose consumption, but lower final ethanol yields and CO 2 production than hydrolysates generated with shake flasks. The entire platform was tested and was able to replicate patterns of fermentation inhibition previously observed for experiments conducted in larger-scale reactors and bioreactors, showing divergent fermentation patterns for drought and normal year switchgrass hydrolysates. Conclusion A pipeline of small-scale AFEX pretreatment and roller bottle enzymatic hydrolysis was able to provide adequate quantities of hydrolysate for respirometer fermentation experiments and was able to overcome hydrolysis bottlenecks at high solids loading by obtaining greater liquefaction compared to batch shake flask hydrolysis. Thus, the roller bottle method can be effectively utilized to compare divergent feedstocks and diverse process conditions.

09 BIOMASS FUELS↗

DOE OSTI2021

Reduced ecosystem resilience quantifies fine-scale heterogeneity in tropical forest mortality responses to drought

Sensitivity of forest mortality to drought in carbon-dense tropical forests remains fraught with uncertainty, while extreme droughts are predicted to be more frequent and intense. Here, in this study, the potential of temporal autocorrelation of high-frequency variability in Landsat Enhanced Vegetation Index (EVI), an indicator of ecosystem resilience, to predict spatial and temporal variations of forest biomass mortality is evaluated against in situ census observations for 64 site-year combinations in Costa Rican tropical dry forests during the 2015 ENSO drought. Temporal autocorrelation, within the optimal moving window of 24 months, demonstrated robust predictive power for in situ mortality (leave-one- out cross-validation R 2 = 0.54), which allows for estimates of annual biomass mortality patterns at 30 m resolution. Subsequent spatial analysis showed substantial fine-scale heterogeneity of forest mortality patterns, largely driven by drought intensity and ecosystem properties related to plant water use such as forest deciduousness and topography. Highly deciduous forest patches demonstrated much lower mortality sensitivity to drought stress than less deciduous forest patches after elevation was controlled. Our results highlight the potential of high-resolution remote sensing to “fingerprint” forest mortality and the significant role of ecosystem heterogeneity in forest biomass resistance to drought.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2019

The Seismic Signatures of Recently Formed Impact Craters on Mars

We investigated the seismic signatures of recent impact crater clusters on Mars that would be recorded by the Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight)seismometers. We used a database of 77 measured and dated impact sites, with craters with diameters between 2.1 and 33.8 m, along with inferred impact angle, bolide trajectory, and varying target material properties to empirically scale for the momentum, expected seismic source function, and radiation pattern of impacts. The impact source is simulated in a local 3‐Dfinite difference wave propagation code and coupled to teleseismic distances by scaling the spectra of 1‐D global synthetic seismograms. We use the InSight seismometer noise floors to estimate detectability of impact(s) across azimuth and distance. Our experiments reveal that impact clusters have a higher peak corner frequency resulting from energy contributed by smaller craters to the power spectrum. We also find that the time separation between individual impacts in a cluster is small (<10–15 ms) and requires a seismometer closely situated to the source (<10 km) and a high sampling rate (>100 Hz) to resolve individual impacts within the cluster. Two of the clusters in our database(>20‐m effective diameter) would have been detectable by InSight, with the assumptions that the Martian background noise and seismic attenuation are both low. Joint detection of surface changes from newly formed crater(s) in images and by InSight will provide precise source locations that are crucial for constraining the internal structure of Mars

N. C. Schmerra↗

NASA NTRS1981

An evaluation of the spatial resolution of soil moisture information

Rainfall-amount patterns in the central regions of the U.S. were assessed. The spatial scales of surface features and their corresponding microwave responses in the mid western U.S. were investigated. The usefulness for U.S. government agencies of soil moisture information at scales of 10 km and 1 km. was ascertained. From an investigation of 494 storms, it was found that the rainfall resulting from the passage of most types of storms produces patterns which can be resolved on a 10 km scale. The land features causing the greatest problem in the sensing of soil moisture over large agricultural areas with a radiometer are bodies of water. Over the mid-western portions of the U.S., water occupies less than 2% of the total area, the consequently, the water bodies will not have a significant impact on the mapping of soil moisture. Over most of the areas, measurements at a 10-km resolution would adequately define the distribution of soil moisture. Crop yield models and hydrological models would give improved results if soil moisture information at scales of 10 km was available.

Hardy, K. R.↗

DOE OSTI2020

Exceptional subgenome stability and functional divergence in the allotetraploid Ethiopian cereal teff

Teff (Eragrostis tef) is a cornerstone of food security in the Horn of Africa, where it is prized for stress resilience, grain nutrition, and market value. Here, we report a chromosome-scale assembly of allotetraploid teff (variety Dabbi) and patterns of subgenome dynamics. The teff genome contains two complete sets of homoeologous chromosomes, with most genes maintaining as syntenic gene pairs. TE analysis allows us to estimate that the teff polyploidy event occurred ~1.1 million years ago (mya) and that the two subgenomes diverged ~5.0 mya. Despite this divergence, we detect no large-scale structural rearrangements, homoeologous exchanges, or biased gene loss, in contrast to many other allopolyploids. The two teff subgenomes have partitioned their ancestral functions based on divergent expression across a diverse expression atlas. Together, these genomic resources will be useful for accelerating breeding of this underutilized grain crop and for fundamental insights into polyploid genome evolution.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Riverscape heterogeneity in estimated Chinook Salmon emergence phenology and implications for size and growth

Abstract Many salmonid‐bearing rivers exhibit thermal and hydrologic heterogeneity at multiple spatial and temporal scales, but how this translates into spatiotemporal patterns of fry emergence is poorly understood. Understanding this variability is important because emergence timing determines the biophysical conditions fish first experience (e.g., temperature, flow, and food supply), thereby influencing growth opportunities and survival during this critical life stage. We predicted spring Chinook Salmon ( Oncorhynchus tshawytscha ) emergence phenology across four northeastern Oregon subbasins over 5–9 years using empirical spawning and temperature data. We then related interannual emergence timing estimates to juvenile salmon size and growth rates at consistent sampling locations. There were clear longitudinal patterns of predicted emergence timing in each subbasin: The shape of these patterns was consistent among years, but not among subbasins. In two subbasins, emergence occurred progressively later with distance upstream, whereas in the other two subbasins emergence was earliest at upstream sites. Within each year, median emergence dates among sites within each subbasin ranged between 44 and 58 days. This spatial variation was comparable to interannual variation, with median emergence dates for a given location in each subbasin ranging between 47 and 74 days among years. Contrary to our expectations, juvenile salmon were not larger in years with earlier emergence, owing to slower estimated spring and summer growth rates compared to years with later emergence. Despite large interannual variation in estimated emergence dates, these results suggest that other factors (e.g., stream flow, temperature, and density‐dependence) were more important than growth duration in determining juvenile salmon growth rates and size among years. We demonstrated considerable spatial and interannual variation in emergence phenology within these subbasins. Understanding how this variation translates to spatiotemporal patterns of juvenile salmon habitat use, growth, and survival has important implications for guiding restoration efforts and understanding how climate change may impact these populations.

Kaylor, Matthew J.↗

DOE OSTI2021

Increasing temperature and flow management alter mercury dynamics in East Fork Poplar Creek

East Fork Poplar Creek (EFPC) is a mercury (Hg) contaminated creek in east Tennessee, USA. Stream restoration activities included the initiation of a flow management programme in 1996 in which water from a nearby lake was pumped to the head of the creek. We conducted regular water sampling for 2 years along the length of EFPC during active flow management and for 5 years after flow management stopped. Total Hg and total monomethylmercury (MMHg) concentration and flux decreased in the uppermost reaches of EFPC that were closest to the point of water addition. Most water quality parameters, including DOC concentration, remained unchanged after flow management termination. Nevertheless, SUVA 254 , a measure of dissolved organic matter (DOM) composition, increased and coincided with increased dissolved Hg (Hg D ) concentration and flux and decreased Hg solid-water partitioning coefficients throughout EFPC. Higher SUVA 254 and Hg D concentration have potential implications for bioavailability and MMHg production. Total and dissolved MMHg concentrations increased in lower reaches of EFPC after the end of flow management and these increases were most pronounced during spring and early summer when biota are more susceptible to exposure and uptake. A general warming trend in the creek after active flow management ended likely acted in concert with higher Hg D concentration to promote higher MMHg concentration. Total and dissolved MMHg concentrations were positively correlated with water temperature above a threshold value of 10°C. Concentration changes for Hg and MMHg could not be accounted for by changes in creek discharge that accompanied the cessation of flow management. In addition to the changing DOM composition in-stream, other watershed-scale factors likely contributed to the observed patterns, as these changes occurred over months rather than instantaneously after flow management stopped. Nevertheless, similar changes in MMHg have not been observed in a tributary to EFPC.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Conditional distribution estimation of building characteristics with diffusion models for urban energy modeling

Understanding current energy consumption behavior in communities is critical for informing future energy use decisions and enabling efficient energy management. Urban energy models, which are used to simulate these energy use patterns, require large datasets with detailed building characteristics for accurate outcomes. However, such detailed characteristics at the individual building level are often unknown and costly to acquire, or unavailable. Through this work, we propose using a generative modeling approach to generate realistic building attributes to fill in the data gaps and finally provide complete characteristics as inputs to energy models. Our model learns complex, building-level patterns from training on a large-scale residential building stock model containing 2.2 million buildings. We employ a tabular diffusion-based framework that is designed to handle heterogeneous (discrete and continuous) features in tabular building data, such as occupancy, floor area, heating, cooling, and other equipment details. We develop a capability for conditional diffusion, enabling the imputation of missing building characteristics conditioned on known attributes. We conduct a comprehensive validation of our conditional diffusion model, firstly by comparing the generated conditional distributions against the underlying data distribution, and secondly, by performing a case study for a Baltimore residential region, showing the practical utility of our approach. Our work is one of the first to demonstrate the potential of generative modeling to accelerate building energy modeling workflows.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Cascading from $\mathscr{N}$ = 2 supersymmetric Yang–Mills theory to confinement and chiral symmetry breaking in adjoint QCD

We argue that adjoint QCD in 3 + 1 dimensions, with any SU(N) gauge group and two Weyl fermion flavors (i.e. one adjoint Dirac fermion), confines and spontaneously breaks its chiral symmetries via the condensation of a fermion bilinear. We flow to this theory from pure $\mathscr{N}$ = 2 SUSY Yang–Mills theory with the same gauge group, by giving a SUSY-breaking mass M to the scalars in the $\mathscr{N}$ = 2 vector multiplet. This flow can be analyzed rigorously at small M, where it leads to a deconfined vacuum at the origin of the $\mathscr{N}$ = 2 Coulomb branch. The analysis can be extended to all M using an Abelian dual description that arises from the N multi-monopole points of the $\mathscr{N}$ = 2 theory. At each such point, there are N −1 hypermultiplet Higgs fields h$^{i=1,2}_m$, which are SU(2) R doublets. We provide a detailed study of the phase diagram as a function of M, by analyzing the semi-classical phases of the dual using a combination of analytic and numerical techniques. The result is a cascade of first-order phase transitions, along which the Higgs fields h i m successively turn on, and which interpolates between the Coulomb branch at small M, where all h$^{i}_m$ = 0, and a maximal Higgs branch, where all h$^{i}_m$ ≠ 0, at sufficiently large M. We show that this maximal Higgs branch precisely matches the confining and chiral symmetry breaking phase of two-flavor adjoint QCD, including its broken and unbroken symmetries, its massless spectrum, and the expected large-N scaling of various observables. The spontaneous breaking pattern SU(2) R → U(1) R , consistent with the Vafa–Witten theorem, is ensured by an intricate alignment mechanism for the h$^{i}_m$ in the dual, and leads to a CP 1 sigma model of increasing radius along the cascade.

D’Hoker, Eric [Univ. of California, Los Angeles, C↗