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At least 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The physics potential of a reactor neutrino experiment with Skipper CCDs: Measuring the weak mixing angle

We analyze in detail the physics potential of an experiment like the one recently proposed by the vIOLETA collaboration: a kilogram-scale Skipper CCD detector deployed 12 meters away from a commercial nuclear reactor core. This experiment would be able to detect coherent elastic neutrino nucleus scattering from reactor neutrinos, capitalizing on the exceptionally low ionization energy threshold of Skipper CCDs. To estimate the physics reach, we elect the measurement of the weak mixing angle as a case study. We choose a realistic benchmark experimental setup and perform variations on this benchmark to understand the role of quenching factor and its systematic uncertainties, background rate and spectral shape, total exposure, and reactor antineutrino flux uncertainty. We take full advantage of the reactor flux measurement of the Daya Bay collaboration to perform a data driven analysis which is, up to a certain extent, independent of the theoretical un- certainties on the reactor antineutrino flux. We show that, under reasonable assumptions, this experimental setup may provide a competitive measurement of the weak mixing angle at few MeV scale with neutrino-nucleus scattering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Moduli stabilisation and the statistics of axion physics in the landscape

String theory realisations of the QCD axion are often said to belong to the anthropic window where the decay constant is around the GUT scale and the initial misalignment angle has to be tuned close to zero. In this paper we revisit this statement by studying the statistics of axion physics in the string landscape. We take moduli stabilisation properly into account since the stabilisation of the saxions is crucial to determine the physical properties of the corresponding axionic partners. We focus on the model-independent case of closed string axions in type IIB flux compactifications and find that their decay constants and mass spectrum feature a logarithmic, instead of a power-law, distribution. In the regime where the effective field theory is under control, most of these closed string axions are ultra-light axion-like particles, while axions associated to blow-up modes can naturally play the role of the QCD axion. Hence, the number of type IIB flux vacua with a closed string QCD axion with an intermediate scale decay constant and a natural value of the misalignment angle is only logarithmically suppressed. In a recent paper we found that this correlates also with a logarithmic distribution of the supersymmetry breaking scale, providing the intriguing indication that most, if not all, of the phenomenologically interesting quantities in the string landscape might feature a logarithmic distribution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Learning physics at future $e^–e^+$ colliders with machine

Information deformation and loss in jet clustering are one of the major limitations for precisely measuring hadronic events at future $e^–e^+$ colliders. Because of their dominance in data, the measurements of such events are crucial for advancing the precision frontier of Higgs and electroweak physics in the next decades. We show that this difficulty can be well-addressed by synergizing the event-level information into the data analysis, with the techniques of deep neutral network. In relation to this, we introduce a CMB-like observable scheme, where the event-level kinematics is encoded as Fox-Wolfram (FW) moments at leading order and multi-spectra of spherical harmonics at higher orders. Then we develop a series of jet-level (w/ and w/o the FW moments) and event-level classifiers, and analyze their sensitivity performance comparatively with two-jet and four-jet events. As an application, we analyze measuring Higgs decay width at $e^–e^+$ colliders with the data of 5ab –1 @240GeV. The precision obtained is significantly better than the baseline ones presented in documents. We expect this strategy to be applied to many other hadronic- event measurements at future $e^–e^+$ colliders, and to open a new angle for evaluating their physics capability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

New physics in multi-electron muon decays

Abstract We study the exotic muon decays with five charged tracks in the final state. First, we investigate the Standard Model rate forμ + → 3e + 2e − 2ν($$ \mathcal{B} $$ B = 4.0 × 10 −10 ) and find that the Mu3e experiment should have tens to hundreds of signal events per 10 15 μ + decays, depending on the signal selection strategy. We then turn to a neutrinolessμ + → 3e + 2e − decay that may arise in new-physics models with lepton-flavor-violating effective operators involving a dark Higgsh d . Following its production inμ + →e + h d decays, the dark Higgs can undergo a decay cascade to twoe + e − pairs through two dark photons,h d → γ d γ d →2(e + e − ). We show that aμ + →3e + 2e − search at the Mu3e experiment, with potential sensitivity to the branching ratio at the$$ \mathcal{O} $$ O (10 −12 ) level or below, can explore new regions of parameter space and new physics scales as high as Λ ∼ 10 15 GeV.

Physics↗
DOE OSTI2023

Wrinkles in the Froggatt-Nielsen mechanism and flavorful new physics

Abstract When the Froggatt-Nielsen mechanism is used to explain the Standard Model flavor hierarchy, new physics couplings are also determined by the horizontal symmetry. However, additional symmetries or dynamics in the UV can sometimes lead to a departure from this naïve scaling for the new physics couplings. We show that an effective way to keep track of these changes is by using the new spurions of the U(3) 5 global flavor symmetry, where we parameterize extra suppression or enhancement factors, referred to aswrinkles, using the same power counting parameter as in the original Froggatt-Nielsen model. As a concrete realization, we consider two flavor spurions of theS 1 leptoquark, and demonstrate that wrinkles can be used to make an enhanced value of$$ \textrm{BR}\left({B}^{+}\to {K}^{+}\nu \overline{\nu}\right) $$ BR B + → K + ν ν ¯ consistent with other flavor observables. We also present example UV models that realize wrinkles, and comment on choosing consistent charges in ordinary Froggatt-Nielsen models without the typical monotonicity condition.

Physics↗
DOE OSTI2016

Search for new physics in final states with two opposite-sign, same-flavor leptons, jets, and missing transverse momentum in pp collisions at sqrt(s) = 13 TeV

A search is presented for physics beyond the standard model in final states with two opposite-sign, same-flavor leptons, jets, and missing transverse momentum. The data sample corresponds to an integrated luminosity of 2.3 fb$^{−1}$ of proton-proton collisions at $ \sqrt{s}=13 $ TeV collected with the CMS detector at the LHC in 2015. The analysis uses the invariant mass of the lepton pair, searching for a kinematic edge or a resonant-like excess compatible with the Z boson mass. Both search modes use several event categories in order to increase the sensitivity to new physics. These categories are based on the rapidity of the leptons, the multiplicity of jets and b jets, the scalar sum of jet transverse momenta, and missing transverse momentum. The observations in all signal regions are consistent with the expectations from the standard model, and the results are interpreted in the context of simplified models of supersymmetry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Learning from Higgs physics at future Higgs factories

Future Higgs factories can reach impressive precision on Higgs property measurements. In this paper, instead of conventional focus of Higgs precision in certain interaction bases, we explored its sensitivity to new physics models at the electron-positron colliders. In particular, we studied two categories of new physics models, Standard Model (SM) with a real scalar singlet extension, and Two Higgs Double Model (2HDM) as examples of weakly-interacting models, Minimal Composite Higgs Model (MCHM) and three typical patterns of the more general operator counting for strong interacting models as examples of strong dynamics. We performed a global fit to various Higgs search channels to obtain the 95% C.L. constraints on the model parameter space. In the SM with a singlet extension, we obtained the limits on the singlet-doublet mixing angle sin(theta), as well as the more general Wilson coefficients of the induced higher dimensional operators. In the 2HDM, we analyzed tree level effects in tan(beta) vs. cos(beta-alpha) plane, as well as the one-loop contributions from the heavy Higgs bosons in the alignment limit to obtain the constraints on heavy Higgs masses for different types of 2HDM. In strong dynamics models, we obtained lower limits on the strong dynamics scale. In addition, once deviations of Higgs couplings are observed, they can be used to distinguish different models. Here, we also compared the sensitivity of various future Higgs factories, namely Circular Electron Positron Collider (CEPC), Future Circular Collider (FCC)-ee and International Linear Collider (ILC).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Physics-informed neural networks (PINNs) for fluid mechanics: a review

Despite the significant progress over the last 50 years in simulating flow problems using numerical discretization of the Navier–Stokes equations (NSE), we still cannot incorporate seamlessly noisy data into existing algorithms, mesh-generation is complex, and we cannot tackle high-dimensional problems governed by parametrized NSE. Moreover, solving inverse flow problems is often prohibitively expensive and requires complex and expensive formulations and new computer codes. Here, we review flow physics-informed learning, integrating seamlessly data and mathematical models, and implement them using physics-informed neural networks (PINNs). Here, we demonstrate the effectiveness of PINNs for inverse problems related to three-dimensional wake flows, supersonic flows, and biomedical flows.

42 ENGINEERING↗
DOE OSTI2022

Detection of early-universe gravitational-wave signatures and fundamental physics

Detection of a gravitational-wave signal of non-astrophysical origin would be a landmark discovery, potentially providing a significant clue to some of our most basic, big-picture scientific questions about the Universe. In this white paper, we survey the leading early-Universe mechanisms that may produce a detectable signal—including inflation, phase transitions, topological defects, as well as primordial black holes—and highlight the connections to fundamental physics. We review the complementarity with collider searches for new physics, and multimessenger probes of the large-scale structure of the Universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Chitosan Depolymerization and Nanochitosan Production Using a Single Physical Procedure

The many applications of the chitosan biopolymers in the areas of nanotechnology and nanomaterials have led to the need to develop novel techniques suitable for the production of nanochitosan. At present these typically involve the use of chemical agents to form chitosan nanoparticles. Physical, chemical, and enzymatic methods have been described for the depolymerizatiton of chitosan. In this work, evaluation was made of the efficiency of a combination of physical methods, including milling of the raw material and drying of the final chitosan, in order to obtain nanochitosan with low molar mass. The results revealed the effectiveness of the combination of milling the raw material under controlled conditions for 4.5 h and drying of the chitosan by thermal shock, which provided depolymerization of up to 10× and resulted in chitosan with M{sub v} less than 21 kDa and hydrodynamic diameter below 30 nm.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Physics of Superconducting Transition Temperatures

While superconductivity is a fascinating phenomenon with many remarkable qualitative features that are widely discussed, the practical issue of what determines the superconducting transition temperature, $T_c$, is often downplayed as being a "microscopic detail." However, my friend, Ted Geballe, has relentlessly focussed on the physics of $T_c$, so in honor of his first century, I discuss some of the general physical considerations that govern $T_c$, both in "conventional" and ''unconventional" superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Stochastic Spatial Models in Ecology: A Statistical Physics Approach

Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D=2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Statistical Physics Approach to Thermophoresis of Colloids

Brownian colloidal particles dispersed in a fluid with a temperature gradient experience a driving force which produces a large biased steady density profile. This phenomenon, named thermophoresis, is quantified by the Soret coefficient S{sub T}. This problem is studied here within the Fokker–Planck formalism. Using the experimental observation of S{sub T} it is possible to extract relevant analytical information about a temperature dependent nonequilibrium effective potential which can produce the thermophoresis force. It will be presented here a statistical physics derivation of this effective potential in terms of some physical parameters. Experimental data are analyzed within this theoretical scenario.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Physics-Informed Neural Networks for PDE-Constrained Optimization and Control

The goal of optimal control is to determine a sequence of inputs for maximizing or minimizing a given performance criterion subject to the dynamics and constraints of the system under observation. This work introduces Control Physics-Informed Neural Networks (PINNs), which simultaneously learn both the system states and the optimal control signal in a single-stage framework that leverages the system’s underlying physical laws. While prior approaches often follow a two-stage process-modeling, the system first and then devising its control—the presented novel framework embeds the necessary optimality conditions directly into the network architecture and loss function. We demonstrate the effectiveness of the novel methodology by solving various open-loop optimal control problems governed by analytical, one-dimensional, and two-dimensional partial differential equations (PDEs).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

From PINNs to PIKANs: recent advances in physics-informed machine learning

Physics-Informed Neural Networks (PINNs) have emerged as a key tool in Scientific Machine Learning since their introduction in 2017, enabling the efficient solution of ordinary and partial differential equations using sparse measurements. Over the past few years, significant advancements have been made in the training and optimization of PINNs, covering aspects such as network architectures, adaptive refinement, domain decomposition, and the use of adaptive weights and activation functions. A notable recent development is the Physics-Informed Kolmogorov-Arnold Networks (PIKANS), which leverage a representation model originally proposed by Kolmogorov in 1957, offering a promising alternative to traditional PINNs. In this review, we provide a comprehensive overview of the latest advancements in PINNs, focusing on improvements in network design, feature expansion, optimization techniques, uncertainty quantification, and theoretical insights. We also survey key applications across a range of fields, including biomedicine, fluid and solid mechanics, geophysics, dynamical systems, heat transfer, chemical engineering, and beyond. Lastly, we review computational frameworks and software tools developed by both academia and industry to support PINN research and applications.

Kolmogorov-Arnold networks↗
DOE OSTI2026

E-PINNs: Epistemic Physics-Informed Neural Networks

Physics-informed neural networks (PINNs) have demonstrated promise as a framework for solving forward and inverse problems involving partial differential equations. Despite recent progress in the field, it remains challenging to quantify uncertainty in these networks. While techniques such as Bayesian PINNs (B-PINNs) provide a principled approach to capturing epistemic uncertainty through Bayesian inference, they can be computationally expensive for large-scale applications. In this work, we propose Epistemic Physics-Informed Neural Networks (E-PINNs), a framework that uses a small network, the epinet, to efficiently quantify epistemic uncertainty in PINNs. The proposed approach works as an add-on to existing, pre-trained PINNs with a small computational overhead. We demonstrate the applicability of the proposed framework in various test cases and compare the results with B-PINNs using Hamiltonian Monte Carlo (HMC) posterior estimation and dropout-equipped PINNs (Dropout-PINNs). In our experiments, E-PINNs achieve calibrated coverage with competitive sharpness at substantially lower cost. We demonstrate that when B-PINNs produce narrower bands, they under-cover in our tests. E-PINNs also show better calibration than Dropout-PINNs in these examples, indicating a favorable accuracy-efficiency trade-off.

AI for Science↗
DOE OSTI2020

Lattice physics calculations using the embedded self-shielding method in polaris, Part II: Benchmark assessment

Polaris is a 2D multigroup lattice physics capability in the SCALE code system used for the analysis of light water reactor fuel designs. In this work, verification and validation results of Polaris in SCALE 6.2 are presented. The SCALE/KENO continuous-energy Monte Carlo code is used as a reference to compare the results of more than 2,000 combinations of pressurized water reactor and boiling water reactor lattice designs and state points. Radiochemical assay measurements were also used to assess the accuracy of depletion calculations. Results show that Polaris, with ENDF/B-VII.1 cross section library, produces accurate lattice physics data for core simulators.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Correlation energy for elementary bosons: Physics of the singularity

We propose a compact perturbative approach that reveals the physical origin of the singularity occurring in the density dependence of correlation energy: like fermions, elementary bosons have a singular correlation energy which comes from the accumulation, through Feynman “bubble” diagrams, of the same non-zero momentum transfer excitations from the free particle ground state, that is, the Fermi sea for fermions and the Bose–Einstein condensate for bosons. This understanding paves the way toward deriving the correlation energy of composite bosons like atomic dimers and semiconductor excitons, by suggesting Shiva diagrams that have similarity with Feynman “bubble” diagrams, the previous elementary boson approaches, which hide this physics, being inappropriate to do so.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗