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At least 1,297 records · Page 72

Constrained curve fitting for semi-parametric models with radial basis function networks

Common to many analysis pipelines in lattice gauge theory and the broader scientific discipline is the need to fit a semi-parametric model to data. We propose a fit method that utilizes a radial basis function network to approximate the non-parametric component of such models. The approximate parametric model is fit to data using the basin hopping global optimization algorithm. Parameter constraints are enforced through Gaussian priors. The viability of our method is tested by examining its use in a finite-size scaling analysis of the $q$-state Potts model and $p$-state clock model with $q=2,3$ and $p=4,\infty$.

Peterson, Curtis T.↗

Constraining the Varied Response of Northern Hemisphere Winter Circulation Waviness to Climate Change

Abstract While a large latitudinal displacement of the westerly jet brings about disproportionate socioeconomic impacts over Northern Hemisphere midlatitude continents, it is not well understood as to whether the winter circulation will become wavier or less in response to climate change. Here, using observations and large ensembles of climate models, we show that changes in atmospheric waviness can be estimated from the optimal structures of the westerly jet for wavier circulation, which are obtained from an advection‐diffusion model. Thus, the changes in westerly jet structure in climate models under climate change provide a physical constraint on changes in atmospheric waviness, indicating that the North Atlantic wave activity will experience a robust decline in a warmer climate, while future North Pacific wave activity is obscured by model uncertainty rather than internal variability. These findings highlight the changes to jet stream structure as a constraint for regional circulation waviness in a changing climate.

54 ENVIRONMENTAL SCIENCES↗

Consumer Expectations of Capacity Constrains and Their Effect on the Demand for Multi-Class Air Travel

This paper argues that a consumer's decision on ticket class takes into account the expected likelihood of obtaining a seat in a particular class which, in turn, partially depends on an optimum "transaction cost". Taking into account the preferences of the consumer and the information that the consumer is endowed with, the consumer will select a ticket that includes its own optimal transaction cost. This motivates the inclusion of the capacity constraint as a proxy independent variable for these consumer expectations This then forms the basis of a model of air-travel demand with specific reference to Australia. A censored likelihood function allowing for correlation in the disturbance term across k classes is introduced. The correlation in the disturbances arises as a result of the interdependence of the capacity constraints in k different ticket classes on each flight.

Battersby, Bryn D.↗

Efficient Trajectory Options Allocation for the Collaborative Trajectory Options Program

The Collaborative Trajectory Options Program (CTOP) is a Traffic Management Initiative (TMI) intended to control the air traffic flow rates at multiple specified Flow Constrained Areas (FCAs), where demand exceeds capacity. CTOP allows flight operators to submit the desired Trajectory Options Set (TOS) for each affected flight with associated Relative Trajectory Cost (RTC) for each option. CTOP then creates a feasible schedule that complies with capacity constraints by assigning affected flights with routes and departure delays in such a way as to minimize the total cost while maintaining equity across flight operators. The current version of CTOP implements a Ration-by-Schedule (RBS) scheme, which assigns the best available options to flights based on a First-Scheduled-First-Served heuristic. In the present study, an alternative flight scheduling approach is developed based on linear optimization. Results suggest that such an approach can significantly reduce flight delays, in the deterministic case, while maintaining equity as defined using a Max-Min fairness scheme.

Traffic Management Initiative (TMI)↗

The persistence of large scale structures. Part I. Primordial non-Gaussianity

Abstract We develop an analysis pipeline for characterizing the topology of large scale structure and extracting cosmological constraints based on persistent homology . Persistent homology is a technique from topological data analysis that quantifies the multiscale topology of a data set, in our context unifying the contributions of clusters, filament loops, and cosmic voids to cosmological constraints. We describe how this method captures the imprint of primordial local non-Gaussianity on the late-time distribution of dark matter halos, using a set of N-body simulations as a proxy for real data analysis. For our best single statistic, running the pipeline on several cubic volumes of size 40 (Gpc/h) 3 , we detect f NL loc =10 at 97.5% confidence on ~ 85% of the volumes. Additionally wetest our ability to resolve degeneracies betweenthe topological signature of f NL loc and variation of σ 8 and argue that correctly identifying nonzero f NL loc in this case is possible via an optimal template method. Our method relies on information living at $\mathcal{O}$(10) Mpc/h, a complementary scale with respect to commonly used methods such as the scale-dependent bias in the halo/galaxy power spectrum. Therefore, while still requiring a large volume, our method does not require sampling long-wavelength modes to constrain primordial non-Gaussianity. Moreover, our statistics are interpretable: we are able to reproduce previous results in certain limits and we make new predictions for unexplored observables, such as filament loops formed by dark matter halos in a simulation box.

Astronomy & Astrophysics↗

Extended flexibility of neutron Larmor diffraction for increased diffraction range in mosaicity measurements

Larmor diffraction (LD) is a neutron scattering technique that offers enhanced resolution by harnessing the Larmor precession of neutron spins in a magnetic field. By encoding subtle changes in neutron momentum transfer into significant alterations in the Larmor phase of neutron spins, LD can be employed to measure lattice expansion, lattice distortion, and mosaicity with exceptional resolution. As originally proposed by Rekveldt et al., LD necessitates the magnetic field boundaries to be tilted to be parallel to the crystal plane of interest. Here, this report explores the fundamental principles shared between LD and spin-echo small-angle neutron scattering (SESANS). Drawing inspiration from the flexibility of SESANS to adjust magnetic field boundaries to optimize the resolution in the measurement of the neutron momentum transfers q, we will demonstrate that the strict requirement of parallel alignment between the magnetic field boundaries and the crystal plane can be relaxed for the measurements of mosaicity. Such relaxation will expand the accessible diffraction angles for these situations that are highly constrained.

Larmor diffraction↗

Active Control of the Forced and Transient Response of a Finite Beam

When studying structural vibrations resulting from a concentrated source, many structures may be modelled as a finite beam excited by a point source. The theoretical limit on cancelling the resulting beam vibrations by utilizing another point source as an active controller is explored. Three different types of excitation are considered, harmonic, random, and transient. In each case, a cost function is defined and minimized for numerous parameter variations. For the case of harmonic excitation, the cost function is obtained by integrating the mean squared displacement over a region of the beam in which control is desired. A controller is then found to minimize this cost function in the control interval. The control interval and controller location are continuously varied for several frequencies of excitation. The results show that control over the entire beam length is possible only when the excitation frequency is near a resonant frequency of the beam, but control over a subregion may be obtained even between resonant frequencies at the cost of increasing the vibration outside of the control region. For random excitation, the cost function is realized by integrating the expected value of the displacement squared over the interval of the beam in which control is desired. This is shown to yield the identical cost function as obtained by integrating the cost function for harmonic excitation over all excitation frequencies. As a result, it is always possible to reduce the cost function for random excitation whether controlling the entire beam or just a subregion, without ever increasing the vibration outside the region in which control is desired. The last type of excitation considered is a single, transient pulse. A cost function representative of the beam vibration is obtained by integrating the transient displacement squared over a region of the beam and over all time. The form of the controller is chosen a priori as either one or two delayed pulses. Delays constrain the controller to be causal. The best possible control is then examined while varying the region of control and the controller location. It is found that control is always possible using either one or two control pulses. The two pulse controller gives better performance than a single pulse controller, but finding the optimal delay time for the additional controllers increases as the square of the number of control pulses.

Post, John Theodore↗

Conditional Entropy-Constrained Residual VQ with Application to Image Coding

This paper introduces an extension of entropy-constrained residual vector quantization (VQ) where intervector dependencies are exploited. The method, which we call conditional entropy-constrained residual VQ, employs a high-order entropy conditioning strategy that captures local information in the neighboring vectors. When applied to coding images, the proposed method is shown to achieve better rate-distortion performance than that of entropy-constrained residual vector quantization with less computational complexity and lower memory requirements. Moreover, it can be designed to support progressive transmission in a natural way. It is also shown to outperform some of the best predictive and finite-state VQ techniques reported in the literature. This is due partly to the joint optimization between the residual vector quantizer and a high-order conditional entropy coder as well as the efficiency of the multistage residual VQ structure and the dynamic nature of the prediction.

Kossentini, Faouzi↗

Economic optimization of the energy transport component of a large distributed solar power plant

A solar thermal power plant with a field of collectors, each locally heating some transport fluid, requires a pipe network system for eventual delivery of energy power generation equipment. For a given collector distribution and pipe network geometry, a technique is herein developed which manipulates basic cost information and physical data in order to design an energy transport system consistent with minimized cost constrained by a calculated technical performance. For a given transport fluid and collector conditions, the method determines the network pipe diameter and pipe thickness distribution and also insulation thickness distribution associated with minimum system cost; these relative distributions are unique. Transport losses, including pump work and heat leak, are calculated operating expenses and impact the total system cost. The minimum cost system is readily selected. The technique is demonstrated on six candidate transport fluids to emphasize which parameters dominate the system cost and to provide basic decision data. Three different power plant output sizes are evaluated in each case to determine severity of diseconomy of scale.

Turner, R. H.↗

A UNIQUE APPROACH TO ACHIEVING SIZE-CONSTRAINED QUASI-HALO ORBITS FOR THE ROMAN SPACE TELESCOPE

The Nancy Grace Roman Space Telescope (RST) is an infrared space observatory planned for launch in the mid-2020’s. The launch window design for RST is subject to a wide variety of simultaneous requirements that require careful consideration and control of mission orbits and the trajectories used to achieve them. This work describes an innovative methodology that blends classical methods with modern manifold approaches and numerical optimization to flexibly determine optimal transfers to desriable mission orbits for any day of the year.Solutions found with this highly automated strategy are gaurunteed to meet requirements by construction. Results show that RST can launch for 80% of the year using maneuvers that are well within the fuel budget, significantly reducing cost and risk to the mission

Lauren Schlenker↗

Charged lepton flavor violation at the EIC

We present a comprehensive analysis of the potential sensitivity of the Electron-Ion Collider (EIC) to charged lepton flavor violation (CLFV) in the channel ep → τX, within the model-independent framework of the Standard Model Effective Field Theory (SMEFT). We compute the relevant cross sections to leading order in QCD and electroweak corrections and perform simulations of signal and SM background events in various τ decay channels, suggesting simple cuts to enhance the associated estimated efficiencies. To assess the discovery potential of the EIC in τ-e transitions, we study the sensitivity of other probes of this physics across a broad range of energy scales, from pp → eτX at the Large Hadron Collider to decays of B mesons and τ leptons, such as τ → eγ, τ → eℓ+ℓ–, and crucially the hadronic modes τ → eY with Yϵ {π, K, ππ, Kπ, …}. We find that electroweak dipole and four-fermion semi-leptonic operators involving light quarks are already strongly constrained by τ decays, while operators involving the c and b quarks present more promising discovery potential for the EIC. An analysis of three models of leptoquarks confirms the expectations based on the SMEFT results. We also identify future directions needed to maximize the reach of the EIC in CLFV searches: these include an optimization of the τ tagger in hadronic channels, an exploration of background suppression through tagging b and c jets in the final state, and a global fit by turning on all SMEFT couplings, which will likely reveal new discovery windows for the EIC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Constrained non-negative matrix factorization enabling real-time insights of in situ and high-throughput experiments

Non-negative matrix factorization (NMF) is an appealing class of methods for performing unsupervised learning on streaming spectral data, particularly in time-sensitive applications such as in situ characterization of materials. These methods seek to decompose a dataset into a small number of components and weights that can compactly represent the underlying signal while effectively reconstructing the observations with minimal error. However, canonical NMF methods have no underlying requirement that the reconstruction uses components or weights that are representative of the true physical processes. In this work, we demonstrate how constraining a subset of the NMF weights or components as rigid priors, provided as known or assumed values, can provide significant improvement in revealing true underlying phenomena. We present a PyTorch-based method for efficiently applying constrained NMF and demonstrate its application to several synthetic examples. Our implementation allows an expert researcher-in-the-loop to provide and dynamically adjust the constraints during a live experiment involving streaming spectral data. Such interactive priors allow researchers to specify known or identified independent components, as well as functional expectations about the mixing or transitions between the components. We further demonstrate the application of this method to measured synchrotron x-ray total scattering data from in situ beamline experiments. In such a context, constrained NMF can result in a more interpretive and scientifically relevant decomposition than canonical NMF or other decomposition techniques. As a result, the details of the method are provided, along with general guidance for employing constrained NMF in the extraction of critical information and insights during time-sensitive experimental applications.

36 MATERIALS SCIENCE↗

Optimizing Long Term Hydrogen Fueling Infrastructure Plans on Freight Corridors for Heavy Duty Fuel Cell Electric Vehicles

The development of a future hydrogen energy economy will require the development of several hydrogen market and industry segments including a hydrogen based commercial freight transportation ecosystem. For a sustainable freight transportation ecosystem, the supporting fueling infrastructure and the associated vehicle powertrains making use of hydrogen fuel will need to be co-established. This paper develops a long-term plan for refueling infrastructure deployment using the OR-AGENT (Optimal Regional Architecture Generation for Electrified National Transportation) tool developed at the Oak Ridge National Laboratory, which has been used to optimize the hydrogen refueling infrastructure requirements on the I-75 corridor for heavy duty (HD) fuel cell electric commercial vehicles (FCEV). This constraint-based optimization model considers existing fueling locations, regional specific vehicle fuel economy and weight, vehicle origin and destination (OD), vehicle volume by class and infrastructure costs to characterize in-mission refueling requirements for a given freight corridor. The authors applied this framework to determine the ideal long term public access locations for hydrogen refueling (constrained by existing fueling stations and dispensing technology), the minimal viable cost to deploy sufficient hydrogen fuel dispensers, and associated equipment, to accommodate a growing population of hydrogen fuel cell trucks. So the framework discussed in this paper can be expanded and applied to additional electrified powertrains as well as a larger interstate system, expanded regional corridor, or other transportation networks.

08 HYDROGEN↗

Advancing Geophysical Techniques to Image a Stratigraphic Hydrothermal Resource

Sedimentary-hosted geothermal energy systems are permeable structural, structural-stratigraphic, and/or stratigraphic horizons with sufficient temperature for direct use and/or electricity generation. Sedimentary-hosted (i.e., stratigraphic) geothermal reservoirs may be present in multiple locations across the central and eastern Great Basin of the USA, thereby constituting a potentially large base of untapped, economically accessible energy resources. Sandia National Laboratories has partnered with a multi disciplinary group of collaborators to evaluate a stratigraphic system in Steptoe Valley, Nevada using both established and novel geophysical imaging techniques. The goal of this study is to inform an optimized strategy for subsequent exploration and development of this resource and analogous ones. Building from prior Nevada Play Fairway Analysis (PFA), this team is primarily 1) collecting additional geophysical data, 2) employing novel joint geophysical inversion/modeling techniques to update existing 3D geologic models, and 3) integrating the geophysical results to produce a working, geologically constrained thermo-hydrological reservoir model. Prior PFA work highlights Steptoe Valley as a favorable resource basin that likely has both sedimentary and hydrothermal characteristics. However, there remains significant uncertainty on the nature and architecture of the resource(s) at depth, which increases the risk in exploratory drilling. Newly acquired gravity, magnetic, magnetotelluric, and controlled-source electromagnetic data products, in conjunction with new and preexisting geoscientific measurements and observations, are being integrated and evaluated for efficacy in understanding stratigraphic geothermal resources and mitigating exploration risk. Furthermore, the influence of hydrothermal activity on sedimentary-hosted reservoirs in favorable structural settings, and whether fault-controlled systems may locally enhance temperature and permeability in some deep stratigraphic reservoirs, will also be evaluated.

Geothermal, Sedimentary Heat, Geophysics, Seismic,↗

After DART: Using the first full-scale test of a kinetic impactor to inform a future planetary defense mission

NASA’s Double Asteroid Redirection Test (DART) is the first full-scale test of an asteroid deflection technology. Results from the hypervelocity kinetic impact and Earth-based observations, coupled with LICIACube and the later Hera mission, will result in measurement of the momentum transfer efficiency accurate to ~10% and characterization of the Didymos binary system. But DART is a single experiment; how could these results be used in a future planetary defense necessity involving a different asteroid? We examine what aspects of Dimorphos’s response to kinetic impact will be constrained by DART results; how these constraints will help refine knowledge of the physical properties of asteroidal materials and predictive power of impact simulations; what information about a potential Earth impactor could be acquired before a deflection effort; and how design of a deflection mission should be informed by this understanding. We generalize the momentum enhancement factor β, showing that a particular direction-specific β will be directly determined by the DART results, and that a related direction-specific β is a figure of merit for a kinetic impact mission. The DART β determination constrains the ejecta momentum vector, which, with hydrodynamic simulations, constrains the physical properties of Dimorphos’s near-surface. In a hypothetical planetary defense exigency, extrapolating these constraints to a newly discovered asteroid will require Earth-based observations and benefit from in-situ reconnaissance. We show representative predictions for momentum transfer based on different levels of reconnaissance and discuss strategic targeting to optimize the deflection and reduce the risk of a counterproductive deflection in the wrong direction.

Asteroids↗

Analyzing the Efficacy of Flexible Execution, Replanning, and Plan Optimization for a Planetary Lander

Plan execution in unknown environments poses a number of challenges: uncertainty in domain modeling, stochasticity at execution time, and the presence of exogenous events. These challenges motivate an integrated approach to planning and execution that is able to respond intelligently to variation. We examine this problem in the context of the Europa Lander mission concept, and propose a planning and execution framework that responds to feedback and task failure using two techniques: flexible execution and replanning with plan optimization. We develop a theoretical framework to predict the value of each of these techniques, and we compare these predictions to empirical results generated in simulation. We demonstrate that an integrated approach to planning and execution that is grounded in flexible execution, replanning, and utility maximization will be an enabling technology for future tightly-constrained planetary surface missions.

Chien, Steve↗

Analyzing the Efficacy of Flexible Execution, Replanning, and Plan Optimization for a Planetary Lander

Plan execution in unknown environments poses a number of challenges: uncertainty in domain modeling, stochasticity at execution time, and the presence of exogenous events. These challenges motivate an integrated approach to planning and execution that is able to respond intelligently to variation. We examine this problem in the context of the Europa Lander mission concept, and propose a planning and execution framework that responds to feedback and task failure using two techniques: flexible execution and replanning with plan optimization. We develop a theoretical framework to predict the value of each of these techniques, and we compare these predictions to empirical results generated in simulation. We demonstrate that an integrated approach to planning and execution that is grounded in flexible execution, replanning, and utility maximization will be an enabling technology for future tightly-constrained planetary surface missions.

Basich, Connor↗

Recent efforts of vapour-phase strategies for EUV resist toward high- and hyper-NA extreme ultraviolet lithography

Extreme ultraviolet lithography (EUVL, λ = 13.5 nm) is critical for sub-1 nm technology nodes but remains constrained by inherent trade-offs among resolution, line-edge roughness (LER), and sensitivity. Stochastic effects originating from photon shot noise, low-energy secondary electron blur, and the random distribution of resist components further limit its advancement toward high numerical-aperture (NA, NA = 0.55) and hyper-NA (NA ≥0.75) EUVL. While the optimization of spin-on chemically amplified resists (CARs) continues, metal-oxide resists (MORs) have emerged as strong candidates for next-generation EUVL by incorporating metals with high EUV absorption coefficients, which enhances both resist sensitivity and etch resistance during pattern transfer. Besides spin-coating, recent advances in vapour-phase techniques, such as vapour-phase infiltration (VPI), chemical vapour deposition (CVD), and molecular atomic layer deposition (MALD), offer promising pathways to achieve new resist platforms, such as dry resists, that satisfy the stringent thickness and uniformity requirements of next-generation EUVL. These methods enable the direct incorporation of metal species into existing resist matrices or the formation of hybrid inorganic–organic resist platforms, thereby improving film uniformity, etch durability, and pattern fidelity while mitigating stochastic defects. This review highlights the latest advancements in vapour-phase-synthesized EUV resists, emphasizing material design, lithographic performance, and the underlying exposure mechanisms. Although still emerging, vapour-phase strategies are paving the way for an all-dry integration framework that could improve EUV patterning workflows and meet the demands of future technology nodes.

36 MATERIALS SCIENCE↗