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At least 901 records · Page 50

The strong coupling constant: state of the art and the decade ahead

Theoretical predictions for particle production cross sections and decays at colliders rely heavily on perturbative Quantum Chromodynamics (QCD) calculations, expressed as an expansion in powers of the strong coupling constant α$_{S}$. The current O(1%)uncertainty of the QCD coupling evaluated at the reference Z boson mass, αS(mZ2)=0.1179±0.0009, is one of the limiting factors to more precisely describe multiple processes at current and future colliders. A reduction of this uncertainty is thus a prerequisite to perform precision tests of the Standard Model as well as searches for new physics. This report provides a comprehensive summary of the state-of-the-art, challenges, and prospects in the experimental and theoretical study of the strong coupling. The current αS(mZ2)world average is derived from a combination of seven categories of observables: (i) lattice QCD, (ii) hadronic τ decays, (iii) deep-inelastic scattering and parton distribution functions fits, (iv) electroweak boson decays, hadronic final-states in (v) e$^{+}$e$^{−}$, (vi) e–p, and (vii) p–p collisions, and (viii) quarkonia decays and masses. We review the current status of each of these seven αS(mZ2)extraction methods, discuss novel α$_{S}$ determinations, and examine the averaging method used to obtain the world-average value. Each of the methods discussed provides a ‘wish list’ of experimental and theoretical developments required in order to achieve the goal of a per-mille precision on αS(mZ2)within the next decade.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Information-Theoretic Bounds on Quantum Advantage in Machine Learning

We study the performance of classical and quantum machine learning (ML) models in predicting outcomes of physical experiments. The experiments depend on an input parameter x and involve execution of a (possibly unknown) quantum process E. Our figure of merit is the number of runs of E required to achieve a desired prediction performance. We consider classical ML models that perform a measurement and record the classical outcome after each run of E, and quantum ML models that can access E coherently to acquire quantum data; the classical or quantum data are then used to predict the outcomes of future experiments. We prove that for any input distribution D(x), a classical ML model can provide accurate predictions on average by accessing E a number of times comparable to the optimal quantum ML model. In contrast, for achieving an accurate prediction on all inputs, we prove that the exponential quantum advantage is possible. For example, to predict the expectations of all Pauli observables in an n-qubit system ρ, classical ML models require 2 Ω(n) copies of ρ, but we present a quantum ML model using only O(n) copies. Our results clarify where the quantum advantage is possible and highlight the potential for classical ML models to address challenging quantum problems in physics and chemistry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The first measurement of the muon anomalous magnetic moment from the Fermilab Muon g-2 collaboration

This paper will cover the physics and methods behind Fermilab’s Muon g-2 Experiment, along with the long-awaited results from Run-1. The experiment was undertaken to resolve the tension between the Standard Model and the previous measurement taken at Brookhaven National Laboratory. The measured value of the muon magnetic anomaly is a µ (FNAL) = 116592040(54) × 10 -11 . This result is in good agreement with Brookhaven’s previous measurement. The new world average, a µ (Exp) = 116592061(41) × 10 -11 , shows a difference from the theoretical value of the Standard Model (SM), a µ (SM) = 116591810(43) × 10 -11 , of 4.2 standard deviations, strongly hinting at physics beyond the Standard Model. The experiment requires the simultaneous measurement of the muon precession frequency, the magnetic field, and the muons’ distribution in the field. All three of these measurements will be discussed in context, along with the main systematic corrections and uncertainties.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Agentic Diagrammatica: Towards Autonomous Symbolic Computation in High Energy Physics

We present Diagrammatica, a symbolic computation extension to the HEPTAPOD agentic framework, which enables LLM agents to plan and execute multi-step theoretical calculations. Symbolic computation poses a distinctive reliability challenge for LLM agents, as correctness is governed by implicit mathematical conventions that are not encoded in a form that can be easily checked in the computational backend. We identify two complementary remedies, tool-constrained computation and targeted knowledge grounding, and pursue the first as the primary architecture. Concretely, we concentrate the agent's action distribution onto tool calls with convention-fixing semantics, in which the agent specifies a compact, human-auditable diagram specification and a trusted backend performs the symbolic or numerical manipulations exactly. The toolkit provides two complementary calculation paths consuming a shared diagram specification: Naive Dimensional Analysis (NDA) for order-of-magnitude rate estimates and Exact Diagrammatic Analysis (EDA) for tree-level symbolic calculations via automatic FeynCalc code generation, both supplemented by automatic Feynman diagram enumeration and a navigable theory knowledge base. The architecture is validated on two benchmarks: (1) an exhaustive catalog of all tree-level, single-vertex $1\to 2$ partial decay widths across scalar, fermion, and vector parents, with complete massless and threshold limits and Standard Model validation; and (2) an NDA sensitivity study of the muon decay multiplicity $μ^+ \to ν_μ\barν_e + n(e^+e^-) + e^-$, determining the maximum observable $n$ at current and planned muon experiments.

Menzo, Tony [Alabama U.; Fermilab] (ORCID:00000002↗

Snowmass2021 theory frontier white paper: Astrophysical and cosmological probes of dark matter

While astrophysical and cosmological probes provide a remarkably precise and consistent picture of the quantity and general properties of dark matter, its fundamental nature remains one of the most significant open questions in physics. Obtaining a more comprehensive understanding of dark matter within the next decade will require overcoming a number of theoretical challenges: the groundwork for these strides is being laid now, yet much remains to be done. Chief among the upcoming challenges is establishing the theoretical foundation needed to harness the full potential of new observables in the astrophysical and cosmological domains, spanning the early Universe to the inner portions of galaxies and the stars therein. Identifying the nature of dark matter will also entail repurposing and implementing a wide range of theoretical techniques from outside the typical toolkit of astrophysics, ranging from effective field theory to the dramatically evolving world of machine learning and artificial-intelligence-based statistical inference. Through this work, the theory frontier will be at the heart of dark matter discoveries in the upcoming decade.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Perspectives and Questions: Toward an Expansive Agenda for Particle Physics

Global celebration greeted the 2012 discovery at CERN's Large Hadron Collider of a particle that matches the textbook description of the Higgs boson. That achievement validated a remarkable chain of theoretical reasoning that combined the prescriptive notion of electroweak gauge symmetry with a simple, but \emph{ad hoc}, embodiment of spontaneous symmetry breaking. It was made possible by generational triumphs of accelerator art and experimental technique, and by human resourcefulness and collaboration on a global scale, all sustained by the enlightened support of many governments and institutions. Some imagine that, once the keystone of the standard model of particle physics has been set, our subject is over. Others worry that we may be at an impasse because no comparable wonders have appeared, leaving us without well-defined clues to a more complete paradigm. I am neither so readily satisfied nor so {easily} discouraged: we have so much more to learn! This essay surveys many questions that, taken together, constitute an inspiring array of opportunities to enhance our understanding of the physical world.

Quigg, Chris [Fermilab] (ORCID:0000000227282445)↗

Isotropic-to-Nematic Transition in Salt-Free Polyelectrolyte Coacervates from Coarse-Grained Simulations

Recent interest in complex coacervation between oppositely charged polyelectrolytes (PEs) has been fueled by its relevance to biology in the context of membraneless organelle formation within living cells. For PEs with limited flexibility (such as double-stranded DNA), theoretical treatments and recent experiments have reported the emergence of liquid crystalline order (LCO) within the resulting coacervate phases. In this work, we study the underlying physics of this phenomenon using coarse-grained molecular dynamics simulations of symmetric semiflexible-semiflexible and asymmetric semiflexible-flexible coacervates. By comparing coacervates with the corresponding semidilute solutions of neutral polymers, we demonstrate that the presence of Coulomb interactions in coacervates facilitates orientational ordering, in agreement with theoretical predictions. Quantitative comparisons between our simulations and theory indicate that, for asymmetric nematic coacervates, the strong orientational ordering of stiff polyanions induces a weak ordering of the flexible polycations-an effect that was not anticipated by available theoretical studies. Simulations reveal that, for nematic coacervates, the preferred orientation of the PE chains at the liquid-liquid coacervate-supernatant interface is parallel, and the alignment of semiflexible PEs is homogeneous. The results presented here provide new molecular-level insights into the intracoacervate LCO and will help motivate further experimental and theoretical activities in this area.

36 MATERIALS SCIENCE↗

The Blanket Effect: How Turning the World Upside Down Reveals the Nature of Graphene Oxide Cytocompatibility

Extensive cytocompatibility testing of 2D nanocarbon materials including graphene oxide (GO) has been performed, but results remain contradictory. Literature has yet to account for settling—although sedimentation is visible to the eye and physics suggests that even individual graphenic flakes will settle. To investigate settling, a series of functional graphenic materials (FGMs) with differing oxidation levels, functionalities, and physical dimensions were synthesized. Though zeta potential indicated colloidal stability, significant gravitational settling of the FGMs was theoretically and experimentally demonstrated. By creating a setup to culture cells in traditional and inverted orientations in the same well, a “blanket effect” was unequivocally demonstrated in which FGMs settle out of solution and cover cells at the bottom of the well, limiting nutrient exchange and viability. Inverted cells protected from the blanket effect are unaffected. Therefore, these results demonstrate that settling is a crucial factor that must be considered for FGM cytocompatibility experiments.

Holt, Brian D.↗

LASSO for CALPHAD Model Selection Enables Data-Efficient Thermodynamic Modeling: An Application in Thermochemical Hydrogen Production Materials

Phenomenological CALPHAD (CALculation of PHAse Diagrams) models, widely used for multicomponent materials, often contain a considerable number of parameters and require fitting using data from a relatively small number of experimental measurements or theoretical calculations. Sometimes these parameters are introduced for the purpose of improving model fits but without clear physical justification, which leads to overparametrized models with poor generalization performance. Automated approaches for optimal model selection based on the available data therefore become critical. Here, in this work, a least absolute shrinkage and selection operator (LASSO)-based approach is developed for model selection by leveraging the linearity of the CALPHAD model with respect to its parameters to convert the model selection and fitting to a LASSO minimization problem. We demonstrate its utility for thermodynamic modeling of thermochemical hydrogen (TCH) production materials using lanthanum strontium manganite (LSM) as an example. Various TCH-relevant properties, including oxygen stoichiometry as a function of oxygen partial pressure, enthalpy of reduction, and entropy of reduction, are successfully predicted with reasonable accuracy using a minimal set of model parameters. Importantly, the model selection and fitting involve minimal human decision; it can therefore be applied to high-throughput DFT defect calculations and yield efficient workflows for TCH material modeling and optimization.

CALPHAD↗

Spectral Performance of Multilayer Amorphous Selenium and Selenium–Tellurium Photodetectors

The ability to robustly and with scalability detect single photons in the visible spectrum with wavelength resolution would transform many imaging applications. Theoretical studies propose an array of carbon nanotubes (CNTs) functionalized with semiconductor quantum dots (QDs) as a physical realization of such photon sensors. In this work, we report approaches to synthesize these CNT-QD nanostructures using DNA as a smart glue to connect CNTs to QDs.

36 MATERIALS SCIENCE↗

Incommensurate transition-metal dichalcogenides via mechanochemical reshuffling of binary precursors

A new family of heterostructured transition-metal dichalcogenides (TMDCs) with incommensurate (“misfit”) spatial arrangements of well-defined layers was prepared from structurally dissimilar single-phase 2H-MoS 2 and 1T-HfS 2 materials. The experimentally observed heterostructuring is energetically favorable over the formation of homogeneous multi-principle element dichalcogenides observed in related dichalcogenide systems of Mo, W, and Ta. The resulting three-dimensional (3D) heterostructures show semiconducting behavior with an indirect band gap around 1 eV, agreeing with values predicted from density functional theory. Results of this joint experimental and theoretical study open new avenues for generating unexplored metal-dichalcogenide heteroassemblies with incommensurate structures and tunable physical properties.

36 MATERIALS SCIENCE↗

Trailhead for quantum simulation of SU(3) Yang-Mills lattice gauge theory in the local multiplet basis

Maintaining local interactions in the quantum simulation of gauge field theories relegates most states in the Hilbert space to be unphysical—theoretically benign, but experimentally difficult to avoid. Reformulations of the gauge fields can modify the ratio of physical to gauge-variant states often through classically preprocessing the Hilbert space and modifying the representation of the field on qubit degrees of freedom. This paper considers the implications of representing SU(3) Yang-Mills gauge theory on a lattice of irreducible representations in both a global basis of projected global quantum numbers and a local basis in which controlled-plaquette operators support efficient time evolution. Classically integrating over the internal gauge space at each vertex (e.g., color isospin and color hypercharge) significantly reduces both the qubit requirements and the dimensionality of the unphysical Hilbert space. Initiating tuning procedures that may inform future calculations at scale, the time evolution of one and two plaquettes are implemented on one of IBM’s superconducting quantum devices, and early benchmark quantities are identified. The potential advantages of qudit environments, with either constrained two-dimensional hexagonal or one dimensional nearest-neighbor internal state connectivity, are discussed for future large-scale calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Transverse momentum moments

We establish robust relations between Transverse Momentum Dependent distributions (TMDs) and collinear distributions. We define weighted integrals of TMDs that we call Transverse Momentum Moments (TMMs) and prove that TMMs are equal to collinear distributions evaluated in some minimal subtraction scheme. The conversion to the modified minimal subtraction ( MS ¯ ) scheme can be done by a calculable factor, which we derive up to three loops for some cases. We discuss in detail the zeroth, the first, and the second TMMs and provide phenomenological results for them based on the current extractions of TMDs. The results of this paper open new avenues for theoretical and phenomenological investigation of the three-dimensional and collinear hadron structures. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Optimal Demand Response Incorporating Distribution LMP with PV Generation Uncertainty

The utilization of aggregated demand-side flexibility via demand response (DR) has become a promising pathway for the integration of renewable energy resources in power systems. Nowadays, there are several management strategies for DR such as the price-based transactive control strategies. However, many of such existing price-based control strategies neglect the physics and operational constraints of the underlying distribution networks when computing the price, raising concerns regarding their theoretical and practical values. This paper studies this issue and investigates optimal DR (ODR) by incorporating the distribution locational marginal price (DLMP). In particular, we discuss DR in connection with DLMPs and propose a multiperiod bilevel optimization problem to find the ODR strategy. Here, the objective is to minimize the peak load, load fluctuation, and payments of load aggregators. In addition, a robust bilevel ODR model is formulated to provide a robust ODR strategy while minimizing operating costs under the worst-case realization of uncertainties; this mitigates the impact of forecasting errors on renewable energy resources. Then, we propose an efficient solution approach by employing the Karush-Kuhn-Tucker conditions and strong duality. Simulation results are presented to illustrate the mutual impacts of the interaction between DR and DLMP and the benefits of the robust ODR strategy.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Experimental demonstration of OSC at IOTA: IOTA Run #3 (Report)

Optical Stochastic Cooling (OSC) is an optical-bandwidth extension of Stochastic Cooling that could advance the state-of-the-art cooling rate in beam cooling by three to four orders of magnitude. The concept of OSC was first suggested in the early 1990s by Zolotorev, Zholents and Mikhailichenko, and replaced the microwave hardware of SC with optical analogs, such as wigglers and optical amplifiers. A number of variations on the original OSC concept have been proposed, and while a variety of proof-of-principle demonstrations and operational uses have been considered, the concept was not experimentally demonstrated up to now. An OSC R&D program has been underway at IOTA for the past several years. Run #3 of the IOTA ring, which began in Nov. 2020 and concluded in Aug. 2021, was focused on the world’s first experimental demonstration of OSC. The experimental program was successful in demonstrating and characterizing the OSC physics with the major outcomes including strong cooling in one, two and three dimensions, validation of the theoretical models of OSC and the demonstration of OSC with a single electron. This report briefly describes the activities and major milestones of the OSC program during Run #3.

42 ENGINEERING↗

Particle Dark Matter Across Scales

This is the final technical report of the DOE Early Career award for PI Safdi. The award was active from 09/01/2018 - 05/01/2021. The Early Career award funded theoretical work to investigate the particle nature of dark matter across a range of astrophysical and particle physics scales.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Simulation-Based Inference for Neutrino Interaction Model Parameter Tuning

High-energy physics experiments studying neutrinos rely heavily on simulations of their interactions with atomic nuclei. Limitations in the theoretical understanding of these interactions typically necessitate ad hoc tuning of simulation model parameters to data. Traditional tuning methods for neutrino experiments have largely relied on simple algorithms for numerical optimization. While adequate for the modest goals of initial efforts, the complexity of future neutrino tuning campaigns is expected to increase substantially, and new approaches will be needed to make progress. In this paper, we examine the application of simulation-based inference (SBI) to the neutrino interaction model tuning for the first time. Using a previous tuning study performed by the MicroBooNE experiment as a test case, we find that our SBI algorithm can correctly infer the tuned parameter values when confronted with a mock data set generated according to the MicroBooNE procedure. This initial proof-of-principle illustrates a promising new technique for next-generation simulation tuning campaigns for the neutrino experimental community.

Tame-Narvaez, Karla Maria [Fermilab]↗