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DOE OSTI2025

Ambiguities in the partial-wave analysis of the photoproduction of pairs of pseudoscalar mesons

Applying the technique of partial-wave analysis, there are cases where more than one set of underlying complex-valued amplitudes can describe the measured observables. These ambiguities can sometimes be resolved using additional information, but assumptions are often required. It is known that the partial-wave analysis of two-pseudoscalar meson systems produced in photoproduction with a linearly polarized photon beam is free from discrete ambiguities stemming from the Barrelet zeros when the nucleon spin is ignored. In this article, we show that continuous ambiguities are possible for certain wave sets, even though the discrete ambiguities do not appear. We also explore ways to resolve these ambiguities and determine the maximal amount of information that can be obtained from analyses that suffer from these continuous ambiguities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Corrosion-Resistant Non-Carbon Electrocatalyst Supports for PEFCS

Insufficient durability of commercial catalysts is a persistent issue for PEFC applications.1 Herein, Pt on Nb-doped-TiO 2 is reported as a highly durable electrocatalyst on which the direct 4-electron reduction of oxygen to water is more facile compared to Pt/C. All performance metrics are reported comparing Pt/Nb-TiO2 with a 15% Pt loading, against a commercial Pt/C catalyst (46.5% Pt loading, Tanaka, K. K.). Nb-doped-TiO 2 with high surface area and high electronic conductivity was synthesized using the supercritical fluid method. Initially, the durability of the catalyst was characterized using accelerated stability tests (ASTs) involving 10,000 high potential cycles (DOE/FCCJ protocol) and the Pt/Nb-TiO 2 was found to retain 78% of its initial electrochemically active surface area (ECSA) compared to the 57.6 % retained by Pt/C. These observations were in excellent agreement with previous reports that the Pt particle size of Pt/C grew from 2nm to 8nm during the AST protocol along with severe corrosion and amorphization of the carbon surface.2, 3 TEM and XPS studies of the Pt-Nb-doped-TiO 2 catalyst showed that the Pt particle size grew from 3nm to 6nm and the Nb(IV) and Ti(III) in the support were oxidized to Nb(V) and Ti(IV) after the durability test. Thus, the improvement in Pt/Nb-TiO 2 ECSA retention was attributed to the lower extent of particle growth and lack of oxidative support loss upon oxidation as compared to Pt/C. The oxygen reduction reaction (ORR) performance was characterized by linear polarization using a rotating disk electrode (RDE). The electrochemical surface areas of Pt/Nb-TiO 2 and Pt/C were found to be 48m2·g -1 and 83m2·g -1 respectively, and the mass activity for the ORR at 0.9V vs. RHE were found to be 150 mA·mg-1Pt and 124 mA·mg-1Pt respectively. The improved mass activity on Pt/Nb-TiO 2 was attributed to strong metal support interaction (SMSI) between the Nb-TiO 2 support and the Pt catalyst based on the 625 meV decrease in the binding energy of the Pt4f x-ray photo-electron spectroscopy (XPS) peaks of Pt/Nb-TiO 2 compared to Pt/C. To quantify the impact of the SMSI, a kinetic model was applied to calculate the elementary reaction rate constants for the various steps of the ORR on both catalysts. The reaction rate constant (k1) for the direct 4-electron transfer pathway to produce H 2 O was significantly larger in Pt/Nb-TiO 2 as compared to Pt/C. Thus, the reduction in the electron binding energy as observed in the XPS was found to aid the facile filling of the higher energy 2p orbitals of O 2 thereby leading to improved 4-electron transfer kinetics and improved overall activity.

08 HYDROGEN↗

DOE OSTI2024

Improving the five-point bootstrap

We present a new algorithm for the numerical evaluation of five-point conformal blocks in d-dimensions, greatly improving the efficiency of their computation. To do this we use an appropriate ansatz for the blocks as a series expansion in radial coordinates, derive a set of recursion relations for the unknown coefficients in the ansatz, and evaluate the series using a Padé approximant to accelerate its convergence. We then study the 〈σσϵσσ〉 correlator in the 3d critical Ising model by truncating the operator product expansion (OPE) and only including operators with conformal dimension below a cutoff ∆ ⩽ ∆cutoff. We approximate the contributions of the operators above the cutoff by the corresponding contributions in a suitable disconnected five-point correlator. Using this approach, we compute a number of OPE coefficients with greater accuracy than previous methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Measurement of spin-density matrix elements in 𝜙⁡(1020) → 𝐾$^{0}_{𝑆}$⁢𝐾$^{0}_{𝐿}$ photoproduction with a linearly polarized photon beam at 𝐸 𝛾 = 8.2–8.8 GeV

We measure the spin-density matrix elements (SDMEs) for the photoproduction of 𝜙⁡(1020) off of the proton in its decay to 𝐾$^{0}_{𝑆}$⁢𝐾$^{0}_{𝐿}$, using 105 pb −1 of data collected with a linearly polarized photon beam using the GlueX experiment. The SDMEs are measured in nine bins of the squared four-momentum transfer 𝑡 in the range −𝑡=0.15−1.0 GeV 2 , providing the first measurement of their 𝑡 dependence for photon beam energies of 𝐸 𝛾 = 8.2−8.8 GeV. We confirm the dominance of Pomeron exchange in this region and put constraints on the contribution of other Regge exchanges. We also find that helicity amplitudes where the helicity of the photon and 𝜙⁡(1020) differ by two units are negligible.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Dirac Magnon in Honeycomb Lattice Magnet NiTiO 3

We performed inelastic neutron scattering experiments on single-crystal samples of the honeycomb lattice magnet, ilmenite NiTiO 3 . Below the Néel temperature of 22 K, spin wave excitations with a band energy of 3.7 meV were observed. Further, the neutron energy spectra were well-reproduced by modeling the system as a ferromagnetic honeycomb lattice with antiferromagnetic interlayer coupling, using linear spin wave theory. Similar to another ilmenite CoTiO 3 , a crossing structure was observed at the K point, suggesting the presence of Dirac magnons in NiTiO 3 . Further calculations suggested the formation of Dirac nodal line.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

A Bayesian framework to investigate radiation reaction in strong fields

Recent experiments aiming to measure phenomena predicted by strong-field quantum electrodynamics (SFQED) have done so by colliding relativistic electron beams and high-power lasers. In such experiments, measurements of collision parameters are not always feasible. However, precise knowledge of these parameters is required to accurately test SFQED. Here, we present a novel Bayesian inference procedure that infers collision parameters that could not be measured on-shot. This procedure is applicable to all-optical non-linear Compton scattering experiments investigating radiation reaction. The framework allows multiple diagnostics to be combined self-consistently and facilitates the inclusion of known information pertaining to the collision parameters. Using this Bayesian analysis, the relative validity of the classical, quantum-continuous and quantum-stochastic models of radiation reaction was compared for several test cases, which demonstrates the accuracy and model selection capability of the framework and highlight its robustness if the experimental values of fixed parameters differ from their values in the models.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Design, Fabrication and Concept for the Surface Treatment of the SRF Cavity Prototype for the CLIC Damping Rings

The Compact Linear Collider (CLIC) Damping Rings (DRs) need to generate ultra-low emittance bunches to achieve high luminosity in CLIC. This requires many wiggler magnets with big energy loss which is compensated by the Radio Frequency (RF) system. The resulting strong beam loading transients lead to a challenging design for the RF system. A novel SRF cavity at 2 GHz with an ultra-low R/Q parameter of below 1 Ω is proposed to minimize the transient beam loading effects below acceptable level. The design and fabrication of the bulk Nb prototype based on turning from a single piece of Nb and EB welding is presented. Moreover, conceptual study of the system for cavity surface treatment to achieve the highest surface magnetic field which is the main goal of the prototype cold test is described as well. To enable excellent performance in this cavity, we plan to apply the 75/120C modified low temperature bake in combination with the cold electropolishing process. This surface treatment approach has been shown to consistently deliver high accelerating gradients and improved quality factors in TESLA-shaped 1.3 GHz SRF cavities. By adapting and implementing this process for the 2 GHz ultra-low R/Q design, we aim to maximize the achievable surface magnetic field while minimizing residual resistance and field emission. This treatment strategy will be critical for demonstrating that the cavity can meet the demanding performance requirements of the CLIC damping ring RF system under high beam loading conditions.

Bafia, Daniel P. [Fermilab]↗

DOE OSTI2025

Applying Linear Optics from Closed Orbits Modulation for finding beam-based alignment of harmonic sextupoles

A fast and accurate beam-based alignment (BBA) method for harmonic sextupoles has been devel oped at NSLS-II using Linear Optics from Closed Orbit Modulation (LOCOM). The approach excites the beam with simultaneous sine-wave signals at two fast correctors, chosen with an appropriate phase advance to span the full betatron phase space. This strategy suppresses systematic errors from hysteresis, while additional errors from orbit drift and power-supply calibration are minimized by the short measurement time (a few minutes) and reliance solely on beam-based current-to-field conver sion of the sextupoles, with hysteresis explicitly included. Simulations indicate that Linear Optics from Closed Orbits (LOCO) combined with 0.5 mm local orbit bumps can resolve relative sextupole field offsets (∆k₂) with precision better than 10% of k₂, reflecting to beam-based alignment (BBA) accuracy finer than 50 µm. Moreover, employing machine-learning-optimized local orbit bumps en hances sextupole-induced quadrupole signals in a deterministic manner and maintains orbit stability under large sextupole strength variations (±40%). The proposed method is experimentally validated through proof-of-principle measurements at NSLS-II, demonstrating its potential as a fast, precise, and robust tool for harmonic sextupole alignment.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Fine-tuning machine-learned particle-flow reconstruction for new detector geometries in future colliders

We demonstrate transfer learning capabilities in a machine-learned algorithm trained for particle-flow reconstruction in high energy particle colliders. This paper presents a cross-detector fine-tuning study, where we initially pretrain the model on a large full simulation dataset from one detector design, and subsequently fine-tune the model on a sample with a different collider and detector design. Specifically, we use the Compact Linear Collider detector (CLICdet) model for the initial training set and demonstrate successful knowledge transfer to the CLIC-like detector (CLD) proposed for the Future Circular Collider in electron-positron mode. We show that with an order of magnitude less samples from the second dataset, we can achieve the same performance as a costly training from scratch, across particle-level and event-level performance metrics, including jet and missing transverse momentum resolution. Furthermore, we find that the fine-tuned model achieves comparable performance to the traditional rule-based particle-flow approach on event-level metrics after training on 100,000 CLD events, whereas a model trained from scratch requires at least 1 million CLD events to achieve similar reconstruction performance. To our knowledge, this represents the first full-simulation cross-detector transfer learning study for particle-flow reconstruction. These findings offer valuable insights towards building large foundation models that can be fine-tuned across different detector designs and geometries, helping to accelerate the development cycle for new detectors and opening the door to rapid detector design and optimization using machine learning.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Density drop at the divertor target in the prototype material plasma exposure eXperiment (Proto-MPEX)

The steady-state linear device “Material Plasma Exposure eXperiment” (MPEX) is currently under construction at Oak Ridge National Laboratory with the goal of enabling Plasma-Material Interaction studies at future fusion reactor relevant plasma conditions. In this work, a newly in-house developed hybrid Particle-In-Cell code-PICOS++ is applied to understand the experimental results obtained from the prototype of MPEX referred to as the “Proto-MPEX” during its helicon-only and helicon with ion cyclotron resonance heating (ICRH) experiments. This study explains the physics of the experimentally observed plasma density-drop at the divertor target in Proto-MPEX device during ICRH. In contrast to previous work on ICRH in MPEX, this study demonstrates that the mirror force plays a central role in the Proto-MPEX plasma transport during ICRH, which has new features not previously explored. Force balance analyses reveal that the temperature anisotropy produced by ICRH leads to a significant increase in the mirror force downstream of the resonance where the magnetic field is diverging. This force accelerates ions toward the target and leads to a drop in plasma density to ensure conservation of particle flux. Simulations with ICRH where the magnetic field divergence downstream of the resonance has been removed, do not produce plasma acceleration nor density drop at the target despite efficient ion heating at the resonance. Moreover, simulation results demonstrate that for a given ICRH power, lowering the source rate produces ions with increased perpendicular energy which interact with the mirror force to produce higher plasma acceleration which increases the strength of the density-drop at the target. The strength of the density drop appears to reach an asymptotic limit at a certain threshold ICRH power. Simulations show that this threshold power increases with increasing particle source rate.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Univariate Prediction of Hammett Parameters and Select Relative Reaction Rates Using Loewdin Atomic Charges

Loewdin charges from density functional theory calculations were used here to obtain general, univariate linear correlations for the prediction of experimental Hammett parameters and relative reaction rates. While previous studies have established that Hirshfeld and CM5 charges perform strongly as univariate predictors, the near-ubiquitous Loewdin charges have not yet been evaluated. To this end, we assess the predictive capability of Loewdin charges for three chemical systems. First, we show that Loewdin charges outperform Hirshfeld and CM5 charges for Hammett parameter prediction. Second, we see that Loewdin charges generally perform comparably to Hirshfeld charges for predicting the relative rates of olefin cleavage by photoexcited nitroarenes. The single case of poor correlation, between relative rates and the Loewdin charges on nitrogen sites, is ameliorated when considering the net charge on the NO 2 group. Third, we show that Loewdin, Hirshfeld, and CM5 charges all perform very well for generating correlations for relative reaction rates for C–H activation of 9-(4-X-phenyl)-9H-fluorene substrates by a transition metal catalyst. The equations generated throughout the study enable the prediction of Hammett parameters and relative reaction rates. Finally, these tools can accelerate synthetic and experimental studies by enabling the in silico prediction of uncharacterized chemical properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Rapidity-dependent spin decomposition of the nucleon

We revisit the two-dimensional Fourier transform of generalized parton distributions (GPDs) at nonzero skewness. At 𝜂 = 0 it reduces to the standard impact-parameter density, while at 𝜂 ≠ 0 it is an off-forward amplitude that we interpret as a genuine parton–nucleon correlation. Its overall strength (the transverse-plane integral of the density) is fixed by the GPD at the kinematic point 𝑡 =−𝑐 𝜂 =−4⁢𝜂 2 ⁢𝑚$^{2}_{𝑁}$/(1 − 𝜂 2 ) and decreases monotonically with the rapidity gap Δ⁢𝑦 = ln⁡[(1+𝜂)/(1−𝜂)] = 2 artanh⁡(𝜂). This rapidity dependence implies rapidity-modified Ji identities that connect helicity, orbital, and total angular momenta of the correlation in closed form. To quantify these effects, we construct leading-twist quark and gluon GPDs in a string-based conformal framework: conformal moments are parametrized by linear open- and closed-string Regge trajectories with slopes constrained by parton distribution functions (PDFs), hadron/glueball spectroscopy, and form-factor data, and GPDs are reconstructed over the full (𝑥,𝜂,𝑡) domain by Mellin-Barnes inversion with next-to-leading order evolution. We find qualitative agreement (and fair quantitative agreement within quoted uncertainties) for several moments and selected nonsinglet 𝑥-space channels at 𝜇 = 2 GeV when compared with lattice QCD, while we also identify channels with visible tension and discuss likely sources (PDF priors and 𝑡-slope systematics).

Gauge-gravity dualities↗

DOE OSTI2026

Small-𝑥 asymptotics of the leading-twist flavor-singlet quark TMDs

In this paper, we investigate the small-𝑥 behavior of the flavor-singlet, leading-twist quark transverse-momentum-dependent parton distribution functions (TMDs) using the light-cone operator treatment. This formalism allows us to express TMD operators at small 𝑥 in terms of polarized dipole amplitudes, enabling a systematic approach to their small-𝑥 evolution. We derive the evolution equations for these TMDs and solve them within the large-𝑁 𝑐 approximation under the linearized, double-logarithmic approximation, where 𝑁 𝑐 represents the number of quark colors. Expanding on previous work on unpolarized and helicity TMDs, we present the small-𝑥 asymptotics for a comprehensive set of TMDs, including the Sivers function, helicity worm-gear, transversity, pretzelosity, Boer-Mulders, and transversity worm-gear distributions. Our results provide a complete picture of the small-𝑥 asymptotic behavior for all leading-twist flavor-singlet quark TMDs. We also discuss the implications of our findings for phenomenological applications and outline potential avenues for further research, particularly in understanding nonlinear effects and extending beyond the double-logarithmic approximation and large-𝑁 𝑐 approximations.

Adamiak, Daniel [Thomas Jefferson National Acceler↗

DOE OSTI2025

Cosmology From CMB Lensing and Delensed EE Power Spectra Using 2019-2020 SPT-3G Polarization Data

From CMB polarization data alone we reconstruct the CMB lensing power spectrum, comparable in overall constraining power to previous temperature-based reconstructions, and an unlensed E -mode power spectrum, with clear detections of the third through tenth acoustic peaks. The observations, taken in 2019 and 2020 with the South Pole Telescope (SPT) and the SPT-3G camera, cover 1500 deg 2 at 95, 150, and 220 GHz with arcminute resolution and roughly 4.9 µ K-arcmin coadded noise in polarization. The power spectrum estimates, together with systematic parameter estimates and a joint covariance matrix, follow from a Bayesian analysis using the Marginal Unbiased Score Expansion (MUSE) method. The E -mode spectrum at ℓ > 2000 and lensing spectrum at L > 350 are the most precise to date. Assuming the ΛCDM model, and using only these SPT data and priors on τ and absolute calibration from Planck, we find H 0 = 66.81 ± 0.81 km/s/Mpc, comparable in precision to the Planck determination and in 5.4 σ tension with the most precise H 0 inference derived via the distance ladder. We also find S 8 ≡ σ 8 (Ω m /0.3) 0.5 = 0.850 ± 0.017, providing further independent evidence of a slight tension with low-redshift structure probes. The ΛCDM model provides a good simultaneous fit to the combined Planck, ACT, and SPT data, and thus passes a powerful test. Combining these CMB datasets with BAO observations, we explore extensions to the ΛCDM model. We find that the effective number of neutrino species, spatial curvature, and primordial helium fraction are consistent with standard model values, and that the 95% confidence upper limit on the neutrino mass sum is 0.075 eV, close to the minimum sum expected from observations of solar and atmospheric neutrino oscillations. The SPT data are consistent with the somewhat weak (< 3 σ ) preference for excess lensing power seen in Planck and ACT data relative to predictions of the ΛCDM model given the combined Planck, ACT, and BAO data sets. Finally, we also detect at greater than 3 σ the influence of non-linear evolution in the CMB lensing power spectrum and discuss it in the context of the S 8 tension. Forthcoming SPT-3G analyses will feature deeper and wider observations in temperature and polarization, providing even tighter constraints and more powerful tests of the ΛCDM model.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Event-Based Energy Impact Tracking and Forecasting with Limited Measurements for Rooftop Units

Packaged air conditioning units and heat pumps, also known as rooftop units (RTUs), are responsible for almost 133 billion kWh of electricity usage annually on site for space cooling U.S. commercial buildings. In addition, the use of heat pumps is a trend we expect to accelerate as buildings transition from fossil fuel-based heating to electricity as a key step for decarbonizing the U.S. commercial buildings sector. However, the operation conditions and energy use of RTUs and heat pumps are usually not well monitored as they are not commonly integrated with building automation systems and lack exposed sensing and control points. To fill this gap, this paper proposes a framework for tracking and forecasting energy impacts resulting from degradation of performance and improved performance for unit servicing using limited data. The proposed framework makes use of a constrained dataset, specifically measurements of the outdoor air temperature and the power demand of individual RTUs, to track and forecast changes in energy use associated with changes in performance over various temporal horizons ranging from days to weeks. Following the detection of an RTU fault, performance degradation, or performance improvement, the framework employs a prediction model to assess the cumulative energy impact. We demonstrate the effectiveness of the method with field-collected data for servicing and degradation examples and compare the predicting accuracy of Gradient Boosting Decision Tree (GBDT) Regression models to Support Vector Regression and Linear Regression models. The results show that GBDT achieved the best accuracy for time-series validation datasets for the servicing and degradation cases, and the prediction model was able to track the cumulative energy impacts of events. The proposed framework can inform building owners of the cumulative change in energy usage of RTUs associated with performance degradation, performance improvement, or a fault.

packaged air conditioners, packaged heat pumps, ro↗

DOE OSTI2025

Temporally-consistent koopman autoencoders for forecasting dynamical systems

Absence of sufficiently high-quality data often poses a key challenge in data-driven modeling of high-dimensional spatio-temporal dynamical systems. Koopman Autoencoders (KAEs) harness the expressivity of deep neural networks (DNNs), the dimension reduction capabilities of autoencoders, and the spectral properties of the Koopman operator to learn a reduced-order feature space with simpler, linear dynamics. However, the effectiveness of KAEs is hindered by limited and noisy training datasets, leading to poor generalizability. To address this, we introduce the Temporally-Consistent Koopman Autoencoder (tcKAE), designed to generate accurate long-term predictions even with limited and noisy training data. This is achieved through a consistency regularization term that enforces prediction coherence across different time steps, thus enhancing the robustness and generalizability of tcKAE over existing models. We provide analytical justification for this approach based on Koopman spectral theory and empirically demonstrate tcKAE’s superior performance over state-of-the-art KAE models across a variety of test cases, including simple pendulum oscillations, kinetic plasma, and fluid flow data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Similarity Metric for Data Optimization and Efficient Training of Reactive Machine Learning Force Fields for Hydrocarbon Radiolysis

Radiolysis is a common approach to sterilize polymers, chemically modify them for upcycling, and accelerate their decomposition for recycling purposes. Reactive molecular dynamics (MD) simulations provide a powerful tool to generate atomic-level trajectories of the reactive processes and quantify radiolytic chemical degradation pathways. For this, machine learning (ML) surrogate models for reactive force fields with quantum mechanical accuracy are now widely used, which require ML training data sets that can provide information on atomic environments for target chemical systems. However, radiolysis chemistry can be highly complex and diverse, which poses significant challenges for generating training data to parametrize ML models. In this regard, we developed a method for optimizing the training data set using a cosine similarity metric to help guide training set selection for radiolysis of polyethylene, a model hydrocarbon polymer, as well as to enhance the transferability of our reactive ML force field (MLFF) to a variety of molecular and polymeric systems. Our approach performs atom-by-atom comparisons between local atomic environments to pinpoint important data points associated with rare and localized events, such as radiolysis damage within structures. We apply this approach to train the Chebyshev Interaction Model for Efficient Simulation (ChIMES) MLFF model, which expresses the atomic interaction potentials in terms of linear combinations of many-body Chebyshev polynomials. We first show that our method can reduce our training set size by ∼70% while improving overall accuracy compared to more standard MD model fitting approaches. We then validate our optimum model against diverse hydrocarbon simulation data, including simple alkanes and systems with unsaturated carbon bonds, over a wide range of thermodynamic conditions. Finally, we use our ChIMES model to perform MD simulations of radiolytic damage with large-scale systems that help avoid system size effects. Overall, our approach yields an MD force field that retains most of the accuracy of the underlying quantum method while yielding many orders of improvement in computational efficiency. In conclusion, our efforts will have impact on future hydrocarbon polymer radiolysis studies, where the chemical details of the polymer–radiation interactions can have a strong effect on the resulting products observed in experiments.

Hydrocarbons↗

DOE OSTI2026

Beam-beam backgrounds for the Cool Copper Collider

In this paper, we present a comprehensive characterization of beam-beam backgrounds for the Cool Copper Collider (C 3 ), a proposed linear e + e - collider designed for precision Higgs studies at center-of-mass energies of 250 and 550 GeV. Using a simulation pipeline based on the Key4hep framework, we evaluate incoherent pair production and hadron photoproduction backgrounds through the SiD detector for baseline, power-efficiency, and high-luminosity C 3 operating scenarios. The occupancy induced by the beam-beam background is evaluated for each scenario, validating the compatibility of the existing SiD detector design with operations at C 3 without substantial modifications. Furthermore, at the same time, the modular simulation framework and analysis methodology presented in this paper offer a versatile toolkit for background studies in future collider proposals, contributing to a common platform for different machine designs.

Analysis and statistical methods↗