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NASA NTRSDate not supplied

Understanding Relationships Between Satellite, Model, and Ground-Based Surface Temperature Characterizations From Overcast to Clear Conditions in Support of Satellite Remote Sensing of Clouds and Radiation

Accurate and consistent global estimates of cloud coverage and their properties are fundamental to long-term Earth radiation budget (ERB) monitoring efforts like the Clouds and the Earth’s Radiant Energy System (CERES) project. Cloud detection algorithms often apply thresholding approaches to identify where clouds occur by comparing satellite-measured radiances with those that are expected under cloud-free conditions. In addition, once a cloud is detected, the derivation of cloud optical and microphysical properties also requires knowledge of the background radiances below the cloud. In the infrared, knowledge of the surface emissivity and the expected skin temperature under both cloudy and cloud-free conditions is needed. These traits are generally well known over the oceans. Over land, however, comparisons between satellite-derived land surface temperature (LST) with that characterized in numerical weather analyses reveal large differences in many parts of the world, often exceeding 5 K, which can lead to significant satellite cloud detection and cloud property retrieval errors. Furthermore, clouds have a dramatic influence on the LST, and therefore characterization of that model parameter also depends on the capability of the model to accurately resolve clouds. Thus, the LST characterized in models is, at times, a poor approximation for what would otherwise be observed, thereby impeding accurate satellite cloud retrievals. As a result, we seek to develop a more robust method for estimating the LST required for satellite cloud characterizations. This effort is accomplished through a combination of surface emission/air temperature relationship studies in all-sky conditions using ground measurement stations, along with deep neural network (DNN) estimates of expected LST under overcast and cloud-free conditions. We demonstrate that substituting DNN-predicted LST for that generated by numerical models can mitigate model-inherent diurnal dependencies and reduce overall bias and uncertainty relative to satellite/ground observations by 0.5–4 K and 0.5–2 K, respectively. It is expected that this work will lead to improved satellite cloud retrievals that enhance ERB monitoring efforts.

B Scarino↗

NASA NTRS2011

C-Band Airport Surface Communications System Engineering-Initial High-Level Safety Risk Assessment and Mitigation

This document is being provided as part of ITT's NASA Glenn Research Center Aerospace Communication Systems Technical Support (ACSTS) contract: "New ATM Requirements--Future Communications, C-Band and L-Band Communications Standard Development." ITT has completed a safety hazard analysis providing a preliminary safety assessment for the proposed C-band (5091- to 5150-MHz) airport surface communication system. The assessment was performed following the guidelines outlined in the Federal Aviation Administration Safety Risk Management Guidance for System Acquisitions document. The safety analysis did not identify any hazards with an unacceptable risk, though a number of hazards with a medium risk were documented. This effort represents an initial high-level safety hazard analysis and notes the triggers for risk reassessment. A detailed safety hazards analysis is recommended as a follow-on activity to assess particular components of the C-band communication system after the profile is finalized and system rollout timing is determined. A security risk assessment has been performed by NASA as a parallel activity. While safety analysis is concerned with a prevention of accidental errors and failures, the security threat analysis focuses on deliberate attacks. Both processes identify the events that affect operation of the system; and from a safety perspective the security threats may present safety risks.

Zelkin, Natalie↗

DOE OSTI2020

Mitigation of LEO Satellite Brightness and Trail Effects on the Rubin Observatory LSST

In this work, we report studies on the mitigation of optical effects of bright low-Earth-orbit (LEO) satellites on Vera C. Rubin Observatory and its Legacy Survey of Space and Time (LSST). These include options for pointing the telescope to avoid satellites, laboratory investigations of bright trails on the Rubin Observatory LSST camera sensors, algorithms for correcting image artifacts caused by bright trails, experiments on darkening SpaceX Starlink satellites, and ground-based follow-up observations. The original Starlink v0.9 satellites are g ~ 4.5 mag, and the initial experiment "DarkSat" is g ~ 6.1 mag. Future Starlink darkening plans may reach g ~ 7 mag, a brightness level that enables nonlinear image artifact correction to well below background noise. However, the satellite trails will still exist at a signal-to-noise ratio ~ 100, generating systematic errors that may impact data analysis and limit some science. For the Rubin Observatory 8.4 m mirror and a satellite at 550 km, the full width at half maximum of the trail is about 3'' as the result of an out-of-focus effect, which helps avoid saturation by decreasing the peak surface brightness of the trail. For 48,000 LEOsats of apparent magnitude 4.5, about 1% of pixels in LSST nautical twilight images would need to be masked.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Vehicle Position Detection Based on Machine Learning Algorithms in Dynamic Wireless Charging

Dynamic wireless charging (DWC) has emerged as a viable approach to mitigate range anxiety by ensuring continuous and uninterrupted charging for electric vehicles in motion. DWC systems rely on the length of the transmitter, which can be categorized into long-track transmitters and segmented coil arrays. The segmented coil array, favored for its heightened efficiency and reduced electromagnetic interference, stands out as the preferred option. However, in such DWC systems, the need arises to detect the vehicle’s position, specifically to activate the transmitter coils aligned with the receiver pad and de-energize uncoupled transmitter coils. This paper introduces various machine learning algorithms for precise vehicle position determination, accommodating diverse ground clearances of electric vehicles and various speeds. Through testing eight different machine learning algorithms and comparing the results, the random forest algorithm emerged as superior, displaying the lowest error in predicting the actual position.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Transformation rate maps of dissolved organic carbon in the contiguous US

Riverine dissolved organic carbon (DOC) plays a vital role in regional and global carbon cycles. However, the processes of DOC conversion from soil organic carbon (SOC) and leaching into rivers are insufficiently understood, inconsistently represented, and poorly parameterized, particularly in land surface and Earth system models. As a first attempt to fill this gap, we propose a generic formula that directly connects SOC concentration with DOC concentration in headwater streams, where a single parameter, the transformation rate from SOC in the soil to DOC leaching flux (P r ), accounts for the overall processes governing SOC conversion to DOC and leaching from soils (along with runoff) into headwater streams. We then derive high-resolution P r maps over the contiguous US (CONUS) using SOC data from two different sources: the Harmonized World Soil Database v1.2 (HWSD) and SoilGrids 2.0. Both maps are developed following the same five major steps: (1) selecting independent catchments where observed riverine DOC data are available with reasonable quality; (2) estimating catchment-average SOC for the independent catchments; (3) estimating the P r values for these catchments based on the generic formula and catchment-average SOC; (4) developing a predictive model of P r with machine learning (ML) techniques and catchment-scale climate, hydrology, geology, and other attributes; and (5) deriving a national map of P r based on the ML model. For evaluation, we compare the DOC concentration derived using the P r map and the observed DOC concentration values at evaluation catchments. The resulting mean absolute scaled error and coefficient of determination are 0.73 and 0.47 for the HWSD-based model and 0.58 and 0.72 for the SoilGrids-based model, respectively, suggesting the effectiveness of the overall methodology. Efforts to constrain uncertainty and evaluate sensitivity of P r to different factors are discussed. To illustrate the use of such maps, we derive a riverine DOC concentration reanalysis dataset over CONUS. The two P r maps, robustly derived and empirically validated, lay a critical cornerstone for better simulating the terrestrial carbon cycle in land surface and Earth system models. Our findings not only set a foundation for improving our predictive understanding of the terrestrial carbon cycle at the regional and global scales, but also hold promises for informing policy decisions related to decarbonization and climate change mitigation. The data presented in this study are publicly available at https://doi.org/10.5281/zenodo.14563816 (Li et al., 2024).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

A fast and robust computational modeling approach for density and shape predictions in powder metallurgy hot isostatic pressing

Powder metallurgy hot isostatic pressing (PM-HIP) is an advanced manufacturing process that produces near-net-shape parts with high material utilization and uniform microstructures. PM-HIP is frequently used for producing small-scale parts with complicated geometries and is potentially economical for producing large-scale parts. However, excessive post-HIP shape distortions can reduce its effectiveness and economic advantage, especially for larger parts. A PM-HIP computational model can predict and help mitigate these distortions. However, due to complex deformation mechanisms and thermo-mechanical coupling present in PM-HIP processes, these non-linear computational models sometimes become numerically unstable. The numerical instabilities in these models can lead to very slow convergence or no convergence at all, which often translates to slow and unreliable models. These limitations are more pronounced in large models with complicated geometries. Hence, in this work, an alternative modeling approach is presented that improves numerical stability and computational performance. The presented approach achieves these improvements through approximating the fully coupled thermo-mechanical PM-HIP model as a decoupled model and adding inertial damping to the model’s mechanical part. In conclusion, a comparison with the fully coupled model indicated a slight dip in prediction accuracy (<5% error) but significant improvements in numerical stability (>20 times larger time step size) and computational performance (5-10 times speed-up with less computational resource usage) when using the presented approach.

Hot isostatic pressing↗

DOE OSTI2026

Data for Soil Oxygen Dynamics: A Key Mediator of Tile Drainage Impacts on Coupled Hydrological, Biogeochemical, and Crop Systems

Tile drainage removes excess water and is an essential, widely adopted management practice to enhance crop productivity in the US Midwest and throughout the world. Tile drainage has been shown to significantly change hydrological and biogeochemical cycles by lowering the water table and reducing the residence time of soil water, although examining the complex interactions and feedbacks in an integrated hydrology–biogeochemistry–crop system remains elusive. Oxygen dynamics are critical to unraveling these interactions and have been ignored or oversimplified in existing models. Understanding these impacts is essential, particularly so because tile drainage has been highlighted as an adaptation under projected wetter springs and drier summers in the changing climate in the US Midwest. We used the ecosys model that uniquely incorporates first-principle soil oxygen dynamics and crop oxygen uptake mechanisms to quantify the impacts of tile drainage on hydrological and biogeochemical cycles and crop growth in corn–soybean rotation fields. The model was validated with data from a multi-treatment, multi-year experiment in Washington, IA. The relative root mean square error (rRMSE) for the corn and soybean yield in validation is 5.66 % and 12.57 %, respectively. The Pearson coefficient (r) of the monthly tile flow during the growing season is 0.78. Plant oxygen stress turns out as an emergent property of the equilibrium between the soil oxygen supply and biological demand. The impact of tile drainage on the system is achieved through a series of coupled feedback mechanisms. The model results show that tile drainage reduces the soil water content and enhances soil oxygenation. It additionally increases the subsurface discharge and elevates inorganic nitrogen leaching, with seasonal variations influenced by climate and crop phenology. The improved aerobic condition alleviates crop oxygen stress during wet springs, thereby promoting crop root growth during the early growth stage. The development of greater root density, in turn, mitigates water stress during dry summers, leading to an overall increase in the crop yield by ∼6 %. These functions indicate the potential of tile drainage in bolstering crop resilience to climate change and the use of this modeling tool for large-scale assessments of tile drainage. The model reveals the underlying causal mechanisms that drive the agroecosystem response to drainage on the coupled hydrology, biogeochemistry, and crop system dynamics.

Modeling↗

DOE OSTI2025

Soil oxygen dynamics: a key mediator of tile drainage impacts on coupled hydrological, biogeochemical, and crop systems

60 APPLIED LIFE SCIENCES↗

NASA NTRS2004

Symbology Development for General Aviation Synthetic Vision Primary Flight Displays for the Approach and Missed-Approach Modes of Flight

Spatial disorientation induced by inadvertent flight into instrument meteorological conditions (IMC) continues to be a leading cause of fatal accidents in general aviation. The Synthetic Vision Systems General Aviation (SVS-GA) research element, an integral part of NASA s Aviation Safety and Security Program (AvSSP), is investigating a revolutionary display technology designed to mitigate low visibility events such as controlled flight into terrain (CFIT) and low-visibility loss of control (LVLoC). The integrated SVS Primary Flight Display (SVS-PFD) utilizes computer generated 3-dimensional imagery of the surrounding terrain augmented with flight path guidance symbology. This unique combination will provide GA pilots with an accurate representation of their environment and projection of their flight path, regardless of time of day or out-the-window (OTW) visibility. The initial Symbology Development for Head-Down Displays (SD-HDD) simulation experiment examined 16 display configurations on a centrally located high-resolution PFD installed in NASA s General Aviation Work Station (GAWS) flight simulator. The results of the experiment indicate that situation awareness (SA) can be enhanced without having a negative impact on flight technical error (FTE), by providing a general aviation pilot with an integrated SVS display to use when OTW visibility is obscured.

Bartolone, Anthony P.↗

NASA NTRS2002

Isotopic Effects in Nuclear Fragmentation and GCR Transport Problems

Improving the accuracy of the galactic cosmic ray (GCR) environment and transport models is an important goal in preparing for studies of the projected risks and the efficiency of potential mitigations methods for space exploration. In this paper we consider the effects of the isotopic composition of the primary cosmic rays and the isotopic dependence of nuclear fragmentation cross sections on GCR transport models. Measurements are used to describe the isotopic composition of the GCR including their modulation throughout the solar cycle. The quantum multiple-scattering approach to nuclear fragmentation (QMSFRG) is used as the data base generator in order to accurately describe the odd-even effect in fragment production. Using the Badhwar and O'Neill GCR model, the QMSFRG model and the HZETRN transport code, the effects of the isotopic dependence of the primary GCR composition and on fragment production for transport problems is described for a complete GCR isotopic-grid. The principle finding of this study is that large errors ( 100%) will occur in the mass-flux spectra when comparing the complete isotopic-grid (141 ions) to a reduced isotopic-grid (59 ions), however less significant errors 30%) occur in the elemental-flux spectra. Because the full isotopic-grid is readily handled on small computer work-stations, it is recommended that they be used for future GCR studies.

Cucinotta, Francis A.↗

NASA NTRS2010

GLobal Integrated Design Environment (GLIDE): A Concurrent Engineering Application

The GLobal Integrated Design Environment (GLIDE) is a client-server software application purpose-built to mitigate issues associated with real time data sharing in concurrent engineering environments and to facilitate discipline-to-discipline interaction between multiple engineers and researchers. GLIDE is implemented in multiple programming languages utilizing standardized web protocols to enable secure parameter data sharing between engineers and researchers across the Internet in closed and/or widely distributed working environments. A well defined, HyperText Transfer Protocol (HTTP) based Application Programming Interface (API) to the GLIDE client/server environment enables users to interact with GLIDE, and each other, within common and familiar tools. One such common tool, Microsoft Excel (Microsoft Corporation), paired with its add-in API for GLIDE, is discussed in this paper. The top-level examples given demonstrate how this interface improves the efficiency of the design process of a concurrent engineering study while reducing potential errors associated with manually sharing information between study participants.

McGuire, Melissa L.↗

DOE OSTI2026

Cosmic axions revealed via amplified modulation of the ellipticity of a laser

We propose a new axion dark matter detection strategy that employs optical readout of laser beam ellipticity modulations caused by axion-induced electric fields in a microwave cavity, using electro-optic (EO) crystals, enhanced by externally injected radio-frequency (rf) power. Building upon the variance-based probing method [Phys. Rev. D 107, 103005 (2023).], we extend this concept to the optical domain: A weak probe laser interacts with an EO crystal coupled to the resonant microwave cavity field at cryogenic temperatures, and the axion-induced electric field is revealed through induced ellipticity. The injected rf signal coherently interferes with that of the axion field, amplifying the optical response and significantly improving sensitivity. While our EO-based method employs a Fabry-Pérot resonator, we do not require Michelson interferometers. Our method, hence, enables compact, high-frequency axion searches, across the 0.5–50 GHz range. Operating at cryogenic temperatures not only suppresses thermal backgrounds, but, critically, allows the probing method to mitigate the quantum noise. This approach offers a scalable path forward for axion detection over the ∼(few−200) μ⁢eV mass range—covering the preferred parameter space for the postinflationary Peccei-Quinn axion dark matter—using compact, tunable systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2007

Star Confusion Effect on SIM PlanetQuest Astrometric Performance

SIM PlanetQuest will measure star positions to an accuracy of a few microarcseconds using precise white light fringe measurements. One challenge for SIM observation scenario is "star confusion," where multiple stars are present in the instrument field of view. This is especially relevant for observing dim science targets because the density of number of stars increases rapidly with star magnitude. We study the effect of star confusion on the SIM astrometric performance due to systematic fringe errors caused by the extra photons from the confusion star(s}. Since star confusion from multiple stars may be analyzed as a linear superposition of the effect from single star confusion, we quantify the astrometric errors due to single star confusion surveying over many spectral types, including AOV, FOV, K5III, and MOV, and for various visual magnitude differences. To the leading order, the star confusion effect is characterized by the magnitude difference, spectral difference, and the angular separation between the target and confusion stars.Strategies for dealing with star confusion are presented. For example, since the presence of additional sources in the field of view leads to inconsistent delay estimates from different channels, with sufficient signal to noise ratio, the star confusion can be detected using chi-square statistics of fringe measurements from multiple spectral channels. An interesting result is that the star confusion can be detected even though the interferometer cannot resolve the separation between the target and confusion stars when their spectra are sufficiently different. Other strategies for mitigating the star confusion effect are also discussed.

crowded field↗

DOE OSTI2023

How does uncertainty of soil organic carbon stock affect the calculation of carbon budgets and soil carbon credits for croplands in the U.S. Midwest?

Cropland carbon budget depicts the amount of carbon flowing in and out of agroecosystems and the changes in carbon stocks of soil and living biomass during the same period. Soil carbon credit is the additional change in soil carbon stock under certain farming practices compared with the business-as-usual practices. Accurately calculating cropland carbon budget and soil carbon credit is critical to assessing climate change mitigation potential in agroecosystems. The calculation of cropland carbon budget and soil carbon credit is sensitive to local soil and climatic conditions, especially initial soil organic carbon (SOC) stock, which is determined by both SOC concentration (SOC%) and bulk density (Bulk_Density). SOC stock data are either from soil sampling or gridded public survey data. In agroecosystem models, SOC stock data are a key model input for quantifying cropland carbon budget and soil carbon credit. However, various types and degrees of uncertainties exist in SOC stock datasets, which propagate to the quantification of SOC stock change. In particular, a large discrepancy is found in two widely used SOC stock datasets — Rapid Carbon Assessment dataset (RaCA) and Gridded Soil Survey Geographic Database (gSSURGO) — in the U.S. Midwest, with a relative difference (quantified using Normalized Root Mean Square Error, NRMSE) of 48.0% for 0–30 cm SOC stock between the two datasets. It remains largely unclear how uncertainty in SOC stocks affects the calculation of cropland carbon budget and soil carbon credit. To address this question, we used a well-validated process-based agroecosystem model, ecosys, to assess the impacts of SOC stock uncertainty on carbon budget and soil carbon credit calculation in the U.S. Midwestern corn-soybean rotation systems. Our results reveal the following findings: (1) A sizable discrepancy exists in simulated cropland carbon budget between using gSSURGO and using RaCA for their SOC% and Bulk_Density as model inputs, with a Pearson correlation coefficient (r) of only 0.4 for simulated change of SOC stock (ΔSOC) using these two different soil datasets. (2) Simulated cropland carbon budget components were more sensitive to initial SOC% than to Bulk_Density. For example, the upper and lower quartiles of multi-year averaged ΔSOC were –29.8 and 4.8 gC/m 2 /year for the selected counties respectively, with an uncertainty of 13.7 and 0.7 gC/m 2 /year induced by uncertainties in initial SOC% and Bulk_Density, respectively. (3) Both simulated ΔSOC and its uncertainty were negatively correlated with initial SOC%, whereas ΔSOC was negatively correlated with air temperature, and ΔSOC uncertainty was positively correlated with air temperature. (4) The uncertainty of calculated soil carbon credits was much smaller compared with the uncertainty of calculated absolute carbon budgets assuming the same SOC stock uncertainty level in the inputs. Specifically, in our assessment comparing planting cover crops vs no cover crop, the uncertainty of calculated soil carbon credits induced by initial SOC% uncertainty was less than 4% (relative to the quantified value of the soil carbon credits) for 90% of the cases. Our analysis highlights that high accuracy measurement of SOC% as inputs is needed for the calculation of cropland carbon budgets; however, soil carbon credit quantification is much less sensitive to the initial SOC% inputs, and the current publicly available soil datasets (e.g., gSSURGO) are largely suitable for the calculation of soil

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2002

Synthetic Vision Systems in GA Cockpit-Evaluation of Basic Maneuvers Performed by Low Time GA Pilots During Transition from VMC to IMC

An experimental investigation was conducted to study the effectiveness of modern flight displays in general aviation cockpits for mitigating Low Visibility Loss of Control and the Controlled Flight Into Terrain accidents. A total of 18 General Aviation (GA) pilots with private pilot, single engine land rating, with no additional instrument training beyond private pilot license requirements, were recruited to evaluate three different display concepts in a fixed-based flight simulator at the NASA Langley Research Center's General Aviation Work Station. Evaluation pilots were asked to continue flight from Visual Meteorological Conditions (VMC) into Instrument Meteorological Conditions (IMC) while performing a series of 4 basic precision maneuvers. During the experiment, relevant pilot/vehicle performance variables, pilot control inputs and physiological data were recorded. Human factors questionnaires and interviews were administered after each scenario. Qualitative and quantitative data have been analyzed and the results are presented here. Pilot performance deviations from the established target values (errors) were computed and compared with the FAA Practical Test Standards. Results of the quantitative data indicate that evaluation pilots committed substantially fewer errors when using the Synthetic Vision Systems (SVS) displays than when they were using conventional instruments. Results of the qualitative data indicate that evaluation pilots perceived themselves to have a much higher level of situation awareness while using the SVS display concept.

Takallu, M. A.↗

DOE OSTI2023

Coupled Cluster Study of the Heats of Formation of UF 6 and the Uranium Oxyhalides, UO 2 X 2 (X = F, Cl, Br, I, and At)

The atomization enthalpies of the U(VI) species UF6 and the uranium oxyhalides UO 2 X 2 (X=F, Cl, Br, I, At) were calculated using a composite relativistic Feller-Peterson-Dixon (FPD) approach based on scalar relativistic DKH3-CCSD(T) with extrapolations to the CBS limit. The inherent multideterminantal nature of the U atom was mitigated by utilizing the singly charged atomic cation in all calculations with correction back to the neutral asymptote via the accurate ionization energy of the U atom. The effects of SO coupling were recovered using full 4-component CCSD(T) with contributions due to the Gaunt Hamiltonian calculated using Dirac-Hartree-Fock. The final atomization enthalpy for UF 6 (752.2 kcal/mol) was within 2.5 kcal/mol of the experimental value, but unfortunately the latter carries a ±2.4 kcal/mol uncertainty that is predominantly due to the experimental uncertainty in the formation enthalpy of U atom. The analogous value for UO 2 F 2 (607.6 kcal/mol) was in nearly exact agreement with experiment, but the latter has a stated experimental uncertainty of ±4.3 kcal/mol. The FPD atomization enthalpy for UO 2 Cl 2 (540.4 kcal/mol) was within the experimental error limits of ±5.5 kcal/mol. FPD atomization energies for the non-U-containing molecules (used for reaction enthalpies) H 2 O and HX (X=F, Cl, Br, I, At) were within at most 0.3 kcal/mol of their experimental values where available. The FPD atomization enthalpies, together with FPD reaction enthalpies for two different reactions, were used to determine heats of formation for all species of this work with estimated uncertainties of ±4 kcal/mol. The calculated heat of formation for UF 6 (-511.0 kcal/mol) is within 2.5 kcal/mol of the accurately-known (±0.45 kcal/mol) experimental value.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Power Flow Models of Grid-Forming Inverters in Unbalanced Distribution Grids

Load unbalance in electric distribution systems is unavoidable. Unbalanced load currents will lead to negative sequence (NS) voltages that may damage electric equipment. Unbalanced power flow analysis is a common tool to detect and mitigate NS voltage issues and requires accurate models of grid components. While traditional source models are available, grid-forming (GFM) inverter models are not well developed. GFM inverters implement various control strategies, which affect their power flow models. Here, in this paper, a novel GFM inverter model considering control effects is proposed. We show that for some control methods, unbalanced system loading will lead to unbalanced terminal voltages of the GFM inverters, which are modeled through an equivalent negative sequence impedance. The proposed models are initially validated using a simple test circuit. Then, they are applied in the power flow analysis on the IEEE 13-bus and 34-bus systems to demonstrate the accuracy improvement over the state-of-the-art. Using time-domain simulations as benchmarks, we show that the proposed models reduce the calculation error of negative sequence voltages by at least 25% in unbalanced distribution systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Lefschetz thimble quantum Monte Carlo for spin systems

Monte Carlo simulations are useful tools for modeling quantum systems, but in some cases they suffer from a sign problem, leading to an exponential slow down in their convergence to a value. While solving the sign problem is generically NP hard, many techniques exist for mitigating the sign problem in specific cases; in particular, the technique of deforming the Monte Carlo simulation's plane of integration onto Lefschetz thimbles (complex hypersurfaces of stationary phase) has seen significant success in the context of quantum field theories. We extend this methodology to spin systems by utilizing spin coherent state path integrals to reexpress the spin system's partition function in terms of continuous variables. Using some toy systems, we demonstrate its effectiveness at lessening the sign problem in this setting, despite the fact that the initial mapping to spin coherent states introduces its own sign problem. The standard formulation of the spin coherent path integral is known to make use of uncontrolled approximations; despite this, for large spins they are typically considered to yield accurate results, so it is somewhat surprising that our results show significant systematic errors. Furthermore, possibly of independent interest, our use of Lefschetz thimbles to overcome the intrinsic sign problem in spin coherent state path integral Monte Carlo enables a novel numerical demonstration of a breakdown in the spin coherent path integral.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗