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At least 55 records · Page 3

MZA: A Data Conversion Tool to Facilitate Software Development and Artificial Intelligence Research in Multidimensional Mass Spectrometry

Modern mass spectrometry-based workflows employing hybrid instrumentation and orthogonal separations collect multidimensional data, potentially allowing deeper understanding in omics studies through adoption of artificial intelligence methods. However, the large volume of these rich data challenges existing data storage and access technologies, therefore precluding informatics advancements. Here we present MZA™ (pronounced m-za), the mass-to-charge (m/z) generic data storage and access tool designed to facilitate software development and artificial intelligence research in multidimensional mass spectrometry measurements. Composed by a data conversion tool and a simple file structure based on the HDF5 format, MZA provides easy, cross-platform and efficient programmatic access to raw MS-data, enabling fast development of new tools in data science programming languages such as Python and R. The software executable and example Python and R scripts are freely available at https://github.com/PNNL-m-q/mza.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multidimensional Distributional Neural Network Output Demonstrated in Super‐Resolution of Surface Wind Speed

Accurate quantification of uncertainty in neural network predictions remains a central challenge for scientific applications involving high-dimensional, correlated data. While existing methods capture either aleatoric or epistemic uncertainty, few offer closed-form, multidimensional distributions that preserve spatial correlation while remaining computationally tractable. In this work, we present a framework for training neural networks with a multidimensional Gaussian loss, generating a closed-form predictive distribution over outputs informed by non-identically distributed training data. Our approach captures aleatoric uncertainty by iteratively estimating the means and covariance matrices, and is demonstrated on a super-resolution example out-of-training-sample. We leverage a Fourier representation of the covariance matrix to stabilize network training and preserve spatial correlation. We introduce a novel regularization strategy—referred to as information sharing—that interpolates between image-specific and global covariance estimates, enabling convergence of the super-resolution downscaling network trained on image-specific distributional loss functions. This framework allows for efficient sampling, explicit correlation modeling, and extensions to more complex distribution families all without disrupting prediction performance. We demonstrate the method on a surface wind speed downscaling task and discuss its broader applicability to uncertainty-aware prediction in scientific models.

17 WIND ENERGY↗

Multidimensional low-Mach number time-implicit hydrodynamic simulations of convective helium shell burning in a massive star

A realistic parametrization of convection and convective boundary mixing in conventional stellar evolution codes is still the subject of ongoing research. Furthermore, to improve the current situation, multidimensional hydrodynamic simulations are used to study convection in stellar interiors. Such simulations are numerically challenging, especially for flows at low Mach numbers which are typical for convection during early evolutionary stages. We explore the benefits of using a low-Mach hydrodynamic flux solver and demonstrate its usability for simulations in the astrophysical context. Simulations of convection for a realistic stellar profile are analyzed regarding the properties of convective boundary mixing. The time-implicit Seven-League Hydro (SLH) code was used to perform multidimensional simulations of convective helium shell burning based on a 25 M ⊙ star model. The results obtained with the low-Mach AUSM + -up solver were compared to results when using its non low-Mach variant AUSM B + -up. We applied well-balancing of the gravitational source term to maintain the initial hydrostatic background stratification. The computational grids have resolutions ranging from 180 × 90 2 to 810 × 540 2 cells and the nuclear energy release was boosted by factors of 3 × 10 3 , 1 × 10 4 , and 3 × 10 4 to study the dependence of the results on these parameters.

79 ASTRONOMY AND ASTROPHYSICS↗

Do not forget the electrons: Extending moderately-sized nuclear networks for multidimensional hydrodynamic codes

Context.Nuclear networks are widely used coupled with hydrodynamical simulations of explosive scenarios to account for the change of nuclear species and energy generation rate due to nuclear reactions. In this way, there is a feedback mechanism between the hydrodynamical state and the nuclear processes. Unfortunately, the timescale of nuclear reactions is orders of magnitude smaller than the dynamical timescale that drives hydrodynamical simulations. Therefore, these nuclear networks are usually very small, reduced in most cases to a dozen elements, especially when simulations are carried out in more than one dimension. Aims.We present here an extended nuclear network, with 90 species, designed for being coupled with hydrodynamic simulations, which includes neutrons, protons, electrons, positrons, and the corresponding neutrino and anti-neutrino emission. This network is also coupled with temperature, making it extremely robust and, together with its size, unique of its kind. The inclusion of electron captures on free protons makes the network very appropriate for multidimensional studies of Type Ia supernova explosions, especially when the exploding object is a massive white dwarf. Methods.We perform several tests that are relevant to simulate explosive scenarios, such as Type Ia supernovae and core-collapse supernovae. We compare the results of the 90 nuclei network with a standardα-chain network with 14 elements to evaluate the differences in the energy generation rate. We also evaluate the relevance of including the electrons in the network in terms of generated yields and how it affects the pressure of a degenerate fluid such as that of white dwarfs. The results obtained with the 90-nuclei network have been verified with a much larger 2000-nuclei network built from REACLIB (WinNet), in terms of nuclear energy generation rate, pressure, and produced yields. Results.The results obtained with the proposed medium-sized network compare fairly well, to a few percent, with those computed withWinNetin scenarios reproducing the gross physical conditions of current Type Ia supernova explosion models. In those cases where the carbon and oxygen fuel ignites at high density, the high-temperature plateau typical of the nuclear statistical equilibrium regime is well defined and stable, allowing large integration time steps. We show that the inclusion of electron captures on free protons substantially improves the estimation of the electron fraction of the mixture. Therefore, the pressure is better determined than in networks where electron captures are excluded, which will ultimately lead to more reliable hydrodynamic models. Explosive combustion of helium at low density, occurring near the surface layer of a white dwarf, is also better described with the proposed network, which gives nuclear energy generation rates much closer toWinNetthan typical reduced alpha networks. Conclusions.A nuclear network withN= 90 species, including electrons, aimed at multidimensional calculations of supernova explosions is described and verified. The proposed network is suitable for the study of Type Ia supernova explosions because it provides better values of pressure and electron abundance than other existing networks with smaller or even a similar size but without including electron capture processes.

Astronomy & Astrophysics↗

Multimodal, Multidimensional, and Multiscale X-ray Imaging at the National Synchrotron Light Source II

Over the last couple of decades, the synchrotron radiation research community has witnessed tremendous advancement in the field of x-ray imaging and microscopy. Continuing enhancement of the light sources’ brightness, advances in x-ray focusing optics, incorporation of precision instruments, and development of innovative imaging techniques are some of the leading contributors for the rapid progress. New imaging and microscopy beamlines, such as the ones at the National Synchrotron Light Source II (NSLS-II), a Department of Energy (DOE) Office of Science user facility located at DOE’s Brookhaven National Laboratory, are capable of performing more sophisticated and complicated measurements than ever before, either on their own or used together as a suite of tools. These sophisticated and complex measurements exhibit attributes for multimodal, multidimensional, and multiscale imaging. Recent popularity of these methods is strongly driven by the current trends in materials characterizations, where researchers desire to map out hierarchical materials structure over a large range of length scales, to understand structure-property correlation, to quantify materials structures in 3D, and/or to perform operando or in situ experiments. It is important to emphasize that “materials” under investigation are not only synthesized materials but also the natural materials. In this article, we describe multimodal, multidimensional and multiscale x-ray imaging capabilities of the NSLS-II beamlines and how these methods are used to tackle complex scientific problems.

47 OTHER INSTRUMENTATION↗

TTHRESH: Tensor Compression for Multidimensional Visual Data

Memory and network bandwidth are decisive bottlenecks when handling high-resolution multidimensional data sets in visualization applications, and they increasingly demand suitable data compression strategies. In this paper, we introduce a novel lossy compression algorithm for multidimensional data over regular grids. It leverages the higher-order singular value decomposition (HOSVD), a generalization of the SVD to three dimensions and higher, together with bit-plane, run-length and arithmetic coding to compress the HOSVD transform coefficients. Our scheme degrades the data particularly smoothly and achieves lower mean squared error than other state-of-the-art algorithms at low-to-medium bit rates, as it is required in data archiving and management for visualization purposes. Further advantages of the proposed algorithm include very fine bit rate selection granularity and the ability to manipulate data at very small cost in the compression domain, for example to reconstruct filtered and/or subsampled versions of all (or selected parts) of the data set.

97 MATHEMATICS AND COMPUTING↗

Multidimensional spectroscopy with attosecond extreme ultraviolet and shaped near-infrared pulses

Dynamics following excitation with attosecond extreme ultraviolet (XUV) pulses arise from enormous numbers of accessible excited states, complicating the retrieval of state-specific time evolutions. We develop attosecond XUV multidimensional spectroscopy here to separate interfering pathways on a near-infrared (NIR) energy axis, retrieving single state dynamics in argon atoms in a two-dimensional (2D) XUV-NIR spectrum. In this experiment, we measure four-wave mixing signal arising from the interaction of XUV attosecond pulses centered around 15 eV with two few-cycle NIR pulses. The 2D spectrum is created by measuring the emitted XUV signal field spectrum while applying narrowband amplitude and phase modulations to one of the NIR pulses. Application of such a technique to systems of high dimensionality will provide for the observation of state-resolved pure electronic dynamics, in direct analogy to phenomena unraveled by multidimensional spectroscopies at optical frequencies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Coupling Front-End Separations, Ion Mobility Spectrometry, and Mass Spectrometry For Enhanced Multidimensional Biological and Environmental Analyses

Ion mobility spectrometry (IMS) is a widely used analytical technique for rapid molecular separations in the gas phase. IMS alone is useful, but its coupling with mass spectrometry (MS) and front-end separations has been extremely beneficial for increasing measurement sensitivity, peak capacity of complex mixtures, and the scope of molecular information in biological and environmental sample analyses. Multiple studies in disease screening and environmental evaluations have even shown these IMS-based multidimensional separations extract information not possible with each technique individually. This review highlights 3-dimensional separations using IMS-MS in conjunction with a range of front-end techniques, such as gas chromatography (GC), supercritical fluid chromatography (SFC), liquid chromatography (LC), solid phase extractions (SPE), capillary electrophoresis (CE), field asymmetric ion mobility spectrometry (FAIMS), and microfluidic devices. The origination, current state, various applications, and future capabilities for these multidimensional approaches are described to provide insight into the utility and potential of each technique.

Environmental Molecular Sciences Laboratory↗

Multidimensional scaling informed by F -statistic: Visualizing grouped microbiome data with inference

Multidimensional scaling (MDS) is a widely used dimensionality reduction technique in microbial ecology data analysis that captures the multivariate structure of the data while preserving pairwise distances between samples. While improvements in MDS have enhanced the ability to reveal group-specific data patterns, these MDS-based methods require prior assumptions for inference, limiting their application in general microbiome analysis. Here, in this study, we introduce a new MDS-based ordination method, “F-informed MDS,” which configures the data distribution based on the F-statistic, the ratio of dispersion between groups sharing common and different characteristics. Using semisynthetic datasets, we demonstrate that the proposed method is robust to hyperparameter selection while maintaining statistical significance throughout the ordination process. Various quality metrics for evaluating dimensionality reduction confirm that F-informed MDS is comparable to state-of-the-art methods in preserving both local and global data structures. Its application to a diatom-associated bacterial community suggests the role of this new method in interpreting the community’s response to the host. Our approach offers a well-founded refinement of MDS that aligns with statistical test results, which can be beneficial for broader multidimensional data analyses in microbiology and ecology. This new visualization tool can be incorporated into standard microbiome data analyses.

Biological and medical sciences↗

Multidimensional partial wave analysis of SIDIS dihadron beam spin asymmetries at CLAS12

Dihadron beam spin asymmetries provide a wide range of insights into nucleon structure and hadronization. Recent measurements at CLAS12 provide the first empirical evidence of nonzero G_1^\perp G 1 ⊥ , the parton helicity-dependent dihadron fragmentation function (DiFF) encoding spin-momentum correlations in hadronization. These measurements also allow for a point-by-point extraction of the subleading-twist PDF e(x) e ( x ) in a collinear framework. We observe different behavior of the asymmetries in different invariant mass regions, motivating a fully multidimensional study. The DiFFs also expand in terms of partial waves, each corresponding to the interference of dihadrons of particular polarizations. Altogether a fully multidimensional partial wave analysis is needed, and this presentation will summarize the efforts and results obtained thus far.

Dilks, Christopher↗

Exploring Multidimensional Spatial-Temporal Hydropower Operational Flexibilities by Modeling and Optimizing Water-Constrained Cascading Hydroelectric Systems

Because of unique characteristics such as clean and cost-competitive electricity as well as fast-ramping and storage abilities, the power industry continues to evolve its operation strategies for cascading hydroelectric (CHE) systems for providing enhanced values to the grid, especially under the deeper renewable resource integration. However, existing operation practices of CHEs predate the integration of renewables, which could prohibit the effective utilization of their inherent flexibilities in delivering maximum financial benefits and providing valuable grid services to the power system and electricity market operations. Indeed, modeling and optimizing these resource-limited while flexible CHE assets with uncertainties and imperfect information across multiple spatial-temporal dimensions present significant challenges. To facilitate CHE facility operators in effectively coordinating water usage and hydropower plant operations across multiple timescales, this project aims to fill the existing gaps by developing a suite of accurate water inflow (WI) forecast models as well as enhanced CHE modeling and optimization approaches with proper consideration of their unique characteristics, which would help explore their multidimensional spatial-temporal operational flexibility potentials. The developed approaches could better align reservoir operation strategies with variability and uncertainty of future water availability. They can also promote more effective utilization of multidimensional spatial-temporal hydropower operational flexibility potentials by designing long-term evacuation plans of reservoirs and short-term operation of CHEs, along with their coordination with other types of renewables. The project leverages various resources to facilitate the research and development activities, including actual characteristics data of CHE systems and a library of current and future cases of Portland General Electric (PGE). These realistic data enable the project team to study how to maximize the value of CHEs under current and future portfolios and evaluate opportunities to improve operation practices.

13 HYDRO ENERGY↗

Multidimensional Coherent Spectroscopy of van der Waals materials and heterostructures (Final Technical Report)

This project advanced multidimensional coherent spectroscopy (MDCS) and related spectroscopic-imaging methods as quantitative probes of many-body optical excitations in two-dimensional (2D) van der Waals (vdW) semiconductors and their heterostructures. Monolayer transition-metal dichalcogenides (TMDs) such as MoSe 2 and WSe 2 provide a uniquely strong platform for excitonic physics due to reduced dielectric screening, which enhances Coulomb interactions and makes higher-order correlated states (e.g., biexcitons and exciton–trion correlations) more prominent than in conventional bulk semiconductors. At the same time, the same sensitivity that enables strong interactions also increases susceptibility to spatial inhomogeneity—e.g., strain gradients, wrinkles, nanoscale disorder potentials, and charge puddling—which can broaden resonances, obscure interaction signatures, and complicate device-to-device reproducibility. The work reported here addressed this dual opportunity and challenge by: (i) developing and deploying coherent multidimensional methods (including double-quantum MDCS) capable of isolating interaction signals with reduced background, (ii) integrating electrostatic control to tune carrier populations and interaction strengths in situ, and (iii) introducing complementary spatially resolved photoluminescence (PL) techniques—hyperspectral PL imaging and polarization-/field-dependent PL lineshape analysis—to directly quantify disorder, strain, and localization that govern the coherent response.

36 MATERIALS SCIENCE↗

Multidimensional Parameter Study of Double Detonation Type Ia Supernovae Originating from Thin Helium Shell White Dwarfs

Despite the importance of Type Ia supernovae (SNe Ia) throughout astronomy, the precise progenitor systems and explosion mechanisms that drive SNe Ia are still unknown. An explosion scenario that has gained traction recently is double detonation, in which an accreted shell of He detonates and triggers a secondary detonation in the underlying white dwarf. Our research presents a number of high-resolution, multidimensional, full-star simulations of thin-He-shell, sub-Chandrasekhar-mass white dwarf progenitors that undergo a double detonation. This suite of thin-shell progenitors incorporates He shells that are thinner than those in previous multidimensional studies. We confirm the viability of the double detonation across a range of He-shell parameter space, as well as present bulk yields and ejecta profiles for each progenitor. The yields obtained are generally consistent with previous works and indicate the likelihood of producing observables that resemble SNe Ia. The dimensionality of our simulations allow us to examine features of the double detonation more closely, including the details of the off-center secondary ignition and asymmetric ejecta. We find considerable differences in the high-velocity extent of postdetonation products across different lines of sight. The data from this work will be used to generate predicted observables and may further support the viability of the double detonation scenario as an SN Ia channel, as well as show how the properties of the progenitor or viewing angle may influence trends in observable characteristics.

79 ASTRONOMY AND ASTROPHYSICS↗

Multidimensional CFM-O3 modeling

Examples of feedback among radiative, chemical and dynamical processes are discussed. The characteristics of the two dimensional (2-D) and three dimensional (3-D) models used in stratospheric ozone studies are discussed. The status of these multidimensional atmospheric photochemical models, their current capabilities and limitations, and possible impact on the chlorofluoromethane problem are presented. Requirements, techniques and problems of the parameterization of transport in 3-D models are described, the observational needs of multidimensional models are presented, and a summary is provided.

Source record↗

Analytical prediction with multidimensional computer programs and experimental verification of the performance, at a variety of operating conditions, of two traveling wave tubes with depressed collectors

Experimental and analytical results are compared for two high performance, octave bandwidth TWT's that use depressed collectors (MDC's) to improve the efficiency. The computations were carried out with advanced, multidimensional computer programs that are described here in detail. These programs model the electron beam as a series of either disks or rings of charge and follow their multidimensional trajectories from the RF input of the ideal TWT, through the slow wave structure, through the magnetic refocusing system, to their points of impact in the depressed collector. Traveling wave tube performance, collector efficiency, and collector current distribution were computed and the results compared with measurements for a number of TWT-MDC systems. Power conservation and correct accounting of TWT and collector losses were observed. For the TWT's operating at saturation, very good agreement was obtained between the computed and measured collector efficiencies. For a TWT operating 3 and 6 dB below saturation, excellent agreement between computed and measured collector efficiencies was obtained in some cases but only fair agreement in others. However, deviations can largely be explained by small differences in the computed and actual spent beam energy distributions. The analytical tools used here appear to be sufficiently refined to design efficient collectors for this class of TWT. However, for maximum efficiency, some experimental optimization (e.g., collector voltages and aperture sizes) will most likely be required.

Dayton, J. A., Jr.↗

Multidimensional aspects: Ozone, temperature and transport

The capability for obtaining four-dimensional data on stratospheric structure, dynamics, and zone is discussed. Progress in the development of multidimensional models of the stratosphere is reported. The discussion of multidimensional aspects of the stratosphere is divided into four major sections: observations, analysis and interpretation, modeling, and transport of trace species.

Source record↗

The Use of Interactive Raster Graphics in the Display and Manipulation of Multidimensional Data

Techniques for the review, display, and manipulation of multidimensional data are developed and described. Multidimensional data is meant in this context to describe scalar data associated with a three dimensional geometry or otherwise too complex to be well represented by traditional graphs. Raster graphics techniques are used to display a shaded image of a three dimensional geometry. The use of color to represent scalar data associated with the geometries in shaded images is explored. Distinct hues are associated with discrete data ranges, thus emulating the traditional representation of data with isarithms, or lines of constant numerical value. Data ranges are alternatively associated with a continuous spectrum of hues to show subtler data trends. The application of raster graphics techniques to the display of bivariate functions is explored.

Anderson, D. C.↗

Multidimensional Programming Methods for Energy Facility Siting: Alternative Approaches

The use of multidimensional optimization methods in solving power plant siting problems, which are characterized by several conflicting, noncommensurable objectives is addressed. After a discussion of data requirements and exclusionary site screening methods for bounding the decision space, classes of multiobjective and goal programming models are discussed in the context of finite site selection. Advantages and limitations of these approaches are highlighted and the linkage of multidimensional methods with the subjective, behavioral components of the power plant siting process is emphasized.

Solomon, B. D.↗