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Microgravity-Induced Physiological Fluid Redistribution: Computational Analysis to Assess Influence of Physiological Parameters

Space flight impacts human physiology in many ways, the most immediate being the marked cephalad (headward) shift of fluid upon introduction into the microgravity environment. This physiological response to microgravity points to the redistribution of blood and interstitial fluid as a major factor in the loss of venous tone and reduction in heart muscle efficiency which impact astronaut performance. In addition, researchers have hypothesized that a reduction in astronaut visual acuity, part of the Visual Impairment and Intracranial Pressure (VIIP) syndrome, is associated with this redistribution of fluid. VIIP arises within several months of beginning space flight and includes a variety of ophthalmic changes including posterior globe flattening, distension of the optic nerve sheath, and kinking of the optic nerve. We utilize a suite of lumped parameter models to simulate microgravity-induced fluid redistribution in the cardiovascular, central nervous and ocular systems to provide initial and boundary data to a 3D finite element simulation of ocular biomechanics in VIIP. Specifically, the lumped parameter cardiovascular model acts as the primary means of establishing how microgravity, and the associated lack of hydrostatic gradient, impacts fluid redistribution. The cardiovascular model consists of 16 compartments, including three cerebrospinal fluid (CSF) compartments, three cranial blood compartments, and 10 thoracic and lower limb blood compartments. To assess the models capability to address variations in physiological parameters, we completed a formal uncertainty and sensitivity analysis that evaluated the relative importance of 42 input parameters required in the model on relative compartment flows and compartment pressures. Utilizing the model in a pulsatile flow configuration, the sensitivity analysis identified the ten parameters that most influenced each compartment pressure. Generally, each compartment responded appropriately to parameter variations associated with itself and adjacent compartments. However, several unexpected interactions between components, such as between the choroid plexus and the lower capillaries, were found, and are due to simplifications in the formulation of the model. The analysis illustrates that highly influential parameters and those that have unique influences within the model formulation must be tightly controlled for successful model application.

gravitational physiology

Image Segmentation, Registration, Compression, and Matching

A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity/topology components of the generated models. The highly efficient triangular mesh compression compacts the connectivity information at the rate of 1.5-4 bits per vertex (on average for triangle meshes), while reducing the 3D geometry by 40-50 percent. Finally, taking into consideration the characteristics of 3D terrain data, and using the innovative, regularized binary decomposition mesh modeling, a multistage, pattern-drive modeling, and compression technique has been developed to provide an effective framework for compressing digital elevation model (DEM) surfaces, high-resolution aerial imagery, and other types of NASA data.

Yadegar, Jacob

NOvA's Current and Future Sterile Neutrino Searches

The NOvA experiment's most recent search for eV-scale sterile neutrinos under a 3+1 model simultaneously analyses muon neutrino and neutral current datasets from the NuMI beam at its Near ($\sim$\qty1{km} baseline) and Far (\qty{810}{km} baseline) detectors to look for oscillations consistent with a sterile neutrino. The analysis is systematically limited in the region of parameter space where $Δm^2_{41} \gtrsim 1~\mathrm{eV}^2$. This region of parameter space is preferred by sterile neutrino interpretations of current experimental anomalies and so improving sensitivity here is high-priority. These proceedings present our current search strategy, and discusses future plans to include data from a second beamline, the Booster Neutrino Beam, to improve our sensitivity in systematics-dominated regions of parameter space.

Lister, Adam [Wisconsin U., Madison; Virginia Tech

Modal parameters of space structures in 1 G and 0 G

Analytic and experimental results are presented from a study of the changes in the modal parameters of space structural test articles from one- to zero-gravity. Deployable, erectable, and rotary modules was assembled to form three one- and two-dimensional structures, in which variations in bracing wire and rotary joint preload could be introduced. The structures were modeled as if hanging from a suspension system in one gravity, and unconstrained, as if free floating in zero-gravity. The analysis is compared with ground experimental measurements, which were made on a spring-wire suspension system with a nominal plunge frequency of one Hertz, and with measurements made on the Shuttle middeck. The degree of change in linear modal parameters as well as the change in nonlinear nature of the response is examined. Trends in modal parameters are presented as a function of force amplitude, joint preload, reassembly, shipset, suspension, and ambient gravity level.

Bicos, Andrew S.

Simulation budgeting for hybrid effective field theories

In this work, we forecast the number of, and requirements on, N-body simulations needed to train hybrid effective field theory (HEFT) emulators for a range of use cases, using a hybrid of HMcode and perturbation theory as a surrogate model. Our accuracy goals, determined with careful consideration of statistical and systematic uncertainties, are 1% accurate in the high-likelihood range of cosmological parameters, and 2% accurate over a broader parameter space volume for k < 1 h Mpc -1 and z < 3. Focusing in part on the 8-parameter w 0 w a CDM+ m ν cosmological model, we find that < 225 simulations are required to meet our error goals over our wide parameter space, including models with rapidly evolving dark energy, given our simulation and emulator recommendations. For a more restricted parameter space volume, as few as 80 simulations are sufficient. We additionally present simulation forecasts for example use cases, and make the code used in our analyses publicly available. These results offer practical guidance for efficient emulator design and simulation budgeting in future cosmological analyses.

cosmological parameters from LSS

Astrometric Detection of Extrasolar Planets: Results of a Feasibility Study with the Palomar 5 Meter Telescope

The detection of extrasolar planets around stars like the Sun remains an important goal of astronomy. We present results from Palomar 5 m observations of the open cluster NGC 2420 in which we measure some of the sources of noise that will be present in an astrometric search for extrasolar planets. This is the first time that such a large aperture has been used for high-precision astrometry. We find that the atmospheric noise is 150 micro-arcsec hr(exp 1/2) across a 90 sec field of view and that differential chromatic refraction (DCR) can be calibrated to 128 micro-arcsec for observations within 1 hr of the meridian and 45 deg of zenith. These results confirm that a model for astrometric measurements can be extrapolated to large apertures. We demonstrate, based upon these results, that a large telescope achieves the sensitivity required to perform a statistically significant search for extra solar planets. We describe an astrometric technique to detect planets, the astrometric signals expected, the role of reference stars, and the sources of measurement noise: photometric noise, atmospheric motion between stars, sky background, instrumental noise, and DCR. For the latter, we discuss a method to reduce the noise further to 66 micro-arcsecond for observations within 1 hr of the meridian and 45 deg of zenith. We discuss optimal lists of target stars taken from the latest Gliese & Jahreiss catalog of nearby stars with the largest potential astrometric signals, declination limits for both telescope accessibility and reduced DCR, and galactic latitude limits for a sufficiant number of reference stars. Two samples are described from which one can perform statistically significant searches for gas giant planets around nearby stars. One sample contains 100 "solar class" stars with an average stellar mass of 0.82 solar mass; the other maximizes the number of stars, 574, by searching mainly low-mass M stars. We perform Monte Carlo simulations of the statistical significance of the expected results by using measured and estimated noise quantities. We show the semimajor axis parameter spaces that are searched for each star and how an increase in the length of the observing program expands these spaces. The search over semimajor axis parameter space relates to the theory of gas giant planet formation.

Pravdo, Steven H.

Parametric-Studies and Data-Plotting Modules for the SOAP

"Parametric Studies" and "Data Table Plot View" are the names of software modules in the Satellite Orbit Analysis Program (SOAP). Parametric Studies enables parameterization of as many as three satellite or ground-station attributes across a range of values and computes the average, minimum, and maximum of a specified metric, the revisit time, or 21 other functions at each point in the parameter space. This computation produces a one-, two-, or three-dimensional table of data representing statistical results across the parameter space. Inasmuch as the output of a parametric study in three dimensions can be a very large data set, visualization is a paramount means of discovering trends in the data (see figure). Data Table Plot View enables visualization of the data table created by Parametric Studies or by another data source: this module quickly generates a display of the data in the form of a rotatable three-dimensional-appearing plot, making it unnecessary to load the SOAP output data into a separate plotting program. The rotatable three-dimensionalappearing plot makes it easy to determine which points in the parameter space are most desirable. Both modules provide intuitive user interfaces for ease of use.

Source record

Physical Parameters of Space Mission Asteroid Targets

Ground-based characterization of asteroids that are planned or potential targets of space missions provides important data on their physical parameters and properties. Knowledge of the properties of mission targets is important especially during mission preparation and planning, as it serves to select best or suitable targets for specific purpose of a given mission, to prepare mission plans, to constrain possible mission scenarios, and to design mission experiments. Such characterization efforts may be particularly critical for flyby missions that take only limited data during the high-speed flybys of their target asteroids, but they also provide very crucial data for targets of rendezvous missions. Moreover, long-term observations taken from Earth also allows the modelling of, or constraining, processes acting on the asteroids over extended time scales. Over the past years and decades we have obtained rich data on physical parameters of 82 asteroids that are planned or potential targets of space missions. Our primary observing technique is time-resolved (lightcurve) photometry, but we use also data obtained with other techniques, such as spectroscopy, thermal or radar observations. 15 of the 82 characterized asteroids are planned or possible targets of several space missions that are in flight or preparation, such as ESA’s Hera, RAMSES and PRIAMOS, NASA’s OSIRIS-APEX, JAXA’s Hayabusa2#, DESTINY+ and Next Generation Sample Return (NGSR), the Emirates Mission to Asteroids (EMA), and Karman+’s High Frontier, but we have also characterized 67 asteroids that are potential targets of space missions for their low delta-V’s and were announced as being “of interest to NASA” in the Small-Bodies-Observations- NASA mailing list or listed on the NHATS page of “Accessible NEAs”. The sample of asteroid targets span 3 orders of magnitude in size, with absolute magnitudes H from 12.57 to 26.8, corresponding to diameters from about 10 m to about 10 km. The sample contains a variety of taxonomic types and physically or dynamically interesting objects. Among them, we have identified 5 binary asteroids and 20 tumblers (i.e., asteroids in excited, non-principal axis rotation states). Rotation periods of the characterized asteroids range from 1.45 min to 280 h, reflecting diversity of their properties and formation/evolution paths. We will present an overview of the data set and highlight several representative cases.

Petr Pravec

Generalized fiducial inference on differentiable manifolds

We introduce a novel approach to inference on parameters that take values in a Riemannian manifold embedded in a Euclidean space. Parameter spaces of this form are ubiquitous across many fields, including chemistry, physics, computer graphics, and geology. Here, this new approach uses generalized fiducial inference (GFI) to obtain a posterior-like distribution on the manifold, without needing to know local parameterizations that map to the constrained space from an unconstrained Euclidean space. Using mathematical tools from Riemannian geometry, we construct a constrained generalized fiducial distribution (CGFD). A Bernstein-von Mises-type result for the CGFD, which provides intuition for how the desirable asymptotic qualities of the unconstrained generalized fiducial distribution are inherited by the CGFD, is provided. To illustrate the practical use of the CGFD, we provide a proof-of-concept example in the context of a linear logspline density estimation problem, and demonstrate that CGFD-based confidence sets exhibit desirable coverage properties via simulation. As an application, we fit a CGFD to COVID-19 case count data from North Carolina, USA.

97 MATHEMATICS AND COMPUTING

LPV Modeling of a Flexible Wing Aircraft Using Modal Alignment and Adaptive Gridding Methods

One of the earliest approaches in gain-scheduling control is the gridding based approach, in which a set of local linear time-invariant models are obtained at various gridded points corresponding to the varying parameters within the flight envelop. In order to ensure smooth and effective Linear Parameter-Varying control, aligning all the flexible modes within each local model and maintaining small number of representative local models over the gridded parameter space are crucial. In addition, since the flexible structural models tend to have large dimensions, a tractable model reduction process is necessary. In this paper, the notion of s-shifted H2- and H Infinity-norm are introduced and used as a metric to measure the model mismatch. A new modal alignment algorithm is developed which utilizes the defined metric for aligning all the local models over the entire gridded parameter space. Furthermore, an Adaptive Grid Step Size Determination algorithm is developed to minimize the number of local models required to represent the gridded parameter space. For model reduction, we propose to utilize the concept of Composite Modal Cost Analysis, through which the collective contribution of each flexible mode is computed and ranked. Therefore, a reduced-order model is constructed by retaining only those modes with significant contribution. The NASA Generic Transport Model operating at various flight speeds is studied for verification purpose, and the analysis and simulation results demonstrate the effectiveness of the proposed modeling approach.

LPV Modeling

Extreme Meteorological Parameters During Space Shuttle Pad Exposure Periods

During the 113 missions of the Space Transportation System (STS), the Space Shuttle fleet has been exposed to the elements on the launch pad for a total of 4195 days. This paper provides a summary of the historical record of the meteorological extremes encountered by the Space Shuttle fleet during the pad exposure period. Parameters included are temperature, dew point, relative humidity, wind speed, sea level pressure and precipitation. All the data presented are archived by the Marshall Space Flight Center Environments Group, and were obtained from a combination of surface observations and meteorological towers at Kennedy Space Center (KSC), Florida. Data are provided from the first launch of the STS in 1981 through the launch of STS-107 in 2003.

B. Glenn Overbey

Hitting the Thermal Target for Leptophilic Dark Matter at Future Lepton Colliders

We study future lepton collider prospects for testing predictive models of leptophilic dark matter (DM) candidates with a thermal origin. We calculate experimental milestones for testing the parameter space compatible with freeze-out and the associated collider signals at past, present, and future facilities. This analysis places new limits on such models by leveraging the utility of lepton colliders. At 𝑒+⁢𝑒− machines, we make projections using precision 𝑍 -pole observables from 𝑒+⁢𝑒−→ℓ+⁢ℓ−+𝐸 signatures at large electron-positron collider and future projections for future circular collider (ee) in these channels. Additionally, a muon collider could also probe new thermal relic parameter space in this scenario via 𝜇+⁢𝜇−→𝑋+𝐸 , where 𝑋 is any easily identifiable standard model object. Collectively, these processes can probe much of the parameter space for which DM direct annihilation to ℓ+⁢ℓ− yields the observed relic density in Higgs-like models with mass-proportional couplings to charged leptons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Experimental targets for dark photon dark matter

Ultralight dark photon dark matter features distinctive cosmological and astrophysical signatures and is also supported by a burgeoning direct-detection program searching for its kinetic mixing with the ordinary photon over a wide mass range. Dark photons, however, cannot necessarily constitute the dark matter in all of this parameter space. In minimal models where the dark photon mass arises from a dark Higgs mechanism, early-Universe dynamics can easily breach the regime of validity of the low-energy effective theory for a massive vector field. In the process, the dark sector can collapse into a cosmic string network, precluding dark photons as viable dark matter. We establish the general conditions under which dark photon production avoids significant backreaction on the dark Higgs and identify regions of parameter space that naturally circumvent these constraints. After surveying implications for known dark photon production mechanisms, we propose novel models that set well-motivated experimental targets across much of the accessible parameter space. We also discuss complementary cosmological and astrophysical signatures that can probe the dark sector physics responsible for dark photon production.

Dark matter

Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts

This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

Numerical Analysi

Machine Learning for Mapping Multipactor Susceptibility in RF Systems: Capabilities and Generalization Constraints

Multipactor is a surface-driven electron avalanche phenomenon that degrades the performance and reliability of radio-frequency (RF) systems in particle accelerator and vacuum electronics applications. Multipactor behavior in a given device structure is conventionally assessed through susceptibility charts, which provide a parameter-space characterization of the instability. In this work, we assess the capabilities of machine-learning (ML) models to learn and predict such susceptibility charts and analyze the constraints governing their generalization across materials. Using a simulation-derived dataset spanning six distinct secondary-electron-yield material profiles in a canonical two-surface planar geometry, we train supervised regression models and artificial neural networks to predict the time-averaged electron growth rate, δavg, across the relevant parameter space. Model performance is evaluated using metrics that explicitly probe the structure of susceptibility charts, including Intersection over Union, Structural Similarity Index, and correlation analysis. Tree-based ensemble models outperform neural-network models in reconstructing susceptibility regions and in generalizing across material domains. Principal-component analysis reveals disjoint material feature distributions, indicating that the piecewise mode structure of multipactor susceptibility is difficult to represent with a single global model and that generalization is constrained by data coverage rather than by model complexity. An exhaustive reduced-coverage study further shows that sparse material-space coverage can yield mean performance in the same general range but producing large variability in the susceptibility-region overlap. These results clarify the capabilities of ML-based surrogate models for parameter-space characterization of multipactor discharge. They also provide guidance for their appropriate use in RF system design.

43 PARTICLE ACCELERATORS

A Uniform Search for Nearby Planetary Companions to Hot Jupiters in TESS Data Reveals Hot Jupiters Are Still Lonely

We present the results of a uniform search for additional planets around all stars with confirmed hot Jupiters observed by the Transiting Exoplanet Survey Satellite (TESS) in its Cycle 1 survey of the southern ecliptic hemisphere. Our search comprises 184 total planetary systems with confirmed hot Jupiters with Rp > 8 R⊕ and orbital period <10 days. The Transit Least Squares algorithm was utilized to search for periodic signals that may have been missed by other planet search pipelines. While we recovered 169 of these confirmed hot Jupiters, our search yielded no new statistically validated planetary candidates in the parameter space searched (P < 14 days). A lack of planet candidates nearby hot Jupiters in the TESS data supports results from previous transit searches of each individual system, now down to the photometric precision of TESS. This is consistent with expectations from a high-eccentricity migration formation scenario, but additional formation indicators are needed for definitive confirmation. We injected transit signals into the light curves of the hot Jupiter sample to probe the pipeline's sensitivity to the target parameter space, finding a dependence proportional to ${R}_{p}^{2.32}{P}^{-0.88}$ for planets within 0.3 ≤ Rp ≤ 4 R⊕ and 1 ≤ P ≤ 14 days. A statistical analysis accounting for this sensitivity provides a median and 90% confidence interval of ${7.3}_{-7.3}^{+15.2} \% $ for the rate of hot Jupiters with nearby companions in this target parameter space. This study demonstrates how TESS uniquely enables comprehensive searches for nearby planetary companions to nearly all the known hot Jupiters.

Benjamin J Hord

Non-Hermitian quantum mechanics approach for extracting and emulating continuum physics based on bound-state-like calculations: Detailed description

Here, this work applies a reduced basis method to study the continuum physics of a finite quantum system—either few or many-body. Specifically, I develop reduced-order models, or emulators, for the underlying inhomogeneous Schrödinger equation and train the emulators against the equation's bound-state-like solutions at complex energies. The emulators rapidly and accurately interpolate and extrapolate the matrix elements of the Hamiltonian resolvent operator (Green's function) across a parameter space that includes both complex energy and other real-valued physical inputs in the Schrödinger equation. The spectra, discretized and compressed as the result of emulation, and the associated resolvent matrix elements (or amplitudes), have the defining characteristics of non-Hermitian quantum mechanics calculations, featuring complex eigenenergies with negative imaginary parts and branch cuts moved below the real axis in the complex energy plane. Therefore, one now has a method that extracts continuum physics from bound-state-like calculations and emulates those extractions in the input parameter space. Building on a prior Letter [Zhang, Phys. Rev. Lett. 135, 242501 (2025)], this article provides the full theoretical details, a comprehensive analysis of the method's performance, and a brief discussion of how it can be coupled with existing continuum approaches to perform emulations in their input parameter spaces.

ab initio calculations

Boosted Dark Matter Search with the ICARUS Detector at the Gran Sasso Underground National Laboratory

The quest to discover dark matter is one of the most pressing topics in modern physics. Evidence of gravitational anomalies is present at different cosmological scales, spanning the stability and rotation of galaxies to the overall density profile of the entire observable Universe. Due to the discrepancy between the mass measured and the gravitational influence on the mass, if General Relativity is to correctly describe gravity at different scales, extra electromagnetically invisible matter termed dark matter must exist. In recent decades, many experiments have been performed to detect dark matter with masses that span many orders of magnitude, from Mass Compact Halo Objects (MACHOs) with masses several orders of magnitude that of our sun to very light particles on the order of $\sim\mu$eV. However, experiments have only been able to constrain the possible parameter space of dark matter models and, in general, probe dark matter models with single constituent dark matter like Weakly Interacting Massive Particles (WIMPs). In the Boosted Dark Matter (BDM) paradigm, there are four particles in the dark sector: $\chi_0$, $\chi_1$, $\chi_2$, and the dark photon $X$. WIMP-like properties are ascribed to $\chi_0$ to describe the physics of the gravitational anomalies, while relativistic components are assigned to $\chi_1$ and $\chi_2$. The inelastic boosted dark matter (iBDM) channel $\chi_1 e^-\rightarrow \chi_2 e^-\rightarrow \chi_1 Xe^-\rightarrow \chi_1 (e^+ e^- ) e^-$, where $\chi_2$ is an excited state of $\chi_1$, has a unique signature that is distinguishable from neutrino interactions, making neutrino experiments a viable search environment for BDM. Using data collected by the ICARUS collaboration with ICARUS T-600 Liquid Argon Time Projection Chamber (LArTPC) during its operation at the Gran Sasso Underground Laboratory (LNGS), the first-ever LArTPC dark matter search using the ICARUS detector is presented. With a total detector exposure of 0.13 kton$\cdot$year, a total of 4 iBDM candidate events were identified by several stages of data scanning. All were rejected due to defined selection criteria and a wire-by-wire $dE/dx$ evaluation, giving a null result. Exclusion plots at 90\%C.L. for the dark photon ($m_X$, $\epsilon$) parameter space for fixed ($m_0,m_1,m_2$) DM mass sets are presented, setting new limits on the dark photon visible decay parameter space.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS