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DOE OSTI2025

RANGE: A robust adaptive nature-inspired global explorer of potential energy surfaces

With the growing demand for realistic representations of chemical structures and the advent of exascale computing, the intelligent sampling of potential energy surfaces and efficient identification of global minima have become more essential but also more feasible. Building on prior studies demonstrating the efficiency of the Artificial Bee Colony (ABC) swarm intelligence algorithm, we report a hybrid metaheuristic framework that integrates the adaptive exploration capabilities of ABC coupled with the exploitation strengths of genetic algorithms (GA) in a scalable, Python-based implementation. The resulting tool, RANGE (Robust Adaptive Nature-inspired Global Explorer), provides seamless interfaces to multiple potential energy evaluators, either directly or via widely used Python libraries, and is designed for high-performance computing environments. We describe the implementation details of RANGE and evaluate its performance, relative to ABC- or GA-alone based algorithms, on a variety of chemical systems, including molecular clusters and heterogeneous surfaces. In conclusion, our results demonstrate RANGE’s efficiency, robustness, and broad applicability in addressing challenging global optimization problems in computational chemistry and materials science.

Algorithms and data structure↗

DOE OSTI2016

Compensation for nonlinear effects in an optical orthogonal frequency-division multiplexed signal using adaptive modulation

We study the influence of nonlinear effects on symbol error statistics when a 16-QAM orthogonal frequency-division multiplexed signal is transmitted in a 1000 km length of fibre. A technique of adaptive modulation is proposed for generating signals that are resistant to nonlinear distortions. A considerable improvement of the transmission quality is shown to take effect in using an adaptive modulation scheme. (paper)

42 ENGINEERING↗

DOE OSTI2017

New adaptive optics control strategy for petawatt-class laser chains

A new generation of ultra-high intensity femtosecond petawatt- and above-class lasers requires new approaches to wavefront corrections. New challenges for adaptive optics consist in overcoming the constraints of potentially bigger diameters, larger amplitude aberrations, faster optics, higher risk of damaging optical components and faster and easier maintenance. Here we present a new technology of a mechanical deformable mirror, which has a large stroke, high temporal stability, low hysteresis, no print-through effect, easy, safe and fast maintenance and an operating frequency up to 10 Hz. We propose the full correction of the final focal spot in the target chamber by a combination of a standard adaptive optics system, a simple focal plane camera and a phase retrieval correction process. We test the reliability of the correction system in terms of intensity variation and wavefront stability. We further verify correction robustness of the method on a large spectral bandwidth and finally perform a focal spot correction on a terawatt laser system in both low and high-power regimes. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Adaptive correction of the image of an incoherent source object

The paper examines the operation of an optical system forming an image of an incoherent source object under conditions of atmospheric noise. The effect of atmospheric turbulence is considered. The calculations are performed in the Fresnel – Huygens approximation. The characteristics of the image for ‘long’ and ‘short’ exposures are investigated. The issues related to the adaptive correction of the general light wavefront slopes are discussed. The limits of applicability of phase adaptive correction using a reference source are shown. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Laser adaptive holographic hydroacoustic intensimeter

A new type of a vector hydrophone, a laser adaptive hydroacoustic intensimeter, is investigated. Two identical, spatially separated coil-type sensors are used as a primary receiver of the acoustic signal. The signals received at the sensor output are phase demodulated in a two-channel adaptive holographic interferometer based on two dynamic holograms multiplexed in a CdTe photorefractive crystal. Using a laser intensimeter, the acoustic field formed in a limited volume is studied. The performance characteristics of the intensimeter are determined experimentally; its threshold sensitivity, according to the acoustic field intensity, constitutes 0.1 × 10{sup −13} W m{sup −2}. (laser applications)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Peculiarities of adaptive phase correction of optical wave distortions under conditions of ‘strong’ intensity fluctuations

The reason for the loss of efficiency of adaptive phase correction in the propagation of optical waves in a turbulent atmosphere under conditions of ‘strong’ intensity fluctuations is experimentally explained for the first time. Based on the data from experiments conducted on both horizontal and vertical atmospheric paths, we have found that intensity fluctuations begin to significantly affect phase measurements when the coherence radius of the optical wave becomes less than the radius of the first Fresnel zone. Under these conditions, the main meter of adaptive optics systems, i. e. the Hartmann sensor, no longer provides correct measurements of the phase distribution in the presence of deep amplitude modulation. Based on the study of the behaviour of the mode components of the phase fluctuations reconstructed from the results of measurements in various operating regimes, we have found that, first of all, the amplitudes of the lowest modes of phase fluctuation expansion (tilts, defocusing, and astigmatism) are distorted, which, as the analysis shows, is very different from the regime of weak fluctuations. (atmospheric optics)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Adapting Nuclear Forensics from Light Water to Molten Salt Reactors: A Survey of Emerging Needs

Rising interest in molten salt reactors for commercial power production presents an opportunity to evaluate the techniques used to characterize materials of nuclear forensic interest. Since extensive research has been performed to identify and develop signatures of light water reactor (LWR) materials (e.g. uranium ore concentrates and uranium dioxide fuel pellets), we use this as a basis to explore possibilities for molten salt signature development. Through this comparative method, nuclear forensic signatures used today to identify the provenance of nuclear materials found out of regulatory control are adapted to molten salt reactor (MSR) fuel cycle materials. Radiological, elemental composition, isotopic composition, and model age signatures will likely not need large adaptations before being applied to MSR materials but may need to expand to be applicable to both thorium- and uranium-fueled systems. The liquid nature of molten salt fuel may erase signatures related to production and irradiation history that are informative for typical LWR materials. However, it may also lead to opportunities for new signatures, such as cooling rate–controlled morphology. Targets identified for further research include radiological attributes of fuel salts; elemental, chemical, and isotopic analysis of salts with differing production routes; morphological effects of various thermodynamic environments; and relevant fuel cycle radiochronometers. Additionally, the comparative nature of the proposed signatures implies a need for MSR-relevant databases and the production of salt standard reference materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

Adaptive Sequential Monte Carlo for Multiple Changepoint Analysis

Process monitoring and control requires detection of structural changes in a data stream in real time. This paper introduces an efficient sequential Monte Carlo algorithm designed for learning unknown changepoints in continuous time. The method is intuitively simple: new changepoints for the latest window of data are proposed by conditioning only on data observed since the most recent estimated changepoint, as these observations carry most of the information about the current state of the process. The proposed method shows improved performance over the current state of the art. Another advantage of the proposed algorithm is that it can be made adaptive, varying the number of particles according to the apparent local complexity of the target changepoint probability distribution. This saves valuable computing time when changes in the changepoint distribution are negligible, and enables re-balancing of the importance weights of existing particles when a significant change in the target distribution is encountered. The plain and adaptive versions of the method are illustrated using the canonical continuous time changepoint problem of inferring the intensity of an inhomogeneous Poisson process, although the method is generally applicable to any changepoint problem. Performance is demonstrated using both conjugate and non-conjugate Bayesian models for the intensity. Lastly, appendices to the article are available online, illustrating the method on other models and applications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

A fourth-order adaptive mesh refinement algorithm for the multicomponent, reacting compressible Navier–Stokes equations

In this study, we present a fourth-order in space and time block-structured adaptive mesh refinement algorithm for the compressible multicomponent reacting Navier–Stokes equations. The algorithm uses a finite-volume approach that incorporates a fourth-order discretisation of the convective terms. The time-stepping algorithm is based on a multi-level spectral deferred corrections method that enables explicit treatment of advection and diffusion coupled with an implicit treatment of reactions. The temporal scheme is embedded in a block-structured adaptive mesh refinement algorithm that includes subcycling in time with spectral deferred correction sweeps applied on levels. Here we present the details of the multi-level scheme paying particular attention to the treatment of coarse–fine boundaries required to maintain fourth-order accuracy in time. We then demonstrate the convergence properties of the algorithm on several test cases including both non-reacting and reacting flows. Finally we present simulations of a vitiated dimethyl ether jet in 2D and a turbulent hydrogen jet in 3D, both with detailed kinetics and transport.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Photon number resolving detection with a single-photon detector and adaptive storage loop

Abstract Photon number resolving (PNR) measurements are beneficial or even necessary for many applications in quantum optics. Unfortunately, PNR detectors are usually large, slow, expensive, and difficult to operate. However, if the input signal is multiplexed, photon ‘click’ detectors, that lack an intrinsic PNR capability, can still be used to realize photon number resolution. Here, we investigate the operation of a single click detector, together with a storage line with tunable outcoupling. Using adaptive feedback to adjust the storage outcoupling rate, the dynamic range of the detector can in certain situations be extended by up to an order of magnitude relative to a purely passive setup. An adaptive approach can thus allow for photon number variance below the quantum shot noise limit under a wider range of conditions than using a passive multiplexing approach. This can enable applications in quantum enhanced metrology and quantum computing.

Sullivan, Nicholas M. (ORCID:0000000248447296)↗

DOE OSTI2017

SkyFACT: high-dimensional modeling of gamma-ray emission with adaptive templates and penalized likelihoods

We present SkyFACT (Sky Factorization with Adaptive Constrained Templates), a new approach for studying, modeling and decomposing diffuse gamma-ray emission. Like most previous analyses, the approach relies on predictions from cosmic-ray propagation codes like GALPROP and DRAGON. However, in contrast to previous approaches, we account for the fact that models are not perfect and allow for a very large number (∼> 10{sup 5}) of nuisance parameters to parameterize these imperfections. We combine methods of image reconstruction and adaptive spatio-spectral template regression in one coherent hybrid approach. To this end, we use penalized Poisson likelihood regression, with regularization functions that are motivated by the maximum entropy method. We introduce methods to efficiently handle the high dimensionality of the convex optimization problem as well as the associated semi-sparse covariance matrix, using the L-BFGS-B algorithm and Cholesky factorization. We test the method both on synthetic data as well as on gamma-ray emission from the inner Galaxy, |ℓ|<90{sup o} and | b |<20{sup o}, as observed by the Fermi Large Area Telescope. We finally define a simple reference model that removes most of the residual emission from the inner Galaxy, based on conventional diffuse emission components as well as components for the Fermi bubbles, the Fermi Galactic center excess, and extended sources along the Galactic disk. Variants of this reference model can serve as basis for future studies of diffuse emission in and outside the Galactic disk.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Time-warping invariant quantum recurrent neural networks via quantum-classical adaptive gating

Adaptive gating plays a key role in temporal data processing via classical recurrent neural networks (RNNs), as it facilitates retention of past information necessary to predict the future, providing a mechanism that preserves invariance to time warping transformations. This paper builds on quantum RNNs (QRNNs), a dynamic model with quantum memory, to introduce a novel class of temporal data processing quantum models that preserve invariance to time-warping transformations of the (classical) input-output sequences. The model, referred to as time warping-invariant QRNN (TWI-QRNN), augments a QRNN with a quantum–classical adaptive gating mechanism that chooses whether to apply a parameterized unitary transformation at each time step as a function of the past samples of the input sequence via a classical recurrent model. The TWI-QRNN model class is derived from first principles, and its capacity to successfully implement time-warping transformations is experimentally demonstrated on examples with classical or quantum dynamics.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Accelerate microstructure evolution simulation using graph neural networks with adaptive spatiotemporal resolution

Abstract Surrogate models driven by sizeable datasets and scientific machine-learning methods have emerged as an attractive microstructure simulation tool with the potential to deliver predictive microstructure evolution dynamics with huge savings in computational costs. Taking 2D and 3D grain growth simulations as an example, we present a completely overhauled computational framework based on graph neural networks with not only excellent agreement to both the ground truth phase-field methods and theoretical predictions, but enhanced accuracy and efficiency compared to previous works based on convolutional neural networks. These improvements can be attributed to the graph representation, both improved predictive power and a more flexible data structure amenable to adaptive mesh refinement. As the simulated microstructures coarsen, our method can adaptively adopt remeshed grids and larger timesteps to achieve further speedup. The data-to-model pipeline with training procedures together with the source codes are provided.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Genome evolution and transcriptome plasticity is associated with adaptation to monocot and dicot plants in Colletotrichum fungi

Colletotrichum fungi infect a wide diversity of monocot and dicot hosts, causing diseases on almost all economically important plants worldwide. Colletotrichum is also a suitable model for studying gene family evolution on a fine scale to uncover events in the genome associated with biological changes. Here we present the genome sequences of 30 Colletotrichum species covering the diversity within the genus. Evolutionary analyses revealed that the Colletotrichum ancestor diverged in the late Cretaceous in parallel with the diversification of flowering plants. We provide evidence of independent host jumps from dicots to monocots during the evolution of Colletotrichum, coinciding with a progressive shrinking of the plant cell wall degradative arsenal and expansions in lineage-specific gene families. Comparative transcriptomics of 4 species adapted to different hosts revealed similarity in gene content but high diversity in the modulation of their transcription profiles on different plant substrates. Combining genomics and transcriptomics, we identified a set of core genes such as specific transcription factors, putatively involved in plant cell wall degradation. These results indicate that the ancestral Colletotrichum were associated with dicot plants and certain branches progressively adapted to different monocot hosts, reshaping the gene content and its regulation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Fluorescent and Bioluminescent Reporter Mouse-Adapted Ebola Viruses Maintain Pathogenicity and Can Be Visualized in Vivo

Abstract Ebola virus (EBOV) causes lethal disease in humans but not in mice. Here, we generated recombinant mouse-adapted (MA) EBOVs, including 1 based on the previously reported serially adapted strain (rMA-EBOV), along with single-reporter rMA-EBOVs expressing either fluorescent (ZsGreen1 [ZsG]) or bioluminescent (nano-luciferase [nLuc]) reporters, and dual-reporter rMA-EBOVs expressing both ZsG and nLuc. No detriment to viral growth in vitro was seen with inclusion of MA-associated mutations or reporter proteins. In CD-1 mice, infection with MA-EBOV, rMA-EBOV, and single-reporter rMA-EBOVs conferred 100% lethality; infection with dual-reporter rMA-EBOV resulted in 73% lethality. Bioluminescent signal from rMA-EBOV expressing nLuc was detected in vivo and ex vivo using the IVIS Spectrum CT. Fluorescent signal from rMA-EBOV expressing ZsG was detected in situ using handheld blue-light transillumination and ex vivo through epi-illumination with the IVIS Spectrum CT. These data support the use of reporter MA-EBOV for studies of Ebola virus in animal disease models.

Immunology↗

DOE OSTI2024

Surface-active antibiotic production as a multifunctional adaptation for postfire microorganisms

Abstract Wildfires affect soils in multiple ways, leading to numerous challenges for colonizing microorganisms. Although it is thought that fire-adapted microorganisms lie at the forefront of postfire ecosystem recovery, the specific strategies that these organisms use to thrive in burned soils remain largely unknown. Through bioactivity screening of bacterial isolates from burned soils, we discovered that several Paraburkholderia spp. isolates produced a set of unusual rhamnolipid surfactants with a natural methyl ester modification. These rhamnolipid methyl esters (RLMEs) exhibited enhanced antimicrobial activity against other postfire microbial isolates, including pyrophilous Pyronema fungi and Amycolatopsis bacteria, compared to the typical rhamnolipids made by organisms such as Pseudomonas spp. RLMEs also showed enhanced surfactant properties and facilitated bacterial motility on agar surfaces. In vitro assays further demonstrated that RLMEs improved aqueous solubilization of polycyclic aromatic hydrocarbons, which are potential carbon sources found in char. Identification of the rhamnolipid biosynthesis genes in the postfire isolate, Paraburkholderia kirstenboschensis str. F3, led to the discovery of rhlM, whose gene product is responsible for the unique methylation of rhamnolipid substrates. RhlM is the first characterized bacterial representative of a large class of integral membrane methyltransferases that are widespread in bacteria. These results indicate multiple roles for RLMEs in the postfire lifestyle of Paraburkholderia isolates, including enhanced dispersal, solubilization of potential nutrients, and inhibition of competitors. Our findings shed new light on the chemical adaptations that bacteria employ to navigate, grow, and outcompete other soil community members in postfire environments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Adaptive responses of Trichlorobacter lovleyi to nitrite detoxification reveal overlooked contributions of Geobacterales to nitrate ammonification

Abstract Poorly understood microorganisms “short-circuit” the nitrogen cycle via the dissimilatory nitrate reduction to ammonium to retain the element in agricultural lands and stimulate crop productivity. The prevalence of Geobacterales closely related to Trichlorobacter lovleyi in nitrate ammonification hotspots motivated us to investigate adaptive responses contributing to ammonification rates in the laboratory type strain T. lovleyi SZ. Here, we describe the identification of tightly regulated pathways for efficient nitrate foraging and respiration with acetate, an important intermediate of organic matter degradation that Geobacterales efficiently assimilate and oxidize. Challenging the established dogma that high carbon/nitrate ratios stimulate the reduction of nitrate to ammonium, T. lovleyi doubled rapidly across a wide range of ratios provided nitrate concentrations were low enough to prevent the accumulation of the toxic nitrite intermediate. Yet, excess electrons during hydrogenotrophic growth alleviated nitrite toxicity and stimulated the reduction of nitrate to ammonium even under conditions of severe acetate limitation. These findings underscore the importance of nitrite toxicity in the ammonification of nitrate by Geobacterales and provide much needed mechanistic understanding of microbial adaptations contributing to soil nitrogen conservation. This information is critical to enhance the predictive value of genomic-based traits in environmental surveys and to guide strategies for sustainable management of nitrogen fertilization as well as mitigation of green-house emissions and agrochemical leaching from agricultural lands.

Environmental Sciences & Ecology↗

DOE OSTI2020

Crystal structure of an atypical cobalamin riboswitch reveals RNA structural adaptability as basis for promiscuous ligand binding

Cobalamin riboswitches encompass a structurally diverse group of cis-acting, gene regulatory elements found mostly in bacterial messenger RNA and are classified into subtypes based on secondary and tertiary characteristics. An unusual variant of the cobalamin riboswitch with predicted structural features was identified in Bacillus subtilis over a decade ago, but its structure and mechanisms of cobalamin selectivity and translational control have remained unsolved. We present the crystal structure of the aptamer domain of this atypical cobalamin riboswitch and a model for the complete riboswitch, including its expression platform domain. We demonstrate that this riboswitch binds to multiple cobalamin derivatives and correlate its promiscuous behavior to its structure and unique arrangement of peripheral elements. Comparative structural analyses between conventional cobalamin riboswitches and the B. subtilis cobalamin riboswitch reveal that the likely basis for this promiscuous ligand binding is intrinsic structural adaptability encoded in the RNA structure. It suggests that cobalamin selectivity might ultimately be viewed as existing on a spectrum of affinity for each derivative rather than as belonging to distinct types based on ligand specificities. Our work provides an interesting and notable example of functional coupling of ligand-sensing and adaptive folding by a structured RNA molecule.

59 BASIC BIOLOGICAL SCIENCES↗