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DOE OSTI2025

Baseband Digital Network Analyzer Upgrade for LLRF Controllers

Digital Network Analyzers (DNA) have been implemented in many Low-Level Radio Frequency (LLRF) systems, notably NSLS-II and CERN, to help tune feedback loops. DNA characterizes feedback loops by measuring the frequency-dependent magnitude and phase transfer functions. It enables the measurement of open loop gains, gain/phase margins, and loop delays to help fine-tune feedback loops. An FPGA-based DNA has been developed and integrated into the current Relativistic Heavy Ion Collider (RHIC) LLRF infrastructure. Its performance has been tested with an implementation of one-turn delay feedback (OTFB) on the bench to maximize gain and stability. The DNA has been used to characterize a RHIC 28 MHz cavity in a RHIC Accelerator Physics Experiment (APEX) to test transient beam loading compensation strategies.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

CRCNS21 Computational Models of Multisensory Integration by Upper Limb in Humanoids and Amputees

This international collaborative research project between Johns Hopkins University (JHU) and the Technical University of Munich (TUM) investigated how the human brain processes and integrates multiple types of sensory information, such as touch and force, with the goal of improving prosthetic limbs for amputees and advancing sensory capabilities in humanoid robots. The research advanced our understanding of how the brain responds to sensory feedback in upper-limb amputees. Through experiments in which amputees received electrical stimulation while performing phantom hand movements, we demonstrated that sensory feedback activates the cortical sensorimotor and multisensory regions, and that these regions communicate dynamically during stimulation. Experiments with intact-limb participants explored the integration of visual, haptic, and force feedback, as well as in virtual reality motor training, further showing how the brain processes multimodal sensory information. In addition, this research inspired work on examining the reliability of where amputees perceive sensations over time, which contributed to a successful doctoral fellowship for continued investigation. Our collaborators at TUM improved multimodal sensor technology combining tactile and thermal feedback for humanoid robots, demonstrating the feasibility of integrating multiple sensor types into a unified system for detecting and responding to environmental stimuli. The experimental methods and analysis techniques developed across both teams, including functional network analysis and multimodal sensor integration, provide a foundation for future research in prosthetics and robotics. This research benefits the public by generating knowledge about how amputees process restored sensory information. Advances in humanoid sensing contribute to safer human-robot interaction. The project also fostered international collaboration and cross-disciplinary training: one TUM doctoral student spent a summer at JHU working on multimodal sensor integration, while two JHU students traveled to TUM to host workshops on neuromorphic sensory encoding and sensory integration.

42 ENGINEERING↗

DOE OSTI2025

The AGORA High-resolution Galaxy Simulations Comparison Project. VIII. Disk Formation and Evolution of Simulated Milky Way Mass Galaxy Progenitors at 1 < z < 5

We investigate how differences in the stellar feedback produce disks with different morphologies in Milky Way–like progenitors over 1 ≤ z ≤ 5, using eight state-of-the-art cosmological hydrodynamics simulation codes in the AGORA project. In three of the participating codes, a distinct, rotation-dominated inner core emerges with a formation timescale of ≲300 Myr, largely driven by a major merger event, while two other codes exhibit similar signs of wet compaction—gaseous shrinkage into a compact starburst phase—at earlier epochs. The remaining three codes show only weak evidence of wet compaction. Consequently, we divide the simulated galaxies into two groups: those with strong compaction signatures and those with weaker ones. Galaxies in these two groups differ in size, stellar age gradients, and disk-to-total mass ratios. Specifically, codes with strong wet compaction build their outer disks in an inside-out fashion, leading to negative age gradients, whereas codes with weaker compaction feature flat or positive age gradients caused primarily by outward stellar migration. Although the stellar half-mass radii of these two groups diverge at z ∼ 3, the inclusion of dust extinction brings their sizes and shapes in mock observations closer to each other and to observed galaxies. We attribute the observed morphological differences primarily to variations in the stellar feedback implementations—such as delayed cooling timescales, and feedback strengths—that regulate both the onset and duration of compaction. Overall, our results suggest that disk assembly at high redshifts is highly sensitive to the details of the stellar feedback prescriptions in simulations.

Jung, Minyong [Seoul National Univ. (Korea, Republ↗

DOE OSTI2025

E3SM‐Arctic: Regionally Refined Coupled Model for Advanced Understanding of Arctic Systems Interactions

Earth system models are essential tools for climate projections, but coarse resolutions limit regional accuracy, especially in the Arctic. Regionally refined meshes (RRMs) enhance resolution in key areas while maintaining computational efficiency. This paper provides an overview of the United States (U.S.) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2.1 with an Arctic RRM, hereafter referred to as E3SMv2.1-Arctic, for the atmosphere (25 km), land (25 km), and ocean/ice (10 km) components. We evaluate the atmospheric component and its interactions with land, ocean, and cryosphere by comparing the RRM (E3SM2.1-Arctic) historical simulations (1950–2014) with the uniform low-resolution (LR) counterpart, reanalysis products, and observational data sets. The RRM generally reduces biases in the LR model, improving simulations of Arctic large-scale mean fields, such as precipitation, atmospheric circulation, clouds, atmospheric river frequency, and sea ice thickness. However, it introduces a seasonally dependent surface air temperature bias, reducing the LR cold bias in summer but enhancing the LR warm bias in winter, which contributes to the underestimated winter sea ice area and volume. Radiative feedback analysis shows similar climate feedback strengths in both model configurations, with the RRM exhibiting a more positive surface albedo feedback and contributing to a stronger surface warming than LR. These findings underscore the importance of high-resolution modeling for advancing our understanding of Arctic climate changes and their broader global impacts, although some persistent biases appear to be independent of model resolution at 10–100 km scales.

Energy Exascale Earth System Model (E3SM)↗

DOE OSTI2026

Reshaping the Quantum Arrow of Time

While the microscopic laws of physics are often symmetric under time reversal, most natural processes that we observe are not. The emergent asymmetry between typical and time-reversed processes is referred to as the arrow of time. In quantum physics, an arrow of time emerges when a sequence of measurements is performed on a system. We introduce quantum control tools that can yield dynamics more consistent with time flowing backward than forward. The control tools are based on the explicit construction of a Hamiltonian that can replicate the stochastic trajectories of a monitored quantum system. Such a Hamiltonian can reverse the effect of monitoring and, via a feedback process, generate trajectories consistent with a reversed arrow of time. It can also be used to simulate the backward-in-time dynamics of an open quantum system. Finally, we design a feedback-driven continuous measurement engine powered by the energy pumped into the system by the monitoring process. We show that the engine can operate under experimentally realizable conditions with feedback delay and finite-efficiency measurements.

Entropy production↗

DOE OSTI2026

Preliminary proof-of-concept of real-time divertor heat flux control from infrared cameras with nitrogen injection in the DIII-D tokamak

In future tokamak reactors like ITER and the Fusion Pilot Plant (FPP), real-time feedback control of heat flux to the plasma-facing components (PFC) will be critical for steady-state operation. This work presents the first experimental demonstration of real-time divertor heat flux estimation with infrared thermography and feedback control with impurity seeding on the DIII-D tokamak. The flexible infrastructure of the Plasma Control System (PCS) on DIII-D makes this new capability possible. The PCS software runs on a gateway computer system, and five real-time compute nodes. An array of low latency streaming digitizers from D-TACQ Solutions connects to these real-time computers to collect and process data, and send commands to actuators during plasma discharges. This system handles the signal IO from the tokamak and allows the PCS to utilize the diagnostic data necessary to perform control in real-time. Feedback control on heat flux was accomplished by feeding infrared camera data from the “Infrared TV” (IRTV) camera to a custom-developed User Datagram Protocol (UDP) server. This server transmits infrared data to a newly developed PCS algorithm that estimates the heat flux to PFC. Here, a proportional integral derivative (PID) controller minimizes the error between a heat flux reference and the real-time estimate by injecting nitrogen gas into the divertor.

Algorithm development↗

DOE OSTI2025

Coupled Climate Simulations With E3SM‐MMF

Simulations of the recent historical period from 1950 to 2014 are conducted with E3SM‐MMF, which uses an embedded 2D cloud resolving model that runs efficiently on GPUs in place of traditional parameterizations for cloud and turbulence. Analysis of the climate and variability reveal several aspects where E3SM‐MMF produces smaller biases compared to E3SMv2, including better agreement with the observed evolution of global mean surface temperature, although the representation of ENSO is too weak and fast. Three idealized abrupt CO 2 experiments were also conducted to assess climate sensitivity and feedbacks. These yield three estimates of effective climate sensitivity (4.38, 5.21, and 6.06 K), with a corresponding spread in the shortwave cloud feedbacks. These estimates are on the higher end of sensitivity estimates from CMIP ensembles, and the spread indicates substantial state‐dependent feedbacks. These results demonstrate how multiscale modeling framework (MMF) models can be used for climate relevant experiments and projections by leveraging modern GPU enabled computational platforms. The unique qualities of E3SM‐MMF shown in previous literature are largely still present, but various instances of reduced biases suggest that MMF models have utility in improving future projections.

E3SM↗

DOE OSTI2024

Wide range of possible trajectories of North Atlantic climate in a warming world

Decadal variability in the North Atlantic Ocean impacts regional and global climate, yet changes in internal decadal variability under anthropogenic radiative forcing remain largely unexplored. Here we use the Community Earth System Model 2 Large Ensemble under historical and the Shared Socioeconomic Pathway 3-7.0 future radiative forcing scenarios and show that the ensemble spread in northern North Atlantic sea surface temperature (SST) more than doubles during the mid-twenty-first century, highlighting an exceptionally wide range of possible climate states. Furthermore, there are strikingly distinct trajectories in these SSTs, arising from differences in the North Atlantic deep convection among ensemble members starting by 2030. We propose that these are stochastically triggered and subsequently amplified by positive feedbacks involving coupled ocean-atmosphere-sea ice interactions. Freshwater forcing associated with global warming seems necessary for activating these feedbacks, accentuating the impact of external forcing on internal variability. Further investigation on seven additional large ensembles affirms the robustness of our findings. By monitoring these mechanisms in real time and extending dynamical model predictions after positive feedbacks activate, we may achieve skillful long-lead North Atlantic decadal predictions that are effective for multiple decades.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Aerosol effective radiative forcing increases Earth’s energy imbalance in recent decades

Earth’s energy imbalance (EEI), a key driver of climate change, has risen markedly over the last two decades. Greenhouse gas forcing, aerosol forcing, and cloud feedback all contribute to this increase. However, the role of aerosol forcing, particularly effective radiative forcing through aerosol-cloud interactions (ERF ACI ), remains highly uncertain and closely intertwined with cloud feedback. Here, we estimate shortwave ERF ACI using satellite observations and show its importance as a contributor to the EEI increase between 2003 and 2023. ERF ACI exhibits a significant increasing trend of 0.33 Wm −2 /decade averaged over oceans between 60°S and 60°N. The increasing trend of ERF ACI stems from a global decline in cloud droplet number concentration driven by decreasing anthropogenic aerosol emissions. It is of similar magnitude as the combined instantaneous forcing trend from greenhouse gases and aerosol-radiation interactions. Our results may reduce the gap between the simulated and observed shortwave contribution to EEI trends while implying a weak shortwave cloud feedback. They also suggest a stronger aerosol forcing than the multi-model mean.

Yuan, Tianle [NASA Goddard Space Flight Center (GS↗

DOE OSTI2025

The AGORA High-Resolution Galaxy Simulations Comparison Project

Context. Satellite galaxies experience multiple physical processes when interacting with their host halos, often leading to the quenching of star formation. In the Local Group, satellite quenching has been shown to be highly efficient, affecting nearly all satellites except the most massive ones. While recent surveys study Milky Way-analogs to assess how representative our Local Group is, the dominant physical mechanisms behind satellite quenching in Milky Way-mass halos remain under debate. Aims. We analyze satellite quenching within the same Milky Way-mass halo simulated using various widely used astrophysical codes, each using different hydrodynamic methods and implementing different supernovae feedback recipes. The goal is to determine whether quenched fractions, quenching timescales, and the dominant quenching mechanisms are consistent across codes or if they show sensitivity to the specific hydrodynamic method and supernovae feedback physics employed. Methods. We used a subset of high-resolution cosmological zoom-in simulations of a Milky Way-mass halo from the multiple-code AGORA CosmoRun suite. Our analysis focuses on comparing satellite quenching across the different models and against observational data. We also analyzed the dominant mechanisms driving satellite quenching in each model. Results. We find that the quenched fraction is consistent with the latest SAGA Survey results within its 1σ host-to-host scatter across all the models. Regarding quenching timescales, all the models reproduce the trend observed in the ELVES survey, Local Group observations, and previous simulations: The less massive the satellite, the shorter its quenching timescale. All of our models converge on the dominant quenching mechanisms: Strangulation halts cold gas accretion in all satellites, while ram pressure stripping is the predominant mechanism for gas removal, and it is particularly effective in satellites with M * <10 8 M ⊙ . Nevertheless, the efficiency of the stripping mechanisms differs among the codes, showing a strong sensitivity to the different supernovae feedback implementations and/or hydrodynamic methods employed.

Local Group↗

DOE OSTI2026

Lab-Scale Cable-Driven Parallel Robot Prototype for Automated Prefabricated Component Manipulation

This paper presents the design and evaluation of a lab-scale cable-driven parallel robot (CDPR) developed as a flexible platform for automated installation of prefabricated components onto exterior building envelopes. Traditional manual installation methods for prefabricated components, which depend on scaffolding, cranes, cherry pickers, and verbal coordination, are not only labor-intensive and error-prone but also face significant limitations in dense urban environments due to site access constraints. To address these challenges, we developed a lab-scale CDPR platform capable of autonomously transporting building envelope components from a designated pickup zone to their target installation location, minimizing the need for human intervention. This study describes the system’s mechanical design, actuation architecture, real-time feedback system, and control strategy of the CDPR, and evaluates its performance in a laboratory environment. The robot’s actuation system uses torque control for end-effector manipulation. The robot’s real-time pose feedback comes from a construction-grade total station and a wireless inertial measurement unit (IMU), which together support precise end-effector control. Experimental results demonstrate the successful integration of the hardware, sensing, state estimation, and control subsystems. Preliminary tests showed that our lab-scale prototype can position the end effector with an error of less than 3 mm, which is a level of precision not previously achieved by existing CDPRs in construction applications. The key findings are twofold: (1) torque-only control is necessary but not sufficient for minimizing final pose error, and (2) incorporating real-time pose feedback can achieve the desired placement accuracy.

Liu, Yifang [Oak Ridge National Laboratory (ORNL),↗

DOE OSTI2026

Consistent inclusion of triple substitutions within a coupled cluster based static quantum embedding theory

We have previously proposed the MPCC static embedding framework for quantum chemistry that self-consistently couples a high-level coupled cluster (CC) treatment of the fragment (active region) with a lower level, Møller–Plesset perturbation treatment of the environment. Our initial implementation was limited to single and double (SD) substitutions, with CCSD for the fragment and first-order perturbative SD amplitudes for the environment. Here, we extend the MPCC embedding treatment to triple substitutions, which is essential for achieving chemical accuracy in energy differences. To this end, we employ a CCSDT solver for the fragment subsystem. For the environment subsystem, we construct a perturbative estimate of the triples amplitudes, explicitly accounting for feedback from all fragment amplitudes. The resulting approach is denoted MPCCSDT(pt). We further introduce a more complete formulation in which feedback from the environment amplitudes to the fragment amplitudes is also included. This scheme involves an iterative treatment of the environment triples amplitudes and is denoted MPCCSDT(it). In addition, we assess the accuracy of the previously proposed low-level method by introducing a modified low-level approach that incorporates a lowest-order treatment of selected long-range effects, including spin fluctuations and charge polarization. All resulting approaches may be viewed as post-CCSD(T) methods. We therefore consider test cases for which CCSD(T) exhibits substantial deviations from CCSDT. These include (i) single- and triple-bond stretching in F 2 and N 2 , (ii) bond dissociation energies of selected molecules from the W4-11 dataset, and (iii) total atomization energies of transition metal hydrides. Our results demonstrate that inclusion of triples amplitudes at the fragment level alone is insufficient; a perturbative treatment of the environment triples amplitudes is required. For many energy-difference applications, feedback from the environment triples amplitudes to the fragment amplitudes is not essential, but it does play a role in the very challenging CoH and FeH molecules. A very interesting finding from our study is that in some challenging cases, we need an improved (second-order) perturbative method for the SD amplitudes, going beyond the first-order one used in our earlier work. In conclusion, considering both cost and accuracy, the MP2CCSDT(pt) model is the most promising for future applications among the candidates considered here.

Shee, Avijit [University of California, Berkeley, ↗

DOE OSTI2025

Transient Modeling and Simulation of a Generic Stable Salt Reactor

A SAM system-level model of a generic stable salt reactor has been developed to investigate thermal-hydraulic behavior and safety performance under steady and transient conditions. The model integrates information generated from a reactor physics analysis using PROTEUS and PERSENT, and a computation fluid dynamics (CFD) analysis using STAR-CCM+. A loose, iterative coupling scheme between PROTEUS and SAM is implemented to calculate the equilibrium power and temperature distributions in the steady-state critical core condition. The converged steady-state model is then used in PERSENT to calculate the four reactivity feedback temperature coefficients (Doppler, fuel density, coolant density, and core radial expansion) and kinetic parameters that are needed in SAM to model the temperature feedback effects in transient simulations. Within the fully enclosed liquid fuel pins, natural convection is the dominant heat transfer mechanism. The STAR-CCM+ model of the fuel pin considers conjugate heat transfer from the liquid fuel salt to the pin cladding and external reactor coolant. The CFD results of the axial and radial temperature profiles are used to empirically determine an effective fuel salt thermal conductivity in the SAM fuel pin model so that the temperatures predicted by the SAM model match as closely as possible the CFD results. In the central region of the fuel pin, the effective thermal conductivity is as high as similar to 60 times the physical fuel salt thermal conductivity. The whole-plant SAM model is then used to simulate an unprotected station blackout transient. The results of this simulation showed that the large negative fuel axial expansion reactivity feedback reduces fission power to similar to 2.4% nominal power. The core is cooled by natural circulation, which removes heat in the core to the emergency heat removal system, and ultimately, to the ambient. However, peak fuel salt and cladding temperatures can potentially reach as high as 1500 K, albeit briefly, if the shutdown mechanism fails to operate.

stable salt reactor; transient simulations; system↗

DOE OSTI2025

Experimental demonstration of real-time electron temperature profile control in DIII-D

Future tokamak reactor operation will require the ability to maintain a given plasma scenario for extended periods of time. This will necessitate the capability to react to changes in the plasma state and return the plasma to the target scenario; the principal method to achieve this is through feedback control. Thus, it is necessary to develop and test feedback controllers for the plasma profiles that define a target scenario. In this work, a feedback controller for the electron temperature (Te) profile is tested experimentally in DIII-D. This experiment relied on the ability to ascertain the electron temperature profile in real time, which was achieved using an observer algorithm. The observer relies on both diagnostic data and a predictive model of the electron temperature profile evolution; this predictive model includes contributions from neural network surrogate models. Because of these dependencies, a number of capabilities needed to be added to the real-time PCS for DIII-D in order to support the Te profile control experiment. The neural network surrogates needed to be integrated into the PCS to be called in real time. An observer algorithm for the Te profile needed to be added and connected to the Thomson scattering system to allow access to the current state of the profile in real time. When tested, the observer was shown to produce Te profiles that are consistent with the shape of the Thomson scattering data while rejecting much of the noise in the diagnostic data. Finally, the controller itself was tested in real time. This experiment showed that the controller is capable of tracking the electron temperature target at locations across the spatial profile.

Morosohk, Shira [Oak Ridge Associated Universities↗

DOE OSTI2023

Investigating permafrost carbon dynamics in Alaska with artificial intelligence

Abstract Positive feedbacks between permafrost degradation and the release of soil carbon into the atmosphere impact land–atmosphere interactions, disrupt the global carbon cycle, and accelerate climate change. The widespread distribution of thawing permafrost is causing a cascade of geophysical and biochemical disturbances with global impacts. Currently, few earth system models account for permafrost carbon feedback (PCF) mechanisms. This research study integrates artificial intelligence (AI) tools and information derived from field-scale surveys across the tundra and boreal landscapes in Alaska. We identify and interpret the permafrost carbon cycling links and feedback sensitivities with GeoCryoAI, a hybridized multimodal deep learning (DL) architecture of stacked convolutionally layered, memory-encoded recurrent neural networks (NN). This framework integratesin-situmeasurements and flux tower observations for teacher forcing and model training. Preliminary experiments to quantify, validate, and forecast permafrost degradation and carbon efflux across Alaska demonstrate the fidelity of this data-driven architecture. More specifically, GeoCryoAI logs the ecological memory and effectively learns covariate dynamics while demonstrating an aptitude to simulate and forecast PCF dynamics—active layer thickness (ALT), carbon dioxide flux (CO 2 ), and methane flux (CH 4 )—with high precision and minimal loss (i.e. ALT RMSE : 1.327 cm [1969–2022]; CO 2 RMSE : 0.697µmolCO 2 m −2 s −1 [2003–2021]; CH 4 RMSE : 0.715 nmolCH 4 m −2 s −1 [2011–2022]). ALT variability is a sensitive harbinger of change, a unique signal characterizing the PCF, and our model is the first characterization of these dynamics across space and time.

Environmental Sciences & Ecology↗

DOE OSTI2024

Probabilistic inference of the structure and orbit of Milky Way satellites with semi-analytic modelling

Semi-analytic modelling furnishes an efficient avenue for characterizing dark matter haloes associated with satellites of Milky Way-like systems, as it easily accounts for uncertainties arising from halo-to-halo variance, the orbital disruption of satellites, baryonic feedback, and the stellar-to-halo mass (SMHM) relation. We use the SatGen semi-analytic satellite generator, which incorporates both empirical models of the galaxy–halo connection as well as analytic prescriptions for the orbital evolution of these satellites after accretion onto a host to create large samples of Milky Way-like systems and their satellites. By selecting satellites in the sample that match observed properties of a particular dwarf galaxy, we can infer arbitrary properties of the satellite galaxy within the cold dark matter paradigm. For the Milky Way’s classical dwarfs, we provide inferred values (with associated uncertainties) for the maximum circular velocity v max and the radius r max at which it occurs, varying over two choices of baryonic feedback model and two prescriptions for the SMHM relation. While simple empirical scaling relations can recover the median inferred value for v max and r max , this approach provides realistic correlated uncertainties and aids interpretability. We also demonstrate how the internal properties of a satellite’s dark matter profile correlate with its orbit, and we show that it is difficult to reproduce observations of the Fornax dwarf without strong baryonic feedback. Furthermore, the technique developed in this work is flexible in its application of observational data and can leverage arbitrary information about the satellite galaxies to make inferences about their dark matter haloes and population statistics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Backlighting extended gas halos around luminous red galaxies: Kinematic Sunyaev-Zel’dovich effect from DESI Y1 and ACT data

The gas density profile around galaxies, shaped by feedback and affecting the galaxy lensing signal, is imprinted on the cosmic microwave background (CMB) by the kinematic Sunyaev-Zel’dovich effect (kSZ). We precisely measure this effect (𝑆/𝑁 ≈ 10) via velocity stacking with 825,283 spectroscopically confirmed luminous red galaxies (LRG) from the Dark Energy Spectroscopic Instrument Year 1 (DESI Y1) survey, which overlap with the Atacama Cosmology Telescope (ACT) Data Release 6 temperature maps over ≥ 4,000 deg 2 . We explore the kSZ dependence with various galaxy parameters and find no significant trend with redshift but clear trends with stellar mass and absolute magnitude in 𝑔, 𝑟, and 𝑧 bands. Our analysis suggests that the gas extends beyond the dark matter halo (99.5% confidence level, i.e., probability to exceed (PTE)⁢ = 0.005). We find a tentative preference for hydrodynamical simulation models with stronger feedback that drives gas further out (Illustris 𝑧 = 0.5, PTE⁢ = 0.37) over weaker-feedback cases (IllustrisTNG 𝑧 = 0.8, PTE⁢ = 0.045), though with limited statistical significance. In all cases, a free multiplicative amplitude was fit to the simulated profiles, and further modeling work is required to firm up these conclusions. We find consistency between kSZ profiles around spectroscopic and photometric LRG, with comparable statistical power, thus increasing our confidence in the photometric analysis. Additionally, we present the first kSZ measurement around the DESI Y1 bright galaxy sample (BGS) and the emission-line galaxies (ELG) whose features match qualitative expectations. Finally, we forecast 𝑆/𝑁 ∼ 50 for future stacked kSZ measurements using data from the ACT, the DESI Y3, and the Rubin Observatory. Furthermore, these measurements will serve as an input for galaxy formation models and baryonic uncertainties in galaxy lensing.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Transverse emittance growth due to rf noise in crab cavities: Theory, measurements, cure, and high luminosity LHC estimates

The High-Luminosity LHC (HL-LHC) upgrade with planned operation from 2029 onward has a goal of achieving a tenfold increase in the integrated number of recorded collisions thanks to a doubling of the intensity per bunch ( 2.2 × 10 11 protons) and a reduction of β * (the β value in the two high luminosity detectors, namely ATLAS and CMS) to 15 cm. Such an increase in recorded collisions would significantly expedite new discoveries and exploration. Crab cavities are an important component of the HL-LHC upgrade and will contribute strongly to achieving an increase in the number of recorded collisions. However, noise injected through the crab cavity radio frequency (rf) system could cause significant transverse emittance growth and limit luminosity lifetime. We presented a theoretical formalism relating transverse emittance growth to rf noise in an earlier work. In this follow-up paper, we summarize measurements in the super-proton synchrotron (SPS) at CERN that validate the theory, we present estimates of the emittance growth rates using state-of-the-art rf and low-level rf (LLRF) technologies, and we set the rf noise specifications to achieve acceptable performance. A novel dedicated feedback system acting through the crab cavities to mitigate emittance growth will be required. In this work, we develop a theoretical formalism to evaluate the performance of such a feedback system in any collider, identify limiting components, present simulation results to validate these studies, and derive key design parameters for an HL-LHC implementation of such a feedback system. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗