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DOE OSTI2013

Neutrino Physics at DPF 2013

The field of neutrino physics was covered at DPF 2013 in 32 talks, including three on theoretical advances and the remainder on experiments that spanned at least 17 different detectors. This summary of those talks cannot do justice to the wealth of information presented, but will provide links to other material where possible. There were allso two plenary session contributions on neutrino physics at this meeting: the current status of what we know about neutrino (oscillation) physics was outlined by Huber, and the next steps in long baseline oscillation expeirments were described by Fleming. This article covers a subset of the topics discussed at the meeting, with emphasis given to those talks that showed data or new results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Security Analysis of Smart Grid Cyber Physical Infrastructures Using Modeling and Game Theoretic Simulation

Cyber physical computing infrastructures typically consist of a number of sites are interconnected. Its operation critically depends both on cyber components and physical components. Both types of components are subject to attacks of different kinds and frequencies, which must be accounted for the initial provisioning and subsequent operation of the infrastructure via information security analysis. Information security analysis can be performed using game theory implemented in dynamic Agent Based Game Theoretic (ABGT) simulations. Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, and information assets. We concentrated our analysis on the electric sector failure scenarios and impact analyses by the NESCOR Working Group Study, From the Section 5 electric sector representative failure scenarios; we extracted the four generic failure scenarios and grouped them into three specific threat categories (confidentiality, integrity, and availability) to the system. These specific failure scenarios serve as a demonstration of our simulation. The analysis using our ABGT simulation demonstrates how to model the electric sector functional domain using a set of rationalized game theoretic rules decomposed from the failure scenarios in terms of how those scenarios might impact the cyber physical infrastructure network with respect to CIA.

Availability↗
DOE OSTI2013

Quarkonium at the Frontiers of High Energy Physics: A Snowmass White Paper

In this Snowmass White Paper, we discuss physics opportunities involving heavy quarkonia at the intensity and energy frontiers of high energy physics. We focus primarily on two specific aspects of quarkonium physics for which significant advances can be expected from experiments at both frontiers. The first aspect is the spectroscopy of charmonium and bottomonium states above the open-heavy-flavor thresholds. Experiments at e^+ e^- colliders and at hadron colliders have discovered many new, unexpected quarkonium states in the last 10 years. Many of these states are surprisingly narrow, and some have electric charge. The observations of these charged quarkonium states are the first definitive discoveries of manifestly exotic hadrons. These results challenge our understanding of the QCD spectrum. The second aspect is the production of heavy quarkonium states with large transverse momentum. Experiments at the LHC are measuring quarkonium production with high statistics at unprecedented values of p_T. Recent theoretical developments may provide a rigorous theoretical framework for inclusive production of quarkonia at large p_T. Experiments at the energy frontier will provide definitive tests of this framework. Experiments at the intensity frontier also provide an opportunity to understand the exclusive production of quarkonium states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Multiple-Scale Physics During Magnetic Reconnection

Magnetic reconnection is a key fundamental process in magnetized plasmas wherein the global magnetic topology is modified and stored energy is transferred from fields to particles. Reconnection is an inherently local process, and mechanisms to couple global-scale dynamics are not well understood. This dissertation explores two different mechanisms for cross-scale coupling during magnetic reconnection. As one example, we theoretically examine reconnection in a collisionless plasma using particle-in-cell simulations and demonstrate that large scale reconnection physics can couple to and drive microscopic instabilities, even in two-dimensional systems if significant scale separation exists between the Debye length and the electron skin depth. The physics underlying these instabilities is explained using simple theoretical models, and their potential connection to existing discrepancies between laboratory experiments and numerical simulations is explored. In three-dimensional systems, these instabilities are shown to generate anomalous resistivity that balances a substantial fraction of the electric field. In contrast, we also use experiments to investigate cross-scale couplings during reconnection in a collisional plasma. A leading candidate for coupling global and local scales is the hierarchical breakdown of elongated, reconnecting current sheets into numerous smaller current sheets -– the plasmoid instability. In the Magnetic Reconnection Experiment (MRX), recent hardware improvements have extended the accessible parameter space allowing for the study of long-lived, elongated current sheets. Moreover, by using Argon, reproducible and collisional plasmas are produced, which allow for a detailed statistical study of collisional reconnection. As a result, we have conclusively measured the onset of sub-ion-scale plasmoids during resistive, anti-parallel reconnection for the first time. The current sheet thickness is intermediate between ion and electron kinetic scales such that the plasma is in the Hall-MHD regime. Surprisingly, plasmoids are observed at Lundquist numbers < 100 well below theoretical predictions (> 10,000). The number of plasmoids scales with both Lundquist number and current sheet aspect ratio. The Hall quadrupolar fields are shown to suppress plasmoids. Finally, plasmoids are shown to couple local and global physics by enhancing the reconnection rate. These results are compared with prior studies of tearing and plasmoid instability, and implications for astrophysical plasmas, laboratory experiments, and theoretical studies of reconnection are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Measurement and Analysis of the Extreme Physical Shock Environment Experienced by Crane-Mounted Radiation Detection Systems.

Potentially, radiation detectors at ports of entry could be mounted on container gantry crane spreaders to monitor cargo containers entering and leaving the country. These detectors would have to withstand the extreme physical environment experienced by these spreaders during normal operations. Physical shock data from the gable ends of a spreader were recorded during the loading and unloading of a cargo ship with two Lansmont SAVER 9X30 units (with padding) and two PCB Piezotronics model 340A50 accelerometers (hard mounted). Physical shocks in the form of rapid acceleration were observed in all accelerometer units with values ranging from 0.20 g’s to 199.99 g’s. The majority of the shocks for all the Lansmont and PCB accelerometers were below 50 g’s. The Lansmont recorded mean shocks of 21.83 ± 13.62 g’s and 24.78 ± 11.49 g’s while the PCB accelerometers experienced mean shocks of 34.39 ± 25.51 g’s and 41.77 ± 22.68 g’s for the landside and waterside units, respectively. Encased detector units with external padding should be designed to withstand at least 200 g’s of acceleration without padding and typical shocks of 30 g’s with padding for mounting on a spreader.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

A Vision on the Status and Evolution of HEP Physics Software Tools

This paper represents the vision of the members of the Fermilab Scientific Computing Division's Computational Physics Department (SCD-CPD) on the status and the evolution of various HEP software tools such as the Geant4 detector simulation toolkit, the Pythia and GENIE physics generators, and the ROOT data analysis framework. The goal of this paper is to contribute ideas to the Snowmass 2013 process toward the composition of a unified document on the current status and potential evolution of the physics software tools which are essential to HEP.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Long-Lived Particles at the Energy Frontier: The MATHUSLA Physics Case

We examine the theoretical motivations for long-lived particle (LLP) signals at the LHC in a comprehensive survey of Standard Model (SM) extensions. LLPs are a common prediction of a wide range of theories that address unsolved fundamental mysteries such as naturalness, dark matter, baryogenesis and neutrino masses, and represent a natural and generic possibility for physics beyond the SM (BSM). In most cases the LLP lifetime can be treated as a free parameter from the $\mu$m scale up to the Big Bang Nucleosynthesis limit of $\sim 10^7$m. Neutral LLPs with lifetimes above $\sim$ 100m are particularly difficult to probe, as the sensitivity of the LHC main detectors is limited by challenging backgrounds, triggers, and small acceptances. MATHUSLA is a proposal for a minimally instrumented, large-volume surface detector near ATLAS or CMS. It would search for neutral LLPs produced in HL-LHC collisions by reconstructing displaced vertices (DVs) in a low-background environment, extending the sensitivity of the main detectors by orders of magnitude in the long-lifetime regime. In this white paper we study the LLP physics opportunities afforded by a MATHUSLA-like detector at the HL-LHC. We develop a model-independent approach to describe the sensitivity of MATHUSLA to BSM LLP signals, and compare it to DV and missing energy searches at ATLAS or CMS. We then explore the BSM motivations for LLPs in considerable detail, presenting a large number of new sensitivity studies. While our discussion is especially oriented towards the long-lifetime regime at MATHUSLA, this survey underlines the importance of a varied LLP search program at the LHC in general. By synthesizing these results into a general discussion of the top-down and bottom-up motivations for LLP searches, it is our aim to demonstrate the exceptional strength and breadth of the physics case for the construction of the MATHUSLA detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Future Opportunities in Accelerator-based Neutrino Physics

This document summarizes the conclusions of the Neutrino Town Meeting held at CERN in October 2018 to review the neutrino field at large with the aim of defining a strategy for accelerator-based neutrino physics in Europe. The importance of the field across its many complementary components is stressed. Recommendations are presented regarding the accelerator based neutrino physics, pertinent to the European Strategy for Particle Physics. We address in particular i) the role of CERN and its neutrino platform, ii) the importance of ancillary neutrino cross-section experiments, and iii) the capability of fixed target experiments as well as present and future high energy colliders to search for the possible manifestations of neutrino mass generation mechanisms.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Higgs Physics at the HL-LHC and HE-LHC

The discovery of the Higgs boson in 2012, by the ATLAS and CMS experiments, was a success achieved with only a percent of the entire dataset foreseen for the LHC. It opened a landscape of possibilities in the study of Higgs boson properties, Electroweak Symmetry breaking and the Standard Model in general, as well as new avenues in probing new physics beyond the Standard Model. Six years after the discovery, with a conspicuously larger dataset collected during LHC Run 2 at a 13 TeV centre-of-mass energy, the theory and experimental particle physics communities have started a meticulous exploration of the potential for precision measurements of its properties. This includes studies of Higgs boson production and decays processes, the search for rare decays and production modes, high energy observables, and searches for an extended electroweak symmetry breaking sector. This report summarises the potential reach and opportunities in Higgs physics during the High Luminosity phase of the LHC, with an expected dataset of pp collisions at 14 TeV, corresponding to an integrated luminosity of 3~ab$^{-1}$. These studies are performed in light of the most recent analyses from LHC collaborations and the latest theoretical developments. The potential of an LHC upgrade, colliding protons at a centre-of-mass energy of 27 TeV and producing a dataset corresponding to an integrated luminosity of 15~ab$^{-1}$, is also discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

A Physics-Driven Deep-Learning Network for Solving Nonlinear Inverse Problems

Geosteering inversion, which can be viewed as a nonlinear inverse problem, is an important technique used by directional drilling. Traditional methods that rely on iterative procedures and regularization are sensitive to the selection of initial values and can be slow due to convergence issues. In industrial applications, a lookup table is used to produce fast predictions. However, performance is not guaranteed by this approach due to the limitation of the hardware. In this paper, we propose a novel physics-driven deep-learning framework for providing a fast, accurate surrogate to solve the inverse problem. Particularly, leveraged by the forward physical model and 1D convolutional neural network (1D-CNN), the proposed method provides more reliable solutions to the inverse problem with improved performance. In addition, a new physics-driven loss function is introduced to accommodate both the model misfit and the data misfit. In conclusion, our experiments demonstrate the effectiveness of our method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Physics-Guided Machine Learning for Prediction of Cloud Properties in Satellite-Derived Solar Data: Preprint

With over 20 years of high-resolution surface irradiance data covering most of the western hemisphere, the National Solar Radiation Database (NSRDB) is a vital public data asset. The NSRDB uses a two-step Physical Solar Model (PSM) that explicitly considers the effects of clouds and other atmospheric variables on radiative transfer. High-quality physical and optical cloud properties derived from satellite imagery are perhaps the most important data input to the PSM, representing the greatest source of radiation attenuation and scattering. However, traditional methods for cloud property retrieval have their own limitations and are unable to accurately predict cloud properties outside of nominal conditions. We introduce a physics-guided neural network that can accurately predict cloud properties when traditional methods fail or are inaccurate. Using this framework, we show reductions in relative Root Mean Square Error (RMSE) for Global Horizontal Irradiance (GHI) up to 13 percentage points for timesteps that previously had missing or low-quality cloud property data. We expect that this methodology will be effective in improving the quality of cloud property and solar irradiance data in the NSRDB.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2021

Cyber-Physical Events Emulation Based Transmission and Distribution Co-Simulation for Situation Awareness and Grid Anomaly (SAGA) Detection: Preprint

Energy management of transmission and distribution networks is becoming more challenged with the accelerated increasing of distributed energy resources (DERs) such as distributed photovoltaic (PV) generation and distributed energy storage. To better analyze the impacts of DERs on both transmission and distribution systems, a comprehensive transmission and distribution co-simulation platform should be developed. Furthermore, with DERs more actively participated in system operation such as providing real time grid services, their cyber vulnerability should be better understood to maintain system reliability. This paper discussed a cyber-physical events emulation based transmission & distribution co-simulation platform to perform different cyber events emulation and analyze the impacts of cyber physical events happened in distribution system on the T&D system operation. The case studies with both a transmission network and a synthetic distribution network data validate that the proposed T&D co-simulation platform can perform comprehensive cyber physical events emulation. Therefore, with extensive simulation using the proposed model, the system operator can accumulate adequate training data for the system situation awareness and grid anomaly detection purpose.

31 CESER - Office of Cybersecurity, Energy Securit↗
DOE OSTI2021

Cyber Physical Grid-Interactive Distributed Energy Resources Control for VPP Dispatch and Regulation: Preprint

This paper presents a cyber-physical algorithm for grid interactive DER control to enable two features of Virtual Power Plants (VPPs) dispatch and grid voltage regulation, considering the communication and security impacts. We first formulate the DER dispatch problem as a real-time, iterative, and grid-interactive DER control problem. Thereafter, we consider a probabilistic traffic model to characterize packet delays and loss in a communication network, and study how the delays enter the process of information exchange among the grid measurement units, local DER controllers and the grid control center that coordinately execute this dispatch algorithm. Finally, we propose a cyber-physical grid-interactive DER control algorithm using the previous message strategy. The tracking and regulation capabilities of this proposed algorithm can be made immune to the asynchrony resulting from the communications network traffic. We carry out simulations to show possible numerical instabilities and sensitivities of the tracking and regulation capabilities on the proposed strategy. Our results exhibit that the uncertainties of the underlying communications infrastructure must be considered in the control algorithm for the VPP tracking and regulation capabilities of any DER in a generic Cyber-Physical System (CPS).

co-simulation↗
DOE OSTI2021

Autoencoders on FPGAs for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider

In this paper, we show how to adapt and deploy anomaly detection algorithms based on deep autoencoders, for the unsupervised detection of new physics signatures in the extremely challenging environment of a real-time event selection system at the Large Hadron Collider (LHC). We demonstrate that new physics signatures can be enhanced by three orders of magnitude, while staying within the strict latency and resource constraints of a typical LHC event filtering system. This would allow for collecting datasets potentially enriched with high-purity contributions from new physics processes. Through per-layer, highly parallel implementations of network layers, support for autoencoder-specific losses on FPGAs and latent space based inference, we demonstrate that anomaly detection can be performed in as little as $80\,$ns using less than 3% of the logic resources in the Xilinx Virtex VU9P FPGA. Opening the way to real-life applications of this idea during the next data-taking campaign of the LHC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Tensor networks for High Energy Physics: contribution to Snowmass 2021

Tensor network methods are becoming increasingly important for high-energy physics, condensed matter physics and quantum information science (QIS). We discuss the impact of tensor network methods on lattice field theory, quantum gravity and QIS in the context of High Energy Physics (HEP). These tools will target calculations for strongly interacting systems that are made difficult by sign problems when conventional Monte Carlo and other importance sampling methods are used. Further development of methods and software will be needed to make a significant impact in HEP. We discuss the roadmap to perform quantum chromodynamics (QCD) related calculations in the coming years. The research is labor intensive and requires state of the art computational science and computer science input for its development and validation. We briefly discuss the overlap with other science domains and industry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Snowmass2021 Cosmic Frontier White Paper: Cosmological Simulations for Dark Matter Physics

Over the past several decades, unexpected astronomical discoveries have been fueling a new wave of particle model building and are inspiring the next generation of ever-more-sophisticated simulations to reveal the nature of Dark Matter (DM). This coincides with the advent of new observing facilities coming online, including JWST, the Rubin Observatory, the Nancy Grace Roman Space Telescope, and CMB-S4. The time is now to build a novel simulation program to interpret observations so that we can identify novel signatures of DM microphysics across a large dynamic range of length scales and cosmic time. This white paper identifies the key elements that are needed for such a simulation program. We identify areas of growth on both the particle theory side as well as the simulation algorithm and implementation side, so that we can robustly simulate the cosmic evolution of DM for well-motivated models. We recommend that simulations include a fully calibrated and well-tested treatment of baryonic physics, and that outputs should connect with observations in the space of observables. We identify the tools and methods currently available to make predictions and the path forward for building more of these tools. A strong cosmic DM simulation program is key to translating cosmological observations to robust constraints on DM fundamental physics, and provides a connection to lab-based probes of DM physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Recoil imaging for dark matter, neutrinos, and physics beyond the Standard Model

Recoil imaging entails the detection of spatially resolved ionization tracks generated by particle interactions. This is a highly sought-after capability in many classes of detector, with broad applications across particle and astroparticle physics. However, at low energies, where ionization signatures are small in size, recoil imaging only seems to be a practical goal for micro-pattern gas detectors. This white paper outlines the physics case for recoil imaging, and puts forward a decadal plan to advance towards the directional detection of low-energy recoils with sensitivity and resolution close to fundamental performance limits. The science case covered includes: the discovery of dark matter into the neutrino fog, directional detection of sub-MeV solar neutrinos, the precision study of coherent-elastic neutrino-nucleus scattering, the detection of solar axions, the measurement of the Migdal effect, X-ray polarimetry, and several other applied physics goals. We also outline the R&D programs necessary to test concepts that are crucial to advance detector performance towards their fundamental limit: single primary electron sensitivity with full 3D spatial resolution at the $\sim$100 micron-scale. These advancements include: the use of negative ion drift, electron counting with high-definition electronic readout, time projection chambers with optical readout, and the possibility for nuclear recoil tracking in high-density gases such as argon. We also discuss the readout and electronics systems needed to scale-up such detectors to the ton-scale and beyond.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Physics-Driven Convolutional Autoencoder Approach for CFD Data Compressions: Preprint

With the growing size and complexity of turbulent flow models, data compression approaches are of the utmost importance to analyze, visualize, or restart the simulations. Recently, in-situ autoencoder-based compression approaches have been proposed and shown to be effective at producing reduced representations of turbulent flow data. However, these approaches focus solely on training the model using point-wise sample reconstruction losses that do not take advantage of the physical properties of turbulent flows. In this paper, we show that training autoencoders with additional physics-informed regularizations, e.g., enforcing incompressibility and preserving enstrophy, improves the compression model in three ways: (i) the compressed data better conform to known physics for homogeneous isotropic turbulence without negatively impacting point-wise reconstruction quality, (ii) inspection of the gradients of the trained model uncovers changes to the learned compression mapping that can facilitate the use of explainability techniques, and (iii) as a performance byproduct, training losses are shown to converge up to 12x faster than the baseline model.

auto-encoders↗