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DOE OSTI2022

Kinematic Variables and Feature Engineering for Particle Phenomenology

Kinematic variables have been playing an important role in collider phenomenology, as they expedite discoveries of new particles by separating signal events from unwanted background events and allow for measurements of particle properties such as masses, couplings, spins, etc. For the past 10 years, an enormous number of kinematic variables have been designed and proposed, primarily for the experiments at the Large Hadron Collider, allowing for a drastic reduction of high-dimensional experimental data to lower-dimensional observables, from which one can readily extract underlying features of phase space and develop better-optimized data-analysis strategies. We review these recent developments in the area of phase space kinematics, summarizing the new kinematic variables with important phenomenological implications and physics applications. We also review recently proposed analysis methods and techniques specifically designed to leverage the new kinematic variables. As machine learning is nowadays percolating through many fields of particle physics including collider phenomenology, we discuss the interconnection and mutual complementarity of kinematic variables and machine learning techniques. We finally discuss how the utilization of kinematic variables originally developed for colliders can be extended to other high-energy physics experiments including neutrino experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2019

New York City Panel on Climate Change 2019 Report Chapter 1: Introduction

While urban areas like New York City and its surrounding metropolitan region are key drivers of climate change through emissions of greenhouse gases, cities are also significantly impacted by climate shifts, both chronic changes and extreme events. These are already affecting the New York metropolitan region, including the five boroughs of New York City through higher temperatures, more intense precipitation, and higher sea levels, and will increasingly do so in the coming decades. The City of New York has embarked on a flexible adaptation pathway (i.e., strategies that can evolve through time as climate risk assessment, evaluation of adaptation strategies, and monitoring continues) to respond to climate change challenges. This entails significant programs to develop resilience in communities and critical infrastructure to observed and projected changes in temperature, precipitation, and sea level. The first NPCC Report laid out the risk management framing for the city and region via flexible adaptation pathways. The second New York City Panel on Climate Change Report (NPCC2) developed the “climate projections of record” that are currently being used by the City of New York in its resilience programs . The NPCC3 2019 Report co-generates new tools and methods for the next generation of climate risk assessments and implementation of region-wide resilience. Co-generation is an interactive process by which stakeholders and scientists work together to produce climate change information that is targeted to decision-making needs. These tools and methods can be used to observe, project, and map climate extremes; monitor risks and responses; and engage with communities to develop effective programs. They are especially important at “transformation points” in the adaptation process when large changes in the structure and function of physical, ecological, and social systems of the city and region are undertaken.

Rosenzweig, Cynthia↗

DOE OSTI2026

A coupled hydrologic-agroeconomic modeling framework to evaluate adaptive irrigation strategies under groundwater withdrawal restrictions

Growing groundwater scarcity requires integrated tools to capture interactions among hydrology, agricultural production, markets, and land use. This study presents an iterative modeling framework that couples hydrologic, crop-yield, and economic models to capture two-way feedback among water availability, agricultural production, and market responses under groundwater constraints. The primary goal of this paper is to describe the methodological development of the coupled framework and demonstrate the significance of iterative model interaction. Applied to the western United States, we evaluated adaptive responses to restricting groundwater use beyond recharge levels, represented through changes in irrigation management and expansion or shrinkage of crop markets through land reallocation. Results demonstrate that the iterative coupling converges to stable equilibrium responses within 10 iterations. At equilibrium, deficit irrigation emerges as the dominant adaptation strategy in California, with irrigation levels stabilizing at approximately 70% of full irrigation demand, while Arizona and New Mexico experience stronger yield sensitivities. Early iterations produce commodity price increases of up to 10% for fruit and vegetable crops; however, these responses moderate as land allocation and production patterns adjust across regions. Deficit irrigation and spatial reallocation of irrigated land partially offset production losses, with variability observed across different states: California maintains yields primarily via deficit irrigation, whereas Arizona and New Mexico will rely mainly on reducing irrigated area to absorb the shock. By capturing feedback between biophysical and economic processes, this approach highlights how irrigation strategies and land-use decisions evolve under water stress and provides a transferable platform for evaluating water management policies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

New physics contamination to precision luminosity measurements at future 𝑒 +⁢ 𝑒 − colliders

Several key observables of the high-precision physics program at future lepton colliders will critically depend on the knowledge of the absolute machine luminosity. The determination of the luminosity relies on the precise knowledge of some reference process, which is, in principle, not affected by unknown physics, so that its cross section can be computed within a well-established theory, like the Standard Model. Quantifying the uncertainties induced by possible new physics effects on such processes is, therefore, crucial. We present an investigation of light and heavy new physics contributions to the small-angle Bhabha process at future 𝑒 + ⁢𝑒 − colliders, and we discuss possible strategies to remove the contamination due to heavy degrees of freedom by relying on observables that are independent of the absolute luminosity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1993

Mars Observer Lecture: Mars Orbit Insertion

The Mars Observer mission spacecraft was primarily designed for exploring Mars and the Martian environment. The Mars Observer was launched on September 25, 1992. The spacecraft was lost in the vicinity of Mars on August 21, 1993 when the spacecraft began its maneuvering sequence for Martian orbital insertion. This videotape shows a lecture by Suzanne R. Dodd, the Mission Planning Team Chief for the Mars Observer Project. Ms Dodd begins with a brief overview of the mission and the timeline from the launch to orbital insertion. Ms Dodd then reviews slides showing the trajectory of the spacecraft on its trip to Mars. Slides of the spacecraft being constructed are also shown. She then discusses the Mars orbit insertion and the events that will occur to move the spacecraft from the capture orbit into a mapping orbit. During the trip to Mars, scientists at JPL had devised a new strategy, called Power In that would allow for an earlier insertion into the mapping orbit. The talk summarizes this strategy, showing on a slide the planned transition orbits. There are shots of the Martian moon, Phobos, taken from the Viking spacecraft, as Ms Dodd explains that the trajectory will allow the orbiter to make new observations of that moon. She also explains the required steps to prepare for mapping after the spacecraft has achieved the mapping orbit around Mars. The lecture ends with a picture of Mars from the Observer on its approach to the planet.

Dodd, Suzanne R.↗

NASA NTRS2015

Evaluating the Utility of Satellite Soil Moisture Retrievals over Irrigated Areas and the Ability of Land Data Assimilation Methods to Correct for Unmodeled Processes

Earth's land surface is characterized by tremendous natural heterogeneity and human-engineered modifications, both of which are challenging to represent in land surface models. Satellite remote sensing is often the most practical and effective method to observe the land surface over large geographical areas. Agricultural irrigation is an important human-induced modification to natural land surface processes, as it is pervasive across the world and because of its significant influence on the regional and global water budgets. In this article, irrigation is used as an example of a human-engineered, often unmodeled land surface process, and the utility of satellite soil moisture retrievals over irrigated areas in the continental US is examined. Such retrievals are based on passive or active microwave observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Advanced Microwave Scanning Radiometer 2 (AMSR2), the Soil Moisture Ocean Salinity (SMOS) mission, WindSat and the Advanced Scatterometer (ASCAT). The analysis suggests that the skill of these retrievals for representing irrigation effects is mixed, with ASCAT-based products somewhat more skillful than SMOS and AMSR2 products. The article then examines the suitability of typical bias correction strategies in current land data assimilation systems when unmodeled processes dominate the bias between the model and the observations. Using a suite of synthetic experiments that includes bias correction strategies such as quantile mapping and trained forward modeling, it is demonstrated that the bias correction practices lead to the exclusion of the signals from unmodeled processes, if these processes are the major source of the biases. It is further shown that new methods are needed to preserve the observational information about unmodeled processes during data assimilation.

land data↗

DOE OSTI2022

Modeling of linear nanopores in a-SiO 2 tuning pore surface structure

Here, new strategies are presented for the generation of models for linear nanopores in amorphous silica (a-SiO 2 ) with surface structure tuned to match experimental observations. Specifically, the models successfully target not only the overall density of surface silanol groups, but also the proportion of geminal versus mono silanols for which additional experimental NMR data is reported. The latter quantity has not been appropriately described in previous modeling, and in fact has typically not been considered. Strategies include “pore drilling” of bulk a-SiO 2 , and “cylindrical resist” methodology forming a-SiO 2 around a cylindrical exclusion region, followed by dehydroxylation and hydroxylation processes, respectively. However, these latter processes must be judiciously tailored in order to tune the proportion of geminals, in addition to the overall silanol density, to achieve experimental values. Such tailoring has not been incorporated into previous modeling. Another approach considered tunes surface structure of pores obtained by “pore drilling” through mild annealing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Screening the complex biological behavior of late lanthanides through genome-wide interactions

Abstract Despite their similar physicochemical properties, recent studies have demonstrated that lanthanides can display different biological behaviors. Hence, the lanthanide series can be divided into three parts, namely early, mid, and late lanthanides, based on their interactions with biological systems. In particular, the late lanthanides demonstrate distinct, but poorly understood biological activity. In the current study, we employed genome-wide functional screening to help understand biological effects of exposure to Yb(III) and Lu(III), which were selected as representatives of the late lanthanides. As a model organism, we used Saccharomyces cerevisiae, since it shares many biological functions with humans. Analysis of the functional screening results indicated toxicity of late lanthanides is consistent with disruption of vesicle-mediated transport, and further supported a role for calcium transport processes and mitophagy in mitigating toxicity. Unexpectedly, our analysis suggested that late lanthanides target proteins with SH3 domains, which may underlie the observed toxicity. This study provides fundamental insights into the unique biological chemistry of late lanthanides, which may help devise new avenues toward the development of decorporation strategies and bio-inspired separation processes.

Pallares, Roger M. (ORCID:0000000174238706)↗

DOE OSTI2022

A Combined Computer Vision and Deep Learning Approach for Rapid Drone-Based Optical Characterization of Parabolic Troughs

Optical accuracy is a primary driver of parabolic trough concentrating solar power (CSP) plant performance, but can be damaged by wind loads, gravity, error during installation, and regular plant operation. Collecting and analyzing optical measurements over an entire operating parabolic trough plant is difficult, given the large scale of typical installations. Distant Observer, a software tool developed at the National Renewable Energy Laboratory, uses images of the absorber tube reflected in the collector mirror to measure both surface slope in the parabolic mirror and offset of the absorber tube from the ideal focal point. This technology has been adapted for fast data collection using low-cost commercial drones, but until recently still required substantial human labor to process large amounts of data. A new method leveraging advanced deep learning and computer vision tools can drastically reduce the time required to process images. This new method addresses the primary analysis bottleneck, identifying featureless, reflective mirror corner points to a high degree of accuracy. Recent work has shown promising results using computer vision methods. The combined deep learning and computer vision approach presented here proved highly effective and has the potential to further automate data collection and analysis, making the tool more robust. The method presented in this paper automatically identified 74.3% of mirror corners within 2 pixels of their manually marked counterparts and 91.9% within 3 pixels. This level of accuracy is sufficient for practical Distant Observer analysis within a target uncertainty. A commercial drone collected video of over 100 parabolic trough modules at an operating CSP plant to demonstrate the deep learning and computer vision method's usefulness in processing large amounts of data. These troughs were successfully analyzed using Distant Observer, paired with the new deep learning and computer vision algorithm, and can provide plant operators and trough designers with valuable insight about plant performance, operating strategies, and plant-wide optical error trends.

computer vision↗

NASA NTRS1988

Nondynamic Tracking Using The Global Positioning System

Report describes technique for using Global Positioning System (GPS) to determine position of low Earth orbiter without need for dynamic models. Differential observing strategy requires GPS receiver on user vehicle and network of six ground receivers. Computationally efficient technique delivers decimeter accuracy on orbits down to lowest altitudes. New technique nondynamic long-arc strategy having potential for accuracy of best dynamic techniques while retaining much of computational simplicity of geometric techniques.

Yunck, T. P.↗

NASA NTRS2005

Using Wind Driven Tumbleweed Rovers to Explore Martian Gully Features

Gully features have been observed on the slopes of numerous Martian crater walls, valleys, pits, and graben. Several mechanisms for gully formation have been proposed, including: liquid water aquifers (shallow and deep), melting ground ice, snow melt, CO2 aquifers, and dry debris flow. Remote sensing observations indicate that the most likely erosional agent is liquid water. Debate concerns the source of this water. Observations favor a liquid water aquifer as the primary candidate. The current strategy in the search for life on Mars is to "follow the water." A new vehicle known as a Tumbleweed rover may be able to conduct in-situ investigations in the gullies, which are currently inaccessible by conventional rovers. Deriving mobility through use of the surface winds on Mars, Tumbleweed rovers would be lightweight and relatively inexpensive thus allowing multiple rovers to be deployed in a single mission to survey areas for future exploration. NASA Langley Research Center (LaRC) is developing deployable structure Tumbleweed concepts. An extremely lightweight measurement acquisition system and sensors are proposed for the Tumbleweed rover that greatly increases the number of measurements performed while having negligible mass increase. The key to this method is the use of magnetic field response sensors designed as passive inductor-capacitor circuits that produce magnetic field responses whose attributes correspond to values of physical properties for which the sensors measure. The sensors do not need a physical connection to a power source or to data acquisition equipment resulting in additional weight reduction. Many of the sensors and interrogating antennae can be directly placed on the Tumbleweed using film deposition methods such as photolithography thus providing further weight reduction. Concepts are presented herein for methods to measure subsurface water, subsurface metals, planetary winds and environmental gases.

Antol, Jeffrey↗

NASA NTRS2004

Using Wind Driven Tumbleweed Rovers to Explore Martian Gully Features

Antol, Jeffrey↗

NASA NTRSDate not supplied

NASA’s NextGen Remote Sensing Instruments Have Arrived: Data Products For Studying Disease Vectors

Remote sensing can be used to measure, evaluate or estimate both the environment (state functions) and interfaces (processfunctions) defining vector habitats. The products of remote sensing can be integrated directly into the epidemiological equationsto significantly enhance our understanding of disease vector’s life cycles and habitats. The next generation of NASA’s remotesensing instruments which have become recently operational will provide a significant enhancement in our ability to studydisease vector’s life cycles and habitats. These instruments are on the International Space Station (ISS) and includeECOSTRESS, DESIS, and GEDI. ECOSTRESS is a 5 channel, thermal IR instrument with 70 m resolution and approximately1-5 day repeat cycle of day/night pairs. DESIS jointly developed by German Aerospace Center and Teledyne Brown Engineeringis a hyperspectral sensor system of 235 channels and 30 m resolution. DESIS data is only being acquired on demand. GEDI is ahigh-resolution laser ranger used for observing Earth’s forests and topography. NASA’s current ISS instrument configuration provides measurements of the critical environmental measures of environmentalstate functions important to vector & disease life cycles. Remote sensing data provide a spatial context and time series oflandscape scale process functions represented by land use mapping and measurements of ecological functions. Global publichealth is entering a new information age through the use of spatial models of disease vector/host ecologies driven by the use ofremotely sensed data to measure environmental and structural factors critical in determining disease vector habitats. In 2018, NASA initiated a new study for the Surface Biology and Geology (SBG) Designated Observable, identified in the 2018National Academies’ Decadal Survey entitled, “Thriving on Our Changing Planet: A Decadal Strategy for Earth Observationfrom Space.” (https://www.nap.edu/catalog/24938/thriving-on-our-changing-planet-a-decadal-strategy-for-earth) . The SBG isplanned to collect global remote sensing measurements using a hyperspectral spectrometer and multispectral thermal data. Thesedata sets will provide a significant enhancement in our ability to study disease vector’s life cycles and habitats globally. The 3sensors on the ISS provide precursor data to prepare the community for the application of future SBG data toward diseasestudies.

Disease Vectors↗

NASA NTRS2021

What it Takes to Compute Highly Accurate Rovibrational Line Lists for Use in Astrochemistry

We review the Best Theory + Reliable High-resolution Experiment (BTRHE) strategy for obtaining highly accurate molecular rovibrational line lists with InfraRed (IR) intensities. The need for highly accurate molecular rovibrational line lists is two-fold: a) assignment of the many rovibrational lines for common stable molecules especially those that exhibit a large amplitude motion, such as NH3, or have a high density of states such as SO2; and b) characterization of the atmospheres of exoplanets which will be one of the main areas of research in astronomy in the coming decades. The first motivation arises due to the need to eliminate lines due to common molecules in an astronomical observation in order to identify lines from new molecules, while the second motivation arises due to the need to obtain accurate molecular opacities in order to characterize the atmosphere of an exoplanet. The BTRHE strategy first consists of using high quality ab initio quantum chemical methods to obtain a global potential energy surface (PES) and dipole moment surface (DMS) that contains the proper physics. The global PES is then refined using a subset of the reliable high-resolution experimental data. The refined PES then gives energy level predictions to an accuracy similar to the reproduction accuracy of the experimental data used in the refinement step in the interpolation region (i.e., within the range of the experimental data used in the refinement step). The accuracy of the energy levels will slowly degrade as they are extrapolated to spectral regions beyond the high-resolution experimental data used in the refinement step. However, because the degradation is slow, the predicted energy levels can be used to assign new high-resolution experiments, and the data from these can then be used in a subsequent refinement step. In this way, the global PES eventually can yield highly accurate energy levels for all desired spectral regions including to very high energies and high J values. We show that IR intensities computed with the BTRHE rovibrational wavefunctions and the DMS can be very accurate provided one has minimized the fitting error of the DMS and tested the completeness of the DMS. Some examples of our work on NH3, CO2, and SO2 are given to highlight the usefulness of the BTRHE strategy and to provide ideas on how to further improve its predictive power in the future. In particular, it is shown how successive refinement steps, once new high-resolution data is available, can lead to PESs that yield highly accurate transition energies to larger spectral regions. The importance of including non-adiabatic corrections to reduce the J-dependence of errors for H-containing molecules is shown with work on NH3. Another very important aspect of the BTRHE approach is the consistency across isotopologues, which allows for highly accurate line lists for any isotopologue once one is obtained for the main isotopologue (which has more high-resolution data available for refinement).

Xinchuan Huang↗

DOE OSTI2021

Single-Molecule Charge Transport through Positively Charged Electrostatic Anchors

The charge transport in single-molecule junctions depends critically on the chemical identity of the anchor groups that are used to connect the molecular wires to the electrodes. In this research, we report a new anchoring strategy — called the electrostatic anchor here — formed through the efficient Coulombic interaction between the gold electrodes and the positively charged pyridinium terminal groups. Our results show that these pyridinium groups serve as efficient electrostatic anchors forming robust gold–molecule–gold junctions. Here, we have also observed binary switching in dicationic viologen molecular junctions, demonstrating an electron injection-induced redox switching in single-molecule junctions. We attribute the difference in low- and high conductance states to a dicationic ground state and a radical cationic metastable state, respectively. Overall, this anchoring strategy and redox switching mechanism could constitute the basis for a new class of redox-activated single-molecule switches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1992

Report to Congress on the restructuring of the Earth Observing System

Contents: (1) The Science Objectives of EOS; (2) New Spacecraft Configurations; (3) The Impact of the Restructured EOS on Understanding the Climate; (4) The Impact of EOS on Adaptation and Mitigation Strategies; (5) EOS Data and Information System; (6) Interdisciplinary Investigations; (7) Missions in Advance of EOS; (8) The Role of the Departments of Energy and Defense; (9) Summary of the Mission to Planet Earth; and (10) Funding Requirement.

Source record↗

DOE OSTI2025

Future Intensity‐Duration‐Frequency Curves of Extreme Precipitation in the Midwest United States From Convection‐Permitting Modeling

Abstract During the last four decades, global warming has statistically significant intensified extreme precipitation events in the Midwestern United States (defined here as the region covering Illinois, Indiana, Ohio, and Kentucky), leading to increased risks to human life, property, and infrastructure. To enable climate change adaptation and resilience across various economic and social sectors in this region, updated information about future climate changes, specifically at finer spatial scales, is essential. Leveraging a new 150‐year dynamical downscaling data set at convection‐permitting resolution, this study introduces a framework to construct the projected future intensity‐duration‐frequency (IDF) curves of heavy precipitation, which are prominent tools for infrastructure design and water resources management. This framework generates IDF curves at both sub‐daily and multi‐day duration utilizing hourly in situ observations as well as quantile‐based statistical techniques in bias‐correction and return levels selection. The assumption of non‐stationarity in the distribution parameter fitting process is also implemented in this workflow. Compared to historical IDF curves for 1980–2022, future projected IDF curves for 2058–2100 under Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios indicate an average intensity increase of approximately 15% and 25%, respectively, across 74 stations, considering both annual and seasonal timescales. Future projections suggest that extreme precipitation events may become more severe across six investigated return periods, with longer return periods showing a greater increase. The frequency of future extreme precipitation events in the Midwest region is also projected to double. Furthermore, current results reveal spatial heterogeneity of future trends across stations owing to the high‐resolution input data set. Plain Language Summary This study investigates the evolving nature of extreme precipitation events in the Midwestern United States under a changing climate. By leveraging a high‐resolution dynamical downscaling data set, we construct projected intensity‐duration‐frequency (IDF) curves for future extreme rainfall events. These curves serve as vital tools for infrastructure planning and water resource management. Our analysis reveals a significant increase in both the intensity and frequency of extreme precipitation events in the region. Future projected IDF curves for the late century indicate an average intensity increase of approximately 15%–25% compared to historical values. Moreover, the frequency of such events is expected to double. Spatial heterogeneity in future trends is observed across different stations within the Midwest, highlighting the importance of high‐resolution modeling in capturing localized climate variability. These findings underscore the urgent need for climate adaptation strategies to mitigate the increasing risks associated with extreme precipitation events in the region. Key Points This study introduces a workflow to construct future intensity‐duration‐frequency (IDF) curves over the Midwest United States using a new convection‐permitting modeling data set The current IDF construction workflow reproduces well the historical observed IDF 30 curves in summer months with median relative errors of 2.4% among 74 stations and 6 investigated durations The projected IDF curves show diverse future trends of extreme precipitation across stations, with intensity increases of approximately 15% and 25% under RCP4.5 and RCP8.5 climate scenarios, respectively, and a doubling of frequency on average

Nguyen, Trung↗

DOE OSTI2025

Influences of Alkali Metal Cation Interactions on N2 Coordination to Iron(I) Beta-Diketiminate Complexes in Electrolyte Solutions

N2 functionalization reactions often use stable, isolable N2-bound complexes and low temperatures or highly activated reagents. However, little work has focused on systems where N2 binds weakly, and the N2 binding equilibrium can be modulated. Here, we describe analysis of surprising trends in alkali metal cation solvation on the formation of an anionic iron(I) beta-diketiminate complex and the subsequent N2 binding equilibrium. Variable temperature UV-vis spectroscopy shows that increased ionic strength in the coordinating solvent tetrahydrofuran promotes N2 coordination. Additionally, less solvated alkali metal cations in noncoordinating 2-methyltetrahydrofuran (MeTHF) stabilize N2 coordination, likely through the formation of contact ion pairs in solution that have enhanced N2 binding. Ionic strength has little effect on the energetics of N2 coordination to these proposed contact ion pairs in MeTHF. When the electrochemical analysis is done at –78 °C, there is an irreversible reduction of iron(II) and an anodically shifted oxidation, which is attributed to the formation of the spectroscopically observed N2 complex. Finally, bulk electrolysis is used to verify the electrochemical formation of the N2-bound anionic iron(I) complex. These studies demonstrate a new strategy for promoting N2 coordination by changing solution properties, which is relevant to homogeneous electrochemical N2 reduction methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗