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DOE OSTI2021

The Bethe-Ansatz approach to the $$ \mathcal{N} $$ = 4 superconformal index at finite rank

We investigate the Bethe-Ansatz approach to the superconformal index of $$ \mathcal{N} $$ N = 4 supersymmetric Yang-Mills with SU( N ) gauge group in the context of finite rank, N . We explicitly explore the role of the various types of solutions to the Bethe-Ansatz Equations in recovering the exact index for N = 2 , 3. We classify the Bethe-Ansatz Equations solutions as standard (corresponding to a freely acting orbifold T 2 /Z m × Z n ) and non-standard. For N = 2, we find that the index is fully recovered by standard solutions and displays an interesting pattern of cancellations. However, for N ≥ 3, the standard solutions alone do not suffice to reconstruct the index. We present quantitative arguments in various regimes of fugacities that highlight the challenging role played by the continuous families of non-standard solutions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Asymptotic growth of the 4d $ \mathcal{N} $ = 4 index and partially deconfined phases

We study the Cardy-like asymptotics of the 4d N = 4 index and demonstrate the existence of partially deconfined phases where the asymptotic growth of the index is not as rapid as in the fully deconfined case. We then take the large-N limit after the Cardy-like limit and make a conjecture for the leading asymptotics of the index. While the Cardy-like behavior is derived using the integral representation of the index, we demonstrate how the same results can be obtained using the Bethe ansatz type approach as well. In doing so, we discover new non-standard solutions to the elliptic Bethe ansatz equations including continuous families of solutions for SU(N) theory with N ≥ 3. Here, we argue that the existence of both standard and continuous non-standard solutions has a natural interpretation in terms of vacua of N = 1* theory on R 3 × S 1 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Gravitational index of the heterotic string

The fundamental heterotic string has a tower of BPS states whose supersymmetric index has an exponential growth in the charges. We construct the saddle-point of the gravitational path integral corresponding to this index. The saddle-point configuration is a supersymmetric rotating non-extremal Euclidean black hole. This configuration is singular in the two-derivative theory. We show that the addition of higher-derivative terms in four-dimensional N = 2 supergravity resolves the singularity. In doing so, we extend the recently-developed “new attractor mechanism” to include the effect of higher-derivative terms. Remarkably, the one-loop, four-derivative F-term contribution to the prepotential leads to a precise match of the gravitational and microscopic index. We also comment, using the effective theory near the horizon, on the possibility of a string-size near-extremal black hole. Our results clarify the meaning of different descriptions of this system in the literature. The thermal state transitions to a winding condensate and a gas of strings without ever reaching a small black hole, while the index is captured by the rotating Euclidean black hole solution and is constant and thus smoothly connected to the microscopic ensemble.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Thermalization of the Kerr index of refraction in acetone and methanol using femtosecond pump-probe scattering spectroscopy

Femtosecond time-resolved pump-probe scattering is used to temporally investigate the index thermalization Δn(t) of the molecular motions associated with the Kerr nonlinear index n 2 . This is done using an intense 300 fs 1034 nm pump pulse and temporally probed by a 517 nm and supercontinuum pulse in acetone and methanol. The optically pumped molecular states change the index of refraction and through the processes of Raman and Rayleigh scattering are shown to engage in a 4-step energy relaxation process. Here, the pump first initiates the Kerr effect as well as populate resonant vibrational molecular motions, which act as a “mother” energy state. The electronic component of the Kerr effect is shown to couple with these vibrational modes through the process of Born-Oppenheimer coupling, which can be measured through the Raman scattering of the probe. The “mother” coupled state then decays into “daughter” anharmonic non-resonant states, which then further decay into “granddaughter” and thermal bath states. The population of these states alter the index of refraction in time, Δn(t), and can be measured through the changing in the probe beam’s Rayleigh scattering. This thermalization process takes ~5.5 ps in acetone and ~3.7 ps in methanol. The scattering signals from each Δn(t) thermalization stage in the localized region, (“mother”, to “daughter”, to “granddaughter”, to the bath states, to the ground state), are fitted to theoretical decay equations that show the rise and fall times of the energy decay routes.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

A Denoising Autoencoder for Improved Kikuchi Pattern Quality and Indexing in Electron Backscatter Diffraction

The rapid collection and indexing of electron diffraction patterns as produced via electron backscatter diffraction (EBSD) has enabled crystallographic orientation and structural determination, as well as additional property-determining strain and dislocation density information with increasing speed, resolution, and efficiency. Pattern indexing quality is reliant on the noise of the collected electron diffraction patterns, which is often convoluted by sample preparation and data collection parameters. EBSD acquisition is sensitive to many factors and thus can result in low confidence index (CI), poor image quality (IQ), and improper minimization of fit, which can result in noisy datasets and misrepresent the microstructure. In an attempt to enable both higher speed EBSD data collection and enable greater orientation fit accuracy with noisy datasets, an image denoising autoencoder was implemented to improve pattern quality. Here, we show that EBSD data processed through the autoencoder results in a higher CI, IQ, and a more accurate degree of fit. In addition, using denoised datasets in HR-EBSD cross correlative strain analysis can result in reduced phantom strain from erroneous calculations due to the increased indexing accuracy and improved correspondence between collected and simulated patterns.

36 MATERIALS SCIENCE↗

DOE OSTI2026

A theoretical index for understanding distinct land relative humidity trends in observations, reanalyses, and models

Land surface relative humidity (RH) is a key variable in the coupled land–atmosphere system that profoundly influences terrestrial hydroclimate and ecosystems. Yet historical changes in land RH are not well understood due to limited observations, biased reanalyses, and the lack of a framework for interpreting RH changes under multiple influencing factors. Here, we show that the spatiotemporal variability of land RH and its distinct historical trends among observations, reanalyses, and Earth system models are captured by a simple index based on the ratio of precipitation (P) to a modified potential evapotranspiration formulated independently of RH (PET°). The index provides a physical calibration of biased land RH in reanalyses and a quantitative framework for interpreting land RH changes. Over 1973–2024, land RH has decreased substantially, owing to the intrinsic rise in PET° with temperature and little increase in land precipitation. Reanalyses overestimate the observed RH decrease, consistent with exaggerated surface warming and precipitation decline. The index captures this coherent bias and enables a calibration using observed precipitation and temperature. Models simulate a wide range of land RH trends, but nearly all runs underrepresent the historical drying. The index captures the model spread and discrepancy and attributes them to contributions of precipitation and PET°. Weaker land RH decreases in models arise mainly from weaker subtropical precipitation declines, linked to muted intensification of subtropical highs and biased subtropical climatology. The model–observation discrepancy is unlikely explained by internal variability, implying model underestimation of forced RH decrease and a drier land future than current projections.

Earth system models↗

DOE OSTI2023

A phenomenological wobbling model for isolated pulsars and the braking index

ABSTRACT An isolated pulsar is a rotating neutron star possessing a very high magnetic dipole moment, thus providing a powerful radiating mechanism. These stars loose rotational energy E through various processes, including a plasma wind originating from a highly magnetized magnetosphere and the emission of magnetic dipole radiation (MDR). Such phenomena produce a time decreasing angular velocity Ω(t) of the pulsar that is usually quantified in terms of its braking index. Although these mechanisms are widely acknowledged as the primary drivers of the spin evolution of isolated pulsars, it is plausible that other contributing factors influencing this effect have yet to be comprehensively investigated. Most of young isolated pulsars present a braking index different from that given by the MDR and plasma wind processes. Working in the weak field (Newtonian) limit, we take in this work a step forward in describing the evolution of such a system by allowing the star’s shape to wobble around an ellipsoidal configuration as a backreaction effect produced by its rotational deceleration. It is assumed that an internal damping of the oscillations occurs, thus introducing another form of energy loss in the system, and this phenomenon may be related to the deviation of the braking index from the models based on $\dot{E} \sim -\Omega ^4$ predictions. Numerical calculations suggest that the average braking index for typical isolated pulsars can be thus explained by a simple phenomenological model.

Araujo, E. C. A. (ORCID:0000000213520879)↗

DOE OSTI2020

Predicting the Cetane Number, Yield Sooting Index, Kinematic Viscosity, and Cloud Point for Catalytically Upgraded Pyrolysis Oil Using Artificial Neural Networks

Abstract The conversion of biomass using fast pyrolysis has the potential to be significantly less expensive at scale compared to alternative methods such as fermentation and gasification. Selective upgrading of the products of fast pyrolysis through chemical catalysis produces compounds with lower oxygen content and lower acidity; however, identifying the specific catalytic pathways for producing viable fuels and fuel additives often requires a trial-and-error approach. Specifically, key properties of the compounds must be experimentally tested to evaluate the viability of the resultant compounds. The present work proposes predictive models constructed with artificial neural networks (ANNs) for cetane number (CN), yield sooting index (YSI), kinematic viscosity (KV), and cloud point (CP), with blind test set median absolute errors of 5.14 cetane units, 3.36 yield sooting index units, 0.07 millimeters squared per second, and 4.89 degrees Celsius, respectively. Furthermore, the cetane number, yield sooting index, kinematic viscosity, and cloud point were predicted for over three hundred expected products from the catalytic upgrading of pyrolysis oil. It was discovered that 130 of these compounds have predicted cetane numbers greater than 40, with four of these compounds possessing predicted yield sooting index values significantly less than that of diesel fuel and predicted viscosities and cloud points comparable to that of diesel fuel.

09 BIOMASS FUELS↗

DOE OSTI2021

Achieving extreme light confinement in low-index dielectric resonators through quasi-bound states in the continuum

Obtaining large field enhancement in low-refractive-index dielectric materials is highly relevant to many photonic and quantum optics applications. However, confining light in these materials is challenging, owing to light leakage through coupling to continuum modes in the surrounding environment. Here, we investigate the possibility of achieving high quality factors in low-index dielectric resonators through the bound states in the continuum (BIC). Our simulations demonstrate that destructive interference between leaky modes can be achieved by tuning the geometrical parameters of the resonator arrays, leading to the emergence of quasi-BIC in resonators that have a small index contrast to the underlying substrates. The resultant large field enhancement gives rise to giant quality factors and Purcell effects. By introducing vertical mirror symmetry, the quasi-BIC can be tuned into an ideal BIC. In addition, the quasi-BIC can modify the emission patterns of the coupled emitters, rendering highly directional and focused far-field emission. These findings may provide a path for the practical implementation of photonic and quantum devices based on low-index dielectric materials.

42 ENGINEERING↗

DOE OSTI2025

Eureka: Enabling Fine-Grained Access and Range Queries on Compressed Scientific Data via Data-Index Co-Compression

Handling large-scale scientific data in high-performance computing (HPC) environments poses significant challenges, including excessive I/O, high storage costs, and slow query performance. Traditional approaches often require full data decompression and scans, making them impractical for real-time or interactive analysis. To address these limitations, we introduce Eureka, a unified data-index co-compression framework that enables fine-grained access and efficient range queries on compressed scientific datasets. Eureka integrates spatial domain decomposition with block-wise error-bounded lossy compression to support selective decompression. It constructs a hierarchical AVL-tree index during compression to capture block-level value ranges, enabling fast pruning during query execution. To reduce metadata overhead, the index itself is also compressed while ensuring recall-preserving results. Experiments on six diverse HPC simulation datasets show that Eureka achieves up to 25x data compression and over 300x index compression, surpassing state-of-the-art compressors such as SZ3 and ZFP in rate-distortion performance. Additionally, Eureka delivers over 30x speedup for low-selectivity range queries, making it a scalable and efficient solution for modern scientific data analysis.

Yan, Ning↗

DOE OSTI2022

Low refractive index OLEDs for practical high-efficiency outcoupling. Final report

Improving OLED light extraction is a significant on-going challenge for the OLED lighting industry. The goal of this program was to explore the potential to improve internal light extraction in a manufacturable way by lowering the refractive index of the OLED stack through dilution with an electrically-inert, low refractive index molecule. We accomplished this goal, identifying a small molecule that can be co-evaporated in the hole transport layer of OLEDs at high loading to reduce the refractive index by 0.2-0.3 refractive index units without degrading charge transport. Implementing this dilution molecule in the hole transport layer of a range of single and multi-stack OLEDs, we demonstrated the ability to improve their internal light extraction by up to ~35% without increasing their drive voltage or reducing their operational lifetime. Importantly, these findings extend to state-of-the-art device architectures with proprietary OLED materials.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

The Workforce Readiness Index: A Local and Regional Assessment Tool for Energy Sector Preparedness

Building up a workforce that is properly trained and adequately sized is essential to ensuring that the deployment of energy generation sources in the United States meets future energy demand. Workforce development to support supply chain or large infrastructure investments typically occurs at a local level. However, there is a critical gap in understanding where and to what extent regional workforces are equipped to meet the needs of an energy industry. The Workforce Readiness Index ("the index") was developed to assess and compare energy sector workforce readiness across the United States at the county level to provide granular information to various stakeholders such as industry members, state decision makers, and training program developers. Workforce readiness is defined as the ability to recruit from the general labor market, transition workers with comparable skill sets, and train a workforce using scalable or existing training programs near a specific location. Therefore, the index evaluates readiness levels based on the likelihood that a county possesses the workforce development infrastructure needed to support the occupations required by an energy-related industry or sector. Furthermore, the index offers a standardized yet flexible approach that captures regional variations and highlights local strengths and challenges.

17 WIND ENERGY↗

DOE OSTI2022

Learning infinite-horizon average-reward restless multi-action bandits via index awareness

We consider the online restless bandits with average-reward and multiple actions, where the state of each arm evolves according to a Markov decision process (MDP), and the reward of pulling an arm depends on both the current state of the corresponding MDP and the action taken. Since finding the optimal control is typically intractable for restless bandits, existing learning algorithms are often computationally expensive or with a regret bound that is exponential in the number of arms and states. In this paper, we advocate \textit{index-aware reinforcement learning} (RL) solutions to design RL algorithms operating on a much smaller dimensional subspace by exploiting the inherent structure in restless bandits. Specifically, we first propose novel index policies to address dimensionality concerns, which are provably optimal. We then leverage the indices to develop two low-complexity index-aware RL algorithms, namely, (i) GM-R2MAB, which has access to a generative model; and (ii) UC-R2MAB, which learns the model using an upper confidence style online exploitation method. We prove that both algorithms achieve a sub-linear regret that is only polynomial in the number of arms and states. A key differentiator between our algorithms and existing ones stems from the fact that our RL algorithms contain a novel exploitation that leverages our proposed provably optimal index policies for decision-makings.

Xiong, Guojun↗

DOE OSTI2023

Circular queue management with split indexes

Methods and apparatus for managing circular queues are disclosed. A pointer designates an index position of a particular queue element and contains an additional pointer state, whereby two pointer values (split indexes) can designate the same index position. Front and rear pointers are respectively managed by dequeue and enqueue logic. The front pointer state and rear pointer state distinguish full and empty queue states when both pointers designate the same index position. Asynchronous dequeue and enqueue operations are supported, no lock is required, and no queue entry is wasted. Hardware and software embodiments for numerous applications are disclosed.

Miniskar, Narasinga Rao↗

DOE OSTI2021

A time-varying vulnerability index for COVID-19 in New Mexico, USA using generalized propensity scores

The coronavirus disease (COVID-19) pandemic has highlighted systemic inequities in the United States and resulted in a larger burden of negative social outcomes for marginalized communities. New Mexico, a state in the southwestern US, has a unique population with a large racial minority population and a high rate of poverty that may make communities more vulnerable to negative social outcomes from COVID-19. To identify which communities may be at the highest relative risk, we created a county-level vulnerability index. After the first COVID-19 case was reported in New Mexico on March 11, 2020, we fit a generalized propensity score model that incorporates sociodemographic factors to predict county-level viral exposure and thus, the generic risk to negative social outcomes such as unemployment or mental health impacts. We used four static sociodemographic covariates important for the state of New Mexico—population, poverty, household size, and minority population—and weekly cumulative case counts to iteratively run our model each week and normalize the exposure score to create a time-varying vulnerability index. We found the relative vulnerability between counties varied in the first eight weeks from the initial COVID-19 case before stabilizing. This framework for creating a location-specific vulnerability index in response to an ongoing disaster may be used as a quick, deployable metric to inform health policy decisions such as allocating state resources to the county level.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Evaluating the effectiveness of M-AMBI with other biotic indexes in a temperate estuary

Need for a scalable and widely applicable index has been increasingly important. This study evaluates the applicability of the M-AMBI, a potential comprehensive index, at small spatial scales. M-AMBI was compared to regional indices (EMAP-E and GOM B-IBI), assessing response to natural environmental gradients and low oxygen stress. Results indicate poor agreement between indices with M-AMBI and GOM B-IBI showing positive correlation but significant disagreement in habitat condition. EMAP-E had no agreement. Indices showed similar patterns of better habitat scores in higher salinities. M-AMBI also showed a negative relationship with sediment organic matter and total nitrogen. DO influenced all indices with M-AMBI the most sensitive. However, mismatches between DO and index score were observed further calibration may be needed before adoption into programs. Altogether, the M-AMBI demonstrates potential at smaller, local scales, but additional studies are needed to validate its performance in different coastal environments and under different conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

LaueMatching: an approach for rapid and robust indexing of Laue diffraction patterns

Traditional Laue diffraction pattern indexing often struggles with noisy data, weak signals, peak overlap and missing reflections, particularly from complex or deformed microstructures. Here, we introduce LaueMatching, a high-throughput indexing algorithm designed to overcome these limitations. LaueMatching utilizes a fundamentally different approach based on direct pattern correlation: experimentally pre-processed images are compared against a comprehensive pre-computed library of simulated diffraction patterns corresponding to a dense grid of possible orientations. This approach bypasses the need for explicit peak identification and fitting, steps that are often a failure point for traditional methods. The algorithm rapidly and robustly indexes multiple crystallographic orientations and crystal systems simultaneously, even from challenging patterns. LaueMatching's effectiveness and accuracy have been rigorously tested and validated on diverse experimental (Ni, Al, EuAl 2 O 4 ) and simulated diffraction patterns, demonstrating high-fidelity orientation refinement. Code to implement this approach on both CPU and GPU resources can be downloaded from https://github.com/AdvancedPhotonSource/LaueMatching.

36 MATERIALS SCIENCE↗

DOE OSTI2024

scifi-ATAC-seq: massive-scale single-cell chromatin accessibility sequencing using combinatorial fluidic indexing

Abstract Single-cell ATAC-seq has emerged as a powerful approach for revealing candidate cis-regulatory elements genome-wide at cell-type resolution. However, current single-cell methods suffer from limited throughput and high costs. Here, we present a novel technique called scifi-ATAC-seq, single-cell combinatorial fluidic indexing ATAC-sequencing, which combines a barcoded Tn5 pre-indexing step with droplet-based single-cell ATAC-seq using the 10X Genomics platform. With scifi-ATAC-seq, up to 200,000 nuclei across multiple samples can be indexed in a single emulsion reaction, representing an approximately 20-fold increase in throughput compared to the standard 10X Genomics workflow.

59 BASIC BIOLOGICAL SCIENCES↗