The "Myth" of the Minimum SAR Antenna Area Constraint
A design constraint traceable to the early days of spaceborne Synthetic Aperture Radar (SAR) is known as teh minimum antenna area constraint for SAR.
SAR↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Was the Sun a Slow Rotator? Sodium and Potassium Constraints from the Lunar Regolith
While the Earth and Moon are generally similar in composition, a notable difference between the two is the apparent depletion in moderately volatile elements in lunar samples. This is often attributed to the formation process of the Moon, and it demonstrates the importance of these elements as evolutionary tracers. Here we show that paleo space weather may have driven the loss of a significant portion of moderate volatiles, such as sodium and potassium, from the surface of the Moon. The remaining sodium and potassium in the regolith is dependent on the primordial rotation state of the Sun. Notably, given the joint constraints shown in the observed degree of depletion of sodium and potassium in lunar samples and the evolution of activity of solar analogs over time, the Sun is highly likely to have been a slow rotator. Because the young Sun's activity was important in affecting the evolution of planetary surfaces, atmospheres, and habitability in the early Solar System, this is an important constraint on the solar activity environment at that time. Finally, as solar activity was strongest in the first billion years of the Solar System, when the Moon was most heavily bombarded by impactors, evolution of the Sun's activity may also be recorded in lunar crust and would be an important well-preserved and relatively accessible record of past Solar System processes.
Prabal Saxena↗
Constraints on the chemical enrichment history of the Perseus Cluster of galaxies from high-resolution X-ray spectroscopy
High-resolution spectroscopy of the core of the Perseus Cluster of galaxies, using the Hitomi satellite above 2 keV and the XMM–Newton Reflection Grating Spectrometer at lower energies, provides reliable constraints on the abundances of O, Ne, Mg, Si, S, Ar, Ca, Cr, Mn, Fe, and Ni. Accounting for all known systematic uncertainties, the Ar/Fe, Ca/Fe, and Ni/Fe ratios are determined with a remarkable precision of less than 10 per cent, while the constraints on Si/Fe, S/Fe, and Cr/Fe are at the 15 per cent level, and Mn/Fe is measured with a 20 percent uncertainty. The average biases in determining the chemical composition using archival CCD spectra from XMM–Newton and Suzaku typically range from 15 to 40 per cent. A simple model in which the enrichment pattern in the Perseus Cluster core and the protosolar nebula are identical gives a surprisingly good description of the high-resolution X-ray spectroscopy results, with X^2=10.7 for 10 degrees of freedom. However, this pattern is challenging to reproduce with linear combinations of existing supernova nucleosynthesis calculations, particularly given the precise measurements of intermediateα-elements enabled by Hitomi. We discuss in detail the degeneracies between various supernova progenitor models and explosion mechanisms, and the remaining uncertainties in these theoretical models. We suggest that including neutrino physics in the core-collapse supernova yield calculations may improve the agreement with the observed pattern ofα-elements in the Perseus Cluster core. Our results provide a complementary benchmark for testing future nucleosynthesis calculations required to understand the origin of chemical elements.
A Simionescu↗
Constraints on Cosmic Strings Using Data from the Third Advanced LIGO-Virgo Observing Run
We search for gravitational-wave signals produced by cosmic strings in the Advanced LIGO and Virgo full O3 dataset. Search results are presented for gravitational waves produced by cosmic string loop features such as cusps, kinks, and, for the first time, kink-kink collisions. A template-based search for short-duration transient signals does not yield a detection. We also use the stochastic gravitational-wave background energy density upper limits derived from the O3 data to constrain the cosmic string tension Gμ as a function of the number of kinks, or the number of cusps, for two cosmic string loop distribution models. Additionally, we develop and test a third model that interpolates between these two models. Our results improve upon the previous LIGO–Virgo constraints on Gμ by 1 to 2 orders of magnitude depending on the model that is tested. In particular, for the one-loop distribution model, we set the most competitive constraints to date: Gμ ≲ 4×10−15. In the case of cosmic strings formed at the end of inflation in the context of grand unified theories, these results challenge simple inflationary models.
J B Camp↗
Diving below the Spin-down Limit: Constraints on Gravitational Waves from the Energetic Young Pulsar PSR J0537-6910
We present a search for quasi-monochromatic gravitational-wave signals from the young, energetic X-ray pulsar PSR J0537−6910 using data from the second and third observing runs of LIGO and Virgo. The search is enabled by a contemporaneous timing ephemeris obtained using Neutron star Interior Composition Explorer (NICER) data. The NICER ephemeris has also been extended through 2020 October and includes three new glitches. PSR J0537−6910 has the largest spin-down luminosity of any pulsar and exhibits fRequent and strong glitches. Analyses of its long-term and interglitch braking indices provide intriguing evidence that its spin-down energy budget may include gravitational-wave emission from a time-varying mass quadrupole moment. Its 62 Hz rotation frequency also puts its possible gravitational-wave emission in the most sensitive band of the LIGO/Virgo detectors. Motivated by these considerations, we search for gravitational-wave emission at both once and twice the rotation frequency from PSR J0537−6910. We find no signal, however, and report upper limits. Assuming a rigidly rotating triaxial star, our constraints reach below the gravitational-wave spin-down limit for this star for the first time by more than a factor of 2 and limit gravitational waves from the l = m = 2 mode to account for less than 14% of the spin-down energy budget. The fiducial equatorial ellipticity is constrained to less than about 3 ×10^(−5), which is the third best constraint for any young pulsar.
R. Abbott↗
Explaining Soft-Goal Conflicts through Constraint Relaxations
Recent work suggests to explain trade-offs between soft goals in terms of their conflicts, i. e., minimal unsolvable soft-goal subsets. But this does not explain the conflicts themselves: Why can a given set of soft-goals not be jointly achieved? Here we approach that question in terms of the underlying constraints on plans in the task at hand, namely resource availability and time windows. In this context, a natural form of explanation for a soft-goal conflict is a minimal constraint relaxation under which the conflict disappears (“if the deadline was 1 hour later, it would work”). We explore algorithms for computing such explanations. A baseline is to simply loop over all relaxed tasks and compute the conflicts for each separately. We improve over this by two algorithms that leverage information – conflicts, reachable states – across relaxed tasks. We show that these algorithms can exponentially outperform the baseline in theory, and we run experiments confirming that advantage in practice.
Planning↗
Constraint-based Brittleness Analysis of Task Networks for Planetary Rovers
We propose a new method to analyze brittleness of task networks with respect to not only temporal but any arbitrary set of constraints. The method allows the detection and enumeration of activities that, with modest duration variation, violate the target constraints.
Agrawal, Jagriti↗
Influence of the Perception Constraint, Installation Effects, and Broadband SelfNoise on Low-Fidelity, Multi-point, UAM Vehicle Perception-Influenced-Design(PID) Optimization
UAM vehicles represent a unique challenge in acoustics because there are a limited number of full-scale datasets that can be used to calibrate and validate prediction models. In addition, acoustics is considered more often in the early design loop as a higher priority concern in UAM vehicle design, whereas with traditional vehicles, acoustics is typically addressed with post-design constraints. This paper will present an approach in design optimization of a proprotor in two flight conditions, hover, and forward flight, with several acoustic objective functions that simulate community response. An adjoint-capable vortex-lattice method (VLM), implemented in VSPAERO, will be used to compute the blade forces and inflow properties required to compute tonal and broadband noise using the second-generation Aircraft NOise Prediction Program (ANOPP2). In addition, a wing is placed near the proprotor to simulate installation effects on a vehicle’s wing. The influence of rotation rate, chord distribution, twist angle, and sweep on installation, broadband noise, and choice of perception constraint from the design optimization will be shown.
acoustics↗
Constraints on Triple Oxygen Isotope Kinetics
Triple oxygen isotope methods (e.g., using δ 18 O, and Δ′ 17 O) have been used to classify meteorites, to constrain atmospheric chemistry, and to estimate primary productivity, among other uses. Such utility relies on the mass dependency of most chemical reactions: δ 17 O is proportional to δ 18 O by roughly a factor of 0.5. However, in detail, mass-dependency factors vary. While constraints on mass dependency are well established for equilibrium isotope effects, similar constraints for kinetic isotope effects are lacking. Using an ab initio Monte Carlo approach (see envelopes in Figure 1), we find the range of kinetic isotope effects (i.e., resulting from unidirectional chemical reactions) contains and exceeds the range of accessible equilibrium isotope effects for the 16 O 17 O 18 O system (Hayles and Killingsworth, 2022). Accessible kinetic isotope effects can yield Δ′ 17 O variations as large 0.8 ‰ from a single kinetic fractionation step. Reactions that yield the largest deviations from equilibrium are those with the largest molecular mass difference between decomposition fragments, typically the two products such as a gas and solid generated from the thermal decomposition of an initial solid. Comparison of DFT transition state model results against previously published experiments on the thermal decomposition of calcite (CaCO 3 ) (Miller et al., 2002) and dehydroxylation of brucite (Mg(OH) 2 ) (Clayton and Mayeda, 2009) show they are matched with mass-dependent kinetic isotope effects. This approach can be applied to any system with more than two isotopes.
Oxygen isotopes↗
Silicon Partitioning Between Iron-Rich Metal and Silicate Melt: New Constraints From Aerodynamic Laser Levitation Furnace Experiments
The partitioning of light elements (e.g., Si, C, H, etc.) between silicate melts and iron metal alloys as a function of pressure and temperature is a critical constraint in defining the compositional evolution of planetary interiors. While there are a significant number of experimental studies in the literature that examine the various influences of oxygen fugacity, temperature, pressure, and composition on the metal-melt partitioning of silicon, it is difficult to disentangle the effects of each variable due to the nominally independent parameters (e.g., pressure, temperature, composition) being collinear. To better test for the independent effects of pressure, temperature, and melt composition on the partitioning of silicon between iron alloy and silicate melt, new high temperature (1800°–2500°C), rapid quench (~700°C/s) aerodynamic levitation laser-heating experiments in the Fe-Si-Mg-O (En65-Fa5-Si3-Fe27) system were conducted. This high temperature, low pressure method is ideal for these experiments because it eliminates the metal container as a sink for elements of interest to partition into, and it has a rapid quench rate that minimizes potential exsolution of silicon from the metal phase during quench cooling. Given the short run times of the levitation experiments (30–60 seconds), a time series at a lower temperature (1700°C) in a vertical gas-mixing muffle tube furnace was also conducted to assess equilibrium times of the bulk composition. All successful runs were imaged using back-scatter electron imaging and analyzed for phase composition using a JEOL 8530F field emission microprobe. These new data were added to a comprehensive and internally consistent data set created from published experiments, and subsequently modeled using parameters designed to minimize collinearity (e.g., optical basicity is used as a proxy for melt composition). High collinearity is found in the data set however between temperature and oxygen fugacity, precluding any model that contains both as nominally independent variables. The resulting model demonstrates a statistically significant effect of pressure, temperature, and melt composition on the partitioning of silicon in Fe-rich metal, which has implications for the formation of planetary cores in rocky planets and provides important constraints on potential bulk core compositions.
Metal↗
Estimating Cosmological Constraints from Galaxy Cluster Abundance using Simulation-Based Inference
Inferring the values and uncertainties of cosmological parameters in a cosmology model is of paramount importance for modern cosmic observations. In this paper, we use the simulation-based inference (SBI) approach to estimate cosmological constraints from a simplified galaxy cluster observation analysis. Using data generated from the Quijote simulation suite and analytical models, we train a machine learning algorithm to learn the probability function between cosmological parameters and the possible galaxy cluster observables. The posterior distribution of the cosmological parameters at a given observation is then obtained by sampling the predictions from the trained algorithm. Our results show that the SBI method can successfully recover the truth values of the cosmological parameters within the 2σ limit for this simplified galaxy cluster analysis, and acquires similar posterior constraints obtained with a likelihood-based Markov Chain Monte Carlo method, the current state-of the-art method used in similar cosmological studies.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Use of Rig Parameter Data in Bit Constraint Models for Improved Drilling Performance at The Geysers
Surface parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. However, these measurements are of reduced value without a standard to aid in evaluation and decision making. A method is demonstrated whereby drill bit constraint models are used to interpret drilling response parameters. Drill rig parameter data for well GDC-36 at the Geysers Geothermal Field Power were acquired by Geysers Power Company and drilling contractor Kenai Drilling using Pason US DataHub and evaluated. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) along with other model constraints in computational algorithms. The method is used to evaluate overall bit performance, monitor bit integrity, and detect the presence of drillstring vibrations and other conditions contributing to bit failure; comparisons are made to observations of bit wear and damage. The method will be applied in real-time to improve decision-making on subsequent wells and has applicability to development of advanced analytics on future geothermal wells using real-time electronic drilling recorder (EDR) data for improved performance and reduced drilling costs.
15 GEOTHERMAL ENERGY↗
Cosmological Constraints from Full-Scale Clustering and Galaxy-Galaxy Lensing with DESI DR1
We present constraints on cosmic structure growth from the analysis of galaxy clustering and galaxy-galaxy lensing with galaxies from the Dark Energy Spectroscopic Instrument (DESI) Data Release 1. We analyze four samples drawn from the Bright Galaxy Survey (BGS) and the Luminous Red Galaxy (LRG) target classes. Projected galaxy clustering measurements from DESI are supplemented with lensing measurements from the Dark Energy Survey (DES), the Kilo-Degree Survey (KiDS), and the Hyper Suprime-Cam (HSC) survey around the same targets. Our method relies on a simulation-based modeling framework using the AbacusSummit simulations and a complex halo occupation distribution model that incorporates assembly bias. We analyze scales down to $0.4 \, h^{-1} \, \mathrm{Mpc}$ for clustering and $2.5 \, h^{-1} \, \mathrm{Mpc}$ for lensing, leading to stringent constraints on $S_8 = σ_8 \sqrt{Ω_\mathrm{m} / 0.3}$ and $Ω_\mathrm{m}$ when fixing other cosmological parameters to those preferred by the CMB. We find $S_8 = 0.794 \pm 0.023$ and $Ω_\mathrm{m} = 0.295 \pm 0.012$ when using lensing measurements from DES and KiDS. Similarly, for HSC, we find $S_8 = 0.793 \pm 0.017$ and $Ω_\mathrm{m} = 0.303 \pm 0.010$ when assuming the best-fit photometric redshift offset suggested by the HSC collaboration. Overall, our results are in good agreement with other results in the literature while continuing to highlight the constraining power of non-linear scales.
Lange, Johannes U. [American U.] (ORCID:0000000224↗
Dark Energy Survey Year 6 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing
We present cosmology results combining galaxy clustering and weak gravitational lensing measured in the full six years (Y6) of observations by the Dark Energy Survey (DES) covering $\sim$5000 deg$^2$. We perform a large-scale structure analysis using three two-point correlation functions (3$\times$2pt): (i) cosmic shear from 140 million source galaxy shapes, (ii) galaxy clustering of 9 million lens galaxy positions, and (iii) galaxy-galaxy lensing from their cross-correlation. We model the data in flat $Λ$CDM and $w$CDM cosmologies. The combined analysis yields $S_8\equiv σ_8 (Ω_{\rm m}/0.3)^{0.5} = 0.789^{+0.012}_{-0.012}$ and matter density $Ω_{\rm m} = 0.333^{+0.023}_{-0.028}$ in $Λ$CDM (68% CL), where $σ_8$ is the clustering amplitude. These constraints show a (full-space) parameter difference of 1.8$σ$ from a combination of cosmic microwave background (CMB) primary anisotropy datasets from Planck 2018, ACT-DR6, and SPT-3G DR1. Projected only into $S_8$ the difference is $2.6σ$. In $w$CDM the Y6 3$\times$2pt results yield $S_8 = 0.782^{+0.021}_{-0.020}$, $Ω_{\rm m} = 0.325^{+0.032}_{-0.035}$, and dark energy equation-of-state parameter $w = -1.12^{+0.26}_{-0.20}$. For the first time, we combine all DES dark-energy probes: 3$\times$2pt, SNe Ia, BAO and Clusters. In $Λ$CDM this combination yields a $2.8σ$ parameter difference from the CMB. When combining DES 3$\times$2pt with other low-redshift datasets (DESI DR2 BAO, DES SNe Ia, SPT clusters), we find a 2.3$σ$ parameter difference with CMB. A joint fit of Y6 3$\times$2pt, CMB, and those low-redshift datasets produces the tightest $Λ$CDM constraints to date: $S_8 = 0.806^{+0.006}_{-0.007}$, $Ω_{\rm m} = 0.302^{+0.003}_{-0.003}$, $h = 0.683^{+0.003}_{-0.002}$, and $\sum m_ν< 0.14$ eV (95% CL). In $w$CDM, this combination yields $w = -0.981^{+0.021}_{-0.022}$.
Abbott, T. M.C. [Cerro-Tololo InterAmerican Obs.]↗
Forecasting Dark Matter Subhalo Constraints from Stellar Streams using Implicit Likelihood Inference
The evidence for dark matter (DM) remains compelling, although attempts to understand its particle nature remain inconclusive. One promising method to study DM is detecting DM subhalos through their gravitational interactions with stellar streams. In this study, we apply Neural Posterior Estimation (NPE) to constrain subhalo interaction parameters, including mass, scale radius, velocity, and encounter geometry, from stellar stream kinematics. We generate particle spray simulations based on the Lagrange Cloud stripping technique, focusing on the ATLAS-Aliqa Uma stream as a test case. We train multiple NPE models across multiple observational scenarios, quantifying how kinematic completeness affects inference and forecasting constraints from upcoming surveys including LSST, 4MOST, and 10-year Gaia data. Our results demonstrate that NPE can produce accurate and well-calibrated posteriors. In the idealized case with full 6D coordinates, we achieve subhalo mass uncertainties of 15-20% for a $10^7 \, \mathrm{M_\odot}$ subhalo, with 5D coordinates (excluding radial velocities) achieving similar performance. Under realistic observational conditions, mass uncertainties range from 50% (present-day) to 20-40% (future scenarios), with comparable performance between the photometric-only LSST sample and a smaller sample that includes Gaia proper motions and 4MOST radial velocities. Most notably, we find that velocity bimodality emerges when phase space is poorly sampled, whether due to missing kinematic information or limited stellar tracers. Combining large photometric samples with targeted spectroscopic follow-up can effectively resolves this degeneracy. These results demonstrate the power of implicit likelihood inference for optimizing stellar stream observational strategies and forecasting DM subhalo constraints from upcoming surveys.
Nguyen, Tri [Northwestern U. (main); SkAI, Chicago↗
High-energy neutrino constraints on primordial black holes as dark matter
Primordial black holes (PBHs) are one of the most appealing dark matter candidates over a wide range of masses and abundances. This broad parameter space has been constrained by a variety of observational probes. In this work, for the first time, we use data from high-energy neutrino telescopes, like IceCube and ANTARES, to constrain sub-asteroid mass ($\lesssim 10^{18}\,\mathrm{g}$) Schwarzschild PBHs with extended mass functions. We derive limits from the diffuse high-energy neutrino flux produced by the direct evaporation of PBHs, as well as from the transient signatures associated with PBHs passing in the vicinity of the Earth. While our bounds are slightly weaker than existing constraints from gamma-ray observations, they provide an independent and complementary probe based on observational high-energy neutrino data. We further show that future detectors such as IceCube-Gen2 and KM3NeT can significantly improve these constraints, potentially excluding PBHs with masses up to $\sim \mathrm{few} \times 10^{18}\,\mathrm{g}$ composing the entirety of dark matter.
Mukhopadhyay, Mainak [Fermilab; Chicago U., KICP] ↗
Dark Matter Constraints from Small-Scale Cosmic Structure
Small-scale cosmic structure provides a powerful test of the fundamental nature of dark matter (DM). A wide range of DM models impact matter clustering on small scales, including warm, fuzzy, and (self-)interacting DM. In these scenarios, DM physics such as free-streaming, wave interference, and self/Standard Model interactions alter the abundance and internal structure of DM halos. Cosmological and astrophysical probes of nonlinear structure---including dwarf galaxies, strong lensing, the Lyman-$α$ forest, stellar streams, and high-redshift galaxies---are therefore sensitive to these effects. Here, we review DM constraints provided by small-scale structure, focusing on observables that probe scales smaller than $\sim 1~\mathrm{Mpc}$, which define the frontier of current measurements. We summarize how these constraints have been translated to limits on microphysical DM models, and we discuss key modeling uncertainties and observational systematics. Finally, we highlight the growing importance of probe combination and simulation-based inference for this field, and we overview upcoming observational facilities that will sharpen small-scale structure tests of DM physics.
Nadler, Ethan O. [UC, San Diego] (ORCID:0000000211↗
Examining organic acid production potential and growth‐coupled strategies in Issatchenkia orientalis using constraint‐based modeling
Abstract Growth‐coupling product formation can facilitate strain stability by aligning industrial objectives with biological fitness. Organic acids make up many building block chemicals that can be produced from sugars obtainable from renewable biomass. Issatchenkia orientalis is a yeast strain tolerant to acidic conditions and is thus a promising host for industrial production of organic acids. Here, we use constraint‐based methods to assess the potential of computationally designing growth‐coupled production strains for I. orientalis that produce 22 different organic acids under aerobic or microaerobic conditions. We explore native and engineered pathways using glucose or xylose as the carbon substrates as proxy constituents of hydrolyzed biomass. We identified growth‐coupled production strategies for 37 of the substrate‐product pairs, with 15 pairs achieving production for any growth rate. We systematically assess the strain design solutions and categorize the underlying principles involved.
59 BASIC BIOLOGICAL SCIENCES↗