SEARCH · Search NASA

Results for “emergent constraint”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

DOE OSTI2025

AI for nuclear physics: the EXCLAIM project

An overview of the recent activity of the newly funded EXCLusives with AI and Machine learning (EXCLAIM) collaboration is presented. The main goal of the collaboration is to develop a framework to implement AI and machine learning techniques in problems emerging from the phenomenology of high energy exclusive scattering processes from nucleons and nuclei, maximizing the information that can be extracted from various sets of experimental data, while implementing theoretical constraints from lattice QCD. A specific perspective embraced by EXCLAIM is to use the methods of theoretical physics to understand the working of ML, beyond its standardized applications to physics analyses which most often rely on industrially provided tools, in an automated way.

Analysis and statistical methods↗

DOE OSTI2022

Unveiling the Universe with emerging cosmological probes

The detection of the accelerated expansion of the Universe has been one of the major breakthroughs in modern cosmology. Several cosmological probes (Cosmic Microwave Background, Supernovae Type Ia, Baryon Acoustic Oscillations) have been studied in depth to better understand the nature of the mechanism driving this acceleration, and they are being currently pushed to their limits, obtaining remarkable constraints that allowed us to shape the standard cosmological model. In parallel to that, however, the percent precision achieved has recently revealed apparent tensions between measurements obtained from different methods. These are either indicating some unaccounted systematic effects, or are pointing toward new physics. Following the development of CMB, SNe, and BAO cosmology, it is critical to extend our selection of cosmological probes. Novel probes can be exploited to validate results, control or mitigate systematic effects, and, most importantly, to increase the accuracy and robustness of our results. This review is meant to provide a state-of-art benchmark of the latest advances in emerging “beyond-standard” cosmological probes. We present how several different methods can become a key resource for observational cosmology. In particular, we review cosmic chronometers, quasars, gamma-ray bursts, standard sirens, lensing time-delay with galaxies and clusters, cosmic voids, neutral hydrogen intensity mapping, surface brightness fluctuations, stellar ages of the oldest objects, secular redshift drift, and clustering of standard candles. The review describes the method, systematics, and results of each probe in a homogeneous way, giving the reader a clear picture of the available innovative methods that have been introduced in recent years and how to apply them. The review also discusses the potential synergies and complementarities between the various probes, exploring how they will contribute to the future of modern cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Conformal freeze-in, composite dark photon, and asymmetric reheating

Large classes of dark sector models feature mass scales and couplings very different from the ones we observe in the Standard Model (SM). Moreover, in the freeze-in mechanism, often employed by the dark sector models, it is also required that the dark sector cannot be populated during the reheating process like the SM. This is the so called asymmetric reheating. Such disparities in sizes and scales often call for dynamical explanations. In this paper, we explore a scenario in which slow evolving conformal field theories (CFTs) offer such an explanation. Building on the recent work on conformal freeze-in (COFI), we focus on a coupling between the Standard Model Hypercharge gauge boson and an anti-symmetric tensor operator in the dark CFT. We present a scenario which dynamically realizes the asymmetric reheating and COFI production. With a detailed study of dark matter production, and taking into account limits on the dark matter (DM) self-interaction, warm DM bound, and constraints from the stellar evolution, we demonstrate that the correct relic abundance can be obtained with reasonable choices of parameters. The model predicts the existence of a dark photon as an emergent composite particle, with a small kinetic mixing also determined by the CFT dynamics, which correlates it with the generation of the mass scale of the dark sector. At the same time, COFI production of dark matter is very different from those freeze-in mediated by the dark photon. This is an example of the physics in which a realistic dark sector model can often be much richer and with unexpected features.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Fractonic coset construction for spontaneously broken translations

We study the homogeneous breaking of spatial translation symmetry concomitantly with the spontaneous breaking of other internal and spacetime symmetries, including dilations. We use the symmetry-breaking pattern as the only input to derive, via the coset construction, general effective field theories for the symmetry-originated modes associated with Goldstone’s theorem, namely the Nambu-Goldstone candidates. Through explicit computations, we show that integrating out the explicit massive Nambu-Goldstone candidates or imposing symmetric constraints, namely the inverse Higgs constraints, to express massive modes in terms of the massless ones leads to physically distinct effective field theories. This sensitivity to the chosen method can be traced back to the homogeneous breaking of translations, the homogeneous aspect of the breaking induces a mixing between internal and spacetime symmetries at the level of the Lie algebra. This, in turn, leads to subtle discussions about the inverse Higgs constraints, in particular that they lead to a loss of generality in our specific examples. The derived general effective field theories also give rise to a broad class of theories exhibiting emergent enhanced shift symmetries, which constrain the mobility of the modes. The latter are referred to as fractonic modes. Published by the American Physical Society 2025

Chavda, Ameya (ORCID:0000000211731605)↗

DOE OSTI2023

On-Chip Batteries as Distributed Energy Sources in Heterogeneous 2.5D/3D Integrated Circuits

Energy efficiency in digital systems faces challenges due to the constraints imposed by small-scale transistors. Moreover, the growing demand for portable consumer electronics necessitates the use of compact energy sources. To address these challenges, heterogeneous 3D IC technology has emerged as a promising solution for the former. Regarding the latter, we propose the concept of distributed batteries within a heterogeneous 3D IC. This approach involves utilizing multiple smaller batteries with different specifications among different modules of 3D ICs. This approach optimizes performance and overcomes limitations associated with both 3D ICs and conventional power delivery methods. Distributed batteries play a vital role in effectively managing the heat generated by energy sources and modules within a 3D IC. Furthermore, they contribute to achieving a uniform distribution of heat throughout the entire structure, which ultimately ensures the optimal performance of the batteries and modules. The simulation results indicate a 40 percent enhancement in achieving a more even distribution of generated heat. Additionally, the proposed distributed battery techniques improve power delivery, enhance reliability, and enable optimized voltage regulation while improving efficiency. In addition to the primary benefits, alternative configurations of the proposed approach can offer extra energy storage capacity and act as efficient electromagnetic shields, resulting in an impressive reduction of external electromagnetic noises by 60 dB.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Wave Prediction using X-Band Radar (Final Summary Report)

Model Predictive Control (MPC) is the best controls framework available to wave energy today. It allows for the maximization of energy yield from a WEC system while respecting various constraints and losses in the system. This type of constrained optimization is a critical capability for the techno-economic optimization of WEC devices and is difficult to do effectively with causal controls frameworks. MPC requires a future prediction of wave excitation forces, requiring wave prediction on a future time horizon of up to 30 seconds. The future horizon required is highly dependent on the WEC and PTO type available. To our knowledge no-one has been able to implement MPC on a WEC device at sea, due to the fact that phase-resolved wave-prediction is not a capability that has been sufficiently developed to date. The key objectives of this project are focused on developing “industry-ready” wave prediction technology building blocks that can be applied to a wide range of different wave energy conversion topologies. Our collaborative work with device developers has demonstrated that the level of improvement attainable for any particular device is heavily dependent on the device and PTO topology chosen. The range of annual average power capture improvements is on the order of 10% to over 100%. However, the important aspect is that we can get within about 10% of theoretical upper limits even when considering errors in the wave prediction and more importantly, we can optimize performance while respecting various constraints such as motion amplitude or peak structural loads. The combination of improved performance while limiting structural loads has a net effect of reducing the levelized cost of energy from these emerging technologies and allows us to design control laws that meet an economic optimum. Efforts under a previous project on controls has focused on developing a set of wave-prediction algorithms that work by leveraging a network of wave sensing measurement buoys that are equipped with real-time telemetry. The present work is focusing primarily on using X-band radar to measure the wave-field around the WEC to predict the future excitation forces on the structure and combining the measurements of these different sources to create improvements in the wave-prediction accuracy.

16 TIDAL AND WAVE POWER↗

DOE OSTI2023

Constraints on simulated past Arctic amplification and lapse rate feedback from observations

The Arctic has warmed more rapidly than the global mean during the past few decades. The lapse rate feedback (LRF) has been identified as being a large contributor to the Arctic amplification (AA) of climate change. This particular feedback arises from the vertically non-uniform warming of the troposphere, which in the Arctic emerges as strong near-surface and muted free-tropospheric warming. Stable stratification and meridional energy transport are two characteristic processes that are evoked as causes for this vertical warming structure. Our aim is to constrain these governing processes by making use of detailed observations in combination with the large climate model ensemble of the sixth Coupled Model Intercomparison Project (CMIP6). We build on the result that CMIP6 models show a large spread in AA and Arctic LRF, which are positively correlated for the historical period of 1951–2014. Thus, we present process-oriented constraints by linking characteristics of the current climate to historical climate simulations. In particular, we compare a large consortium of present-day observations to co-located model data from subsets that show a weak and strong simulated AA and Arctic LRF in the past. Our analyses suggest that the vertical temperature structure of the Arctic boundary layer is more realistically depicted in climate models with weak (w) AA and Arctic LRF (CMIP6/w) in the past. In particular, CMIP6/w models show stronger inversions in the present climate for boreal autumn and winter and over sea ice, which is more consistent with the observations. These results are based on observations from the year-long Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic, long-term measurements at the Utqiagvik site in Alaska, USA, and dropsonde temperature profiling from aircraft campaigns in the Fram Strait. In addition, the atmospheric energy transport from lower latitudes that can further mediate the warming structure in the free troposphere is more realistically represented by CMIP6/w models. In particular, CMIP6/w models systemically simulate a weaker Arctic atmospheric energy transport convergence in the present climate for boreal autumn and winter, which is more consistent with fifth generation reanalysis of the European Centre for Medium-Range Weather Forecasts (ERA5). We further show a positive relationship between the magnitude of the present-day transport convergence and the strength of past AA. With respect to the Arctic LRF, we find links between the changes in transport pathways that drive vertical warming structures and local differences in the LRF. This highlights the mediating influence of advection on the Arctic LRF and motivates deeper studies to explicitly link spatial patterns of Arctic feedbacks to changes in the large-scale circulation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Locality and analyticity of the crossing symmetric dispersion relation

This paper discusses the locality and analyticity of the crossing symmetric dispersion relation (CSDR). Imposing locality constraints on the CSDR gives rise to a local and fully crossing symmetric expansion of scattering amplitudes, dubbed as Feynman block expansion. A general formula is provided for the contact terms that emerge from the expansion. The analyticity domain of the expansion is also derived analogously to the Lehmann-Martin ellipse. Our observation of type-II super-string tree amplitude suggests that the Feynman block expansion has a bigger analyticity domain and better convergence.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Dynamical moment fragmentation in the all-in all-out pyrochlore Nd 2 ⁢Sn 2⁢ O 7

We report single crystal neutron spectroscopy and bulk characterization on hydrothermally grown Nd 2 Sn 2 O 7 , revealing magnetic moment fragmentation embedded within the all-in–all-out ordered state. The spectra reveal a nearly flat band with pinch-point momentum dependence accompanied by dispersive branches that produce half-moon features across multiple Brillouin zones. These defining signatures are captured quantitatively by a minimal dipolar-octupolar spin Hamiltonian, demonstrating excellent agreement between experiment and theory. The higher flat-mode energy helps account for the absence of dynamical interference in prior μSR studies, while the lack of any photon-like excitation imposes strict constraints on the proposed Coulombic antiferromagnet scenario. Furthermore, our results extend moment fragmentation to Nd 2 Sn 2 O 7 and identify it as a clean, tractable platform for quantitative exploration of emergent gauge field physics in frustrated magnets.

DC susceptibility measurements↗

DOE OSTI2021

Exploring a quantum-information-relevant magnonic material: Ultralow damping at low temperature in the organic ferrimagnet V[TCNE]x

Quantum information science and engineering require novel low-loss magnetic materials for magnon-based quantum-coherent operations. The search for low-loss magnetic materials, traditionally driven by applications in microwave electronics near room temperature, has gained additional constraints from the need to operate at cryogenic temperatures for many applications in quantum information science and technology. Whereas yttrium iron garnet (YIG) has been the material of choice for decades, the emergence of molecule-based materials with robust magnetism and ultra-low damping has opened new avenues for exploration. Specifically, thin films of vanadium tetracyanoethylene (V[TCNE]x) can be patterned into the multiple, connected structures needed for hybrid quantum elements and have shown room-temperature Gilbert damping (α = 4 × 10−5) that rivals the intrinsic (bulk) damping otherwise seen only in highly polished YIG spheres (far more challenging to integrate into arrays). Here, the authors present a comprehensive and systematic study of the low-temperature magnetization dynamics for V[TCNE]x thin films, with implications for their application in quantum systems. These studies reveal a temperature-driven, strain-dependent magnetic anisotropy that compensates the thin-film shape anisotropy and the recovery of a magnetic resonance linewidth at 5 K that is comparable to room-temperature values (roughly 2 G at 9.4 GHz). The authors can account for these variations of the V[TCNE]x linewidth within the context of scattering from very dilute paramagnetic impurities and anticipate additional linewidth narrowing as the temperature is further reduced.

Yusuf, H. (ORCID:0000000194627928)↗

DOE OSTI2022

Theory, phenomenology, and experimental avenues for dark showers: a Snowmass 2021 report

In this work, we consider the case of a strongly coupled dark/hidden sector, which extends the Standard Model (SM) by adding an additional non-Abelian gauge group. These extensions generally contain matter fields, much like the SM quarks, and gauge fields similar to the SM gluons. We focus on the exploration of such sectors where the dark particles are produced at the LHC through a portal and undergo rapid hadronization within the dark sector before decaying back, at least in part and potentially with sizeable lifetimes, to SM particles, giving a range of possibly spectacular signatures such as emerging or semi-visible jets. Other, non-QCD-like scenarios leading to soft unclustered energy patterns or glueballs are also discussed. After a review of the theory, existing benchmarks and constraints, this work addresses how to build consistent benchmarks from the underlying physical parameters and present new developments for the PYTHIA Hidden Valley module, along with jet substructure studies. Finally, a series of improved search strategies is presented in order to pave the way for a better exploration of the dark showers at the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Analyzing School Bus Electrification in Richmond, Virginia

School buses are an essential component of the transportation infrastructure, serving as a lifeline for students across the globe. However, the widespread use of diesel school buses has raised concerns about the health impact on millions of students exposed to harmful emissions daily. Recognizing this issue, school districts worldwide are urgently seeking cleaner energy alternatives. Electric school buses emerge as an environmentally friendly and sustainable option, fostering a healthier environment for both students and communities. However, school bus electrification faces the challenges of high upfront cost, cumbersome charging management, and constraints from power grids. To help school bus operators address those challenges, this study presents a data-driven analysis for school bus electrification. This study considered a real-world school bus system in Richmond, VA, and developed a mathematical programming model to analyze the system design, charging strategies, and charging load profiles for the electrification scenario. The study evaluated different charging strategies based on model outcomes, aiming to optimize efficiency and effectiveness. Ultimately, this research generated electric school bus charging demand profiles under various scenarios, shedding light on the feasibility and implications of transitioning to electric-powered school buses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

Micro-architected material design for mechanical response

Rapid advances in additive manufacturing (AM) have enabled the creation of micro-architected materials—also known as mechanical metamaterials—with unprecedented control over fine-scale geometries and arrangements of multiple material constituents. These “materials” can achieve unique and extraordinary effective mechanical properties through their complex architectures rather than composition alone. A key challenge is to design for these bespoke effective mechanical responses within the constraints of available AM techniques (i.e., given a set of desired effective properties), identify a (often nonunique) micro-architecture and selection of material constituents that achieves them. Two main strategies have emerged. Gradient-based methods use sensitivity analysis to iteratively refine candidate designs, while data-driven methods learn micro-architecture-constituent relationships from existing examples to propose new designs. This article reviews these design approaches for micro-architected materials with tailored mechanical responses that can be fabricated by AM as well as their applications.

Spadaccini, Christopher M [Lawrence Livermore Nati↗

DOE OSTI2024

Understanding Process–Structure Relationships during Lamination of Halide Perovskite Interfaces

Fabrication of halide perovskite (HP) solar cells typically involves the sequential deposition of multiple layers to create a device stack, which is limited by the thermal and chemical incompatibility of top contact layers with the underlying HP semiconductor. One emerging strategy to overcome these restrictions on material selection and processing conditions is lamination, where two half-stacks are independently processed and then diffusion bonded to complete the device. Lamination reduces the processing constraints on the top side of the solar cell to allow new device designs, expanded use of deposition methods, and self-encapsulation of devices. While laminated perovskite solar cells with high efficiencies and novel interlayer combinations have been demonstrated, there is a limited understanding of how the lamination process parameters affect the diffusion-bond quality and material properties of the resulting HP layer. In this study, we systematically vary temperature, pressure, and time during lamination and quantify the resulting impacts on bonded area, grain domain size, and photoluminescence. A design of experiments is performed, and statistical analysis of the experimental results is used to quantitatively evaluate the resulting process–structure–property relationships. The lamination temperature is found to be the key parameter controlling these properties. Furthermore, a temperature of 150 °C enables successful bonding over 95% of the substrate area and also results in increases in apparent grain domain size and photoluminescence intensity. Based on these insights, the lamination temperature of functional perovskite solar cell devices is varied, demonstrating the importance of the resulting bond quality on device performance metrics.

14 SOLAR ENERGY↗

DOE OSTI2025

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↗

DOE OSTI2023

Classical and quantum compression for edge computing: the ubiquitous data dimensionality reduction

Edge computing aims to address the challenges associated with communicating and transferring large amounts of data generated remotely to a data center in a timely and efficient manner. A central pillar of edge computing is local (i.e., at- or near-source) data processing capability so that data transfer to a data center for processing can be minimized. Data compression at the edge is therefore a natural component of edge workflows. Here we present a survey of data compression algorithms with a focus on edge computing. Not all compression algorithms can accommodate the data type heterogeneity, tight processing and communication time constraints, or energy efficiency requirement characteristics of edge computing. We discuss specific examples of compression algorithms that are being explored in the context of edge computing. We end our review with a brief survey of emerging quantum compression techniques that are of importance in quantum information processing, including the proposed concept of quantum edge computing.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Position Papers for the ASCR Workshop on Reimagining Codesign

On behalf of the Advanced Scientific Computing Research (ASCR) program in the US Department of Energy (DOE) Office of Science, we are organizing a Workshop on Reimagining Codesign (ReCoDe). Codesign is the process of jointly designing interoperating components of a computing system—in particular: applications, algorithms, system software, programming models, and the hardware on which they run. The goal is to maximize the overall performance, efficiency, and other desirable qualities of the system as a whole. Codesign is a standard methodology in the embedded-systems community, where space, power, and cost constraints are commonly pitted against execution speed for a tightly constrained feature set. Over the last decade, the DOE has invested in codesign efforts to foster the development of exascale computing systems for broad classes of scientific and engineering applications. The ReCoDe workshop hopes to explore how scientific applications of interest to the DOE can be accelerated through close interactions with hardware designers and software-stack developers, in which all components adapt to each other’s requirements and constraints. We want to answer the question of what are the key tools and methodologies for accomplishing codesign in today’s computing landscape, and what will be the highest impact targets for meeting DOE’s emerging mission requirements. This workshop aims to bring together DOE, industry, and academia to identify opportunities to build on past codesign successes and identify new areas that are either emerging or that may need reimagining for the future. We want to continue to find opportunities that can be pursued as a joint effort and continue to break down the traditional customer/vendor dichotomy with true partnerships. From this work, DOE will benefit from increased application performance relative to what stock hardware or existing general-purpose roadmaps can provide, and vendors will benefit from expanding their hardware’s capabilities to address needs they might have not otherwise anticipated and thereby create more widespread interest in their products. The workshop will be structured around a set of breakout sessions, with every attendee expected to participate actively in the discussions. Afterward, workshop attendees—from DOE, industry, and academia—will produce a report for ASCR that summarizes the findings made during the workshop.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)

The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environments and operational constraints. Harnessing this data for scientific discovery demands real-time inference and decision-making, intelligent data reduction, and efficient processing architectures beyond current capabilities. Crucial to the success of this experimental paradigm are several emerging technologies, such as artificial intelligence and machine learning (AI/ML) and silicon microelectronics, and the advent of quantum algorithms and processing. Their intersection includes areas of research such as low-power and low-latency devices for edge computing, heterogeneous accelerator systems, reconfigurable hardware, novel codesign and synthesis strategies, readout for cryogenic or high-radiation environments, and analog computing. This white paper presents a community-driven vision to identify and prioritize research and development opportunities in hardware-based ML systems and corresponding physics applications, contributing towards a successful transition to the new data frontier of fundamental science.

Gonski, Julia [SLAC]↗