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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.

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28 records · Page 2

Search for new physics in final states with semivisible jets or anomalous signatures using the ATLAS detector

A search is presented for hadronic signatures of beyond the Standard Model (BSM) physics, with an emphasis on signatures of a strongly coupled hidden dark sector accessed via resonant production of a 𝑍′ mediator. The ATLAS experiment dataset collected at the Large Hadron Collider from 2015 to 2018 is used, consisting of proton-proton collisions at $\sqrt{𝑠}$ = 13 TeV and corresponding to an integrated luminosity of 140 fb −1 . The 𝑍′ mediator is considered to decay to two dark quarks, which each hadronize and decay to showers containing both dark and Standard Model particles, producing a topology of interacting and noninteracting particles within a jet known as “semivisible.” Machine learning methods are used to select these dark showers and reject the dominant background of mismeasured multijet events, including an anomaly detection approach to preserve broad sensitivity to a variety of BSM topologies. A resonance search is performed by fitting the transverse mass spectrum based on a functional form background estimation. No significant excess over the expected background is observed. Results are presented as limits on the production cross section of semivisible jet signals, parametrized by the fraction of invisible particles in the decay and the 𝑍′ mass, and by quantifying the significance of any generic Gaussian-shaped mass peak in the anomaly region.

particle dark matter↗

Applying Gaussian Process Machine Learning and Modern Probabilistic Programming to Satellite Data to Infer CO 2 Emissions

Satellite data provides essential insights into the spatiotemporal distribution of CO 2 concentrations. However, many atmospheric inverse models fail to adequately incorporate the spatial and temporal correlations inherent in satellite observations and often lack rigorous methods for estimating parameters like spatial length scales. We introduce an inference model that processes the spatiotemporal covariance in satellite data and estimates hyperparameters such as covariance length scales. Our approach uses the Gaussian process (GP) machine learning (ML) and modern probabilistic programming languages (PPLs) to perform atmospheric inversions of emissions from satellite data. We develop a GP ML inversion system based on modern PPLs and the GEOS-Chem chemical transport model, simulating atmospheric CO 2 concentrations corresponding to the Orbiting Carbon Observatory-2/3 (OCO-2/3) data for July 2020. In our supervised learning framework, we treat the GEOS-Chem simulated data set as the target, with predictors derived by scaling the target with sector-specific factors hidden from the GP machine. Our results show that the GP model, combined with GPU-enabled PPLs, effectively retrieves true emission scaling factors and infers noise levels concealed within the data. This suggests that our method could be applied over larger areas with more complex covariance structures, enabling comprehensive analysis of the spatiotemporal patterns observed in OCO-2/3 and similar satellite data sets.

54 ENVIRONMENTAL SCIENCES↗

Non-perturbative quarkonium dissociation rates in strongly coupled quark-gluon plasma

Heavy quarks and quarkonia are versatile probes of the transport properties of the hot QCD medium produced in ultra-relativistic heavy-ion collisions (URHICs). A robust description of heavy-flavor transport coefficients requires a microscopic approach that treats the open and hidden heavy-flavor sectors on the same footing. Here, we employ the quantum many-body T -matrix formalism to evaluate the dissociation rates of heavy quarkonia in the quark-gluon plasma (QGP). The basic ingredient is the heavy-light T -matrix, which utilizes a nonperturbative driving kernel constrained by lattice-QCD data. Its resummation in a ladder series provides a much enhanced interaction strength compared to a previously used perturbative coupling to the quasiparticle partons in the QGP. The in-medium quarkonium properties, particularly their temperature-dependent binding energies, are obtained from selfconsistent calculations with the same interaction kernel, including interference effects (also referred to as the imaginary part of the heavy-quark potential) as well as off-shell parton spectral functions. We systematically investigate the interplay of these effects and elaborate on the connections to the dipole approximation used in effective field theory.

effective field theories of QCD↗

Inflation and shadow matter

The possible production of shadow matter during the period of cosmic inflation is considered. The superstring theory of Gross et al. (1985), which results in a gauge group E8 x E8, could, at low energies, result in the existence of two sectors: an observed sector associated with all familiar particles and interactions, and a hidden one whose particles couple only through gravitational interactions with ordinary matter. It is demonstrated here that if, in the early universe, an inflationary phase is associated with the breaking of one of the symmetries in the E8 x E8 theory, this strongly constrains the physics of both sectors if shadow matter is to be the missing mass in the universe.

Krauss, L. M.↗

Hidden Rotation Symmetry of the Jordan–Wigner Transformation and Its Application to Measurement in Quantum Computation

Using a global rotation by 𝜃 about the z-axis in the spin sector of the Jordan–Wigner transformation rotates Pauli matrices 𝑋̂ and 𝑌̂ in the 𝑥−𝑦 -plane, while it adds a global complex phase to fermionic quantum states that have a fixed number of particles. With the right choice of angles, this relates expectation values of Pauli strings containing products of 𝑋̂ and 𝑌̂ to different products, which can be employed to reduce the number of measurements needed when simulating fermionic systems on a quantum computer. Here, we derive this symmetry and show how it can be applied to systems in Physics and Chemistry that involve Hamiltonians with only single-particle (hopping) and two-particle (interaction) terms. We also discuss the consequences of this for finding efficient measurement circuits in variational ground state preparation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Smooth splitting and zeros from on-shell recursion

We describe a new approach to understanding the origins of recently discovered “hidden zeros” and “smooth splitting” of tree-level amplitudes in Tr ϕ 3 , Non-Linear Sigma Model (NLSM), Yang-Mill-Scalar (YMS) and the special Galileon. Introducing a new type of linear shift in kinematic space we demonstrate that the mysterious splitting formulae follow from a simple contour integration argument in the style of on-shell recursion. The argument makes use of only standard notions of tree-level factorization on propagators, but assumes improved UV behavior in the form of the absence of a residue at infinity. In the case of Tr ϕ 3 and NLSM this is proven by identifying our shift as a special case of a more general construction called a g-vector shift; in the case of YMS it remains an unproven conjecture. This recursive perspective leads to numerous new results: we derive generalizations of the splitting formulae on more relaxed near-zero kinematics, including interesting new kinematic limits in which the amplitude splits into a triple-product; we also demonstrate that the uncolored special Galileon model has improved UV scaling and hence also splits. We also investigate the possible realization of hidden zeros in four dimensions. The conditions under which the dimensionality constraints are compatible with zero kinematics is investigated in detail for Tr ϕ 3 and YMS; for the latter we find they can be realized only with certain restrictions on external helicity states. The realizable 4d zeros are proven by a similar recursive argument based on BCFW and is found to generalize to a new class of intrinsically 4d “helicity zeros” present in all sectors of YM and also gravity.

effective field theories↗

Discovering Elusive Dynamics Across Frontiers (Final Technical Report)

Profound puzzles, such as the nature of dark matter, the origins of the electroweak scale, the mechanism behind the small neutrino mass, and the strong CP problem, suggested new physics beyond the Standard Model and drove the particle physics program in search of the associated new particles. Despite extensive searches, conventional realizations of new physics have not yet provided conclusive evidence. This raised the serious possibility that new dynamics might be more elusive, perhaps due to a richer gauge and matter structure than previously considered. Notably, the existence of dark matter and advancements in understanding the naturalness problem urged exploration into sectors with complex gauge and matter structures. Through experiments like the LHC, DUNE, and small-scale experiments, the robust US HEP program played a critical role in pursuing these well-motivated but under-explored scenarios for new physics. I explored these physics opportunities in depth, focusing on novel searches and significant improvements in parameter space coverage. The elusive dynamics revealed rich information about the underlying theory and were essential in identifying observable opportunities. Understanding the observable consequences required a deep comprehension of the theory, which I also developed. The proposal included essential components aimed at coherently increasing our knowledge in well-motivated elusive dynamics models. Through research on high-quality axions, composite neutrinos, the Higgs boson as a portal to hidden strong dynamics, and new scalar potentials to generate alternative electroweak phase transitions, I focused on identifying new signatures and parameter regions in plausible elusive dynamics models. The exploration emphasized generic possibilities motivated by broad classes of elusive dynamics models. These signatures were not effectively probed previously due to various challenges such as triggering, background suppression, or experimental design. My research involved close interaction with experimental colleagues to overcome these difficulties, leveraging new theoretical and experimental possibilities. These efforts included identifying new observables such as timing information and substructure in calorimetries, new multiple-hit techniques, new scattering events, and new resonance searches in liquid argon detectors. This work created a positive feedback loop: theory and experimental work inspired each other, revealing new exciting opportunities that supported both programs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Clean Energy Cybersecurity Accelerator: Cohort 2 - runZero Public Report

The U.S. Department of Energy (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER) sponsors the Clean Energy Cybersecurity Accelerator™ (CECA) to expedite the deployment of emerging security technologies that address the most urgent security concerns facing modern and future electric grids. CECA Cohort 2 assessed solutions focused on hidden risks due to incomplete system visibility and device security and configuration. Improving visibility can be achieved through operational technology (OT) asset identification solutions, including capabilities like automatic discovery, vulnerability reporting, and configuration monitoring. Solutions that monitor and identify assets in information technology (IT) networks in other domains are widely used; however, there is far less adoption of monitoring solutions for operational technology environments. Wider adoption may increase with increased confidence in the ability for these solutions to understand and respond to the specific requirements of OT environments. CECA Cohort 2 evaluated the active and passive asset discovery capabilities of market-ready solutions, documented and analyzed results, and identified gaps in functionality or capabilities. This report and describes how these results can help advance the adoption of these and similar solutions in the electric sector.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Clean Energy Cybersecurity Accelerator: Cohort 2 - Asimily Public Report

The U.S. Department of Energy (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER) sponsors the Clean Energy Cybersecurity Accelerator (TM) (CECA) to expedite the deployment of emerging security technologies that address the most urgent security concerns facing modern and future electric grids. CECA Cohort 2 assessed solutions focused on hidden risks due to incomplete system visibility and device security and configuration. Improving visibility can be achieved through operational technology (OT) asset identification solutions, including capabilities like automatic discovery, vulnerability reporting, and configuration monitoring. Solutions that monitor and identify assets in information technology (IT) networks in other domains are widely used; however, there is far less adoption of monitoring solutions for operational technology environments. Wider adoption may increase with increased confidence in the ability for these solutions to understand and respond to the specific requirements of OT environments. CECA Cohort 2 evaluated the active and passive asset discovery capabilities of market-ready solutions, documented and analyzed results, and identified gaps in functionality or capabilities. This report and describes how these results can help advance the adoption of these and similar solutions in the electric sector.

24 POWER TRANSMISSION AND DISTRIBUTION↗