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At least 91 records · Page 5

Physics-Informed Deep Neural Network Method for Limited Observability State Estimation

The precise knowledge regarding the state of the power grid is important in order to ensure optimal and reliable grid operation. Specifically, knowing the state of the distribution grid becomes increasingly important as more renewable energy sources are connected directly into the distribution network, increasing the fluctuations of the injected power. In this paper, we consider the case when the distribution grid becomes partially observable, due to for example cyber attacks, and the state estimation problem is under-determined. We present a new methodology that leverages a deep neural network (DNN) to estimate the grid state. The standard DNN training method is modified to explicitly incorporate the physical information of the grid topology and line/shunt admittance. We show that our method leads to a superior accuracy of the estimation when compared to the case when no physical information is provided. Finally, we compare the performance of our method to the standard state estimation approach, which is based on the weighted least squares with pseudo-measurements, and show that our method performs significantly better with respect to the estimation accuracy.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Forward Physics Facility: Sites, Experiments, and Physics Potential

The Forward Physics Facility (FPF) is a proposal to create a cavern with the space and infrastructure to support a suite of far-forward experiments at the Large Hadron Collider during the High Luminosity era. Located along the beam collision axis and shielded from the interaction point by at least 100 m of concrete and rock, the FPF will house experiments that will detect particles outside the acceptance of the existing large LHC experiments and will observe rare and exotic processes in an extremely low-background environment. In this work, we summarize the current status of plans for the FPF, including recent progress in civil engineering in identifying promising sites for the FPF; the FPF experiments currently envisioned to realize the FPF’s physics potential; and the many Standard Model and new physics topics that will be advanced by the FPF, including searches for long-lived particles, probes of dark matter and dark sectors, high-statistics studies of TeV neutrinos of all three flavors, aspects of perturbative and non-perturbative QCD, and high-energy astroparticle physics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Impact of baryonic physics on intrinsic alignments

We explore the effects of specific assumptions in the subgrid models of star formation and stellar and AGN feedback on intrinsic alignments of galaxies in cosmological simulations of "MassiveBlack-II" family. Using smaller volume simulations, we explored the parameter space of the subgrid star formation and feedback model and found remarkable robustness of the observable statistical measures to the details of subgrid physics. The one observational probe most sensitive to modeling details is the distribution of misalignment angles. We hypothesize that the amount of angular momentum carried away by the galactic wind is the primary physical quantity that controls the orientation of the stellar distribution. Finally, our results are also consistent with a similar study by the EAGLE simulation team.

79 ASTRONOMY AND ASTROPHYSICS↗

Physics Briefing Book: Input for the 2026 update of the European Strategy for Particle Physics

The European Strategy for Particle Physics (ESPP) reflects the vision and presents concrete plans of the European particle physics community for advancing human knowledge in fundamental physics. The ESPP is updated every five-to-six years through a community-driven process. It commences with the submission of specific proposals and other input from the community at large, outlining projects envisioned for the near-, mid-, and long-term future. All submitted contributions are evaluated by the Physics Preparatory Group (PPG), and a preliminary analysis is presented at a Symposium meant to foster a broad community discussion on the scientific value and feasibility of the various ideas proposed. The outcomes of the analysis and the deliberations at the Symposium are synthesized in the current Briefing Book, which provides an important input in the deliberations of the Strategy recommendations by the European Strategy Group (ESG)

Gouskos, Loukas [Brown University]↗

Physics in perspective. Volume 2, part A: The core subfields of physics

Panel reports to the Survey Committee are presented to provide detailed technical background and documentation for committee findings, and to indicate the vitality and strength of the subfields of physics. Included are the core subfields of acoustics, optics, condensed matter, plasmas and fluids, atomic molecular and electron physics, nuclear physics, and elementary particle physics.

Source record↗

Physics through the 1990s: Gravitation, cosmology and cosmic-ray physics

The volume contains recommendations for space-and ground-based programs in gravitational physics, cosmology, and cosmic-ray physics. The section on gravitation examines current and planned experimental tests of general relativity; the theory behind, and search for, gravitational waves, including sensitive laser-interferometric tests and other observations; and advances in gravitation theory (for example, incorporating quantum effects). The section on cosmology deals with the big-bang model, the standard model from elementary-particle theory, the inflationary model of the Universe. Computational needs are presented for both gravitation and cosmology. Finally, cosmic-ray physics theory (nucleosynthesis, acceleration models, high-energy physics) and experiment (ground and spaceborne detectors) are discussed.

Source record↗

Design methodologies and engineering applications for ecosystem biomimicry: an interdisciplinary review spanning cyber, physical, and cyber-physical systems

Abstract Ecosystem biomimicry is a promising pathway for sustainable development. However, while typical form- and process-level biomimicry is prevalent, system-level ecosystem biomimicry remains a nascent practice in numerous engineering fields. This critical review takes an interdisciplinary approach to synthesize trends across case studies, evaluate design methodologies, and identify future opportunities when applying ecosystem biomimicry to engineering practices, including cyber systems (CS), physical systems (PS), and cyber-physical systems (CPS). After systematically sourcing publications from major databases, the papers were first analyzed at a meta level for their bibliographic context and for statistical correlations among categorical variables. Then, we investigated deeper into the engineering applications and design methodologies. Results indicate that CPS most frequently mimic organisms and ecosystems, while CS and PS frequently mimic populations-communities and molecules-tissues-organ systems, respectively (statistically highly significant). An indirect approach is most often used for mimicry at organizational levels from populations to ecosystems, while a direct approach frequently suits levels from molecules to organisms (highly significant). Dominant themes across engineering applications include symbiotic organism search algorithms for CS and ecological network analysis for CPS, while PS are highly diverse. For design methodologies, this work summarizes and details ten well-documented biomimetic process models among literature, which addresses an outdated concern for a lack of systematic methods for ecosystem biomimicry. In addition to the Biomimetics Standard ISO 18458, these methods include the Natural Step and Techno-Ecological Synergy framework, among others. Further, the analyses revealed future opportunities from less utilized design methods (e.g. interdisciplinary teams tackling indirect, ecosystem-level projects) to well-established engineering concepts ready for technological advancement (e.g. implementing membrane computing for physical applications). For future studies, this review provides a comprehensive reference for ecosystem biomimetic design practices and application opportunities across multiple engineering domains.

42 ENGINEERING↗

Separable physics-informed DeepONet: Breaking the curse of dimensionality in physics-informed machine learning

The deep operator network (DeepONet) has shown remarkable potential in solving partial differential equations (PDEs) by mapping between infinite-dimensional function spaces using labeled datasets. However, in scenarios lacking labeled data, the physics-informed DeepONet (PI-DeepONet) approach, which utilizes the residual loss of the governing PDE to optimize the network parameters, faces significant computational challenges, particularly due to the curse of dimensionality. This limitation has hindered its application to high-dimensional problems, making even standard 3D spatial with 1D temporal problems computationally prohibitive. Additionally, the computational requirement increases exponentially with the discretization density of the domain. Here, to address these challenges and enhance scalability for high-dimensional PDEs, we introduce the Separable physics-informed DeepONet (Sep-PI-DeepONet). This framework employs a factorization technique, utilizing sub-networks for individual one-dimensional coordinates, thereby reducing the number of forward passes and the size of the Jacobian matrix required for gradient computations. By incorporating forward-mode automatic differentiation (AD), we further optimize computational efficiency, achieving linear scaling of computational cost with discretization density and dimensionality, making our approach highly suitable for high-dimensional PDEs. We demonstrate the effectiveness of Sep-PI-DeepONet through three benchmark PDE models: the viscous Burgers’ equation, Biot’s consolidation theory, and a parameterized heat equation. Our framework maintains accuracy comparable to the conventional PI-DeepONet while reducing training time by two orders of magnitude. Notably, for the heat equation solved as a 4D problem, the conventional PI-DeepONet was computationally infeasible (estimated 289.35 h), while the Sep-PI-DeepONet completed training in just 2.5 h. These results underscore the potential of Sep-PI-DeepONet in efficiently solving complex, high-dimensional PDEs, marking a significant advancement in physics-informed machine learning.

Neural operator↗

New Physics Agnostic Selections For New Physics Searches

We discuss a model-independent strategy for boosting new physics searches with the help of an unsupervised anomaly detection algorithm. Prior to a search, each input event is preprocessed by the algorithm - a variational autoencoder (VAE). Based on the loss assigned to each event, input data can be split into a background control sample and a signal enriched sample. Following this strategy, one can enhance the sensitivity to new physics with no assumption on the underlying new physics signature. Our results show that a typical BSM search on the signal enriched group is more sensitive than an equivalent search on the original dataset.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Linking the micro and macro: L-H transition dynamics and threshold physics

The links between the microscopic dynamics and macroscopic threshold physics of the L → H transition are elucidated. Emphasis is placed on understanding the physics of power threshold scalings, and especially on understanding the minimum in the power threshold as a function of density P{sub thr} (n). By extending a numerical 1D model to evolve both electron and ion temperatures, including collisional coupling, we find that the decrease in P{sub thr} (n) along the low-density branch is due to the combination of an increase in collisional electron-to-ion energy transfer and an increase in the heating fraction coupled to the ions. Both processes strengthen the edge diamagnetic electric field needed to lock in the mean electric field shear for the L→H transition. The increase in P{sub thr} (n) along the high-density branch is due to the increase with ion collisionality of damping of turbulence-driven shear flows. Turbulence driven shear flows are needed to trigger the transition by extracting energy from the turbulence. Thus, we identify the critical transition physics components of the separatrix ion heat flux and the zonal flow excitation. The model reveals a power threshold minimum in density scans as a crossover between the threshold decrease supported by an increase in heat fraction received by ions (directly or indirectly, from electrons) and a threshold increase, supported by the rise in shear flow damping. The electron/ion heating mix emerges as important to the transition, in that it, together with electron-ion coupling, regulates the edge diamagnetic electric field shear. The importance of possible collisionless electron-ion heat transfer processes is explained.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Implementation multi representation and oral communication skills in Department of Physics Education on Elementary Physics II

The ability of multi representation has been widely studied, but there has been no implementation through a model of learning. This study aimed to determine the ability of the students multi representation, relationships multi representation capabilities and oral communication skills, as well as the application of the relations between the two capabilities through learning model Presentatif Based on Multi representation (PBM) in solving optical geometric (Elementary Physics II). A concurrent mixed methods research methods with qualitative–quantitative weights. Means of collecting data in the form of the pre-test and post-test with essay form, observation sheets oral communication skills, and assessment of learning by observation sheet PBM–learning models all have a high degree of respectively validity category is 3.91; 4.22; 4.13; 3.88. Test reliability with Alpha Cronbach technique, reliability coefficient of 0.494. The students are department of Physics Education Unnes as a research subject. Sequence multi representation tendency of students from high to low in sequence, representation of M, D, G, V; whereas the order of accuracy, the group representation V, D, G, M. Relationship multi representation ability and oral communication skills, comparable/proportional. Implementation conjunction generate grounded theory. This study should be applied to the physics of matter, or any other university for comparison.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Les Houches 2017: Physics at TeV Colliders New Physics Working Group Report

We present the activities of the `New Physics' working group for the `Physics at TeV Colliders' workshop (Les Houches, France, 5--23 June, 2017). Our report includes new physics studies connected with the Higgs boson and its properties, direct search strategies, reinterpretation of the LHC results in the building of viable models and new computational tool developments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Sea quarks contribution to the nucleon magnetic moment and charge radius at the physical point

We report a comprehensive analysis of the light and strange disconnected-sea quarks contribution to the nucleon magnetic moment, charge radius, and the electric and magnetic form factors. The lattice QCD calculation includes ensembles across several lattice volumes and lattice spacings with one of the ensembles at the physical pion mass. We adopt a model-independent extrapolation of the nucleon magnetic moment and the charge radius. We have performed a simultaneous chiral, infinite volume, and continuum extrapolation in a global fit to calculate results in the continuum limit. We find that the combined light and strange disconnected-sea quarks contribution to the nucleon magnetic moment is μ M (DI) = –0.022(11)(09)μ N and to the nucleon mean square charge radius is ⟨r 2 ⟩ E (DI) = –0.019 (05)(05) fm 2 which is about 1/3 of the difference between the ⟨r$^{2}_{p}$⟩ E of electron-proton scattering and that of a muonic atom and so cannot be ignored in obtaining the proton charge radius in the lattice QCD calculation. Here, the most important outcome of this lattice QCD calculation is that while the combined light-sea and strange quarks contribution to the nucleon magnetic moment is small at about 1%, a negative 2.5(9)% contribution to the proton mean square charge radius and a relatively larger positive 16.3(6.1)% contribution to the neutron mean square charge radius come from the sea quarks in the nucleon. For the first time, by performing global fits, we also give predictions of the light and strange disconnected-sea quarks contributions to the nucleon electric and magnetic form factors at the physical point and in the continuum and infinite volume limits in the momentum transfer range of 0 ≤ Q 2 ≤ 0.5 GeV 2 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Impact of GW170817 for the nuclear physics of the EOS and the r-process

The recent LIGO/Virgo detection of gravitational radiation from GW170817 bears the clear signature of a binary neutron star merger and has validated a number of theoretical predictions. High-energy radiation in the form of a short gamma-ray burst was observed 1.7 s following the merger, and an extended optical/infrared afterglow lasting weeks was observed by dozens of observatories. Short gamma-ray bursts had been thought to be produced by mergers, and the afterglow is the predicted signal of radioactive decays from decompressing neutron-rich matter catastrophically ejected from the merging stars. The afterglow provided solid evidence that neutron star mergers are a major, if not primary, source of r-process nuclei, that half of all nuclei heavier than iron formed from the rapid capture of neutrons. Although this idea was proposed nearly 45 years ago, it was largely ignored in favor of a supernova mechanism. Over the last decade, however, evidence has been accumulating that supernovae are not the primary r-process source. GW170817 may have finally settled this question, which has been one of the thorniest problems in nuclear physics and astrophysics. This article presents my personal perspective of this paradigm shift.

79 ASTRONOMY AND ASTROPHYSICS↗

An assessment of coupling algorithms for nuclear reactor core physics simulations

This paper evaluates the performance of multiphysics coupling algorithms applied to a light water nuclear reactor core simulation. The simulation couples the k-eigenvalue form of the neutron transport equation with heat conduction and subchannel flow equations. We compare Picard iteration (block Gauss–Seidel) to Anderson acceleration and multiple variants of preconditioned Jacobian-free Newton–Krylov (JFNK). The performance of the methods are evaluated over a range of energy group structures and core power levels. A novel physics-based approximation to a Jacobian-vector product has been developed to mitigate the impact of expensive on-line cross section processing steps. Numerical simulations demonstrating the efficiency of JFNK and Anderson acceleration relative to standard Picard iteration are performed on a 3D model of a nuclear fuel assembly. Both criticality (k-eigenvalue) and critical boron search problems are considered.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Foreword to special issue: Papers from the 57th Annual Meeting of the APS Division of Plasma Physics, November 16–20, 2015, Savannah, Georgia, USA

The 57th annual meeting of the APS Division of Plasma Physics (DPP) was held November 16–20, 2015 in Savannah, Georgia. The meeting brings together researchers (undergraduate students through retirees) from all areas of plasma physics. 1887 abstracts were included in the program, approximately 200 more than the previous year. The presentations included five invited review talks, 97 invited talks, three invited postdeadline talks, and four tutorials. Furthermore, there were approximately 1780 contributed presentations, with about 40% oral and 60% poster. Three mini-conferences were held concurrently.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗